ISSN 0288-4534

CODEN: KPPJAD

KONA

Powder andParticle Journal

No.39 (2022)

Hosokawa Powder Technology Foundation
available online-www.kona.or.jp

KONA Powder and Particle Journal No. 39 (2022)

About this Journal
KONA Powder and Particle Journal is a refereed scientificjournal that publishes articles in the field of powder andparticle science and technology annually since 1983. Thisjournal is distributed free of charge to the members of scientific communities and universities and research libraries
throughout the world by the Hosokawa Powder Technology
Foundation (www.kona.or.jp) established by Mr. Masuo
Hosokawa in 1991.
The Chinese character “ 粉 ” in the cover is pronounced as“KONA” in Japanese, and means "Powder", which was
hand-written by Mr. Eiichi Hosokawa, the founder of the
Hosokawa Micron Corporation (www.hosokawamicron.
co.jp/en/global.html).

About the Cover
Various types of particulate materials with controlled size,
morphology, component and additive have been prepared via
gas phase, liquid phase, and solid phase routes. These modified powder and particles have been applied as pharmaceutical drugs with different dosage forms ranging from tablets,
capsules, eye drops, to injection. In order to achieve the effective and safe drug delivery, colloidal drug carriers such as
liposomes, liquid emulsion, and polymeric nanoparticles
have great potential to deliver drugs mainly by oral, pulmonary and ocular routes. Particle design research for a varietyof pharmaceutical materials will contribute to the design ofpatient-friendly dosage forms to solve various issues related
to the unmet medical needs of patients. Review on this topic
is discussed on pp. 150–175.

www.kona.or.jp

Editorial Board
Editor-in-Chief
K. Okuyama(Hiroshima Univ., Japan)

Asian / Oceanian Editorial Board
S. Biggs(Univ. of Western Australia, Australia)
X.S. Cai(Univ. of Shanghai for Sci. & Tech., China)
T. Charinpanitkul(Chulalongkorn Univ., Thailand)
Y.F. Chen(Chinese Academy of Sciences, China)
H. Choi(Changwon National Univ., Korea)
S. Das(Indian Institute of Technology, India)
M. Fuji(Nagoya Institute of Technology, Japan)
E. Iritani(Nagoya Univ., Japan)
H. Kage(Kyushu Institute of Technology, Japan)
A. Kawasaki(Tohoku Univ., Japan)
D.J. Lee(National Taiwan Univ., Taiwan)
J.H. Li(Chinese Academy of Sciences, China)
H. Makino(CRIEPI, Japan)
S. Matsusaka(Kyoto Univ., Japan)
M. Naito(Osaka Univ., Japan)
Y. Otani(Kanazawa Univ., Japan)
Y. Sakka(NIMS, Japan)
Y. Shirakawa(Doshisha Univ., Japan)
H. Takeuchi(Gifu Pharmaceutical Univ., Japan)
W. Tanthapanichakoon (The Royal Society of Thailand, Thailand)
C.H. Wang(National Univ. of Singapore, Singapore)
S. Watano(Osaka Pref. Univ., Japan)
Secretariat
T. Yokoyama(Hosokawa Powder Tech. Foundation, Japan)
L. Cui(Hosokawa Micron Corp., Japan)
European / African Editorial Board
Chairman
G.M.H. Meesters(Delft Univ. of Technology, Netherlands)
F. Bourgeois
M.-O. Coppens
L. Gradon
A. Kwade
P. Milani
M.G. Rasteiro
J.M. Valverde
Secretariat
S. Sander
S. Wilk(Univ. of Toulouse, France)(Univ. College London, UK)(Warsaw Univ. of Technology, Poland)(TU Braunschweig, Germany)(Univ. of Milan, Italy)(Univ. of Coimbra, Portugal)(Univ. of Seville, Spain)(KONA Europe e.V., Germany)(KONA Europe e.V., Germany)

American Editorial Board
Chairman
B.M. Moudgil(Univ. of Florida., USA)
A.J. Hickey
A.D. Rosato
L.M. Tavares
R. Vehring
Q. Zhang
Secretariat
C.C. Huang(Univ. of North Carolina, USA)
(New Jersey Institute of Technology, USA)(UFRJ, Brazil)(Univ. of Alberta, Canada)(Univ. of Manitoba, Canada)(Hosokawa Micron Intl. Inc., USA)

■ Publication Office

Hosokawa Powder Technology Foundation (www.kona.or.jp)(in the headquarters building of Hosokawa Micron Corporation)
1-9, Shodaitajika, Hirakata-shi, Osaka 573-1132, Japan
E-mail: contact_zainq@hmc.hosokawa.com■ Printing Office: Nakanishi Printing Co., Ltd., Japan

Headquarters of Hosokawa Micron Corporation■ Publication Date: 10 January 2022

KONA Powder and Particle Journal No. 39 (2022) Contents<Editorial>
1

Editor's Preface<Review Papers>
3

Progress in Multidimensional Particle
Characterization

Uwe Frank, Maximillian J. Uttinger,
Simon E. Wawra, Christian Lübbertand Wolfgang Peukert
29

The Sevilla Powder Tester: A Tool for
Measuring the Flow Properties of Cohesive
Powders at High Temperatures

Rahma Gannoun, José Manuel Pérez Ebrí,
Alberto T. Pérez and José Manuel Valverde
45

Numerical Modelling of Formation of Highly
Ordered Structured Micro- andNanoparticles – A Review

Jakub M. Gac
62

Review and Further Validation of a Practical
Single-Particle Breakage Model

Luís Marcelo TavaresiKONA Powder and Particle Journal No. 39 (2022) 

84

Advances in the Rheological Characterizationof Slurries of Elongated Particles

Saif Shaikh, Scott Strednak and Jason E. Butler
100 A Review of Distribution and Segregation
Mechanisms of Dockage and Foreign
Materials in On-Farm Grain Silos forCentral Spout Loading

Fuji Jian
110

Synthesis of Noble Metals and Their Alloy
Nanoparticles by Laser-Induced Nucleation
in a Highly Intense Laser Field

Takahiro Nakamura, Yuki Yamazaki andShunichi Sato
119 Influence of Anions and Cations on theFormation of Iron Oxide Nanoparticles in
Aqueous Media

Hidekazu Tanakaii

Contents

KONA Powder and Particle Journal No. 39 (2022) Contents

130 High Performance Nickel Based Electrodes inState-of-the-Art Lithium-Ion Batteries:
Morphological Perspectives

Agus Purwanto, Shofirul Sholikhatun Nisa,
Ike Puji Lestari, Muhammad Nur Ikhsanudin,
Cornelius Satria Yudha and Hendri Widiyandari
150 Contribution of Particle Design Research to
the Development of Patient-Centric Dosage
Forms

Hirofumi Takeuchi
176

The Development of Thin-Film Freezing and
Its Application to Improve Delivery of
Biologics as Dry Powder Aerosols

Stephanie Hufnagel, Sawittree Sahakijpijarn,
Chaeho Moon, Zhengrong Cuiand Robert O. Williams III<Original Research Papers>
193

Grain-Size Effects on Mechanical Behavior
and Failure of Dense Cohesive GranularMaterials

Payam Poorsolhjouy and Anil Misraiii

KONA Powder and Particle Journal No. 39 (2022) 

208 Verification of Polyhedral DEM with
Laboratory Grinding Mill Experiments

Alberto M. Puga, Nicolin Govenderand Raj K. Rajamani
219 Smart Mechanical Powder Processing for
Producing Carbon Nanotube Reinforced
Aluminum Matrix Composites

Behzad Sadeghi, Genlian Fan, Zhanqiu Tan,
Zhiqiang Li, Akira Kondo and Makio Naito
230 Correlating Granule Surface Structure
Morphology and Process Conditions in
Fluidized Bed Layering Spray Granulation

Maike Orth, Paul Kieckhefen, Swantje Pietschand Stefan Heinrich
240

Carbonation Kinetics of Fine CaO Particles
in a Sound-Assisted Fluidized Bed for
Thermochemical Energy Storage

Federica Raganati and Paola Ammendolaiv

Contents

KONA Powder and Particle Journal No. 39 (2022) Contents

251 Biodegradable PLGA Microsphere Formation
Mechanisms in Electrosprayed Liquid
Droplets

Moe Tanaka, Ayaka Ochi, Aiko Sasai,
Hiroyuki Tsujimoto, Hitomi Kobara,
Hiromitsu Yamamoto and Akihiro Wakisaka
262

Continuous Synthesis of Precision Gold
Nanoparticles Using a Flow Reactor

Jiaqi Dong, Jonathan Lau, Spyros A. Svoronosand Brij M. Moudgil<Addition/Correction>
270 Author Correction: Analysis of Industry-Related Flows
by Optical Coherence Tomography—A Review
Antti I. Koponen and Sanna Haavisto<Information Articles>
271

Book Review

275

The 8th APT (Asian Particle Technology Symposium) 2021 Held in Osaka

276

The KONA Award 2020 (Awardee: Prof. Dr. Brij M. Moudgil)

277 General Information

Selected research achievements for the KONA Award 2020: Interfacial engineering of particulate
system for enhanced performance. (p. 276)v

KONA Powder and Particle Journal No. 39 (2022) /https://doi.org/10.14356/kona.2022020

Editorial

Reviewer Appreciation
Kikuo Okuyama, Editor-in-Chief
Professor Emeritus, Hiroshima University, Japan

I would like to express my sincere gratitude to the reviewers for their hard work for the KONA Powder and Particle
Journal. Thanks to the generous contributions of the volunteer reviewers as well as the interest of researchers in ourjournal, the number of submission to this journal is increasing after the registration on the major international journal
platforms and its level is further improving. Thanks to their strong support and effort, I am pleased to inform that2020 Impact Factor (JCR) of the KONA Powder and Particle Journal is increased to 2.897, with the CiteScore 2020of 5.7. Because of the limited space of this annual journal, the number of papers published here is regrettably rather
restricted. Therefore, only the papers of good quality will be selected for the journal and further improved and refinedby the reviewing process. Moreover, we have created a channel on J-STAGE Data to enable authors to deposit, shareand link to the data within their papers which will be or were published in this journal. J-STAGE Data which is thedata repository provided by the Japan Science and Technology Agency (JST) enables KONA authors to contribute to
the promotion of Open Science with the reviewers and editors.
The editorial team of the KONA Journal would like to take this opportunity to gratefully acknowledge the reviewers
here and deeply appreciate their valuable time and professional contributions to the KONA Journal. We apologize to
any reviewers who may have been inadvertently omitted from this list. We are sincerely grateful to all who have beenof any assistance to the publication of this journal.

COPPENS, Marc-Olivier

MEESTERS, Gabriel

SHIRAKAWA, Yoshiyuki

HICKEY, Anthony

MOUDGIL, BrijTAVARES, Luis Marcelo

ICHIKAWA, Hideki

OZEKI, Tetsuya

YOKOYAMA, Toyokazu

ISKANDAR, Ferry

PURI, Virendra

ZHANG, Qiang

KAWASAKI, Akira

RAJAMANI, Raj

KWADE, Arno

RASTEIRO, Maria da Graça

October 2021

vi

Copyright © 2022 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

KONA Powder and Particle Journal No. 39 (2022) 1–2/https://doi.org/10.14356/kona.2022021

Editorial

Editor’s Preface
Wiwut Tanthapanichakoon
Asian / Oceanian Editorial Board
Fellow, Science Academy, the Royal Society of Thailand

It is my great honor and privilege to be invited by the Editor-in-Chief to write an Editor’s Preface for the KONA
Powder and Particle Journal No. 39. As mentioned by Prof. Brij M. Moudgil, the recent issues continue the traditionof presenting high quality review articles and original research papers. KONA is also reaching out to an everexpanding cadre of researchers as illustrated by the diversity of discipline represented by the authors of the articles,
thereby continuing to serve academic and industrial researchers from physical sciences to engineering and beyond.
As an international researcher who serendipitously entered this field and subsequently played a pivotal role as asort of bridge between Thailand and Japan, I was greatly honored with an Imperial Decoration ‘the Order of the
Rising Sun, Gold Rays with Neck Ribbon’ in Autumn 2016. Started over a half century ago, my relationship and involvement in powder/particle science and technology (or PST) encompass the establishment of the Thai Powder
Technology Center with a strong support from Japan (Association of Powder Process Industry and Engineering;Society of Powder Technology) in 1992, followed by Center of Excellence in Particle Technology, both in Facultyof Engineering, Chulalongkorn University (CU) and the establishment of Thailand’s NANOTEC (National
Nanotechnology Center) in 2003 affiliated with National Science and Technology Development Agency. In retrospect, my serendipitous first brush with PST happened when I was an RA/PhD student in Prof. David M.
Himmelblau’s Lab, University of Texas at Austin from 1973–1978, and a Dr. Chikao Kanaoka, Kanazawa University (KZU), Japan, came to his Lab for 2 years as visiting scientist to carry out experimental research in atmospheric aerosol engineering. After graduation in late 1978, I immediately joined the Chemical Engineering Dept. of
Chulalongkorn University in Bangkok and was persuaded by Dr. Kanaoka to apply for a short-term JSPS (Japan
Society for the Promotion of Science) Fellowship to carry out research collaboration with him in Prof. Hitoshi Emi’sLab, KZU, in 1980. Starting essentially from scratch, in only 3 months I managed to develop, code, validate andsimulate an innovative computer model for the stochastic convective diffusional deposition and dendritic growth ofsubmicron aerosol particles on a single fiber using the Monte-Carlo method. It was deemed the first practical computer model of its kind as the random movement of submicron particles was governed by Brownian motion and theLangevin equation that was known to take a large amount of CPU time even on a supercomputer to simulatestraight-forwardly without applying practical insight of Brownian diffusion to transform and simplify the equation.
As widely recognized globally, especially in the developed countries, powder/particle science and technology inThailand has also played key roles in her industries and society, including environmental protection and human life
well-being. For example, researchers of NANOTEC and their collaborators are active in developing and applying
nanoparticle technology, including nanoencapsulation and nanosensors, to drug delivery and medical diagnosis(screening and monitoring) of diabetes, cervical cancer and breast cancer. Recently first-principle models and computer simulation of complex powder processing equipment have taken root in leading Thai industrial plants, including SCG Chemicals (SCGCh) where I am a full-time technology advisor, thanks to the availability of advanced

Copyright © 2022 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

1

software on CFD (Computational Fluid Dynamics) and DEM (Discrete Element Method) in tandem with highperformance computers as well as cloud computing.
Incidentally, I recently had an opportunity to fully participate over five weeks in an Autonomous Systems AI
Architect Training Workshop offered by SCGCh’s collaborator Microsoft. Based upon AI (more specifically, deep
reinforced learning of AI machine learning coupled with availability of plant big data), a well-designed autonomous
system should enable real-time optimization and control (RTOC) of large-scale chemical process plants, including
powder/particle ones, in the foreseeable future. Currently, the insurmountable limitations of using reliable
first-principle modeling of machinery and process equipment to simulate a large-scale petrochemical plant (which
inevitably requires a huge amount of CPU time, thereby causing significant real time delay) in conjunction withhuge collections of historical plant operational datasets (which generally suffer from lacking of diversity of
wide-ranging operating conditions and reflect mostly steady-state non-dynamic conditions) have rendered the current implementation of plant-wide RTOC technically infeasible. However, a practical solution would be to develop
and validate the necessary dynamic first-principle models of the whole process plant with the aid of decade-longhistorical plant data that include process disturbances and interruptions; then simulate the validated dynamic plantmodel to generate detailed dynamic responses to millions of different operational scenarios, including process disturbances and parametric uncertainty. Next an appropriately designed autonomous AI system is employed off-line
to train itself using the generated big data and come up with reasonably reliable correlations between process inputs/parameters and the corresponding state variables/outputs. The derived correlations would next be used in placeof the dynamic first-principle plant model to efficiently carry out timely plant-wide RTOC. The beauty of the AI
methodology is that, even after the actual implementation of the RTOC, the autonomous system can continue to automatically learn and refine the existing correlations by making good use of the newly observed plant data. Thougha dynamic powder processing system/plant is generally more complicated than a typical chemical plant, I believethat a similar, or perhaps some more innovative, AI methodology would be applicable to the implementation of
RTOC of powder processing plants in the not too distant future. Last but not least, I look forward to the advent ofarticles related to AI and its applications to powder/particle science and technology in future issues of KONA
Powder and Particle Journal.

Wiwut Tanthapanichakoon
Asian / Oceanian Editorial Board
June 13, 2021

2

KONA Powder and Particle Journal No. 39 (2022) 3–28/https://doi.org/10.14356/kona.2022005

Review Paper

Progress in Multidimensional Particle Characterization †Uwe Frank 1, Maximillian J. Uttinger 1, Simon E. Wawra 1, Christian Lübbert 1,2
and Wolfgang Peukert 1,2*
1 Institute of Particle Technology (LFG), Friedrich Alexander Universität Erlangen-Nürnberg, Germany

2 Interdisciplinary Center for Functional Particle Systems, Friedrich Alexander Universität Erlangen-Nürnberg, Germany

Abstract
The properties of particle ensembles are defined by a complex multidimensional parameter space, namely particle
size, shape, surface, structure, composition and their distributions. Macroscopic product properties are a direct
result of these disperse particle properties. Therefore, the comprehensive multidimensional characterizationof particle ensembles is a key task in any product design. However, the determination of complex property
distributions is major challenge. We provide a broad overview of the current tools for multidimensional particle
characterization. First, the mathematical handling of multidimensional (nD) property distribution is outlined asa necessary framework for the correct handling of nD particle size distributions (PSDs). Then, well-establishedtechniques as well as recent developments with the potential to extract nD property distributions are reviewed. Ex­
situ imaging techniques like electron tomography or Raman spectroscopy with AFM co-localization, for instance,
provide a resolution on the level of single particles but are limited in terms of sample statistics. A particular focus
lies therefore on methods in the gas and the liquid phase, which provide multidimensional particle properties either
directly or by a combination of one-dimensional techniques.
Keywords: particle characterization, multidimensional measurement, nanoparticles, particle technology, particle
properties, particle property distribution

1. Introduction
Modern micro- and nanoparticle systems are key toadvancements in various applications including additive
manufacturing (Ngo et al., 2018; Ligon et al., 2017),
printable electronics (Kim D. and Moon, 2005), solar cells(Kim S.S. et al., 2008), fuel cells (Chan K.Y. et al., 2004),
batteries (Wessells et al., 2012), medical applications(Murthy, 2007) and biomedical sensors (Polavarapu andLiz-Marzán, 2013). Functional particle systems are widely
applied in many different fields because of their wide rangeof tunable physical properties. This rich behavior is the
direct result of the five-dimensional parameter space thatis defined by particle size, shape, surface, structure, andcomposition. The relationship between particle properties
and the dispersity is known as property function and was
first coined by (Rumpf, 1967)
Property = f (dispersity)†*

Received 15 July 2020; Accepted 19 August 2020
J-STAGE Advance published online 6 March 2021
Corresponding author: Wolfgang Peukert;
Add: Cauerstraße 4, 91058 Erlangen, Germany
E-mail: wolfgang.peukert@fau.de
TEL: +49-9131-85-29400 FAX: +49-9131-85-29402(1)

where the dispersity includes particle size, shape, surface,structure in terms of inner porosity, crystalline or amorphous phases and composition as well as their respective
distributions. Examples for the manifold realizations ofmultidimensional (nD) particle systems are provided in Table 1 and are highlighted in Fig. 1. The particle size ranges
from about one nanometer for quantum dots up to several
tens of centimeters for mineral particles. With the adventof nanoparticle technology, also particle shape came into
focus. Prominent examples are plasmonic nanoparticles,
where the shape influences the number and the position of
the plasmonic resonance peaks (Yu R. et al., 2017). Below
particle sizes of a few microns, particle surfaces become
increasingly important. The ratio of van der Waals attraction between two spherical particles and particle weightscales with the inverse diameter squared, i.e. the dispersive
particle interactions are orders of magnitude larger thanthe particle weight. Moreover, surface functionalization bymolecules or small nanoparticles can be used to tailor particle-particle interactions and adhesion forces (Soto-Cantu
et al., 2012; Giesbers et al., 2002). Core-shell structures areused for controlled release in life sciences or to enhancechemical stability.
The internal structure is most important for porous
systems such as activated carbon, zeolites or metal-organic
frameworks (MOF) (Holst and Cooper, 2010; Wang T.C.

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

3

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28
Table 1 Application examples of micro- and nanoparticle systems
with multidimensional property distributions beyond size.

Disperse
property

Application example

Shape

Plasmonic metal NPs a, nanorods b, platelets a
2D materials, e.g. graphene c, BN d, MoS2 e
Semiconducting NPs, e.g. nanorods f, tetrapods g

Surface

Control of surface energy h, Hydrophiliclipophilic balance i
Roughness for controlled adhesion andpowder flow j
Surface chemistry for controlled reactivity kCharge for controlled colloidal stability l
Toner size-charge (see E-SPART analyzer) m
Core-shell microparticles, e.g. controlled
release in life sciences nCore-shell semiconducting nanoparticles, e.g.
CdSe@ZnS oStructure

Amorphous vs crystalline particles p
Polymorphic forms in pharmacy q
Controlled pore size, e.g. in MOFs r, zeolites sor pore size distributions, e.g. adsorbentssuch as activated carbon t, CO2-absorbers u
Magnetic properties v

Complexcompositions

Minerals w
Semiconducting NPs, e.g. CIS x, CZTS y
Electrode materials, e.g. hybrid NPs z, catalyst particles aaa (Yu R. et al., 2017) b (Olson et al., 2015) c (Novoselov, 2011; Damm C.
et al., 2015) d (Duan et al., 2016) e (Theerthagiri et al., 2017) f (Zhuang
et al., 2020) g (Mokari et al., 2004) h Platz (Navrotsky, 2003; Finnegan
et al., 2007) i (He et al., 2014; Maestro et al., 2012) j (Jallo et al., 2011;
Tanaka et al., 2008; Esayanur et al., 2005) k (Yan et al., 2018) l (Kim
K.M. et al., 2014; Zhong et al., 2012) m (Mazumder et al., 1991) n (ReyM. et al., 2020; Khan et al., 2015; Wang Y. et al., 2013) o (Zhang L. etal., 2011; Haubold et al., 2001; Gerdova and Haché, 2005) p (Dimitrov
et al., 1999) q (Chistyakov and Sergeev, 2020) r (Hu J. et al., 2010;
Brown J.W. et al., 2013) s (Roth et al., 2013) t (Yao and Lenhoff, 2004;
Mangun et al., 2001) u (Del Rosso et al., 2016) v (Li Q. et al., 2017) w(Mogyorósi et al., 2003; Waychunas and Zhang H., 2008) x (So et al.,2016) y (Kannan et al., 2016) z (Lee J.S. et al., 2014) aa (Kleijn S.E.F.
et al., 2012)

et al., 2015; Hu Z. and Srinivasan, 2001). Also, particles,
which are composed of several crystalline or amorphous
phases, belong to that group. Minerals but also advanced
semiconducting particles (e.g. CIS, CTZS, battery materials or active catalysts) often have a rich phase behavior(Hochella et al., 2008). Little is known if and how it
depends on size. At the lower nanoscale, even the phasebehavior of less intricate materials such as alumina (Sun J.
and Simon, 2007) or CdS is size-dependent (Neeleshwar et4Fig. 1 Exemplary nano- and microparticle systems sorted by theirunderlying properties, which are defined by the five parameters namely
size, shape, surface, structure and composition. Size: (1a) lead tin
quantum dots, (1b) silicon nanoparticles, (1c) spherical polybutylene
terephthalate polycarbonate blend particles. Shape: (2a) gold nanocubes
after a HAuCl4 solution was added, (2b) zinc oxide prisms, (2c) aggregated silicon nanoparticles in toluene. Surface: (3a) nanoparticle withcomplex surface, (3b) silver patches grown on borosilicate microsphere,(3c) functionalized ZnO nanorod. Structure: (4a) colloidal crystal, (4b)hematite mesocrystal, (4c) silver nanorod. Composition: (5a) Cu/Zn
catalyst precursor, (5b) Silicon Germanium hybrid nanoparticle, (5c)kesterite crystal. Reproduced with permission from (Frank U. et al.,2019) Copyright 2019, Wiley.

al., 2005; Eom et al., 2013).
In order to study these complex phenomena, various
nano- and microparticle systems have to be characterizedwith respect to structural (via the dispersity) and functional
properties. Examples depending on the five-dimensionalparameter space are highlighted in Table 2.
Characterization tools provide single mean or distributed
parameters like the volume-equivalent, the hydrodynamicor the sedimentation-equivalent diameter (Modena et al.,2019). With increasing complexity in terms of nD particle
parameters it becomes more and more difficult to interpretdirect measurement results. Different combinations ofdispersed particle properties can lead to the same value ofa measured quantity, e.g. the volume of a particle. Combining results from different measurement techniques or using
experimental setups, which are sensitive to nD properties
directly, are therefore required in order to gain more information on complex particle systems.
The objective of this review is to provide an overview ofpast and current developments concerning the multidimensional characterization of particles. In a few recent cases,

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28
Table 2 Multi-dimensional particle properties for technological andfunctional properties.

Technologicalproperties

Transport properties: size, density, shape a
Powder flow: surface, size, shape, structure b
Packing characteristics: size, shape,
structure c
Colloidal stability: size, shape, composition dFunctional
properties

Mechanical properties: size, structure,composition e
Optical properties: size, shape, structure,composition f
Electronic and magnetic properties: size,
shape, structure, composition, surface g
Chemical properties: surface, structure,composition h
Sensory properties, e.g. taste: size, composition, structure i
Thermodynamic properties, e.g. solubility,
melting, sintering: size, surface, composition ja (Hansen 2004; La Torre et al., 2007; Wawra et al., 2018) b (Schmidt

J. et al., 2014) c (Parteli and Pöschel, 2016) d (Chemseddine and Weller
H., 1993; Gudarzi, 2016) e (Herre P. et al., 2017) f (Yu R. et al., 2017;
Link S. et al., 1999; Motl et al., 2010) g (Zhang W. et al., 2003; Sharma
et al., 2010; Zhu M. et al., 2012) h (Domaschke et al., 2019) i (Fathi etal., 2013; Davidov-Pardo et al., 2015; Joye I.J. and McClements, 2014)
j (Letellier et al., 2007; Guisbiers, 2019; Castro and Gouvêa, 2016; Li
W. et al., 2016)

two-dimensional (2D) information was obtained from one
single experiment as will be highlighted in this review.
First, a thorough mathematical description of multidimensional particle ensembles will be provided. Comparabilityof measurement results from different techniques can beachieved by taking different weightings into account. The
derivation of one-dimensional (1D) distributions frommultidimensional distributions is always possible while
the reverse case, i.e. the derivation of multidimensional
distributions from 1D ones, is an ill-posed problem. Basedon this theoretical background, the focus of the review lies
on experimental procedures. Therefore, comprehensive
techniques based on microscopic imaging and characterization methods for gas phase and liquid phase analysis
are reviewed and critically discussed with respect to theirpotential for nD particle characterization.

2. Multidimensional particle size distributions
As the properties of nano- and micron-sized particles
are typically distributed, mathematical tools for property

distributions require a comprehensive description. Mostoften the size of particles is the key parameter, as many
properties of particulate products are influenced by theirsize distribution. Only for spherical particles, the size canbe described by using a single parameter, i.e. the diameter.
In the general case, particle size of an irregular particle isunderstood in terms of an equivalent size, such as the diameter of a sphere of equal volume, equal surface or equalhydrodynamic transport behavior. To date, disperse particle
systems are mostly characterized by one-dimensional (1D)
particle size distributions (PSDs), which were comprehensively described by Rumpf and Leschonski (Leschonski
K. et al., 1974a; 1974b). This concept has proven to bevery useful for rather simple particle systems but must
be expanded for the description of more complex particle
systems. One general difficulty is that different particle
parameter sets can lead to the same equivalent diameter,
e.g. different diameter and length combinations of a rodlike particle result in the same volume-equivalent diameter.
Therefore, a nD description of complex particle ensembles
is required. In general, nD PSDs are defined as (Frank U.
et al., 2019)
Amount of kind r in interval dx(2)interval size dx * total amount of kind r
(2) the nD PSD qr of the random vector x   n . The
withdistribution qr fulfils several requirements, it is non[21]negative, integrable and normalized. The index r is related
to the weighting of the PSD. Depending on the measurement technique, PSDs are differently weighted, basedon the underlying physical measurement principles, e.g.
counting (r = 0) or weighing, (r = 3). If not taken into
account, the weighting introduces comparability issues
between different measurement techniques (Modena et al.,2019). In the 1D scenario, it is very convenient to convert
differently weighted PSDs into each other, e.g. from kind k
to kind r (Leschonski K. et al., 1974a; 1974b)
q r  x 

qr  x 

x r  k qk  x
M r  k,k(3)x(3) the moment M r  k , k   max x r  k qk  x dx , which is
with
xmin
calculated by integration from the minimum xmin to the
maximum particle [22]size xmax. Of course, the situation ismore complicated in the nD case. Here, weighting functions need to be considered and the notation is slightly
adapted (Frank U. et al., 2019)q  x  κ  x
q r  x  k
(4)
M r,k
with
(4) the weighting function κ, which maps the random
vector x to a positive scalar. An intuitive example is thevolume of a regular, non-spherical particle (e.g. a rod or[23]
platelet), which is calculated from the particle geometry

5

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

parameters of length and diameter. The denominatoris 
defined as generalized moment M r,k   x nqk  x κ  x d n x .
A simple example for a 2D PSD alongside the extractionof 1D distributions of linked [24]variables is presented in thefollowing paragraphs.

2.1 Two-dimensional particle size distributions
The concept of 2D PSDs was recently illustrated forthe example of normal-distributed gold nanorods, which
are characterized by their length l and diameter d (FrankU. et al., 2019), and is recapped here for an intuitive wayof understanding multidimensional distributions. Similar
conclusions and relations hold true for the case of a 2D
log-normal distribution with two log-scaled axis.
To demonstrate the influence of different weightings, thesurface weighted q2 and volume weighted q3 distributions
were calculated from the number-weighted PSD q0 via Eq.
4. Here κ is replaced with functions for the surface andvolume1πd 2  πdl
2πV l, d   d 2l
(5)4Sd , l(5)(6)

A comparison of the obtained distributions can be found(6)
in Fig. 2. The function maximum is depicted with a staralongside an isoline, which illustrates the shape of the
distribution. A significant shift within the distributions isclearly visible and stresses the importance of the different
weightings. The stars indicate the modal values, which shift
from finer to coarser values for the length and diameter.

2.2 Calculation of one-dimensional data fromtwo-dimensional particle size distributions
With the 2D PSDs at hand, it is possible to calculate respective 1D distributions. This can be performed either via
marginalization or via the calculation of a linked variable.
Marginalization is the simpler case. Here one can calculate
the distributions for length and diameter simply by integration with respect to the complementary variable, e.g.
q0 l  

d max
d min

q0 l, d  dd

(7)

(7)
The more general case is to obtain r weighted 1D
distributions ρ of a linked variable y, like sedimentation
coefficient, aspect ratio or volume. This can be achieved
via conditional integration to obtain the cumulative distribution function (CDF) and subsequent derivationd
q x dnx{x n | f x  y} r  

(8)
dy

(8)the mapping function f  x. Applied to the 2D case ofwiththe aspect ratio ν of a rod-like particle, which is defined as[25]
the ratio of length to diameter ν = l/d, one obtainsdρ ν q0 l, d  dl ddldν  {l,d | d  ν}(9)d d max d ν
q0 l, d  dl dddν  d min lmin
This can be interpreted as calculation of a cumulative(9)
distributionof the aspect ratio with subsequent derivation,
which is illustrated in Fig. 3. The calculation of other
distributions can be performed analogously. This procedure enables the calculation of various quantities from 2D
nanoparticle property distributions.
Furthermore, 1D weight-dependent expected values(weight averages) Er can be computed from the 1D distributions via evaluation of the integralρ  y 

E r  y   yρ  y dy



 d

  y
qr  x d n x  dyx n |f  x  y


d
y



(10)

Applied to the example above, one can obtain the number(10)weighted mean aspect ratio via

E0 ν   νρ ν dν  ν(


Fig. 2 Comparison of differently weighted PSDs. Depicted are thenumber-weighted q0, surface-weighted q2 and volume-weighted q3 PSD
of gold nanorods. The stars indicate the maximal values of the distri1
max qi  . Reproduced withbution. The line is an isoline at the valueepermission from (Frank U. et al., 2019). Copyright 2019, Wiley.

Fig. 2 [31]6d d max d ν
q0 l, d  dl dd ) dνdν  d min lmin(11)

Equivalent calculations for other physical quantities, e.g.
(11)mean sedimentation coefficient, mean mobility diameteretc. are possible.
In summary, this section provided a detailed overview
of the current state-of-the-art for the mathematical handling of nD particle property distributions. However, their

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

3. Image analysis and microscopy
Manifold different analytical techniques exist to directly
image particles. The underlying principles used for image
characterization of samples vary across the length scalesof the material systems under investigation. Apart from themultidimensional characterization in terms of geometry,other complementary techniques based on spectral orelectronic characterization are used to retrieve correlationsof certain physical properties like the size and chemicalcomposition of particles. While it is possible to acquire detailed data on the single particle level, statistically reliablecharacterization of particle ensembles requires a significant
number of measured particles. In the case of 1D properties,
usually hundreds to thousands of particles are analyzed(Rice et al., 2013; Nacken T.J. et al., 2015; Verleysen et al.,2019). Estimations for sufficient particle numbers exist, seee.g. (Stieß, 1995). For instance, the determination of themedian particle size within +/– 3 % accuracy and a confidence interval of 95 % requires counting of close to 5000
particles, counting only 400 particles leads an accuracy of
only 10 %. For the determination of nD PSDs, the numberof particles that need to be investigated must be even higher
to avoid obtaining data of limited accuracy and reliability.
Many publications using image based characterization are
clearly below these numbers, even though software-based
image analysis can help reducing the temporal effort ofacquiring particle size and shape information (Verleysen etal., 2019; Frei and Kruis F.E., 2020).
Furthermore, microscopic techniques require carefulsample preparation from the gas or liquid phase to separate
individual particles on a substrate. Sampling can lead tovarious artefacts and systematic errors by size-selective
deposition, drying or agglomeration.

3.1 Light microscopy

Fig. 3 Schematic way to obtain a distribution of a linked variable. In(I) a 2D Gaussian PSD is depicted alongside lines indicating different
aspect ratios. In (II) the CDF is displayed, which is obtained by integration of the areas and which are defined by the lines of constant aspectratios in (I). Derivation of the CDF leads to the 1D distributions of the
aspect ratio in (III). Reproduced with permission from (Frank U. et al.,2019). Copyright 2019, Wiley.

experimental retrieval is a quite challenging task. Recent
progress in novel experimental approaches allows thedetermination of higher dimensional property functions. In
the following sections, we will present some of the most
relevant characterization methods and briefly recap theirunderlying physical principle and the respective results.

Imaging single particles (reasonably larger than the
wavelength) with light enables determining their 2D
projection on a substrate or directly in sufficiently diluteand thus optically transparent flowing systems. Particles
on a substrate typically lie in their stable position while
particles imaged in a flowing gas or liquid can be viewed
from different projections. Analysis on-the-fly is excellent
to image a very high numbers of particles to enhance thestatistical reliability of such measurements. Image analysis
of projected areas of particles in flow cells has been appliedin order to retrieve nD information on particle properties(Bujak and Bottlinger, 2008). More details on the conceptsof flow cells can be found in Section 5.1. Recently, a novel
omics-like method has been proposed collecting images of> 2,000,000 particles (of several 10 μm in size) per sample
in sediments, soils and dusts by a Sympatec GmbH QICPIC
particle size and shape analyzer. The morphological7

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

descriptors of each particle including equivalent diameter,
sphericity, aspect ratio and convexity were extracted as the“particle morphome”, an outcome of the large data set (SunY. et al., 2019).
Furthermore, light microscopy is often used as a priorstep to find a valid measurement position in spectroscopy
applications like Raman or fluorescence spectroscopy. The
combination of these techniques is rather common andtherefore not subject of this review.
Raman spectroscopy itself can be a valuable tool
for the analysis of the composition of a sample or theidentification of polymorphs of e.g. organic crystals inpharmaceutical applications. A current trend in energy
conversion and storage is towards particles consisting of
three (e.g. chalcogenide such as CuInS2), four (kesterites
such as Cu2InZnS4) or even multinary components. The
same holds true for complex catalyst or advanced battery
materials. A particular challenge during synthesis is theformation and identification of binary, ternary or quaternary by-products (see e.g. (Ahmad et al., 2017)). Statisticalcomposition mapping via Raman spectroscopy, supported
by atomic force microscopy (AFM) co-localization, is very
promising to study size-dependent composition in suchparticulate products (Nacken T. et al., 2015).
The limitations of using solely light microscopy interms of particle projections can be overcome via the useof digital holography (DH), which allows determining thethree-dimensional (3D) structure of micron-sized particles.
DH is based on interferometric imaging. As shown in
Fig. 4, interference patterns between diffracted light fromthe object and a reference wave are formed. SophisticatedFig. 4 Reconstructed spatial intensity image obtained from a gold
nanorod covered with fluorophore, obtained via super-resolution
microscopy. The oval shows the dimensions of the particle obtained
via AFM (see inset). Scale bars are 50 nm, the colour coded heat map
indicates the spatial fluorescence intensity distribution. Reproduced
from (Willets et al., 2017) with permission from American Chemical
Society, Copyright 2017.

8

image analysis allows to reconstruct intensity and phase
images, which can be transformed to yield 3D information(Tahara et al., 2018).
The resolution of light-based microscopes is physically
restricted by the Abbe diffraction limit, which hinders single particle investigations of nano-sized objects by conventional light microscopy (Siedentopf and Zsigmondy, 1902).
The advent of super-resolution microscopy enhanced themeasurement range for fluorescent labelled samples. The
combination of other techniques with super-resolution
microscopy is possible, although most applications arefocusing on biological samples (Hauser M. et al., 2017).
An example for the use of super-resolution microscopy
for particle characterization is the determination of theparticle geometry of anisotropic plasmonic particles. The
single emission of the fluorophores that are attached to theparticle can be utilized to determine the shape and size ofthe particle, as shown in Fig. 4. However, care needs tobe taken to avoid localization errors due to the interactionof the fluorophore with the substrate or due to a changing
dielectric environment (Willets et al., 2017).

3.2 Computed tomography
Using illumination sources with smaller wavelengths(electrons, X-rays, neutrons) considerably improves theresolution. The spatial resolution of X-ray computed tomography (X-ray CT) can reach below 100 nm (Maire andWithers, 2014) depending on the light source. Recently,
Leißner et al. reviewed the application of X-ray CT in
the field of particle technology (Leißner T. et al., 2020).
The technique relies on the spatially resolved detectionof the X-ray transmission of a sample. The 3D structureof an immobilized sample can be reconstructed from thedetection of projections from different directions. Individual X-ray attenuations are assigned as grey values tovolume elements. These depend on the material density andthe average atomic number, which allows to distinguishbetween different materials but may also exclude certain
materials or material combinations from thorough analysis
due to similarities or - in contrast - large differences in grey
values (Leißner et al., 2020; Ketcham and Carlson, 2001).
This limitation can be overcome with higher experimental
effort, by e.g. taking into account the energy- and material-specific attenuation of X-rays via hyperspectral X-ray
tomography (Egan et al., 2015). Stochastic modelling of
nD particle properties can further help to identify different
material classes from a X-ray CT experiment (Furat etal., 2019). Correlations between particle composition andcharacteristic particle properties like volume, sphericity or
the median grey value can be used to identify the 3D structure and material classes from an X-ray CT experiment.
Therefore, the authors calibrated their stochastic model via
scanning electron microscopy (SEM) – energy-dispersiveUwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

X-ray (EDX) measurements (see Section 3.4). Particle
characterization of e.g. crystals via X-ray tomography canbe improved by utilizing models of particle shape. The
identification of the crystal’s face normals offers thus interesting options for the robust evaluation of size- and shape
distributions (Kovačević et al., 2014).

3.3 Atomic force microscopy
Atomic force microscopy (AFM) is a surface sensitivetechnique based on tracking the oscillation and the position of a cantilever equipped with a nano-sized tip close
to the surface under investigation (Binnig et al., 1986).
Various measurement modes exist, which not only allow
the determination of the geometry of anisotropic particles
via evaluation of the sample topography but also provide
information on surface roughness or mechanical properties
and adhesion forces (Voigtländer, 2019).
The combination of AFM with other techniques denoted
as “Hybrid-AFM” provides access to additional information. Heating the sample at the measurement spot via an
infrared light beam of a defined wavelength and measuring
the heat-induced change in oscillation behavior of the cantilever enables measuring spectrally resolved infrared (IR)absorption. This way, correlating the chemical composition
with topographic information is possible (Fu W. and Zhang
W., 2017; Dazzi and Prater, 2017). Similar information canbe obtained via a combination of Raman spectroscopy andAFM (Fu W. and Zhang W., 2017). For the example of the2D material graphene, both techniques are complementary.
While the lateral geometry of graphene sheets is easily
accessible by AFM, the measured height of the sheets
may be influenced by adsorbates at the surface. Using
complementary Raman spectroscopy allows accurately
determining the number of sheets (up to 5 layers) and theirdefect states (Eigler et al., 2014; Nacken T. et al., 2015).
As the signals of both techniques are evaluated at the same
sample position by co-localization, true multidimensional
property distributions in terms of lateral sheet size andnumber of graphene sheets (thickness) can be acquired.
This technique thus enables process optimization of the
production of 2D materials (Halbig et al., 2016)

too small for a reliable statistical analysis. In other words,
information on 2D distributions have to be taken with greatcare due to the underlying scatter of data.
The detection of secondary or backscattered electrons
provides information on topography and composition. As
for other microscopy-based techniques, the combination ofimaging techniques with additional characterization methods can further enlarge the multidimensional dataset. SEMbased mineral liberation analysis can be used to determine
the projected 2D area of a mineral via SEM, while complementary EDX measurements allow the characterization of
the composition at the measurement position (Fandrich etal., 2007). From the overlay of 2D EDX and SEM images,
equivalent circle diameters of particles can be calculated
together with their densities from the individual specificmineral densities and EDX based area fractions. As a result
2D size and density distribution can be obtained, which allows analyzing e.g. separation processes in detail (Schachet al., 2019).
Furthermore, mechanical particle properties can be
determined by mechanical testing directly in the SEM bynano-compression. The set-up described in (Romeis S. etal., 2012) allows to test several hundred particles for statistically reliable analysis (see Fig. 5 I). Elastic and inelastic
deformation of carefully deposited individual particles
allows to determine distributions of Young’s modulus,
yield stress, hardness, energy absorption or strain at theonset of the crack formation. All these quantities can be

3.4 Electron microscopy
Scanning electron microscopy (SEM) and transmission
electron microscopy (TEM) rely on the interaction ofprobing electrons with the sample. Typically, topographic
or transmission images are used to determine the size andgeometrical anisotropy of individual particles. Characterizing a significantly large number of particles allows obtaining the 2D length and diameter distributions of particles,
see e.g. (Murphy et al., 2017; Elazzouzi-Hafraoui et al.,2008). However, the number of counted particles is often

Fig. 5 (I) Nano-indentation of particles by a flat punch in an SEM, (II)Au particles (1 μm) after defined compression, the red lines indicate theparticle shapes modelled by FEM. (I) adapted from (Paul J. et al., 2015b)with permission from Elsevier, Copyright 2015, (II) reprinted from(Paul J. et al., 2015a) with permission from Elsevier, Copyright 2015.

9

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

investigated depending on size. Additionally, the influenceof further size-dependent properties such as the brittle-ductile transition of glass particles, different compositions orinternal structures can be studied (Paul J. et al., 2015b).
Furthermore, quantitative shape analysis is possible as
highlighted in Fig. 5 II, which shows gold particles of
1 μm in diameter for various states of compression and particle shapes obtained from finite-element-method (FEM)
simulation.
TEM uses higher energetic electrons than SEM enabling
the spatial material transmission (Fultz and Howe, 2008)
and provides thus access to the local particle structure. The
2D characterization of particles can be extended to three
dimensions by applying 3D tomography (Miao et al., 2016;
Song H. et al., 2019). This method relies on tilt series of
TEM images obtained after careful sample preparation(Przybilla T. et al., 2018) as shown in Fig. 6 I or on TEM
images from freely rotating particles in a graphene based
liquid cell (Park J. et al., 2015). The obtained images areused to reconstruct the 3D morphology including the inner
structure (Park J. et al., 2015), the inner porosity (Distaso

M. et al., 2017) or the exact position of any primary particle in self-assembled supraparticles (Wang J. et al., 2018)as shown in Fig. 6 II. Therefore, this technique enables
obtaining vast information on the single particle level. Various other measurement techniques such as energy-filtered
TEM imaging, high resolution TEM imaging or diffraction
based modes, which allow chemical or structural analysis,
are available, but are beyond the scope of this review (Fultz
and Howe, 2008).

4. Gas phase measurements
In the following section, basic principles of multidimensional particle characterization in aerosols are presented.
Moreover, recent results for the determination of full 2D
mass-mobility distributions and additional 1D distributions
extracted from this data set are discussed.
An excellent possibility to analyze multidimensional
particle properties in a gaseous environment is the couplingof different measurement devices like the differential mobility analyzer (DMA) with a subsequent measurement device. Examples are the combination of a DMA with a low
pressure impactor to obtain radius and mass simultaneously(Schleicher et al., 1995), the simultaneous measurement of
mass, surface and mobility diameter of silver agglomerates
via coupling of DMA, inductively coupled plasma atomic
emission spectrometry (ICP-AES), epiphaniometer (EPI)
and condensation particle counter (CPC) (Weber A.P. etal., 1991).

4.1 DMA and low-pressure impactor

Fig. 6 (I) Flow chart of preparative work required for a 3D TEM tomography based reconstruction of the particle morphology. Reproducedwith permission from (Przybilla T. et al., 2018) Copyright 2019, Wiley.
(II) (a–c): Bright field STEM images of a colloidal crystals. (d–e:) Reconstructed surface and inner structure. (f–h) TEM mimicking imagesof the colloidal cluster. (i–j) external and internal cross-sectional views.
Reproduced from (Wang J. et al., 2018) under the terms of the CC-BY
4.0 license. Copyright: (2018) The Authors, published by Springer
Nature.

10

One of the earlier works on the retrieval of 2D property
distributions from aerosol measurements was carriedout by Schleicher et al. The simultaneous determinationof size and density for submicron aerosol particles wasdemonstrated for metal nanoparticles (Pd, Ag, Co), carbon
particles, oil droplets and oil burner exhaust (Schleicher etal., 1995).
The measurement itself is a two-step process. First a particle fraction with a certain electrical mobility is selected ina DMA, afterwards a low-pressure impactor classifies theparticles according to inertia. The combination of those two
devices allows to determine the particle density and mobility diameter of single particles. Prior to the DMA, the particle surface charge needs to be brought to charge equilibrium
via a 63Ni β− radioactive source. The applied electricalfield in the DMA leads to the separation of a mobilityselected particle fraction, which enters the low-pressure
impactor. The particle properties in the gas stream can be
estimated by a critical Stokes number. After calibration of
the two devices, the density for a previously mobilityselected particle regime is detected. It is possible to gainUwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

even more information by using a further classifying stepwith a subsequent scanning measurement device for particle counting.

4.2 Tandem differential mobility analyzer
In tandem DMA systems, two DMAs are used in series,
whereby the properties of the particles exiting the first
DMA are manipulated before entering the second DMA.
Tandem DMA setups are used at least since the 1980’s
for aerosol particle analysis. Depending on the type ofmanipulation performed on the particles that exit the first
DMA, different properties of the particles can be derived
from the second mobility analysis. One prominent typeof manipulation is heating of the aerosol. Heating allows
to determine the volume of metal particle aggregates bysintering the aggregates to a spherical shape or removal oforganic material from particles which reveals properties onparticle chemical composition (Shin W.G. et al., 2010; Tsai
D.-H. et al., 2013).
The second prominent type of manipulation is the exposure of the particles to a different gas atmosphere thatinteracts with the particles either in form of condensationor chemical reactions (Wu et al., 2013; McMurry et al.,1983). Such gas phase manipulations reveal the fractionof hygroscopic particle material or the acidic material
fraction, respectively.

4.3 Atmospheric-pressure ion mobility mass
spectroscopy (IM-MS)
The outlined techniques in this section are related toion mobility mass spectroscopy approaches, which consist
generally of a two stage separation process. In the first stepions or particles are separated according to electrical mobility, while in the second step separation occurs according
to the mass to charge ratio.
The development of atmospheric pressure mass analysis(APM) added a strong analytical tool for the analysis ofaerosols (Ehara et al., 1996). The combination of a DMA
and an APM is capable to attribute (effective) densities toparticles as shown by McMurry for discrete particle sizes
classified by the DMA (McMurry et al., 2002).
Pratsinis and co-workers analyzed nanoparticle agglomerates of silica in a diffusion flame. Upon leaving theflame, the agglomerates were classified with a DMA andtheir mass was measured with an APM resulting in theirmass fractal dimension and dynamic shape factor while
SEM/TEM images were used to determine primary particle
diameters and agglomerate morphology. This combination
was used to study the effects of flame process variables onparticle characteristics in-depth (Scheckman et al., 2009).
Hogan et al. employed the DMA-APM combination tomeasure well resolved 2D size-density distributions. In

their most recent publication (Li C. et al., 2020) it wasdemonstrated how a full 2D size-mass distribution canbe obtained by ion mobility mass spectrometry and how
1D distributions can be derived from these datasets. The
method was applied to several standard particles, i.e.
polystyrene, latex and silica nanoparticles and porous mesostructured silica. In their setup, the aerosol is classified ina DMA according to the electrophoretic mobility. Subsequently, the particles are analyzed via an APM and condensation particle counter (CPC). This combination leads to a
 2nfull 2D size-mass distribution function d m , with particleppdiameter dp and mass mp. Notably, this quantity cannot be[26]
measured directly but was obtained via the system transfer
function and data inversion algorithms (Li C. et al., 2020).
The schematic setup is shown in Fig. 7 along with the 2D
mass-diameter function, additional 1D data can be obtained
from this 2D function.
For structural characterization of even smaller species,
DMA classification can be combined with conventional
mass spectrometry. Based on molecular dynamics (MD)simulations it is possible to attribute particle shapes to cluster ions (Ouyang et al., 2013). The observation of structuralchanges in molecular conformation is beautifully demonstrated on electrosprayed PEG, see e.g. Fig. 8, which isfound in the gas phase in different - though very defined- levels of deconvolution (Larriba et al., 2014; Larriba
and Fernandez de la Mora, 2012). These results show thatthe lower limit of the combined DMA-mass analysis isat the molecular level. Such analysis is though limited tonarrow distributions of shape for each observed species.
With broader shape distributions, different charge states,in which a species is observed, become indistinguishable
Beside the characterization of the mass of particles,
access to the elemental composition of large particles is investigated since many years based on particle evaporationby either laser pulses or inductively coupled plasmas andmass analysis of the generated ions. A summary of suchapproaches that intend to reveal chemical compositions ofparticles is found in (Noble and Prather, 2000). While ICP
ionization was quite rare in early setups for single particle
mass spectrometry, this technology is on its way to a routine analysis today (Montaño et al., 2016). The access toparticle morphology and composition has been shown using coherent X-ray radiation from a free electron laser forparticle imaging and as ionization source (Loh et al., 2012).

4.4 Optical measurements
A cooperation between several universities and industrial partners in Germany demonstrated the benefits of multiparameter characterization approaches in the gas phase.
Therefore, three new devices have been developed (Babick
et al., 2018), which facilitate or support multidimensional

11

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Fig. 7 (I) DMA-APM-CPC system for the IM-MS measurements, (II) simulated bimodal porous nanoparticles distribution of SiO2 nanoparticles.
Adapted with permission from (Li C. et al., 2020). Copyright 2020 American Chemical Society.

Fig. 8Gas phase structures for PEG. Adapted with permission from (Larriba and La Mora, 2012). Copyright 2012 American Chemical Society.

characterization of aerosols and are principally suitedfor quasi-real-time measurements in technical processes.
These systems probe the optical scattering pattern of
single particles (laser light scattering in 3D, 3D-LSS) andaerosols (wide angle light scattering, WALS) or determine
the aerodynamic diameter (or Stokes diameter) of finely
resolved aerosol fractions (differential aerodynamic par-12

ticle sizer, DAPS). The systems allow for a simultaneous
determination of particle size and shape (WALS, 3D-LSS)or facilitate the rapid multiparameter characterization by
combined analysis with other techniques, e.g., DAPS anddifferential electric mobility analysis (DEMA). For instance, the dynamic shape factor (obtained via e.g. DEMA
and DAPS) and the fractal dimension (via WALS) reflectUwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

the morphology changes of SiO2 aggregates in a sintering
furnace by increasing temperature. The two parameters are
not equivalent but provide complementary information on
shrinking and loss of fractal structure, respectively. Highly
resolved PSDs that refer to different particle properties, i.e.
to different equivalent diameters, facilitate the quantification of particle shape.
Two of these devices will briefly be introduced here,
namely, the 3D LSS and the WALS device. With thefirst one it is possible to measure the spatially distributed
scattering signal of a single particle. In contrast to mostcommon laser scattering instruments, scattering signals
depending on the azimuth angle φ are detected too (seeFig. 9), which allows for the measurement of anisotropic
nanoparticles (Babick et al., 2018). Possible particle sizesfor detection range from 500 nm up to 5 μm.
The second instrument, WALS, depicted in Fig. 10,
records scattered light signals over many angles (including
forward- and backscattering, but no azimuthal angles) in ascattering plane with high resolution. This setup directly
measures the intensity distribution for different angles,
which is directly linked to particle size and the structureof agglomerates (Babick et al., 2018). With these developments, the comprehensive multidimensional characterization of aerosol particles can be further improved.

of (nano) particles in numerous technical applications.
Often, detailed knowledge of the particle property spaceis required for the determination and optimization of themacroscopic properties of the dispersions. The choice ofanalytic techniques depends upon the state of the (nano)5. Characterization in the liquid phase
The comprehensive multidimensional characterizationof nanoparticle ensembles directly in the liquid phase isof outmost importance for understanding the formation ofparticles and their formulation including colloidal stability

Fig. 10

Fig. 9 (I) Detection scheme of the 3D LSS. (II) section of the sphericalmeasurement chamber. Adapted with permission from (Babick et al.,2018). Copyright 2018, Wiley.

WALS scheme with optical components. Reproduced with permission from (Babick et al., 2018). Copyright 2018, Wiley.

13

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

particles in the dispersion, the particles’ hydrodynamic
behavior as well as the functional particle property (e.g.
light absorption or emission).
Single particle counting is only possible for particles
larger than roughly half a micron. The application of super-resolution microscopy and its combination with othertechniques has been outlined in the respective chapter onlight microscopy. In the liquid phase, super-resolution
microscopy has also been used in order to characterizedispersed particles. One example is the investigation ofparticle wetting behavior at the oil/water interface depending on the particle geometry: single particles are immersed
in water containing a fluorescent dye; the distribution of thedye within the liquid and on the particle surface is determined via super-resolution microscopy (Aloi et al., 2019).
Ensemble techniques are based on ultrasound attenuation, light extinction or emission measurement. Electroacoustic spectroscopy provides access to the particle
size distribution and the zeta potential even in opaquedispersions up to 40 vol-% (Dukhin A.S. and Goetz, 1998;
Richter et al., 2005). Fractionating techniques like analytical (ultra-)centrifugation (AUC) or field flow fractionation(FFF) require rather dilute systems but yield superior information on the entire particle ensembles.
Most techniques are well-established in literature andhave been extensively used in the past. However, their application with respect to multidimensional characterizationis still at an early stage although considerable progress
was achieved in recent years, examples are given in thefollowing sections.

5.1 Image analysis in the flow
In the first part, we briefly address commercial applications for the characterization of μm-sized particles. Thereare existing commercial systems from Sympatec GmbH fordynamic imaging techniques targeting particle systems in
the liquid phase, namely QICPIC and PICTOS. These canbe efficiently used in order to analyze particle sizes up to
several tens of millimeters through a flow setup and an automated image analysis algorithm (Sympatec, 2021). Malvern Panalytical Ltd combines image analysis techniqueswith Raman spectroscopy in order to analyze particle size,
shape and chemical composition within one measurement(Malvern, 2021).
Mazotti and coworkers described a method that uses
focused beam reflectance measurement in order to measureparticle size and shape on a 2D grid (Kempkes et al., 2008).
In particular, 2D growth rates are extracted from the measurements (Schorsch et al., 2014). In short, the suspension
is illuminated using a xenon-flash lamp. Two images arerecorded. The transmission image allows the analysis of
the planar view on the particles directly in suspension. The
reflection image contains information on the lateral view.

14

For the determination of the nD PSD (i.e. axis length distribution), an automated image analysis algorithm is applied
for the sorting of the particles into distinct particle classes.
Each pair of projections is analyzed individually in order toextract volumetric information from two orthogonal projections. Examples for the shape classes are spheres (1D,the diameter as the characteristic length), needles (2D, cylinders with length and diameter) and cuboids (3D: length,
width, and height). The key of these studies is the accurate
extraction of particle dimensions from directly measured
and simulated images. A multidimensional PSD can bereconstructed from the data and moments can be computed.
The group of Sundmacher developed a method to
identify face-specific crystal growth rates based on animage analysis (Borchert et al., 2014). For this application,
the flow cell analyzer QICPIC from Sympatec GmbH
(Clausthal, Germany) was used in direct connection to a
crystallizer. The authors reconstructed 3D crystal shapes
from microscopic images with arbitrary orientations. A
schematic representation of their setup and methodology isprovided in the following figure. As nicely demonstrated in
the lower panel of Fig. 11, it was possible to determine 2D
PSDs of various particle shapes.

5.2 Laser diffraction
Laser diffraction (LD) also called laser diffraction
spectroscopy or static light scattering or is a powerful andwidely used technique to determine PSDs over a broad
size range. Early developments were implemented byLeschonski and co-workers (Heuer and Leschonski K.,
1985) by retrieving the one-dimensional PSDs of aerosols
and particles in suspension. The technique is fast, precise,and cost efficient when compared to other characterization
techniques. Eshel et al. critically evaluated the applicationof LD for the analysis of particle size distributions (Eshelet al., 2004).
The influence of particle shape on the measured PSD
has been thoroughly investigated by the Scarlett group andothers, see for instance (Ma et al., 2001; Eshel et al., 2004;
Matsuyama and Yamamoto, 2005; Kang et al., 1994).
Furthermore, 1D equivalent diameter distributions were
measured for platelets and rods by calculating Fraunhofer
diffraction patterns for arbitrary polyhedron particles(Heffels et al., 1996). Recently, a detailed analysis of LD
of anisotropic particles was published providing information on particle orientation. Micropillars with ellipticalcross-sections were used to determine the dependence
between the spatial orientation of elongated particles andchanges in the PSD (Font-Muñoz et al., 2020).
The angle-dependent intensity of scattered light can be correlated with the fractal dimension of aggregates comprisedof a large number of primary nanoparticles. For the caseof hematite aggregates, LD could be used to determine theUwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

5.3 Dynamic light scattering
Dynamic light scattering (DLS) is a well-establishedtechnique, which has been extensively used for the characterization of nanoparticle dispersions (Xu R., 2015). In
short, DLS allows for a temporal analysis of the scatteredsignal decay due to Brownian movement of nanoparticles
in a suspension (Berne and Pecora, 2000). This approach
is frequently applied in order to measure the translational
diffusion in colloidal systems, which can be exploited to
calculate the hydrodynamic diameter and the respectivehydrodynamic diameter distribution via the StokesEinstein relation close to infinite dilution. At higher concentration, concentration-dependent diffusion properties
can be extracted as well.
Moreover, there are approaches for the extraction of
more than a single parameter from DLS measurements.
For non-spherical particles, e.g. in the case of nanorods,
the additionally occurring rotational diffusion can beseparated into two parts, namely tumbling and spinningmotion around the symmetry axis of the nanorods. The
orientation-averaged rotational diffusion coefficients canbe extracted from DLS measurements together with thetranslational one by analyzing the differently polarizedcomponents of scattered light (Berne and Pecora, 2000;
Glidden and Muschol, 2012). The translational diffusion
coefficient DT and the rotational diffusion coefficient DR
can be retrieved from the decay times of the scattering
intensity (Berger Bioucas et al., 2019)
Fig. 11 (I) Shape distribution with sketches of representative shapes
for each region. (II) Estimated distribution on the basis of synthetic
images from which Fourier descriptors are extracted and used to match
it with the closest entry in a precomputed database. Adapted with permission from (Borchert et al., 2014). Copyright 2014 American Chemical
Society.

fractal dimension of differently aggregated structures. Highfractal dimensions could be correlated with slow (“reactionlimited”) aggregation, while loose tenuous aggregates were
found within the diffusion-limited aggregation regime(Raper and Amal, 1993). In an application example fromthe papermaking process, flocculation dynamics and thestability of floc against shear stress could be monitored
for different polymer additives using LD. In particular,
the influence of the floc structure on the stability could beassessed via the determination of the fractal dimension of
the flocs (Rasteiro et al., 2008). Further information on
LD of aerosols can be found in the reviews by Sorensen(Sorensen C.M., 2001; Sorensen C.M. et al., 2018).

τ C,T  DT q 2 
τ
(12)
C,mix

1

 DT q 2  6 D R   1

(12)
(13)

τC,T(13)is the mean decay time associated with translation
diffusion and τC,mix is the mean decay time associated withtranslation and rotational diffusion. The scattering vector
is %%%%%%%%%%%%%%%%%%%%%%%%%%%%
q. In particular, polarized DLS in a heterodyne detection
scheme was shown to provide the orientation-averagedtranslational and rotational diffusion coefficients of gold
nanorods in a single experiment (Berger Bioucas et al.,2019). The scattering geometry of the detection reduces
multiple scattering effects and thus allows lower laser
powers and hence reduced laser heating. This was demonstrated for non-transparent dispersions of gold nanorods
dispersed in water and in water-glycerol mixtures (Berger
Bioucas et al., 2019). Furthermore, from translational androtational relaxation times, Glidden and Muschol derived
an approach for directly obtaining particle dimensions ofgold nanorods in the case of narrowly distributed samples(Glidden and Muschol, 2012), which was confirmed byconfirmed by auxiliary TEM analysis.

15

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

5.4 Ultrasonic and electro-acoustic spectroscopy
The particle mass concentration and the PSD of suspended particles can be analysed by means of ultrasonicmeasurements. As the interaction of suspended particles
and ultrasonic waves changes the sonic velocity as well as
the extinction of sound waves, the changes of the frequencyof the ultrasonic extinction can be evaluated in order todetermine PSDs. The accessible particle sizes range from10 nm up to 1 mm, which depends on the particle properties and the experimental setup (Riebel and Löffler, 1989).
Electroacoustic spectroscopy was pioneered by O’Brien(O’Brien, 1988) and Dukhin (Dukhin A.S. and Goetz,
2001). Electroacoustic spectroscopy deals with the interaction of electric and acoustic fields. In particular, it allows
to measure the zeta potential of particles even in dense
suspensions (O’Brien, 1988). The combination of both
ultrasound sound absorption with electroacoustics provide
the unique opportunity to characterize concentrated dispersions, emulsions and microemulsions in their naturalstate. Concentrated systems can reliably be measured withconcentrations ranging up to 45 vol.-% (Dukhin A.S. and
Goetz, 2001).
The combination of these techniques is extremely valuable for the characterization of colloidal stability without
dilution and thus for the formulation of dispersions. Here
we cite only one example from our own work. The simultaneous measurement of PSD and zeta potential paved
the way to break the technical grinding limit around halfa micron, which was postulated by Jimbo (Jimbo, 1992).
Agglomeration during grinding in stirred media mills
could be avoided by inline control of the particle stability
in electrostatically stabilized dispersions. This way, the true
grinding limit could be identified and clearly distinguishedfrom an apparent grinding limit, which is the equilibriumof breakage and agglomeration. Nanomilling down to only
10 nm for refractory materials such as alumina and zirconia
became thus possible (Stenger et al., 2005; Knieke et al.,2011), depending on the defect structures in the particles.
So far, the defect structures in particles are largely unknown
and remain a “universe inside” to be explored in future.
The strength of electroacoustic measurements can beextended to the determination of charge effects withinpores. Electroacoustic measurements of the seismic electric
current generated by ultrasound in wetted porous materials
yield information on pore size distributions. This effectoccurs when electric double layers inside the pore overlap
or when the pore size is sufficiently large that for a given
frequency the hydrodynamic flow cannot achieve a steady
Poiseuille profile inside of the pores (Dukhin A. et al., 2013).

5.5 Small angle X-ray and neutron scattering
Li, Sensi and Lee published an extensive review on

16

small angle X-ray scattering (SAXS) for nanoparticle research (Li T. et al., 2016). In short, the scattering behaviorof a single particle depends on its geometry as well as on
its surface properties (Hofman et al., 1993). Therefore,
SAXS is a suitable method to characterize particle size andanisotropy. The measured intensity profile of a sample isthe superposition of all particle scattering intensities andadditionally influenced by the sample structure. Therefore,
the analysis of disperse properties of nanoparticles via
SAXS requires assumptions regarding size or shape. Typically, a suitable type of distribution must be chosen for the
retrieval of particle size distributions. (Li T. et al., 2016).
As the intensity profile also depends on the particle
shape, SAXS can also be used for the characterizationof particle anisotropy. This was visualized for ellipsoids
and cylinders in literature (Li T. et al., 2016) based on the
Guinier-Porod model (Hammouda, 2010). However, it is
not possible so far to determine full 2D PSDs solely fromSAXS profiles due to the ill-posed inversion problem forthe deconvolution of the scattering curve. A combination
with other techniques can help to overcome this limitation.
Hubert et al. were able to determine the growth dynamics
of length and diameter of gold nanorods via SAXS basedon prior information on the 2D PSD of the particles obtained by TEM (Hubert F. et al., 2012). Similar restrictions
hold also true for Grazing Incidence Small Angle X-ray
Scattering (GISAXS). This method allows the versatile
characterization of nanostructures and thin films. To unravel its full potential for the investigation of the spatialorganization, the depth profile or the morphology of thesample, the use of synchrotron radiation source is beneficial (Müller-Buschbaum, 2009; Renaud et al., 2009).
Another small angle scattering technique is small angle
neutron scattering (SANS). In these experiments, neutronradiation is monitored in order to extract information about
the particle size or shape. Further details on this techniquehave been provided by Blazek and Gilbert, focusing on theapplication of SAXS and SANS to the characterization oforganic structures (Blazek and Gilbert, 2011). Strunz et al.
characterized Ni3Si-type nanoparticles by SANS. Combining
TEM and SANS, it could be demonstrated that an amor­
phous shell forms on the particle core (Strunz et al., 2007).
In another example, SAXS and SANS have been combined. Core size and shell properties of ZnO quantum dotswith a size below 6 nm were characterized by Unruh andco-workers by a combination of SANS and SAXS for thesame sample. The X-rays provide information on the coreof the nanoparticles due to the fact that X-rays are scatteredat the electrons of the core atoms, while the neutrons arescattered at the cores of the organic shell atoms. These
results were in excellent agreement with the nanoparticle
analysis via analytical ultracentrifugation (AUC) andallowed to monitor changes of the shell during the ripening processes as a function of temperature (Schindler etUwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

al., 2015). Moreover, gold nanorods in aqueous solution
were characterized by a combination of SAXS and SANS
alongside TEM measurements. Based on these results, a
direct measurement of the thickness of the surfactant layer
CTAB on the surface of the gold nanorods was derived(Gómez-Graña et al., 2012).

5.6 Field flow fractionation
Throughout FFF an external field is applied to a suspension flowing through a narrow channel. The laminarparabolic flow velocity profile in the channel induces fasterparticle transport in the middle of the channel. The external
field acts perpendicular to the flow, whereby the interplayof acting drag and field forces leads to a separation of particles in field direction. With the different particle velocities
present, particles elute from the channel at different times
and position in dependence of particle properties and theapplied external field. FFF is subdivided into e.g. thermal,
centrifugal, gravitational and asymmetric FFF (Baalousha
et al., 2011). In particular, centrifugal FFF has recently
been applied to separate silica nanoparticles and to determine number-based PSDs (Kato et al., 2019).
A step towards the determination of nD PSDs was
conducted by Cölfen and coworkers. The authors studied
asymmetric field flow fractionation (AF4) coupled to a
multiple laser light scattering detector (Schmid et al.,2018). AF4 was used to measure diffusion coefficient
distributions based on peak broadening corrected by a newalgorithm, which uses diffusion coefficient distributions
instead of a single mean diffusion coefficient. With this,it was possible to obtain a hydrodynamic diameter distribution with increased resolution. Further evaluation of thescattered light by deconvolution of the detector signals
allowed calculating the corresponding molecular weights
of formerly not properly separated signals. Their results
are summarized in the Fig. 12. While FFF has shown to
be a powerful method for the determination of pairs of two
different parameters, the determination of full 2D PSDs is
yet to be demonstrated.
AF4 was coupled with single particle inductively coupled plasma mass spectrometry (spICP-MS). spICP-MS
is an emerging technique with respect to nanomaterial
characterization as outlined in detail in (Mozhayeva andEngelhard, 2020). Degueldre et al. presented the underlying theoretical background of spICP-MS for characterizing
nanoparticle dispersions (Degueldre et al., 2004), while
Pace et al. presented a detailed study with a focus on
sizing of nanoparticles (Pace et al., 2011). With this, theparticle mass diameter distributions of silver nanoparticles
were measured. Notably, the detector system of the MS
analyzer requires a transfer into a carrier gas. So far, thesemethods yield a particle mass diameter distribution. The
main advantage of spICP-MS is the discrimination of thenanoparticle based on elemental composition, whereas
many current characterization techniques are unable to differentiate between different types of nanoparticles. Further
classification prior to spICP-MS analysis is necessary to
distinguish between particles with the same composition(Pace et al., 2011).
The complex issue of fractionation prior to spICP-MS
was directly addressed in (Huynh et al., 2016). The authors

Fig. 12 Hydrodynamic radius distribution (Ri) and the respective molecular weight (MW) of the analysed species as retrieved from a FFF measurement after deconvolution with varying number of algorithm iterations (It). Adapted with permission from (Schmid et al., 2018). Copyright 2018
American Chemical Society.

17Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Fig. 13 Representative contour plot result of an AF4-spICP-MS
analysis of a suspension containing 40 (571 ng/L), 60 (2.39 μg/L), 80(5.25 μg/L), and 100 nm AgNPs (10.0 μg/L). Adapted with permission
from (Huynh et al., 2016). Copyright 2016 American Chemical Society.

combined AF4 with spICP-MS to solve the current limitations of conventional ICP-MS or spICP-MS. This setup
uses the advantages of two orthogonal characterization
techniques based on different physical principles in order
to simultaneously provide both mass and hydrodynamic
diameters of the detected nanoparticles yielding a full
2D PSD. From this information relevant and otherwise
hardly accessible properties such as layer thickness andaggregation states of nanoparticles can be obtained. AF4spICP-MS was capable of measuring Ag NPs from suspensions, fractionating polydisperse AgNPs (see Fig. 13),and distinguishing AgNPs from Ag-SiO2 NPs with similar
Ag mass. One limitation of the method still is the quantification of defined nanoparticle sizes in heterogeneous
samples.

5.7 2D analysis by analytical ultracentrifugation
Over decades, AUC was mostly used in the biomedical
field with a few exceptions for the analysis of colloidal systems (Planken and Cölfen, 2010; Karabudak and Cölfen,2016). Due to recent progress in the development of new
detector systems, AUC can be considered as gold standard
due to its unprecedented accuracy, reproducibility andresolution in a large range of applications (Walter J. et al.,2014; Karabudak et al., 2016; Pearson et al., 2018; Wawra
et al., 2019).
In AUC experiments, the sedimentation of nanoparticles
is tracked under the influence of a centrifugal field directlyin the liquid phase with the use of an optical detection system. The temporal and radial evolution of the concentration
profiles allow for the extraction of sedimentation (s) anddiffusion coefficients (D) alongside their associated opticalproperties. Available detection systems allow combining
extinction and fluorescence spectra with hydro- and thermodynamic properties (Uchiyama et al., 2016; Wawra et18al., 2019). While sedimentation and diffusion depend bothon size and shape of the particle, the particle density further
influences the sedimentation process.
As AUC measurements provide combined information
on sedimentation, diffusion properties and optical properties for small particles, multidimensional information canbe obtained from a single experiment. Carney et al. usedthe combination of s and D to study the particle size andparticle density distribution (Carney et al., 2011). For thecase of spherical core-shell gold nanoparticles, the sedimentation and the diffusion coefficient depend on size anddensity. Therefore, it was possible to determine the core
diameter distribution alongside the shell properties of thepolydisperse core-shell gold nanoparticles. The results areillustrated in Fig. 14 and were validated by auxiliary TEM
analysis.
Furthermore, Nontapot et al. analyzed core-shell silica
nanocrystals terminated with cyclohexane or allylamine
via AUC (Nontapot et al., 2013). In their work, the effective
particle density was determined by measuring the sedimentation properties of the nanoparticles in different solvents.
Based on these results, the shell thickness could be calculated, which provided the effective 1D PSD in agreementwith the data from other nanoparticle characterization
techniques, namely DLS and TEM. Demeler et al. further
addressed the issue of analyzing core-shell nanoparticles(Demeler et al., 2014). Their work demonstrated a powerful data evaluation tool, which is implemented in the
UltraScan-III software. With this, it was possible to determine the effective density and molar mass for CdSe and
PbS QDs from a single AUC experiment.
Thajudeen et al. (Thajudeen T. et al., 2017) combined
the measured sedimentation coefficients from AUC in
liquid phase and electrical mobility measurements from the
combination of DMA and CPC in the gas phase via transferof the nanorods from the liquid to the gas phase by anadvanced electrospray technique (Lübbert and Peukert W.,
2018). This work demonstrated that it is possible to determine mean values of length and diameter for Au and ZnOnanorods by combining the two techniques, as mobility
diameter and sedimentation coefficients depend differently
on the geometry of the rods. The results were validated byauxiliary TEM and SEM analysis. While this is a powerful
technique for the description of this system, the measurement of a full 2D PSD was not yet possible.
Analytical centrifugation (AC) is an emerging techniquefor nanoparticle characterization (Detloff et al., 2007),
which is more easily applicable than AUC, less expensive
and delivers high sample throughput by parallelization of
up 12 samples in one run. Interestingly, software tools forthe comprehensive determination of PSD from AUC data
have been transferred to AC (Walter J. et al., 2015). This
step significantly enhanced the precision of the obtained
distributions in particular for heterogeneous samples.

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Fig. 14 (I) 1D sedimentation coefficient distribution (black) with TEM PSD (dashed red); (II) 2D sedimentation and diffusion coefficient distribution
obtained with AUC of polydisperse gold nanoparticles. Reproduced with permission from (Carney et al., 2011) under the terms of the CC BY-NC-SA
3.0 license. Copyright: (2011) The Authors, published by Springer Nature.

Moreover, the recent development of sector-shaped centerpieces for AC experiments enabled the measurementof a full diffusion-corrected sedimentation coefficient
distribution. With this, it is possible to determine the hydrodynamic diameter distribution and the core-diameter
distribution of gold nanoparticles alongside the stabilizer
shell thickness of 3 nm only (Uttinger et al., 2020).

5.8 Analytical ultracentrifugation: optical backcoupling
A very promising technique for the characterizationof plasmonic nanoparticles is the Optical Back Coupling (OBC) method (Wawra et al., 2018), which allows
obtaining number-weighted 2D PSDs. Therefore, thesedimentation of particles within an AUC is tracked via a
multiwavelength detector. This allows deducing sedimentation coefficient distributions for many different detection
wavelengths. In return, extinction spectra can be extracted
for defined intervals of the sedimentation coefficient
distribution enabling to correlate the mean sedimentation
coefficient of the respective interval with the spectra of theparticles exhibiting these defined sedimentation properties,
as shown in Fig. 15 for gold nanorods.
As the spectra of the gold nanorods as well as thesedimentation coefficients depend on the geometry of theparticle, the combined optical and hydrodynamic informa-

Fig. 15 (I) Cumulative sedimentation coefficient distribution at awavelength of 480 nm with indicated separation in sedimentation coefficient intervals. (II) Spectra for selected intervals with associated mean
sedimentation coefficient. Reproduced with permission from (Wawra etal., 2018) under the terms of the CC-BY 4.0 license. Copyright: (2018)
The Authors, published by Springer Nature.

tion can be used to deduce length and diameter alongside
the particle concentration. Therefore, the extracted spectra
are analyzed using different optical models under theconstrain of the interval’s mean sedimentation coefficient.
The length, diameter, aspect ratio, volume, surface andcross-sectional distributions can be readily obtained fromthese results. As the technique can be extended to othernonspherical plasmonic particles and can be used for determining relative amounts of particles of different shapes,
it provides complete and quantitative insights into suchparticulate systems.
An exemplary 2D measurement is depicted in Fig. 16
I. The displayed TEM inset shows very good agreement

19Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Fig. 16 (I) 2D PSD of a gold nanorod sample obtained using the Mie-Gans model. The axes correspond to length and diameter, while the heatmap
indicates the distribution value. The inset shows results from TEM analysis. (II) Comparison of the 1D cumulative length and diameter distributions
from TEM data and AUC for different optical models (Mie-Gans, FEM finite element methods, LP analytical longitudinal polarization model, which
only considers polarizations along the length axis of the gold rod). Adapted with permission from (Wawra et al., 2018) under the terms of the CC-BY
4.0 license. Copyright: (2018) The Authors, published by Springer Nature.

of OBC and TEM. An even better comparison is possible
via the 1D length and 1D diameter distributions. Eq. 4 canbe used for the calculation of the reduced 1D distributions
from the 2D PSD, integration leads to the cumulative distributions. All used optical models show excellent agreementwith TEM statistics, see Fig. 16 II, which emphasizes theaccuracy and potential of the OBC method for 2D characterization of plasmonic nanoparticle ensembles.
In addition to advances in the data analysis of plasmonic
nanoparticle ensembles, a multi-wavelength emission detector has recently been developed for AUC (Wawra et al.,2019). These hardware developments significantly enlarge
the measurement window of AUC for the detection ofsize-dependent emission properties of nanoparticles.

6. Conclusions
Modern particle systems are associated with a wide
range of applications. The necessary functionality of micro- and nanoparticle systems is a direct result of the fivedimensional parameter space that is defined by particle
size, shape, surface, structure, and composition.
In the first part of this review, we provided the mathematical background for the comprehensive description ofparticle property distributions. These concepts extent thewell-known 1D PSD to a multidimensional description ofparticle property distributions. In particular, it was shownhow to calculate 1D distributions from 2D property distributions.
While the determination of 1D PSDs is well established,
the direct retrieval of nD PSDs is a challenging task but
necessary next step towards the control of the full particle
property space. Recent progress in the description andcharacterization of multivariate particle property distributions is summarized.
Well-established techniques such as light microscopy,

20

SEM and TEM or AFM allow for the retrieval of 2D projections of particles while more advanced 3D tomography
provides full 3D information. Moreover, correlating thechemical composition with topographic or geometric
information is possible by coupling spectroscopic measurements with AFM co-localization. However, most ofthese techniques, are very tedious, time-consuming andrequire complex sample handling. Moreover, the results
are typically associated with the common problem of poor
statistics. For nD PSDs, large sample numbers are required.
Early works for the determination of 2D property
distributions were conducted for aerosols. The couplingof different measurement devices like the DMA with asubsequent device allows to determine nD property distributions. This has been demonstrated by coupling DMA andinductively coupled plasma atomic emission spectrometry,epiphaniometer, CPC and MS, for instance.
For μm-sized particles dispersed in the liquid phase,
there are several techniques for nD characterization by
image analysis in flowing systems. These are applied inorder to investigate crystal growth kinetics in situ. Wellestablished scattering techniques such as DLS, SAXS orSANS allow for extracting information on the particle sizeand shape directly in liquid phase.
Fractionating techniques, such as FFF and A(U)C
bear the advantage of particle separation prior to theirdetection. This enables the detailed analysis of individual
fractions of an entire particle ensemble. In particular,
AUC was successfully applied for a 2D analysis of coreshell nanoparticles by the analysis of sedimentation anddiffusion properties. Recently, novel approaches were
demonstrated for the coupling of optical and hydrodynamic
properties of plasmonic nanoparticles in combination witha multi-wavelength detector to analyze number-weighted
2D dimensional distributions of diameter and length ofgold nanorods.
In summary, our review discusses advances andUwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

experimental possibilities to characterize particle ensembles with respect to nD property distributions. Few
techniques are available, which deliver multidimensional
particle properties directly. As the complexity continues
to increase, further method development is required. We
foresee that clever combinations of several techniques willallow to shed light on the complex multiparameter space offine particle systems. As often in science, progress strongly
depends on our ability to “see” what is going on, i.e. advances in multidimensional particle characterization aremandatory for the further development and full exploitation of particulate products of high-added value.

Acknowledgements
The authors thank the Deutsche Forschungsgemeinschaft (DFG) for financial support through the priority
program SPP 2045: “Highly specific and multidimensional
fractionation of fine particle systems with technical relevance.”, and projects PE427/37-1, PE 427/33-1. The
authors gratefully acknowledge funding from the DFG
through the collaborative research centers SFB 953 andSFB 1411.

References
Ahmad R., Nicholson K.S., Nawaz Q., Peukert W., Distaso M.,
Correlation between product purity and process parameters
for the synthesis of Cu2ZnSnS4 nanoparticles using microwave irradiation, Journal of Nanoparticle Research, 19(2017) 1–13. DOI: 10.1007/s11051-017-3932-5
Aloi A., Vilanova N., Isa L., Jong A.M. de, Voets I.K., Superresolution microscopy on single particles at fluid interfaces
reveals their wetting properties and interfacial deformations, Nanoscale, 11 (2019) 6654–6661. DOI: 10.1039/
C8NR08633H
Baalousha M., Stolpe B., Lead J.R., Flow field-flow fractionation
for the analysis and characterization of natural colloids andmanufactured nanoparticles in environmental systems: a
critical review, Journal of Chromatography A, 1218 (2011)
4078–4103. DOI: 10.1016/j.chroma.2011.04.063
Babick F., Hillemann L., Stintz M., Dillenburger T., Pitz M.,
Hellmann A., Antonyuk S., Ripperger S., Huber F.J.T.,
Will S., Wernet R., Seipenbusch M., Gensch M., Weber A.,
Kiesler D., Kruis E., Friehmelt R., Sachweh B., Multiparameter characterization of aerosols, Chemie Ingenieur Technik,
90 (2018) 923–936. DOI: 10.1002/cite.201700094
Berger Bioucas F.E., Damm C., Peukert W., Rausch M.H., Koller
T.M., Giraudet C., Fröba A.P., Translational and rotational
diffusion coefficients of gold nanorods dispersed in mixturesof water and glycerol by polarized dynamic light scattering,
The Journal of Physical Chemistry B, 123 (2019) 9491–9502.
DOI: 10.1021/acs.jpcb.9b08274
Berne B.J., Pecora R., Dynamic Light Scattering: With Applications to Chemistry, Biology, and Physics, Dover Publications,Mineola, N.Y., 2000, ISBN: 0486442276.
Binnig, Quate, Gerber, Atomic force microscope, PhysicalReview Letters, 56 (1986) 930–933. DOI: 10.1103/
PhysRevLett.56.930
Blazek J., Gilbert E.P., Application of small-angle X-ray andneutron scattering techniques to the characterisation of
starch structure: a review, Carbohydrate Polymers, 85 (2011)
281–293. DOI: 10.1016/j.carbpol.2011.02.041
Borchert C., Temmel E., Eisenschmidt H., Lorenz H.,
Seidel-Morgenstern A., Sundmacher K., Image-based insitu identification of face specific crystal growth rates fromcrystal populations, Crystal Growth & Design, 14 (2014)
952–971. DOI: 10.1021/cg401098x
Brown J.W., Henderson B.L., Kiesz M.D., Whalley A.C.,
Morris W., Grunder S., Deng H., Furukawa H., Zink J.I.,
Stoddart J.F., Yaghi O.M., Photophysical pore control in anazobenzene-containing metal-organic framework, Chemical
Science, 4 (2013) 2858. DOI: 10.1039/c3sc21659d
Bujak B., Bottlinger M., Three-dimensional measurement ofparticle shape, Particle & Particle Systems Characterization,
25 (2008) 293–297. DOI: 10.1002/ppsc.200800027
Carney R.P., Kim J.Y., Qian H., Jin R., Mehenni H., Stellacci F.,
Bakr O.M., Determination of nanoparticle size distribution
together with density or molecular weight by 2D analyticalultracentrifugation, Nature Communications, 2 (2011) 335.
DOI: 10.1038/ncomms1338
Castro R.H.R., Gouvêa D., Sintering and nanostability: the thermodynamic perspective, Journal of the American CeramicSociety, 99 (2016) 1105–1121. DOI: 10.1111/jace.14176
Chan K.-Y., Ding J., Ren J., Cheng S., Tsang K.Y., Supported
mixed metal nanoparticles as electrocatalysts in low temperature fuel cells, Journal of Materials Chemistry, 14 (2004) 505.
DOI: 10.1039/b314224h
Chemseddine A., Weller H., Highly monodisperse quantum sized
CdS particles by size selective precipitation, Berichte derBunsengesellschaft für physikalische Chemie, 97 (1993)
636–638. DOI: 10.1002/bbpc.19930970417
Chistyakov D., Sergeev G., The polymorphism of drugs: newapproaches to the synthesis of nanostructured polymorphs,
Pharmaceutics, 12 (2020) 34. DOI: 10.3390/pharmaceutics
12010034
Damm C., Nacken T.J., Peukert W., Quantitative evaluation ofdelamination of graphite by wet media milling, Carbon, 81(2015) 284–294. DOI: 10.1016/j.carbon.2014.09.059
Davidov-Pardo G., Joye I.J., McClements D.J., Food-grade
protein-based nanoparticles and microparticles for bioactive
delivery: fabrication, characterization, and utilization,
Advances in Protein Chemistry and Structural Biology, 98(2015) 293–325. DOI: 10.1016/bs.apcsb.2014.11.004
Dazzi A., Prater C.B., AFM-IR: Technology and applicationsin nanoscale infrared spectroscopy and chemical imaging,Chemical Reviews, 117 (2017) 5146–5173. DOI: 10.1021/
acs.chemrev.6b00448
Degueldre C., Favarger P.-Y., Bitea C., Zirconia colloid analysis
by single particle inductively coupled plasma–mass spectrometry, Analytica Chimica Acta, 518 (2004) 137–142. DOI:
10.1016/j.aca.2004.04.015
Del Rosso T., Rey N.A., Rosado T., Landi S., Larrude D.G., Romani
E.C., Junior F.L.F., Quinteiro S.M., Cremona M., Aucelio
R.Q., Margheri G., Pandoli O., Synthesis of oxocarbonencapsulated gold nanoparticles with blue-shifted localized
surface plasmon resonance by pulsed laser ablation in waterwith CO2 absorbers, Nanotechnology, 27 (2016) 255602.
DOI: 10.1088/0957-4484/27/25/255602
Detloff T., Sobisch T., Lerche D., Particle size distribution by
space or time dependent extinction profiles obtained byanalytical centrifugation (concentrated systems), Powder

21Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Technology, 174 (2007) 50–55. DOI: 10.1016/j.powtec.
2006.10.021
Dimitrov A.S., Miwa T., Nagayama K., A comparison between
the optical properties of amorphous and crystalline monolayers of silica particles, Langmuir, 15 (1999) 5257–5264. DOI:
10.1021/la990225r
Distaso M., Apeleo Zubiri B., Mohtasebi A., Inayat A., Dudák
M., Kočí P., Butz B., Klupp Taylor R., Schwieger W.,
Spiecker E., Peukert W., Three-dimensional and quantitative
reconstruction of non-accessible internal porosity in hematite
nanoreactors using 360° electron tomography, Microporousand Mesoporous Materials, 246 (2017) 207–214. DOI:
10.1016/j.micromeso.2017.03.028
Domaschke M., Zhou X., Wergen L., Romeis S., Miehlich
M.E., Meyer K., Peukert W., Schmuki P., Magnéli-phases
in anatase strongly promote cocatalyst-free photocatalytichydrogen evolution, ACS Catalysis, 9 (2019) 3627–3632.
DOI: 10.1021/acscatal.9b00578
Duan Z.-Q., Liu Y.-T., Xie X.-M., Ye X.-Y., Zhu X.-D., h-BN
nanosheets as 2D substrates to load 0D Fe3O4 nanoparticles:
a hybrid anode material for lithium-ion batteries, Chemistry–
An Asian Journal, 11 (2016) 828–833. DOI: 10.1002/
asia.201501439
Dukhin A., Swasey S., Thommes M., A method for pore size andporosity analysis of porous materials using electroacoustics
and high frequency conductivity, Colloids and Surfaces
A: Physicochemical and Engineering Aspects, 437 (2013)
127–132. DOI: 10.1016/j.colsurfa.2013.01.018
Dukhin A.S., Goetz P.J., Characterization of aggregation
phenomena by means of acoustic and electroacoustic
spectroscopy, Colloids and Surfaces A: Physicochemical
and Engineering Aspects, 144 (1998) 49–58. DOI: 10.1016/
S0927-7757(98)00565-2
Dukhin A.S., Goetz P.J., Acoustic and electroacoustic spectroscopy for characterizing concentrated dispersions and emulsions, Advances in Colloid and Interface Science, 92 (2001)
73–132. DOI: 10.1016/S0001-8686(00)00035-X
Egan C.K., Jacques S.D.M., Wilson M.D., Veale M.C., Seller P.,
Beale A.M., Pattrick R.A.D., Withers P.J., Cernik R.J., 3D
chemical imaging in the laboratory by hyperspectral X-ray
computed tomography, Scientific Reports, 5 (2015) 15979.
DOI: 10.1038/srep15979
Ehara K., Hagwood C., Coakley K.J., Novel method to classify
aerosol particles according to their mass-to-charge ratio—
Aerosol particle mass analyser, Journal of Aerosol Science,
27 (1996) 217–234. DOI: 10.1016/0021-8502(95)00562-5
Eigler S., Hof F., Enzelberger-Heim M., Grimm S., Müller P.,
Hirsch A., Statistical raman microscopy and atomic force
microscopy on heterogeneous graphene obtained after reduction of graphene oxide, The Journal of Physical Chemistry C,
118 (2014) 7698–7704. DOI: 10.1021/jp500580g
Elazzouzi-Hafraoui S., Nishiyama Y., Putaux J.-L., Heux L.,
Dubreuil F., Rochas C., The shape and size distribution of
crystalline nanoparticles prepared by acid hydrolysis ofnative cellulose, Biomacromolecules, 9 (2008) 57–65. DOI:
10.1021/bm700769p
Eom N.S.A., Kim T.-S., Choa Y.-H., Kim W.-B., Kim B.S.,
Core-size-dependent properties of CdSe/CdS core/shell
QDs, Materials Letters, 99 (2013) 14–17. DOI: 10.1016/j.
matlet.2013.02.065
Esayanur M.S., Yeruva S.B., Rabinovich Y.I., Moudgil B.M.,
Interaction force measurements using atomic force
microscopy for characterization and control of adhesion,
dispersion and lubrication in particulate systems, Journal of
Adhesion Science and Technology, 19 (2005) 611–626. DOI:

22

10.1163/1568561054890516
Eshel G., Levy G.J., Mingelgrin U., Singer M.J., Critical evaluation of the use of laser diffraction for particle-size distribution
analysis, Soil Science Society of America Journal, 68 (2004)
736–743. DOI: 10.2136/sssaj2004.7360
Fandrich R., Gu Y., Burrows D., Moeller K., Modern SEMbased mineral liberation analysis, International Journal of
Mineral Processing, 84 (2007) 310–320. DOI: 10.1016/j.
minpro.2006.07.018
Fathi M., Varshosaz J., Mohebbi M., Shahidi F., Hesperetin-loaded solid lipid nanoparticles and nanostructure lipid
carriers for food fortification: preparation, characterization,and modeling, Food and Bioprocess Technology, 6 (2013)
1464–1475. DOI: 10.1007/s11947-012-0845-2
Finnegan M.P., Zhang H., Banfield J.F., Phase stability andtransformation in titania nanoparticles in aqueous solutions
dominated by surface energy, The Journal of Physical Chemistry C, 111 (2007) 1962–1968. DOI: 10.1021/jp063822c
Font-Muñoz J.S., Jeanneret R., Tuval I., Basterretxea G., Method
for the determination of preferential orientation of marine
particles from laser diffraction measurements, Optics
Express, 28 (2020) 14085–14099. DOI: 10.1364/OE.390388
Frank U., Wawra S.E., Pflug L., Peukert W., Multidimensional
particle size distributions and their application to nonspherical particle systems in two dimensions, Particle &Particle Systems Characterization, 36 (2019) 1800554. DOI:
10.1002/ppsc.201800554
Frei M., Kruis F.E., Image-based size analysis of agglomerated
and partially sintered particles via convolutional neuralnetworks, Powder Technology, 360 (2020) 324–336. DOI:
10.1016/j.powtec.2019.10.020
Fu W., Zhang W., Hybrid AFM for nanoscale physicochemical
characterization: recent development and emerging applications, Small, 13 (2017) 1603525. DOI: 10.1002/smll.
201603525
Fultz B., Howe J., Transmission Electron Microscopy and Diffractometry of Materials, 3rd ed., Springer Berlin Heidelberg,
Berlin, Heidelberg, 2008, ISBN: 3540738851.
Furat O., Leißner T., Bachmann K., Gutzmer J., Peuker U.,
Schmidt V., Stochastic modeling of multidimensional
particle properties using parametric copulas, Microscopy
and Microanalysis, 25 (2019) 720–734. DOI: 10.1017/
S1431927619000321
Gerdova I., Haché A., Third-order non-linear spectroscopyof CdSe and CdSe/ZnS core shell quantum dots, Optics
Communications, 246 (2005) 205–212. DOI: 10.1016/j.
optcom.2004.10.068
Giesbers M., Kleijn J.M., Cohen Stuart M.A., Interactions
between acid- and base-functionalized surfaces, Journal of
Colloid and Interface Science, 252 (2002) 138–148. DOI:
10.1006/jcis.2002.8388
Glidden M., Muschol M., Characterizing gold nanorods in solution using depolarized dynamic light scattering, The Journalof Physical Chemistry C, 116 (2012) 8128–8137. DOI:
10.1021/jp211533d
Gómez-Graña S., Hubert F., Testard F., Guerrero-Martínez A.,
Grillo I., Liz-Marzán L.M., Spalla O., Surfactant (bi)layers
on gold nanorods, Langmuir, 28 (2012) 1453–1459. DOI:
10.1021/la203451p
Gudarzi M.M., Colloidal stability of graphene oxide: aggregationin two dimensions, Langmuir, 32 (2016) 5058–5068. DOI:
10.1021/acs.langmuir.6b01012
Guisbiers G., Advances in thermodynamic modelling of nanoparticles, Advances in Physics: X, 4 (2019) 1668299. DOI:
10.1080/23746149.2019.1668299

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Halbig C.E., Nacken T.J., Walter J., Damm C., Eigler S., Peukert
W., Quantitative investigation of the fragmentation process
and defect density evolution of oxo-functionalized graphene
due to ultrasonication and milling, Carbon, 96 (2016)
897–903. DOI: 10.1016/j.carbon.2015.10.021
Hammouda B., A new Guinier-Porod model, Journal of Applied
Crystallography, 43 (2010) 716–719. DOI: 10.1107/
S0021889810015773
Hansen S., Translational friction coefficients for cylinders ofarbitrary axial ratios estimated by Monte Carlo simulation,
The Journal of Chemical Physics, 121 (2004) 9111–9115.
DOI: 10.1063/1.1803533
Haubold S., Haase M., Kornowski A., Weller H.,
Strongly luminescent InP/ZnS core-shell nanoparticles, ChemPhysChem, 2 (2001) 331–334. DOI:
10.1002/1439-7641(20010518)2:5<331::AID-CPHC331>
3.0.CO;2-0
Hauser M., Wojcik M., Kim D., Mahmoudi M., Li W., Xu K.,
Correlative super-resolution microscopy: new dimensions
and new opportunities, Chemical Reviews, 117 (2017)7428–7456. DOI: 10.1021/acs.chemrev.6b00604
He Z., Wang P., Liu D., Zhou Z., Hydrophilic-lipophilic balanced
magnetic nanoparticles: preparation and application in magnetic solid-phase extraction of organochlorine pesticides andtriazine herbicides in environmental water samples, Talanta,
127 (2014) 1–8. DOI: 10.1016/j.talanta.2014.03.074
Heffels C.M.G., Verheijen P.J.T., Heitzmann D., Scarlett B., Correction of the effect of particle shape on the size distribution
measured with a laser diffraction instrument, Particle &Particle Systems Characterization, 13 (1996) 271–279. DOI:
10.1002/ppsc.19960130504
Herre P., Romeis S., Mačković M., Przybilla T., Paul J.,
Schwenger J., Torun B., Grundmeier G., Spiecker E., Peukert
W., Deformation behavior of nanocrystalline titania particles
accessed by complementary in situ electron microscopy
techniques, Journal of the American Ceramic Society, 100(2017) 5709–5722. DOI: 10.1111/jace.15072
Heuer M., Leschonski K., Results obtained with a new instrument
for the measurement of particle size distributions fromdiffraction patterns, Particle & Particle Systems Characterization, 2 (1985) 7–13. DOI: 10.1002/ppsc.19850020102
Hochella M.F., Lower S.K., Maurice P.A., Penn R.L., Sahai N.,
Sparks D.L., Twining B.S., Nanominerals, mineral nanoparticles, and earth systems, Science, 319 (2008) 1631–1635.
DOI: 10.1126/science.1141134
Hofman R., Westheim J.G.F., Fransen T., Gellings P.J., Improved
SiO2-coatings against high temperature sulphidation by internal stress reduction, Le Journal de Physique IV, 03 (1993)
C9-865–C9-871. DOI: 10.1051/jp4:1993989
Holst J.R., Cooper A.I., Ultrahigh surface area in porous solids,
Advanced Materials, 22 (2010) 5212–5216. DOI: 10.1002/
adma.201002440
Hu J., Wang H., Gao Q., Guo H., Porous carbons prepared byusing metal-organic framework as the precursor for supercapacitors, Carbon, 48 (2010) 3599–3606. DOI: 10.1016/j.
carbon.2010.06.008
Hu Z., Srinivasan M.P., Mesoporous high-surface-area activatedcarbon, Microporous and Mesoporous Materials, 43 (2001)
267–275. DOI: 10.1016/S1387-1811(00)00355-3
Hubert F., Testard F., Thill A., Kong Q., Tache O., Spalla O.,
Growth and overgrowth of concentrated gold nanorods: time
resolved SAXS and XANES, Crystal Growth & Design, 12(2012) 1548–1555. DOI: 10.1021/cg2016116
Huynh K. an, Siska E., Heithmar E., Tadjiki S., Pergantis S.A.,
Detection and quantification of silver nanoparticles at envi-

ronmentally relevant concentrations using asymmetric flow
field-flow fractionation online with single particle inductively
coupled plasma mass spectrometry, Analytical Chemistry, 88(2016) 4909–4916. DOI: 10.1021/acs.analchem.6b00764
Jallo L.J., Chen Y., Bowen J., Etzler F., Dave R., Prediction ofinter-particle adhesion force from surface energy and surface
roughness, Journal of Adhesion Science and Technology, 25(2011) 367–384. DOI: 10.1163/016942410X525623
Jimbo G., Chemical engineering analysis of fine grinding phenomenon and process, Journal of Chemical Engineering ofJapan, 25 (1992) 117–127. DOI: 10.1252/jcej.25.117
Joye I.J., McClements D.J., Biopolymer-based nanoparticles andmicroparticles: fabrication, characterization, and application,
Current Opinion in Colloid & Interface Science, 19 (2014)
417–427. DOI: 10.1016/j.cocis.2014.07.002
Kang S.H., Lyoo P.J., Kim D.W., Park J.H., Laser diffraction
pattern analysis of various two-dimensional regular-shaped
model particles, Advanced Powder Technology, 5 (1994)
33–42. DOI: 10.1016/S0921-8831(08)60623-8
Kannan A.G., Manjulavalli T.E., Chandrasekaran J., Influenceof solvent on the properties of CZTS nanoparticles, Procedia Engineering, 141 (2016) 15–22. DOI: 10.1016/j.
proeng.2015.08.1112
Karabudak E., Brookes E., Lesnyak V., Gaponik N., Eychmüller
A., Walter J., Segets D., Peukert W., Wohlleben W., Demeler
B., Cölfen H., Simultaneous identification of spectral properties and sizes of multiple particles in solution with subnanometer resolution, Angewandte Chemie International Edition,
55 (2016) 11770–11774. DOI: 10.1002/anie.201603844
Karabudak E., Cölfen H., The multiwavelength UV/Vis detector:
new possibilities with an added spectral dimension, in:Uchiyama S., Arisaka F., Stafford W.F., Laue T. (Eds.), Analytical Ultracentrifugation—Instrumentation, Software, andApplications, Springer Japan, Tokyo, 2016, pp. 63–80. DOI:
10.1007/978-4-431-55985-6_5
Kato H., Nakamura A., Banno H., Determination of number-based
size distribution of silica particles using centrifugal field-flow
fractionation, Journal of Chromatography. A, 1602 (2019)409–418. DOI: 10.1016/j.chroma.2019.05.055
Kempkes M., Eggers J., Mazzotti M., Measurement of particle
size and shape by FBRM and in situ microscopy, Chemical
Engineering Science, 63 (2008) 4656–4675. DOI: 10.1016/j.
ces.2007.10.030
Khan I.U., Stolch L., Serra C.A., Anton N., Akasov R., Vandamme
T.F., Microfluidic conceived pH sensitive core-shell particles
for dual drug delivery, International Journal of Pharmaceutics, 478 (2015) 78–87. DOI: 10.1016/j.ijpharm.2014.10.010
Kim D., Moon J., Highly conductive ink jet printed films ofnanosilver particles for printable electronics, Electrochemical and Solid-State Letters, 8 (2005) J30–J33. DOI:
10.1149/1.2073670
Kim K.-M., Kim H.M., Lee W.-J., Lee C.-W., Kim T.-I., Lee
J.-K., Jeong J., Paek S.-M., Oh J.-M., Surface treatment ofsilica nanoparticles for stable and charge-controlled colloidal
silica, International Journal of Nanomedicine, 9 Suppl 2(2014) 29–40. DOI: 10.2147/IJN.S57922
Kim S.-S., Na S.-I., Jo J., Kim D.-Y., Nah Y.-C., Plasmon
enhanced performance of organic solar cells using electrodeposited Ag nanoparticles, Applied Physics Letters, 93 (2008)
073307. DOI: 10.1063/1.2967471
Kleijn S.E.F., Lai S.C.S., Miller T.S., Yanson A.I., Koper M.T.M.,
Unwin P.R., Landing and catalytic characterization ofindividual nanoparticles on electrode surfaces, Journal of theAmerican Chemical Society, 134 (2012) 18558–18561. DOI:
10.1021/ja309220m

23Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Knieke C., Romeis S., Peukert W., Influence of process parameters on breakage kinetics and grinding limit at the nanoscale,
AIChE Journal, 57 (2011) 1751–1758. DOI: 10.1002/
aic.12408
Kovačević T., Reinhold A., Briesen H., Identifying faceted crystal
shape from three-dimensional tomography data, Crystal
Growth & Design, 14 (2014) 1666–1675. DOI: 10.1021/
cg401780p
La Torre J.G. de, Echenique G.d.R., Ortega A., Improved calculation of rotational diffusion and intrinsic viscosity of beadmodels for macromolecules and nanoparticles, The Journalof Physical Chemistry B, 111 (2007) 955–961. DOI: 10.1021/
jp0647941
Larriba C., Fernandez de la Mora J., Clemmer D.E., Electrosprayionization mechanisms for large polyethylene glycol chainsstudied through tandem ion mobility spectrometry, Journalof the American Society for Mass Spectrometry, 25 (2014)
1332–1345. DOI: 10.1007/s13361-014-0885-0
Larriba C., Fernandez de la Mora J., The gas phase structureof coulombically stretched polyethylene glycol ions, The
Journal of Physical Chemistry B, 116 (2012) 593–598. DOI:
10.1021/jp2092972
Lee J.S., Shin D.H., Jun J., Lee C., Jang J., Fe3O4/carbon hybrid
nanoparticle electrodes for high-capacity electrochemicalcapacitors, ChemSusChem, 7 (2014) 1676–1683. DOI:
10.1002/cssc.201301188
Leißner T., Diener A., Löwer E., Ditscherlein R., Krüger K.,
Kwade A., Peuker U.A., 3D ex-situ and in-situ X-ray CT
process studies in particle technology—A perspective,
Advanced Powder Technology, 31 (2020) 78–86. DOI:
10.1016/j.apt.2019.09.038
Leschonski K., Alex W., Koglin B., Teilchengrößenanalyse. 1.
darstellung und auswertung von teilchengrößenverteilungen,
Chemie Ingenieur Technik, 46 (1974a) 23–26. DOI: 10.1002/
cite.330460105
Leschonski K., Alex W., Koglin B., Teilchengrößenanalyse. 1.
darstellung und auswertung von teilchengrößenverteilungen(Fortsetzung), Chemie Ingenieur Technik, 46 (1974b)
101–106. DOI: 10.1002/cite.330460307
Letellier P., Mayaffre A., Turmine M., Solubility of nanoparticles:
nonextensive thermodynamics approach, Journal of Physics:
Condensed Matter, 19 (2007) 436229. DOI: 10.1088/09538984/19/43/436229
Li C., Lee A.L., Chen X., Pomerantz W.C.K., Haynes C.L., Hogan
C.J., Multidimensional nanoparticle characterization throughion mobility-mass spectrometry, Analytical Chemistry, 92(2020) 2503–2510. DOI: 10.1021/acs.analchem.9b04012
Li Q., Kartikowati C.W., Horie S., Ogi T., Iwaki T., Okuyama
K., Correlation between particle size/domain structure andmagnetic properties of highly crystalline Fe3O4 nanoparticles, Scientific Reports, 7 (2017) 9894. DOI: 10.1038/
s41598-017-09897-5
Li T., Senesi A.J., Lee B., Small angle X-ray scattering fornanoparticle research, Chemical Reviews, 116 (2016)
11128–11180. DOI: 10.1021/acs.chemrev.5b00690
Li W., Xue Y., Cui Z., Size dependence of surface thermodynamic
properties of nanoparticles and its determination method byreaction rate constant, Physica B: Condensed Matter, 495(2016) 98–105. DOI: 10.1016/j.physb.2016.05.011
Ligon S.C., Liska R., Stampfl J., Gurr M., Mülhaupt R., Polymers
for 3D printing and customized additive manufacturing,
Chemical Reviews, 117 (2017) 10212–10290. DOI: 10.1021/
acs.chemrev.7b00074
Link S., Wang Z.L., El-Sayed M.A., Alloy formation of gold–
silver nanoparticles and the dependence of the plasmon

24

absorption on their composition, The Journal of Physical
Chemistry B, 103 (1999) 3529–3533. DOI: 10.1021/
jp990387w
Loh N.D., Hampton C.Y., Martin A.V., Starodub D., Sierra R.G.,
Barty A., Aquila A., Schulz J., Lomb L., Steinbrener J., Shoeman R.L., Kassemeyer S., Bostedt C., Bozek J., Epp S.W., etal., Fractal morphology, imaging and mass spectrometry of
single aerosol particles in flight, Nature, 486 (2012) 513–517.
DOI: 10.1038/nature11222
Lübbert C., Peukert W., The mass transfer at Taylor cones, Journalof Aerosol Science, 123 (2018) 39–51. DOI: 10.1016/j.
jaerosci.2018.05.014
Ma Z., Merkus H.G., van der Veen H.G., Wong M.,
Scarlett B., On-line measurement of particle sizeand shape using laser diffraction, Particle & Particle Systems Characterization, 18 (2001) 243–247.
DOI:
10.1002/1521-4117(200112)18:5/6<243::AIDPPSC243>3.0.CO;2-4
Maestro A., Guzmán E., Santini E., Ravera F., Liggieri L., Ortega
F., Rubio R.G., Wettability of silicananoparticle-surfactant
nanocomposite interfacial layers, Soft Matter, 8 (2012)
837–843. DOI: 10.1039/C1SM06421E
Maire E., Withers P.J., Quantitative X-ray tomography,
International Materials Reviews, 59 (2014) 1–43. DOI:
10.1179/1743280413Y.0000000023
Malvern Panalytical, Morphologi 4 range homepage, <www.
malvernpanalytical.com/en/products/product-range/morphologi-range/> accessed 02.02.2021.
Mangun C.L., Benak K.R., Economy J., Foster K.L., Surface
chemistry, pore sizes and adsorption properties of activated carbon fibers and precursors treated with ammonia,
Carbon, 39 (2001) 1809–1820. DOI: 10.1016/S00086223(00)00319-5
Matsuyama T., Yamamoto H., Particle shape and laser diffraction:a discussion of the particle shape problem, Journal of Dispersion Science and Technology, 25 (2005) 409–416. DOI:
10.1081/DIS-200025692
Mazumder M.K., Ware R.E., Yokoyama T., Rubin B.J., Kamp
D., Measurement of particle size and electrostatic charge
distributions on toners using E-SPART analyzer, IEEE
Transactions on Industry Applications, 27 (1991) 611–619.
DOI: 10.1109/28.85472
McMurry P.H., Takano H., Anderson G.R., Study of the ammonia(gas)-sulfuric acid (aerosol) reaction rate, Environmental
Science & Technology, 17 (1983) 347–352. DOI: 10.1021/
es00112a008
McMurry P.H., Wang X., Park K., Ehara K., The relationshipbetween mass and mobility for atmospheric particles: a
new technique for measuring particle density, Aerosol
Science and Technology, 36 (2002) 227–238. DOI:
10.1080/027868202753504083
Miao J., Ercius P., Billinge S.J.L., Atomic electron tomography:
3D structures without crystals, Science, 353 (2016) aaf2157.
DOI: 10.1126/science.aaf2157
Modena M.M., Rühle B., Burg T.P., Wuttke S., Nanoparticle
characterization: what to measure?, Advanced Materials, 31(2019) 1901556. DOI: 10.1002/adma.201901556
Mogyorósi K., Dékány I., Fendler J.H., Preparation and characterization of clay mineral intercalated titanium dioxide
nanoparticles, Langmuir, 19 (2003) 2938–2946. DOI:
10.1021/la025969a
Mokari T., Rothenberg E., Popov I., Costi R., Banin U., Selective
growth of metal tips onto semiconductor quantum rods andtetrapods, Science, 304 (2004) 1787–1790. DOI: 10.1126/
science.1097830

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Montaño M.D., Olesik J.W., Barber A.G., Challis K., Ranville
J.F., Single particle ICP-MS: advances toward routine analysis of nanomaterials, Analytical and Bioanalytical Chemistry,
408 (2016) 5053–5074. DOI: 10.1007/s00216-016-9676-8
Motl N.E., Ewusi-Annan E., Sines I.T., Jensen L., Schaak R.E.,
Au–Cu alloy nanoparticles with tunable compositions andplasmonic properties: experimental determination of composition and correlation with theory, The Journal of Physical
Chemistry C, 114 (2010) 19263–19269. DOI: 10.1021/
jp107637j
Mozhayeva D., Engelhard C., A critical review of single particle
inductively coupled plasma mass spectrometry—a step
towards an ideal method for nanomaterial characterization,
Journal of Analytical Atomic Spectrometry, 35 (2020)
1740–1783. DOI: 10.1039/c9ja00206e
Müller-Buschbaum P., A basic introduction to grazing incidence
small-angle X-ray scattering, in: Gomez M., Nogales A.,
Garcia-Gutierrez M.C., Ezquerra T.A. (Eds.), Applicationsof Synchrotron Light to Scattering and Diffraction in Materials and Life Sciences, Springer Berlin Heidelberg, 2009,
pp.61–89, ISBN: 978-3-540-95968-7. DOI: 10.1007/978-3540-95968-7_3
Murphy R.P., Hong K., Wagner N.J., Synthetic control of thesize, shape, and polydispersity of anisotropic silica colloids,
Journal of Colloid and Interface Science, 501 (2017) 45–53.
DOI: 10.1016/j.jcis.2017.04.026
Murthy S.K., Nanoparticles in modern medicine: state of the art
and future challenges, International Journal of Nanomedicine, 2 (2007) 129–141.
Nacken T., Damm C., Xing H., Rüger A., Peukert W., Determination of quantitative structure-property and structure-process
relationships for graphene production in water, Nano
Research, 8 (2015) 1865–1881. DOI: 10.1007/s12274-0140694-6
Nacken T.J., Damm C., Walter J., Rüger A., Peukert W.,
Delamination of graphite in a high pressure homogenizer,
RSC Advances, 5 (2015) 57328–57338. DOI: 10.1039/
c5ra08643d
Navrotsky A., Energetics of nanoparticle oxides: interplay
between surface energy and polymorphism, Geochemical
Transactions, 4 (2003) 34–37. DOI: 10.1039/b308711e
Neeleshwar S., Chen C.L., Tsai C.B., Chen Y.Y., Chen C.C.,
Shyu S.G., Seehra M.S., Size-dependent properties of CdSequantum dots, Physical Review B, 71 (2005) 201307. DOI:
10.1103/PhysRevB.71.201307
Ngo T.D., Kashani A., Imbalzano G., Nguyen K.T.Q., Hui D.,
Additive manufacturing (3D printing): A review of materials,
methods, applications and challenges, Composites Part B:
Engineering, 143 (2018) 172–196. DOI: 10.1016/j.compositesb.2018.02.012
Noble C.A., Prather K.A., Real-time single particle mass spectrometry: a historical review of a quarter century of the chemical
analysis of aerosols, Mass Spectrometry Reviews, 19 (2000)
248–274. DOI: 10.1002/1098-2787(200007)19:4<248::AIDMAS3>3.0.CO;2-I
Nontapot K., Rastogi V., Fagan J.A., Reipa V., Size and density
measurement of core-shell Si nanoparticles by analyticalultracentrifugation, Nanotechnology, 24 (2013) 155701.
DOI: 10.1088/0957-4484/24/15/155701
Novoselov K.S., Nobel lecture: graphene: materials in the flatland, Reviews of Modern Physics, 83 (2011) 837–849. DOI:
10.1103/RevModPhys.83.837
O’Brien R.W., Electro-acoustic effects in a dilute suspension of
spherical particles, Journal of Fluid Mechanics, 190 (1988)
71–86. DOI: 10.1017/S0022112088001211

Olson J., Dominguez-Medina S., Hoggard A., Wang L.-Y., Chang
W.-S., Link S., Optical characterization of single plasmonic
nanoparticles, Chemical Society Reviews, 44 (2015) 40–57.
DOI: 10.1039/c4cs00131a
Pace H.E., Rogers N.J., Jarolimek C., Coleman V.A., Higgins
C.P., Ranville J.F., Determining transport efficiency forthe purpose of counting and sizing nanoparticles via single
particle inductively coupled plasma mass spectrometry,
Analytical Chemistry, 83 (2011) 9361–9369. DOI: 10.1021/
ac201952t
Park J., Elmlund H., Ercius P., Yuk J.M., Limmer D.T., Chen
Q., Kim K., Han S.H., Weitz D.A., Zettl A., Alivisatos A.P.,
Nanoparticle imaging. 3D structure of individual nanocrystals in solution by electron microscopy, Science, 349 (2015)
290–295. DOI: 10.1126/science.aab1343
Parteli E.J.R., Pöschel T., Particle-based simulation of powder
application in additive manufacturing, Powder Technology,
288 (2016) 96–102. DOI: 10.1016/j.powtec.2015.10.035
Paul J., Romeis S., Herre P., Peukert W., Deformation behaviorof micron-sized polycrystalline gold particles studied by insitu compression experiments and frictional finite element
simulation, Powder Technology, 286 (2015a) 706–715. DOI:
10.1016/j.powtec.2015.09.020
Paul J., Romeis S., Mačković M., Marthala V.R.R., Herre P.,
Przybilla T., Hartmann M., Spiecker E., Schmidt J., Peukert
W., In situ cracking of silica beads in the SEM and TEM—
Effect of particle size on structure–property correlations,
Powder Technology, 270 (2015b) 337–347. DOI: 10.1016/j.
powtec.2014.10.026
Pearson J., Walter J., Peukert W., Cölfen H., Advanced multiwavelength detection in analytical ultracentrifugation,
Analytical Chemistry, 90 (2018) 1280–1291. DOI: 10.1021/
acs.analchem.7b04056
Planken K.L., Cölfen H., Analytical ultracentrifugation ofcolloids, Nanoscale, 2 (2010) 1849–1869. DOI: 10.1039/
c0nr00215a
Polavarapu L., Liz-Marzán L.M., Towards low-cost flexible
substrates for nanoplasmonic sensing, Physical Chemistry
Chemical Physics: PCCP, 15 (2013) 5288–5300. DOI:
10.1039/c2cp43642f
Przybilla T., Zubiri B.A., Beltrán A.M., Butz B., Machoke
A.G.F., Inayat A., Distaso M., Peukert W., Schwieger W.,
Spiecker E., Transfer of individual micro- and nanoparticles
for high-precision 3D analysis using 360° electron tomography, Small Methods, 2 (2018) 1700276. DOI: 10.1002/
smtd.201700276
Raper J.A., Amal R., Measurement of aggregate fractal dimensions using static light scattering, Particle & Particle Systems
Characterization, 10 (1993) 239–245. DOI: 10.1002/
ppsc.19930100505
Rasteiro M.G., Garcia F.A.P., Ferreira P., Blanco A., Negro C.,
Antunes E., The use of LDS as a tool to evaluate flocculation
mechanisms, Chemical Engineering and Processing: Process
Intensification, 47 (2008) 1323–1332. DOI: 10.1016/j.
cep.2007.04.009
Renaud G., Lazzari R., Leroy F., Probing surface and interface
morphology with grazing incidence small angle X-ray scattering, Surface Science Reports, 64 (2009) 255–380. DOI:
10.1016/j.surfrep.2009.07.002
Rey M., Uttinger M.J., Peukert W., Walter J., Vogel N., Probing
particle heteroaggregation using analytical centrifugation, Soft Matter, 16 (2020) 3407–3415. DOI: 10.1039/
d0sm00026d
Rice S.B., Chan C., Brown S.C., Eschbach P., Han L., Ensor D.S.,
Stefaniak A.B., Bonevich J., Vladár A.E., Hight Walker A.R.,

25

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Zheng J., Starnes C., Stromberg A., Ye J., Grulke E.A., Particle size distributions by transmission electron microscopy: aninterlaboratory comparison case study, Metrologia, 50 (2013)
663–678. DOI: 10.1088/0026-1394/50/6/663
Richter A., Babick F., Ripperger S., Polydisperse particle size
characterization by ultrasonic attenuation spectroscopy forsystems of diverse acoustic contrast in the large particle limit,
The Journal of the Acoustical Society of America, 118 (2005)
1394–1405. DOI: 10.1121/1.2000773
Riebel U., Löffler F., The fundamentals of particle size analysis
by means of ultrasonic spectrometry, Particle & Particle
Systems Characterization, 6 (1989) 135–143. DOI: 10.1002/
ppsc.19890060124
Romeis S., Paul J., Ziener M., Peukert W., A novel apparatus forin situ compression of submicron structures and particles in ahigh resolution SEM, The Review of Scientific Instruments,
83 (2012) 095105. DOI: 10.1063/1.4749256
Roth W.J., Nachtigall P., Morris R.E., Wheatley P.S., Seymour
V.R., Ashbrook S.E., Chlubná P., Grajciar L., Položij M.,
Zukal A., Shvets O., Cejka J., A family of zeolites with controlled pore size prepared using a top-down method, Nature
Chemistry, 5 (2013) 628–633. DOI: 10.1038/nchem.1662
Rumpf H., Über die Eigenschaften von Nutzstäuben, Staub-Reinhalt der Luft, 27 (1967) 3–13.
Schach E., Buchmann M., Tolosana-Delgado R., Leißner T., Kern
M., van den Gerald Boogaart K., Rudolph M., Peuker U.A.,
Multidimensional characterization of separation processes—
Part 1: Introducing kernel methods and entropy in the context
of mineral processing using SEM-based image analysis,
Minerals Engineering, 137 (2019) 78–86. DOI: 10.1016/j.
mineng.2019.03.026
Scheckman J.H., McMurry P.H., Pratsinis S.E., Rapid characterization of agglomerate aerosols by in situ mass-mobility
measurements, Langmuir, 25 (2009) 8248–8254. DOI:
10.1021/la900441e
Schindler T., Walter J., Peukert W., Segets D., Unruh T., In
situ study on the evolution of multimodal particle size
distributions of ZnO quantum dots: some general rules forthe occurrence of multimodalities, The Journal of Physical
Chemistry B, 119 (2015) 15370–15380. DOI: 10.1021/acs.
jpcb.5b08005
Schleicher B., Künzel S., Burtscher H., Insitu measurementof size and density of submicron aerosol particles,
Journal of Applied Physics, 78 (1995) 4416–4422. DOI:
10.1063/1.359849
Schmid M., Häusele B., Junk M., Brookes E., Frank J., Cölfen H.,
High-resolution asymmetrical flow field-flow fractionation
data evaluation via Richardson-Lucy-based fractogram correction, Analytical Chemistry, 90 (2018) 13978–13986. DOI:
10.1021/acs.analchem.8b03483
Schmidt J., Sachs M., Blümel C., Winzer B., Toni F., Wirth K.-E.,
Peukert W., A novel process route for the production of
spherical LBM polymer powders with small size and goodflowability, Powder Technology, 261 (2014) 78–86. DOI:
10.1016/j.powtec.2014.04.003
Schorsch S., Ochsenbein D.R., Vetter T., Morari M., Mazzotti
M., High accuracy online measurement of multidimensional
particle size distributions during crystallization, Chemical
Engineering Science, 105 (2014) 155–168. DOI: 10.1016/j.
ces.2013.11.003
Sharma A., Singh A.P., Thakur P., Brookes N.B., Kumar S., Lee
C.G., Choudhary R.J., Verma K.D., Kumar R., Structural,electronic, and magnetic properties of Co doped SnO2
nanoparticles, Journal of Applied Physics, 107 (2010) 93918.
DOI: 10.1063/1.3415541

26

Shin W.G., Mulholland G.W., Pui D.Y.H., Determination of
volume, scaling exponents, and particle alignment of
nanoparticle agglomerates using tandem differential mobility
analyzers, Journal of Aerosol Science, 41 (2010) 665–681.
DOI: 10.1016/j.jaerosci.2010.04.009
Siedentopf H., Zsigmondy R., Uber Sichtbarmachung undGrößenbestimmung ultramikoskopischer Teilchen, mit
besonderer Anwendung auf Goldrubingläser, Annalen der
Physik, 315 (1902) 1–39. DOI: 10.1002/andp.19023150102
So D., Pradhan S., Konstantatos G., Solid-state colloidal CuInS2
quantum dot solar cells enabled by bulk heterojunctions,
Nanoscale, 8 (2016) 16776–16785. DOI: 10.1039/
c6nr05563j
Song H., Yang Y., Geng J., Gu Z., Zou J., Yu C., Electron tomography: a unique tool solving intricate hollow nanostructures,
Advanced Materials, 31 (2019) 1801564. DOI: 10.1002/
adma.201801564
Sorensen C.M., Light scattering by fractal aggregates: a review,
Aerosol Science and Technology, 35 (2001) 648–687. DOI:
10.1080/02786820117868
Sorensen C.M., Yon J., Liu F., Maughan J., Heinson W.R., Berg
M.J., Light scattering and absorption by fractal aggregates
including soot, Journal of Quantitative Spectroscopy andRadiative Transfer, 217 (2018) 459–473. DOI: 10.1016/j.
jqsrt.2018.05.016
Soto-Cantu E., Cueto R., Koch J., Russo P.S., Synthesis and rapid
characterization of amine-functionalized silica, Langmuir, 28(2012) 5562–5569. DOI: 10.1021/la204981b
Stenger F., Mende S., Schwedes J., Peukert W., Nanomillingin stirred media mills, Chemical Engineering Science, 60(2005) 4557–4565. DOI: 10.1016/j.ces.2005.02.057
Stieß M., Mechanische Verfahrenstechnik 1, Zweite, neubearbeitete Auflage, Springer Berlin Heidelberg, Berlin, Heidelberg,
1995.
Strunz P., Mukherji D., Pigozzi G., Gilles R., Geue T., Pranzas K.,
Characterization of core-shell nanoparticles by small angle
neutron scattering, Applied Physics A, 88 (2007) 277–284.
DOI: 10.1007/s00339-007-4008-7
Sun J., Simon S.L., The melting behavior of aluminum nanoparticles, Thermochimica Acta, 463 (2007) 32–40. DOI:
10.1016/j.tca.2007.07.007
Sun Y., Cai Z., Fu J., Particle morphomics by high-throughput
dynamic image analysis, Scientific Reports, 9 (2019) 9591.
DOI: 10.1038/s41598-019-46062-6
Sympatec, Dynamic Image Analysis <www.sympatec.com/en/
particle-measurement/sensors/dynamic-image-analysis/>accessed 02.02.2021.
Tahara T., Quan X., Otani R., Takaki Y., Matoba O., Digitalholography and its multidimensional imaging applications: areview, Microscopy, 67 (2018) 55–67. DOI: 10.1093/jmicro/
dfy007
Tanaka M., Komagata M., Tsukada M., Kamiya H., Fractal analysis of the influence of surface roughness of toner particles
on their flow properties and adhesion behavior, Powder Technology, 186 (2008) 1–8. DOI: 10.1016/j.powtec.2007.10.030
Thajudeen T., Walter J., Srikantharajah R., Lübbert C., Peukert
W., Determination of the length and diameter of nanorods
by a combination of analytical ultracentrifugation and scanning mobility particle sizer, Nanoscale Horizons, 2 (2017)
253–260. DOI: 10.1039/c7nh00050b
Theerthagiri J., Senthil R.A., Senthilkumar B., Reddy Polu A.,
Madhavan J., Ashokkumar M., Recent advances in MoS2
nanostructured materials for energy and environmental
applications—A review, Journal of Solid State Chemistry,
252 (2017) 43–71. DOI: 10.1016/j.jssc.2017.04.041

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Tsai D.-H., DelRio F.W., Pettibone J.M., Lin P.-A., Tan J., Zachariah M.R., Hackley V.A., Temperature-programmed electrospray-differential mobility analysis for characterization ofligated nanoparticles in complex media, Langmuir, 29 (2013)
11267–11274. DOI: 10.1021/la402311c
Uchiyama S., Arisaka F., Stafford W.F., Laue T.M., (Eds.),
Analytical Ultracentrifugation Instrumentation, Software,and Applications, Springer Japan, Tokyo, 2016, ISBN: 9784-431-55983-2. DOI: 10.1007/978-4-431-55985-6
Uttinger M.J., Boldt S., Wawra S.E., Freiwald T.D., Damm
C., Walter J., Lerche D., Peukert W., New prospects forparticle characterization using analytical centrifugation
with sector-shaped centerpieces, Particle & Particle Systems Characterization, 37 (2020) 2000108. DOI: 10.1002/
ppsc.202000108
Verleysen E., Wagner T., Lipinski H.-G., Kägi R., Koeber R.,
Boix-Sanfeliu A., De Temmerman P.-J., Mast J., Evaluationof a TEM based Approach for Size Measurement of Particulate (Nano)materials, Materials, 12 (2019) 2274. DOI:
10.3390/ma12142274
Voigtländer B., Atomic Force Microscopy, 2nd ed. Springer,
Cham, Switzerland, 2019. ISBN: 978-3-030-13653-6. DOI:
10.1007/978-3-030-13654-3
Walter J., Löhr K., Karabudak E., Reis W., Mikhael J., Peukert
W., Wohlleben W., Cölfen H., Multidimensional analysis
of nanoparticles with highly disperse properties using
multiwavelength analytical ultracentrifugation, ACS Nano, 8(2014) 8871–8886. DOI: 10.1021/nn503205k
Walter J., Thajudeen T., Süss S., Segets D., Peukert W., New
possibilities of accurate particle characterisation by applying direct boundary models to analytical centrifugation,
Nanoscale, 7 (2015) 6574–6587. DOI: 10.1039/c5nr00995b
Wang J., Mbah C.F., Przybilla T., Apeleo Zubiri B., Spiecker
E., Engel M., Vogel N., Magic number colloidal clusters as
minimum free energy structures, Nature Communications, 9(2018) 5259. DOI: 10.1038/s41467-018-07600-4
Wang T.C., Bury W., Gómez-Gualdrón D.A., Vermeulen N.A.,
Mondloch J.E., Deria P., Zhang K., Moghadam P.Z., SarjeantA.A., Snurr R.Q., Stoddart J.F., Hupp J.T., Farha O.K.,
Ultrahigh surface area zirconium MOFs and insights into
the applicability of the BET theory, Journal of the American
Chemical Society, 137 (2015) 3585–3591. DOI: 10.1021/
ja512973b
Wang Y., Yang X., Liu W., Zhang F., Cai Q., Deng X.,
Controlled release behaviour of protein-loaded microparticles prepared via coaxial or emulsion electrospray,
Journal of Microencapsulation, 30 (2013) 490–497. DOI:
10.3109/02652048.2012.752537
Wawra S.E., Onishchukov G., Maranska M., Eigler S., Walter
J., Peukert W., A multiwavelength emission detector for
analytical ultracentrifugation, Nanoscale Advances, 1 (2019)4422–4432. DOI: 10.1039/C9NA00487D
Wawra S.E., Pflug L., Thajudeen T., Kryschi C., Stingl M.,
Peukert W., Determination of the two-dimensional distributions of gold nanorods by multiwavelength analyticalultracentrifugation, Nature Communications, 9 (2018) 4898.
DOI: 10.1038/s41467-018-07366-9
Waychunas G.A., Zhang H., Structure, chemistry, and propertiesof mineral nanoparticles, Elements, 4 (2008) 381–387. DOI:
10.2113/gselements.4.6.381
Weber A.P., Baltensperger U., Gäggeler H.W., Tobler L., Keil R.,
Schmidt-Ott A., Simultaneous in-situ measurements of mass,
surface and mobilitydiameter of silver agglomerates, Journalof Aerosol Science, 22 (1991) S257–S260. DOI: 10.1016/
S0021-8502(05)80084-9
Wessells C.D., McDowell M.T., Peddada S.V., Pasta M., Huggins
R.A., Cui Y., Tunable reaction potentials in open framework
nanoparticle battery electrodes for grid-scale energy storage,
ACS Nano, 6 (2012) 1688–1694. DOI: 10.1021/nn204666v
Willets K.A., Wilson A.J., Sundaresan V., Joshi P.B., Superresolution imaging and plasmonics, Chemical Reviews, 117(2017) 7538–7582. DOI: 10.1021/acs.chemrev.6b00547
Wu Z.J., Poulain L., Henning S., Dieckmann K., Birmili W.,
Merkel M., van Pinxteren D., Spindler G., Müller K.,
Stratmann F., Herrmann H., Wiedensohler A., Relating
particle hygroscopicity and CCN activity to chemical composition during the HCCT-2010 field campaign, Atmospheric
Chemistry and Physics, 13 (2013) 7983–7996. DOI: 10.5194/
acp-13-7983-2013
Xu R., Light scattering: a review of particle characterization
applications, Particuology, 18 (2015) 11–21. DOI: 10.1016/j.
partic.2014.05.002
Yan J., Teo B.K., Zheng N., Surface chemistry of atomically
precise coinage-metal nanoclusters: from structural control
to surface reactivity and catalysis, Accounts of Chemical
Research, 51 (2018) 3084–3093. DOI: 10.1021/acs.
accounts.8b00371
Yao Y., Lenhoff A.M., Determination of pore size distributions ofporous chromatographic adsorbents by inverse size-exclusion chromatography, Journal of Chromatography A, 1037
(2004) 273–282. DOI: 10.1016/j.chroma.2004.02.054
Yu R., Liz-Marzán L.M., García de Abajo F.J., Universal analytical modeling of plasmonic nanoparticles, Chemical Society
Reviews, 46 (2017) 6710–6724. DOI: 10.1039/c6cs00919k
Zhang L., Blom D.A., Wang H., Au–Cu2O core–shell nanoparticles: a hybrid metal-semiconductor heteronanostructurewith geometrically tunable optical properties, Chemistry ofMaterials, 23 (2011) 4587–4598. DOI: 10.1021/cm202078t
Zhang W., Ge Q., Wang L., Structure effects on the energetic,
electronic, and magnetic properties of palladium nanoparticles, The Journal of Chemical Physics, 118 (2003)
5793–5801. DOI: 10.1063/1.1557179
Zhong L., Fu S., Peng X., Zhan H., Sun R., Colloidal stabilityof negatively charged cellulose nanocrystalline in aqueous
systems, Carbohydrate Polymers, 90 (2012) 644–649. DOI:
10.1016/j.carbpol.2012.05.091
Zhu M., Lin Y., Lo E.W.C., Wang Q., Zhao Z., Xie W., Electronic
and magnetic properties of La2NiMnO6 and La2CoMnO6
with cationic ordering, Applied Physics Letters, 100 (2012)
062406. DOI: 10.1063/1.3683550
Zhuang T.-T., Li Y., Gao X., Wei M., García de Arquer F.P.,
Todorović P., Tian J., Li G., Zhang C., Li X., Dong L., SongY., Lu Y., Yang X., Zhang L., Fan F., Kelley S.O., Yu S.-H.,
Tang Z., Sargent E.H., Regioselective magnetization in semiconducting nanorods, Nature Nanotechnology, 15 (2020)
192–197. DOI: 10.1038/s41565-019-0606-827

Uwe Frank et al. / KONA Powder and Particle Journal No. 39 (2022) 3–28

Authors’ Short Biographies
Uwe Frank
Uwe Frank obtained his Bachelor and Master degrees in physics at the Friedrich Alexander
University Erlangen-Nürnberg. Now he is a doctoral researcher at the Institute of Particle Technology
in the group of Wolfgang Peukert. His main research fields contain the multidimensional characterization of anisotropic particle systems, the fundamentals of multidimensional particle technology andanalytical ultracentrifugation.

Maximilian J. Uttinger
Maximilian J. Uttinger received his Bachelor degree in Chemical Engineering from FriedrichAlexander University Erlangen-Nürnberg in 2014. Afterwards, Maximilian received his Master degree in Advanced Materials and Processes from Friedrich-Alexander University Erlangen-Nürnberg
in 2017. Currently, he is a doctoral researcher at the Institute of Particle Technology in the group of
Wolfgang Peukert. His research interest is on Analytical Ultracentrifugation and Analytical Centrifugation with a focus on non-ideal sedimentation behavior.

Simon E. Wawra
Simon Wawra received his Bachelor of Science degree in physics from the University of Bayreuthin 2013 and his Master of Science degree in physics from the Technical University of Dresden in2015. Currently, Simon is a doctoral researcher at the Institute of Particle Technology in the groupof Wolfgang Peukert. Simon’s main research topic is the simultaneous hydrodynamic and opticalcharacterization of nanoparticles using analytical ultracentrifugation.

Christian Lübbert
Dr.-Ing. Christian Lübbert received his Diploma in chemical engineering and environmental
technology at the University of Cottbus (BTU Cottbus). He received his doctor’s degree at the chairof Particle Technology (BTU Cottbus). Currently, he is working in Wolfgang Peukert’s group at theInstitute of Particle Technology (Friedrich-Alexander University Erlangen-Nürnberg). His work is
focussed on electrosprays, mobility classified mass spectrometry and electrostatics effects in particle
systems.

Wolfgang Peukert
Wolfgang Peukert studied Chemical Engineering at the University Karlsruhe, where he obtained
his Dr-Ing. He was research engineer at Hosokawa Micron, Japan, R&D director of Hosokawa
MikroPul, Cologne and board member of Hosokawa Int., New York. From 1998 until 2003 he helda full professorship at the Technical University of Munich. Since 2003 Wolfgang Peukert is the headof the institute of Particle Technology (LFG) at the Friedrich-Alexander University of ErlangenNuremberg. His research interests are widespread in Particle Technology with emphasis on nanoparticle technology, product design and formulation technology, interface science and engineering.

28

KONA Powder and Particle Journal No. 39 (2022) 29–44/https://doi.org/10.14356/kona.2022008

Review Paper

The Sevilla Powder Tester: A Tool for Measuring the Flow
Properties of Cohesive Powders at High Temperatures †Rahma Gannoun, José Manuel Pérez Ebrí, Alberto T. Pérez and José Manuel Valverde *Facultad de Física, Universidad de Sevilla, Spain

Abstract
Understanding the flowability of cohesive powders at high temperature is of great importance for many industrial
applications where these materials are handled at harsh thermal conditions. For instance, the Calcium-Looping(CaL) process, involving the transport, storage and fluidization of limestone powders at high temperature, is being
considered nowadays as a promising technology for thermochemical energy storage (TCES) in concentrated
solar power plants (CSP). In this context, the High Temperature Seville Powder Tester (HTSPT) is presented inthis work as a useful tool to analyze how the flow behavior of cohesive powders changes with temperature. The
manuscript reviews the main results obtained so far using this novel apparatus. The change of powder cohesivenessand therefore of powder flowability as depending on temperature, particle size, material properties and nanosilica
surface coating is illustrated.
Keywords: calcium looping (CaL), HTSPT, flowability, thermochemical energy storage (TCES), fluidization

1. Introduction
The calcium looping (CaL) process has been widely
investigated as a 2nd generation technology to capture CO2from fossil fuel power plants with already proven high efficiency in large scale pilot plants (1–2 MWh) (Barker, 1974;
Blamey et al., 2010; Chacartegui et al., 2016; Kierzkowska
et al., 2013; Prieto et al., 2016; Valverde, 2013). The CaL
technology benefits from the abundance, low price and lackof toxicity of natural CaO precursors such as limestone
and dolomite that can be used as raw material. Basically,
the CaL process relies on the reversible calcination/
carbonation reaction
CaCO3 (s)  CaO (s) + CO2 (g)H r0  178 kJ/mol(1)

During the exothermic carbonation reaction, solid CaO
particles
react in a fluidized bed reactor at approximately(1)
650 °C with the flue gas containing a small concentrationof CO2 (around 15 % vol). The carbonated particles arethen taken to a fluidized bed calciner where the endothermic decomposition of CaCO3 takes place to regenerate the
CaO at temperatures above 900 °C in a high CO2 concen†*

Received 10 March 2021; Accepted 11 May 2021
J-STAGE Advance published online 26 June 2021
Corresponding author: José Manuel Valverde;
Add: Avenida Reina Mercedes s/n, 41012 Sevilla, Spain
E-mail: jmillan@us.es
TEL: +34-954550960

tration environment (Valverde, 2013; 2015). More recently,
the CaL process has been the subject of several studies
to store energy in concentrated solar power (CSP) plants(Chacartegui et al., 2016; Paksoy, 2007; Pardo et al., 2014).
Currently, small scale pilot plants are under development
showing promising results (Cordis, 2020).
Due to the growing need to employ green renewableenergy, the massive deployment of CSP plants has comeup as an affordable and highly efficient solution for electricity generation at large scale. However, the efficiency of
CSP plants is hindered by the intermittence of solar direct
radiation which leads to an unbalance between electricity
production and demand. Thermal energy storage (TES)
technologies allow releasing thermal energy to generate
electricity when is required by means of heat storage
materials, thus solving shortcomings and discontinuity
issues. A major challenge to minimize the cost of CSP withstorage and enhance its efficiency is to select adequate
thermal energy storage system. Based on different factors,
energy storage technologies are classified as sensible heatstorage (SHS), latent heat storage (LHS), and thermochemical energy storage (TCES) (Hall and Hausz, 1979).
Sensible heat storage stores and releases sensible heat bymeans of a change in the temperature of the material used.
Synthetic oils, molten salts, liquid metals and concretes
are the main sensible heat storage materials employable
in CSP. Characterized by their high specific heat capacity,
relatively low cost and acceptable safety, molten salts
are being currently employed in commercial CSP plants(Fernández et al., 2014; Sang et al., 2015; Wu et al., 2017;

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

29

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

Zhang et al., 2013). However, below temperatures around
200 °C, molten salts solidify, which requires keeping thewhole circuit above this melting temperature even during
prolonged periods of absence of solar direct solar radiation.
In addition, above temperatures ~560 °C, molten salts
degrade whereas the temperatures achievable at CSP plants
with tower technology are around 1000 °C. Thus, the useof molten salts for power generation burdens the potential
efficiency of CSP plants for power production. Moreover,molten salts are corrosive particularly at high temperature
which requires the use of special equipment and therefore
leads to high maintenance costs (Dunn et al., 2012; Ortega
et al., 2008).
Latent heat storage or phase-change energy storage isbased on the heat stored and released when the material experiences a phase change (evaporation, melting, crystallization etc.). The choice of phase change materials (PCMs)
intended for TES applications needs to meet some suitablefeatures: kinetic, physical, chemical, thermodynamic and,of course, economic affordability. Solid-liquid PCMs are
the most used ones in research projects under development.
Yet, these materials release low latent heat and only in thelimited range of temperatures wherein phase transition
occurs. In addition some significant drawbacks are theirgenerally low thermal conductivity, phase separation,
expensive maintenance costs, and also low operating temperature ranges (up to ~90 °C) (Herrmann and Kearney,
2002; Pintaldi et al., 2015; Sharma et al., 2009).
In this context, thermochemical energy storage (TCES)
is considered as a promising technology for energy storage
in CSP systems (Abedin, 2011; Cabeza et al., 2012; Paksoy,
2007; Tatsidjodoung et al., 2013), as demonstrated by thegrowing number of reviews published in the last years
on this technology which is currently under development(André et al., 2016; Barker, 1974; Carrillo et al., 2019; Gilet al., 2010; Mahlia et al., 2014; Pardo et al., 2014). TCES
relies on the storage/release of heat via reversible chemical
reactions (Carrillo et al., 2019; Dinçer and Rosen, 2010).
The most relevant advantages of TCES include the possibility of long term heat storage, high stored energy density,
small energy loss and the suitability to operate at very
high temperatures (up to 1000 °C or above (Abedin, 2011;
Cabeza et al., 2012; Tatsidjodoung et al., 2013). Among thediverse options investigated for TCES a major candidate
is the CaL process. Besides of the low cost, abundance
and lack of toxicity of limestone used as raw material, aparticularly relevant advantage of the integration of the
CaL process in CSP plants is that the CaCO3 calcination
temperature fits in the range of temperatures attainable atthe receiver of CSP plants with tower technology (Pinel etal., 2011).
A possible technique for operating the CaL process in
CSP plants is to use fluidized bed reactors albeit othertype of reactors such as falling particle, entrained flow and30

centrifugal particle reactors that might be better integrated
in solar receivers are being investigated (Cordis, 2020;
Esence et al., 2020; Karasavvas et al., 2020; Lisbona etal., 2020; Sarrion et al., 2016; Tesio et al., 2019; 2020),
CaCO3/CaO solids to be employed in the CaL-CSP integration would preferably be in the form of fine powders
to mitigate reaction rate limiting mechanisms such as poreplugging (Benitez-Guerrero et al., 2017) that might hinder
the process at the most favorable operating conditions for
the CaL-CSP integration (Hanak et al., 2015). As it is wellknown from experience, the lack of material flowability
may be a serious issue in industrial applications wherefine powders are employed due to their high cohesiveness,
which can be enhanced even further at high temperatures(Chirone et al., 2020; Lettieri et al., 2000; Macrì et al.,2017; Tomasetta et al., 2011). The Sevilla Powder Tester(SPT) has proven itself as a reliable and accurate device forthe characterization of cohesive powders (Barletta et al.,2019; Castellanos, 2005; Castellanos et al., 2004; Chen etal., 2009; Valverde et al., 2000; Zafar et al., 2015). Recently,
it has been upgraded to be used at high temperatures. The
present manuscript aims to present a detailed descriptionof the so-called High Temperature Sevilla Powder Tester(HTSPT). We review the main results recently obtained bymeans of this novel setup, with a special focus on the effectof temperature on the tensile yield strength of fine powders
as depending on particle size, surface coating and material
properties.

2. A brief critical review on powder
flowability testers
Exhaustive research has been conducted with the aimof exploring relevant techniques to assess the ability of
powders to flow (Schwedes, 2003). Here we summarize
the main methods envisaged from a critical comparative
analysis.
One of these methods, as described in the book of theAmerican Society for Testing and Materials Standards(ASTM, 1978), is based on measuring the time required bya certain amount of powder to discharge through a hopper.
Hall and Cutress (1960) showed that this technique canbe useful for metallic powders. An external energy source
should be provided to enhance the flow for very cohesive
powders, which introduces uncertainty to the results. A
rheometer composed of shear heads, blades and pistons isanother tool to evaluate powder flowability. To measure
the rotational and axial forces, the components of the setup
are rotated and stirred in the axial direction. A detailed
description of the setup can be found in (Freeman, 2004).
The reliability of these testers is somewhat compromised
due to the lack of reproducibility. For instance, the historyof the powder is dependent on the filling procedure, theRahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

applied load, the device used and the working conditions(Castellanos et al., 2004).
At the microscopic level, interparticle contact forces
are ultimately the main drive for powder flowability(Quintanilla et al., 2001a). Thus, the direct measurement ofthese forces is the best method to understand the physicalmechanism that governs powder flow behavior. Shimada
et al. (2002) conceived an instrument to directly measureadhesive contact forces between particles or between aplane surface and a powder sample. This study concernedorganic powders (potato starch, lactose and cornstarch). An
advantage of the device is that it can handle fine and very
cohesive particles (even below 10 μm in size). Thereafter,by means of a camera or microscope, it analyses the adhesion force for a selected individual particle. They compared
the obtained results with those found by another direct
method (the centrifugal method) based also on a postprocess image analysis of powder avalanches in a rotating
drum (Lüddecke et al., 2021; Quintanilla et al., 2001b). The
authors confirmed that both methods agree qualitatively.
Unfortunately, these techniques do not allow to control
the stress state of the powder that greatly impacts thecontact forces (Quintanilla et al., 2001a). In this context,
Quintanilla et al. (2001a) employed an atomic force microscope (AFM) to determine the adhesion force between
irregularly shaped particles of xerographic toners. The load
force previously applied on the individual particles can be
accurately controlled through this technique. Comparing
their findings with the interparticle forces estimated frommeasurements of the bulk stresses in the Seville Powder
Tester (SPT) (Castellanos et al., 2004), they reported an acceptable agreement. However, it should be highlighted thatthe results on the forces directly measured using the AFM
technique showed a large degree of dispersion, which was
attributed to the critical dependence of the adhesion contact forces to the highly variable local surface properties(Castellanos, 2005; Castellanos et al., 2004).
Recently, Marchetti and Hulme-Smith (2021) investigated the flowability of 11 metal powders with different
properties and particle size distributions employing six
different testers. The ability of the powders to flow wasdetermined by means of diverse indicators such as theflow rate, Hausner ratio, basic flowability energy (BFE),
compressibility (CPS), major principal stress (MPS),
angle of internal friction (AIF), flow factor (FF), angleof repose, specific energy (SE), and the unconfined yieldstress (UYS). The interested reader could find further details about the powder testers and the different parametersin (Marchetti and Hulme-Smith, 2021; Schwedes, 2003;
Castellanos et al., 2004; Lettieri and Macrì, 2016).
Marchetti and Hulme-Smith (2021) demonstrated theexistence of correlations between these different parameters to characterize powder flow. They reported that,for cohesive powders, the Hall and Carney funnels areblocked, while the flowability indicator for these devices isthe flow rate. Consequently, they are not appropriate in thiscase. Indeed, thanks to their simplicity, the tests based on
fundamental properties (all the mentioned tests except for
the rheometer with shear cell device) are widely employed
in industrial and academic fields. However, the insufficient
reproducibility represents a serious drawback (Ghadiri etal., 2020; Santomaso et al., 2003).
The Jenike shear cell is one of the most commonly usedtesters. Firstly developed by Jenike in 1953 (Schwedes,
1976), the powder sample in this test is previously subjected to a controlled consolidation stress. The sample iscontained in a cylindrical cell formed by two superposed
steel rings. Once the normal load is withdrawn, the tester
determines the minimum steady state shear stress that must
be applied to initiate powder flow. However, the Jeniketester is not suitable to evaluate powder flowability at verysmall consolidations (typically below 1 kPa). Besides, thistechnique assumes that the powder shears in a horizontal
slip plane homogeneously across the sample, which is
uncertain (Svarovsky, 1987).
The Peschl shear cell (Barletta et al., 2005; 2007; Bruni
et al., 2007a; 2007b) was presented as an alternative to circumvent some of the above mentioned problems. The tester
is essentially based on the same technic as the previously
cited cells albeit the shear stress is exerted by the rotationof the upper part of the annular shear cell containing thepowder sample (Svarovsky, 1987). This tester allows
to determine the powder flow for an unrestrained shear
distance and for a constant shear surface. Nevertheless,non-negligible wall effects and non-uniformity of stress
distribution may give rise to strong uncertainties(Castellanos et al., 2004).
The above reviewed shear testers are designed to be used
only at ambient temperature. Early works to assess powder
flowability at high temperature were carried out by Smithet al. (1997). These authors employed the Jenike shear
cell to test CaSO4 and MgSO4 powder samples that werepreviously heated (up to 750 °C) although the sample temperature was not controlled during the tests. The authors
demonstrated that the powder yield strength increased withtemperature presumably due to the formation of agglomerates during heating. Kanaoka et al. (2001), Kamiya etal. (2002) and Tsukada et al. (2008) succeeded to control
the temperature during the measurement by placing theshear cell inside a furnace. These authors mainly studied
the adhesion behavior as represented by the variation of theshear yield stress of fly ash particles. Kanaoka et al. (2001)
assumed that the samples behavior followed the Coulomb’s
law to estimate powder cohesion and the angle of internal
friction. In general, they observed an increase in the shear
yield stress with temperature, and therefore of cohesion,
which was attributed to the formation of solid bridges
during heating. Similar observations are reported by31

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

Tsukada et al. (2008), who showed that this phenomenon
can be attenuated by adding coarse silica particles.
More recently some works have modified the standard
Schulze cell in order to study the effect of temperature(Chirone et al., 2015; 2020) (Macrì et al., 2017; Tomasetta
et al., 2011). Further details about these studies will be
discussed in section 5.
Although these tests have shown satisfactory results, assessing powder flowability at high temperature in fluidized
beds would be desirable as this system stands as the mostcommonly used for an adequate temperature control, better
efficiency of heat transfer and gas-solid contact (Ding et al.,2019). All in all, since interparticle forces are very sensitive
to numerous parameters (humidity, temperature, particles’
size and shape, solid mechanical properties, etc.) there
is still a long way to go to fully understand powder flow
behavior. Our HTSPT based on the fluidized bed technique
is presented in detail in the next section as a further contribution to further exploring this critical issue.

3. Experimental setup
Fig. 1 shows a schematic view of the HTSPT used in
the works reviewed in this manuscript. This setup is aimed
to measure the tensile yield strength and porosity of fine
powders as depending on temperature and consolidationstress. It is based on the original SPT originally conceived
by Valverde et al. (2000). Essentially, the equipment isbased on measuring the pressure drop of a controlled gas
flow across the bed. The powder bed is held in a cylindricalquartz vessel of 4.5 cm diameter. A quartz porous plate isplaced at the bottom of the vertical cylinder that serves as
gas distributor. Before entering the bed reactor, the gas
crosses a filter and dryer (model SMC IDFA3E) in orderto get rid of pollutant particles or humidity that can modify
particle surface properties and therefore powder cohesion

Fig. 132(Schubert, 1984). Then a controlled gas flow is pumped
through the bed by means of a digital mass flow controller(omega model FMA-2606A, 2000 sccm). The gas pressure
drop across the powder is measured by a MKS differential
pressure transducer that generates an analogue signal readable by the computer. The measured pressure drop has twocontributions, the pressure drop across the powder bed andthe pressure drop across the porous plate. Obtaining thepressure drop across the porous plate requires a calibration
procedure which consists of measuring the pressure dropof the plate alone. This pressure is subtracted from thetotal pressure drop to obtain Δp, the actual pressure drop
across the powder bed. The registered pressure drop hasan accuracy of ±5 Pa. A loudspeaker is placed at the top of
the vessel that yields an acoustical excitation of 150 dB at
a frequency of 130 Hz. This high intensity sound field isheld for 5 s during the initialization procedure as explained
below to disrupt any plugs or channels that may formand hinder fluidization, particularly in the case of highlycohesive powders (Valverde, 2013) yields an acousticalexcitation of 150 dB at a frequency of 130 Hz. This highintensity sound field is held for 5 s during the initialization
procedure as explained below to disrupt any plugs or channels that may form and hinder fluidization, particularly inthe case of highly cohesive powders (Valverde, 2013). A
set of valves is used to control the gas flow direction, whenvalves 1 and 3 are open while 2 and 4 are closed the gas
flows upward across the powder bed. This is the operating
mode for breaking and fluidize the bed. On the other hand,in the inverse situation (valves 1 and 3 closed while 2 and4 open) the flow is directed downward, which is used for
bed consolidation. The bed is placed inside a furnace which
serves to put the bed at high temperature.
The fully automated setup starts by a standard initialization procedure during which a sufficiently high gas flowrate drives the bed into the bubbling fluidization regime for
30 s. Fluidization is assisted for the first 5 s by the sound

HTSPT: schematic of the experimental set-up. Reprinted with permission from Ref. (Espin et al., 2020). Copyright: (2020) Elsevier.

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

excitation. Then the gas flow is turned off and the bed isleft to settle for 30 s. This first step is important in order toensure reproducibility of the initial state of the sample. In
the second step the bed is heated by using a PID controller(Eurotherm 3216). When the target temperature is reached,a one-hour thermal stabilization period is set, aiming toguarantee a homogenous temperature distribution within
the sample. Thereafter, the bed is subjected to a gradually
increasing downward gas flow rate (by increments of
5 cm3/min each 3 s) up to reach a target consolidationstress (ranging from the weight per unit area of the bed
up to σc~2 kPa). When the target consolidation stress ismet, the downward directed gas flow rate is maintained for10 s. Then it is decreased progressively until it is stopped.
In the last stage, a gradually increasing upward gas flow
is imposed to put the bed under tension which allows toderive the tensile yield strength of the powder as a functionof temperature and the previously imposed consolidationstress as explained below.
Importantly, in all the tests the height of the bed is kept
below the bed diameter which allows us to dismiss wall
retention effects to calculate the tensile yield stress. This
critical issue is discussed in further detail in Castellanos etal. (2004).

4. Breaking and fluidization curves
The gas pressure drop across the powder bed Δp is madenon-dimensional by the weight per unit area (W) in order tobetter assess when fluidization is reached ( WP  1) which
in turn helps to determine the tensile strength. By plotting
the gas pressure drop through the bed as a function of
the upward directed gas flow rate we obtain the so-called
fluidization curve (Fig. 2). At small gas flow(11)rates, the bed
remains in a solid-like state and Δp increases linearly underFig. 2 Dimensionless pressure drop Δp/W vs the gas flow rate qm
for CaCO3 powder samples (average particle size dp = 88.02 ± 0.7 μm,
T = 500 °C) previously subjected to different consolidation stresses σc
as indicated. Reprinted with permission from Ref. (Espin et al., 2020).
Copyright: (2020) Elsevier.

the effect of frictional resistance through the bed. This
linear behavior conforms to the Carman-Kozeny law at low
Reynolds numbers (Carman, 1997)E
p 

ψ p2d p2η hφqm
ρ S 1  φ 2(2)where E is the empirical Ergun’s constant (taking a typicalvalue between 150 and 180 (Nedderman, 1992), dp standsfor(2)
the average particle diameter, ψp is the sphericity ofthe particle (ratio of the surface area of a sphere with same
volume as the particle to the surface area of the particle), ƞ
is the dynamic viscosity of the gas, ρ alludes to the gas density, h and S are, respectively, the height and cross-sectional
area of the powder bed, φ is the particle volume fraction
and qm is the gas flow rate.
The pressure drop balances the powder weight per unit
area at the so-called minimum fluidization gas flow rate qmf.
At this point, a non-cohesive powder would be fluidized.
However, when interparticle adhesive forces are significant(compared to particle weight), the powder remains in asolid-like state as the gas flow is further increased over qmf.
Then, the gas flow puts the bed under tension while thepressure drop continues to increase linearly. At a criticalgas flow, interparticle adhesive forces are overcome anda sudden break of the powder occurs at the bottom of the
bed while the pressure drop falls abruptly to a level aroundthe powder weight per unit area. The tensile yield strengthof the powder at the bottom of the bed is obtained fromthe overshoot of the gas pressure drop over the weight perunit area σt = Δpmax – W. As the gas flow rate is further
increased over the breaking point, the pressure drop oscillates around the weight per unit area while the powder
enters a heterogeneous fluidization state (see Fig. 2).

5. Effect of temperature
Studying the powder behavior at high temperatures isvery important not only for the CaL process but also formany other industrial applications (hydrocarbons cracking,nuclear and metallurgical industries etc.) (Lettieri P. andMacrì D., 2016) where operating conditions involve thehandling of powders at temperatures much higher thanroom temperature (Kunii D. et al., 1991). Several works
have addressed the effect of temperature on the fluidizationof powders. However, the reported observations on theminimum fluidization velocity are somewhat controversial.
Different correlations have been proposed to predict theeffect of temperature on the minimum fluidization velocity(Lettieri P. and Macrì D., 2016). However, these correlations are not reliable at high temperature. Furthermore,
an extrapolation of the results to the tested conditions isrequired (Valverde et al., 2000; Yang et al., 1985). Somealternatives trying to solve this problem have been

33

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

suggested (Wen and Yu, 1966), yet the evolution of theminimum fluidization velocity and bed voidage εmf withtemperature is still considered as uncertain despite theseveral correlations reported in the literature (Botterill etal., 1982).
In order to check the efficiency and agreement between
the different powder shear testers, Salehi et al. (2017)
compared the results obtained with the Schulze ring shear
tester, the Jenike shear tester and the Brookfield powder
tester (PFT) using three different materials that belong todifferent Jenike powder classes (calcium lactate, calcium
carbonate and dolomitic lime). Their results had shownthat the degree of agreement between the different setups
depends on the nature of powder tested. For instance, fordolomitic lime, the PFT and Schulze tester show a good
agreement while the Jenike tester yielded higher cohesion
values. For calcium lactate material, the Jenike and Schulze
testers yield a considerable increase of the powder cohesion with consolidation stress, however the PFT measures
do not uphold this observation. In all the cases, the Jeniketester give the higher cohesion values. In what concerns
particularly CaCO3 powders, the cohesion determined by
the Schulze tester is typically higher than the estimated by
the other testing devices. It is noteworthy that all the mentioned tests have been performed at ambient temperature
due to technical limitations.
In regards to the assessment of powder flow properties
as affected by temperature, Tomasetta et al. (2011) madesome modifications to the standard annular Schulze shear
cell. However, for small consolidations (typically below~1 kPa), the results are not fully reliable. They attributed
this issue to design problems. For this reason, only tests
at higher consolidation stresses were realized. At highconsolidations they confirmed that temperature (in therange up to 500 °C) does not have a significant impact on
the powder flowability for all the materials tested (FCC
powder, Corundum and fly ashes). Using the same setup,
Chirone et al. (2015) investigated the flow characteristics
at room temperature and at 500 °C of five different ceramic
powders. Their findings show that the powder cohesivenessconsiderably increased with temperature and consolidationstress. However, for the samples with the smallest size,
the powders were already very cohesive, and the effect oftemperature was not significant. For powders of 20–38 μm
particle size, there is an increase of cohesion of about 35 %.
For samples of 63–88 μm particle size and over 88 μm
particle size, a cohesion increase of 35 and 45 % at 500 °C
was noticed.
The results demonstrated also that free flowing powders(63–88 μm and more than 88 μm) turned into easy flowing
at 500 °C as a consequence of the increase in cohesion by
35 and 45 % respectively. In this context, for the same temperature range and using the same setup, Macrì et al. (2017)confirmed these observations but for two different types of34

TiO2 powders (natural and synthetic).
Chirone et al. (2020) studied the flow behavior of
powder samples sieved to obtain a range of particle sizes
covering Group B, A and C of Geldart’s classification attemperatures in the range between 25 °C and 500 °C in aheated fluidized bed. They found that the tensile strengthof the powders was increased with temperature. They
claimed that this behavior was not attributable only to thevariation of interparticle forces with temperature but also
to other factors such as the difference in particle size andbed expansion.
Durán-Olivencia et al. (2020) studied the effect oftemperature on the tensile strength measured for limestone
samples having an average particle size of about 50 μm(details on the powder used are illustrated in Table A1) bymeans of the HTSPT. Their results indicated a considerable
increase of powder cohesiveness as the temperature wasincreased (Figs. 3 and 4). Moreover, the effect of temperature was further enhanced as the consolidation stress towhich the sample was previously subjected was increased.
The obtained results fitted well to the empirical correlation(Fig. 5).
3/2  σ 1/3
σ t  a  bT 3/2  cσ 1/3c  bTc(3)

indicating the existence of a cross effect between temperature(3)and consolidation. Thus, the consolidation stress canbe considered as a promoter of the temperature effect on thetensile strength. The foregoing is of great importance. For
instance, during their storage in CaL-CSP plants, the solids

Fig. 3 Tensile strength measured for a limestone powder as a functionof the temperature for different values of the previously applied consolidation stress σc: the gray highlighted area stands for σc < 1000 Pa,
the red colored curve area represents the tensile strength values forσc ≥ 1000 Pa. Reprinted with permission from Ref. (Durán-Olivencia etal., 2020). Copyright: (2020) Elsevier.

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

Fig. 6 Powder tensile strength σt as a function of the consolidationstress σc previously applied to the powder bed for CaCO3 powder
samples of particle size between 4 μm and 30 μm at room temperature.
Reprinted with permission from Ref. (Espin et al., 2019). Copyright:(2019) Elsevier.
Fig. 4 Tensile strength of a limestone powder measured as a functionof the previously applied consolidation stress for temperatures ranging
between 25 °C and 500 °C. The solid lines represent the best fit to a
power law σt ~ σc 1/3. Reprinted with permission from Ref. (DuránOlivencia et al., 2020). Copyright: (2020) Elsevier.

Fig. 5 3D representation of the tensile strength measured for a limestone powder as a function of consolidation stress and temperature. The
plotted surface shows the cross effect existing between these parameters
3/ 2  σ 1/3
governed by the expression σ t  a  bT 3/ 2  cσ 1/3c  bTc . Thepoints are the experimental measures. Reprinted with permission from
Ref. (Durán-Olivencia F.J. et al., 2020). Copyright: (2020) Elsevier.

[21]
could undergo various working conditions involving highconsolidation stresses (above 1 kPa) and high temperatures(more than 300 °C).

6. Effect of particle size on the powder tensile
strength
Particle size is a major physical property that impacts thecohesive behavior of powders (Macrì et al., 2017; Chirone

et al., 2020; Espin et al., 2019; 2020). As particle size is reduced, the gas-solid contact efficiency is enhanced, which
promotes mass and heat transfer in solid-gas reactors.
However, powder cohesiveness is also promoted, whichhinders powder flowability and fluidizability (Castellanos,2005). Using the SPT, Espin et al. (2019) showed that thetensile strength of limestone powders is notably enhanced
as the average particle size is decreased. Importantly, thelimestone powder samples used in these tests were obtainedby aerodynamic classification yielding a narrow particle
size distribution, which made possible to better analyze therelevant effect of temperature on powder cohesiveness as
depending on particle size. The experiments revealed that
there is a synergetic effect between the consolidation stressto which the powder was previously subjected and particle
size on the increase of the tensile strength. The impactof the consolidation stress on the powder tensile strength
becomes more marked for smaller particle sizes (Fig. 6).
As seen in a previous work, the increase of temperature
promotes further powder cohesiveness. This phenomenon
may turn free flowing powders at ambient conditions into
cohesive as temperature is increased whereas low cohesive
powders may show a very cohesive behavior at high temperatures (Chirone et al., 2020). The effect of temperatureand consolidation stress could be well fitted by a powerlaw σ t  a σ cb where the value of b progressively increased
from 0.3 to 0.9 as the temperature of the powder bed wasincreased in the range from ambient to 500 °C (Fig. 7).
The (12)
results reported by Espin et al. (2020) revealed that
powder flowability is critically influenced by particle size
as depending on temperature. As it is clear from Fig. 7
the impact of temperature on the powder tensile strengthis strongly influenced by particle size. An appreciable
increase of powder cohesiveness was observed when thetemperature exceeded a certain threshold which depends
on particle size at the relatively small consolidations

35

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

tested. For relatively small particles (average particle size
dp = 30 μm) the increase of the tensile strength is appreciable already at temperatures below 100 °C. As particle size
is increased, higher temperatures are required to promote
notably the tensile strength. For instance, the temperaturethreshold that causes a significant effect on the tensile
strength is about 300 °C for the powders with 60 μm and80 μm particle size. This temperature is reduced to 200 °C
when particle size is decreased to 45 μm. These results
show the importance for practical applications of assessing

the impairment of powder flowability with temperature as
depending on particle size and the typical consolidationstresses to which the powders will be subjected during storage and transport. For thermal storage of CaCO3 powders at
industrial scale, consolidation stresses may be well above
1 kPa at temperatures clearly exceeding 300 °C (Valverde,2013; 2015), which implies that powder flowability could
be seriously hindered at the typical temperatures of the CaL
process if fine particles (below ~60 um) are employed.

Fig. 7 Tensile strength σt versus the consolidation stress σc for CaCO3 powders for different temperatures and particle size: (a) dp = 88.2 ± 0.7 μm; (b)dp = 59.3 ± 0.8 μm; (c) dp = 42.5 ± 0.8 μm; and (d) dp = 32 ± 1 μm. The solid lines are the best fits of the equation σ t  a σ cb to the experimental data.
Reprinted with permission from Ref. (Espin et al., 2020). Copyright: (2020) Elsevier.

[22]

Fig. 8 Tensile yield strength σt of diverse powders measured as a function of the previously applied consolidation stress σc and temperature T. (a)CaCO3, (b) soda-lime glass beads and (c) SiC powder samples. The solid lines represent the best fit of a power law to the data σ t = aσcb, with b close tounity. Reprinted with permission from Ref. (Durán-Olivencia et al., 2021).

36

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

7. Effect of material properties
Durán-Olivencia et al. (2021) tested the effect of the increase of temperature on the tensile yield strength for powders of similar particle size (between ~42 μm and ~72 μm)
but of different materials (limestone, soda lime and SiC).
The main results obtained are summarized in Fig. 8. These
measurements revealed that, regardless of the powder
nature, cohesiveness is augmented with temperature. Thiseffect is especially appreciable when the temperature isT ≥ 200 °C for limestone and soda-lime powders, with anegligible difference in the measured σt up to 300 °C for
both materials as it can be clearly observed in Fig. 9. On
the other hand, cohesiveness was promoted further for thesoda-lime powder at higher temperatures. Powder beds
could not be broken when the temperature was above
300 °C, even by the highest gas flow rates achievable in thetest (qmmax = 0.8 g/min), which indicates a great increase of
the powder tensile strength near this temperature. Indeed,at temperatures above 300 °C, soda lime is close to its
glass-transition temperature Tg (Tg ~520 °C) (Gerhard,2017; Varshneya and Mauro, 2019). At this temperature,
the powder transits from pure-solid to rubbery-like. Thischange is accompanied by an appreciable decrease of thematerial hardness and, therefore, a marked increase of thetensile strength according to contact mechanics predictions (Castellanos, 2005). In addition, high consolidationstresses promote further material softening as T approaches
Tg. Fig. 10 shows SEM picture of soda-lime powder samples after being heated up to 500 °C and subjected to a consolidation stress σc = 2 kPa. As may be seen, the particles
have experienced a visible local deformation presumably
due to material softening. Dimples are clearly seen at thesurface of the glass beads which were arguably created atinterparticle contact points during consolidation at hightemperature. In contrast, powder samples of a much hardermaterial (SiC) show values of the tensile strength up to fourtimes smaller than those measured for the CaCO3 powderof similar particle size for given values of the consolidationstress and temperature (Fig. 8). In the case of limestone, nodeformations of the surface of the particles were appreciable after the samples (either silica coated or uncoated) were
subjected to the high temperature fluidization cycles (Espin
et al., 2020). These findings can be qualitatively explainedby the change in the mechanical properties of the material
as affected by temperature, particularly its hardness, which
decreases significantly with temperature (Michel et al.,
2004; Wheeler and Michler, 2013; Zhang et al., 2017)
yielding an increase of the tensile strength as predicted bycontact mechanics (Castellanos, 2005) when the particles
deform plastically at contact points. Another importantparameter to consider in the case of non-glass solids is theTamman temperature TTam which is estimated as half of themelting point and indicates the temperature at which mate-Fig. 9 Comparison of Tensile yield strength σt as a function of the previously applied consolidation stress σc for the different powders tested
at T = 300 °C. Reprinted with permission from Ref. (Durán-Olivencia etal., 2021). Copyright: (2021) Elsevier.

Fig. 10 SEM pictures of soda-lime glass beads after undergoinga consolidation stress of σc ≈ 2000 Pa at a temperature of 500 °C(magnifications: 2500×). The arrow indicates permanent deformations
on the beads surface suffered during consolidation at high T (notobserved in the fresh sample). Reprinted with permission from Ref.
(Durán-Olivencia et al., 2021).

rial deformation starts to be appreciable (Tammann, 1932).
For limestone, this temperature is approximately in thesame order of the highest temperature tested in the works
reviewed in this manuscript (TTam (CaCO3) = 565 °C (Xu etal., 2016)), which would explain the appreciable increasein the tensile strength seen in this case as the material
would soften considerably at temperatures close to TTam
(Fig. 8 (soda-lime particles)). However, in the case of SiC,
the Tamman temperature is very high (TTam ~1238 °C (Xuet al., 2016) ). Thus, the tensile strength measured for thispowder in the range of tested temperatures (below 500 °C)
is increased only slightly and powder flowability is notseriously compromised as is the case for the soda-lime andlimestone powders.

37Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

8. Effect of nanosilica addition
The CaL process involves storing and handling CaCO3/
CaO powders at high temperatures and consolidations(Paksoy, 2007). As it has been shown in the works reviewed above (Durán-Olivencia et al., 2021; Espin et al.,2020), the increase of temperature rises the cohesivenessof the powders which could be a serious restraint to theirflowability. The results shown in Figs. 11 and 12 demonstrate that using nanosilica as additive at small concentrations can be a suitable solution to improve the flowabilityof diverse fine cohesive powders at ambient temperature(Chen et al., 2008; Quintanilla et al., 2006; Ramlakhan etal., 2000; Watson et al., 2001; Yang et al., 2005). Espin etal. (2019) demonstrated that for fine limestone powders
the addition of nanosilica to cohesive limestone powders
contributes to significantly reduce their tensile strength atambient temperature (see Fig. 11). SEM pictures (Fig. 13)
showed that CaCO3 particles were uniformly coated withnanosilica when both powders were physically dry mixed

by a simple procedure in a rotating drum. More recently
Durán-Olivencia et al. (2021) extended this observation toa range of temperatures up to 500 °C. At 500 °C, nanosilica
coating leaded to a reduction of the powder tensile strength
up to half of the value measured for the pure limestone
powder (Fig. 12). Moreover, it was shown that the effectof nanosilica persisted when the sample was subjected torepeated fluidization cycles (see Fig. 13).
Thus, a practical solution for CaL applications wherefine limestone powders are to be employed would be theaddition of nanosilica by small concentrations. Arguably,
the physical mechanism behind this behavior is that thecoating of limestone particles with nanosilica aggregates
would effectively increase the hardness of interparticle
contacts since silica is a much harder material than limestone thus mitigating contact plastic deformation and therefore reducing the increase of interparticle adhesion forces
with consolidation and temperature, which would serveto mitigate the undesirable effect of high temperatures on
powder flowability.

9. Conclusions

Fig. 11 Tensile yield strength as a function of the previously applied
consolidation stress for limestone powder samples (dp ~30 μm) mixed
with nanosilica at different weight concentrations and ambient temperature. The experimental data are fitted to the equation σ t  aσ cb data.
Reprinted with permission from Ref. (Espin et al., 2019). Copyright:(2019) Elsevier.

Nowadays, the deployment at large scale of power plants
based on renewable energies is considered as a worldwidepriority. Several technologies aiming to develop new alternatives based on non-polluting energy resources and using
abundant, cheap and non-toxic materials that allow for a
massive deployment of these technologies are conceived.
In this regard CSP plants with energy storage are gaining
an increasing interest.
However, a high efficiency and low-cost energy storage
technology is still required for CSP plants to be competitive
against fossil fuel-based plants. TCES is one of the mostpromising technologies for this goal, and the CaL process
is a potential candidate to integrate TCES in CSP plants.
Yet, the CaL process requires the handling and transport of[23]

Fig. 12 Measured tensile yield strength σt as a function of the applied consolidation stress σc at different temperatures T for powder samples of (a)pure limestone and (b) limestone mixed with nanosilica (0.83 % by weight). Reprinted with permission from Ref. (Durán-Olivencia et al., 2021).

38

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

Fig. 13 SEM images of different size limestone particles coated with diffrent ratios of nanosilica : (a) dp ≈ 4 μm, 0.38 wt% SiO2 ; (b) dp ≈ 4 μm,
1.88 wt% SiO2 ; (c) dp ≈ 15 μm, 0.1 wt% SiO2 ; (d) dp ≈ 15 μm, 0.5 wt% SiO2 ; (e) dp ≈ 30 μm, 0.07 wt% SiO2 ; (f) dp ≈ 30 μm, 0.25 wt% SiO2. Reprinted
with permission from Ref (Espin et al., 2019). Copyright : (2019) Elsevier.

CaCO3 and CaO powders at high temperatures. This may
be an issue as in many other powder processing industrial
applications where high temperatures are involved. Thus,
understanding the powder behavior at high temperatures is
crucial to improve the efficiency of these processes. In thismanuscript the HTSPT device designed for this purpose ispresented and the main results so far obtained have beenreviewed.
The HTSPT can measure the tensile yield strength of fine
powders as a function of temperature and the previously
applied consolidation stress as depending on temperature.
Generally, the results obtained have shown that powder
cohesiveness is adversely affected at high temperatures as
the consolidation stress is increased. Moreover, particle
size is a critical parameter that determines the effect oftemperature. As particle size is decreased, limestone powders become significantly more cohesive for temperatures
just above 100 °C. Furthermore, for limestone powders
with an average particle size of ~50 μm and below, thetensile yield strength increases significantly because of asynergistic effect of temperature and consolidation stress.
Consolidation of the powders greatly enhances the detrimental effect of temperature on the tensile strength since
plastic deformation at interparticle contacts is promoted bya reduction of the material hardness. For example, the tensile yield stress raises by one order of magnitude at 500 °C
when a limestone powder of particle size around 50 μm is
subjected to a consolidation stress of σc ~2 kPa comparedto the case when no consolidation stress is applied at ambient temperatures. Thus, relative free flowing powders at
ambient temperature may become highly cohesive at hightemperatures, which may pose a serious problem in industrial applications. Some material properties play a relevantrole on the effect of temperature on powder cohesiveness.
Thus, the negative effect of temperature is mitigated in materials with a high Tammann temperature and mechanicalhardness as, for example, SiC powders whose flowability is
not seriously compromised with temperature and would betherefore in this regard an excellent candidate for thermalenergy storage. On the other hand, it has been shown that39

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

surface coating with nanosilica by means of dry physicalmixing, is a practical and efficient solution to lessen theincrease of powder cohesiveness with temperature forlimestone powders.

Acknowledgements
This research was supported by the Spanish Government
Agency “Ministerio de Economía y Competitividad” (grant
number CTQ2017-83602-C2-2-R).

Appendix A
Table A1 Mechanical properties of the material tested, reprinted with permission from Ref. (Espin et al., 2020). Copyright: (2020) Elsevier.

Material

Particle Densityρp (kg/m3)

Average
Diameter dp(μm)

Young’s
Modulus E(GPa)

MechanicalHardness H(GPa)

Poissonratio ν (-)

Surface Energyγ (J/m 2)

CaCO3

2700a

51a

25–88.19b

0.75–5.11c

0.21–0.34d

0.32–0.347e

References: a (data provided by the supplier),b (Crystran, 2020; Daniel et al., 1982; Ghadami Jadval Ghadam, 2015; Gunda and Volinsky, 2011; Gupta, 2010; Lee et al., 2016; Shi et al., 2018;
Surfacenet, 2020)c (Gunda and Volinsky, 2011; Hubermaterials, 2020; Lee et al., 2016; Matweb, 2020; Shi et al., 2018)
d (Daniel et al., 1982; Gunda and Volinsky, 2011; Gupta, 2010; Lomboy et al., 2011; Materialsproject, 2020; Ramlakhan et al., 2000; Upadhyay, 2013)
e (Røyne et al., 2011; Santhanam. and Gupta, 1968)

References
Abedin A., A critical review of thermochemical energy storage
systems, The Open Renewable Energy Journal, 4 (2011)42–46. DOI: 10.2174/1876387101004010042
ASTM (American Society for Testing and Materials), Annual
Book of ASTM Standards, 1978.
André L., Abanades S., Flamant G., Screening of thermochemicalsystems based on solid-gas reversible reactions for hightemperature solar thermal energy storage, Renewable andSustainable Energy Reviews, 64 (2016) 703–715. DOI:
10.1016/j.rser.2016.06.043
Barker R., The reactivity of calcium oxide towards carbon dioxide
and its use for energy storage, Journal of Applied Chemistry
and Biotechnology, 24 (1974) 221–227. DOI: 10.1002/jctb.
2720240405
Barletta D., Donsì G., Ferrari G., Poletto M., Aerated flow of finecohesive powders in a Peschl shear cell, Powders and Grains
2005—Proceedings of the 5th International Conference on
Micromechanics of Granular Media, 2 (2005) 1033–1037.
Barletta D., Donsì G., Ferrari G., Poletto M., A rotational tester
for the characterization of aerated shear flow of powders,Particle & Particle Systems Characterization, 24 (2007)
259–270. DOI: 10.1002/ppsc.200701115
Barletta D., Poletto M., Santomaso A.C., Chapter 4 bulk
powder flow characterisation techniques, in: Hassanpour
A., Hare C., Pasha M. (Eds.), Powder Flow: Theory,
Characterisation and Application, The Royal Society ofChemistry, 2019, pp. 64–146, ISBN: 978-1-78801-224-9.
DOI: 10.1039/9781788016100-00064
Benitez-Guerrero M., Sarrion B., Perejon A., Sanchez-Jimenez
P.E., Perez-Maqueda L.A., Manuel Valverde J., Large-scale
high-temperature solar energy storage using natural minerals,
Solar Energy Materials and Solar Cells, 168 (2017) 14–21.
DOI: 10.1016/j.solmat.2017.04.013
Blamey J., Anthony E.J., Wang J., Fennell P.S., The calcium looping cycle for large-scale CO2 capture, Progress in Energy andCombustion Science, 36 (2010) 260–279. DOI: 10.1016/j.
pecs.2009.10.001
Botterill J.S.M., Teoman Y., Yüregir K.R., The effect of operating

40

temperature on the velocity of minimum fluidization, bed
voidage and general behavior, Powder Technology, 31 (1982)
101–110. DOI: 10.1016/0032-5910(82)80009-0
Bruni G., Barletta D., Poletto M., Lettieri P., A rheologicalmodel for the flowability of aerated fine powders, Chemical
Engineering Science, 62 (2007a) 397–407. DOI: 10.1016/j.
ces.2006.08.060
Bruni G., Lettieri P., Newton D., Barletta D., An investigationof the effect of the interparticle forces on the fluidization
behaviour of fine powders linked with rheological studies,
Chemical Engineering Science, 62 (2007b) 387–396. DOI:
10.1016/j.ces.2006.08.059
Cabeza L.F., Sole C., Castell A., Oro E., Gil A., Review of solar
thermal storage techniques and associated heat transfer
technologies, Proceedings of the IEEE, 100 (2012) 525–538.
DOI: 10.1109/jproc.2011.2157883
Carman P.C., Fluid flow through granular beds, Chemical Engineering Research and Design, 75 (1997) S32–S48. DOI:
10.1016/s0263-8762(97)80003-2
Carrillo A.J., González-Aguilar J., Romero M., Coronado J.M.,
Solar energy on demand: a review on high temperaturethermochemical heat storage systems and materials, Chemical Reviews, 119 (2019) 4777–4816. DOI: 10.1021/acs.
chemrev.8b00315
Castellanos A., The relationship between attractive interparticle forces and bulk behaviour in dry and uncharged fine
powders, Advances in Physics, 54 (2005) 263–376. DOI:
10.1080/17461390500402657
Castellanos A., Valverde J.M., Quintanilla M.A.S., The Sevillapowder tester: a tool for characterizing the physical properties of fine cohesive powders at very small consolidations,
KONA Powder and Particle Journal, 22 (2004) 66–81. DOI:
10.14356/kona.2004011
Cordis,2020,<https://cordis.europa.eu/project/id/727348>
accessed 24.05.2021.
Crystran, 2020, <https://www.crystran.co.uk/optical-materials/
calcite-caco3> accessed 08 october.2020.
Chacartegui R., Alovisio A., Ortiz C., Valverde J.M., Verda V.,
Becerra J.A., Thermochemical energy storage of concentrated solar power by integration of the calcium loopingRahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

process and a CO2 power cycle, Applied Energy, 173 (2016)
589–605. DOI: 10.1016/j.apenergy.2016.04.053
Chen Y., Quintanilla M.A.S., Yang J., Valverde J.M., Dave R.N.,
Pull-off force of coated fine powders under small consolidation, Physical Review E, 79 (2009) 041305. DOI: 10.1103/
PhysRevE.79.041305
Chen Y., Yang J., Dave R.N., Pfeffer R., Fluidization of coatedgroup C powders, AIChE Journal, 54 (2008) 104–121. DOI:
10.1002/aic.11368
Chirone R., Barletta D., Lettieri P., Poletto M., Measurement ofhigh temperature powder flow properties to estimate interparticle forces in high temperature fluidization, Proceedingsof the 8th International Conference for Conveying and
Handling of Particulate Solids (CHoPS 2015), 2015.
Chirone R., Poletto M., Barletta D., Lettieri P., The effect of temperature on the minimum fluidization conditions of industrial
cohesive particles, Powder Technology, 362 (2020) 307–322.
DOI: 10.1016/j.powtec.2019.11.102
Daniel I.M., Fibers A.C.D.-o.H.M., Their C., International A.,
Composite materials: testing and design (sixth conference):
a conference, ASTM, Philadelphia, Pa. (1916 Race St., Philadelphia 19103), 1982, ISBN: 9780803148499 0803148496.
Dinçer İ., Rosen M.A., Energy Storage Systems, in: İ. Dinçer
and M.A. Rosen (Eds) Thermal Energy Storage: Systems
and Applications (Second Edition), 2010, pp. 51–82. DOI:
10.1002/9780470970751.ch2
Ding W., Chen G., Qin M., He Y., Qu X., Low-cost Ti powders
for additive manufacturing treated by fluidized bed, Powder
Technology, 350 (2019) 117–122. DOI: 10.1016/j.powtec.
2019.03.042
Dunn R.I., Hearps P.J., Wright M.N., Molten-salt power towers:
newly commercial concentrating solar storage, Proceedings of the IEEE, 100 (2012) 504–515. DOI: 10.1109/
JPROC.2011.2163739
Durán-Olivencia F.J., Ebri J.M.P., Espín M.J., Valverde J.M., The
cohesive behaviour of granular solids at high temperature insolar energy storage, Energy Conversion and Management,
240 (2021) 114217. DOI: 10.1016/j.enconman.2021.114217
Durán-Olivencia F.J., Espín M.J., Valverde J.M., Cross effectbetween temperature and consolidation on the flow behaviorof granular materials in thermal energy storage systems,
Powder Technology, 363 (2020) 135–145. DOI: 10.1016/j.
powtec.2019.11.125
Esence T., Benoit H., Poncin D., Tessonneaud M., Flamant G., A
shallow cross-flow fluidized-bed solar reactor for continuous
calcination processes, Solar Energy, 196 (2020) 389–398.
DOI: 10.1016/j.solener.2019.12.029
Espin M.J., Duran-Olivencia F.J., Valverde J.M., Role of particle
size on the cohesive behavior of limestone powders at hightemperature, Chemical Engineering Journal, 391 (2020)
123520. DOI: 10.1016/j.cej.2019.123520
Espin M.J., Ebri J.M.P., Valverde J.M., Tensile strength andcompressibility of fine CaCO3 powders. Effect of nanosilica
addition, Chemical Engineering Journal, 378 (2019) 122166.
DOI: 10.1016/j.cej.2019.122166
Fernández A.G., Ushak S., Galleguillos H., Pérez F.J., Development of new molten salts with LiNO3 and Ca(NO3)2 forenergy storage in CSP plants, Applied Energy, 119 (2014)
131–140. DOI: 10.1016/j.apenergy.2013.12.061
Freeman R., The importance of air content on the rheology of
powders: an empirical study, American laboratory, 36 (2004)
8–10.
Gerhard C., Optics Manufacturing, CRC Press, Boca Raton, 2017,
ISBN: 9781351228367. DOI: 10.1201/9781351228367
Ghadami Jadval Ghadam A., Investigation of mechanical proper-

ties prediction of synthesized nylon-66/nano-calcium carbonate composites, Journal of Particle Science & Technology, 1(2015) 241–251. DOI: 10.22104/jpst.2015.307
Ghadiri M., Pasha M., Nan W., Hare C., Vivacqua V., Zafar U.,
Nezamabadi S., Lopez A., Pasha M., Nadimi S., Cohesive
powder flow: trends and challenges in characterisation andanalysis, KONA Powder and Particle Journal, 37 (2020)
3–18. DOI: 10.14356/kona.2020018
Gil A., Medrano M., Martorell I., Lázaro A., Dolado P., Zalba
B., Cabeza L.F., State of the art on high temperature thermalenergy storage for power generation. Part 1—Concepts,
materials and modellization, Renewable and Sustainable
Energy Reviews, 14 (2010) 31–55. DOI: 10.1016/j.
rser.2009.07.035
Gunda R., Volinsky A.A., Tip-Induced calcite single crystal
nanowear, MRS Proceedings, 1049 (2011) 1049-AA1005–
1015. DOI: 10.1557/PROC-1049-AA05-15
Gupta N.S., Chitin: Formation and Diagenesis, Springer Netherlands, 2010, ISBN: 9789048196845. DOI: 10.1007/978-90481-9684-5
Hall D., Cutress J., The effect of fines content, moisture and added
oil on the handling of small coal, Institute of Fuels, 33 (1960)
63–72.
Hall E.W., Hausz W., Thermal energy storage for electric utility
applications, Transactions of the American Nuclear Society:
United States, 32 (1979) CONF-790602-(Summ.).
Hanak D., Anthony E., Manovic V., A review of developments inpilot plant testing and modelling of calcium looping process
for CO2 capture from power generation systems, Energy &Environmental Science, (2015) DOI: 10.1039/C5EE01228G
Herrmann U., Kearney D., Survey of Thermal energy storage
for parabolic trough power plants, Journal of Solar Energy
Engineering, 124 (2002) 145–152. DOI: 10.1115/1.1467601
Hubermaterials, 2020, <https://www.hubermaterials.com/>
accessed 05-09.2020.
Kamiya H., Kimura A., Yokoyama T., Naito M., Jimbo G.,
Development of a split-type tensile-strength tester andanalysis of mechanism of increase of adhesion behavior of
inorganic fine powder bed at high-temperature conditions,
Powder Technology, 127 (2002) 239–245. DOI: 10.1016/
S0032-5910(02)00117-1
Kanaoka C., Hata M., Makino H., Measurement of adhesive force
of coal flyash particles at high temperatures and different
gas compositions, Powder Technology, 118 (2001) 107–112.
DOI: 10.1016/S0032-5910(01)00300-X
Karasavvas E., Panopoulos K.D., Papadopoulou S., Voutetakis S.,
Energy and exergy analysis of the integration of concentrated
solar power with calcium looping for power production andthermochemical energy storage, Renewable Energy, 154(2020) 743–753. DOI: 10.1016/j.renene.2020.03.018
Kierzkowska A., Pacciani R., Müller C., CaO-based CO2 sorbents: from fundamentals to the development of new, highly
effective materials, ChemSusChem, 6 (2013). DOI: 10.1002/
cssc.201300178
Kunii D., Levenspiel O., Brenner H., Fluidization Engineering,
Elsevier Science, 1991, ISBN: 9780409902334.
Lee S.-W., Kim Y.-J., Lee Y.-H., Guim H., Han S.M., Behavior
and characteristics of amorphous calcium carbonate andcalcite using CaCO3 film synthesis, Materials & Design, 112(2016) 367–373. DOI: 10.1016/j.matdes.2016.09.099
Lettieri P., Macrì D., Effect of process conditions on fluidization,
KONA Powder and Particle Journal, 33 (2016) 86–108. DOI:
10.14356/kona.2016017
Lettieri P., Yates J.G., Newton D., The influence of interparticle
forces on the fluidization behaviour of some industrial mate-41

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

rials at high temperature, Powder Technology, 110 (2000)
117–127. DOI: 10.1016/S0032-5910(99)00274-0
Lisbona P., Bailera M., Hills T., Sceats M., Díez L.I., Romeo
L.M., Energy consumption minimization for a solar lime
calciner operating in a concentrated solar power plant forthermal energy storage, Renewable Energy, 156 (2020)
1019–1027. DOI: 10.1016/j.renene.2020.04.129
Lomboy G., Sundararajan S., Kejin W., Subramaniam S., A
test method for determining adhesion forces and Hamaker
constants of cementitious materials using atomic force
microscopy, Cement and Concrete Research, 41 (2011)
1157–1166. DOI: 10.1016/j.cemconres.2011.07.004
Lüddecke A., Pannitz O., Zetzener H., Sehrt J.T., Kwade A.,
Powder properties and flowability measurements of tailored nanocomposites for powder bed fusion applications,
Materials & Design, 202 (2021) 109536. DOI: 10.1016/j.
matdes.2021.109536
Macrì D., Poletto M., Barletta D., Sutcliffe S., Lettieri P., Analysis of industrial reactive powders flow properties at hightemperature, Powder Technology, 316 (2017) 131–138. DOI:
10.1016/j.powtec.2016.10.064
Mahlia T.M.I., Saktisahdan T.J., Jannifar A., Hasan M.H.,
Matseelar H.S.C., A review of available methods and development on energy storage; technology update, Renewable
and Sustainable Energy Reviews, 33 (2014) 532–545. DOI:
10.1016/j.rser.2014.01.068
Marchetti L., Hulme-Smith C., Flowability of steel and toolsteel powders: a comparison between testing methods,
Powder Technology, 384 (2021) 402–413. DOI: 10.1016/j.
powtec.2021.01.074
Materialsproject, 2020, <https://materialsproject.org/materials/
mp-3953/> accessed 15.04.2020.
Matweb, 2020, <http://matweb.com/> accessed 18.09.2020.
Michel M.D., Mikowski A., Lepienski C.M., Foerster C.E.,
Serbena F.C., High temperature microhardness of sodalime glass, Journal of Non-Crystalline Solids, 348 (2004)
131–138. DOI: 10.1016/j.jnoncrysol.2004.08.138
Nedderman R.M., Statics and Kinematics of Granular Materials,
Cambridge University Press, Cambridge, 1992, ISBN:
9780521404358.
Ortega J.I., Burgaleta J.I., Téllez F.M., Central receiver system
solar power plant using molten salt as heat transfer fluid,
Journal of Solar Energy Engineering, 130 (2008) 024501 (6pages). DOI: 10.1115/1.2807210
Paksoy H.Ö., Thermal Energy Storage for Sustainable
Energy Consumption: Fundamentals, Case Studies andDesign, Springer Netherlands, Dordrecht, 2007, ISBN:
9781402052903. DOI: 10.1007/978-1-4020-5290-3
Pardo P., Deydier A., Anxionnaz-Minvielle Z., Rougé S.,
Cabassud M., Cognet P., A review on high temperaturethermochemical heat energy storage, Renewable and Sustainable Energy Reviews, 32 (2014) 591–610. DOI: 10.1016/j.
rser.2013.12.014
Pinel P., Cruickshank C.A., Beausoleil-Morrison I., Wills A., A
review of available methods for seasonal storage of solar
thermal energy in residential applications, Renewable andSustainable Energy Reviews, 15 (2011) 3341–3359. DOI:
10.1016/j.rser.2011.04.013
Pintaldi S., Perfumo C., Sethuvenkatraman S., White S.,
Rosengarten G., A review of thermal energy storage technologies and control approaches for solar cooling, Renewable
and Sustainable Energy Reviews, 41 (2015) 975–995. DOI:
10.1016/j.rser.2014.08.062
Prieto C., Cooper P., Fernández A., Cabeza L.F., Review of technology: thermochemical energy storage for concentrated solar

42

power plants, Renewable and Sustainable Energy Reviews,
60 (2016) 909–929. DOI: 10.1016/j.rser.2015.12.364
Quintanilla M.A.S., Castellanos A., Valverde J.M., Correlation
between bulk stresses and interparticle contact forces infine powders, Physical Review E, 64 (2001a) 031301. DOI:
10.1103/PhysRevE.64.031301
Quintanilla M.A.S., Valverde J.M., Castellanos A., Adhesion
force between fine particles with controlled surface properties, AIChE Journal, 52 (2006) 1715–1728. DOI: 10.1002/
aic.10770
Quintanilla M.A.S., Valverde J.M., Castellanos A., Viturro R.E.,
Looking for self-organized critical behavior in avalanchesof slightly cohesive powders, Physical Review Letters, 87(2001b) 194301. DOI: 10.1103/PhysRevLett.87.194301
Ramlakhan M., Wu C.Y., Watano S., Dave R.N., Pfeffer R.,
Dry particle coating using magnetically assisted impaction
coating: modification of surface properties and optimizationof system and operating parameters, Powder Technology,
112 (2000) 137–148. DOI: 10.1016/S0032-5910(99)00314-9
Røyne A., Bisschop J., Dysthe D., Experimental investigationof surface energy and subcritical crack growth in calcite,
Journal of Geophysical Research-Solid Earth, 116 (2011)
B04204. DOI: 10.1029/2010jb008033
Salehi H., Barletta D., Poletto M., A comparison between powder
flow property testers, Particuology, 32 (2017) 10–20. DOI:
10.1016/j.partic.2016.08.003
Sang L., Cai M., Zhao Y., Ren N., Wu Y., Burda C., Mixed
metal carbonates/hydroxides for concentrating solar power
analyzed with DSC and XRD, Solar Energy Materials
and Solar Cells, 140 (2015) 167–173. DOI: 10.1016/j.
solmat.2015.04.006
Santhanam A.T., Gupta Y.P., Cleavage surface energy of calcite,
International Journal of Rock Mechanics and Mining
Sciences & Geomechanics Abstracts, 5 (1968) 253–259.
DOI: 10.1016/0148-9062(68)90013-2
Santomaso A., Lazzaro P., Canu P., Powder flowability anddensity ratios: the impact of granules packing, Chemical
Engineering Science, 58 (2003) 2857–2874. DOI: 10.1016/
s0009-2509(03)00137-4
Sarrion B., Valverde J.M., Perejon A., Perez-Maqueda L.,
Sanchez-Jimenez P.E., On the multicycle activity of natural
limestone/dolomite for thermochemical energy storage ofconcentrated solar power, Energy Technology, 4 (2016)
1013–1019. DOI: 10.1002/ente.201600068
Schubert H., Capillary forces—modeling and application in particulate technology, Powder Technology, 37 (1984) 105–116.
DOI: 10.1016/0032-5910(84)80010-8
Schwedes J., Fließverhalten von Schüttgütern in Bunkern,
Chemie Ingenieur Technik, 1976, pp. 294–300, ISBN: 0009286X.
Schwedes J.r., Review on testers for measuring flow properties ofbulk solids, Granular Matter, 5 (2003) 1–43. DOI: 10.1007/
s10035-002-0124-4
Sharma A., Tyagi V.V., Chen C.R., Buddhi D., Review on thermalenergy storage with phase change materials and applications,
Renewable and Sustainable Energy Reviews, 13 (2009)318–345. DOI: 10.1016/j.rser.2007.10.005
Shi C., Palomo Sánchez A., Torgal F.P., Carbon dioxide sequestration in cementitious construction materials, Elsevier Science& Technology, Cambridge, United Kingdom, 2018, ISBN:
978-0-08-102444-7.
Shimada Y., Yonezawa Y., Sunada H., Nonaka R., Katou K.,
Morishita H., Development of an apparatus for measuring
adhesive force between fine particles [Translated], KONA
Powder and Particle Journal, 20 (2002) 223–230. DOI:

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

10.14356/kona.2002024
Smith D.H., Haddad G.J., Ferer M., Shear strengths of heated andunheated mixtures of MgSO4 and CaSO4 powders. Modelpressurized fluidized bed combustion filter cakes, Energy &Fuels, 11 (1997) 1006–1011. DOI: 10.1021/ef970037d
Surfacenet, 2020, <https://www.surfacenet.de/calcite-217.html>
accessed 08.11.2020.
Svarovsky L., Powder Testing Guide: Methods of measuring thephysical properties of bulk powders, Published on behalf of
the British Materials Handling Board by Elsevier Applied
Science, 1987.
Tammann G., Lehrbuch der Metallkunde, Leipzig, 1932.
Tatsidjodoung P., Le Pierrès N., Luo L., A review of potential
materials for thermal energy storage in building applications,
Renewable and Sustainable Energy Reviews, 18 (2013)
327–349. DOI: 10.1016/j.rser.2012.10.025
Tesio U., Guelpa E., Ortiz C., Chacartegui R., Verda V., Optimized
synthesis/design of the carbonator side for direct integrationof thermochemical energy storage in small size concentrated
solar power, Energy Conversion and Management: X, 4(2019) 100025. DOI: 10.1016/j.ecmx.2019.100025
Tesio U., Guelpa E., Verda V., Integration of thermochemicalenergy storage in concentrated solar power. Part 2: Comprehensive optimization of supercritical CO2 power block,Energy Conversion and Management: X, 6 (2020) 100038.
DOI: 10.1016/j.ecmx.2020.100038
Tomasetta I., Barletta D., Poletto M., The effect of temperature
on flow properties of fine powders, Chemical Engineering
Transactions, 24 (2011) 655–660. DOI: 10.3303/cet1124110
Tsukada M., Kawashima K., Yamada H., Yao Y., Kamiya H.,
Analysis of adhesion behavior of waste combustion ash athigh temperatures and its control by the addition of coarse
particles, Powder Technology, 180 (2008) 259–264. DOI:
10.1016/j.powtec.2007.04.005
Upadhyay S.K., Seismic Reflection Processing: With Special
Reference to Anisotropy, Springer Berlin Heidelberg, 2013,
ISBN: 9783662098431. DOI: 10.1007/978-3-662-09843-1
Valverde J.M., Ca-based synthetic materials with enhanced CO2
capture efficiency, Journal of Materials Chemistry A, 1
(2013) 447–468. DOI: 10.1039/c2ta00096B
Valverde J.M., On the negative activation energy for limestone
calcination at high temperatures nearby equilibrium, Chemical Engineering Science, 132 (2015) 169–177. DOI: 10.1016/
j.ces.2015.04.027
Valverde J.M., Castellanos A., Ramos A., Pérez A.T., Morgan
M.A., Watson P.K., An automated apparatus for measuring
the tensile strength and compressibility of fine cohesive

powders, Review of Scientific Instruments, 71 (2000)
2791–2795. DOI: 10.1063/1.1150694
Varshneya A.K., Mauro J.C., Fundamentals of Inorganic Glasses,
Third Edition, Elsevier, 2019, ISBN: 9780128162255. DOI:
10.1016/C2017-0-04281-7
Watson P.K., Valverde J.M., Castellanos A., The tensile strengthand free volume of cohesive powders compressed by gas
flow, Powder Technology, 115 (2001) 45–50. DOI: 10.1016/
s0032-5910(00)00275-8
Wen C.Y., Yu Y.H., A generalized method for predicting theminimum fluidization velocity, AIChE Journal, 12 (1966)
610–612. DOI: 10.1002/aic.690120343
Wheeler J.M., Michler J., Indenter materials for high temperaturenanoindentation, Review of Scientific Instruments, 84 (2013)
101301. DOI: 10.1063/1.4824710
Wu Y.-t., Li Y., Ren N., Ma C.-f., Improving the thermal properties of NaNO3-KNO3 for concentrating solar power byadding additives, Solar Energy Materials and Solar Cells, 160(2017) 263–268. DOI: 10.1016/j.solmat.2016.10.013
Xu Y., Luo C., Zheng Y., Ding H., Wang Q., Shen Q., Li X., Zhang
L., Characteristics and performance of CaO-based high temperature CO2 sorbents derived from a sol–gel process withdifferent supports, RSC Advances, 6 (2016) 79285–79296.
DOI: 10.1039/c6ra15785h
Yang J., Sliva A., Banerjee A., Dave R.N., Pfeffer R., Dry particle
coating for improving the flowability of cohesive powders,
Powder Technology, 158 (2005) 21–33. DOI: 10.1016/j.
powtec.2005.04.032
Yang W.-C., Chitester D.C., Kornosky R.M., Keairns D.L., A
generalized methodology for estimating minimum fluidization velocity at elevated pressure and temperature, AIChE
Journal, 31 (1985) 1086–1092. DOI: 10.1002/aic.690310706
Zafar U., Hare C., Calvert G., Ghadiri M., Girimonte R.,
Formisani B., Quintanilla M.A.S., Valverde J.M.,
Comparison of cohesive powder flowability measured by
Schulze shear cell, raining bed method, Sevilla powder testerand new ball indentation method, Powder Technology, 286(2015) 807–816. DOI: 10.1016/j.powtec.2015.09.010
Zhang H.L., Baeyens J., Degrève J., Cacères G., Concentrated
solar power plants: review and design methodology, Renewable and Sustainable Energy Reviews, 22 (2013) 466–481.
DOI: 10.1016/j.rser.2013.01.032
Zhang W., Sun Q., Zhu S., Wang B., Experimental study onmechanical and porous characteristics of limestone affected byhigh temperature, Applied Thermal Engineering, 110 (2017)356–362. DOI: 10.1016/j.applthermaleng.2016.08.194

43

Rahma Gannoun et al. / KONA Powder and Particle Journal No. 39 (2022) 29–44

Authors’ Short Biographies
Rahma Gannoun
Holds a PhD (2019) in process-chemical engineering from the national school of engineers ofGabes in collaboration with laboratory of metrology and thermal measurement of the national schoolof engineers of Monastir. She was undergraduated as a chemical-process engineer in 2014 fromthe same school. Actually she has a post-doc fellowship with the faculty of physics (university of
Seville). Her areas of interest include electrohydrodynamics, Computational fluid dynamics (CFD),
heat transfer, renewable energy, fine powder flow.

José Manuel Pérez Ebrí
A member of the Electrohydrodynamics and Cohesive Granular Materials (EHD-CGM) researchgroup at the Universidad de Sevilla (Seville, Spain). PhD in Science and Technology of New
Materials (2016). He began his career as an industrial technical engineer in EHD-CGM group in
2005, where he took part in developing several experimental setups, one of his areas of interest. He
worked four years in aeronautical industry as a materials engineer. He is developing his research
activity in Ca-Looping process for CO2 capture and mechanical properties of granular materials.

Alberto T. Pérez
Was born in El Puerto de Santa María (Spain) in 1962. He received his PhD degree from the
Universidad de Sevilla in 1989, where he has developed his academic career. Since 2009 he is Full
Professor of Electromagnetism in this university. His interests are primarily in electrohydrodynamics, powder flow, and electric behavior of colloids. He has authored more than 90 papers in indexed
journals on these subjects. He is also a popular science writer. Professor Pérez is currently the head of
the group of Electrohydrodynamics and Cohesive Granular Materials of the Universidad de Sevilla

José Manuel Valverde
Professor of electromagnetism and materials engineering. PhD in physics (1997). His research
activity has been focused on the study of fluidization and the mechanical properties of granular materials. A main subject of current interest is development of novel techniques to enhance the CO2 capture efficiency of CaO-based materials by means of the Ca-looping technology based on carbonation/
calcination of natural limestone in fluidized beds. He has published over 100 papers mostly in Q1
journals with over 1000 citations.

44KONA Powder and Particle Journal No. 39 (2022) 45–61/https://doi.org/10.14356/kona.2022019

Review Paper

Numerical Modelling of Formation of Highly Ordered
Structured Micro- and Nanoparticles – A Review †Jakub M. Gac
Faculty of Chemical and Process Engineering, Warsaw University of Technology, Poland

Abstract
The aerosol particles play a significant role in the environment and human health. They are also increasingly usedin medicine (drug carriers), preparation (nanocatalysts) and many other fields. For these applications, the particles
have to possess unique properties which arise directly from their structure and topology. Indeed, the functionalityof the nanostructure particle is defined through its application, like chromatography, sensors, microelectronics,
catalysis, and others. That is the reason why people are more and more interested in manufacturing structured
particles. The structured particles are the particles with well-defined topological structure. Examples of suchparticles are porous particles, hollow particles (with the empty space inside), or multi-component particles withthe segregation of components in the particle structure. Such particles usually have very interesting features, e.g.
porous particles have a significantly larger surface area than the simple spherical particles with similar volume.
The present paper contains a comprehensive review of the numerical simulation methods of the formation of highlyordered structured particles. The most important methods will be described in detail and their fields of application(with specific examples), advantages, limitations and information about their accuracy will be given.
Keywords: structured particles, particle synthesis, numerical modeling, self-organization

1. Introduction
The structured particles are the particles with welldefined, usually ordered, topological structure (Yang
S.-M. et al., 2008). Examples of such particles are porous
particles, hollow particles (with the empty space inside) or
the multi-component particles with the segregation of components in the particle structure (e.g. core-shell particles).
Such particles usually have very interesting features, e.g.
porous particles have a significantly bigger surface than thesimple spherical particles with similar volume. This featureallows us to use these particles as a nanocatalytic objects.
Even if the substance that builds the particle has not catalytic properties, the particles may be covered with the thinlayer of catalyzing substance.
Hollow particles (HP), on the other side, may beconsidered as a carrier for encapsulation of molecules or
nanoparticles (Liu B. and Hu X., 2020). Other possible
applications of HP are coatings (polymeric HP are considered as a white pigment, competitive to conventionallyapplied TiO2), cosmetics (carboxymethyl cellulose-based
HP are applied for encapsulation of active ingredients of†Received 11 May 2021; Accepted 3 August 2021
J-STAGE Advance published online 9 October 2021
Add: ul. Waryńskiego 1, 00-645 Warsaw, Poland
E-mail: jakub.gac@pw.edu.pl
TEL: +48-22-234-6508

various cosmetics) and electronics (mesoporous polymeric
HP are considered as a filler in the electrolyte membranes
for solid-state batteries). For the possible application of HP
see the comprehensive review of Wichaita et al. (2019) andreferences therein.
Core–shell particles (CSPs) are a class of particles whichcontain a core region and a shell layer covering a core. The
core and the shell can be different materials or the same materials with different structures (e.g. solid core and highly
porous shell). One of the possible applications of core-shellparticles is chromatography, e.g. high-performance liquid
chromatography, where silica core-shell microspheres areused as a packing material (Hayes et al., 2014).
CSPs are an example of composite particles. In general,by the concept of composite particles we understand particles made of at least two different substances. The atoms or
molecules that make up a particle may be randomly distributed in its structure or create some geometrically orderedpattern. In the latter case, it can be said that the composite
particle is a structural particle. Apart from CSPs, an example of these particles are the so-called Janus particles (JPs).
They were named after the Roman god Janus, who had two
faces, each facing a different direction. Similarly, Janus
particles have two sides which exhibit different properties.
E.g. one of these sides may be non-polar and the otherpolar. Such particles may exhibit properties and behavior
similar to surfactant molecules (de Gennes, 1992). Another

Copyright © 2022 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

45

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

example of Janus particles is when both sides are madefrom different materials (e.g. different metals), which may
catalyze different chemical reactions. Such particles may
catalyze a chemical reaction and, at the same time, moveto regions where the concentration of reactants is higher.
One should also not forget about nano- and microcrystals. Such small crystals are often monocrystals i.e. thecrystal lattice of the entire particle is continuous and has
no defects nor grain boundaries (however, there are exceptions). Thus, the structure and morphology of nano- andmicrocrystals are defined by the geometry of crystal lattice.
One of the most known examples are the snowflakes.
Though they may differ in appearance and shape (“no two
snowflakes are alike”—as the famous saying goes) but allof them have characteristic six-fold symmetry which arises
from the hexagonal crystalline structure of ice.
The structure of matter, on a microscopic scale may
dramatically influence its functionality. Engineering ofparticle structures on a microscopic scale would also leadto their unique optical, electrical, magnetic, or rheologicalproperties maintaining at the same time the high surface
area. The functionality of the nanostructure particle is defined through its application, like chromatography, sensors,
microelectronics, catalysis, and others.
Well-controlled synthesis of nanomaterials and nano­scale characterization enables us to unambiguously correlate the structural properties with the physical, chemicaland biological properties of nanomaterials, which form thecore of nanoscience research. Excellent examples of theuse of advanced particle engineering to design the structure
and properties of catalysts are described in the review paper (Czelej et al., 2021). An essential requirement for nanomaterial synthesis is the uniformity of the final productin size, shape and chemical composition. Recently, many
synthesis approaches have been developed to produce
high-quality nanoparticles, nanorods, nanowires, or othernanostructures using metals, semiconductors and oxides(Mao et al., 2005; Mohanty, 2011).
Each of the types of structural particles mentioned
can usually be obtained in several different ways. Thesemethods depend on the particle structure itself and will bebriefly presented in the next chapter. There is a suitable
synthesis method to obtain a particle with a predetermined
structure. A good guideline that helps to choose the appropriate method of particle synthesis may be to perform
a numerical synthesis of such a particle. Numerical calculations, with the participation of a computer, allow forcheap and quick prediction of the effect of the assumed
procedure. For this reason, in parallel with the methodsof synthesizing particles of a given structure, methods ofnumerical modeling of the synthesis of such particles arebeing developed. Therefore, the chemical development of
numerical methods related to the preparation of structural
particles has taken place in the last 30 years. Currently,

46

there are many methods that allow obtaining particles witha specific structure.
The purpose of this publication is to provide an overview
of the numerical methods used to describe the formationof particles with a specific structure. Four of them we cancall classic: these are groups of methods based on heatand mass balances, population balances, single atoms or
molecules tracking (based on molecular dynamics) andMonte Carlo methods. They have been applied many times
in numerous practical issues and constantly developed.
Apart from them there will be described some less popularmethods which may still be useful in specific issues.

2. Types of structured particles and methodof their synthesis
Currently, many methods are known for the synthesis of
structured particles. To choose the right one for a specificprocess, you must first determine what type of particles
you want to get. Methods that will allow synthesizing, forexample, HP, may not work at all in the case of JP and viceversa.
In general, all the methods of formation of particles,
independently – structured or not – may be divided into
two main groups: top-down and bottom-up (Verma et al.,2009; Fernandez et al., 2014). The first group of synthesis
methods implies that the nano- or microparticles (NMPs)
are synthesized by breaking larger structures (e.g. crushing, grinding or etching out crystals). A top-down method
can thus be considered as an approach where the building
blocks are removed from the substrate to form the particles(Aryal et al., 2019).
Oppositely, a bottom-up synthesis method means thatthe particles are synthesized by joining smaller structures
together (e.g. atoms, molecules or smaller nanoparticles).
A bottom-up approach can thus be viewed as a synthesis
approach where the building blocks are added onto the substrate to form the particles (Betke and Kickelbick, 2014;
Lesov et al., 2018).
From a practical point of view, the bottom-up synthesis
is considered more advantageous than the top-down one,because the former usually leads to more homogeneous
products with less defects and more homogenous chemicalcomposition. Thus, in the next part of this paper, primarily
the bottom-up methods will be considered.
Ones of the earliest known methods of synthesis of
NMPs were the crystallization of particles from solutions(and similar precipitation) and spray drying (de Souza Limaet al., 2020). These methods have led usually to poorly
structured particles. Indeed, by means of above-mentioned
techniques particles with a wide range of sizes and shapes
and a chemical composition that is difficult to control are
obtained. Nevertheless, it is possible to obtain structured

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

particles by means of these methods under strict conditions. Crystallization and precipitation may lead to theformation of nanocrystals and spray drying—to sphericalparticles, or even core-shell or hollow particles.
However, the more complex particle morphology, themore advanced methods should be used. Template methods may serve as an example of such a sophisticated andmultistep approach, where first the template is synthesized,then modified to obtain the particle, and finally removed tocreate desired pores and voids in the structure. E.g. in thecase of HP formation, the template is a simple sphericalparticle. This particle is then coated with a layer of thedesired material and finally – removed, e.g. by meansof etching (Liu B. and Hu X., 2020), leaving an empty
shell. Following this description, we may conclude thatthe template method may be considered a combination ofbottom-up (template formation, coating) and top-down(template removal) methods.

2.1 Hollow particles
Hollow particles (HPs), defined as particles (usually of
spherical shape) with void space surrounded by a shell areones of the most popular structured particles (Lou et al.,2008; Wang X. et al., 2016; Liu B. and Hu X., 2020). It
has been observed that this type of particle morphology
may appear during the spray drying technique when thesolution or slurry is atomized into small droplets which arethen evaporated (Mezhericher et al., 2010; 2011; Vehring,2008). This technique, together with a similar gas blowing
technique, was the most popular synthesis method of thiskind of HPs (Kellerman, 2011; Tsotsas, 2012; Liu B. and
Hu X., 2020).
Today, a lot of other methods for the formation of HPs
are known. The most popular ones are collectively referred
to as “colloidal templating” (Caruso et al., 1998). This
group of methods boils down to producing a template on
the basis of which the shell of HP is synthesized, and thenremoving this template (Tu and Gösele, 2005; Fan et al.,2007). In the group of templating methods we may distinguish hard-templating methods, soft templating methods
and self-template methods (Liu B. and Hu X., 2020).
During the hard templating methods hard templates withspecific (usually spherical) shapes are synthesized first, andthen their outer surface is coated with a layer of the desired
material. During the soft-templating method, the role of“template” plays the droplet of emulsion or the bubbleof gas (Hadiko et al., 2005). Finally, the core material isselectively removed to obtain the hollow structure (Lou etal., 2008). Finally, self-template methods denote direct synthesis without the need of additional templates (Zhang Q.
et al., 2009). Methods from this group contain two stages:
the synthesis of template nanomaterials and the transformation of templates into HP. The main difference between

the conventional templating methods and self-templating
methods, the templates used in self-templating methods are
not only the templates used to formation of a void space inside the HP but also form the outer region – the crust of HP.
An exhaustive review of methods of synthesis HPs ispresented in (Liu B. and Hu X., 2020).

2.2 Core-shell particles
Core–shell particles are the particles which contain an
inner core and an outer shell (Ghosh Chaudhuri and Paria,2012). The core and the shell differ in material type, in the
structure (e.g. solid core and porous shell made from thesame substance) or both of them (Hayes et al., 2014).
Core–shell particles are usually synthesized by amultiple-step process. The core is synthesized first and theshell is then formed on the core particle via different methods, depending on the type of core and shell materials andtheir morphologies (Ghosh Chaudhuri and Paria, 2012).
Among these methods, layer-by-layer approach via electrostatic interaction, shell synthesis on pre-formed cores,
droplet-based microfluidic method and many others can be
mentioned. An exhaustive review of methods of synthesisof core-shell particles has been made in work (Hayes et al.,2014).

2.3 Janus particles and other composite particles
As it has been stated in Introduction, Janus particles (JP)are the particles which have two sides which exhibit different properties. They are probably the best-known and mostwidely used composite NMPs. The excellent overview ofthese particles’ properties, applications and synthesis methods is reviewed in the paper (Walther and Müller, 2013).
There are three principal methods of synthesizing JP(Walther and Müller, 2013). The first one is based on the
self-assembly of block copolymers (Walther et al., 2007).
As a result of this process, individual blocks of polymers
form regions of a particle with different properties. Thismethod allows obtaining JPs with various shapes, not only
spherical ones (Liu Y. et al., 2003). The second method
uses “masking” (blocking) of a part of the surface of analready formed particle and then surface modification of
the unblocked part of the surface (Lin et al., 2010). Afterremoving the masking agent, a particle is obtained having
surface regions with different properties. Finally, the third
method consists in creating droplets of emulsions composed of various substances, and then leading to phase separation in the droplets thus formed and their solidification.
In addition to JPs, there are many particles that deserve to
be called composite particles because of their complex,
usually more or less ordered internal structure containing
at least two substances with different properties. Some ofthem can be treated as certain modifications of the more47

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

popular structures described above. For example, if in acore-shell particle the outer shell is not a continuous, solidor porous spherical layer but a layer of smaller particles
covering the core more or less closely, we are dealing witha raspberry-like particle (when the core is tightly covered
with smaller particles) or core-satellite particle (when there
are larger gaps between the particles covering the core andpossibly the particles covering the core are of different
sizes) (Mourdikoudis et al., 2015). Particles analogous to
HPs but with multilayered crust are sometimes reported
as “sandwich-like particles” (Liu Q. et al., 2020). Yolkshell particles, like CSPs, have an inner spherical core
and an outer spherical shell - but in their case, the shell is“too big” for the core: a small spherical nucleus can movefreely in the space surrounded by the shell (Sun X. et al.,2020). There are many more such examples and it is to
be expected that as nanotechnology develops, structured
particles with an increasingly complex internal structure
will be obtained.
These particles are usually synthetized by means of gasphase or vapor-phase methods (Swihart, 2003) or by meansof coating of simple particles with appropriate substance(Demirörs et al., 2009). Very promising method of synthesis of composite particles is flame spray pyrolysis (FSP)(Mädler et al., 2002; Chiarello et al., 2008). In FSP, thesolution containing liquid precursor and fuel is atomized toform the droplets which are then evaporated and ignited bymeans of an additive small flame (so-called pilot flame) toform solid nano particles.

2.4 Other types of structured particles
In addition to the particles with the structure describedabove, other, less popular types can also be found innanoengineering applications. Among them, porous particles, as well as superficially porous particles, are worth
mentioning. The latter kind of particles has a structure
somewhat similar to CSPs, where the core is a solid sphere,
while the shell is characterized by the presence of pores ofvarious sizes. Both of these particle segments can be madeof the same substance and differ only in terms of internal
structure—so it is not a composite particle. Porous and superficially porous particles are applied as catalyst supports(Ye et al., 2017) and filling in chromatographic columns(Wang X. et al., 2012).
Micro- and nanocrystals of various substances also
may be considered structured particles. They have a welldefined shape which in turn results from the structure andsymmetry of the crystal lattice of the substance underconsideration. The formation of submicron-sized single
crystals has long been studied both experimentally andtheoretically.
Last but not least, viruses should be mentioned as an
example of structured particles. These objects, which are48

Fig. 1 Examples of structured particles: (a) hollow particle, (b) coreshell particle, (c) Janus particle, (d) raspberry-like (core-satellite) particle, (e) yolk-shell particle, (f) superficially porous particle.

intermediate between particles and living organisms, arecharacterized by a ordered structure, which consists of
the nucleic acid (DNA or RNA), a shell (capsid) made ofproteins and sometimes some other additional components.
The structure of viruses is much more complicated than the
structural particles discussed earlier, e.g. CSPs. Due to thegreat importance of viruses in medicine and biomedical engineering, there are recently more and more attempts to describe the formation of this type of “particles” numerically(Kraft et al., 2012). Most attention is paid to the modelingof capsid formation from protein subunits (Zlotnick, 1994).
The most popular and most often investigated types ofstructured particles are presented in Fig. 1.

3. Numerical models of formation of
structured particles
3.1 Models based on heat and mass balance
equations
One of the most popular groups of numerical modelsof the formation of NMPs are those based directly onequations of heat and mass balances (HMB). They areespecially popular for considering droplet formation during
the spray drying method; however, they are also applied tomodel some other processes of formation of NMPs, e.g.
precipitation.

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

The aim of all those models is to formulate the massbalance equation which takes into account the mass flux
from surrounding to the particle or vice versa. In parallel,
the energy balance equation is formulated. Both of thoseequations, with proper initial and boundary conditions
are solved using widely applied numerical schemes, e.g.
finite difference method. Levi-Hevroni et al. (1995) andMezhericher et al. (2007; 2008; 2011) have applied thisscheme for the spray drying process. During the first stageof drying—evaporation of droplet—they considered theescape of solvent molecules from the droplet leading to adecrease in its radius (Fig. 2a). The mass balance equation—when assuming spherical symmetry of a droplet—takes
a form of the ordinary differential equation describing thedependence of droplet radius on time (Levi-Hevroni et al.,1995):

dRd
1

m v
dt
4πρd, w Rd2(1)

Where the mass flux ṁv is given as (Mezhericher M. etal., 2007):(1)m v  hD  ρv,s  ρv,  Ad

(2)

All the symbols are described in Nomenclature at theend(2)of the paper.
The mass transfer coefficient hD is obtained usuallyfrom the Ranz-Marshall correlation (Levi-Hevroni D. etal., 1995) and is a function of the diffusion coefficient ofsolvent vapor in air as well as viscosity and density of air.
These parameters, together with solvent density ρd andsaturated solvent vapor concentration ρv,s, are dependent on
the temperature of a droplet surface which may be obtainedby solving a heat balance equation:

Fig. 2 Scheme of a model of hollow particle formation in spray drying
process based on heat and mass balance equation: (a) first drying stageand (b) second drying stage.

ρdc p,dTd
1   2 Td 
 2
kd r

r r 
t
r 

(3)

With the boundary condition at the droplet surface:
T
m
(3)
hc T  Td   λ d  Lh v
r
Ad

(4)

The set of equation (1–4) is solved through the whole
first drying period by means of well-known discretization(4)
methods(e.g. finite difference scheme). This period ends
when the concentration of solutes or suspended particles
in a droplet is big enough to start the formation of solid
crust. The simulation of the second drying stage is much
more complicated. In their early works, Mezhericher M. etal. (2007; 2008) considered the emerging crust as a porous
solid medium through which further solvent evaporation
took place. Because the further decrease of particle radius
is impossible after the formation of the crust, the evaporation of a solvent results in formation of internal bubble
inside the dried particle (Fig. 2b). That leads directly to the
HP formation.
Later on, these authors have considered the more realistic crust structure as built from spherical nanoparticles
suspended in droplet (Mezhericher et al., 2011; 2012). Thisapproach allowed formulating the criterion of the final particle morphology: hollow particle or solid particle. Similar
investigations – with the use of the same approach – havebeen done to investigate the morphology of particles obtained by means of spray pyrolysis (Lenggoro et al., 2000;
Eslamian et al., 2006). The described model allowed theformulation of the conditions of solid or hollow particle
formation for this process as well. Also, Shabde et al.
(2005) have used the described method to simulate theformation of HP during spray drying. Likewise, Maurice
et al. (2017) considered the dynamics of growth of internal
bubble during the HP formation in spray drying process.
The main difficulty in the application of the numericalmethod described above is the existence of moving boundaries. Indeed, during the drying a droplet shrinks and thus
the condition (4) is fulfilled for the different value of r at
every time step. The Mezhericher group usually applies themethod elaborated by Moyano and Scarpettini (2000) for
one-dimensional moving boundary problem with implicit
boundary conditions. They use the Landau’s transformation in order to work with a fixed number of nodes at eachtime step despite the moving boundaries. Shabde et al.
(2005), on the other hand, have used the gradient-weighted
moving finite element method (Miller, 1997). Recently,
a work (Larbi et al., 2021) appeared in which a spectral
collocation method has been applied. This method is basedon the expansion of the unknown function in terms of the
Lagrange elementary polynomials. The solution of HMB
equations comes down to finding the dependence of thecoefficients of this expansion on time.

49

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

Another step towards the description of the structure ofparticle formed in the spray drying process is analyzing the
distribution of concentration of solutes inside the droplet.
The mass balance equation for the solute takes the form of
convection and diffusion equation:
c A
c
1  
c A 
 vr A  2
 DA r 2

t
r
r 
r r 

(5)

The radial velocity of a solvent in a droplet vr is dependent on the velocity of the droplet surface caused by its(5)shrinking. Eqn. (5) may be transformed into:
cA
D   2cA 2 cA  R cA rd 2A trd  R 2
R R  rd R t(6)where rd is a radius of a droplet and R  r rd denotes thenormalized radial coordinate. Eqn. (6) is a base for the nu(6) model of particle formation elaborated by Vehring
merical
et al. (2007) and further developed by(21)other authors under
the name of VLF model (Chen X.D., 2011). Originally, themodel assumed steady-state evaporation of a droplet whatdefined a proper boundary condition at the droplet surface.
Later on, it has been extended to take into account thetransient nature of the solute concentration profiles (Boraey
and Vehring, 2014).
As a method of description of particle formation during
spray drying, the VLF model has been applied mainly
for the simulation of HPs formation. It allows finding out
the time of drying of a droplet and the final thickness anddensity of a crust.
More advanced approaches use computational fluid
dynamics (CFD) methods to solve HMB equations, e.g.
finite element method (Vasiliauskas et al., 2015). Recently,
Wu and Chung (2020) used the volume of fluid method tosimulate the synthesis of HPs by means of spray drying
process. At the expense of a significant complication of
the mathematical apparatus, this approach makes it possible to follow the dynamics of particle synthesis without
introducing additional assumptions, e.g. regarding thesymmetry of the particle. The proposed model allowed
directly distinguishing four sequential stages of the drying
process: temperature adjustment, isothermal drying, crust
formation, and crust thickening. While in the previously
discussed papers, these stages were artificially separated,
and for each of them, a slightly modified system of equations was used—in this case, one system of equations
allows describing the entire drying process.
The methods based on mass and heat balance equations
have also been applied for modeling of synthesis of NMPs
other than HPs, e.g. core-shell particles. The works presenting the results of this type of simulation focus not onbalance within a single emerging particle but rather on theentire system (apparatus) in which the particles are formed.
In such an approach, the material balance, which describes
rather chemical reactions taking place during the process50

than the convection and diffusion of compounds, is coupled
with—usually simplified—population balance of particles,
e.g. (Aul’chenko S. and Kartaev E., 2018). The authors
use a single-liquid flow model to describe the synthesisof composite core-shell TiO2-SiO2 particles from the gas
substrates (mixture of titanium tetrachloride and silica
tetrachloride). The efficiency of solid particle formation is
obtained from kinetic reactions—both homogeneous andheterogeneous—and phase transition between gas and solid
phase. Such an approach, coupled with a simplified balanceof particle number, allowed to calculate the average size ofparticles at an arbitrary time point. From this model any
other properties of structured particles could be obtained,
e.g. the mean thickness of silica shell—however, authors
did not consider this properly.
Model based on heat and mass balances equations has
been also applied for simulation of FSP method (Ren et al.,2021). Similarly as in work by Mezhericher group, authorsof this works considered single droplet and assumed its
spherical symmetry. The main difference between modeling of spray drying and FSP is considering the effects ofchemical reactions in the last one.
A similar assumption has been applied in (Hamzehlou
et al., 2016) to simulate the dynamic evolution of the morphology of polymer-polymer latex particles. This paper’s
main goal was to consider the formation of clusters of oneof polymers (P1) at the surface of the particles built fromthe second polymer (P2). By considering the distributionof cluster size at different time points, the equilibrium morphology of particles (described as core-shell or hemispherical particles) and non-equilibrium one (a few of P1-clusters
with various sizes deposited randomly on particle P2surface) were recognized.
To sum up—a group of methods based on mass andenergy balance equations has been found and still is widelyused to describe the synthesis of particles with various
morphologies. It also allows tracing the dynamics of theparticle morphology over time and obtaining information
about the quantitative distribution of parameters describing
this morphology. With the help of this method, it is also
possible to determine the structure of non-equilibrium
particles (which are sometimes formed under not properly
selected process conditions). The most important disadvantage of the described method is its relative complexity andhigh demand for computing power—and for this reason,other numerical methods are constructed, which sometimes constitute a better choice when it comes to particle
synthesis description. These methods are described in thenext section.

3.2 Multiple shells model
As mentioned above, the most challenging issue concerning the solution of differential balance equations (e.g.

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

modeling the droplet during spray drying process) are themoving boundaries of drying droplets. To get around thisdifficulty, a set of methods in which the droplet is divided
into imaginary regions were proposed. These regions arecharacterized by the same value of the concentration of
every solute and the same temperature. This is, of course,
an idealization of real situation and these regions mimic theparts of dried droplet where these parameters are nearly thesame. This group of numerical methods is usually called
the distributed parameter methods (Wang S. and Langrish
T.A.G., 2009). Because of the spherical symmetry of thedrying droplet, the above-mentioned regions usually have ashape of concentric spherical shells (the central one is a fullsphere); thus, the described method is also known under thename multiple shells model (Parienta D. et al., 2011).
The first method from this group simply utilized themass balance equations discretized in respect to radial
coordinate (Adhikari B. et al., 2007). Wang S. and Langrish
T.A.G. (2009) have used an explicit form of the concentricshells to analyze the changes of solute concentration andtemperature in every part of a droplet. Parienta D. et al.
(2011) used the same model for investigations of diameterand composition change of exhaled respiratory droplets.
Also, similar model has been applied to investigate the
distribution of protein and sugar in an evaporating droplet(Grasmeijer N. et al., 2016a; 2016b). In the last work notonly the droplet but also the layer of surrounding air was
divided into concentric shells. This allowed the solvent
evaporation rate from the droplet to be simulated directly
rather than using mass transfer coefficients obtained fromsemi-empirical correlations.
All these works, however, did not describe the processof solid particle formation. In fact, as they analyzed thechange of solute concentrations inside the droplets, theirresults may be accounted as numerical modeling of the firststep of particle formation.
The second step, i.e. crust formation, has been modeledin (Gac and Gradoń, 2013a). The scheme of the method
has been presented in Fig. 3. The authors assumed that the
crystallization in this shell starts and the solid crust forms
when in any of the shells (typically, it was the outermost
shell) the supersaturation exceeds the critical value. In
forthcoming time steps, this shell is not considered – thesecond shell becomes the outermost. During this period,
the diameter of all the shells stops decreasing and remains
constant till the end of the simulation. Instead, the concentration of all the compounds (including a solvent) in thecentral sphere decrease and finally reaches zero. When it
is happened, in this sphere there is no solvent nor solutes—that means the gas bubble is formed. In next steps theconcentration of solutes in the outermost shell increases(what may finally lead to the attachment of this shell tothe solid crust) and the concentration of both solutes andsolvent in the innermost shell decreases (what may result

Fig. 3 Scheme of the multiple shell model of (a) a dried droplet and (b)a wet particle with solid crust (marked in black and white), wet core anda gas bubble inside.

in the attachment of this shell to the central bubble). This
scheme is repeated until all the shells do not belong to solid
crust or gas bubble.
The multiple shells model, as described above, has
found its application not only for modeling the formationof NMPs. There are a few works which use a similar model
to describe the thermal evolution of planetesimals (Weiss
and Elkins-Tanton, 2013; Blackburn et al., 2017). These
works describe the changes of temperature profile inside
the spherical planetesimal and the change of aggregation
state of its compounds – they, however, do not consider thechange of the diameter of the body. In (Gac and Gradoń,2013b) the multiple shells model has been adapted to simulate the evolution of deposits appearing during the dryingof sessile droplets (e.g. the famous “coffee rings”).
It should be stated that the multiple shells model ischaracterized by a very simple mathematical apparatus.
The transport of mass and energy is described here entirely
using ordinary differential equations, which can be solved
with not very advanced numerical techniques. However,for such a description to be applied, the simulation object(the resulting particle) must have an appropriate (usuallyspherical) symmetry. This condition, in principle, limits thescope of potential applications of the described model tohollow particles or core-shell particles. However, it is sucha common morphology of particles produced in various
processes that the described model can be considered,despite significant limitations in its applicability.

3.3 Models based on population balance equations
Population balance equations (PBEs) are widely usedin several branches of modern science, mainly in chemicalengineering, to describe the evolution of a population ofparticles. They define how populations of particles develop
specific properties over time, taking into account such phenomena as nucleation, aggregation, coagulation, breakupof aggregates, evaporation, dissolution, etc. (Vetter et al.,51

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

2013; Hao et al., 2013).
Moving on to the modeling of synthesis of NMPs, thePBEs may be applied to describe the evolution of nanoparticles’ agglomeration leading to the creation of the larger
structured particle. This procedure is usually applied tomodel the formation of particles by means of spray drying.
Handscomb et al. (2009a) applied the PBE method formodeling spray drying kinetics. As during spray drying
HPs are often formed, the authors investigated the time ittakes to form a solid crust for various conditions of the process. For a description of the drying of a droplet containing
suspended solids, the dynamics of particle number density
function inside the droplet N(L,r,t) is analyzed, where L isparticle size, r—its radial coordinate (spherical symmetryof dried droplet is assumed) and t—time. The equation
fulfilled by function N has a form:



1  2
N
GN   2
r vr N 
t
L
r r
1   2 N 
 2
r D
0
r r 
r (7)where G is the velocity of motion through the state spaceof internal coordinates, i.e. the linear growth rate. The
authors(7) have assumed that this growth rate is independentof particle size. For solving Eqn. (7) a moment method is
employed to yield the evolution of the first four integer moments of the internal coordinate. In their subsequent work
(Handscomb C.S. et al., 2009b), the same authors extended
their model for droplets drying in the presence of a solid
crust. The improved model incorporates crust thickening,along with wet and dry crust drying. That allows predicting
not only the kinetics of a particle formation process but also
its final structure: crust thickness and its porosity.
The PBEs method of modeling the formation of particles
during the spray drying process has also been applied in(Bück et al., 2012). The authors considered the evolutionof the distribution of nanoparticles suspended in dried
droplets with particular emphasis on their aggregation. In
contrast to the above-mentioned works, the effect of droplet shrinking on the PBE was not modeled as an artificial
boundary source but as a flux term in the PBE. The authorsof the discussed study also drew attention to the hierarchical structure of the solid crust formed during drying. They
defined its porosity as εsh, taking into account that the crust
was formed from previously formed aggregates which also
have internal porosity εagg. The model proposed by the authors allowed finding out both the porosities. However, thepotential of these results has not yet been fully exploited.
The modeling of synthesis of structured particles bymeans of PBEs seems to be one of the more general
methods. A significant feature of this approach is a lack ofdetailed assumptions about the morphology of the formed
particle. E.g. one need not assume that the final particle isof a spherical shape or spherical symmetry – these proper-

52

ties are to be obtained directly from the model.
The downside of the described method may be a relatively large complication of the mathematical apparatus.
However, modern computers make it possible to overcome
this difficulty.

3.4 Models based on single atoms, molecules or
nanoparticles tracking
As it has been mentioned in Sec. 2, many structured
NMPs are synthesized by means of bottom-up methods,i.e. as a result of joining of atoms, molecules or smaller
particles (hereinafter referred to as the common term“individuals”) into the desired structure. Therefore, anobvious method of numerical modeling of such a process
is a direct tracking of the mentioned individuals making up
the particle. This may be done by numerical solution of theequations of motion of individuals in form:


x

1
F  x, x ,tm

(8)

In Eqn. (8) ẍ denotes the second derivative of a position
vector of individuals, i.e. the vector of acceleration and F
is a(8)vector of force, which may (or may not) depend on position vector, velocity vector and time. The most common
method in this group is molecular dynamics (MD) which
is widely used for the description of various phenomena
occurring at the atomic or molecular level.
MD algorithms are common for the simulation of the
behavior of structured particles at various conditions. For
example, the alloying reaction in core-shell Al-Ni particle(Levchenko et al., 2010), changes in structure during theheating and cooling of such a particle (Song and Wen,
2010), melting behavior of core-shell Pt−Au nanoparticles(Yang Z. et al., 2008) and many others have been investigated by means of this method.
Of course, MD has also been applied for modeling ofsynthesis of structured NMPs. Förster et al. (2019) useda very simple MD model to investigate the dependence ofa particle structure on the parameters of the interactions
between the atoms. In their investigations, three kinds ofatoms have been considered. The first kind represented aninert gas (the atoms of this species react neither with eachother nor with atoms of other kinds). Two other species arereactive and interact with each other by means of classicalLennard-Jones (L-J) potential:

 σ ij 12  σ ij  6U ij  4εij      (9) rij  rij  
In Eqn. (9) i and j denote the name of species of atoms(referred as A and B), εij is a parameter describing thestrength(9) of interaction and σij—a range of this interaction.
By changes of these two parameters, three types of structures of NMPs have been observed. The most importantJakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

parameter influencing the morphology of the obtained
particles turned out to be εij. It appeared that when εBB <εAA < εAB (i.e. the interaction between atom A and atom B
is stronger than both between two atoms A and two atoms
B) an alloy particle is obtained. When εBB < εAB < εAA,
most of the simulations ultimately result in a core-shellparticle. When εAB < εBB < εAA, the Janus particle is mostfrequently obtained, however also quite often (about a thirdof the cases), the formation of pure B particles and pure A
particles is observed.
Another example of the application of MD for the formation of structured particles has been applied in (Singhet al., 2014). In this paper, an MD was used to model thegas-phase synthesis and growth of silicon–silver (Si–Ag)
hybrid nanoparticles. For simulating such a real system
more advanced model of interatomic interactions has
been applied than L-J potential. While the latter takes into
account the interactions of pairs of atoms, it may be applicable with good accuracy to describing rarefied gases, especially noble ones. However, this model may be too vague
to describe, for example, metals in solid state. In this case,
L-J potential allows insight into qualitative properties of an
inner structure of formed particles. More specific problems
require taking into account collective effects between
atoms. One of the most popular models including theseeffects is the embedded atom method (Foiles et al., 1986;
Daw et al., 1993) which is a semi-empirical, many-atom
approximation describing potential for computing the totalenergy of a metallic system. This model has been appliedby Singh et al. (2014) to describe the energy of interactions
between Si and Ag atoms. The nanoparticles obtained inthis process had a form of Janus or core-satellite particles.
The simulations allowed concluding that the individual
species first form independent clusters of Si and Ag without
significant intermixing. The formation of stable hybrid
structures took place in the subsequent stages of process. In
addition to MD, other models are used in engineering applications, which also boil down to tracking the evolutionof the system by solving equations describing the dynamics
of individual particles included in it. An example of suchmodel is dissipative particle dynamics (DPD)—a coarsegrained model, in which functional groups or polymer
segments are considered as individual “particles” (coarsegrained beads) which interact with each other (Español and
Warren, 1995). The forces acting between beds i and j are
given by the formula:εij 1  rij rc  , rij  rc
Fij rij   f x  
0, rij  rc
(10)

where rij is a distance between beds i and j, rc is a range
of interactions between beds and εij—repulsion parameter,(10)characterizing the magnitude of the force of interaction.
The DPD method has been applied in (Chen H. and
Ruckenstein, 2012) to investigate the formation of complex

colloidal particles formed by self-assembling a three-arm
star-shaped polymer. By using this mathematical apparatus,
pathways for a few kinds of structured particle formation
have been identified, e.g. core-shell, multicore or stacked
layered particle. The control parameters in the model wererepulsion parameters between polymer segments and between polymer segments and solvent particles.
Similar methods can be used to track the movement of
nanoparticles as they are used to create larger particles.
Jabłczyńska et al. (2018) presented an experimental andmodeling study of the formation of structured microparticles by spray drying of a droplet of slurry containing
nanoparticles in one or two sizes. The change of droplet
radius during the first stage of drying has been describedby means of mass and heat balance equations as describedin Sec. 3.1. The motion of nanoparticles inside the droplets
has been tracked by direct solving of their equations of
motion. To take into account the diffusion of nanoparticles
inside the dried droplet, these equations have a form of
overdamped Langevin equations:x  F  x b  Γ t(11)Here b denotes a damping coefficient and Γ(t) is astochastic
component of the motion. This component rep(11)resents a white noise with zeroth mean value, i.e. it fulfills
the conditions:Γ t  0
Γ t1 Γ t 2   2Dδ t1  t 2 

(12a)
(12b)

It has been shown that as a result of spray drying of such
(12a)
droplets,(12b) solid (full) aggregates or hollow particles built
from nanoparticles may appear. Implemented scenario
depends on the process conditions: the temperature of thedrying gas and the initial diameter of the slurry droplets.
In the case of two sizes of primary nanoparticles and theformation of HP, self-organization of nanopraticles inside
the crust may also appear. The larger nanoparticles forma hexagonal pattern while the smaller ones are trapped in
void spaces between larger ones.
The molecular dynamics and related methods should
be considered by far the most accurate models of theformation of structural particles. Indeed, in the case of
these techniques, we directly follow the behavior of atoms,
molecules or nanoparticles—i.e. the “building blocks” thatform an organized particle. The main disadvantage of thisgroup of methods is the long computation time. Especiallyin the case of the original MD method, a very large numberof differential equations should be numerically solved, corresponding to the number of molecules or atoms involvedin the particle synthesis. It should be emphasized that evena small particle consists of many hundreds of thousands
or even millions of atoms or molecules (e.g. Förster et

53

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

al., (2019) conducted simulations for 200,000 atoms).
Another problem may be to formulate a realistic model ofinteractions between atoms and molecules that make up theparticle. Especially when dealing with a composite particle
composed of metal atoms, one should take into account thecomplicated effects resulting from the quantum mechanics
of many bodies. However, it is worth paying attention to
the fact that even a greatly simplified description using the
L-J potential allows obtaining qualitatively (though notnecessarily quantitatively) correct results.
The methods from the group discussed in this section
should be used when interested in a detailed description of
the particle structure. The models presented here allow describing any deviation of the final structure from symmetry.
Also, the analysis of non-equilibrium structures (“failed”
particles, formed under inappropriately selected process
conditions) is possible using these methods (Jabłczyńska
et al., 2018).

3.5 Monte Carlo methods
Monte Carlo (MC) algorithms are another group of
numerical methods which found their application in numerical simulations of structured particles formation. The
beginning of the development of these numerical methods
had its place in the first half of 20th century. However, they
became most popular after the dissemination of computers
in applications for scientific computing. They found an
application not only (and not even most of all) in the simulation of particle formation but also in many branches ofphysics, engineering, biology and even social sciences (e.g.
for modeling of the dynamics of political views in society).
In a broader sense of the term, MC methods are understood as methods that use repeated random sampling to obtain numerical results (Metropolis et al., 1953; Metropolis,
1987). The concept that stands for this method boils down
to the observation that the phenomena occurring in systems
with many degrees of freedom can be described with agood accuracy as random phenomena. A trivial example
is the modeling of diffusion by considering the random
walking of test particles. By tracking these particles, one
may find out, e.g. the dependence of their mean squaredistance on time and thus the diffusion coefficient of theparticle. The extension of this simple method is Kinetic
Monte Carlo (KMC) method which is intended to simulate the time evolution of physical process (Voter et al.,2007). This evolution is realized as a sequence of “jumps”
between individual states of the system. The probabilityof all possible “jumps” is known and thus, the “jumps”
are chosen randomly. Such a sequence of states may givea picture of exemplary realization of the evolution of aprocess. By repeating the simulation as described above, it
is possible to describe the average dynamics of the studied
phenomenon and estimate possible deviations from these54

average dynamics resulting from the random nature of its
description.
The very first applications of MC method in particle
formation modeling concerned particle agglomeration.
Tandon and Rosner (1999) applied a very simple MCbased scheme to find the final size distribution of agglomerates. In the mentioned work, the probability of merging
particles/agglomerates has been set as proportional to the
coagulation kernel (obtained from collision theory). In
every MC step, the pair of particles has been randomly
chosen, then a random number from 0 to 1 has been
generated and compared with the probability of merging.
If the random number was lower than the probability,
the aggregation took place. This simple method allowed
obtaining the size distribution function, which was in good
agreement with the one received by means of experiments
or other numerical methods. Other papers presented theapplication of MC algorithms for modeling the synthesisof nanoparticles from microemulsions (Tojo et al., 1997a;
1997b; 1998) and the formation of the shell in core-shell
nanocrystals in reverse micelle systems (Shukla andMehra, 2006). All these early works focused on obtaining
the size distribution function of the particles rather than on
their internal structure.
Kinetic Monte Carlo method has also been applied formodeling the formation of structured particles. Gorshkov
et al. (2014) have modeled shell formation of core-shell
noble metal nanoparticles with a core made from gold anda shell—from silver or platinum. Based on their earlier
work (Gorshkov et al., 2011), authors have considered the
diffusion of point-like “atoms” (in general, standing foratoms, ions, or molecules) from the solution to the surface
pre-formed core where they were adsorbed to form a shell.
As a result of these simulations, the mean values of theparameters of particles (e.g. shell thickness) have beenobtained. The numerical results appear to be in good agreement with experimental ones.
Another very popular group of MC models which havefound their application for modeling of formation of NMPs
are the Markov chain MC methods (Gilks et al., 1995;
Andrieu et al., 2010). The clue of this conception is toobtain a chain of states of the system so these states havethe desired probability distribution. For typical physical orengineering problems, this equilibrium distribution is theBoltzmann (or canonic) distribution which describes theprobability of appearance of a specific state of the system
as (Creutz et al., 1983):
 E 
pB s  exp   s 
 k BT (13)where s denotes the vector of parameters of state, Es—energy of this state, kB is the Boltzmann constant and(13)
T—temperatureof the system. Generation of a Markov
chain which has the canonic distribution may be done inJakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

many ways. The most popular is the Metropolis–Hastings
algorithm. According to this algorithm, one starts from arandomly chosen state s. To obtain the next state in Markov
chain, the new state s1 is generated by random disturbing ofstate s. The new state is accepted as an element of Markov
chain with probability equal to pB s1 pB s . If a newstate s1 would not be accepted, the previous state s appears
once again in the Markov chain. Then the whole procedure
is repeated. Thus, it can be easily (23)concluded that the stateswith a relatively high probability pB appear in Markov
chain more often than those with low pB.
The works in which Markov chain MC methods wereused to model the formation of particles with internal
structure has appeared since the beginning of the 21st century. The synthesis of composite latex particles of various
morphology by means of two-step emulsion polymerization has been simulated using an MC algorithm (Duda and
Vázquez, 2005). The authors considered a mixture of two
kinds of polymers, A and B and water particles W. Theinteractions between these three types of individuals aredescribed by the very simple scheme:, if r  σ ij
U ij r  
0, if r  σ ij

(14)where Uij denotes the potential energy between interacting
particles, r—the distance between them, indexes i and j(14) polymers A, B or water W. Finally, σ is a diameter
denoteij
of particle i if i = j or, for i ≠ j is defined as σij =0.5(σii + σjj)(1 + ∆ij). The parameter ∆ij > 0 for every pair iand j favors the grouping of particles of the same type andthus separation of the three compounds of the mixture. To
complete the description of the system, the circular domain
is introduced and the energy of every particle which leaves
the domain is also assigned as infinity. The MC simulations
are performed in the classical canonical ensemble. As a result, these simulations lead to (dependently on the concentrations of all the compounds) to various morphologies ofstructured particles: core-shell, sandwich-like, raspberrylike and some other.
When investigating the final structure of structured
NMPs rather than the dynamics of the formation process,MC models have appeared to be more efficient than any
others what has been shown in (Chandross, 2014). In thispaper, the synthesis of core-shell Cu–Ag nanoparticles
has been investigated. Two different methods have been
applied. The first one was MD which has been used to
track every individual Cu and Ag atom during the synthesis
process. The second one was the MC model. The MC
method performed random particle swaps (understood as
the exchange of Cu and Ag atoms at each MC step) witha small random translation below 0.2 Å. The successive
states have been used to construct the Markov chain in themanner described above. The simulations show that the
final state of a particle was achieved in a shorter time with

the MC method than with the molecular dynamics.
While most of the applications of MC algorithms
concern core-shell particle formation—this group of methods is also suitable for modeling the formation of othercomposite particles. In the article by Sdobnyakov et al.
(2020) various morphologies of composite CuNi particles
obtained by the modified solution combustion synthesis in
the air have been analyzed. The MC simulations showed
the patterns of neck formation for various cases of theinitial arrangement of copper and nickel nanoparticles. The
final structures obtained numerically were again in good
agreement with XRD measurements.
MC methods have also been used for modeling theformation of porous particles from self-assembly of amphiphilic block copolymers inside an oil-in-water emulsion
droplet (Zheng L. et al., 2019). The authors of this work
used the MC method to obtain the final structure of suchparticles what allowed to construct the morphologicaldiagram of particles as a function of the surfactant concentration and the copolymer composition (represented by thevolume fraction of the hydrophilic block). They observed,
dependently on simulation parameters, various morphologies of particles: non-porous, particles with closed pores
and opened ones.
Among the many modifications of MC, it is worth noting
the dual population balance Monte Carlo method, whichallows tracking the distributions of two kinds of particles
present in the system. In Skenderović et al. (2018) thismethod has been applied to simulate the particle formation
by means of flame spray pyrolysis, where the solid particles
may form from the gas phase or by means of droplet drying.
As shown, the MC models are widely used to investigate
structures of NMPs synthesized in many processes. The
main field of application of this group of methods is themulti-component systems. MC models are then used forthe investigation of the formation of, e.g., composite or
core-shell particles. When we are interested in the structureof resulting particles, the group of MC methods seems tobe the most suitable tool. However, using these methods
makes it difficult to track the dynamics of the synthesis
and determine the structure of transitional states. This issue
may be approached to a certain extent by the use of kinetic
Monte Carlo methods. When we are interested in synthesis
dynamics rather than in final structures, other numericalmethods are worth considering.

3.6 Other approaches
The previous sections discussed the most popular numerical models for the synthesis of structured NMPs. In
addition to these popular models, each of which has been
described and used in at least a few scientific papers—there
exist also some other models of formation of structured
particles. These models were usually less versatile and55

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

were constructed ad hoc to describe a specific process that
resulted in forming particles with a well-defined structure.
The possibilities of generalizing such models to othercases of organized particle synthesis are relatively little.
In this section, one of these less common models will bepresented because of their originality, clever constructionor the importance of the process they describe.
Specific methods have to be applied for the simulationof the synthesis of HPs by means of colloidal templating
methods. As already mentioned, the starting point for thesemethods is the synthesis of CSPs followed by the removalof the core using physical phenomena such as Ostwald ripening or the Kirkendall effect. The first of these phenomenais the mass transport from smaller particles (grouped within
the core) to larger ones, which make up the outer layers of
the primary particle (Zeng, 2007). This process is theoretically described by the following continuity equation:
N  L 

N
0
t
L  t (15)

Various methods of solution of Eqn. (15) are reviewed in(Baldan, 2002).
(15)
Kirkendall effect is the motion of the interface between
two substances (usually metals) that occurs as a consequence of the difference in diffusion rates of the atoms ofboth kinds. This leads to the formation of vacancies between
core and shell and shrinkage of the core and finally HPs (oryolk-shell particles). Therefore, since this phenomenon isbased on diffusion processes, the Kirkendall effect models
boil down to numerical solving of the diffusion equationsof both components under geometrical conditions imposedby the shape and size of the originally formed CSP. Froma numerical point of view, applied numerical schemes andmethods are typical, e.g. finite difference methods (Gusak
and Tu, 2009; Jana et al., 2013), the variational method of
calculating the chemical potential of the atoms diffusing
along with the core–shell boundary (Klinger et al., 2015)or the thermodynamic extremal principle which minimizes
Gibbs free energy (Svoboda et al., 2009). Energy considerations have also been applied to the investigation of
random shape fluctuations during the formation of HP from
CSP by Kirkendall effect in room temperature (Erlebacher
and Margetis, 2014). It has been (qualitatively only) shownthat surface thickness fluctuations of the shell are highly
probable at room temperature and may lead to exposure of
the core as a result of arising of some pinholes. When coredissolves, pinholes quickly close and classic HP is formed.
For considerations of process dynamics and final structures of porous particles, the class of models which may
be named “topological” has been formulated. This class isbased on elementary laws of topology. Papers presenting
this approach (Gradoń et al., 2004; Lee et al., 2010) investigate the formation of porous silica particles by means ofspray drying of a mixture of silica and polystyrene latex

56(PSL) colloids above the decomposition temperature of
PSL. PSL nanoparticles are much larger than silica ones
and during the first stage of drying, they take such positions
that the mutual distances between them are as large as possible. As long as their number in a single drop is properly
selected, they are the vertices of regular polyhedron, e.g.
when there are four PSL particles in a dried drop, their
dots will form a regular tetrahedron. In the second stage ofdrying, pores (cavities) will be formed in these places dueto the thermal decomposition of PSL.
Modeling of the formation of virus capsids has beendeveloped since 1990s. First works in this subject (Zlotnick
et al., 1994) applied the formalism similar to PBEs to de­scribe the dynamics of merging of protein subunits to form
icosahedral capsid. The described model assumes that theprotein aggregates may join or dissociate. However, at eachstage the appropriate value of the angle between the subunits is maintained—the same as the value of the doublewall angle in the icosahedra. Based on this approach, thekinetics of the concentration of all transition structures andcomplete capsids in time is determined. This approach tomodeling the kinetics of capsid formation dominates theworks in this field - sometimes KMC methods are used instead of PBEs (Kivenson and Hagan, 2010). In both cases,
it is crucial to know the energy of interaction between
protein subunits. For the formation of viruses with different shapes of capsid, e.g. tobacco mosaic virus, models
more suited to their topology were elaborated. E.g. for the
tobacco mosaic virus mentioned above, it is the so-called“zipper model” (Kraft et al., 2012). This model assumes
the elongation of rod-like virus capsid by random bindingof protein subunits along the helical line. In recent years
works dealing with multiscale modeling of capsids formation (Wang B. et al., 2019) have appeared. Besides protein
subunits merging modeling, these models also consider theprotein conformation changes, what is done by means of
MD-based methods.
Recently, multi-scale models and models combining
several approaches described earlier have been gaining
popularity. E.g. Buesser and Pratsinis (2011) proposed thesimulation of gas-phase synthesis of CSPs (TiO2-SiO2) bycoupling of CFD with tracking of single particle motion.
An example of the application of multiscale model may
be found in (Xiao and Chen, 2014). For simulation ofsynthesis of two components particles in the spray drying
process, the molecular-level model has been coupled with acontinuum diffusion approach. The latter description gave
the information about the segregation of components inthe particle, while the microscopic one allowed describing
the composition of single molecules at the particle surface.
Similar multi-scale model, basing on CFD has been also
applied for modeling of TiO2 structured nanoparticles bymeans of FSP (Torabmostaedi and Zhang T., 2018).

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

4. Conclusions and perspectives
Along with the progress of research on structured particles, their synthesis and application, the development of
numerical methods and models is progressing, allowing
predicting the kinetics of formation and properties of theseparticles. This subject is still new, which is due to the factthat numerical modeling of the synthesis of structural
particles, firstly, required appropriate computing powerof computers, and secondly—the development of proper
methods of particle characterization, enabling the verification of the results of numerical simulations. In recent years,
many numerical descriptions of the synthesis of particles
with a given structure have been created and are still being
prepared.
The most popular are (i) methods based on the numericalsolution of the differential equations of mass and energy,(ii) closely related multi-layer methods, (iii) the molecular
dynamics method and other methods allowing for tracking
individual atoms, groups of atoms or molecules joining
a particle, (iv) methods based on population balance
equations; and (v) Monte Carlo methods. The choice ofthe method that will be used to describe and optimize a
specific process for obtaining structured particles depends
mainly on the properties of the particles to be described inthis process. Table 1 presents the possibilities of using thefive most popular methods mentioned above to describe
the synthesis of structural particles of various structures.
As this table shows, molecular dynamics method and similar methods seem to be the most universal. Monte Carlo
methods have an almost equally wide range of applications.
It should be expected that in the near future, these methods
will be most often used to simulate the NMPs synthesis
processes and will be most intensively developed.
The greatest disadvantage of using these two mostpopular methods, i.e. the relatively long computation time
Table 1 Usefulness of most popular numerical models for modelingthe synthesis of particles with a specific structure.

Model

HP

CSP

JPs and othercomposite

HMB equations

++

+

−

multiple shells

++

+

−

PBEs

++

−

−

MD and related

++

++

++

MC

+

++

++

++ Model has been successfully applied to simulation ofsynthesis of this kind of particles.
+ Model might be potentially applied to simulation ofsynthesis of this kind of particles but there are no (or single)
papers showing that.
− Model cannot be applied to simulation of synthesis of thiskind of particles.

and the high degree of complexity of the mathematical
apparatus, has prompted and will probably continue toencourage scientists to develop other, less universal, but
simpler models for the synthesis of particles with a specificstructure. Models are used primarily by practitioners andexperimenters to support their experiences. It is worth continuing to use these types of models where possible, being
aware, however, that their use is limited to the assumptions
made.

Acknowledgement
The author would like to thank Katarzyna Jabłczyńska
of the Warsaw University of Technology for her valuable
discussions on this topic.

Nomenclature
Abbreviations
CFD computational fluid dynamics
CSP core-shell particle
DPD dissipative particle dynamics
FSP flame spray pyrolysis
HMB heat and mass balanceHPhollow particle
JP
Janus particle
KMC kinetic Monte Carlo method
L-J
Lennard-Jones potential
MC Monte Carlo method
MD molecular dynamics
NMPs nano- and microparticles
PBE population balance equation
PSL polystyrene latex
Latin symbols
droplet surface (m 2)Adbdamping coefficient in Langevin equation (kg/s)
concentration of solute A inside the droplet (kg/m3, mol/cA
m3 or other concentration units)DA, D diffusion coefficient (m 2/s)
energy of the microscopic state (J/mol)
Es
F, F force (N)G
linear growth rate of particles/cluster (m/s)
heat transfer coefficient (W/m 2/K)
hc
mass transfer coefficient (m/s)
hD
Boltzmann constant (kB = 1.38064852 × 10 –23 J/K)
kB
L
particle internal coordinate (in PBE) – size (m)heat of evaporation (J/kg)
Lhmmass (kg)mass flux (kg/s)
ṁvN
particle number density function (m–3)
Ppressure (Pa)probability (-)
pB
Rnormalized radial coordinate (-)

57

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

r
rc
rd
rij

radial coordinate (m)range of interactions between beds (m)radius of a droplet (m)distance between individuals (atoms, molecules, particles) i and j (m)s, s1 vector of parameters of state (various units)ttime (s)Ttemperature (K)temperature of a droplet (K)Tdtemperature of ambient (K)T∞potential energy of interactions between individuals
Uij(atoms, molecules, particles) i and j (J)xposition (m)Greek symbols
Γ(t)stochastic component in Langevin equation (m/s)δ
Dirac δ-function
parameter describing interactions between individuals
εij(atoms, molecules, particles) i and j (various units)
λheat conductivity (W/m/K)
solvent density (kg/m3)
ρdsaturated solvent vapor concentration (kg/m3)
ρv,ssolvent vapor concentration in the ambient (kg/m3)
ρv,∞
a range of interaction between individuals (atoms, moleσij
cules, particles) i and j (m)References
Adhikari B., Howes T., Bhandari B.R., Use of solute fixed
coordinate system and method of lines for prediction ofdrying kinetics and surface stickiness of single droplet during
convective drying, Chemical Engineering and Processing:Process Intensification, 46 (2007) 405–419. DOI: 10.1016/j.
cep.2006.06.018
Andrieu C., Doucet A., Holenstein R., Particle Markov chain
Monte Carlo methods, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72 (2010) 269–342.
DOI: 10.1111/j.1467-9868.2009.00736.x
Aryal S., Park H., Leary J.F., Key J., Top-down fabrication-based
nano/microparticles for molecular imaging and drugdelivery, International Journal of Nanomedicine, 14 (2019)
6631–6644. DOI: 10.2147/IJN.S212037
Aul’chenko S., Kartaev E., Numerical simulation of the synthesisof titania-silica composite nanoparticles in plasmachemical
reactor, AIP Conference Proceedings, 2027 (2018) 040002.
DOI: 10.1063/1.5065276
Baldan A., Review progress in Ostwald ripening theories andtheir applications to nickel-base superalloys Part I: Ostwald
ripening theories, Journal of Materials Science, 37 (2002)
2171–2202. DOI: 10.1023/a:1015388912729
Betke A., Kickelbick G., Bottom-up, wet chemical technique forthe continuous synthesis of inorganic nanoparticles, Inorganics, 2 (2014) 1–15. DOI: 10.3390/inorganics2010001
Blackburn T., Alexander C.M.O., Carlson R., Elkins-Tanton L.T.,
The accretion and impact history of the ordinary chondrite
parent bodies, Geochimica et Cosmochimica Acta, 200(2017) 201–217. DOI: 10.1016/j.gca.2016.11.038
Boraey M.A., Vehring R., Diffusion controlled formation of
microparticles, Journal of Aerosol Science, 67 (2014)
131–143. DOI: 10.1016/j.jaerosci.2013.10.002

58

Bück A., Peglow M., Naumann M., Tsotsas E., Population
balance model for drying of droplets containing aggregating
nanoparticles, AIChE Journal, 58 (2012) 3318–3328. DOI:
10.1002/aic.13726
Buesser B., Pratsinis S.E., Design of gas-phase synthesis ofcore-shell particles by computational fluid–aerosol dynamics, AIChE Journal, 57 (2011) 3132–3142. DOI: 10.1002/
aic.12512
Caruso F., Caruso R.A., Möhwald H., Nanoengineering of
inorganic and hybrid hollow spheres by colloidal templating, Science, 282 (1998) 1111–1114. DOI: 10.1126/
science.282.5391.1111
Chandross M., Energetics of the formation of Cu–Ag core–shell
nanoparticles, Modelling and Simulation in Materials Scienceand Engineering, 22 (2014) 075012. DOI: 10.1088/09650393/22/7/075012
Chen H., Ruckenstein E., Formation of complex colloidal particles: morphologies and mechanisms, Soft Matter, 8 (2012)
8911–8916. DOI: 10.1039/C2SM26035B
Chen X.D., Sidhu H., Nelson M., Theoretical probing of thephenomenon of the formation of the outermost surface layerof a multi-component particle, and the surface chemicalcomposition after the rapid removal of water in spray drying,
Chemical Engineering Science, 66 (2011) 6375–6384. DOI:
10.1016/j.ces.2011.08.035
Chiarello G.L., Selli E., Forni L., Photocatalytic hydrogenproduction over flame spray pyrolysis-synthesised TiO2 andAu/TiO2, Applied Catalysis B: Environmental, 84 (2008)
332–339. DOI: 10.1016/j.apcatb.2008.04.012
Creutz M., Microcanonical Monte Carlo simulation, PhysicalReview Letters, 50 (1983) 1411–1414. DOI: 10.1103/
PhysRevLett.50.1411
Czelej K., Colmenares J.C., Jabłczyńska K., Ćwieka K., Werner
Ł., Gradoń L., Sustainable hydrogen production by plasmonic thermophotocatalysis, Catalysis Today, (2021). DOI:
10.1016/j.cattod.2021.02.004
Daw M.S., Foiles S.M., Baskes M.I., The embedded-atom
method: a review of theory and applications, Materials
Science Reports, 9 (1993) 251–310. DOI: 10.1016/09202307(93)90001-U
de Gennes P.G., Soft matter, Science, 256 (1992) 495–497. DOI:
10.1126/science.256.5056.495
Demirörs A.F., van Blaaderen A., Imhof A., Synthesis of eccentric
titania−silica core−shell and composite particles, Chemistryof Materials, 21 (2009) 979–984. DOI: 10.1021/cm803250w
de Souza Lima R., Ré M.I., Arlabosse P., Drying droplet as atemplate for solid formation: a review, Powder Technology,
359 (2020) 161–171. DOI: 10.1016/j.powtec.2019.09.052
Duda Y., Vázquez F., Modeling of composite latex particle morphology by off-lattice Monte Carlo simulation, Langmuir, 21(2005) 1096–1102. DOI: 10.1021/la048065t
Erlebacher J., Margetis D., Mechanism of hollow nanoparticle
formation due to shape fluctuations, Physical Review Letters,
112 (2014) 155505. DOI: 10.1103/PhysRevLett.112.155505
Eslamian M., Ahmed M., Ashgriz N., Modelling of nanoparticle
formation during spray pyrolysis, Nanotechnology, 17 (2006)
1674–1685. DOI: 10.1088/0957-4484/17/6/023
Español P., Warren P., Statistical mechanics of dissipative particle
dynamics, Europhysics Letters (EPL), 30 (1995) 191–196.
DOI: 10.1209/0295-5075/30/4/001
Fan H.J., Gösele U., Zacharias M., Formation of nanotubes andhollow nanoparticles based on Kirkendall and diffusion processes: a review, Small, 3 (2007) 1660–1671. DOI: 10.1002/
smll.200700382
Fernandez Y.A.D., A. Gschneidtner T., Wadell C., H. FornanderJakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

L., Avila S.L., Langhammer C., Westerlund F., Moth-Poulsen
K., The conquest of middle-earth: combining top-down andbottom-up nanofabrication for constructing nanoparticle
based devices, Nanoscale, 6 (2014) 14605–14616. DOI:
10.1039/C4NR03717K
Foiles S.M., Baskes M.I., Daw M.S., Embedded-atom-method
functions for the fcc metals Cu, Ag, Au, Ni, Pd, Pt, and their
alloys, Physical Review B, 33 (1986) 7983–7991. DOI:
10.1103/PhysRevB.33.7983
Förster G.D., Benoit M., Lam J., Alloy, Janus and core–shell
nanoparticles: numerical modeling of their nucleationand growth in physical synthesis, Physical Chemistry
Chemical Physics, 21 (2019) 22774–22781. DOI: 10.1039/
C9CP04231H
Gac J.M., Gradoń L., A distributed parameter model for the spraydrying of multicomponent droplets with a crust formation,
Advanced Powder Technology, 24 (2013a) 324–330. DOI:
10.1016/j.apt.2012.08.004
Gac J.M., Gradoń L., A distributed parameter model for the drying of multicomponent aerosol and sessile droplets, Chemical
Engineering Transactions, 32 (2013b) 1927–1932. DOI:
10.3303/CET1332322
Ghosh Chaudhuri R., Paria S., Core/shell nanoparticles: classes,
properties, synthesis mechanisms, characterization, andapplications, Chemical Reviews, 112 (2012) 2373–2433.
DOI: 10.1021/cr100449n
Gilks W.R., Richardson S., Spiegelhalter D., Markov Chain Monte
Carlo in Practice, CRC Press, 1995, ISBN: 9780412055515.
Gorshkov V., Kuzmenko V., Privman V., Modeling of growthmorphology of core–shell nanoparticles, The Journal of
Physical Chemistry C, 118 (2014) 24959–24966. DOI:
10.1021/jp506331u
Gorshkov V., Zavalov O., Atanassov P.B., Privman V., Morphology of nanoclusters and nanopillars formed in nonequilibrium surface growth for catalysis applications, Langmuir, 27(2011) 8554–8561. DOI: 10.1021/la103113f
Gradoń L., Janeczko S., Abdullah M., Iskandar F., Okuyama K.,
Self-organization kinetics of mesoporous nanostructured particles, AIChE Journal, 50 (2004) 2583–2593. DOI: 10.1002/
aic.10257
Grasmeijer N., Frijlink H.W., Hinrichs W.L.J., An adaptablemodel for growth and/or shrinkage of droplets in the respiratory tract during inhalation of aqueous particles, Journalof Aerosol Science, 93 (2016a) 21–34. DOI: 10.1016/j.
jaerosci.2015.11.011
Grasmeijer N., Frijlink H.W., Hinrichs W.L.J., Model to predict
inhomogeneous protein–sugar distribution in powders
prepared by spray drying, Journal of Aerosol Science, 101(2016b) 22–33. DOI: 10.1016/j.jaerosci.2016.07.012
Gusak A.M., Tu K.N., Interaction between the Kirkendall effectand the inverse Kirkendall effect in nanoscale particles,
Acta Materialia, 57 (2009) 3367–3373. DOI: 10.1016/j.
actamat.2009.03.043
Hadiko G., Han Y.S., Fuji M., Takahashi M., Synthesis of hollow
calcium carbonate particles by the bubble templating method,
Materials Letters, 59 (2005) 2519–2522. DOI: 10.1016/j.
matlet.2005.03.036
Hamzehlou S., Leiza J.R., Asua J.M., A new approach formathematical modeling of the dynamic development of particle morphology, Chemical Engineering Journal, 304 (2016)
655–666. DOI: 10.1016/j.cej.2016.06.127
Handscomb C.S., Kraft M., Bayly A.E., A new model for the
drying of droplets containing suspended solids after shell formation, Chemical Engineering Science, 64 (2009a) 228–246.
DOI: 10.1016/j.ces.2008.10.019

Handscomb C.S., Kraft M., Bayly A.E., A new model for the
drying of droplets containing suspended solids, Chemical
Engineering Science, 64 (2009b) 628–637. DOI: 10.1016/j.
ces.2008.04.051
Hao X., Zhao H., Xu Z., Zheng C., Population balance-Monte
Carlo simulation for gas-to-particle synthesis of nanoparticles, Aerosol Science and Technology, 47 (2013) 1125–1133.
DOI: 10.1080/02786826.2013.823642
Hayes R., Ahmed A., Edge T., Zhang H., Core–shell particles:
preparation, fundamentals and applications in high performance liquid chromatography, Journal of Chromatography
A, 1357 (2014) 36–52. DOI: 10.1016/j.chroma.2014.05.010
Jabłczyńska K., Gac J.M., Sosnowski T.R., Self-organizationof colloidal particles during drying of a droplet: modelingand experimental study, Advanced Powder Technology, 29(2018) 3542–3551. DOI: 10.1016/j.apt.2018.09.036
Jana S., Chang J.W., Rioux R.M., Synthesis and modeling of
hollow intermetallic Ni–Zn nanoparticles formed by the
Kirkendall effect, Nano Letters, 13 (2013) 3618–3625. DOI:
10.1021/nl401467r
Kellerman D.W., Review of low dielectric constant thick film
electronic ceramics using hollow microspheres, MRS
Proceedings, 372 (2011) 239. DOI: 10.1557/PROC-372-239
Kivenson A., Hagan M.F., Mechanisms of capsid assembly
around a polymer, Biophysical Journal, 99 (2010) 619–628.
DOI: 10.1016/j.bpj.2010.04.035
Klinger L., Kraft O., Rabkin E., A model of Kirkendall hollowingof core–shell nanowires and nanoparticles controlled byshort-circuit diffusion, Acta Materialia, 83 (2015) 180–186.
DOI: 10.1016/j.actamat.2014.09.050
Kraft D.J., Kegel W.K., van der Schoot P., A kinetic zipper modeland the assembly of tobacco mosaic virus, Biophysical Journal, 102 (2012) 2845–2855. DOI: 10.1016/j.bpj.2012.05.007
Larbi Z., Sadoun N., Si-Ahmed E., Legrand J., An efficient numerical prediction of the crust onset of a drying colloidal drop,
International Journal of Heat and Mass Transfer, 165 (2021)
120613. DOI: 10.1016/j.ijheatmasstransfer.2020.120613
Lee S.Y., Gradon L., Janeczko S., Iskandar F., Okuyama K., Formation of highly ordered nanostructures by drying micrometer colloidal droplets, ACS Nano, 4 (2010) 4717–4724. DOI:
10.1021/nn101297c
Lenggoro I.W., Hata T., Iskandar F., Lunden M.M., Okuyama
K., An experimental and modeling investigation of particle
production by spray pyrolysis using a laminar flow aerosol
reactor, Journal of Materials Research, 15 (2000) 733–743.
DOI: 10.1557/jmr.2000.0106
Lesov I., Valkova Z., Vassileva E., Georgiev G.S., Ruseva K.,
Simeonov M., Tcholakova S., Denkov N.D., Smoukov S.K.,
Bottom-up synthesis of polymeric micro- and nanoparticles
with regular anisotropic shapes, Macromolecules, 51 (2018)
7456–7462. DOI: 10.1021/acs.macromol.8b00529
Levchenko E.V., Evteev A.V., Riley D.P., Belova I.V., Murch G.E.,
Molecular dynamics simulation of the alloying reaction in
Al-coated Ni nanoparticle, Computational Materials Science,
47 (2010) 712–720. DOI: 10.1016/j.commatsci.2009.10.014
Levi-Hevroni D., Levy A., Borde I., Mathematical modeling ofdrying of liquid/solid slurries in steady state one-dimensional
flow, Drying Technology, 13 (1995) 1187–1201. DOI:
10.1080/07373939508917016
Lin C.-C., Liao C.-W., Chao Y.-C., Kuo C., Fabrication andcharacterization of asymmetric Janus and ternary particles,
ACS Applied Materials & Interfaces, 2 (2010) 3185–3191.
DOI: 10.1021/am1006589
Liu B., Hu X., Chapter 1—Hollow micro- and nanomaterials:
synthesis and applications, in: Zhao Q. (Ed.), Advanced59

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

Nanomaterials for Pollutant Sensing and Environmental
Catalysis, Elsevier, 2020, pp. 1–38. DOI: 10.1016/B978-012-814796-2.00001-0
Liu Q., Wu Y., Xing F., Liu Q., Guo X., Huang C., B2O3@
BPO4 sandwich-like hollow spheres as metal-free supported
liquid-phase catalysts, Journal of Catalysis, 381 (2020)
599–607. DOI: 10.1016/j.jcat.2019.11.028
Liu Y., Abetz V., Müller A.H.E., Janus cylinders, Macromolecules, 36 (2003) 7894–7898. DOI: 10.1021/ma0345551
Lou X.W. (David), Archer L.A., Yang Z., Hollow micro-/nanostructures: synthesis and applications, Advanced Materials,
20 (2008) 3987–4019. DOI: 10.1002/adma.200800854
Mädler L., Kammler H.K., Mueller R., Pratsinis S.E., Controlled
synthesis of nanostructured particles by flame spray pyrolysis, Journal of Aerosol Science, 33 (2002) 369–389. DOI:
10.1016/S0021-8502(01)00159-8
Mao Y., Park T.-J., Wong S.S., Synthesis of classes of ternary
metal oxide nanostructures, Chemical Communications,(2005) 5721–5735. DOI: 10.1039/B509960A
Maurice U., Mezhericher M., Levy A., Borde I., Particle formation from droplet containing nanoparticles: internal bubble
growth, Drying Technology, 35 (2017) 969–984. DOI:
10.1080/07373937.2016.1263647
Metropolis N., The beginning of the Monte Carlo method, Los
Alamos Science, 15 (1987) 125–130.
Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H.,
Teller E., Equation of state calculations by fast computing
machines, The Journal of Chemical Physics, 21 (1953)
1087–1092. DOI: 10.1063/1.1699114
Mezhericher M., Levy A., Borde I., Theoretical drying modelof single droplets containing insoluble or dissolved
solids, Drying Technology, 25 (2007) 1025–1032. DOI:
10.1080/07373930701394902
Mezhericher M., Levy A., Borde I., Heat and mass transfer ofsingle droplet/wet particle drying, Chemical Engineering
Science, 63 (2008) 12–23. DOI: 10.1016/j.ces.2007.08.052
Mezhericher M., Levy A., Borde I., Theoretical models of single
droplet drying kinetics: a review, Drying Technology, 28(2010) 278–293. DOI: 10.1080/07373930903530337
Mezhericher M., Levy A., Borde I., Modelling the morphologicalevolution of nanosuspension droplet in constant-rate drying
stage, Chemical Engineering Science, 66 (2011) 884–896.
DOI: 10.1016/j.ces.2010.11.028
Mezhericher M., Naumann M., Peglow M., Levy A., Tsotsas
E., Borde I., Continuous species transport and population
balance models for first drying stage of nanosuspension droplets, Chemical Engineering Journal, 210 (2012) 120–135.
DOI: 10.1016/j.cej.2012.08.038
Miller K., A geometrical-mechanical interpretation of gradientweighted moving finite elements, SIAM Journal on
Numerical Analysis, 34 (1997) 67–90. DOI: 10.1137/
S0036142994260884
Mohanty U.S., Electrodeposition: a versatile and inexpensive tool
for the synthesis of nanoparticles, nanorods, nanowires, andnanoclusters of metals, Journal of Applied Electrochemistry,
41 (2011) 257–270. DOI: 10.1007/s10800-010-0234-3
Mourdikoudis S., Chirea M., Zanaga D., Altantzis T., Mitrakas M.,
Bals S., Liz-Marzán L.M., Pérez-Juste J., Pastoriza-Santos I.,
Governing the morphology of Pt–Au heteronanocrystals withimproved electrocatalytic performance, Nanoscale, 7 (2015)
8739–8747. DOI: 10.1039/C4NR07481E
Moyano E.A., Scarpettini A.F., Numerical stability study anderror estimation for two implicit schemes in a moving boundary problem, Numerical Methods for Partial Differential
Equations, 16 (2000) 42–61. DOI: 10.1002/(SICI)1098-

60

2426(200001)16:1<42::AID-NUM4>3.0.CO;2-L
Parienta D., Morawska L., Johnson G.R., Ristovski Z.D.,
Hargreaves M., Mengersen K., Corbett S., Chao C.Y.H., Li
Y., Katoshevski D., Theoretical analysis of the motion andevaporation of exhaled respiratory droplets of mixed composition, Journal of Aerosol Science, 42 (2011) 1–10. DOI:
10.1016/j.jaerosci.2010.10.005
Ren Y., Cai J., Pitsch H., Theoretical single-droplet model for particle formation in flame spray pyrolysis, Energy & Fuels, 35(2021) 1750–1759. DOI: 10.1021/acs.energyfuels.0c03669
Sdobnyakov N., Khort A., Myasnichenko V., Podbolotov K.,
Romanovskaia E., Kolosov A., Sokolov D., Romanovski
V., Solution combustion synthesis and Monte Carlo simulation of the formation of CuNi integrated nanoparticles,
Computational Materials Science, 184 (2020) 109936. DOI:
10.1016/j.commatsci.2020.109936
Shabde V.S., Emets S.V., Mann U., Hoo K.A., Carlson N.N.,
Gladysz G.M., Modeling a hollow micro-particle production
process, Computers & Chemical Engineering, 29 (2005)
2420–2428. DOI: 10.1016/j.compchemeng.2005.05.019
Shukla D., Mehra A., Modeling shell formation in core−shell
nanocrystals in reverse micelle systems, Langmuir, 22 (2006)
9500–9506. DOI: 10.1021/la061499z
Singh V., Cassidy C., Grammatikopoulos P., Djurabekova F.,
Nordlund K., Sowwan M., Heterogeneous gas-phase synthesis and molecular dynamics modeling of Janus and core–satellite Si–Ag nanoparticles, The Journal of Physical Chemistry C, 118 (2014) 13869–13875. DOI: 10.1021/jp500684y
Skenderović I., Kotalczyk G., Kruis F.E., Dual population balanceMonte Carlo simulation of particle synthesis by flame spraypyrolysis, Processes, 6 (2018) 253. DOI: 10.3390/pr6120253
Song P., Wen D., Molecular dynamics simulation of a core−shellstructured metallic nanoparticle, The Journal of Physical
Chemistry C, 114 (2010) 8688–8696. DOI: 10.1021/
jp908788b
Sun X., Han J., Guo R., A mini review on yolk-shell structured
nanocatalysts, Frontiers in Chemistry, 8 (2020). DOI:
10.3389/fchem.2020.606044
Svoboda J., Fischer F.D., Vollath D., Modeling of formationof binary-phase hollow nanospheres from metallic solid
nanospheres, Acta Materialia, 57 (2009) 1912–1919. DOI:
10.1016/j.actamat.2008.12.038
Swihart M.T., Vapor-phase synthesis of nanoparticles, Current
Opinion in Colloid & Interface Science, 8 (2003) 127–133.
DOI: 10.1016/S1359-0294(03)00007-4
Tandon P., Rosner D.E., Monte Carlo simulation of particle aggregation and simultaneous restructuring, Journal of Colloid
and Interface Science, 213 (1999) 273–286. DOI: 10.1006/
jcis.1998.6036
Tojo C., Blanco M.C., López-Quintela M.A., Preparation of
nanoparticles in microemulsions: a Monte Carlo study of theinfluence of the synthesis variables, Langmuir, 13 (1997a)
4527–4534. DOI: 10.1021/la9606207
Tojo C., Blanco M.C., López-Quintela M.A., Microemulsions as
microreactors: a Monte Carlo simulation on the synthesis ofparticles, Journal of Non-Crystalline Solids, 235–237 (1998)
688–691. DOI: 10.1016/S0022-3093(98)00572-9
Tojo C., Blanco M.C., Rivadulla F., López-Quintela M.A.,
Kinetics of the formation of particles in microemulsions,Langmuir, 13 (1997b) 1970–1977. DOI: 10.1021/la9607870
Torabmostaedi H., Zhang T., Numerical simulation of TiO2
nanoparticle synthesis by flame spray pyrolysis, Powder
Technology, 329 (2018) 426–433. DOI: 10.1016/j.powtec.
2018.01.051
Tsotsas E., Influence of drying kinetics on particle formation:

Jakub M. Gac / KONA Powder and Particle Journal No. 39 (2022) 45–61

a personal perspective, Drying Technology, 30 (2012)
1167–1175. DOI: 10.1080/07373937.2012.685139
Tu K.N., Gösele U., Hollow nanostructures based on the Kirkendall effect: design and stability considerations, Applied
Physics Letters, 86 (2005) 093111. DOI: 10.1063/1.1873044
Vasiliauskas R., Liu D., Cito S., Zhang H., Shahbazi M.-A.,
Sikanen T., Mazutis L., Santos H.A., Simple microfluidic
approach to fabricate monodisperse hollow microparticles
for multidrug delivery, ACS Applied Materials & Interfaces,
7 (2015) 14822–14832. DOI: 10.1021/acsami.5b04824
Vehring R., Pharmaceutical particle engineering via spray drying, Pharmaceutical Research, 25 (2008) 999–1022. DOI:
10.1007/s11095-007-9475-1
Vehring R., Foss W.R., Lechuga-Ballesteros D., Particle formation in spray drying, Journal of Aerosol Science, 38 (2007)
728–746. DOI: 10.1016/j.jaerosci.2007.04.005
Verma S., Gokhale R., Burgess D.J., A comparative study of topdown and bottom-up approaches for the preparation of micro/
nanosuspensions, International Journal of Pharmaceutics,
380 (2009) 216–222. DOI: 10.1016/j.ijpharm.2009.07.005
Vetter T., Iggland M., Ochsenbein D.R., Hänseler F.S., MazzottiM., Modeling nucleation, growth, and Ostwald ripening in
crystallization processes: a comparison between population
balance and kinetic rate equation, Crystal Growth & Design,
13 (2013) 4890–4905. DOI: 10.1021/cg4010714
Voter A.F., Introduction to Kinetic Monte Carlo Method, in:Sickafus K.E., Kotomin E.A., Uberuaga B.P. (Eds.), Radi­
ation Effects in Solids, Springer Netherlands, Dordrecht,
2007, pp. 1–23. DOI: 10.1007/978-1-4020-5295-8_1
Walther A., André X., Drechsler M., Abetz V., Müller A.H.E.,
Janus discs, Journal of the American Chemical Society, 129(2007) 6187–6198. DOI: 10.1021/ja068153v
Walther A., Müller A.H.E., Janus particles: synthesis, selfassembly, physical properties, and applications, chemical
Reviews, 113 (2013) 5194–5261. DOI: 10.1021/cr300089t
Wang B., Zhang J., Wu Y., A multiscale model for the selfassembly of coat proteins in bacteriophage MS2, Journal ofChemical Information and Modeling, 59 (2019) 3899–3909.
DOI: 10.1021/acs.jcim.9b00514
Wang S., Langrish T.A.G., A distributed parameter model forparticles in the spray drying process, Advanced Powder Technology, 20 (2009) 220–226. DOI: 10.1016/j.apt.2009.03.004
Wang X., Barber W.E., Long W.J., Applications of superficiallyporous particles: High speed, high efficiency or both?,
Journal of Chromatography A, 1228 (2012) 72–88. DOI:
10.1016/j.chroma.2011.07.083
Wang X., Feng J., Bai Y., Zhang Q., Yin Y., Synthesis, properties,

and applications of hollow micro-/nanostructures, Chemical
Reviews, 116 (2016) 10983–11060. DOI: 10.1021/acs.
chemrev.5b00731
Weiss B.P., Elkins-Tanton L.T., Differentiated planetesimals andthe parent bodies of chondrites, Annual Review of Earthand Planetary Sciences, 41 (2013) 529–560. DOI: 10.1146/
annurev-earth-040610-133520
Wichaita W., Polpanich D., Tangboriboonrat P., Review on
synthesis of colloidal hollow particles and their applications,
Industrial & Engineering Chemistry Research, 58 (2019)
20880–20901. DOI: 10.1021/acs.iecr.9b02330
Wu B.-H., Chung C.A., Modeling and simulation of solidcontaining droplet drying and different-structure particle
formation, International Journal of Heat and Mass Transfer,
152 (2020) 119469. DOI: 10.1016/j.ijheatmasstransfer.2020.
119469
Xiao J., Chen X.D., Multiscale modeling for surface compositionof spray-dried two-component powders, AIChE Journal, 60(2014) 2416–2427. DOI: 10.1002/aic.14452
Yang S.-M., Kim S.-H., Lim J.-M., Yi G.-R., Synthesis andassembly of structured colloidal particles, Journal of
Materials Chemistry, 18 (2008) 2177–2190. DOI: 10.1039/
B716393B
Yang Z., Yang X., Xu Z., Molecular dynamics simulation of themelting behavior of Pt−Au nanoparticles with core−shellstructure, The Journal of Physical Chemistry C, 112 (2008)
4937–4947. DOI: 10.1021/jp711702y
Ye G., Sun Y., Zhou X., Zhu K., Zhou J., Coppens M.-O., Method
for generating pore networks in porous particles of arbitrary
shape, and its application to catalytic hydrogenation ofbenzene, Chemical Engineering Journal, 329 (2017) 56–65.
DOI: 10.1016/j.cej.2017.02.036
Zeng H.C., Ostwald ripening: a synthetic approach for hollow
nanomaterials, Current Nanoscience, 3 (2007) 177–181.
DOI: 10.2174/157341307780619279
Zhang Q., Wang W., Goebl J., Yin Y., Self-templated synthesis ofhollow nanostructures, Nano Today, 4 (2009) 494–507. DOI:
10.1016/j.nantod.2009.10.008
Zheng L., Wang Z., Yin Y., Jiang R., Li B., Formation mech­anisms of porous particles from self-assembly of amphiphilic
diblock copolymers inside an oil-in-water emulsion droplet
upon solvent evaporation, Langmuir, 35 (2019) 5902–5910.
DOI: 10.1021/acs.langmuir.9b00613
Zlotnick A., To build a virus capsid: an equilibrium model ofthe self assembly of polyhedral protein complexes, Journalof Molecular Biology, 241 (1994) 59–67. DOI: 10.1006/
jmbi.1994.1473

Author’s Short Biography
Jakub M. Gac
PhD, DSc, Professor at the Faculty of Chemical and Process Engineering Warsaw University ofTechnology, Poland. 2005: MSc Physics; 2006: MSc Chemical Engineering; 2009: PhD Physics;
2017: DSc Chemical Engineering; 2018 - visiting professor, Federal Institute of Technology in
Zürich (Switzerland). Scientific interests: aerosol physics and chemistry, functional particles andmaterials formation, gas and wastewater filtration, air quality monitoring and analysis, numericalmodelling in chemical engineering. Author and co-author of over 60 peer-reviewed papers publishedin periodicals and conference proceedings and 2 books.

61

KONA Powder and Particle Journal No. 39 (2022) 62–83/https://doi.org/10.14356/kona.2022012

Review Paper

Review and Further Validation of a Practical Single-Particle
Breakage Model †Luís Marcelo Tavares
Department of Metallurgical and Materials Engineering, Universidade Federal do Rio de Janeiro, Brazil

Abstract
Particle breakage occurs in comminution machines and, inadvertently, in other process equipment during handlingas well as in geotechnical applications. For nearly a century, researchers have developed mathematical expressions
to describe single-particle breakage having different levels of complexity and abilities to represent it. The work
presents and analyses critically a breakage model that has been found to be suitable to describe breakage of brittle
materials in association to the discrete element method, either embedded in it as part of particle replacement
schemes or coupled to it in microscale population balance models. The energy-based model accounts for variability
and size-dependency of fracture energy of particles, weakening when particles are stressed below this value, as
well as energy and size-dependent fragment size distributions when particles are stressed beyond it, discriminating
between surface and body breakage. The work then further validates the model on the basis of extensive data from
impact load cell and drop weight tests. Finally, a discussion of challenges associated to fitting its parameters andon applications is presented.
Keywords: particle breakage, fracture, modelling, impact, compression, discrete element method

1. Introduction
Single-particle breakage tests have long been used toanalyze fracture phenomena (Arbiter et al., 1969; Schönert,
1972; Rumpf, 1973), study energy utilization in comminution processes (Rumpf, 1973; Schubert, 1987; Dan andSchubert, 1990; Tavares, 1999), analyze the effect of particle size, shape, material properties and modes of loadingon particle breakage characteristics (Yashima et al., 1987;
Tavares and King, 1998; Rozenblat et al., 2012; Saeidi etal., 2016; Saeidi et al., 2017; Lois-Morales et al., 2020), investigate energy-size reduction relationships (Piret, 1953;
Bergstrom et al., 1961; Rumpf, 1973; Narayanan andWhiten, 1988; Morrell, 2004) and analyze material deformation response under applied stresses (Schönert, 1991;
Sikong et al., 1990; Tavares and Almeida, 2020).
One application of single-particle breakage informationthat has grown significantly in recent decades has been
to support mathematical models of comminution andmechanical degradation during handling. This information
was initially used as part of phenomenological models ofcomminution devices, including ball mills, autogenous†

62

Received 21 March 2021; Accepted 7 June 2021
J-STAGE Advance published online 7 August 2021
Add: COPPE/UFRJ, Cx. Postal 68505, CEP 21941-972, Rio deJaneiro, Brazil
E-mail: tavares@metalmat.ufrj.br
TEL: +55-21-2290-1544

and semi-autogenous mills and cone crushers (Narayanan
and Whiten, 1988; Napier-Munn et al., 1996), as well asof degradation during handling (Teo et al., 1990; Weedon
and Wilson, 2000), although originally in a fairly simplistic
way. Perhaps influenced by the conditions used in thestandardized twin pendulum, and later also in the drop
weight tester (JKDWT) by the Julius Kruttschnitt Mineral
Research Centre (JKMRC) (Napier-Munn et al., 1996),
attention was initially only given to the relationship between the energy applied and the resulting fragmentation at
relatively high specific impact energies.
From the beginning of the 1990s, research on the discrete element method (DEM) applied to tumbling mills(Mishra and Rajamani, 1992; King and Bourgeois, 1993;
Morrison and Cleary, 2006) has demonstrated that very few
impacts occur at the high specific energies that are objectof testing in the JKDWT, and that the majority of collisions
occur at impact energies that are either able to only impose
limited breakage to particles or break them only after repeated stressing. This led to recognition of the importanceof deepening the investigation of conditions that result inprimary breakage, including breakage probability, weakening by repeated impacts and progeny size distributions
at very low specific impact energies (Tavares, 2007). This
shed new light into the subject, which had been objectof relatively scattered studies before then (Rumpf, 1973;
Baumgardt et al., 1975; Krogh, 1980; Schönert, 1979;
Yashima et al., 1987). Nevertheless, the importance of very

Copyright © 2022 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

low energy impacts was recognized over 70 years ago byFred Bond, when developing the standard crushability test
(Bond, 1947), in which particles are repeatedly stressed atincreasing impact energies until primary breakage occurs(Tavares and Carvalho, 2007).
A definition that has a central role when dealing withparticle breakage is that of particle fracture energy(Baumgardt et al., 1975; King and Bourgeois, 1993). It
corresponds to the stressing energy below which the coreof the particle is maintained unbroken, whereas potentiallydamaged, while the surface of the particle may lose massdue to abrasion-like breakage when it is subjected to a
stressing event. This particle fracture energy varies fromparticle to particle as well as with particle size and defines
the threshold between massive or body breakage at higher
impact energies and surface breakage that occurs at lower
stressing energies (Tavares and King, 1998).
As mathematical models of different mills, crushers andhandling systems evolved, incorporating information from
DEM, it became evident that more detailed information on
particle breakage was necessary. It is worth mentioningthat several approaches circumvented the need for thisinformation by either using data from particle bed breakage tests (Datta and Rajamani, 2002) or from the processitself, by back-calculating the selection function from data
(Capece et al., 2014; Wang et al., 2012). However, they
are not as generally applicable given their more limited
ability to decouple material from process (Tavares, 2017).
As such, the most powerful approaches used in advanced
mathematical models and simulations are particle-based,that is, require information on how individual particles
respond to stresses, either when they are fully resolved in
the DEM simulation or when they are not. It is important torecognize that in order to be useful in such models, particle
response must be known under the variety of conditions

Fig. 1

to which it will be subjected to in a comminution device
or a system that can cause mechanical degradation. These
typically include widely varied particle sizes, stressing intensities, geometries and rates of stressing as well as modesof stress application.
A fairly large number of mathematical models describing
particle breakage has been proposed in the literature, which
may be potentially of use in association to advanced mathematical models and DEM simulations. In most of themthe variable of interest is the stressing energy (Tavares andKing, 1998; Vogel and Peukert, 2003; Morrison et al., 2007;
Bonfils, 2017; Ballantyne et al., 2017), whereas in a few thevariable of interest is impact velocity (Ghadiri and Zhang,2002; Rozenblat et al., 2012) or force (Rodnianski et al.,2019). Also, several of these models have been proposedthat relate the size distribution of fragments to the stressing
energy applied, not discriminating between volume orsurface breakage (Ballantyne et al., 2017; Ouchterlony andSanchidrián, 2018). These models, however, are not meant
to discriminate particles individually, being only suited todescribe the response of the entire batch. Other models
have been proposed to describe the so-called incremental
breakage, lumping together surface breakage and weakening by repeated stressing (Morrison et al., 2007; Bonfils etal., 2016), being very limited when used in association toadvanced mathematical models of comminution and degradation. Yet other models focused exclusively on surface
breakage (Ghadiri and Zhang, 2002).
The present work analyzes critically and also presents
further evidence of the validity of a comprehensive mathematical model proposed by the author and his co-workers
over the last 25 years (Tavares, 1997; Tavares and King,
1998; Tavares and King, 2002; Tavares, 2009; Carvalho et al.,2015; Tavares and Chagas, 2021) and schematically shown in
Fig. 1 to describe several aspects of particle breakage.

General scheme of the breakage model.

63

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

2. Breakage probability
2.1 Body breakage probability distributions
Arguably, the central part of the model is the breakage
probability (Fig. 1). It represents the relationship between
the applied stressing energy and the resulting proportionof particles that have undergone body or massive breakage
when particles contained in a batch are stressed underidentical conditions. Breakage in this context is defined
arbitrarily as loss of at least 10 % of the particle mass (Danand Schubert, 1990; Tavares, 2007). Estimates of breakage
probability may be obtained experimentally from tests inwhich lots of particles contained in narrow size ranges
are subjected to impacts by propelling them, one-by-one,
against a target at a controlled velocity or dropping themunder gravity. In this case the mass-specific impact energy
is given by
v2
Ek 
2

(1)

where v is the average velocity at the instant of collision
against the target, which can be obtained, for instance, from(1)
measurements using a high-speed camera (Cavalcanti etal., 2021).
(31)
Alternatively, an estimate of breakage probability may
be obtained by impacting particles using a drop weighttester. Assuming no loss of momentum during drop of the
impactor (free-fall), the specific impact energy may be
given by

Ek 

mgh
mp

(2)

where m is the mass of the drop weight, mp is the average
weight of particles in the lot tested, g the acceleration due
to (2)
gravity and h the net drop height, that is, the distance
between the bottom of the striker and the top(32)of the particle.
In either case, the estimate of breakage probability for agiven mass-specific impact energy E is given by the proportion broken, represented by the ratio

P Ek  

Nb
N

Nb
α
 z  N
2

Nb  Nb 
1 

N 
N 
N

(4)

where α is the significance and z is the reduced Gaussian
distribution.
(4)
An example of data collected following this approachis presented in Fig. 2. Obtained from impact of iron orepellets against a target, it exhibits the typical S shape andasymmetry, evident from the skewness of the distribution
to the right.
A more direct and less time-consuming approach is tomeasure directly the energy required to break individual
particles, using either slow compression devices (Sikong
et al., 1990; Tavares, 2007; Rozenblat et al., 2011; Ribas
et al., 2014; Campos et al., 2021) or instrumented drop
weight test devices, such as the impact load cell (King and
Bourgeois, 1993; Tavares and King, 1998; Bonfils, 2017;
Lois-Morales et al., 2020), analyzing the distribution ofdata. While requiring more specialized equipment, thisapproach has the advantage of demanding significantly
smaller sample volumes. In this approach, the force-(3)

where N is the number of stressed particles and Nb is thenumber of particles that underwent body breakage as a(3)
result of application of the specific impact energy Ek. Although Eqn. (3) relates numbers of particles, it is assumed
to be equivalent to the mass-based probability, given theirnarrow size range. In order to remove ambiguity in identifying which particles underwent breakage during executionof the test, each should be weighed individually prior to
the test and also after each impact, to verify if loss of atleast 10 % of their mass occurred. The measurement after
the impact becomes obviously unnecessary if the particle

64

suffered evident disintegration.
Either when particles are projected against a target
or when a drop weight impacts individual particles, thespecific impact energy Ek is actually a random variable,
subjected to variability owing to the velocity of impact and,in the case of the later, also due to variability in particle
weight. In addition to that, the proportion broken given by
Eqn. (3) is only an estimate of the breakage probability,with the uncertainty reducing as the number of testparticles increase, provided no bias existed in selecting
particles for the test. The magnitude of the sampling error
has been estimated (Tavares, 2009) on the basis of the Binomial distribution, so that the confidence interval for the
proportion broken is given by

Fig. 2 Proportion broken as a function of specific impact energy frompropelling fired iron ore pellets contained in the size range 12.5–9.0 mm
against a steel target (data from Cavalcanti et al., 2021). Vertical error
bars are given by Eqn. (4) and horizontal error bars were estimated frommeasurements of impact velocity using a high-speed camera.

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

deformation profile during loading of each particle isrecorded and the mass-specific particle fracture energy E
is given by numerical integration of the curve up to thedeformation or force responsible for fracture

E

1 Δc
F dΔ
mp  0(5)where mp is the weight of each individual particle, F theload, whereas Δ and Δc are the deformations and the defor(5) at primary fracture, respectively.
mationTypically, data in these tests present large variability(Tavares and King, 1998), so that they should be properly
analyzed. A convenient method is order statistics, throughwhich the test results are ranked in ascending order and thevalues i = 1, 2, …, N assigned to the ranked observations,where N is the total number of valid tests performed. The
cumulative probability distribution estimates for the particle fracture energy are given by

P Ei  i  0.5
N(6)

An example of this type of data is shown in Fig. 3 from
impact-breakage of quartz particles. Different probability(6)
distributions
have been proposed over the years to describe
data such as in Figs. 2 and 3, including the lognormal andupper truncated lognormal (Baumgardt et al., 1975; Kingand Bourgeois, 1993; Tavares and King, 1998; Tavares
and King, 2002), the logistic and log-logistic (Vervoorn
and Austin, 1990; Rozenblat et al., 2011; 2012), thegamma (Cavalcanti and Tavares, 2019) and the Weibull
distribution (Weichert, 1992; Salman et al., 2002; Vogel
and Peukert, 2004), just to name a few that have beenused to fit such data (Cavalcanti and Tavares, 2018). These
distributions are typically skewed to the right, with either
two or three parameters and with or without a clear upper
limiting (truncation) value. Fig. 3 compares some of theFig. 3 Distribution of fracture energies from impact of 200 quartz
particles contained in the size range 1.18–1.0 mm in the impact load cell
device. Data from Tavares (1997).

distributions to data. In particular when dealing with datafrom proportion broken, in which results only from relatively a limited number of stressing energies are available(Fig. 2), several distributions may provide fairly similar fit(Tavares, 1997), so that the selection of the most suitable
distribution is not straightforward but is often not criticaleither. Differences in fit provided by the distribution functions are typically limited to the extremes (tails) of the data.
In particular, the lower tail of the distribution, represented
by the particles that are more amenable to breakage, isparticularly important when describing degradation due tohandling (Cavalcanti et al., 2021). On the other hand, theaccurate description of the upper part of the distribution, inparticular for the coarser particles, is particularly criticalwhen using the model to predict breakage in tumblingmills, since it will determine the likelihood that particles
will remain unbroken in spite of the collisions in the mill
(Tavares and Carvalho, 2009).
A distribution that has demonstrated to be able to describe well the variability of the data is the upper truncatedlognormal distribution, given by
P E 1 ln E *  ln E50 
1  erf 


2


2σ 2

(7)

and

(7)
E* 

Emax E
Emax  E(8)where P(E) represents the breakage probability or the
cumulative distribution, E is the mass-specific fracture(8) of the particle, which corresponds to the maximum
energystressing energy that it can sustain in a collision and notbreak, Emax is the upper truncation value of the distribution,
E50 and σ2 are the median and the variance of the distribution, respectively. The upper truncation value is often
represented by the ratio Emax/E50. In the case when thisratio is equal to infinity, E* = E and Eqn. (7) becomes thelognormal distribution.
Besides stressing energy, several other variables also
influence breakage probability (Fig. 1). The stiffness of thesurface in contact is such a variable, which is analyzed ingreater detail in 2.2, whereas the important effect of particle
size is analyzed in section 2.3. The effect of impact angle on
the breakage probability has been the object of some studies (Dan and Schubert, 1990; Salman et al., 2003; Tavares
et al., 2018; Cavalcanti et al., 2021). In a comprehensive
campaign of experiments in which iron pellets were propelled against a target (Tavares et al., 2018; Cavalcanti etal., 2021) it was found that breakage probability, and therefore body breakage, may be described considering only
the normal component of the impact velocity, at least for
impacts at angles that range from 90° (normal) to 30°. The
effects of other variables, such as particle shape, stressing
rate and mode of stressing (single or double) (Fig. 1) have65

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

been studied in the literature (Tavares, 2007; Bonfils, 2017;
Saeidi et al., 2017; Lois-Morales et al., 2020) but the lackof a proper understanding on how they affect the several
aspects of breakage for brittle materials in general made it
impossible to properly account for them in the model. As
such, it is advised that the user fits the model parameters
using data that most closely match conditions that dominate in the device that is meant to be simulated.
Adapting Eqns. (7) and (8) to be used to describe discrete particles, such as those embedded in a DEM simulation (Tavares et al., 2020b; 2021) is quite straightforward,
since it only requires randomly sampling the distribution
every time a particle is created.

2.2 Effect of stiffness on body breakage
probability
Analyzes in section 2.1 assumed that the stiffness of aparticle is significantly smaller than that of the surface ofthe testing device or machine which is in contact with theparticle. In several instances, however, that is not the case,so that a correction must be used. Given the local nature of
the contacts involving application of stresses to particles
and assuming validity of the Hertz contact theory (Tavares
and King, 1998; Tavares et al., 2021), the proportion e ofthe stressing energy involved in any given event that isused to deform the particle is given by (Becker et al., 2001;
Tavares and Carvalho, 2011; Tavares et al., 2021)e

1
1  k p / ks

(9)where kp is the particle stiffness (Tavares and King, 1998),
ks is the Hertzian stiffness of the surface in contact with(9)
the particle. For instance, Eqn. (9) may be used to estimate
the proportion of the energy recorded using Eqn. (5) in thetest that was actually dissipated in breakage of the particle.
Since steel surfaces are typically used in the testing devices, with Young’s modulus (Y) of 209 GPa and Poisson’s
ratio of 0.3, their stiffness [ks = Y/(1 – ν2)] is 230 GPa.
The apparent particle stiffness may be estimated using a
convenient procedure in an earlier work (Tavares and King,
1998), whereas a more accurate, but more laborious, measure may be obtained using a procedure that was recently
proposed (Angulo et al., 2020). If the particle stiffness
is significantly lower than that of the surface, then e ≅ 1.
However, in a collision involving two particles of the samematerial, then e = 1/2, with the energy being equally shared
between the colliding particles.
In order to assess the validity of Eqn. (9), tests were conducted in an impact load cell device on limestone particles
using different types of impactors. In this modified impact
load cell device a rod rather than a drop ball is used as impactor (Tavares and King, 2004), so that tests were carriedout comparing the specific fracture energies measured us-

66

ing steel or hard polymer (Polyether ether ketone or PEEK)
impacting rods. The values of Hertzian stiffness of the
impactors were estimated as 230 GPa for steel and 4.8 GPa
for PEEK, this later calculated on the basis of data frommanufacturer’s catalogs (Young’s modulus of 4.0 GPa
with Poisson’s ratio of 0.4). The median apparent stiffness
for the limestone particles, estimated using the procedure
proposed by Tavares and King (1998) was 6.4 GPa. Fig. 4
shows that the energies required to break particles when
the softer impactor (PEEK) is used are significantly higher
than when steel surfaces are used. These higher values forthe polymeric striker are consistent with the larger dissipation of the energy which results from using a striker withlower stiffness (Eqn. 9). Considering now the applicationof Eqn. (9) considering the stiffness values, Fig. 4 shows
the dashed line, which nearly superimposes to data for the
steel striker, showing that the actual fracture energies of thelimestone particles were independent of the striker used.
It is important to bear in mind that Eqn. (9) only accounts for the elastic part of the deformation (Tavares et al.,2021). Whenever stressing events occur with significant
contribution from plastic deformation, Eqn. (9) provides
only a conservative estimate. An example of this was theimpact of iron ore pellets against an aluminum alloy plate,
in which Eqn. (9) underestimated the energy dissipatedon the impact surface, leading to incorrect predictions(Cavalcanti et al., 2021).
This effect of stiffness of the parts in contact can be dealt
with readily using Eqn. (9) either in the case of applying
the model to continuum distributions, such as in microscale
population balance model formulations (Tavares, 2017),
and in discrete forms imbedded in DEM (Tavares et al.,2020a; 2021).

Fig. 4 Distribution of particle fracture energies of 4.75–4.0 mm limestone (Karslruhe) particles stressed with different strikers in an impact
load cell device. Symbols are experimental data, solid lines the fit to thelognormal distribution, whereas the dashed line the fit to PEEK striker
after applying Eqn. (9) (data from Tavares, 1997).

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

2.3 Size effect on body breakage probability

where E∞, do and φ are model parameters that must be fitted
to experimental data and di is the representative size of(10) contained in size class i. k and k are the values
particlespsof Hertzian stiffness of the particle and of the surface ofthe device used in measuring the breakage characteristics,
respectively. As such, Eqn. (10) already incorporates theeffect of stiffness of the tools, given by Eqn. (9).
Data from a variety of materials are presented in Fig. 6,
which also shows the model fit. It is evident that the model
is able to represent variations that range from power-law
relationships of fracture energies with particle size up to
cases in which a constant fracture energy is achieved atcoarse sizes. Parameters of Eqn. (10) for these and othermaterials are presented in Table 1. Values of parameter φvary from as low as about 0.7 to as high as 2. However,since it describes primarily the power-law increase of themedian fracture energies with the reduction in particle
size, this parameter is more prone to uncertainty, due to thechallenge associated with estimations of fracture energies
at fine sizes, as discussed in section 5.1. Values of parameter do, on the other hand, varied significantly, from values
as low as 0.5 mm to values as high as 200 mm. When thisvalue lies in the range of particle sizes tested (Table 1),
it may be interpreted as a characteristic dimension of thematerial microstructure (Tavares and King, 1998; Tavares
and Neves, 2008). On the other hand, values of do above
these make it simply a fitting parameter with no particularphysical meaning, implying that no clear plateau would
have been reached in the measurements of fracture energies
at coarse sizes.
Fitting all three parameters in Eqn. (10) typically requires data from at least five widely different particle sizeclasses, ideally spanning at least two size decades. This
is not typically a straight-forward task, since it would
almost certainly require using multiple impact load cell orcompression testing devices, given the different resolutions
required.
Besides the effect of particle size on the median particle
fracture energy, it is also worth examining its effect on thestandard deviation of the distribution (Eqn. 7). For several
materials, the variation of the standard deviation of the
distribution may be considered small or negligible. An example of this is presented in Fig. 7, which shows data from
Fig. 5 plotted as a function of ratio between the specificparticle fracture energy of individual particles and the median value E50 for each size. Since data approximately superimpose, forming a mastercurve, it may be assumed thatthe standard deviation of the distribution is invariable withparticle size in the range studied. Values of the variance σ2have been found to vary, exceptionally, from as low as 0.15

Fig. 5 Distribution of specific particle fracture energies for different
particle sizes of gneiss (Santa Luzia quarry). Symbols represent experimental data and lines the fit to the lognormal distribution (Eqn. 7).

Fig. 6 Variation of median particle fracture energies of selected materials as a function of representative particle size.

Besides stressing energy, the most critical variable influencing breakage probability is particle size. When dealing
with brittle materials, it is expected that the stress or energy
require for their fracture increases as particle sizes reduce(Schönert, 1979; Yashima et al., 1987; Tavares, 2007).
However, such variation depends on material, with Fig. 5
showing the distributions of particle fracture energies for asample of gneiss.
Several expressions have been proposed in the literature to describe the size effect on the median value of the
distribution (Vogel and Peukert, 2004; Rozenblat et al.,2012). In the present model the effect of particle size on
E50 is described using an expression inspired in reliability
theory (Tavares and King, 1998; Tavares and Neves, 2008),
given by  d o  φEE50,i 1 
1  k p / ks   d i  

(10)

67

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83
Table 1 Values of parameters in the size model for selected materials (Eqn. 10).

Material

SourceSpecific
gravity(g/cm3)

E∞(J/kg)

do(mm)

φSize range(mm)

Reference

ApatiteCantley, Canada

3.21

1.50

19.3

1.62

0.25–8.00

Tavares (1997)

GalenaPark Valley, Idaho

7.40

3.19

7.31

1.03

0.70–7.60

Tavares (1997)

Gilsonite

Fort Duchesne, Utah

1.07

5.50

7.07

1.60

1.18–10.0

Tavares (1997)

QuartzKarlsruhe, Germany

2.65

43.4

3.48

1.61

0.25–4.75

Tavares (1997)

Sphalerite

Na*

4.10

7.00

8.24

1.16

0.35–10.0

Tavares (1997)

Basalt

Utah

2.59

9.59

3.93

1.96

0.25–7.20

Tavares (1997)

Limestone

Karlsruhe, Germany

2.73

114

0.49

2.05

0.35–5.60

Tavares (1997)

Limestone

Cantagalo, Brazil

2.71

7.0

100.

0.80

0.50–37.5

Carvalho and Tavares (2013)

Limestone

Brazil

2.98

150

0.79

1.30

0.50–37.5

Carvalho and Tavares (2013)MarbleVermont

2.68

45.9

0.88

1.76

0.35–10.0

Tavares (2007)

GneissSanta Luzia, Brazil

2.80

48.7

2.78

1.82

0.50–90.0

Tavares and Neves (2008)

SyeniteVigné, Brazil

2.64

26.5

101.

0.67

0.50–90.0

Tavares and Neves (2008)

Granulite

Pedra Sul, Brazil

2.79

123

0.91

1.68

0.50–90.0

Tavares and Neves (2008)

BauxiteParagominas, Brazil

2.40

70.3

14.6

0.91

0.50–75.0

Tavares (2007)

Copper ore

Bingham Canyon, Utah

2.83

96.1

1.17

1.26

0.25–15.8

Tavares (2007)

Copper ore

Green Valley, Arizona

2.83

171

1.37

1.41

0.50–12.5

Tavares (2007)

Copper ore

Sossego mine, Brazil

2.93

60.0

400.

0.45

0.50–90.0

Carvalho and Tavares (2013)

Copper ore

NSW, Australia

2.75

22.5

41.1

0.71

0.35–37.5

Tavares et al. (2020b)

Iron ore

Newfoundland, Canada

3.80

47.3

1.08

2.30

0.25–15.0

Tavares (2007)

Iron ore

Eveleth mine, Minnesota

3.65

164

0.86

1.76

0.35–10.0

Tavares (1997)

Iron ore

Conceição mine, Brazil

2.80

16.8

20.1

0.84

2.36–80.0

Tavares and Carvalho (2011)

Iron ore

Australia

Na*

0.86

200.

1.21

2.36–90.0

Fandrich et al. (1998)

Cement clinker

CEMEX, Mexico

2.49

46.4

6.68

1.09

0.25–12.5

Tavares (1997)

Cement clinker

CEMEX, Mexico

2.49

100

5.04

0.92

0.25–12.5

Tavares (1997)* Na: not available

to as high as 1.2, with typical values of about 0.7. For somematerials, however, it has been found that the variability ofthe distribution increases for f﻿iner particle sizes (Barrios etal., 2011) and expressions that are analogous to Eqn. (10)have been successfully used to describe the data (Carvalho
and Tavares, 2013). The ratio Emax/E50 also shows the samegeneral trend as the variance with size. These variations are
typically associated to rocks/ores, which behave as composites at coarser sizes, responding as individual minerals
at finer sizes, with the corresponding wide range of fractureenergies of the components.

2.4 Weakening by repeated stressing events
Fig. 7 Distributions of particle fracture energies of gneiss particles ofdifferent sizes (data from Fig. 5) plotted in normalized form.

68

Breakage models in the literature have been proposed todescribe the so-called incremental damage (Morrison et al.,

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

2007; Bonfils et al., 2016), which is given by the proportionof fines generated as a function of repeated stressing. In
these models, however, weakening by repeated stressing isconfounded with the fines associated to surface breakage.
Thus, a more rigorous approach is to describe the increasein breakage probability with the repeated impacts separately. Indeed, when the specific stressing energy involvedin a collision is smaller than the fracture energy of theparticle, the particle will not undergo breakage (Fig. 1),
but will sustain internal crack-like damage, which will
make it more amenable to break in a future stressing event.
This weakening has been described on the basis of a model
based on continuum damage mechanics (Kachanov, 1958),
through which the specific fracture energy of the particle
will be reduced to (Tavares and King, 2002; Tavares, 2009)E  E 1  D(11)

where E′ is the fracture energy of the particle after the(11) event and D is the damage variable, which isstressing
given by (Tavares, 2009)2γ
eE k  25γD 2γ  5D  5 E 

Fig. 8 Proportion broken from drops on a steel surface at different
drop height (or specific impact energies) of 125–75 mm copper ore(Sossego) particles. Experimental results represent symbols and lines
the model fit (Carvalho and Tavares, 2011).

(12)

where γ, the only fitting parameter in the model, is thedamage accumulation coefficient, which characterizes the(12)amenabilityof a material to sustain damage prior to catastrophically breaking, and eEk is the specific energy in thecollision available to the particle. Eqn. (12) is implicit but
can be easily solved iteratively with the initial guess D = 0.
The constant γ is typically estimated through tests inwhich lots of particles are repeatedly impacted at a given
specific energy and the proportion broken recorded (Eqn.
3). From the distribution of specific particle fracture energies, given by Eqns. (7) and (8) and the model Eqns. (11)and (12) the optimal value of the constant may be estimated.
This is illustrated in Fig. 8, which compares the model fit toexperiments. Tavares (2009) carried out a comprehensive
study, which demonstrated that the constant γ is typicallyindependent of particle size, with more limited data showing independence of particle shape. Also, it was observedthat values of γ varied from about 1.5 for materials that arehighly amenable to accumulate damage prior to breakage,
up to 8.1 for materials with exceptionally little amenability
to weaken by repeated stressing, with average values being
in the range of 3 and 4. Finally, it has then been found thatthe value of γ is not directly influenced by the mechanicalstrength of the particle, but by its microstructure: it is often
lower for materials with complex microstructures, which
are more capable of sustaining damage prior to collapsingand higher for more brittle materials (Tavares, 2000).
Eqns. (11) and (12) are useful when the model is applied to individual particles, such as when it is embedded
in a DEM simulation (Tavares et al., 2020a; 2021). An

alternative formulation of the model, useful when it isapplied in a continuum, such as associated to microscale
population balance formulations (Tavares and Carvalho,
2009; Carvalho and Tavares, 2013; Oliveira et al., 2020),
is given by P E / 1  D  P eE k  P´E  

1  P eE k 



(13)

which should be solved in association to 2γ 1  D eEk  25γ
(13)
D

 2γ  5D  5 E (14)where E in Eqns. (13) and (14) represent the fracture energy of the particle after the impact.
(14)
The model does not have a minimum threshold, that
is, as Ek reduces, D vanishes in Eqns. (12) and (14). In
practice, however, a minimum value of Ek is often selected,
for computation efficiency, when using the model, so as toprevent computing damage in collisions with negligibly
small magnitudes.

2.5 Surface breakage mass loss
In the breakage model the description of surface breakage is certainly in an earlier stage of development than themodels described in sections 2.1 to 2.4. Surface breakage
has been widely investigated as part of attrition studies andan elegant model has been proposed by Ghadiri and Zhang(2002). An adaptation of the model for the case when thecontrolled variable is the specific impact energy gives(Cavalcanti et al., 2019)ξ i  100 κ d i eEk(15)

where κ is the attrition parameter, fitted from data, and di(15)representative particle size. This model has been sucis the69

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

Fig. 9 Average percentage of mass loss per impact of selectedmaterials dropped by gravity onto a thick steel plate. Gneiss andgranulite: 22.4–19 mm; recycled aggregate: 14–10 mm; iron ore pellet:
12.5–9 mm.

cessfully applied to both natural and recycled aggregates(Cunha et al., 2014; Moreno-Juez et al., 2021) and ironore pellets (Boechat et al., 2018; Cavalcanti et al., 2019).
Unfortunately, it has only been validated for particles
contained in a relatively limited (22–9 mm) range of sizes.
Selected results are presented in Fig. 9 for tests in which
particles are dropped one-by-one by gravity and their massloss recorded after each impact, showing the validity of themodel.
Evidently, this model does not account for the fact that
surface breakage tends to deviate from linearity as thenumber of impacts increases and neither for the dependency on particle shape, so it may only be used as a first approximation of a rather complex problem. In an attempt toaccount for the effect of impact angle on surface breakage,
Cavalcanti et al. (2019) used the total energy dissipated in
the collision, given by the sum of the normal and the shear
energy loss estimated in DEM in place of Ek in Eqn. (15),obtaining good agreement to data from impact of iron orepellets.

3. Breakage distribution
3.1 Breakage distribution function
As mentioned in the introductory section, several models
have been proposed in the literature to describe the progeny
size distribution from single-particle breakage. Several ofthem benefit from the fact that when cumulative progeny
size distributions are plotted as a function of the relativefragment size, that is, the ratio between the sieve size andthe representative size of the parent particles, they superimpose, independently of parent particle size. This representative parent particle size is given by the geometric mean

70

Fig. 10 Progeny size distributions from testing syenite particles from
Vigné quarry contained in different size ranges in drop weight testers(modified from Tavares and Neves, 2008).

Fig. 11 Progeny size distributions from testing gneiss particles fromSanta Luzia quarry contained in different size ranges in drop weighttesters (modified from Tavares and Neves, 2008).

sizes of the initial sieve sizes containing the tested lot.
An illustration of this is presented in Fig. 10, whichshows data for different initial sizes for syenite. In spite of
the scatter, data for the different initial sizes superimpose
reasonably well, demonstrating that such normalization ofdata in respect to the initial parent size is valid. This behavior has been explained on the basis of the fractal nature ofbreakage of brittle particulate materials (Tavares, 2007).
However, for some materials such normalization is only
valid above a minimum fragment size. This is illustrated
in Fig. 11 for a sample of gneiss. These so-called nonnormalizable fragment size distributions have been identified to be associated to some brittle materials in which
discontinuities concentrate in well-defined size scales,

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

creating an inflection point in the cumulative fragment size
distribution (Tavares and Neves, 2008; Powell et al., 2014).
As such, data contained in sizes below this value should betreated separately, as addressed later in the section.
One convenient method to deal with data such as thosein Fig. 10 is to select particular markers on each curve.
This is the so-called t10 procedure originally proposed by
Narayanan and Whiten (1988). As part of this procedure
the percentage of material passing different 1/nth fractionsof the initial particle size, called tns, are estimated from thecumulative size distribution, typically interpolated using
cubic splines. Commonly used values of n are 2, 4, 10,25, 50 and 75. With the aim of representing the progeny
size distribution in greater detail, additional markers
may also be used, including 1.2 and 1.5 (Carvalho et al.,2015; Ballantyne et al., 2017). In order to illustrate this,breakage data in Fig. 10 are presented in normalized formin Fig. 12, which shows that data for each n value follows
well-defined trends as a function of t10. The principle of themethod is that, if the user has an estimate of the t10 value ofthe size distribution, likely from an expression that relates
the initial particle size and the specific impact energy, theentire size distribution can be reconstructed (Napier-Munn
et al., 1996; Tavares, 2017).
Several functional forms have been proposed over
the years to describe cumulative progeny size distributions from drop weight tests, including the cubic splines(Narayanan and Whiten, 1988; Napier-Munn et al., 1996),
the upper truncated Rosin-Rammler (King, 2001; Tavares,
2004) and combined exponential functions (Ballantyne
et al., 2017). Given its ability to describe data with great
flexibility, the incomplete beta function is used as part ofthe present model (Carvalho et al., 2015), given byt n t10 100

1

t10 /1000β 1x α 1 1  x
dx

x αn 1(1  x) βn 1dx

(16)

n

0

n





where the cumulative mass of the particles passing a screen(tn(16)) with relative size x is calculated by the given t10 valueof the distribution. In the model two parameters (α and β)
must be fitted to each value of n selected. As such, with theseven n values (1.2, 1.5, 2, 4, 25, 50 and 75) a total of 14
parameters must be fitted from data, which is substantial.
Fig. 12 shows that data can be well described using Eqn.
(16). The equation has also demonstrated to successfully fit
the data for several other materials, as was also evident inprevious publications (Barrios et al., 2011; Carvalho andTavares, 2013; Carvalho et al., 2015). Unfortunately, given
the lack of a proper physical description of fragmentationthat would allow extrapolation of data, characterizing the
response of a given material requires extensive testingover a range of stressing energies and sizes, which is atime-consuming task. Although it may be argued that eachFig. 12 Progeny size distributions presented in the normalized t10
versus t n format for syenite from Vigné quarry (data from Fig. 10).

material has its well-defined breakage pattern, so that they
will present different t10 versus tn relationships such as theone presented in Fig. 12 (Tavares and Neves, 2008), it isworthwhile to search for a mean distribution that would be
able to describe data for a variety of materials with reasonable confidence.
As such, data from drop weight tests of a total of 40
materials have been gathered (Tavares and Chagas, 2021)
and plotted in normalized axes as those in Fig. 12, withresults being presented in Fig. 13 for selected values of n.
A large scatter in the data appears, but it is also evident thatdata can be reasonably well represented using a single setof curves. The scatter in the graph in a logarithmic scalesuggests the structure of the errors and the validity of thelogarithmic objective function used in fitting the model
parameters (Carvalho et al., 2015).
A more detailed examination of the data (Tavares andChagas, 2021) allowed to conclude that the different typesof materials (rocks, ores, cement clinkers and coals) did
not appear particularly segregated in each of the plots in
Fig. 13, which suggests the validity of the generalization
proposed. The only exceptions were iron ores (Tavares andChagas, 2021), which were not included in model fitting.
Also, deviations were typically limited to the extremes ofthe size distributions, that is, either at the coarse (t1.2 andt1.5) or the fine (t50 or t75) end.
The list of parameters that resulted from fitting the data
in Fig. 13 is presented in Table 2, covering the 40 materials(Tavares and Chagas, 2021). These parameters may be
used as default in case of the absence of enough fragmentation data that would allow fitting of the various parametersin Eqn. (16) for a material of interest.
Fig. 14 is obtained by plotting the various tn values as afunction of normalized fragment size for selected t10 values
using Eqn. (16) with parameters given in Table 2.
Although not included in the present work (Cavalcanti71

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

et al., 2021), data from projecting particles against a target
could also be well described using the incomplete beta
function and parameters from Table 2.
The normalizable breakage function can then be obtained from Eqn. (16) using the ratio between the fragment
size Di and the parent particle size dj, so thatBij t10   B x, t10   interp t10 , x(17)where x = di/Dj.
As mentioned earlier in the section, there are instances(17)
in which the normalization approach proposed by the t10
procedure is not valid below a given fragment size D*. Thisis the case of the so-called non-normalizable progeny size
distributions, which appear typically when materials havea well-defined dimension in which discontinuities concentrate (Tavares, 2000). Indeed, non-normalizable breakage
functions have occasionally been used with the population
balance model equations for materials such as iron ores
(Faria et al., 2019; Campos et al., 2019). Table 3 shows
examples of materials whose breakage description required
the non-normalizable part of the breakage distribution.
This behavior can be described in the form of a powerlaw relationship below a minimum normalization size D*,
Fig. 13 Relationship between t10 and selected t ns for a variety of materials, with the exception of iron ores. Solid lines represent the fit to theincomplete beta function (data from Tavares and Chagas, 2021).
Table 2 Optimal parameters of the incomplete beta function (Eqn. 16)
for 40 materials (Tavares and Chagas, 2021), without including iron
ores.

n

αn

βn

1.2

0.448

10.508

1.5

0.706

7.913

2

0.959

5.780

4

1.105

2.619

25

0.981

0.524

50

0.956

0.339

75

0.934

0.255

Fig. 14 Calculated normalized size distributions using the incomplete
beta function and parameters from Table 2 (Tavares and Chagas, 2021).
Symbols represent the calculated t values for the different n markers,
while lines are cubic spline fits (Eqn. 17) to these values.

Table 3 Fragment sizes below which progeny size distributions are not normalizable for selectedmaterials (Eqn. 18).

72

Material

Particle size – D* (mm)ηReference

Vermont marble

0.32

1.46

Tavares (1997)

Utah siltstone

0.15

0.59

Tavares (1997)

IOCC iron ore

0.35

1.83

Tavares (1997)

Pedra Sul granulite

0.17

0.64

Barrios et al. (2011)

Santa Luzia gneiss

0.80

0.80

Tavares and Neves (2008)

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83(18)

2008; Carvalho and Tavares, 2011). This parameter will
likely be strongly influenced by parent particle size, but thedata are not yet comprehensive enough to characterize suchdependence (Cavalcanti et al., 2021).

which shows that the non-normalizable part of the dis(18)-2 is attached to the fine end of the normalizable
tribution
progeny size distribution obtained using the incomplete
beta function (Eqn. 16). Values of the exponent η are shownin Table 3 for selected materials. It is worth comparing
these to the average slope at fine sizes from the model forthe 40 materials (Fig. 14), which varies from 0.53 at low t10
values to 0.63 (Tavares and Chagas, 2021).
Adapting the present model to describe breakage of
discrete particles in DEM has been carried out by different
methods, depending on the shapes of particles. In the caseof polyhedral particles (Tavares et al., 2020a) these havebeen used as part of the Voronoi tessellation scheme tocreate the appropriate fragment size distribution and are
implemented in the commercial software Rocky DEM. On
the other hand, in order to represent breakage of sphericalparticles in a DEM simulation, families of spherical progeny have been created for a variety of values of t10 using
a procedure described elsewhere (Tavares and Chagas,
2021). This later has been implemented in the commercial
software Altair EDEM (Tavares et al., 2021).
The described normalization procedure only accounts
partially for the effect of particle size. The additional effectof particle size associated to the increase in resistance tobreakage as particle sizes reduce, as well as the effect ofstressing energy, are described using expressions presented
in detail in section 3.2. In addition to those, studies haveshown that other variables, such as impact geometry(Tavares, 2007; Saeidi et al., 2016), stressing rate (Saeidi
et al., 2017) and mode of stressing, if single or double
impact (Tavares, 2007), are known to have an influence on
breakage distribution. However, the lack of a proper understanding of their effect made it unfeasible to take them into
account explicitly in the model.
At stressing energies that are insufficient to cause
body breakage, particles will undergo surface breakage.
Carvalho and Tavares (2011) proposed to describe it using
the Gaudin-Schuhmann equation

3.2 Effect of particle size and stressing energy on
body breakage distribution

Bij  B Di , d j   Bi  j for Di  D *η

DBij  B Di , d j   *i  for Di  D *D (18)-1

Aij  1 for d i  d A

(19)

λ

d 
Aij   i  for d i  d A
 dA 
(19)-1

where dA is the top size of surface breakage products,
which
together with λ, must be fit from data. The variation(19)-2of these as a function of parent particle size and stressing energy has not been studied in as much detail in theliterature. From tumbling tests dA has been found to vary
typically from about 0.20 to 0.45 mm (Tavares and Neves,In the original t10 method (Narayanan and Whiten, 1988;
Napier-Munn et al., 1996), size-independent relationships
between the stressing energy and the t10 value were proposed. In the present model the relationship accounts simultaneously for the effects of stressing energy and particle
size, this later incorporated in the median fracture energy ofparticles (Tavares, 2009), beEk 
t10  A 1  exp   E50b (20)

where A and b′ are model parameters fitted to experimental
data, in which A corresponds to the maximum value of t10
(20)
that
can be achieved when breaking a material in a single
stressing event, whereas E50b is the median specific fractureenergy of particles that underwent breakage. The higher
the specific impact energy Ek in comparison to the specificfracture energy of the particles, the higher the value of t10
and the finer the progeny size distribution. By using themedian specific fracture energy of the particles that underwent breakage, Eqn. (20) is able to account for the particle
size effect in breakage.
Data from a variety of materials have been fitted to Eqn.
(20) and results are listed in Table 4. Values of parameter
A, representing the maximum t10 value achieved in a single
stressing event, were found to vary between about 40 to 75,
with typical values around 50 %. This demonstrates thata limiting maximum fineness can be achieved in a single
stressing event on individual particles, regardless of theintensity of the stressing energy. The product of the parameters (A*b′), which corresponds to the derivative of Eqn.
(20) at the origin, represents the amenability of the material
to fragmentation. Since the toughness of the material isalready captured in the value of E50b, this product actuallycharacterizes how effectively the stressing energy is used
to create new fracture surfaces and fragments. Its values
range from as low as 0.5 % to as high as 10 % (Table 4). As
such, some grouping in respect to type of material has been
observed (Tavares, 2000), in which materials with simple
microstructures, such as individual minerals or crystals,present values below about 1 %, whereas most rocks andores present values in the range from about 1 and 2 %. Values higher than 2 % have been observed for ores and rocks
with poor intergranular bonding (Tavares, 2000), coals, aswell as some porous materials, such as cement clinkers.
Typical results from fitting the model to data arepresented in Fig. 15, which shows the good agreement

73

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83
Table 4 Values of parameters A and b′ (Eqn. 20) for selected materials.

Mineral/ore/rockSource

A

b′

A*b′

Reference

ApatiteCantley, Canada

45.4

0.012

0.52

Tavares (2007)

QuartzKarlsruhe, Germany

38.8

0.018

0.68

Tavares (2007)

Hematite

Québec, Canada

45.6

0.016

0.75

Tavares (2007)

GalenaPark Valley, Idaho

44.5

0.018

0.78

Tavares (2007)

Copper-gold ore

Australia

66.2

0.013

0.85

Tavares et al. (2020b)

Granulite

Embu, Brazil

62.6

0.014

0.90

Tavares and Neves (2008)

Limestone

Utah

54.5

0.018

0.96

Tavares (2007)

SyeniteVigné quarry, Brazil

58.0

0.017

0.97

Tavares and Neves (2008)

Limestone

Ribeirão Branco, Brazil

46.6

0.022

1.03

—

Copper ore (K)Bingham Canyon, Utah

44.8

0.026

1.18

Tavares (2007)

Copper ore

Cyprus Sierrita, Arizona

58.9

0.020

1.20

Tavares (2007)

Granulite

Pedra Sul, Brazil

47.5

0.027

1.27

Tavares and Neves (2008)

Iron ore

Conceição Mine, Brazil

44.2

0.029

1.27

Tavares and Carvalho (2011)

Basalt

Utah

52.0

0.025

1.31

Tavares (2007)

Titanium ore

Titania, Norway

51.0

0.027

1.37

Tavares (2007)

GneissSanta Luzia, Brazil

59.7

0.025

1.50

Tavares and Neves (2008)

Limestone #1

Brazil

53.3

0.033

1.76

Barrios et al. (2011)

Cement Clinker A

CEMEX, Mexico

69.2

0.028

1.91

Tavares (2007)

Copper ore (S)Sossego, Brazil

67.7

0.029

1.96

Barrios et al. (2011)

Limestone #2

Brazil

63.4

0.033

2.09

Carvalho and Tavares (2013)

Cement Clinker B

CEMEX, Mexico

60.5

0.044

2.64

Tavares (2007)

Gold oreSouth Africa

44.1

0.060

2.65

Pauw and Maré (1988)

Iron ore

Brazil

60.4

0.051

3.08

Carvalho and Tavares (2013)

Coal

Candiota, Brazil

44.1

0.091

4.01

—

MarbleVermont

76.3

0.079

6.04

Tavares (2007)

Iron ore

Newfoundland, Canada

65.4

0.158

10.3

Tavares (2007)

between the two. In some cases, however, the scatter islarger when particles of several sizes are included in the fit,potentially a consequence of effects that are not accounted
for in the model, such as variation in standard deviation of
the distribution with particle size, impact velocity and particle shape. The direct connection in the model between the
breakage probability and the fragment distribution, offeredby the normalizing value of E50b in Eqn. (20), is considered
an important feature, which renders internal consistency inthe model.
Adapting the model given by Eqn. (20) to describe
breakage of discrete particles results in the modified equation (Tavares et al., 2021)

Fig. 15 t10 as a function of impact energy for different particle size
ranges of limestone #1.

74bkeE k ´  A 1  exp  
t10



E 


(21)

where k is a variable introduced because the mean and the
median values of the distribution do not coincide (Tavares(21)
andChagas, 2021). This expression has been used in as-

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

sociation to discrete implementations of the model for thecase of either spherical (Tavares and Chagas, 2020; Tavares
et al., 2021) or polyhedral particles (Tavares et al., 2020a)
in DEM.

4. Model implications
4.1 Primary body breakage function
In several mills and crushers, the breakage distributionfunction is widely used to describe the average size distribution from each stressing event inside the devices, playing
a central role in traditional population balance models(Austin et al., 1984; King, 2001). In practice, rather thana true material property, it represents the result of model
fitting, at best estimated on the basis of the size distribution
from short grinding times (Austin et al., 1984).
For the case in which the particle is stressed with theminimum energy to produce body breakage, the resulting
fragment distribution is called primary single-particle
breakage function (Saeidi et al., 2016). In the few studies
that attempted to measure directly this primary breakage
distribution function of individual particles, Bourgeois(1993) estimated in about 2 % the value of t10 for quartz
particles under double impact (Saeidi et al., 2016), whereas
the corresponding value was about 1 % for iron ore pellets
subjected to single impact (Cavalcanti et al., 2021). Tavares(2009) then demonstrated, for a sample of limestone, thatit did not vary after each repeated impact. The importanceof this primary single-particle breakage function has been
demonstrated by Saeidi et al. (2016), who showed that it
was possible to predict the response of a material in a drop
weight tester to higher impact energies on the basis of thisprimary breakage function, besides Eqn. (10) and empiricalfunctions representing probability of selection of fragments
to secondary breakage. This has also been demonstrated to
be valid in DEM environment, where the size distribution
from higher impact energies could be predicted using
the breakage model in the case of polyhedral particles
in Rocky DEM (Tavares et al., 2020a) and Altair EDEM
(Tavares et al., 2021).
The present model allows estimating this primary breakage function by considering the case in which eEk ≅ E in
Eqn. (21), giving

Fig. 16 Primary breakage functions for selected materials, obtainedby fitting single-particle breakage data to the incomplete beta function
for t10 given by Eqn. (22).

the experimental measurements by Bourgeois (1993) andCavalcanti et al. (2021), values estimated using Eqn. (22)are likely an underestimation of the actual value. Nevertheless, they may be considered generally valid, given thechallenge in estimating directly the primary body breakage
function.
With the aim of illustrating the variations encounteredfor different materials, Fig. 16 compares primary bodybreakage distribution functions for selected materials estimated using this approach. It shows the variations in shapeand position of the primary fragment size distributions,representing differences in fragmentation pattern, with thesingle-phase materials (minerals) generating less fines thanrocks/ores (Tavares, 2000).

4.2 Predicting the outcome of a single stressing
event
Arguably, the simplest demonstration of the applicationof a breakage model is to predict the outcome of a single
impact on individual particles, such as in drop weight tester(Napier-Munn et al., 1996; Tavares, 2007). The outcome ofthis single impact event, considering both body and surface
breakage, may be described by the mass balance given by(Tavares and Carvalho, 2011)
wi*  wi 1  Pi eE k  1  ξ i eE k i´  A 1  exp b
t10







(22)

Given the values of the constants A and b′ (Table 4) andsince(22)at such low impact energies the constant k in Eqn.
(22) may be considered equal to about 0.95 (Tavares andChagas, 2021), then the resulting t10 values corresponding
to primary breakage range from as low as 0.5 to, exceptionally, higher than 5 %. As such, from comparison with(23)

w j Pj eE k  bij eEk   ξ i eE k  1  Pj eEk  aij 1

where wi* and wi are the weight fractions of the material
contained in size class i after and before the impact event,(23)
respectively. ξi is the fractional generation of surface(33)products, aij is the surface breakage distribution
breakagefunction and bij is the energy-specific body breakage distribution function. The term [1 – Pi(eEk)][1 – ξi(eEk)] on the%%%%%%%%%%%%%%%%%%%%%%%

75

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

right-hand side of Eqn. (23) represents the mass fractionof material that did not suffer body breakage during thestressing event and remained in the original size, whereas
the term Σ ij 1w j Pj eE k  bij eEk  represents the proportionof material from size classes i and coarser that suffered
body breakage and generated fragments reported to sizeclass i. The(35)term Σ ij 1w j ξ i eE k  1  Pj eE k  ai gives the
cumulative proportion of surface breakage products that reports to size class i. Pi(eEk) is the probability that a particle
contained in size (36)class i will suffer body breakage when it
captures energy eEk from a collision event.
When varying the specific impact energy applied to abatch of particles, breakage can transition from no bodybreakage at very low impact energies, where all particles
undergo only surface breakage, to body breakage of allparticles at high impact energies. In between these are
impact energies in which a fraction of the particles underwent body breakage, whereas the remainder only sufferedsurface breakage. This is illustrated in Fig. 17 for particles
of Pedra Sul granulite. In the figure, stressing energies
above 360 J/kg were able to produce body breakage inthe first impact on all particles, whereas those at 9 J/kg
produced only surface breakage. For stressing energies
between these, only a fraction of the particles underwent
body breakage, resulting in size distributions that represent
the transition between surface and body breakage. Unfortunately, validation data are available only for the higher impact energies, since at the lower impact energies the small
amount of surface breakage products makes collection of
accurate data a challenging task.

Fig. 17 Progeny size distributions from impact of 31.5–26.5 mm
granulite (Pedra Sul) particles in a drop weight tester at variable specificimpact energies. Large symbols represent experiments and lines andsmall circles model predictions. σ = 0.90, κ = 4 × 10 –4 kg/mmJ. Other
parameters given in Tables 1 and 4.

76

5. Discussion
5.1 Breakage testing and model fitting
The breakage model contains a variety of parametersthat must be fitted on the basis of experiments. Althoughsome parameters, in particular those related to the fragment
size distribution, may be assumed as default, since theirvariation for different materials may be relatively limited(section 3.1), experiments are required to estimate theseveral remaining ones. The originally proposed and mostdirect approach to estimate parameters from the model was
based on the use of the impact load cell device (Tavares,
2007). It is an instrumented drop weight tester in which theminimum energy required for primary fracture (Tavares
and King, 1998) as well as the net energy absorbed(Tavares, 1999) may be estimated for each individual particle. Besides that, repeated impact tests have then been used
to estimate the damage accumulation parameter (section2.3), whereas the fragment size distributions from different
impact energies served as the basis to fitting the parametersin the model described in 3.2. Slow compression tests canalso be used to estimate the fracture energy distributionof particles. Data from non-instrumented devices can also
be used to estimate the parameters in several of the model
equations. For instance, the breakage probability distributions may be estimated from either standard drop weighttests (Baumgardt et al., 1975) or tests in which particles
are projected against a target (Dan and Schubert, 1990;
Cavalcanti et al., 2021). These later are particularly relevant when modeling with the aim of simulating material
degradation during handling.
Although the detailed analysis of the experimental procedures and devices used to fit parameters in the breakage
model is beyond the scope of the present work and is wellcovered in other publications (Tavares and King, 1998;
Tavares, 2007; Rozenblat et al., 2012; Ribas et al., 2014;
Bonfils, 2017), it is worthwhile to highlight some important issues related to the tests. Indeed, one key challenge
when estimating the fracture energy of individual particles
using Eqn. (5) is the identification of primary fracture.
This primary fracture or primary body breakage point isgiven by the condition in which the force suddenly drops,
given the inability of the particle to continue transmitting
stresses. Such condition is relatively straightforward to
identify in some cases, such as in Fig. 18a, which is often
found from testing regularly-shaped brittle particles. In
these cases separation of newly created fracture surfaces
is rapid, resulting from propagation of a major crack
through the entire particle, facilitating the identification of
the fracture point, given the sudden drop in load. In othercases, however, identifying the instant of fracture can be far
more challenging and amenable to subjective judgement. A
few examples of such cases are also illustrated in Fig. 18.

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

Fig. 18 Typical force-time profiles from breakage of single particles of 12.5–9.0 mm iron ore pellets and their fragments in an impact load cell device.
Arrows depict presumed primary breakage point.

Fig. 18b shows the case in which the particle suffered chipping at approximately 100 ms, but that primary breakage
is still relatively straightforward to identify. This response
is often found while testing highly irregularly-shaped particles, in which a small fraction of their volume becomessubjected to concentration of tensile stresses early in thetest, causing the appearance of such superficial cracks. Yet
in other cases either multiple peaks appear (Fig. 18c) or noclear fracture point may be identified (Fig. 18d), requiring
some subjectivity in identifying the fracture load. Challenges such as these appear in association to testing more
deformable and/or less brittle materials. This can be associated to cases in which either a single crack or several cracks
grow sub-critically, being responsible for not such a clear
reduction in load at primary fracture. However, since norelative motion of the fragments occur, due to the limited
brittleness of the particle, the fragments continue to be able
to sustain load, preventing a drop in load-bearing ability ofthe particle and, therefore, identification of the instant ofprimary breakage. Techniques that can be used to assist ininterpreting these results will be analyzed in greater detailin a future publication.

A few useful guidelines when conducting experimentswith the aim of estimating the distribution of particle fracture energies are:
● Particles should be contained in very narrow size ranges,
ideally resulting from sieving following a 4 2 series;● Particle selection for the test should be conducted
randomly, so as to guarantee that each lot tested has
approximately the same average weight; (37)
● Sample preparation should be carried out carefully, so
as to avoid the use of crushing processes that may be
responsible for generating flaky material, such as rollcrushing (Gupta, 2016). Ideally either no crushing or
the adoption of the size reduction process that is meant
to be used in the targeted industrial operation should
be preferred. Also, size reduction processes which are
known to induce cracks in particles, sub as high-pressureroll grinding (Tavares, 2005), should also be avoided,
whenever possible, in this task;● Differences in particle shapes introduce variability in the
distribution (Tavares, 2007; Lois-Morales et al., 2020).
One possibility to deal with this is to segregate particles
contained within the 4 2 series according to mass and

(37)
77

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

test separately. If that approach is not used, particles
should be randomly selected and the size of the tested lot
increased accordingly with the variability;● The number of particles tested in each size range must be
at least 30, but should increase as the variability of particle composition and shape in the sample also increases,
so that 50 or 100 are typically optimal;● In the case of tests in impact load cell devices, it is advisable to select an average specific impact energy for thetest (Eqn. 2) that is just high enough to break the toughest particle in the lot. The use of specific impact energies
that are much higher than those must be avoided, in particular in the case of testing less brittle materials, since
they can lead to greater difficulty in identifying properly
the load responsible for primary fracture (Fig. 18d).
While particles in the size range from 100 mm (Fandrichet al., 1998; Tavares, 2007) down to 0.25 mm (Tavares
and Cerqueira, 2007) have been tested in impact load cell
devices, the greatest challenge lies in measuring fractureenergies of particles contained in the lower range andeven finer sizes, given the tedious nature of testing single
particles and the limitation in the resolution of the devices.
Some researchers have demonstrated the potential of measuring the strength and fracture energies of fine particles in
special devices (Steier and Schönert, 1972; Yashima et al.,
1979; Sikong et al., 1990; Antonyuk et al., 2005; Nguyen
et al., 2009; Yan et al., 2009). Ribas et al. (2014) showed
the potential of using a commercially-available micro compression tester to measure the fracture energy distributionsof single particles in the 45–37 μm size range, whereas
Campos et al. (2021) recently applied it to test iron ore
particles contained in the range of 45 to 150 μm, with goodresults. Nevertheless, due to the challenge in measuring
breakage characteristics of single particles down to suchfine sizes, some indirect estimation approaches have been
proposed. Barrios et al. (2011) proposed testing particles asfine as 150 μm contained in monolayer particle beds, combining them to data from single-particle breakage tests atcoarser sizes, and estimating the breakage parameters fromback-calculation, with reasonable success. More recently,
Tavares et al. (2020b) proposed combining measurementsof particle fracture energies of particles at relatively coarse
sizes to data from impact tests using a rotary breakage
tester. This allowed estimating selected material breakage
parameters of a copper-gold ore down to 350 μm (Tavares
et al., 2020b).
Yet another alternative to estimate breakage parametersin Eqn. (10) is to back-calculate them from batch grinding
tests, assuming that predictions using the UFRJ mechanistic mill model (Tavares and Carvalho, 2009; Carvalho
and Tavares, 2013) are strictly accurate. This approach has
been used to estimate breakage parameters of an iron ore
from batch milling data (Carvalho et al., 2021) as well as of78

limestone to stirred milling data (Oliveira et al., 2020). In
these cases, the parameters from Eqns. (7), (12), (16) and(20) were taken from similar ores.
Evidently, errors can appear in estimates from backcalculation, since they rely on the validity of the various
assumptions. In the particular case when only batch
grinding results are used, errors may be associated to thefact that any limitation in the mill model in describing thephenomenon would inevitably contaminate the estimatesof material breakage parameters, partially contradicting thevery approach of the advanced models in fully decouplingmaterial from process. In addition to that, this approachalso requires that some parameters be taken from similarmaterials, which also involves a potential source of bias,
since each material is intrinsically unique in regard to
breakage response.
As discussed in section 3.3, more effort should be
dedicated to modeling the primary breakage function
from single-particle breakage, given its central role in theapplication of the model in particular to discrete systems
in DEM. One device that could be useful in this task is
the rigidly-mounted roller mill, which crushes particles
nearly individually between rigidly-mounted rollers withcarefully controlled gaps (Böttcher et al., 2021). In spiteof challenges in measuring the energy required to break
particles contained in the finest sizes studied (45 μm), it
provided good estimates of the size distribution of particles
under stressing conditions that approach the minimum
required for fracture (Campos et al., 2021).

5.2 Model applications
The breakage model described has been used either incomplete form or in parts in simulating different systems ofinterest using a variety of approaches. In its discrete form
it has been embedded in DEM as part of different particle
replacement schemes. Initially, a cutdown version of themodel, which did not incorporate description of weakening
by repeated impacts (section 2.4), was implemented in
EDEM (Jiménez-Herrera et al., 2018; Barrios et al., 2020),
demonstrating some ability to describe breakage in bothconfined and unconfined particle beds. A more complete
version of the model, incorporating a new stochastic
description of particle replacement (Tavares and Chagas,
2021) was implemented in an updated version of EDEM
(Tavares et al., 2021), demonstrating very good ability
to predict unconfined breakage of particle beds. Bothapproaches were based on spherical particle replacement,
which has the advantage of computational efficiency. This
later implementation also incorporated description of theunresolved fines, which were added upon completion of
the simulation to the size distribution given by the resolved
spheres. The more complete version of the model has also
been implemented in the commercial software package

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

Rocky DEM (Tavares et al., 2020a). Such implementation,
based on breakage of polyhedral particles, provided very
good predictions of breakage in unconfined particle beds
(Tavares et al., 2020a) and cone crushing (André andTavares, 2020).
The breakage model has also been widely used as partof advanced models of crushers and mills. For instance,
Austin (2004a; 2004b) used the damage model fromsection 2.4 in a phenomenological model of high-speed
hammer milling. The full version of the breakage model
has been used to predict degradation during handling ofmaterials (Tavares and Carvalho, 2011). It has also been
used, coupled to DEM, to model crushing in a vertical shaft
impact crusher (Cunha et al., 2014), as well as of degradation of recycled aggregate in a high-shear mixer (MorenoJuez et al., 2021). The modeling approach has also beenused to predict degradation of iron ore pellets during
handling using slightly customized mathematical expressions (Cavalcanti et al., 2019; 2021; Tavares et al., 2018).
The widest use of the model has been in association to a
microscale population balance formulation, called UFRJ
model, to describe grinding in media mills, including ballmills (Tavares and Carvalho, 2009; Carvalho and Tavares,
2013), semi-autogenous mills (Carvalho and Tavares,
2011) and stirred mills (Oliveira et al., 2020; 2021). A version of the ball mill model of continuous milling with some
simplifications is available in the state-of-the-art mining
and mineral processing plant simulator IES (Integrated
Extraction Simulator).

6. Summary and conclusions

autogenous and semi-autogenous, being even available(ball mill model) in the plant simulator IES.
While being able to account for several importantvariables that influence particle breakage, challenges are
identified in application and fitting of the model parameters
for particular applications. Being a single-particle-basedmodel, challenges exist in estimating breakage parameters
for fine particles. Establishing the validity of novel testing
devices as well as of back-calculation approaches, is an
important task. Further, modifications in the model in orderto make it applicable to describe breakage of non-brittle
materials (Tavares and Almeida, 2020) is another worthwhile task for advancing model applicability. Finally,models describing surface breakage, which are particularly
relevant in predicting mechanical degradation during
handling, require more attention, since they are still at acomparatively earlier stage of development and validation.

Acknowledgements
The author would like to thank the financial support fromthe Brazilian agencies CNPq (grant number 310293/20170) and FAPERJ (grant number E-26/202.574/2019), as wellas the team of researchers in his group and outside collaborators for their contributions throughout the developmentof this work.

NomenclatureA

A practical model describing breakage of single particles
has been proposed over the last 25 years. It discriminates
body and surface breakage, accounting for the body breakage probability through the upper-truncated lognormal
distribution. It is able to predict breakage by repeatedimpacts owing to a model describing weakening based oncontinuum damage mechanics. Body-breakage progeny
size distribution is described using the incomplete beta
function, which also considers the exceptional cases inwhich the material exhibits non-normalizable breakage
response. With an empirical expression that describes thestressing energy and size-dependent breakage intensity,
it can predict the size distribution of fragments from any
stressing event.
This breakage model has been implemented and is
now an integral part of particle replacement schemes embedded in commercial DEM software (Rocky DEM andAltair EDEM), through which it may be used to simulate anumber of industrial processes of interest. It has also been
incorporated in microscale population balance models describing several mill types, namely ball mills, stirred mills,

Aij
aij
b′
Bij
bij
D
Di
D*
dA
di
do

parameter of the t10 versus specific impact energy
relationship (%)
proportion of particles finer than size i generated
from surface breakage of particles in size class j (-)
proportion of particles contained in size class i
generated from surface breakage of particles in sizeclass j (= Ai–1,j – Aij) (-)
parameter of the t10 versus specific impact energy
relationship (-)
proportion of particle finer than size class i resulting
from body breakage of particles contained in sizeclass j (-)
proportion of particle contained in size class i
resulting from body breakage of particles containedin size class j (= Bi–1,j – Bij) (-)
damage variable (-)
sieve size (m)minimum normalization size (m)maximum size of surface breakage products (m)representative size of particles contained in sizeclass i (m)parameter describing the variation of the particle
fracture energy with particle size (m)79

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

e
E
Ek
Emax
E50
E50b
E*

E′
E∞
F
g
h
k

kp
ks
m
mp

mp
Nb
N
(51)
P(Ek)
tn
t10
v

wi

(52)
x
Y
z
α
αn
βn
γ
Δ
Δc
η
κ
λ
ν
ξi

80

proportion of the impact energy dissipated in theparticle (-)
mass-specific fracture energy of the particle (J/kg)
specific impact energy (J/kg)
upper truncation value of the distribution (J/kg)
median specific fracture energy (J/kg)
median specific fracture energy of particle thatbroke in an event (J/kg)
variable used to incorporate the upper truncationin the lognormal distribution of particle fractureenergies (J/kg)
fracture energy of the particle after the stressing
event (J/kg)
parameter describing the variation of the particle
fracture energy with particle size (J/kg)
force (N)acceleration due to gravity (m/s2)
net drop height (m)variable introduced to correct the bias of using themedian instead of the mean value of the distribution(-)
apparent particle stiffness (GPa)apparent surface stiffness (GPa)mass of the drop weight (kg)weight of each individual particle (kg)average weight of particles in the lot tested (kg)number of particles that underwent body breakage(-)
number of stressed particles (-)
proportion broken in impact of magnitude Ek (-)
proportion passing 1/nth of the parent particle size inthe fragments of a stressing event (-)
proportion passing 1/10th of the parent particle sizein the fragments of a stressing event (-)
average velocity at the instant of collision against
the target (m/s)
weight fraction of material contained in size classi (-)
relative fragment size (-)
Young’s modulus (GPa)reduced Gaussian distribution (-)
significance level of the confidence interval
parameter of the incomplete beta function for tn (-)
parameter of the incomplete beta function for tn (-)
damage accumulation coefficient (-)
deformation (m)deformation at primary fracture (m)parameter describing the shape of the nonnormalizable part of the breakage distribution (-)
attrition parameter (kg/mmJ)
parameter in the non-normalizable body breakage
function (-)
Poisson’s ratio (-)
proportion of attrition products (-)σφ

standard deviation of the lognormal distribution of
fracture energies (-)
parameter describing the variation of the particle
fracture energy with particle size (-)

References
André F.P., Tavares L.M., Simulating a laboratory-scale conecrusher in DEM using polyhedral particles, Powder
Technology, 372 (2020) 362–371. DOI: 10.1016/j.powtec.
2020.06.016
Angulo S.C., Silva N.V., Lange D.A., Tavares L.M., Probability
distributions of mechanical properties of natural aggregatesusing a simple method, Construction and Building Materials, 233 (2020) 117269. DOI: 10.1016/j.conbuildmat.
2019.117269
Antonyuk S., Tomas J., Heinrich S., Mörl L., Breakage behaviourof spherical granulates by compression, Chemical Engineering Science, 60 (2005) 4031–4044. DOI: 10.1016/j.
ces.2005.02.038
Arbiter N., Harris C.C., Stamboltzis G.A., Single fracture ofbrittle spheres, Transactions of the SME/AIME, 244 (1969)
118–133.
Austin L.G., A preliminary simulation model for fine grindingin high speed hammer mills, Powder Technology, 143–144(2004a) 240–252. DOI: 10.1016/j.powtec.2004.04.017
Austin L.G., The effect of damage on breakage kinetics, Powder
Technology, 143–144 (2004b) 151–159. DOI: 10.1016/j.
powtec.2004.04.048
Austin L.G., Klimpel R.R., Luckie P.T., Process Engineering ofSize Reduction: Ball Milling, Society of Mining Engineersof the AIME, 1984, ISBN: 9780895204219.
Ballantyne G.R., Bonfils B., Powell M.S., Evolution of impact
breakage characterisation: re-defining t-family relationship,
International Journal of Mineral Processing, 168 (2017)
126–135. DOI: 10.1016/j.minpro.2017.10.001
Barrios G.K.P., de Carvalho R.M., Tavares L.M., Extending
breakage characterisation to fine sizes by impact on particle
beds, Mineral Processing and Extractive Metallurgy, 120(2011) 37–44. DOI: 10.1179/1743285510y.0000000002
Barrios G.K.P., Jiménez-Herrera N., Tavares L.M., Simulationof particle bed breakage by slow compression and impact
using a DEM particle replacement model, Advanced Powder Technology, 31 (2020) 2749–2758. DOI: 10.1016/j.
apt.2020.05.011
Baumgardt S., Buss B., May P., Schubert H., On the comparisonof results in single grain crushing under different kinds ofload, Proceedings of the 11th International Mineral Processing Congress, Cagliari, 1975, pp. 3–32.
Becker M., Kwade A., Schwedes J., Stress intensity in stirred
media mills and its effect on specific energy requirement,International Journal of Mineral Processing, 61 (2001)
189–208. DOI: 10.1016/s0301-7516(00)00037-5
Bergstrom B.H., Sollenberger C.L., Mitchell Jr. W., Energy
aspects of single particle crushing, Transactions of the AIME,
220 (1961) 367–372.
Boechat F.O., de Carvalho R.M., Tavares L.M., Simulation of
mechanical degradation of iron ore pellets in a direct reduction furnace, KONA Powder and Particle Journal, 35 (2018)
216–225. DOI: 10.14356/kona.2018009
Bond F.C., Crushing tests by pressure and impact, Transactions of
the AIME, 169 (1947) 58–66.

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

Bonfils B., Quantifying of impact breakage of cylindrical rockparticles on an impact load cell, International Journal of
Mineral Processing, 161 (2017) 1–6. DOI: 10.1016/j.minpro.
2017.02.005
Bonfils B., Ballantyne G.R., Powell M.S., Developments in incremental rock breakage testing methodologies and modelling,
International Journal of Mineral Processing, 152 (2016)
16–25. DOI: 10.1016/j.minpro.2016.04.010
Böttcher A.-C., Thon C., Fragnière G., Chagas A., Schilde C.,
Kwade A., Rigidly-mounted roll mill as breakage tester forcharacterizing fine particle breakage, Powder Technology,
383 (2021) 554–563. DOI: 10.1016/j.powtec.2021.01.055
Bourgeois F.S., Single-particle fracture as a basis for
microscale modeling of comminution processes, Ph.D.
thesis, The University of Utah, 1993. https://utah-primoprod.
hosted.exlibrisgroup.com/permalink/f/dtufc4/UUU_
ALMA21242038230002001
Capece M., Bilgili E., Davé R.N., Formulation of a physicallymotivated specific breakage rate parameter for ball milling
via the discrete element method, AIChE Journal, 60 (2014)
2404–2415. DOI: 10.1002/aic.14451
Campos T.M., Bueno G., Barrios G.K.P., Tavares L.M., Pressing
iron ore concentrate in a pilot-scale HPGR. Part 1: experimental results, Minerals Engineering, 140 (2019) 105875.
DOI: 10.1016/j.mineng.2019.105875
Campos T.M., Bueno G., Rodriguez V.A., Böttcher A.-C., Kwade
A., Mayerhofer F., Tavares L.M., Relationships between particle breakage characteristics and comminution response offine iron ore concentrates, Minerals Engineering, 164 (2021)
106818. DOI: 10.1016/j.mineng.2021.106818
Carvalho R.M., Campos T.M., Faria P.M., Tavares L.M.,
Mechanistic modeling and simulation of grinding iron orepellet feed in pilot and industrial-scale ball mills, Powder
Technology, 392 (2021) 489–502. DOI: 10.1016/j.powtec.
2021.07.030
Carvalho R.M., Secchi A.R., Tavares L.M., A new breakage
function model and optimization procedure for mechanistic comminution models, Proceedings of the 14th
European Symposium on Comminution and Classification,
Gothenburg, 2015, pp. 42–45.
Carvalho R.M., Tavares L.M., Leaping forward in SAG and
AG mill simulation using a mechanistic model framework,
Proceedings of the International Autogenous Grinding,Semi-Autogenous Grinding and High-Pressure Roll Technology Conference, Vancouver, 2011, pp. 1–26.
Carvalho R.M., Tavares L.M., Predicting the effect of operating
and design variables on breakage rates using the mechanistic ball mill model, Minerals Engineering, 43–44 (2013)
91–101. DOI: 10.1016/j.mineng.2012.09.008
Cavalcanti P.P., de Carvalho R.M., das Chagas A.S., da Silveira
M.W., Tavares L.M., Surface breakage of fired iron orepellets by impact, Powder Technology, 342 (2019) 735–743.
DOI: 10.1016/j.powtec.2018.10.044
Cavalcanti P.P.S., Petit H.A., Thomazini A.D., de Carvalho
R.M., Tavares L.M., Modeling of degradation by impact ofindividual iron ore pellets, Powder Technology, 378 (2021)
795–807. DOI: 10.1016/j.powtec.2020.10.037
Cavalcanti P.P., Tavares L.M., Statistical analysis of fracture characteristics of industrial iron ore pellets, Powder Technology,
325 (2018) 659–668. DOI: 10.1016/j.powtec.2017.11.062
Cavalcanti P.P., Tavares L.M., Static and dynamic compressive
loading of fired iron ore pellets, Powder Technology, 354(2019) 281–288. DOI: 10.1016/j.powtec.2019.06.006
Cunha E.R., Carvalho R.M., Tavares L.M., A predictive modelof the Vertical Shaft Impact (VSI) crusher, Proceedings of

the 9th International Comminution Symposium, Cape Town,
2014, 2014, v. 1. p. 1–13.
Dan C.C., Schubert H., Breakage probability, progeny size distribution and energy utilization of comminution by impact,
Aufbereitungs-Technik, 31 (1990) 241–247.
Datta A., Rajamani R.K., A direct approach of modeling batch
grinding in ball mills using population balance principles
and impact energy distribution, International Journal of
Mineral Processing, 64 (2002) 181–200. DOI: 10.1016/
s0301-7516(01)00044-8
Fandrich R.G., Clout J.M.F., Bourgeois F.S., The CSIRO
Hopkinson bar facility for large diameter particle breakage,
Minerals Engineering, 11 (1998) 861–869. DOI: 10.1016/
s0892-6875(98)00073-9
Faria P.M.C., Rajamani R.K., Tavares L.M., Optimization ofsolids concentration in iron ore ball milling through modelingand simulation, Minerals, 9 (2019) 366. DOI: 10.3390/
min9060366
Ghadiri M., Zhang Z., Impact attrition of particulate solids. Part
1: a theoretical model of chipping, Chemical Engineering
Science, 57 (2002) 3659–3669. DOI: 10.1016/s00092509(02)00240-3
Gupta V.K., Determination of the specific breakage rate
parameters using the top-size-fraction method: preparationof the feed charge and design of experiments, Advanced
Powder Technology, 27 (2016) 1710–1718. DOI: 10.1016/j.
apt.2016.06.002.
Jiménez-Herrera N., Barrios G.K.P., Tavares L.M., Comparisonof breakage models in DEM in simulating impact on particle
beds, Advanced Powder Technology, 29 (2018) 692–706.
DOI: 10.1016/j.apt.2017.12.006
Kachanov L.M., Time of the rupture process under creep conditions (in Russian), Izy Akad. Nank SSR Otd Tech Nauk, 8(1958) 26–31.
King R.P., Modeling and Simulation of Mineral Processing Systems, 1st edition, Butterworth-Heinemann, London, 2001,
ISBN: 978-0-08-051184-9.
King R.P., Bourgeois F.S., A new conceptual model for ball milling, Proceedings of the 18th International Mineral Processing
Congress, Sydney, 1993, pp. 81–86.
Krogh S.R., Crushing characteristics, Powder Technology, 27(1980) 171–181. DOI: 10.1016/0032-5910(80)85019-4
Lois-Morales P., Evans C., Bonfils B., Weatherley D., The impact
load cell as a tool to link comminution properties to geomechanical properties of rocks, Minerals Engineering, 148(2020) 106210. DOI: 10.1016/j.mineng.2020.106210
Mishra B.K., Rajamani R.K., The discrete element method for thesimulation of ball mills, Applied Mathematical Modelling, 16(1992) 598–604. DOI: 10.1016/0307-904x(92)90035-2
Moreno-Juez J., Tavares L.M., Artoni R., de Carvalho R.M.,
da Cunha E.R., Cazacliu B., Simulation of the Attrition of
Recycled Concrete Aggregates during Concrete Mixing,
Materials, 14 (2021) 3007. DOI: 10.3390/ma14113007
Morrell S., An alternative energy–size relationship to that proposed by Bond for the design and optimisation of grinding
circuits, International Journal of Mineral Processing, 74(2004) 133–141. DOI: 10.1016/j.minpro.2003.10.002
Morrison R.D., Cleary P.W., Using DEM to model ore breakage
within a pilot scale SAG mill, Minerals Engineering, 17(2004) 1117–1124. DOI: 10.1016/j.mineng.2004.06.016
Morrison R.D., Shi F., Whyte R., Modelling of incrementalrock breakage by impact – for use in DEM models, Minerals Engineering, 20 (2007) 303–309. DOI: 10.1016/j.
mineng.2006.10.015
Napier-Munn T.J., Mineral Comminution Circuits: Their Opera-

81

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

tion and Optimisation, Julius Kruttschnitt Mineral ResearchCentre, 1996, ISBN: 9780646288611.
Narayanan S.S., Determination of comminution characteristics
from single particle breakage tests and its application to ballmill scale-up, Transactions of the Institution of Mining andMetallurgy C, 97 (1988) 115–124.
Nguyen V.B., Wang C.X., Thomas C.R., Zhang Z., Mechanicalproperties of single alginate microspheres determined by
microcompression and finite element modelling, Chemical
Engineering Science, 64 (2009) 821–829. DOI: 10.1016/j.
ces.2008.10.050
Oliveira A.L.R., de Carvalho R.M., Tavares L.M., Predicting
the effect of operating and design variables in grinding
in a vertical stirred mill using a mechanistic mill model,
Powder Technology, 387 (2021) 560–574. DOI: 10.1016/j.
powtec.2021.04.057
Oliveira A.L.R., Rodriguez V.A., de Carvalho R.M., Powell M.S.,
Tavares L.M., Mechanistic modeling and simulation of abatch vertical stirred mill, Minerals Engineering, 156 (2020)
106487. DOI: 10.1016/j.mineng.2020.106487
Ouchterlony F., Sanchidrián J.A., The Fragmentation-energy fan
concept and the Swebrec function in modeling drop weighttesting, Rock Mechanics and Rock Engineering, 51 (2018)
3129–3156. DOI: 10.1007/s00603-018-1458-5
Pauw O.G., Maré M.S., The determination of optimum
impact-breakage routes for an ore, Powder Technology, 54(1988) 3–13. DOI: 10.1016/0032-5910(88)80043-3
Piret E.L., Fundamental aspects of grinding, Chemical Engineering Progress, 49 (1953) 56–63.
Powell M.S., Hilden M., Ballantyne G., Liu L.X., Tavares
L.M., The appropriate, and inappropriate, application of
the JKMRC t10 relationship, Proceedings of the 27th International Mineral Processing Congress, Santiago, Gecamin,
2014, v. 1, pp. 1–13.
Ribas L., Cordeiro G.C., Toledo Filho R.D., Tavares L.M.,
Measuring the strength of irregularly-shaped fine particles ina microcompression tester, Minerals Engineering, 65 (2014)
149–155. DOI: 10.1016/j.mineng.2014.05.021
Rodnianski V., Levy A., Kalman H., A new method for simulationof comminution process in jet mills, Powder Technology, 343(2019) 867–879. DOI: 10.1016/j.powtec.2018.11.021
Rozenblat Y., Portnikov D., Levy A., Kalman H., Aman S., TomasJ., Strength distribution of particles under compression,
Powder Technology, 208 (2011) 215–224. DOI: 10.1016/j.
powtec.2010.12.023
Rozenblat Y., Grant E., Levy A., Kalman H., Tomas J., Selection
and breakage functions of particles under impact loads,
Chemical Engineering Science, 71 (2012) 56–66. DOI:
10.1016/j.ces.2011.12.012
Rumpf H., Physical aspects of comminution and new formulationof a law of comminution, Powder Technology, 7 (1973)
145–159. DOI: 10.1016/0032-5910(73)80021-x
Saeidi F., Tavares L.M., Yahyaei M., Powell M., A phenomenological model of single particle breakage as a multi-stage
process, Minerals Engineering, 98 (2016) 90–100. DOI:
10.1016/j.mineng.2016.07.006
Saeidi F., Yahyaei M., Powell M., Tavares L.M., Investigating
the effect of applied strain rate in a single breakage event,
Minerals Engineering, 100 (2017) 211–222. DOI: 10.1016/j.
mineng.2016.09.010
Salman A.D., Biggs C.A., Fu J., Angyal I., Szabó M., Hounslow
M.J., An experimental investigation of particle fragmentation
using single particle impact studies, Powder Technology, 128(2002) 36–46. DOI: 10.1016/s0032-5910(02)00151-1
Salman A.D., Fu J., Gorham D.A., Hounslow M.J., Impact break-82

age of fertiliser granules, Powder Technology, 130 (2003)
359–366. DOI: 10.1016/s0032-5910(02)00237-1
Schönert K., Role of fracture physics in understanding comminution phenomena, Transactions of the SME/AIME, 252 (1972)
21–26.
Schönert K., Aspects of physics of breakage relevant to comminution, Proceedings of the 4th Tewksbury Symposium,
Melbourne, 1979, pp. 3.1–3.9.
Schönert K., Advances in comminution fundamentals and impacts
on technology, Aufbereitungs-Technik, 32 (1991) 487–494.
Schubert H., On the microprocesses of comminution. Aufbereitungs–Technik, 5 (1987) 237–246.
Sikong L., Hashimoto H., Yashima S., Breakage behavior of fineparticles of brittle minerals and coals, Powder Technology, 61(1990) 51–57. DOI: 10.1016/0032-5910(90)80065-7
Steier K., Schönert K., Verformung und Bruchphanomene unter
druckbeanspruchung von sehr kleinen kornern aus Kalkstein,
Quarz und Polystyprol, Dechema-Monographien, 69 (1972)
167–192.
Tavares L.M., Microscale investigation of particle breakage
applied to the study of thermal and mechanical predamage,
Ph.D. thesis, University of Utah, 1997. https://utah-primoprod.
hosted.exlibrisgroup.com/permalink/f/1g0gstr/TN_cdi_
proquest_journals_304394788
Tavares L.M., Energy absorbed in breakage of single particles indrop weight testing, Minerals Engineering, 12 (1999) 43–50.
DOI: 10.1016/s0892-6875(98)00118-6
Tavares L.M., Role of particle microstructure in comminution,
Proceedings of the 21st International Mineral Processing
Congress, Rome, Elsevier, 2000, Vol. C, pp. C4-99–C4-106.
Tavares L.M., Optimum routes for particle breakage by impact,
Powder Technology, 142 (2004) 81–91. DOI: 10.1016/j.
powtec.2004.03.014
Tavares L.M., Particle weakening in high-pressure roll grinding,Minerals Engineering, 18 (2005) 651–657. DOI: 10.1016/j.
mineng.2004.10.012
Tavares L.M., Breakage of single particles: quasi-static. In: A.D.
Salman, M. Ghadiri, M.J. Hounslow (Eds.), Handbook ofParticle Breakage, volume 12, 1st edition, Elsevier, 2007,
pp. 3–68, ISBN: 9780444530806.
Tavares L.M., Analysis of particle fracture by repeated stressing
as damage accumulation, Powder Technology, 190 (2009)
327–339. DOI: 10.1016/j.powtec.2008.08.011
Tavares L.M., A review of advanced ball mill modelling, KONA
Powder and Particle Journal, 34 (2017) 106–124. DOI:
10.14356/kona.2017015
Tavares, L.M., André, F.P., Potapov, A., Maliska Jr., C., Adapting
a breakage to discrete elements using polyhedral particles,
Powder Technology, 362 (2020a), 208–220. DOI: 10.1016/j.
powtec.2019.12.007
Tavares L.M., Carvalho R.M., Impact work index prediction
from continuum damage model of particle fracture, Minerals Engineering, 20 (2007) 1368–1375. DOI: 10.1016/j.
mineng.2007.08.021
Tavares L.M., Cavalcanti P.P., de Carvalho R.M., da Silveira
M.W., Bianchi M., Otaviano M., Fracture probability andfragment size distribution of fired Iron ore pellets by impact,
Powder Technology, 336 (2018) 546–554. DOI: 10.1016/j.
powtec.2018.06.036
Tavares L.M., Cerqueira M.C., Statistical analysis of impactfracture characteristics and microstructure of industrial
Portland cement clinkers, Cement and Concrete Research,
36 (2006) 409–415. DOI: 10.1016/j.cemconres.2005.09.012
Tavares L.M., das Chagas A.S., A stochastic particle replacement strategy for simulating breakage in DEM, Powder

Luís Marcelo Tavares / KONA Powder and Particle Journal No. 39 (2022) 62–83

Technology, 377 (2021) 222–232. DOI: 10.1016/j.powtec.
2020.08.091
Tavares L.M., das Neves P.B., Microstructure of quarry rocks andrelationships to particle breakage and crushing, International
Journal of Mineral Processing, 87 (2008) 28–41. DOI:
10.1016/j.minpro.2008.01.007
Tavares L.M., de Almeida R.F., Breakage of green iron orepellets, Powder Technology, 366 (2020) 497–507. DOI:
10.1016/j.powtec.2020.02.074
Tavares L.M., de Carvalho R.M., Modeling breakage rates ofcoarse particles in ball mills, Minerals Engineering, 22(2009) 650–659. DOI: 10.1016/j.mineng.2009.03.015
Tavares L.M., de Carvalho R.M., Modeling ore degradation
during handling using continuum damage mechanics, International Journal of Mineral Processing, 101 (2011) 21–27.
DOI: 10.1016/j.minpro.2010.07.008
Tavares L.M., de Carvalho R.M., Bonfils B., de Oliveira A.L.R.,
Back-calculation of particle fracture energies using data fromrotary breakage testing devices, Minerals Engineering, 149(2020b) 106263. DOI: 10.1016/j.mineng.2020.106263
Tavares L.M., King R.P., Single-particle fracture under impact
loading, International Journal of Mineral Processing, 54(1998) 1–28. DOI: 10.1016/S0301-7516(98)00005-2
Tavares L.M., King R.P., Modeling of particle fracture by
repeated impacts using continuum damage mechanics,
Powder Technology, 123 (2002) 138–146. DOI: 10.1016/
S0032-5910(01)00438-7
Tavares L.M., King R.P., Measurement of the load–deformation
response from impact-breakage of particles, International
Journal of Mineral Processing, 74 (2004) S267–S277. DOI:
10.1016/j.minpro.2004.07.017
Tavares L.M., Rodriguez V.A., Sousani M., Padros C.B., Ooi J.Y.,
An effective sphere-based model for breakage simulationin DEM, Powder Technology, 392 (2021) 473–488. DOI:
10.1016/j.powtec.2021.07.031
Teo C.S., Waters A.G., Nicol S.K., Quantification of the breakageof lump materials during handling operations, International
Journal of Mineral Processing, 30 (1990) 159–184. DOI:

10.1016/0301-7516(90)90013-o
Vervoorn P.M.M., Austin L.G., The analysis of repeated breakage
events as an equivalent rate process, Powder Technology, 63(1990) 141–147. DOI: 10.1016/0032-5910(90)80036-x
Vogel L., Peukert W., Breakage behaviour of different materials—
construction of a mastercurve for the breakage probability,
Powder Technology, 129 (2003) 101–110. DOI: 10.1016/
S0032-5910(02)00217-6
Vogel L., Peukert W., Determination of material properties relevant to grinding by practicable labscale milling tests, International Journal of Mineral Processing, 74 (2004) S329–S338.
DOI: 10.1016/j.minpro.2004.07.018
Wang M.H., Yang R.Y., Yu A.B., DEM investigation of energy
distribution and particle breakage in tumbling ball mills,
Powder Technology, 223 (2012) 83–91. DOI: 10.1016/j.
powtec.2011.07.024
Weedon D.M., Wilson F., Modelling iron ore degradation usinga twin pendulum breakage device, International Journal of
Mineral Processing, 59 (2000) 195–213. DOI: 10.1016/
S0301-7516(99)00066-6
Weichert R., Application of defect statistics and fracture mechanics for describing comminution processes, Zement-KalkGips, 45 (1992) 51–57.
Yan Y., Zhang Z., Stokes J.R., Zhou Q.-Z., Ma G.-H., Adams
M.J., Mechanical characterization of agarose micro-particles
with a narrow size distribution, Powder Technology, 192(2009) 122–130. DOI: 10.1016/j.powtec.2008.12.006
Yashima S., Kanda Y., Sano S., Relationships between particle
size and fracture energy or impact velocity required to
fracture as estimated from single particle crushing, Powder
Technology, 51 (1987) 277–282. DOI: 10.1016/00325910(87)80030-x
Yashima S., Morohashi S., Saito F., Single particle crushingunder slow rate of loading, Science Reports of the ResearchInstitutes, Tohoku University Ser A, Physics, Chemistry
And Metallurgy, 28 (1979) 116–133. http://hdl.handle.
net/10097/28092

Author’s Short Biography
Luís Marcelo Tavares
Luís Marcelo Tavares is a Professor at Universidade Federal do Rio de Janeiro (UFRJ) in Brazil.
He received his bachelor’s degree in Mining Engineering (honors) and his master’s degree from
Universidade Federal do Rio Grande do Sul. He was awarded a Ph.D. degree in Extractive Metallurgy at the University of Utah. He has been a member of the faculty of UFRJ since 1998, where he
is head of the Laboratório de Tecnologia Mineral and has been Department chairman. His researchinterests include particle breakage, advanced models of comminution and of degradation during
handling, DEM, physical concentration, classification, iron ore processing and development of
pozzolanic materials. He is a founding member and currently president of the Global Comminution
Collaborative (GCC) and has received a number of awards from the Brazilian Association of Metallurgy, Materials and Mining (ABM).

83

KONA Powder and Particle Journal No. 39 (2022) 84–99/https://doi.org/10.14356/kona.2022009

Review Paper

Advances in the Rheological Characterization of Slurries ofElongated Particles †Saif Shaikh, Scott Strednak and Jason E. Butler *Department of Chemical Engineering, University of Florida, USA

Abstract
Inherent challenges regarding the rheological characterization of slurries of elongated particles have necessitatedthe development of alternatives to standardized rheometers. These methods of measurement, and the associatedadvances in the quantification of shear and normal stress measurements, are described. Also, recent advances inmodeling and predictive capabilities are summarized. During shearing flows, confinement substantially influences
the orientation distribution of the particles; this change in the microstructure impacts the rheology, even as thesmallest confining dimension exceeds seven particle lengths. The slow development of the orientation distributions
renders additional difficulties in evaluating the rheology. Achievements of the measurement methods include a
universal shear viscosity as a function of concentration for a wide range of particle lengths to diameters (aspectratios). The jamming limit (divergence of the viscosity with concentration) of the suspensions has been also
shown to scale differently than for spheres. More general dynamics of the suspensions and the additional needs formeasurement improvements are discussed.
Keywords: rheology, concentrated slurries, fibers, microstructure

1. Introduction
Suspensions, a class of complex fluids wherein an insoluble phase, either a solid or a liquid is dispersed in a liquid(Larson, 1999), are ubiquitous in nature. Suspended particles can be spherical or near-spherical, discs, or elongatedin the form of fibers, and can be rigid or soft and flexible.
Suspensions occur naturally, with macroscale examples
such as lava and silt-laden rivers where the solid particles
are anisotropic and polydisperse. At the microscale, bloodis an example of another natural suspension where disc-likeplatelets are suspended in plasma. These suspensions canbe further categorized on the basis of their particle sizes
as Brownian and colloidal with sizes on the order of tensof nanometers to a few microns, to non-Brownian andnon-colloidal for particle sizes larger than a few microns.
In industry, suspensions of non-colloidal particles arefound in a wide variety of applications. Transport and processing of slurries containing wood fibers in the manufacture of paper products is an example where the particles arelong and flexible (Lundell et al., 2011). Rod-like particles
and flexible fibers are added to materials to create compos†*

84

Received 31 March 2021; Accepted 11 May 2021
J-STAGE Advance published online 26 June 2021
Corresponding author: Jason E. Butler;
Add: Gainesville, Florida 32611, USA
E-mail: butler@che.uﬂ.edu
TEL: +1-352-392-2591

ite materials with enhanced strength and performance, aswith fiber-reinforced concrete (Hassanpoura et al., 2012).
Fibers, both rigid and flexible, are also added to modify therheological properties of fluids used in the production ofoil (Bivens et al., 2005; Elgaddafi et al., 2012; Hammond,
1995; Osiptsov, 2017). In contrast, the presence of fibrous
minerals can have a detrimental impact on the operation of
flotation processes (Patra et al., 2012; Somasundaran et al.,2019), which are often used at mining sites to separate highvalue minerals from a slurry.
Various trade-offs exist while designing and operatingprocesses that contain particle suspensions. Decisions often
center on the balance between high energy usage at highparticle concentrations and high suspending fluid usage at
low particle concentrations. Regarding the latter, concerns
regarding overuse of water resources have been associatedwith many industries, including the example of mining andthe operation of on-site flotation processes (Liu et al., 2011;
Rao and Finch, 1989). At the other limit of high solids
content, the viscosity of the suspension increases and evendiverges as the solids content approaches maximum packing. As an immediate consequence, the power requirementsfor pumping and mixing suspensions can increase significantly, thereby significantly increasing processing costs.
Reliable, quantitative information on the rheology ofsuspensions can assist in managing these trade-offs. For
suspensions of spheres that are non-Brownian and noncolloidal, there has been considerable development of

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

rheological models. For volume fractions ϕ < 0.02 (i.e thethe ratio of the total volume of the suspended particles tothe total volume of the suspension), the viscosity ηs increases linearly according to Einstein’s equation (Einstein,1906),
5ηs  ηf 1   
 2 

(1)

where ηf is the viscosity of the suspending fluid. Higher
order corrections for suspension viscosity have been de(1)termined which extend the range of the volume fraction(Batchelor and Green, 1972). However, the complexityof the problem quickly surpasses analytical capabilities
as the concentration is increased, and computational
methods such as the Stokesian dynamics method (Brady
and Bossis, 1988) must be employed in order to makeprogress on calculations of rheology based on first principles. Experimentally characterizing the rheology ofconcentrated suspensions of spheres can pose difficulties
as well. Acrivos (1995) summarized discrepancies among
published reports on the shear viscosity and attributed thedifferences to a number of effects including shear-induced
migration (Leighton and Acrivos, 1987), which causes a
non-uniform distribution of particles within the testinggeometry. One generally accepted correlation for the
shear viscosity of suspensions of non-Brownian spheresin Newtonian fluids over a wide range of volume fractions
is given by the Krieger-Dougherty equation (Krieger andDougherty, 1959),
 ηs  ηf 1 



m 

ηm(2)

where ϕm is the maximum volume fraction at which theparticles pack randomly and [η] ≈ 2.5. Still, some debate(2) regarding rheological properties of concentrated
persists
suspensions of spheres, such as the sign of the first normal
stress difference (Guazzelli and Pouliquen, 2018).
Making well-informed decisions regarding processes
that utilize suspensions of particles that are non-sphericalis hampered by a relative lack of data and incomplete information on how to interpret that data. In the specific caseof suspensions of elongated particles, though the viscosity
scales with an increasing particle volume fraction, therelationship is much more complex. As an example, Fig. 1
shows rheological data obtained experimentally by Tapia
et al. (2017) for rigid polyamide fibers of different aspectratios and particle diameters. It is evident that the particle
shape has a significant impact on the rheology, and hence
equipment design as well as operating decisions must
consider these factors. However, obtaining reliable andaccurate rheological data can be challenging for these typesof suspensions composed of large rigid fibers at high concentration owing to confinement effects and the tendencyof the suspension microstructure to change drasticallyFig. 1 Rheological data obtained from Tapia et al. (2017) showing thedependence of the shear viscosity ηs on the particle volume fraction ϕ for
rigid fibers. The measured viscosities depend on the particle aspect ratio
A = L/d, where L and d are the particle length and diameter, respectively.
The results indicate that the viscosity diverges at a different volume
fraction for each aspect ratio, which roughly corresponds to maximum
random packing (ϕm).

depending upon the pattern of shearing flow.
This review focuses on the concentrated regime of slurries of elongated particles in effort to consolidate the sparsework done previously in this area and to summarize recent
and ongoing studies. Section 2 outlines the properties ofthe particles and fluids, as well as the regimes of particle
concentrations in the slurries under consideration in thisreview. Section 3 examines the rheological techniquesand measurements in the semi-dilute (Section 1) and concentrated (Section 2) regimes of concentration, focusing
on studies of the near-jamming limit. This section also
explores the effects of time-varying flow fields, focusing on
the relatively recent advances in oscillatory flows (Section2). Normal stress differences, which are of importancein predicting shear-induced migration, are discussed in
Section 4. Some comments on remaining challenges areoffered in the conclusions.

2. Suspension properties
This review focuses on slurries of elongated particles inviscous Newtonian fluids. Many of the studies described
use rod-shaped particles of aspect ratio, A = L/d >> 1,
where L is the length of the rod and d is its diameter. Unlessspecified otherwise, these particles are sufficiently large
to be non-Brownian. Consequently, the rotational Péclet
number Per = γ/dr should be large, where γ is the rate ofshear and dr is the rotational diffusivity,dr 

3kT ln 2 A
(31)
πηf L3(31)(3)

for a rod of high aspect ratio. The fluid viscosity is ηf, k
is the Boltzmann constant, and T is the temperature. An(3)85

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

alternative definition for the rods to be non-Brownian
requires a large Péclet number as defined by Pe = L2 γ/DT,
where DT is the mean center of mass diffusivity. Basing thedefinition of non-Brownian on Pe >> 1 is more stringent
than using Per since Pe = 9Per.
(31)
The particles chosen for idealized experiments are monodisperse in length and diameter. The materials of thesefibers are generally polymeric, for ease of production, use,
and manipulation. Polyamides like Nylon-6 and polystyrene (PS) are used in conventional rheometry experiments
owing to the ease of obtaining particles with a wide arrayof lengths, diameters, and aspect ratios, and mechanicalstrength. For imaging experiments, poly-methylmethacrylate (PMMA/acrylic) obtained from the core of fiber optic
cables have been optimal owing to their uniform opticalproperties.
The suspending media are Newtonian in all of the work
described in this review. The density of the fluids (ormixtures) were selected or altered to match the density ofthe particles; the particles neither sediment to the bottomor float to the top, negating any possible effects of gravity
on the dynamics and rheology. The above-mentioned
conditions are imposed upon the slurries to simplify thesubsequent measurements and analyses, by assuming thatin the absence of Brownian fluctuations and gravity, themotion of the particles in the slurries are primarily driven
by the flow imposed upon them. For imaging experiments,
the suspending media must also be chosen, or its composition altered, in order to match the refractive index of
the particles. When the fluid is subsequently dyed with afluorescing agent and properly illuminated, the contrast canbe used to obtain spatial and orientation data.
The elongated particles on which this review focuses
are rigid, neither stretching nor bending under the forces
imposed by the flow. For materials that are relatively soft,
shearing forces may be sufficient to bend a fiber and impact
the dynamics and rheology. Consequently, criteria havebeen developed for estimating the stress at which fibers
bend appreciably. Forgacs and Mason (1959) determineda critical stress, Σcrit, at which a slender rod buckles undercompressional flow as,Σ crit Eb ln 2 A  1.75
2 A4

(4)

where Eb is the bending modulus, estimated to be twice theYoung’s modulus of the particle. This model provided good(4)
agreement
for the bending of polymer fibers in shearing
flows with stresses of ηf γ (Forgacs and Mason, 1959). It
is assumed that any deformation of the elongated fiber isnegligible when the maximum stress exerted by the flow
field is much smaller than
Σcrit. A number of authors have(31)
developed similar ideas, defining a ratio of the imposed
fluid stresses of ηf γ and critical stresses as calculatedusing relations identical or similar to Eq. (4). Switzer andKlingenberg (1959) defined an effective stiffness, Seff, as
E y π (31)(5)
S eff  4
256ηf γA
where Ey is the Young’s modulus of the particle. Others(Lauga, 2007; Wandersman et al., 2010) inverted the ratioof (5)
shear stress and critical stress to create the “sperm number” SP as,

SP 

 4
8ηf γA
Ey(6)

Young and Shelley (2007) corrected the value of criticalstress used in the sperm number to give a slightly different(6)dimensionless
number ofS P* 

 4
128ηf γAE y ln 2 A  0.5(7)

Despite the differences in the various definitions, bendingof a fiber can be ignored so long as the product of the im(7)posed shear and viscosity (ηf γ) are much smaller than the
stress at which the fiber buckles.
The rheology and dynamics of suspensions of rigid fibers
differ greatly depending on the(31)extent to which rotation isimpeded by the presence of other fibers. Consequently,(Doi and Edwards, 1978) suggested defining concentration
regimes in terms of simple geometric constraints; examples
are shown in Fig. 2 of fibers randomly placed in a fixedvolume at dilute, semi-dilute, and concentrated conditions.

Fig. 2 Images of rigid fibers of aspect ratio A = L/d = 10 placed randomly in a volume at concentrations within the (a) dilute (nL3 << 1), (b) semi-dilute(1/L3 < n < 1/L2 d), and (c) concentrated (nL2 d > 1) regime. The volume fraction ϕ corresponding to each dimensionless number density is given in the
figure. At the highest concentration of nL2 d = 3.0, the suspension is isotropic for this aspect ratio.

86Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

For the case of dilute suspensions (nL3 << 1), sphericalvolumes that enclose each particle do not generally overlap
and each fiber can rotate freely. Here n = N/V is the number
density, the number of particles N per unit volume V ofthe suspension. Note the dimensionless number density
nL3 is equivalent to 4A2ϕ/π, where ϕ is the particle volume
fraction. In the semi-dilute region, fibers can no longer
rotate freely. The upper limit of the semi-dilute regime(nL2d = 4Aϕ/π ≈ 1) roughly corresponds to close packing
of a collection of flattened discs having a diameter of L
and thickness d. Further increases in concentration beyond
nL2d = 1 can occur while the spatial and orientation distribution remains isotropic, as demonstrated in Fig. 2c for
A = 10 and nL2d = 3.0. However at some point, maximum
random packing is exceeded and adding more particles
requires organizing the particle orientations into a nematic
phase. Studies (Williams and Philipse, 2003) indicate thatthe maximum volume fraction at which sphero-cylinders
can still pack randomly scales inversely with the aspectratio. For the case of A = 10 shown in Fig. 2, maximum
random packing occurs at nL2d ≈ 4.7, or ϕ ≈ 0.37; higher
concentrations require aligning the fibers. At A = 20, thetransition occurs at ϕ ≈ 0.22, or nL2d = 5.6.

3. Shear rheology and structure
The rheology of suspensions of well-dispersed rigid
fibers depends strongly upon the orientation distribution.
As a quantitative example, the shear viscosity for dilute
solutions of rigid fibers (nL3 < 1) that are force-free (i.e.
non-Brownian) is given by Batchelor (1970)(8)ηs  ηf 1  cnL3 p x2 p 2y 

where ηs is the viscosity of the suspension relative to thatof (8)
the fluid (ηf), c is a constant that depends on the particle

size and shape, and the expression ignores the small contributions to stress from the thickness of the particle, whichis assumed to be of high aspect ratio. The brackets,  ,indicate an average over all fibers in the suspension, where
the fibers have an orientation of p. Here, px and py represent
the orientation components in the flow (x) and gradient (33)(y)
directions.
Generally, the orientation (and position) of each rod ina suspension is set by balancing the non-hydrodynamic
torques (and forces) with hydrodynamic drag. In the particular case of a force-free fiber at dilute conditions, the fiber
tumbles indefinitely in a well-defined orbit that depends
on its initial orientation (Jeffery, 1922). Consequently theviscosity ηs oscillates in time as indicated in Eq. (8) owing
to its dependence of the ever-changing orientation momentp x2 p y2 . Measurements performed by Ivanov et al. (1982)
confirm that the viscosity oscillates during steady shear,though the amplitude of the oscillation decays over time.
The decay to a steady value is likely due to small effects(32)
that influence the torque balance on the fibers, possibly
including weak Brownian motion (Hinch and Leal, 1972)
or inertia (Einarsson et al., 2015).
Thorough reviews of the rheology of dilute suspensions
are available (Powell, 1991; Petrie, 1999) that discuss theseissues in depth. The remainder of this section describes
the measurement of more concentrated suspension whereparticle interactions begin to influence the orientation distributions and the measured rheology.

3.1 Semi-dilute concentrations
Fig. 3 shows viscosity measurements by Bibbó (1987)
and Djalili-Moghaddam and Toll (2006) for glass and nylon fibers of aspect ratios A ≈ 32 and 50. Measurements areshown for volume fractions of ϕ = 0.01 to 0.1, which correspond to dimensionless number densities nL3 spanning thesemi-dilute concentration regime (nL3 > 1 and nL2d < 1).

Fig. 3 Shear viscosity ηs relative to the fluid viscosity ηf as a function of fiber concentration nL3 for aspect ratios of (a) A ≈ 50 and (b) A ≈ 32; theconcentration range spans the semi-dilute regime of nL3 > 1 and nL2 d < 1. Experimental measurements of Bibbó (1987) and Bounoua et al. (2016a) arecompared to simulations (Mackaplow and Shaqfeh, 1996; Claeys and Brady, 1993) and the theory for semi-dilute suspensions of rigid rods by Shaqfeh
and Fredrickson (1990). A value of p x2 p 2y = 0.01 was used when evaluating the theory numerically. Error bars are shown for the sets of data whenavailable; for the data of Mackaplow and Shaqfeh (1996), the error is often smaller than the size of the data point.

[51]
87

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Viscosities for higher aspect ratio fibers are expected to belarger at the same concentration and for the same orientation
distribution, as indicated in the figure by the semi-dilute
theory (Shaqfeh and Fredrickson, 1990) where the samevalue of 0.01 for p x2 p y2 was used in calculating the curves.
Indeed, the experimentally measured viscosities in Fig. 3
are larger for the higher aspect ratio fibers. However, theinfluence of the (32)orientation distribution is strong: the viscosity of suspensions with fibers aligned with the flow wassignificantly lower than that of an isotropically distributed
fibers as seen in Fig. 3a (isotropic versus non-isotropic
data by Bibbó (1987)). For this reason, the influence ofbounding walls in confined geometries must be consideredwhen evaluating the measured rheology, especially as theconcentration approaches and surpasses nL2d = 1.
Beyond the dilute limit of nL3 = 1, interactions between
particles become increasingly important, and predicting therheology depends on at least two complicated calculations.
First, accurate determination of the spatial and orientation
distribution is necessary. Second, calculations that relate
the microstructure and stresses must be performed. In bothcases as reviewed in detail by Butler and Snook (2018),
hydrodynamic interactions between the particles must be
considered. This differs from the dilute and concentrated
regimes where the particles are either too far apart or the
dynamics and rheology are dominated by direct particleparticle contacts. Calculations that consider hydrodynamic
interactions between rigid rods, such as those shown in
Fig. 3, are computationally expensive, hence predicting the
microstructure and rheology for large numbers of fibers inthe semi-dilute regime remains an outstanding challenge.
Some results shown in Fig. 3 represent the high shear
limit of the measured viscosity. In the semi-dilute regime,
many slurries of rigid fibers exhibit shear-thinning rheology, where the measured viscosity decreases with increases
in rate of shear (Ganani and Powell, 1985; Powell, 1991;

Fig. 4 Steady shear viscosity ηs as a function of shear rate for a suspension of ellipsoids of aspect ratio A = 7 and for spheres (Bricker etal., 2008). Both suspensions have a volume fraction of ϕ = 0.07, and theparticles differ only in their shape, as each particle was composed of an
identical volume of polystyrene and was manufactured using the sameprocess.

88

Bricker et al., 2008; Bounoua et al., 2019). One example
from Bricker et al. (2008) is shown in Fig. 4 for a suspension of ellipsoids with a moderate aspect ratio of A = 7
at a concentration of nL3 = 4.4 (ϕ = 0.07). Although theparticles were relatively small in these experiments, thevalue of the rotational Péclet number was large, ranging
from approximately Per = 103 at the lowest shear rate ofγ = 0.1 s–1 to 106 at 100 s–1. Note that Fig. 4 also shows
viscosity data over the same range of shear rates for spheres
having properties (material of composition, volume of eachparticle, and method of manufacture) identical to that of the(31)
ellipsoids.
The substantial shear-thinning of the suspension of ellipsoids versus the spheres indicates a remarkable differencein the rheology originating from the shape of the particles.
These results contradict numerical simulations (Dinh andArmstrong, 1984; Shaqfeh and Fredrickson, 1990; Schiek
and Shaqfeh, 1995) which predict viscosities that are independent of shear-rate. Indeed, the rheology of suspensionsof non-Brownian and non-colloidal particles is expected
to be pseudo-Newtonian regardless of their shape: thoughattaining steady-state may require a large strain, or time,
the steady viscosity of the fluids should be independentof shear rate. Many ideas regarding the origin of the shear
thinning have been given, including the possibility that
non-Newtonian suspending fluids are responsible (Bibbó etal., 1985; Maschmeyer and Hill, 1977) and that the fibers
used in the experiments deform under the imposed stresses(Sepehr et al., 2004; Bennington et al., 1990). Attractive
colloidal forces have also been incorporated into models
to explain shear thinning (Chaouche and Koch, 2001;
Bounoua et al., 2016b), and this line of investigation has
been argued to be promising (Butler and Snook, 2018).

3.2 Concentrated suspensions
The rheology of suspensions of rod-shaped elongatedparticles in a Newtonian fluid beyond the semi-dilute regime remain largely unexplored. This is largely due to thedifficulty in performing rheological experiments with large,
rigid fibers at dimensionless number densities nL2d above
1.0. Under these conditions, confinement is a significant issue. Standard rheological tooling employs shearing geometries having gaps between the bounding walls of H≲1 mm.
This is particularly problematic for suspensions composedof non-colloidal fibers where the particles of interest canhave lengths L ≳ 0.1 mm. Typically it has been assumed
that the rheological measurements are not influenced by thebounding walls so long as H/L > 2 or 3 (Bibbó et al., 1985;
Powell, 1991; Chaouche and Koch, 2001). This is true fordilute, or even semi-dilute, suspensions since the additionaldrag on any one rod rapidly decays as the distance from thebounding wall increases (Zurita-Gotor et al., 2007; Park
and Butler, 2009). However, at higher concentrations theSaif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Fig. 5 Novel pressure-imposed rheometer used to measure bulk rheological properties at high concentrations near the jamming limit used by Tapia
et al. (2017). (A) Schematic of the experimental setup. (B): Microscope images of the plastic fibers. (C) Porous top plate with zoomed image of nylon
mesh. From “Rheology of concentrated suspensions of non-colloidal rigid fibers” by Franco Tapia, Saif Shaikh, Jason Butler, Olivier Pouliquen, andÉlisabeth Guazzelli, J. Fluid Mech (2017), vol. 827, R5. Reprinted with permission.

bounding walls have a strong effect on the rheology: thewalls prevent particles from rotating and moving freely,altering the orientation distribution. This disturbance inthe structure imposed by the wall propagates a significant
distance into the fluid at high concentrations. The measured
rheology will not match that of a bulk fluid unless the wall
spacing is much larger than 3L.
Consequently, Tapia et al. (2017) used a large, custombuilt device to make the viscosity measurements shown in
Fig. 1. The rheometer was originally constructed by Boyeret al. (2011a) and was used by them and Dagois-Bohy etal. (2015) to characterize a Newtonian fluid containing
spheres. This “imposed load” rheometer consisted of awide-gap annular shear cell with a movable top plate, as
shown in Fig. 5. The movable top plate has a porous screen
which allowed fluid to pass freely across the plate, butprevented fibers from passing. This enabled the dynamic
adjustment of the particle volume fraction while maintaining the volume of the particles.
Experiments were conducted in two modes: conventional rheometry with a controlled volume and a novel“pressure-imposed” mode. For the former mode, thevolume fraction of the suspension was maintained at aconstant value by holding the top plate at a fixed height; thetorque was measured as a function of rotation rate while
also recording the normal force needed to prevent the top
plate from moving. In the pressure-imposed mode, a constant normal force was applied to the top plate, allowing it
to move while measuring the torque as a function of rotation rate. In this case, the volume fraction ϕ varied with therate of rotation. The torque and rotation rate were used to
calculate the shear viscosity ηs as a function of ϕ as shownin Fig. 1. The normal force on the plate was corrected forbuoyancy and divided by the plate area to give a pressure P.

Fig. 6 Normal viscosity ηn for concentrated suspensions of rigid polyamide fibers suspended in a viscous Newtonian fluid (Tapia et al., 2017).
The normal viscosity is a unique measurement, as it is a bulk rheologicalmeasure of particle pressure.

This quantity represents the particle pressure that the fluctuating particles exert on the porous plate and is reported asa normal viscosity,
P
ηn 
(9)
ηf γ
as was done by Morris and Boulay (1999). These results
are shown in Fig. 6.
(9)
A unique result provided by these experiments is themeasurement of the rheology at concentration ranges approaching maximum packing fraction, ϕm. These measurements were made possible by performing experiments inthe “pressure-imposed” mode. Fig. 1 and Fig. 6 show thatthe shear and normal viscosities diverge at a value of ϕ that
depends on the aspect ratio A of the fibers and corresponds
closely to maximum random packing (ϕm) for each aspectratio. As the concentration, ϕ approaches ϕm, the suspension approaches the “jamming transition”. The maximum

89

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Fig. 7 (a) Shear viscosity and (b) normal viscosity of rod-shaped elongated particles as a function of increasing volume fraction ϕ collapse onto asingle curve when scaled with the maximum packing fraction ϕ/ϕm (Tapia et al., 2017). The solid red curves corresponds to the model equations given in
Eq. (10) and (11). The insets are log-log plots to determine the exponent value in Eq. (10) and is compared to that of spherical shaped particles (dashed).

packing fraction serves as an important scaling factor as
well: as shown in Fig. 7, the rheological data collapses onto
single-valued curves over the entirety of the range of particle sizes, aspect ratios, and concentrations measured in theexperiments. Constitutive equations (Tapia et al., 2017) for
the shear and normal viscosities, along with the coefficientof friction, developed using the maximum packing fraction
as a scaling factor, are0.90   ηs    14.51 m
 m 

(10)ηn    ηs   / μ   and
(10)

(11)
2

    m   μ    μs  c1  m(11)
  c2 

  
  

Fig. 8 The shear viscosity ηs before and after reversing the directionsof flow at the strain value of γ = 0. The suspension was composed of rigid
fibers with A = 18 and nL2 d = 3.2, and the measurements were madeusing a stress-controlled rheometer at two different values of the stress.
Data is from Bounoua et al. (2019).

(12)

where μs is the coefficient of static friction, c1 and c2 areconstants obtained from curve-fitting, and differ from the(12)values obtained from experiments with spherical particles(Dagois-Bohy et al., 2015).
Shear-thinning rheology has also been reported for suspensions of elongated fibers in the concentrated regime andthere is a wider range of measured values in this range ofconcentrations (Ganani and Powell, 1985; Powell, 1991).
Theories similar to those mentioned at the end of Sec. 3.1
have been put forward to explain both observations, including the presence of attractive interparticle forces. Tapia etal. (2017) did not report shear-thinning behavior in theirsystem, but did report finite yield stresses as have others.
These yield stresses increased with increasing volume fraction and fiber aspect ratio. Many have attributed the yieldstresses to attractive forces between the fibers, just as withshear thinning (Mongruel and Cloitre, 1999; Chaouche andKoch, 2001; Bounoua et al., 2016b).

3.3 Unsteady shear rheology
As with other non-Newtonian fluids such as polymer
and colloid solutions, rheological characterizations of fiber
suspensions under time-varying shearing flows can probe
the microstructure and forces that act within the system.
However, the absence of Brownian motion and a welldefined equilibrium state for these fluids requires carefulconsideration regarding what is measured; for example, theCox-Merz rule cannot be relied-upon for interpreting small
amplitude oscillatory flows. Here, the shear reversal andoscillatory shear rheology for concentrated suspensionsof fibers are described. As with steady shearing flows, apoint of concern is the effect of confinement on the measurements.

3.3.1 Shear reversal
Bounoua et al. (2019) measured the time-dependentshear viscosities upon suddenly reversing the direction ofa steady shearing flow. Fig. 8 shows the measurements asa function of strain (γ = γt) for a concentrated suspension(nL2d = 3.2, ϕ = 0.14) of rigid fibers of aspect ratio A = 18;

(31)
90

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

the results share similarities with other studies of shear
reversal of fiber suspensions (Sepehr et al., 2004). First,
the samples were sheared until the viscosity reached steadystate. Note that these suspensions of fibers were found to be
shear thinning, consequently the steady shear viscosity differed depending upon the applied stress. The reversal was
initiated at γ = 0 (i.e. t = 0), at which point the measured
viscosity dropped significantly. The low point following
the reversal was followed by a transient overshoot in theviscosity, before it returned to its steady value as confirmed
by comparing viscosity values at large γ to the values at
γ < 0, before reversing the flow direction.
Suspensions of non-colloidal spheres also exhibit reduction in the shear viscosity when the flow direction
is suddenly changed following a period of steady shear(Gadala-Maria and Acrivos, 1980; Narumi et al., 2002;
Blanc et al., 2011). Stresses resulting from the shearing flowof non-Brownian and non-colloidal particle suspensions
have two sources: hydrodynamic and contact forces. The
hydrodynamic contribution from each particle arises fromthe difference in velocity of the particle with the imposed
shear flow and velocity disturbances caused by the otherparticles, which depends upon the relative arrangement of
the particles. Direct contact forces between particles occur
due to the breakdown of lubrication interactions, possibly
because of surface roughness (Rampall et al., 1997; Ingber
et al., 2006; Pham et al., 2015).
For shear-reversal of suspensions of spherical particles, detailed analysis (Peters et al., 2016) of Stokesian
dynamics simulations indicate that the viscosity measured
immediately after the reversal represents the purely hydrodynamic contributions to the shear viscosity, as thecontact contribution disappears nearly entirely. During
steady shearing flow, contact interactions build-up among
the particles and contribute to the shear stresses. Suddenly
reversing the direction of flow relieves the contact forces,
which are purely repulsive, and the shear stress accordingly

drops.
Similarly, the sudden drop in the viscosity shown in
Fig. 8 indicates the presence of contact interactions between the fibers. However, the overshoot in viscosity represents an important difference in the results as comparedwith spheres, where the viscosity returns to its steady value
in a monotonic fashion. Bounoua et al. (2019) attributed
the overshoot to weak attractive force between the particles, rather than the dynamics changes in the orientation
distribution of the particles which surprisingly changes
little during the course of the reversal process (Cieslinski
et al., 2016). Measurements on suspensions of fibers that
do not shear-thin (i.e. have no attractive forces) would
presumably show no overshoot in the viscosity after shear
reversal.

3.3.2 Oscillatory shearing
A suspension of rigid fibers undergoing oscillatory shear
may yield vastly different measurements of the rheology,
depending on the concentration, confinement, and strain
amplitude of oscillation. Fig. 9a shows a strong qualitative
difference for the latter case, where η’’ (i.e. imaginary component of the complex viscosity) vanishes with increasing
oscillation number (N) or remains finite, depending on thestrain amplitude γ0 of the oscillation (Franceschini et al.,2014). The rheological data reported is for aspect ratio
A = 11 and a concentration of ϕ = 0.20; importantly, thesuspension was highly confined (H/L = 1.5).
Measurements (Franceschini et al., 2011; 2014; Strednak
et al., 2021) and simulations (Snook et al., 2012; Strednak
et al., 2021) of the orientation distribution under oscillatory flows also demonstrate a remarkable transition in thealignment as a function of strain amplitude. As shown in
Fig. 9b for the same aspect ratio A = 11 and a concentrationof ϕ = 0.20, the order parameter Sθ is maximized when
γ0 ≈ 2.5 (γ0ϕ/Φc ≈ 1.25 where Φc = 0.4). Here,Sθ = 1 – 2 < cos2θ >(13)

Fig. 9 Oscillatory rheology and orientation distribution for suspensions of rigid rods at a confinement of H = 1.5L. (a) The value of η'' as a functionof oscillation number N at A = 11 and ϕ = 0.20 for a range of strain amplitudes γ 0 (Franceschini et al., 2014). The result for γ 0 < 2.60 marks a transition
between vanishing and persistent values for η''. (b) Simulated predictions (Strednak et al., 2021) and an experimental measurement (Franceschini et al.,2014) of the microstructure S θ at steady state as a function of the rescaled strain amplitude, γ 0 ϕ/Φc. A value of 0.4 was used for Φc.

91

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Fig. 10 (a) The angle between the fiber’s projection in the flow-vorticity plane and the flow direction is θ. The x, y, and z directions are the flow,
gradient, and vorticity directions, respectively. (b) Reproduced rendering of simulations from Strednak et al. (2021) showing an example initial (N = 0)
and steady (N = 4000) distribution of the fibers for H = 1.5L, A = 11, ϕ = 0.20, and γ 0 = 2.5. Larger values of S θ reflect an increased alignment of fibers
in the vorticity direction.

where θ is the angle between the fiber projection in theflow-vorticity plane and the flow direction as depicted inFig. 10a; the brackets (  ) indicate an average over all
fibers. Note that fibers are perfectly aligned in the flow
and vorticity directions when Sθ = –1 and 1, respectively;
the gradient direction is perpendicular
to the flow-vorticity(33)
plane and is the same direction of the confinement in theexperiments. Consequently, the large value of Sθ at γ0 ≈ 2.5
indicates strong alignment of the fibers in the vorticity direction, as can be directly seen in Fig. 10b which compares
the initial and final distribution of the fibers predicted bysimulations. Note that the simulated values of Sθ quantitatively matched the experimental results over a wide rangeof conditions (Strednak et al., 2021).
Franceschini et al. (2014) suggested that the transitionin Sθ and η’’ is controlled by a critical effective volume
fraction (Φc) of the suspension. The effective volume
fraction of a fiber suspension is the ratio of the volume
swept out by all fibers during a cycle to the total volume ofthe suspension, and is therefore proportional to the strain
amplitude γ0. The critical effective volume fraction, Φcdefines the combination of volume fraction ϕ and strain
displacement γ0 at which the particles are forced to contact.
For oscillatory shear below Φc, Franceschini et al. (2014)
speculated that η’’ disappears as the suspension rearranges
to avoid contact, though simulations indicate that at least
some contacts persist (Snook et al., 2012; Strednak et al.,2021). Above Φc, contacts between particles must occur
during the course of every oscillation and η’’ remains finite.
As seen in Fig. 9a for the case of A = 11 and ϕ = 0.20, thetransition in η’’ occurs between γ0 = 2.0 and 2.6. Consequently, Franceschini et al. (2014) defined Φc = γ0ϕ ≈ 0.4.
This corresponds to the value of γ0ϕ at which Sθ is maximized for the same conditions of A = 11 and ϕ = 0.20 (bluecircles in Fig. 9b).
Strednak et al. (2021) found that the maximum value ofSθ declined when the gap spacing H was increased while92

holding the fiber length L constant, both in experiments andsimulations. This indicates that the vorticity alignment of
the fibers is promoted by the bounding walls, as was speculated by Snook et al. (2012). This change in orientation distribution with H/L likely impacts the complex viscosity ina qualitative fashion as well. However, rheological data for
oscillatory flow currently is lacking for large values of H/L.

4. Normal stresses
Suspensions can exhibit finite normal stress differences
during shear. This non-Newtonian property of suspensions
holds true even if the suspending fluid exhibits no normal
stresses (i.e., the suspending fluid is Newtonian). Hencethe normal stress differences originate with the particles,
which must be present at a sufficiently high concentration
for the normal stresses to be measurable. Non-zero normal
stress differences can cause a number of effects, including
shear-induced migration of particles within non-linear
flows (Nott and Brady, 1994; Nott et al., 2011; Snook et al.,2016; Strednak et al., 2018).

4.1 Measuring normal stresses
Measuring normal stresses for suspensions of rigid fibers
requires addressing at least two problems. As with otherrheological characterizations, confinement of the particles
at high concentrations creates difficulties when using
standard shear cells. Additionally, the normal stresses are
small and scale linearly with the rate of shear rather thanquadratically, as with polymer solutions. As a result, normal stress differences cannot be measured at low rates ofshear and concentration using most rotational rheometers,
and inertial effects can alter the measurements if the shear
rate is increased too much in an attempt to generate a larger
force that can be resolved by the transducers.

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Fig. 11 Free surface flows used to evaluate normal stresses. (a) The interfacial deformation of a suspension flowing due to gravity through an open
channel flow can be used to determine the second normal stress difference. (b) The value of α2 + α1/2 can be determined from the deformation of theinterface in the Weissenberg geometry. In both cases, the deformation can be measured by imaging, from above, the intersection of the surface and alaser sheet projected at a low angle.

Fig. 12 a) The coefficient α2 for the second normal stress difference as determined from the tilted trough experiments. b) The coefficient α1 ascalculated from combining the experimental results from the tilted trough and rotating rod geometries. The experimental results (filled symbols) arecompared to simulation results (open symbols) for similar values of the fiber aspect ratios A. All results taken from Snook et al. (2014).

Two approaches for overcoming the challenges ofexperimentally measuring the normal stresses have been
employed. The first makes use of the fact that normal stressdifferences deform the interface during slow free-surface
flows as illustrated in Fig. 11. Because the geometries arelarge, confinement does not influence the measurement.
Analysis and experimental approaches using free surface
flows originally were developed for viscoelastic fluids(Beavers and Joseph, 1975; Wineman and Pipkin, 1966;
Tanner, 1970). Also, the rotating rod geometry (Zarraga etal., 2000; Boyer et al., 2011b) and tilted trough (Couturier
et al., 2011; Dai et al., 2013) previously were used to quantify normal stresses in suspensions of spheres. Whether
or not the particles are spherical or rod-like, the analysis
relating the interface deformations and normal stresses issimilar, though also simpler than the analysis for elastic
fluids. Each normal stress component is assumed to be
proportional to the magnitude of the shear stress, |τ|, andthe results are reported as coefficients of the normal stressdifferences,
α1 

N1
N
and α2  2
τ
τ

(14)

where N1 and N2 are the first and second normal stressdifference. Using either a domain perturbation method ora “cut-away” analysis, while accounting for the tendencyof surface tension to flatten the surface, small interface
deformation due to normal stress differences can be predicted accurately. The deformation of interface in the tilted
trough is related to α2, while analysis of the interface inthe rotating rod geometry yields α2 + α1/2. Comparing thepredicted deformations to those measured in experiments(see Fig. 11) enables determination of both coefficients.
The values of α2 as determined from the tilted troughare shown in Fig. 12a (Snook et al., 2014). The values arestrongly negative for small aspect ratios and high concentrations. In the case of the rotating rod geometry, Snook etal. (2014) reported that no deformation of the surface wasobserved across all tested conditions. Using the fact that
α2 + α1/2 ≈ 0 together with the results for α2 gives α1 > 0
for small aspect ratios and high concentrations, as shown in
Fig. 12b. The result contrasts with suspensions of spheres,
where the interface dips near the rotating rod (Zarraga etal., 2000) and α1 is zero or weakly negative.
The second approach for measuring the bulk normal
stresses of rigid fibers used a custom-built torsional flow
cell (Bounoua et al., 2016a). As originally described by
Dbouk et al. (2013), the device uses an unusually large sep-

(13)
93

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Fig. 13 The normal stress coefficients as a function of confinement, H/L, for (a) α2, the second normal stress difference relative to the shear stress, and(b) α1, the first normal stress difference coefficient. The results of Bounoua et al. (2016a) are compared to those from the free-surface measurements
Snook et al. (2014) (marked as H/L 1) at similar concentrations of nL2 d ≈ 3.0 and aspect ratios A between 10 and 18.

aration of up to 2.5 mm between the two plates. An arrayof force transducers, flush mounted to the stationary plate,enabled measurement of both normal stress difference
coefficients, α1 and α2 (Bounoua et al., 2016a). This device,
by varying the plate spacing and using fibers with lengthsof less than 0.5 mm, was used to characterize the normal
stresses over a range of confinements from H/L = 2 to 11.
Fig. 13a compares measurements at nL2d ≈ 3.0 of
Bounoua et al. (2016a) as a function of confinement withthose from the free surfaces where H/L was very large. The
results are qualitatively similar, with α2 < 0, α1 > 0, and themagnitude of the coefficients are smaller at higher aspectratios. The results for α1 and α2 at the smaller aspect ratioof A = 10 indicate that the magnitudes decline as the confinement is relaxed, approaching the values attained using
the much larger geometries. For the data with A = 18, thenormal stress coefficients measured with the torsional flow
cell are nearly independent of the confinement. However,
the magnitude of the coefficients as measured at H/L >> 1
are quite different than those for which H/L < 10.

4.2 Origin and effects of normal stresses
Normal stress differences within non-colloidal suspensions can arise from hydrodynamic interactions as well
as from contact stresses. For spheres at concentrations of
ϕ > 0.20, the balance of an implied shear flow, disturbancevelocities created by the presence of the particles, and interparticle forces that maintain hydrodynamic interactions
causes an asymmetry in the relative positions of particles
pairs. This asymmetry generates a hydrodynamic contribution to the normal stress differences, and there are also
contributions from the contact forces. Note that a dilute
suspension of spheres (ϕ < 0.02) has no normal stressdifferences, as the symmetry of the velocity disturbancedoes not allow for it. Unlike spheres, individual fibers ina sheared fluid can induce normal stress differences depending on the instantaneous angle with respect to the flow
direction. However, normal stress differences do not exist

94

in a dilute suspension since the orientation distribution
remains symmetric relative to the flow direction.
Simulations by Snook et al. (2014) demonstrate that evenunder concentrated conditions, symmetry of the orientation
distribution about the direction of flow is not broken. Consequently, the predicted normal stresses shown in Fig. 12
originate solely from contact interactions. The predictedvalues of the normal stress coefficients correspond closely
to the measured values. At fixed aspect ratio, the magnitudes of α1 and α2 are lower for low number densities since
there are many fewer contacts. Likewise, fewer contacts
occur at higher aspect ratios and fixed concentration, hence
the normal stress coefficients (magnitudes) are lower. The
relative signs of the coefficients can also be discerned fromthe simulations, which indicate the fibers align strongly
with the direction of flow. As a result, the contact interactions, which are purely repulsive, are strongest in thegradient direction and weakest in the flow direction. This
creates the positive values for α1 and negative values for α2.
Fig. 12 shows predictions from simulations with periodic boundaries rather than with solid bounding planes
separated by a distance H in the gradient direction. However, Snook et al. (2014) also incorporated boundaries into
the simulations and verified that the simulations predictthat normal stress coefficients depend on confinement.
This occurs because the bounding walls of the shearing
geometry alter the orientation distribution, and hence thecontact interactions between particles which control thenormal stresses.
The existence of non-zero normal stresses in a shearedsuspension of fibers implies that particles will migrate
in inhomogeneous shearing flows according to theories
for spherical particles (Nott and Brady, 1994; Nott et al.,2011). This migration creates a non-uniform concentrationthat further complicates predictions and rheological analysis of the flowing suspensions. The net migration of spheresfrom regions of high to low shear rates has been reported
in multiple publications (Leighton and Acrivos, 1987;
Altobelli et al., 1991; Hampton et al., 1997; Snook et al.,

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Fig. 14 Experimental data characterizing migration of fibers in tube flow with L/R ≈ 3 (Strednak et al., 2018). (a) Concentration, n(r/R)L2 d, as afunction of position r within a circular tube of radius R at the same volume fraction of ϕ = 0.03 for two different aspect ratios of A = 11 and 23. In bothcases, the ratio of R/L was identical. (b) Example image from experiments showing fibers (A = 11, nL2 d = 0.42) concentrated near the center of the tube.

2016). Currently, there are few studies of the shear-induced
migration of rigid fibers, though these studies qualitatively
agree with suspensions of spheres. For example, Mondy etal. (1994) measured the spatial distribution of ellipsoids ofaspect ratios A = 2 to 18.4 within a wide-gap Couette flow
and found results similar to that for spheres. More recent
measurements (Strednak et al., 2018) indicate that fibers
migrate within tube flow, away from the walls and toward
the center as expected from observations of spheres. However, significant migration occurs at much smaller volume
fractions in suspensions of fibers as compared to spheres.
Fig. 14 shows the position dependent concentration atsteady-state for two different aspect ratios for suspensions
at ϕ = 0.03, whereas Snook et al. (2016) observed no
particle migration for suspensions of spheres at ϕ < 0.1.
Generally, Strednak et al. (2018) found that the extent of
migration for the rigid fibers was similar at the same valueof nL2d = 4Aϕ/π, regardless of the aspect ratio.

5. Conclusions
Various studies related to the experimental and numerical determination of the rheology have been outlined in thisreview. However, the reviewed studies have been limited
to relatively rigid fibers of uniform size suspended under
neutrally buoyant conditions in a viscous fluid. Moving
away from this limited set of conditions introduces a number of possible complexities, such as Brownian motion andviscoelasticity, to the fluid mechanics and rheology of thesuspension system.
Even for the relatively large size of fiber suspensions described in this review, weak and attractive colloidal forceswere discussed as a possible cause of shear-thinning. For
strongly colloidal suspensions, the rheology can be more
complex (Mewis and Wagner, 2011). Notably for somecolloidal suspensions of fibers, shear thickening rheology
is observed, wherein the viscosity of the suspension increases with an increase in shear rate. Reviews by Barnes(1989) and Brown and Jaeger (2014) provide an in-depth
look at the shear thickening of colloidal suspensions ofboth spherical and elongated particles. At this length scale,various mechanisms are claimed to cause non-Newtonian
rheological behavior; more recently, fiber orientation was
also attributed to causing shear-thickening (Rathee et al.,2020). Furthermore, shear thickening in colloidal suspensions of elongated particles is often related to the jamming
transition (Cates et al., 1998; Liu and Nagel, 1998). However, shear thickening for colloidal suspensions should not
be confused with the jamming transition for non-colloidal
slurries (i.e., divergence of viscosity with increased concentration), as discussed in Section 3.2.
The stipulated condition of monodispersity of particle
size in the experimental and numerical studies describedin this review is far removed from real-world applications.
For colloidal suspensions near the jamming transition, it
is observed that at the same volume fraction, the viscosity and normal stresses measured are lower than that ofmonodisperse suspensions (Pednekar et al., 2018). Martiet al. (2005) performed rheological measurements for concentrated non-colloidal suspensions, with polydispersity inboth shape (mixture of spheres and fibers) and particle size.
Accurate and rigorous experimental measurements of therheology in polydisperse systems continues to be lacking,with particularly few results for suspensions of fibers.
Moving past neutrally buoyant, rigid elongated particles, flexibility adds additional restorative forces to thehydrodynamics and particle-particle interactions, leading
to complex non-linear, and irreversible dynamics affecting
bulk rheological measurements (du Roure et al., 2019).
For non-neutrally buoyant particles in shearing flows,
sedimentation (or creaming) is countered only partially by95

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

resuspension of spherical particles (Acrivos et al., 1993);
the resulting inhomogeneity in the spatial distribution ofparticles will affect the bulk measurements of rheology. For
further reading, Shaqfeh (2019) collates several studies ofsuspensions of various non-colloidal particles in viscoelastic fluids, including rigid fibers.
Finally, there is a lack of detailed numerical and experimental work describing the microstructure at concentrations
beyond the dilute limit and up to the jamming transition.
The dependence of bulk rheological measurements on
the changes in the microstructure of slurries of elongatedparticles in flow have been discussed (Franceschini et al.,2011; Snook et al., 2012; Tapia et al., 2017; Strednak et al.,2018). The changes in the microstructure are irreversible inconcentrated suspensions which contradict the reversible
nature of the Stokes equations, which govern their hydrodynamics. As an illustrative example to motivate moredetailed measurements, results obtained from experiments
performed by Tapia et al. (2017) show that for higher
particle aspect ratio, volume fractions measured exceeded
the limit described by numerical simulations performed byWilliams and Philipse (2003), who prescribed the maximum isotropic packing fraction of spherocylinders, suggesting local or bulk ordering of the particles. Additionally,
the appearance of yield stresses, a phenomenon generally
associated with fiber flexibility and studied extensively inthe pulp industry, was observed in slurries of rigid particles
near the jamming limit, warranting deeper examination.
Even within the limits placed upon the suspension
properties, the studies discussed in this review demonstratethat the rheology of slurries of rigid elongated particles iscomplex and frequently non-intuitive. Recent publications
make it clear that care must be taken in interpreting rheological quantities for rigid fibers, especially when measured
using confined geometries at large concentration. Failure toconsider this latter aspect on the measurements can resultin inaccurate assessments of the bulk viscosity, normal
stress differences, and oscillatory rheology and dynamics.
The enhancements in the measurement and modeling forthese systems have been aided significantly by numericalsimulations that have been validated against experiments.
Continuing advances likely will rely on simulations thatincorporate the additional physical mechanisms describedin the previous paragraphs.

Acknowledgements
This work was supported by the National Science
Foundation (NSF Award No. 1511787 and 1602032) andthe CPaSS industrial partners. Any opinions, findings, andconclusions or recommendations expressed in this material
are those of the author(s) and do not necessarily reflect theviews of the NSF or the CPaSS industry members.

96

References
Acrivos A., Bingham Award Lecture–1994 Shear-induced
particle diffusion in concentrated suspensions of noncolloidal particles, Journal of Rheology, 39 (1995) 813–826.
DOI:10.1122/1.550619
Acrivos A., Mauri R., Fan X., Shear-induced resuspension in a
Couette device, International Journal of Multiphase Flow, 19(1993) 797–802. DOI:10.1016/0301-9322(93)90043-T
Altobelli S., Givler R., Fukushima E., Velocity and concentration
measurements of suspensions by nuclear magnetic resonance imaging, Journal of Rheology, 35 (1991) 721–734.
DOI:10.1122/1.550156
Barnes H.A., Shear-thickening (dilatancy) in suspensionsof nonaggregating solid particles dispersed in Newtonian liquids, Journal of Rheology, 33 (1989) 329–366.
DOI:10.1122/1.550017
Batchelor G.K., Slender-body theory for particles of arbitrary
cross-section in Stokes flow, Journal of Fluid Mechanics, 44(1970) 419–440. DOI:10.1017/S002211207000191X
Batchelor G.K., Green J.T., The determination of the bulk stressin a suspension of spherical particles to order c2, Journalof Fluid Mechanics, 56 (1972) 401–427. DOI:10.1017/
S0022112072002435
Beavers G., Joseph D., The rotating rod viscometer, Journalof Fluid Mechanics, 69 (1975) 475–511. DOI:10.1017/
S002211207500153X
Bennington C.P.J., Kerekes R.J., Grace J.R., The yield stress offibre suspensions, The Canadian Journal of Chemical Engineering, 68 (1990) 748–757. DOI:10.1002/cjce.5450680503
Bibbó M.A., Rheology of semiconcentrated fiber suspensions,Ph.D. thesis, Massachusetts Institute of Technology (1987).
http://hdl.handle.net/1721.1/14875

Bibbó M.A., Dinh S.M., Armstrong R.C., Shear flow properties ofsemiconcentrated fiber suspensions, Journal of Rheology, 29(1985) 905–929. DOI:10.1122/1.549836
Bivens C.H., Boney C., Fredd C., Lassek J., Sullivan P., Engels
J., Fielder E., Gorham T., Judd T., Mogollon A.E.S., Tabor
L., Munoz A.V., Willberg D., New fibers for hydraulic fracturing, Oilfield Review (published by Schlumberger Ltd.),
Summer Issue (2005) 34–43.
Blanc F., Peters F., Lemaire É., Local transient rheologicalbehavior of concentrated suspensions, Journal of Rheology,
55 (2011) 835–854. DOI:10.1122/1.3582848
Bounoua S., Kuzhir P., Lemaire É., Normal stress differences in
non-Brownian fiber suspensions, Journal of Rheology, 60(2016a) 661–671.
Bounoua S., Lemaire É., Férec J., Ausias G., Kuzhir P.,
Shear-thinning in concentrated rigid fiber suspensions:aggregation induced by adhesive interactions, Journal of
Rheology, 60 (2016b) 1279–1300. DOI:10.1122/1.4965431
Bounoua S.N., Kuzhir P., Lemaire E., Shear reversal experimentson concentrated rigid fiber suspensions, Journal of Rheology,
63 (2019) 785–798. DOI:10.1122/1.5097658
Boyer F., Guazzelli É., Pouliquen O., Unifying suspension andgranular rheology, Physical Review Letters, 107 (2011a)
188301. DOI:10.1103/PhysRevLett.107.188301
Boyer F., Pouliquen O., Guazzelli É., Dense suspensions inrotating-rod flows: normal stresses and particle migration,
Journal of Fluid Mechanics, 686 (2011b) 5. DOI:10.1017/
jfm.2011.272
Brady J.F., Bossis G., Stokesian dynamics, Annual Review of
Fluid Mechanics, 20 (1988) 111–157. DOI:10.1146/annurev.
fl.20.010188.000551

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Bricker J.M., Park H., Butler J.E., Rheology of semidilute
suspensions of rigid polystyrene ellipsoids at high Peclet
numbers, Journal of Rheology, 52 (2008) 941–955.
DOI:10.1122/1.2930670
Brown E., Jaeger H.M., Shear thickening in concentrated
suspensions: phenomenology, mechanisms and relations tojamming, Reports on Progress in Physics, 77 (2014) 046602.
DOI:10.1088/0034-4885/77/4/046602
Butler J.E., Snook B., Microstructural dynamics and rheologyof suspensions of rigid fibers, Annual Review of Fluid
Mechanics, 50 (2018) 299–318. DOI:10.1146/annurev-fluid122316-045144
Cates M.E., Wittmer J.P., Bouchaud J.P., Claudin P., Jamming,
force chains, and fragile matter, Physical Review Letters, 81(1998) 1841–1844. DOI:10.1103/PhysRevLett.81.1841
Chaouche M., Koch D.L., Rheology of non-Brownian rigid fiber
suspensions with adhesive contacts, Journal of Rheology, 45(2001) 369–382. DOI:10.1122/1.1343876
Cieslinski M.J., Baird D.G., Wapperom P., Obtaining repeatable
initial fiber orientation for the transient rheology of fiber
suspensions in simple shear flow, Journal of Rheology, 60(2016) 161–174. DOI:10.1122/1.4938229
Claeys I.L., Brady J.F., Suspensions of prolate spheroids in Stokes
flow. Part 2. Statistically homogeneous dispersions, Journalof Fluid Mechanics, 251 (1993) 443–477. DOI:10.1017/
S0022112093003477
Couturier É., Boyer F., Pouliquen O., Guazzelli É., Suspensions
in a tilted trough: second normal stress difference, Journal of
Fluid Mechanics, 686 (2011) 26. DOI:10.1017/jfm.2011.315
Dagois-Bohy S., Hormozi S., Guazzelli É., Pouliquen O.,
Rheology of dense suspensions of non-colloidal spheres inyield-stress fluids, Journal of Fluid Mechanics, 776 (2015)
R2. DOI:10.1017/jfm.2015.329
Dai S.C., Bertevas E., Qi F., Tanner R.I., Viscometric functions
for noncolloidal sphere suspensions with Newtonian
matrices, Journal of Rheology, 57 (2013) 493–510.
DOI:10.1122/1.4774325
Dbouk T., Lobry L., Lemaire E., Normal stresses in concentrated
non-Brownian suspensions, Journal of Fluid Mechanics, 715(2013) 239. DOI:10.1017/jfm.2012.516
Dinh S.M., Armstrong R.C., A rheological equation of state forsemiconcentrated fiber suspensions, Journal of Rheology, 28(1984) 207–227. DOI:10.1122/1.549748
Djalili-Moghaddam M., Toll S., Fibre suspension rheology: effectof concentration, aspect ratio and fibre size, Rheologica Acta,
45 (2006) 315–320. DOI:10.1007/s00397-005-0021-y
Doi M., Edwards S.F., Dynamics of rod-like macromolecules
in concentrated solution. Part 1, Journal Chemical Society,
Faraday Transactions 2, 74 (1978) 560–570. DOI:10.1039/
F29787400560
du Roure O., Lindner A., Nazockdast E.N., Shelley M.J.,
Dynamics of flexible fibers in viscous flows and fluids,
Annual Review of Fluid Mechanics, 51 (2019) 539–572.
DOI:10.1146/annurev-fluid-122316-045153
Einarsson J., Candelier F., Lundell F., Angilella J.R., Mehlig
B., Effect of weak fluid inertia upon Jeffery orbits, PhysicalReview E, 91 (2015) 041002. DOI:10.1103/PhysRevE.
91.041002.
Einstein A., A new determination of the molecular dimensions,Annalen der Physik, 19 (1906) 289–306.
Elgaddafi R., Ahmed R., George M., Growcock F., Settling
behavior of spherical particles in fiber-containing drilling
fluids, Journal of Petroleum Science Engineering, 84 (2012)
20–28. DOI:10.1016/j.petrol.2012.01.020
Forgacs O.L., Mason S.G., Particle motions in sheared sus-

pensions: IX. Spin and deformation of threadlike particles,
Journal of Colloid and Interface Science, 14 (1959) 457–472.
DOI:10.1016/0095-8522(59)90012-1
Franceschini A., Filippidi E., Guazzelli É., Pine D.J., Transversealignment of fibers in a periodically sheared suspension: anabsorbing phase transition with a slowly varying control
parameter, Physical Review Letters, 107 (2011) 250603.
DOI:10.1103/PhysRevLett.107.250603
Franceschini A., Filippidi E., Guazzelli É., Pine D.J., Dynamics
of non-Brownian fiber suspensions under periodic shear, Soft
Matter, 10 (2014) 6722–6731. DOI:10.1039/C4SM00555D
Gadala-Maria F., Acrivos A., Shear-induced structure in a concentrated suspension of solid spheres, Journal of Rheology, 24(1980) 799–814. DOI:10.1122/1.549584
Ganani E., Powell R.L., Suspensions of rodlike particles: literature review and data correlations, Journal of Composite Matter, 19 (1985) 194–215. DOI:10.1177/002199838501900301
Guazzelli É., Pouliquen O., Rheology of dense granular suspensions, Journal of Fluid Mechanics, 852 (2018). DOI:10.1017/
jfm.2018.548
Hammond P., Settling and slumping in a Newtonian slurry,
and implications for proppant placement during hydraulicfracturing of gas wells, Chemical Engineering Sciences, 50(1995) 3247–3260. DOI:10.1016/0009-2509(95)00152-U
Hampton R.E, Mammoli A.A., Graham A.L., Tetlow N., Altobelli
S.A., Migration of particles undergoing pressure-driven
flow in a circular conduit, Journal of Rheology, 41 (1997)
621–640. DOI:10.1122/1.550863
Hassanpoura M., Shafighb P., Mahmudb H.B., Lightweightaggregate concrete fiber reinforcement – A review,Construction and Building Materials, 37 (2012) 452–461.
DOI:10.1016/j.conbuildmat.2012.07.071
Hinch E.J., Leal L.G., The effect of Brownian motion on therheological properties of a suspension of non-sphericalparticles, Journal of Fluid Mechanics, 52 (1972) 683–712.
DOI:10.1017/S002211207200271X
Ingber M.S., Mammoli A.A., Vorobieff P., McCollam T., Graham
A.L., Experimental and numerical analysis of irreversibilities
among particles suspended in a Couette device, Journal of
Rheology, 50 (2006) 99–114. DOI:10.1122/1.2169806
Ivanov Y., Van de Ven T.G.M., Mason S.G., Damped oscillationsin the viscosity of suspensions of rigid rods. I. Monomodal
suspensions, Journal of Rheology, 26 (1982) 213–230.
DOI:10.1122/1.549664
Jeffery G.B., The motion of ellipsoidal particles immersed in a
viscous fluid, Proceedings of the Royal Society London A,
102 (1922) 161–179. DOI:10.1098/rspa.1922.0078
Krieger I.M., Dougherty T.J., A mechanism for non-Newtonian
flow in suspensions of rigid spheres, Transactions of the Society of Rheology, 3 (1959) 137–152. DOI:10.1122/1.548848
Larson R.G., The Structure and Rheology of Complex Fluids, Oxford university press, New York (1999), ISBN:
9780195121971.
Lauga E., Floppy swimming: viscous locomotion of actuatedelastica, Physical Review E, 75 (2007) 041916. DOI:10.1103/
PhysRevE.75.041916
Leighton D., Acrivos A., The shear-induced migration of particles
in concentrated suspensions, Journal of Fluid Mechanics, 181(1987) 415–439. DOI:10.1017/S0022112087002155
Liu A.J., Nagel S.R., Jamming is not just cool any more, Nature,
396 (1998) 21–22. DOI:10.1038/23819
Liu W., Moran C.J., Vink S., Quantitative risk-based approach
for improving water quality management in mining, Environmental Science and Technology, 45 (2011) 7459–7464.
DOI:10.1021/es201876c

97

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Lundell F., Söderberg L.D., Alfredsson P.H., Fluid mechanics ofpapermaking, Annual Review of Fluid Mechanics, 43 (2011)
195–217. DOI:10.1146/annurev-fluid-122109-160700
Mackaplow M.B., Shaqfeh E.S.G., A numerical study of therheological properties of suspensions of rigid, non-Brownian
fibres, Journal of Fluid Mechanics, 329 (1996) 155–186.
DOI:10.1017/S0022112096008889
Marti I., Höfler O., Fischer P., Windhab E.J., Rheology of concentrated suspensions containing mixtures of spheres andfibres, Rheologica Acta, 44 (2005) 502–512. DOI:10.1007/
s00397-005-0432-9
Maschmeyer R.O., Hill C.T., Rheology of concentrated suspensions of fibers in tube flow. II. An exploratory study,
Transactions of the Society of Rheology, 21 (1977) 183–195.
DOI:10.1122/1.549453
Mewis J., Wagner N.J., Colloidal Suspension Rheology,
Cambridge Series in Chemical Engineering, Cambridge
University Press (2011). DOI:10.1017/CBO9780511977978
Mondy L.A., Brenner H., Altobelli S.A., Abbott J.R., Graham
A.L., Shear-induced particle migration in suspensionsof rods, Journal of Rheology, 38 (1994) 444–452.
DOI:10.1122/1.550522.
Mongruel A., Cloitre M., Shear viscosity of suspensions ofaligned non-Brownian fibres, Rheologica Acta, 38 (1999)
451–457. DOI:10.1007/s003970050196.
Morris J.F., Boulay F., Curvilinear flows of noncolloidal suspensions: the role of normal stresses, Journal of Rheology, 43(1999) 1213–1237. DOI:10.1122/1.551021
Narumi T., See H., Honma Y., Hasegawa T., Takahashi T., PhanThien N., Transient response of concentrated suspensions
after shear reversal, Journal of Rheology, 46 (2002) 295–305.
DOI:10.1122/1.1428321
Nott P.R., Brady J.F., Pressure-driven flow of suspensions: simulation and theory, Journal of Fluid Mechanics, 275 (1994)
157–199. DOI:10.1017/S0022112094002326
Nott P.R., Guazzelli É., Pouliquen O., The suspension balance
model revisited, Physics of Fluids, 23 (2011) 043304.
DOI:10.1063/1.3570921
Osiptsov A.A., Fluid mechanics of hydraulic fracturing: a review,
Journal of Petroleum Science and Engineering, 156 (2017)513–535. DOI:10.1016/j.petrol.2017.05.019
Park J., Butler J.E., Inhomogeneous distribution of a rigid fibre
undergoing rectilinear flow between parallel walls at highPeclet numbers, Journal of Fluid Mechanics, 630 (2009)
267–298. DOI:10.1017/S0022112009006545
Patra P., Bhambhani T., Vasudevan M., Nagaraj D., SomasundaranP., Transport of fibrous gangue mineral networks to froth bybubbles in flotation separation, International Journal of
Mineral Processing, 104 (2012) 45–48. DOI:10.1016/j.
minpro.2011.11.007
Pednekar S., Chun J., Morris J.F., Bidisperse and polydisperse
suspension rheology at large solid fraction, Journal of Rheology, 62 (2018) 513–526. DOI:10.1122/1.5011353
Peters F., Ghigliotti G., Gallier S., Blanc F., Lemaire E., Lobry L.,
Rheology of non-Brownian suspensions of rough frictional
particles under shear reversal: a numerical study, Journal of
Rheology, 60 (2016) 715–732. DOI:10.1122/1.4954250
Petrie C.J.S., The rheology of fibre suspensions, Journal of
Non-Newtonian Fluid Mechanics, 87 (1999) 369–402.
DOI:10.1016/S0377-0257(99)00069-5
Pham P., Metzger B., Butler J.E., Particle dispersion in shearedsuspensions: crucial role of solid-solid contacts, Physics of
Fluids, 27 (2015) 051701. DOI:10.1063/1.4919728
Powell R.L., Rheology of suspensions of rodlike particles, Journalof Statistical Physics, 62 (1991). DOI:10.1007/BF01128178

98

Rampall I., Smart J.R., Leighton D.T., The influence of surface
roughness on the particle-pair distribution function of dilute
suspensions of non-colloidal spheres in simple shear flow,
Journal of Fluid Mechanics, 339 (1997) 1–24. DOI:10.1017/
S002211209600479X
Rao S.R., Finch J.A., A review of water re-use in flotation,
Mineral Engineering, 2 (1989) 65–85. DOI:10.1016/08926875(89)90066-6
Rathee V., Arora S., Blair D.L., Urbach J.S., Sood A.K., Ganapathy
R., Role of particle orientational order during shear thickening in suspensions of colloidal rods, Physical Review E, 101(2020) 040601. DOI:10.1103/PhysRevE.101.040601
Schiek R.L., Shaqfeh E.S.G., A nonlocal theory for stress inbound, Brownian suspensions of slender, rigid fibers, Journalof Fluid Mechanics, 296 (1995) 271–324. DOI:10.1017/
S0022112095002138
Sepehr M., Carreau P.J., Moan M., Ausias G., Rheological properties of short fiber model suspensions, Journal of Rheology,
48 (2004) 1023–1048. DOI:10.1122/1.1773783
Shaqfeh E.S.G., Fredrickson G.H., The hydrodynamic stress in asuspension of rods, Physics of Fluids A: Fluid Dynamics, 2(1990) 7–24. DOI:10.1063/1.857683
Shaqfeh E.S.G., On the rheology of particle suspensions inviscoelastic fluids, AIChE Journal, 65 (2019) e16575.
DOI:10.1002/aic.16575
Snook B., Butler J.E., Guazzelli É., Dynamics of shear-induced
migration of spherical particles in oscillatory pipe flow, Journal of Fluid Mechanics, 786 (2016) 128–153. DOI:10.1017/
jfm.2015.645
Snook B., Davidson L.M., Butler J.E., Pouliquen O., Guazzelli É.,
Normal stress differences in suspensions of rigid fibres, Journal of Fluid Mechanics, 758 (2014) 486–507. DOI:10.1017/
jfm.2014.541
Snook B., Guazzelli É., Butler J.E., Vorticity alignment of rigid
fibers in an oscillatory shear flow: Role of confinement, Physics of Fluids, 24 (2012) 121702. DOI:10.1063/1.4770141
Somasundaran P., Patra P., Bhambani T., Nagaraj D.R., Rheology
of ore suspensions with fibrous minerals and its impact on
flotation performance, Mining, Metallurgy & Exploration, 36(2019) 111–116. DOI:10.1007/s42461-018-0040-8
Strednak S., Butler J.E., Bergougnoux L., Guazzelli É.,
Fiber alignment in oscillating confined shearing flows,
Physical Review Fluids, 6 (2021) 014302. DOI:10.1103/
PhysRevFluids.6.014302
Strednak S., Shaikh S., Butler J.E., Guazzelli É., Shear-induced
migration and orientation of rigid fibers in an oscillatory
pipe flow, Physical Review Fluids, 3 (2018) 091301.
DOI:10.1103/PhysRevFluids.3.091301
Switzer L.H., Klingenberg D.J., Rheology of sheared flexible
fiber suspensions via fiber-level simulations, Journal of Rheology, 47 (2003) 759–778. DOI:10.1122/1.1566034
Tanner R., Some methods for estimating the normal stressfunctions in viscometric flows, Transactions of the Society ofRheology, 14 (1970) 483–507. DOI:10.1122/1.549175
Tapia F., Shaikh S., Butler J.E., Pouliquen O., Guazzelli E.,
Rheology of concentrated suspensions of non-colloidal
rigid fibres, Journal of Fluid Mechanics, 827 (2017) R5.
DOI:10.1017/jfm.2017.552
Wandersman E., Quennouz N., Fermigier M., Lindner A., Du
Roure O., Buckled in translation, Soft Matter, 6 (2010)
5715–5719. DOI:10.1039/C0SM00132E
Williams S.R., Philipse A.P., Random packings of spheres andspherocylinders simulated by mechanical contraction,
Physical Review E, 67 (2003) 051301. DOI:10.1103/PhysRevE.67.051301

Saif Shaikh et al. / KONA Powder and Particle Journal No. 39 (2022) 84–99

Wineman A.S., Pipkin A., Slow viscoelastic flow in tilted
troughs, Acta Mechanica, 2 (1966) 104–115. DOI:10.1007/
BF01176732
Young Y.N., Shelley M.J., Stretch-coil transition and transport offibers in cellular flows, Physical Review Letters, 99 (2007)058303. DOI:10.1103/PhysRevLett.99.058303
Zarraga I.E., Hill D.A., Leighton Jr D.T., The characterization of

the total stress of concentrated suspensions of noncolloidal
spheres in Newtonian fluids, Journal of Rheology, 44 (2000)
185–220. DOI:10.1122/1.551083
Zurita-Gotor M., Bławzdziewicz J., Wajnryb E., Motion of arod-like particle between parallel walls with application tosuspension rheology, Journal of Rheology, 51 (2007) 71–97.
DOI:10.1122/1.2399084

Authors’ Short Biographies
Saif Shaikh
Saif Shaikh earned a Ph.D. in chemical engineering from the University of Florida, USA under
the guidance of Dr. Jason E. Butler, as well as a Ph.D. in physics and mechanics of fluids from the
University of Aix-Marseille, France. His doctoral work focused on characterizing the rheologicalbehavior of concentrated suspensions of rigid, non-colloidal fibers. His contributions further extended the understanding of complex fluid dynamics near the fluid-solid transition, which remains
largely unexplored. Saif is interested in applying his experimental skills and knowledge-base to help
develop, optimize, and market products and technology to the scientific and industrial community.

Scott Strednak
Scott Strednak received B.S. degrees in Paper Science and Engineering and Chemical Engineeringfrom North Carolina State University in 2014. He also received his Ph.D. in Chemical Engineeringfrom the University of Florida in 2020, where he performed experimental and numerical work on
spatial and orientation distributions of concentrated suspensions of rigid fibers in oscillatory flows.

Jason E. Butler
Jason E. Butler is a Professor of Chemical Engineering at the University of Florida (Gainesville,
Florida). His educational and research expertise is the dynamics of complex fluids, and his workspans theoretical, computational, and experimental approaches to resolving questions that impact
a wide range of applications. Among other achievements, Jason has contributed to the theory andmodeling of sedimentation and rheology of non-spherical particles, the Brownian dynamics of rigid
polymers and colloidal fibers, and the electrokinetics of polyelectrolytes.

99

KONA Powder and Particle Journal No. 39 (2022) 100–109/https://doi.org/10.14356/kona.2022014

Review Paper

A Review of Distribution and Segregation Mechanisms ofDockage and Foreign Materials in On-Farm Grain Silos forCentral Spout Loading †Fuji Jian
Department of Biosystems Engineering, University of Manitoba, Canada

Abstract
Dockage and foreign material (DFM) distribution in grain silos is an important factor in managing stored grain.
The DFM distribution in grain silos is dictated by the segregation mechanisms of DFM during grain loading.
Loading grain into silos from a central spout is a special case of heap flows of granular materials. However,
our understanding of heap flows is still evolving, and no models are currently available to predict the dockage
and foreign material distribution in grain silos. Based on an extensive literature review, this paper identified thedominant mechanisms of DFM segregations during central spout filling in grain silos and main factors influencing
DFM distribution. The DFM distribution patterns were characterized. The experimental methods for analyzing
DFM segregations and distribution were also reviewed. The gaps of our knowledge on segregation mechanisms andfactors influencing segregation were summarized and future research directions and challenges were discussed.
Keywords: dockage and fine material distribution, segregation mechanism, farm silo, stored grain

1. Introduction
Flat and hopper bottom cylindrical silos (bins) are commonly used in North America for on-farm storage of crop
grains (cereal grains, oil seeds, and pulses). In Canada andUSA, almost all of the harvested crop grains are stored inthis type of silos. Typically, grain is lifted to the roof heightof silo with a grain auger (or a bucket elevator) and discharged into the silo through a central spout. Grain contains
dockage and foreign materials (DFM), which are different
from grain kernels in terms of physical properties, suchas density, size, and shape. The differences between grainkennels and DFM result in segregation during silo loading,causing ununiform distribution of DFM in the grain bulk.
Ununiform distribution of DFM leads to uneven airflow
through the grain bulk, which adversely affects grain storage management operations, such as aeration, drying, andfumigation for insect control. For example, if airflow is uneven, grain at the low airflow locations might not be cooled
or dried, which may lead to grain spoilage during storage.
There are very limited studies on the DFM distribution in
on-farm grain silos, although segregation in granular materials during handling has been extensively studied (Fan†

Received 21 June 2021; Accepted 2 August 2021
J-STAGE Advance published online 11 September 2021
Add: Winnipeg, MB R3T 5V6, Canada
E-mail: Fuji.jian@umanitoba.ca
TEL: +1-204-474-7965

100

et al., 2017; Gray, 2018; Mosby et al., 1996). Applying theknowledge of particle segregation to analyzing the DFM
distribution may help to better understand the distributionof DFM in grain silos, thus improving management of
stored grain to reduce grain spoilage.
Loading grain into silos through a central spout from theroof top is a special case of surface flows of granular materials, that is, a thin layer of grain continuously flows on the
top of a nearly quiescent granular bed. Even though granular surface flows are important in many industrial practices
and natural systems, and have been extensively studied,our understanding of surface flows is still incomplete atpresent, and in particular no constitutive laws are currently
able to predict and explain all the range of segregation
behaviors of DFM in grain silos. The relevant segregation
mechanisms involved in DFM distribution have yet to be
identified, although there were several studies on DFM
distribution inside grain silos (Bartosik and Maier, 2006;
Chang et al., 1981; 1983; Jayas, 1987; Narendran et al.,2019; Salarikia, et al., 2021).
Fan et al. (2017) extensively reviewed physical mechanisms of heap segregation and developed predictivemodels. Similar reviews were conducted by Gray (2018),
and Mosby et al. (1996). However, these reviews did notprovide any specific information of heap segregation forfarm grain silos filled by a central spout. The review in thisarticle focused exclusively on the segregation of DFM inside on-farm grain silos. The main objectives of this review

Copyright © 2022 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

were to identify the main mechanism(s) of DFM segregation and main factors influencing these mechanisms.
Commonly used experimental methods and mathematicalmodels to analyze segregations and DFM distribution werealso reviewed.

2. Segregation mechanisms in grain silos
filled by central spouting
Researchers have reported different mechanisms of particle segregation, including agglomeration, air current, avalanche, bouncing, displacement, embedding, fluidization,
impact, percolation, push-away, rolling, sifting, sliding,and trajectory (Fan et al., 2017; Jian et al., 2019; Mosby etal., 1996; Tang and Puri, 2004). During grain loading andunloading, more than one of these mechanisms occur simultaneously, and some of these mechanisms overlap witheach other or act as a special case of another mechanism.
Jian et al. (2019) attributed the primary patterns of segregation to four main mechanisms in bulk grain handling:
trajectory, fluidization, sifting, and impact segregation.
Another phenomenon, avalanche, could result in siftingand fluidization segregation and induce variations of DFM
distribution at the silo center and walls.

2.1 Trajectory segregation
When a mixture of particles with different sizes, shapes
and densities leaves a loading equipment, such as a spout,auger, and conveyor, at an initial velocity, dense and larger
particles have higher momentums than light and small
particles. In addition, particle shape and size differences
also result in different air drag forces while the particles are
moving in the air. Due to this combined effect of momentum and drag force small and light particles do not travel as
far as large and dense particles, and thus accumulate under
the spout at the center of silos (Fig. 1). After the particles
have landed on the heap, the momentum in the horizontal
direction causes them to roll or slide along the heaped
surface and small particles percolate through the poresamong larger particles during rolling or sliding, resulting in
sifting segregation. The momentum in the vertical direction

Fig. 1

pushes particles far away from the drop location, resulting
in impact segregation.
If the initial velocity of particles leaving the loading
equipment is zero in the horizontal direction, rolling andsliding occur on the surface of heap due to the difference
in repose angle between different materials, resulting in
sifting segregation.
The consequence of trajectory segregation during central
spout loading is that fines, small stones, other particles
larger and denser than grain kernels, such as internode andwild oat kernels, and other larger grain kernels with similar
density are concentrated at the central of the silo (Fig. 1).
This result was consistent with the observations reported
in the literature. Salarikia et al. (2021) found that broken
and shrunk kernels even distributed from the center to thewalls in a grain silo. This could be explained by their similar shapes and densities as the small grain kernels, whichwere not segregated from the sound grain kernels. Other
particles which are larger and less dense than grain kernels,
such as chaff, straw, knuckle, rachis, and spikelet, could be
more influenced by sifting segregation on the heap surface.

2.2 Impact segregation
When particles hit the heap surface, larger particle canpush small particles further down the heap surface towards
the silo periphery (Fig. 1) due to lower mass of the small
particles (Carson et al., 1986). This impact segregation
may result in a wider distribution of some small particles,
while the larger particles mostly stay at the heap center.
Narendran et al. (2019) found that small canola kernels
were concentrated at the periphery of the bin filled withclean wheat mixed with soybean, red kidney bean, andcanola. The authors suggested the impact segregation
was responsible for the canola distribution, while some of
red kidney bean and soybean kernels were embedded in
the wheat mixture after pushing away the canola kernels.
Furthermore, impact and trajectory segregation also resultin the same distribution for large and heavy particles (likestones). For small particles, even though impact segregation can result in a different segregation pattern from trajectory and sifting segregation, its effect in farm silos might
be minimum because of the low percentage of the large andSchematic of four primary segregation mechanisms in bulk materials.

101

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

heavy particles in grains (Jian et al., 2019). In other words,
impact segregation might not a main mechanism for the
DFM distribution pattern in farm silos.

2.3 Fluidization segregation
Fluidization segregation can occur when a grain bulk
containing light materials such as dusts and small chaff
is loaded into a silo and the drop height is high enough to
induce air currents by the moving streams of grain (Carson
et al., 1986; Mosby et al., 1996). The effect of the air currents increases with the increase of drop height and loadingrate. This type of fluidization segregation results in settlingof dust and chaff on the surface of the grain pile (Fig. 1),
which might not influence the DFM distribution because
dust and chaff on the heap surface would be further segregated on the heap surface due to the surface flows. Fluidization segregation can also occur when the grain mixture
fluidizes on the surface of the heap and pushes lighterand larger particles away from the heap center (Zigan etal., 2008). This type of fluidization segregation might bemore influenced by the avalanche segregation (Fig. 2). The
dust content is usually much lower than other impurities
in stored grain (Jian et al., 2019). Therefore, fluidization
segregation in farm silos might not be a main mechanism
influencing the DFM distribution.

2.4 Sifting (sieving) segregation
Sifting segregation occurs when particles are moving
over each other (Fig. 1), e.g., particles in the grain bulk rollor slide down on the surface of a grain pile when the angleof the heap is larger than the repose angle of the grain bulk.
The heap surface acts like a sieve and smaller particles are
more likely to be embedded in the surface pores and gradually percolate down to the bottom of the moving layer,
while larger particles have a higher probability of sliding
or rolling down further from the top of the heap and stayon the surface (Ketterhagena et al., 2007; NourmohamadiMoghadami et al., 2020; Tang and Puri, 2004). Johanson etal. (2005) identified three requirements for sifting: 1) the
fines must be small enough to fit through the pores in thecoarse matrix; 2) inter-particle motion must exist to allow

Fig. 2102

fine particle to be exposed to multiple voids, and 3) the
fines need to be significantly free flowing to pass throughthe pores and result in percolation. Carson et al. (1986)
concluded that sifting (sieving) was the most importantmechanism in heap segregation when the content of fines
was low because when there were enough large particles toform a moving layer, the fines could pass through this layer
and percolate downwards. The effect of sifting segregationis that small particles end up at the locations close to theheap center, which is similar to the pattern of trajectory
segregation. Grain bulks usually have low concentrationsof fines and the size ratio of grain kernels to the fines isusually larger than 1.5 (Makse et al., 1998), which explains
why stratification rarely occurs and the sifting segregation
for fines in grain silos might be one of the main mechanisms.

2.5 Avalanche segregation
Avalanche segregation on heaped surfaces has been
extensively studied (Dahmen et al., 2011; Fan et al., 2017;
Gray, 2018; Lemieux and Durian, 2000; Pouliquen et al.,
1997; Woodhouse et al., 2012), but not specific to loadingof crop grain into storage silos. Narendran et al. (2019)were the first to report the occurrence of avalanche duringgrain loading. At low loading rates, the particles can build
up at the apex of the pile and the dynamic angle of repose
gradually increases. After the dynamic angle of repose
becomes larger than the static repose angle of the heap, thedynamic angle collapses, which results in an intermittent
and periodical avalanche. Sifting segregation occurs during
avalanching because small particles percolate to the bottomof the flowing layer and large particles move upwards as
the grain and DFM mixture moves along the heaped surface. This results in a stratification pattern which has interleaved layers of large and small particles. The stratification
layers are then buried by subsequent avalanches, which ultimately may result in a Christmas tree distribution pattern.
At high loading rates, the grain continuously moves down
the heap, resulting in fines close to the drop point and thelarge particle close to the base of the heap or the silo walls(Fig. 2). Surface avalanches, during which the grain bulk
can shear and dilate freely on the heap surface, provide the

Schematic of avalanche segregation and kink.

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

ideal conditions for segregation because: 1) shear force on
the surface of the heap could slow down the moving of theparticles and different velocities of different particles will
enlarge spaces between them; 2) more large spaces makemore particles sifting down possible; and 3) low velocities
give particles more time to sift down. In certain situations(e.g., condensed chaff at the moving front of avalanches),
the large particles are stopped before the flowing particles
reach the base of the pile, which leads to the formation ofa kink. This kink moves in the direction opposite to theflow of grain, conserving its profile until it reaches the topof the pile. When a grain bulk contains a small number oflarger particles (than the grain kernels), a kink might notoccur, but the silo walls might produce the same effect as
the kink movement when grain kernels have a small repose
angle (Fig. 2). A kink will not occur when grain particles
in different avalanches move together. The phenomenaof kink and Christmas tree have not been reported duringgrain loading.
A structure of “Christmas tree” had been observed in discrete avalanching flow (Gray, 2018; Khakhar et al., 2001;
Lemieux and Durian, 2000). The “Christmas tree” distribution of DFM would not be observable during grain loading
if frequency of avalanche is high so that grain mixtures indifferent avalanches move together at the same time. Thishigh frequency can occur at high loading rate which wasobserved in most published studies (Bartosik and Maier,
2006; Chang et al., 1981; 1983; Jayas, 1987; Narendran etal., 2019; Salarikia et al., 2021) and during grain loading
into farm silos (Fig. 2). If the total percentage of DFM islow, the “Christmas tree” distribution will not occur neither(Narendran et al., 2019).
Segregation patterns due to avalanches are dependent on
several factors, including how the heap forms, the heap geometry, the loading rate, and the size ratios of the particles
on the heap (Mosby et al., 1996). Even though avalanche isa simple phenomenon, its occurrence is difficult to predict,and it is not known how and when it occurs under whatgrain loading conditions. Therefore, DFM segregation due
to avalanche is also not fully known. Avalanches might
frequently and irregularly develop at the free surface ofheaps. Therefore, segregation due to avalanche is complex
because the heap geometry changes continuously duringgrain loading, and so do the static and dynamic angles ofrepose on the heap. The angle of repose is mostly influenced by irregularity of the particles (e.g., larger sphericity
has a smaller repose angle) and the composition of the particle assembly at the apex, both might change continuously
during grain loading. At the same time, high moving speedof avalanche can cause fines and larger particles to move
far away from the central drop point, resulting in sifting
segregation and wide distribution of fines. Grain mixtures
can either segregate into layers or remain mixed, dependent
on the balance between particle-size and particle-density

segregation. Therefore, segregation due to avalanche could
result in variations of DFM distribution even at the samegrain loading conditions and might be the main reason
causing the DFM variations at the center and walls. This
speculation should be further verified.

3. Segregation mechanisms responsible for
DFM distribution during grain loading
Grain loading consists of several consecutive steps:
heap formation at the drop point, particles moving along
the heap surface and stopping at the walls, and avalanches
occurring at the apex of the heap. Therefore, multiple
segregation processes (mechanisms) occur simultaneously
when grain is loaded into the silo. Most experiments reported in the literature only presented the final conditions
after the grain had been loaded into the silos. It is difficult
to systematically assess each segregation mechanism ateach step of grain loading.
In on-farm grain silos in Canada and USA, the DFM
is usually lower than 1 % and occasionally could reachto the maximum 15 % (Jian et al., 2019). When the DFM
concentration is low, the trajectory and sifting segregation
might become more significant. Avalanching can intensify
sifting segregation and fluidization segregation of chaff.
Therefore, these main segregation processes (trajectory,
sifting, and avalanche segregation) result in a concentrated
distribution of smaller and denser particles (smaller than
the sound grain kernels) at the center and larger and lighter(than the sound grain kernels) particles at the walls. The
cleanest location (minimum amount of fines and chaff) is
the annular area about the midway between the silo center
and walls (Jayas, 1987; Salarikia et al., 2021). Even thoughdifferent researchers had different conclusions on the dominant mechanisms of segregation and the factors influencing
segregation, they usually reported this similar distribution
pattern (Bartosik and Maier, 2006; Chang et al., 1981;
1983; Salarikia et al., 2021), and the only exception is thefine distribution in canola silos (Jayas, 1987) (Table 1).
Chang et al. (1981) reported that more than 10 % fines were
found at center of a corn silo, while less than 4 % fines
were found at other locations. In a wheat silo, Chang et al.
(1983) found more than 4 % of fines were at the silo center,
while less than 4 % fines at other locations. In a 10-meter
diameter silo, fine particles, dust, fragments, and foreignmaterials (corn and soybean kernels) mainly accumulated
in the center, while chaff accumulated mostly near thewalls (Salarikia et al., 2021). Jayas (1987) found chaff wasconcentrated near the walls of a canola silo.

103

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109
Table 1

Measured distribution of dockage and foreign materials in different studies.

Test condition a

Definition of DFM

DFM distribution

SourcesCorn was dropped at 7 m height into a
6.4 m diameter flat bottom silo througha spout. Initial velocity was about
0.12 m/s

Particles passed through sieve(4.8 mm diameter round-hole) werefines

Fine at center ranged
from 2 to 22 % andaverage of 4.5 % in
the bin(Chang et al., 1981)

Grain was dropped through an orifice
at 7.4 m height into a silo with 6.4 m
diameter. Choke flow with 0.6 to
0.7 m/s initial loading velocity. Initialfines were 2.00, 3.17, and 3.87 % forwheat, corn, and sorghum, respectively.

Particles passed through a sieve(1.6 × 9.5 mm 2 oblong-hole forwheat, 4.8 mm diameter round-holefor corn, 2.0 mm circle triangularhole for sorghum) were fines

Chang et al. (1983)
Fines were concentrated in the bin
center within a radiusof about 60 cm andas 4 to 5 times higher
than the average

Canola (6 to 10 % moisture content)
was dropped at 7.2 m height into a
4.6 m diameter flat bottom silo

Chaff and canola were retained on
a 1.7 mm and 1.18 mm opening
meshes, respectively. Fines passed
through the 1.18 mm mesh

Jayas (1987)
Chaff was concentrated near walls. The
center and walls had
the similar fines

Wheat (12.2 % moisture content) was
dropped at 6 m height from a funnel
with 0.2 m by 0.3 m outlet to a 10 m
diameter flat bottom silo. Auger with
45 t/h was used to load the wheat to thefunnelWheat kernels < 3.35 mm and> 2.0 mm. Other particles orother grains were ≥ wheat kernels(≥ 2.0 mm). Fines were pieces ofbroken wheat kernels, awn, broken
chaff, and canola kernels (≥ 0.3 mm
and < 2.0 mm. Dusts < 0.3 mm

Salarikia et al. (2021)
Other particles wereconcentrated near thewalls. Fines and dusts
were concentrated at
the bin center

Yellow dent shelled corn was dropped
at 7 m height into a 6.4 m diameter flatbottom bin through a spout. Initial fines
were < 6 %Particles passed a sieve (4.8 mm
round hole opening) were fines,
while retained on the sieve werecorn

Fines in the center
and walls ranged
from 11.6 to 24.8 %and from 1.7 to
2.2 %, respectively

Stephens and Foster (1976)

Wheat mixture (including less than
6 % kidney bean, soybean, and canola)
was dropped at 2.4 m height into a 2 m
diameter circular steel ringThree sieves with apertures of 7.09,
4.75 and 2.45 mm were used toseparate the grain mixture. Grain
mixture was cleaned before test

Canola was concentrated near walls,
kidney and soybean
were concentrated at
the middle radius

Narendran et al. (2019)a Drop height is the initial height and this height is gradually decreased as the increase of grain depth in the silo. Grain is dropped

at the roof centers of the bins in all tests.

4. Factors influencing segregation

4.1 Drop height

Many factors influence DFM distribution, including thebin size and shape; physical properties of particles (grainkernels and other materials), such as the size and size
distribution and size ratio, percentage of dockage and foreign materials, density, moisture content, shape and shapefactor, modulus of elasticity, friction coefficient, surface
texture, cohesion, and adhesion; and process variables(loading method, loading direction and rate, drop height,
size of the loading outlet, heap size, and mixing ratio).
The factors that are mostly studied include the drop height,
grain type, silo size, and composition of grain bulks. Lessstudied factors are the loading method, loading direction
and speed (loading rate), and the size of loading outlet.
There are several reports on DFM distribution by using
spreaders. However, spreader is rarely used now due to theincreased airflow resistance.

Researchers have drawn different conclusions on theeffect of drop height. Narendran et al. (2019) investigatedthe effect of three different drop heights of 0.8, 1.6 and2.4 m on segregation of canola, kidney beans, and soybeans mixed with wheat in a 2 m diameter steel ring. All
grains were cleaned before test and at ≤ 11 % moisture
content (wet basis). They concluded that loading heightsignificantly influenced the distribution for canola but notfor soybeans and kidney beans and the DFM distribution
in canola was mainly dictated by the impact segregation.
Nourmohamadi-Moghadami et al. (2020) found that as
the drop height decreased in a 1-m diameter bin filled withshelled corn, broken kernels and foreign materials found in
the periphery of the bin decreased. They explained that thevelocity of the particles in the flowing layer of the grain on
the heap surface decreased as the drop height decreased,
which gave more time to the small particles to be embedded among large particles. Wheat in a 10 m diameter silo

104

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

was studied for five loading heights (1.6, 2.5, 3.4, 4.3 and5.2 m) by Salarikia et al. (2021). They observed that thedrop height significantly influenced the radial distributionof fine particles, dust, and fragments, but not the distribution of other grain kernels (corn, soybean, white bean) andother particles (straw, internode, knuckle, rachis, spikelet,
large chaff, wild oat kernels and stem) mixed in the wheat.
Even though the drop height influenced the fines and dusts,
no particular distribution pattern was found. Chang et al.
(1986) observed that the drop height up to 7.4 m had no
significant effect on the distribution of fines in bulk corn.
Jayas (1987) reported that the effect of drop height up to
7 m on the distribution of fines and chaff in canola was insignificant. These different observations could be explainedby the low drop height in the reported studies (≤ 7 m) anddifferent definitions of fines. A greater drop height mostly
results in more impact segregation which embeds morelarger particles and bounces more small particles awayfrom the silo center. The amounts of larger particles andsmall particles are usually lower than the fines and chaff
in grain silos, and therefore the drop height effect on DFM
distribution might not be observable.

4.2 Silo diameter
Heap formation during grain loading is one of the main
reasons that trigger particle segregation because sifting
segregation occurs as the particles move down on the heap
surface. Increase of the silo diameter leads to greater moving distances, hence large silos would intensify segregation(Mosby et al., 1996). However, Prasad (1974) reported thatthe distribution of dockage (smaller and larger than wheat
kernels in bulk wheat) followed the same trend in 4.2 m
and 5.4 m diameter bins. But it was not known whether
this no-difference was caused specifically by the small silodiameters or not.

4.3 Size ratio
The difference in particle sizes (or the size ratio) is themost important reason for segregation in bulk materials.
The degree of segregation increases with the increase of thesize ratio. Unfortunately, size ratio was not reported in theliterature related to the segregation of crop grain mixtures
because it was difficult to quantify the size ratio in a crop
grain mixture with different particle sizes. Therefore, size
ratio can be estimated by using the average size of soundkernels and the average size of the segregated particles.
Stephens and Foster (1978) pointed out that the segregation of fines (smaller than 1.2 mm) in wheat and sorghum(larger than 2.0 mm) was lower than the segregation in corn(larger than 4.8 mm). However, Chang et al. (1983) showed
no difference in the trend of fine distribution between corn,
wheat, and sorghum in 6.4 m diameter silos.

4.4 Percentage of DFM and moisture content
The percentage of DFM and moisture content of grain
might also influence the particle segregation because:
1) grain kernel with a higher moisture content is usuallylarger than the same kernel with a lower moisture content;2) grain kernels with different moisture contents might
have different shapes and different friction forces between
kernels; 3) different amounts of DFM could influence theoccurrence (frequency and size) of avalanches and associated segregation; and 4) more DFM with a larger size ratio
could result in more impact and kink segregations. In a silo,different parts might be subjected to different segregation
mechanisms if the percentage of dockage and foreignmaterials, moisture content of the grain mixture change.
However, Narendran et al. (2019) found that the percentage
of other grains (kidney bean, soybean, and canola) in thewheat bulk did not have any significant effect on the distribution and segregation of the other grains.

4.5 Missing link
It is generally agreed that segregation can be influenced
by many factors, but these factors are not all considered inmost studies. Specifically, 1) most studies only separated
the larger and smaller particles from the grain kernels(Table 1); 2) some factors were not controlled or difficult
to control (Table 1), so the multifactor effects or interactionof multifactors might be missed if only examining the final
DFM distribution; and 3) the segregation mechanisms
might be induced from the DFM distribution, and thesemechanisms are usually specified in a qualitative mode,
which further contributes to the mystery of the effect ofthese factors on segregation.

5. Experimental studies
5.1 Focus of measurements
One of the main reasons why particle segregation isremained somewhat mysterious is that it is difficult tocollect the evolving particle size distribution data to verify
the segregation mechanisms. In grain storage management,
the most concerned detrimental effects of DFM distribution are: airflow resistance during drying and aeration;
insect multiplication and fungi infestation in concentrated
DFM regions; uneven distribution of fumigants during
fumigation; and uneven distribution of gases (CO2, N2,
and O2) during controlled atmosphere storage. Therefore,
most methods used to measure the DFM segregation are
designed to determine the airflow resistance and sample
the loaded grain to determine the DFM distribution after
the loading is completed. Compared to sampling grain

105

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

for DFM determination, airflow resistance measurement
is relatively easy because it only needs to run the fan
and measure the airflow rate at the surface of the grainbulk. However, this method can only provide an indirectindication of the DFM distribution, not the actual DFM
distribution.

5.2 Field studies
There are a few studies on the mechanisms of segregation of DFM in grain silos filled by center spouts (Table 1).
Typical size on-farm grain silos with 4 to 10 m diameterand up to 7.5 m drop heights have been tested (Table 1).
The tested crops included corn, wheat, sorghum, andcanola. Most of these studies were aimed to compare theDFM distributions between spreader loading and spout
loading. It was found that spreader loading increased theairflow resistance even though the DFM distribution was
more even than spout loading. In these studies, grain atdifferent locations was sampled after loading, and larger
impurities (chaff), small impurities, and grain kernels
were separated from the grain samples by using sieves. All
these studies did not further separate the larger and smaller
impurities except one study conducted by Salarikia et al.
(2021). Salarikia et al. (2021) further separated the small
impurities into shrunken and broken kernels, fine particles,
and dusts and fragments. The larger impurities were further
separated into stones, other grains, and other particles byusing sieves. This further separation provided more detailsof the DFM distribution in silos.

5.3 Laboratory studies
Under lab conditions, the following factors influencing
DFM distribution have been studied: drop height, components of the grain bulk (mixture), filling method, loading
rate, and fill pipe diameter (Narendran et al., 2019). The lab
studies have improved our understanding of DFM segregation mechanisms, but they are usually conducted by using
smaller than 2 m diameter silos or rings, which limits theheap size (please refer 4.2).

5.4 Limitations of current studies
One of the common limitations in most studies is thefocus on the DFM distribution without exploring the segregation mechanisms. Few studies have isolated the main
segregation mechanisms from other mechanisms. If only
measuring the final distribution, experiments are simple
because just loading the grain mixture into a grain silo canachieve this goal. However, identifying particle movement
and segregation mechanisms during their movement requires different approaches and complex techniques, suchas high quality imaging and laser tracing (Lemieux and106

Durian, 2000; Pouliquen et al., 1997). Due to the lack of
information associated with the segregation of moving
grain kernels, segregation mechanisms and their impact
on DFM distribution can only be inferred from the final
observed DFM distribution, which might generate uncertainties. Currently, segregation mechanisms of grain kernels are also inferred from studies using non-grain kernels
such as sand and lead particles. Some early studies on the
segregation mechanisms of these non-grain particles used
the mechanical approaches such as mass and momentum
balances of the purely frictional fluid (Savage and Hutter,1989), slow heap formation of cellular automata (Frette etal., 1996), conservation of particles being absorbed into thestationary heap or eroded from the heap into the flowing
layer (Bouchaud et al., 1994), and quasi-two-dimensional
heap formation of open and closed systems (Khakhar etal., 2001). These approaches and models are capable ofdescribing the qualitative behavior of the system, but theycannot predict the quantitative distribution of DFM in
grain silos because these predictions require the estimationof several phenomenological parameters associated withgrain kernels and identification of the dominant segregation mechanisms, which have not been fully understood.

5.5 Inconsistencies
5.5.1 Confusion of definitions

Different studies use different definitions of DFM whichmight lead to different conclusions. For example, fines areusually defined in the literature as the particles smaller thangrain kernels (Table 1). However, different grain kernels
have different sizes, and the fines have different sizes in different reports. For example, Jayas (1987) defined the fines
as the particles passing through a Tyler woven wire meshwith 1.18 mm opening and canola kernels were the underflow of a 1.70 mm opening and overflow of the 1.18 mm
opening (Table 1). Chang et al. (1983) defined the particle
passing 1.6 × 9.5 mm2 oblong-hole for wheat, 4.8 mm
diameter round-hole for corn, 2.0 mm circle triangular-holefor sorghum. Salarikia et al. (2021) defined the fines as theparticles smaller than 2.0 mm. Therefore, fine distribution
inside canola bulks should have different patterns fromlarger grain kernels if we define the fine as the particles lessthan the grain kernels. Salarikia et al. (2021) found dusts
were concentrated in the bin center, while Jayas (1987)
found fines were not concentrated at the center of the bin,and the concentration of fines near the bin center was
almost equal to that near the sides of the bin. These results
are not comparable due to the inconsistency in definitions.

5.5.2 Different sampling methods

Another reason generating different conclusions of DFM
distribution might be the method of sampling. Different
researchers used different sample sizes and units. Most

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

researchers took less than 1 kg samples at few locations
and only separated chaff and fines from the samples(Bartosik and Maier, 2006; Chang et al., 1981; 1983;
Jayas, 1987). Considering the uneven distribution and low
concentration of DFM, a few samples of 1 kg grain takenfrom a silo holding more than 100 tons of grain might not
represent the DFM distribution (Jian et al., 2014). Salarikia
et al. (2021) took about 22 kg at each sample location anddifferent categories of DFM were further separated: stones,
other grains, other particles, shrunken and broken kernels,
fine particles, dusts, and fragments. Based on the larger
samples, this study had different conclusions from otherpublished studies on the distribution of shrinkage and broken grain kernels, other particles, dust and fragments, andsmall and larger grain kernels.

6. Mathematical and numerical modeling
6.1 Mathematical modeling
Even though there is no theoretical model developed
to directly describe the DFM segregation in grain silos
with spout filling, models related to heap segregation havebeen in existence. Some models are developed based oncontinuum of mass and advection diffusion combined withflux function. Some examples are the one-dimensionalmodels developed by Bridgwater et al. (1985) and Savage
and Lun (1988), and two-dimensional models developed
by Dolgunin and Ukolov (1995). Many models are developed based on mixture theory (Gray and Ancey, 2015;
Tunuguntla et al., 2014), and Gray et al. (2015) provided
an extensive review on these models. Non-diffuse theoryis also used by researchers to develop models describing
particles sheared over large heap surface (Pouliquen et al.,
1997; Pouliquen and Vallance, 1999; Woodhouse et al.,2012). Depth-averaged models have been developed todescribe avalanches and finger instability (Woodhouse etal., 2012). Other approaches such as segregation inducedby shear force (Fan and Hill, 2011), pure density (Tripathi
and Khakhar, 2013), and size (Marks et al., 2012) havebeen tested. Gray et al. (2015) provided a review on themodeling of a single avalanche (without mass exchange).
Even though these models mentioned above can help us tounderstand the segregation mechanisms, these models are
not capable of predicting DFM segregation in silos because
they only consider the binary mixture or three components.
Gray (2018) reviewed these equations and solution techniques. Even though polydisperse mixture might be able
to be modeled, some additive decomposition mechanisms
must be introduced, hence the complexity. Marks et al.
(2012) developed an alternative theory for polydisperse
segregation with a continuous grain-size distribution thatis closer to the reality of both industrial and geophysicalmaterials. This model must be solved simultaneously infive dimensions: space, time, and the three dimensions ofgrain-size coordinates.
It should be noted that the models discussed above only
considered the open flow. Segregation in grain silos is theclosed flow except at the beginning of loading before grainreaches the walls. The complexity of these models, as wellas the difficulties to solve the equations in the models, limits the practical applicability of these models to predicting
particle distributions.

6.2 DEM modeling
The discrete element method (DEM) has been used tosimulate the segregation of particle mixtures, but thesesimulations are mostly used as a tool to understand the segregation principles by using the idealized materials and are
not yet at the stage of simulating segregation in real grainsilos. For example, by using DEM simulation, Pereira et al.
(2011) verified a continuum theory based on a species balance equation in the flowing layer by balancing the convective flow with diffusion and segregation fluxes. Khakhar etal. (1999) used transport equations from the kinetic theoryof mixtures for a mixture of nearly elastic smooth particles
to analyze density segregation. Marks et al. (2012) used theapproach based on partial stresses in their DEM simulation.
Tripathi and Khakhar (2013) simulated the segregationof granular mixtures of equal-size particles with different
densities. Using three-dimensional DEM model, Fan and
Hill (2011) proved that a gradient of shear rate alone could
drive segregation in dense sheared systems. The effect ofshear caused small particles to move to the regions of low
shear rate and large particles in the opposite direction. Currently, DEM simulations are typically limited to sphericalparticles, and it is difficult to treat particles having irregularshapes and a wide size distribution directly because ofmathematical complexity and computational demand. The
compromise is to treat the particles as “spherical particles
with an equivalent rolling behavior to the particle with
arbitrary shape” (Shimoska et al., 2013). This assumption
increases the prediction error, and the error is usually unacceptable for the grain industry because grain kernels and
DFM are usually not spherical particles.

7. Challenges and directions for future
research
A challenge of studying segregation in grain silos isthe difficulty in collecting the reliable detailed data which
can be used to identify the effect of individual segregation
mechanisms. High speed camera and laser used to capture
the motion of individual kernels during grain loadingmight be the examples of collecting the reliable detailed

107

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

data for the understanding of segregation mechanisms.
Another challenge is to develop predictive models capableof handling multiple segregation factors and mechanisms.
Currently, researchers mostly focus on the final distribution
which can be directly used for grain storage management.
There are rarely fundamental studies on segregation
mechanisms and factors influencing these segregation
mechanisms. Without studying segregation mechanisms
and factors influencing segregation, focusing only on the
DFM distribution might impede the understanding of thesegregation mechanisms.

8. Conclusions
Loading grain into silos from a central spout is a mostcommon method used by the grain industry in the world
and a special case of heap flows of granular materials. Thisloading method results in a concentrated distribution ofsmaller and denser particles (smaller than the sound grainkernels) at the center and larger and lighter (than the soundgrain kernels) particles at the walls of silos. The main
mechanisms responsible for this distribution pattern are
trajectory, sifting, and avalanche segregations. The main
factors influence these main segregation mechanisms are
size ratio and percentage of DFM and moisture content,
while the contribution of drop height and silo diameter tothis distribution pattern is not known due to limited studies
and contradictory reports on these factors. The following
facts also contribute to our incomplete understanding of
this distribution pattern: 1) both lab and field studies focus
on final distribution of DFM; 2) inconsistencies of term
definition, sampling method, and sample analysis; and 3)
no theoretical model is developed to directly explain the
DFM segregation in grain silos. One of challenges of studying segregation in grain silos is the difficulty in collecting
the reliable detailed data which can be used to identify theeffect of individual segregation mechanisms. Fundamental
studies on segregation mechanisms and factors influencing
these segregation mechanisms in the future might help ourunderstanding of this distribution pattern and develop atheoretical model to predict this distribution pattern.

Acknowledgements
The author thanks the Natural Sciences and Engineering
Research Council of Canada for partial funding of thisstudy; and Canada Foundation for Innovation, Manitoba
Research Innovation Fund, and several other partners
for creating research infrastructure. The author thanks
Dr. Qiang Zhang, University of Manitoba, Canada, forcommenting on the earlier version of the manuscript.

108

References
Bartosik R.E., Maier D.E., Effect of airflow distribution on the performance of NA/LT in-bin drying of corn, Transactions of the
ASABE, 49 (2006) 1095–1104. DOI: 10.13031/2013.21715
Bouchaud J.P., Cates M.E., Prakash J.R., Edwards S.F., A modelfor the dynamics of sandpile surface, Journal de Physique I, 4
(1994) 1383–1410. DOI: 10.1051/jp1:1994195
Bridgwater J., Foo W., Stephens D., Particle mixing and segregation in failure zones – theory and experiment, Powder Technology, 41 (1985) 147–158. DOI: 10.1016/0032-5910(85)87033-9Carson J.W., Royal T.A., Goodwill D.J., Understanding and eliminating particle segregation problems, Bulk Solids Handling,
6 (1986) 141–146.
Chang C.S., Convers H.H., Lai F.S., Distribution of fines and bulk
density of corn as affected by choke-flow, spout-flow, anddrop-height, Transactions of the ASAE, 29 (1986) 618–620.
DOI: 10.13031/2013.30201
Chang C.S., Converse H.H., Martin C.R., Bulk properties of grain
as affected by self-propelled rotational type grain spreaders,
Transactions of the ASAE, 26 (1983) 1544–1550. DOI:
10.13031/2013.34167
Chang C.S., Shackelford L.E., Lai F.S., Martin C.R., Miller B.S.,
Bulk properties of corn as affected by multiple-point grain
spreaders, Transactions of the ASAE, 24 (1981) 1632–1636.
DOI: 10.13031/2013.34504
Dahmen K.A., Ben-Zion Y., Uhl J.T., A simple analytic theory
for the statistics of avalanches in sheared granular materials,
Nature Physics, 7 (2011) 554–557. DOI: 10.1038/nphys1957
Dolgunin V.N., Ukolov A.A., Segregation modelling of particle
rapid gravity flow, Powder Technology, 83 (1995) 95–103.
DOI: 10.1016/0032-5910(94)02954-m
Fan Y., Hill K.M.T., Theory for shear-induced segregation ofdense granular mixtures, New Journal of Physics, 13 (2011)
1–30. DOI: 10.1088/1367-2630/13/9/095009
Fan Y., Jacoba K.V., Reireich B., Lueptow R.M., Segregationof granular materials in bounded heap flow: a review,
Powder Technology, 312 (2017) 67–88. DOI: 10.1016/j.
powtec.2017.02.026
Frette V., Christensen K., Malthe-Sorensen A., Feder J., JossangT., Meakin P., Avalanche dynamics in a pile of rice, Nature,379 (1996) 49–52. DOI: 10.1038/379049a0
Gray J.M.N.T., Particle segregation in dense granular flows,
Annual Review of Fluid Mechanics, 50 (2018) 407–433.
DOI: 10.1146/annurev-fluid-122316-045201
Gray J.M.N.T., Ancey C., Particle-size and density segregation in
granular free-surface flows, Journal of Fluid Mechanics, 779(2015) 622–668. DOI: 10.1017/jfm.2015.438
Gray J.M.N.T., Gajjar P., Kokelaar P., Particle-size segregationin dense granular avalanches, Comptes Rendus Physique, 16(2015) 73–85. DOI: 10.1016/j.crhy.2015.01.004
Jayas D.S., Resistance of bulk canola oilseed to airflow, PhD
dissertation, University of Saskatchewan, 1987. http://hdl.
handle.net/10388/7893
Jian F., Jayas D.S., White N.D.G., How many kilograms ofgrain per sample unit is big enough? Part II – Simulation ofsampling from grain mass with different insect densities anddistribution patterns, Journal of Stored Products Research, 56(2014) 67–80. DOI: 10.1016/j.jspr.2013.05.006.
Jian F., Narendran R.B., Jayas D.S., Segregation in stored grainbulks: kinematics, dynamics, mechanisms, and minimization—a review, Journal of Stored Products Research, 81(2019) 11–21. DOI: 10.1016/j.jspr.2018.12.004

Fuji Jian / KONA Powder and Particle Journal No. 39 (2022) 100–109

Johanson K., Eckert C., Ghose D., Djomlija M., Hubert M.,
Quantitative measurement of particle segregation mechanisms, Powder Technology, 159 (2005) 1–12. DOI:
10.1016/j.powtec.2005.06.003
Ketterhagena W.R., Curtisb J.S., Wassgrenc C.R., Kongd A.,
Narayane P.J., Hancock B.C., Granular segregation in discharging cylindrical hoppers: a discrete element and experimental study, Chemical Engineering Science, 62 (2007) 6423
– 6439. DOI: 10.1016/j.ces.2007.07.052
Khakhar D.V., Mccarthy J.J., Ottino J.M., Mixing and segregation of granular materials in chute flows, Chaos, 9 (1999)
594–610. DOI: 10.1063/1.166433
Khakhar D.V., Orpe A.V., Andresen P., Ottino J.M., Surface flowof granular materials: model and experiments in heap formation, Journal of Fluid Mechanics, 441 (2001) 255–264. DOI:
10.1017/s0022112001005201
Lemieux P.A., Durian D.J., From avalanches to fluid flow: acontinuous picture of grain dynamics down a heap, Physical Review Letters, 85 (2000) 4273–4276. DOI: 10.1103/
physrevlett.85.4273
Makse H.A., Ball R.C., Stanley H.E., Warr S., Dynamics ofgranular stratification, Physical Review E, 58 (1998) 1–12.
DOI: 10.1103/physreve.58.3357
Marks B., Rognon P., Einav I., Grain size dynamics ofpolydisperse granular segregation down inclined planes,
Journal of Fluid Mechanics, 690 (2012) 499–511. DOI:
10.1017/jfm.2011.454
Mosby J., de Silva S.R., Enstad G.G., Segregation of particulatematerials – mechanisms and testers, KONA Powder and Particle Journal, 14 (1996) 31–43. DOI: 10.14356/kona.1996008
Narendran R.B., Jian F., Jayas D.S., Fields P.G., White N.D.G.,
Segregation of canola, kidney bean, and soybean in wheatbulks during bin loading, Powder Technology, 344 (2019)307–313. DOI: 10.1016/j.powtec.2018.12.042
Nourmohamadi-Moghadami A., Zare D., Singh C.B., Stroshine
R.L., Filling of a grain silo. Part 1: Investigation of finematerial distribution in a small scale center-filled silo, Biosystems Engineering, 191 (2020) 145–156. DOI: 10.1016/j.
biosystemseng.2020.01.001
Pereira G., Sinnott M., Cleary P., Liffman K., Metcalfe G., Stalo
I., Insights from simulations into mechanisms for density
segregation of granular mixtures in rotating cylinders,
Granular Matter, 13 (2011) 53–74. DOI: 10.1007/s10035010-0223-6
Pouliquen O., Delour J., Savage S.B., Fingering in granular flows,
Nature, 386 (1997) 816–817. DOI: 10.1038/386816a0

Pouliquen O., Vallance J.W., Segregation induced instabilities of granular fronts, Chaos, 9 (1999) 621–630. DOI:
10.1063/1.166435
Prasad D.C., Abiotic and biotic characteristics of freshlyharvested grain, MSc dissertation, University of Manitoba,
1974. http://hdl.handle.net/1993/13475
Salarikia A., Jian F., Jayas D.S., Zhang Q., Segregation of
dockage and foreign materials in wheat during loading into
a 10-meter diameter corrugated steel bin, Journal of Stored
Products Research, 93 (2021) 101837. DOI: 10.1016/j.
jspr.2021.101837
Savage S.B., Hutter K., The motion of a finite mass of granularmaterial down a rough incline, Journal of Fluid Mechanics,
199 (1989) 177–215. DOI: 10.1017/s0022112089000340
Savage S.B., Lun C.K.K., Particle size segregation in inclined
chute flow of dry cohesionless granular solids, Journalof Fluid Mechanics, 189 (1988) 311–335. DOI: 10.1017/
s002211208800103x
Shimoska A., Nousou I., Shirakawa Y., Hidaka J., Effect ofparticle shape on size segregation of particles, Chemical
Engineering Transactions, 32 (2013) 2143–2148. DOI:
10.3303/CET1332358
Stephens L.E., Foster G.H., Bulk properties of wheat andgrain sorghum as affected by a mechanical grain spreader,Transactions of the ASAE, 19 (1978) 1217–1221. DOI:
10.13031/2013.35471
Tang P., Puri V., Methods for minimizing segregation: a review,
Particulate Science and Technology, 22 (2004) 321–337.
DOI: 10.1080/02726350490501420
Tripathi A., Khakhar D.V., Density difference-driven segregation
in a dense granular flow, Journal of Fluid Mechanics, 717(2013) 643–669. DOI: 10.1017/jfm.2012.603
Tunuguntla D.R., Bokhove O., Thornton A.R., A mixture theory
for size and density segregation in shallow granular freesurface flows, Journal of Fluid Mechanics, 749 (2014)
99–112. DOI: 10.1017/jfm.2014.223
Woodhouse M.J., Thornton A.R., Johnson C.G., Kokelaar B.P.,
Gray J.M.N.T., Segregation-induced fingering instabilities in
granular free-surface flows, Journal of Fluid Mechanics, 709(2012) 543–580. DOI: 10.1017/jfm.2012.348
Zigan S., Thorpe R.B., Tuzun U., Enstad G.G., Battistin F.,
Theoretical and experimental testing of a scaling rule for air
current segregation of alumina powder in cylindrical silos,
Powder Technology, 183 (2008) 133–145. DOI: 10.1016/j.
powtec.2007.11.030

Author’s Short Biography
Fuji Jian
Dr. Fuji Jian is a professional engineer and Assistant Professor in the Department of Biosystems
Engineering at the University of Manitoba, Canada. Fuji’s research interests are in post-harvest grain
quality, stored-product protection, drying and aeration of grains, insect control, particle segregation,and sensor development with the sole purpose to enhance food safety and security. He is the leadauthor in 85 of more than 100 technical articles in scientific journals, conference proceedings andbooks.

109

KONA Powder and Particle Journal No. 39 (2022) 110–118/https://doi.org/10.14356/kona.2022002

Review Paper

Synthesis of Noble Metals and Their Alloy Nanoparticles by
Laser-Induced Nucleation in a Highly Intense Laser Field †Takahiro Nakamura *, Yuki Yamazaki and Shunichi Sato
Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, Japan

Abstract
The synthesis of noble metals and their alloy nanoparticles by laser-induced nucleation is described. Femtosecond
laser pulses with an energy on the order of mJ were tightly focused to create an intensity of 1014 W/cm 2 or more in
an aqueous solution of noble metal ions. The intense laser field generated solvated electrons and hydrogen radicals
that have a highly reducing ability, resulting in nucleation through the reduction of the noble metal ions andparticle growth through ripening. This laser-induced nucleation method can be performed without any reducing
agents. Excess irradiation of chloroauric acid solution led to the formation of a stable colloidal solution of gold
nanoparticles without any surfactants. Additionally, the irradiation of a mixed solution of different noble metal
ions formed solid–solution alloy nanoparticles, even though these metals were immiscible in the bulk. Moreover,the laser-induced nucleation made it possible to form quinary solid-solution alloy nanoparticles of noble metals.
The mechanism of superior catalytic activity found for alloy nanoparticles by using Rh–Pd–Pt solid–solution
nanoparticles is discussed in terms of elemental distributions inside the particles.
Keywords: high-intensity laser field, femtosecond laser, nanoparticles, solutions, noble metals

1. Introduction
Lasers have a variety of excellent features in terms ofwavelength, output, pulse width, spectral width, and so on.
As a result, many applications have been developed in awide range of fields, such as communication, information
technology, and medicine in both academic and industrial
societies. In particular, in laser processing, lasers are rapidly expanding the application range, for example, heating,welding, cutting, drilling, marking, surface modification,
particle synthesis and thin film deposition by laser ablation,
and additive manufacturing. From the viewpoint of themorphological transformation of a material, these process
techniques include top-down or bottom-up approaches
between large- and small-scale materials. One of the meritsof laser processing is the ability to sustain the crystalline
structure, composition, and property of the materials
during the process.
Currently, with the progress of laser technology, especially, ultrafast pulse generation and regenerative amplification, the laser output has become strong enough togenerate an unprecedented ultra-intense optical field. Sup†*

Received 30 June 2020; Accepted 16 August 2020
J-STAGE Advance published online 17 October 2020
Corresponding author: Takahiro Nakamura;
Add: 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
E-mail: nakamu@tohoku.ac.jp
TEL: +81-22-217-5672 FAX: +81-22-217-5671

110

posing that a laser pulse with a pulse energy of 1 mJ anda pulse width of 100 fs is focused to an area of 10 μm2 byaberration-free optics, the peak intensity at the focal point
will be 1017 W/cm2, according to calculations. This value
is comparable to the Coulomb field inside the hydrogenatom, which is 5.0 × 1011 V/m, corresponding to the lightintensity of 7.0 × 1016 W/cm2. Such an ultrahigh electricfield is not achievable by conventional electric techniques
and is expected to result in a novel reaction field in materials science. The reaction in this unprecedented field would
be different from those in a thermal equilibrium state athigh temperature achieved by commonly used processing
techniques and could offer an ultimate reaction field thathas never existed on Earth. Highly intense laser science,
however, has mainly focused on gas-phase reactions(Cornaggia et al., 1995; Cornaggia, 1995; Castillejo et al.,
1999; Talebpour et al., 2000), where the density of atoms,
ions, fragments, and molecules are dilute enough to ignore
their interactions. As a result, the production of species
and molecules different from the starting materials in acondensed state, such as a liquid or solid, has been outsideof the scope of highly intense laser science for a long time.
As a next step, small particle synthesis by laser irradiation of a solid target immersed in liquid has been reported,which utilized the high energy density state created by theconfinement effect of plasma in liquid (Wang et al., 2002;
Pearce et al., 2004). In this pulsed laser ablation in liquid(PLAL), a uniformly dense reaction field was formed to

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118

avoid the generation of large debris by suppressing thelaser energy. In contrast, as mentioned earlier, if ultrashortlaser pulses with an energy on the order of mJ are strongly
focused to a diffraction-limited small spot, an ultrahighintense laser field can be created in condensed matter,like liquid or solid, by using a commercially available
regenerative amplifier laser system. In this intense laser
field, photoionization and photodissociation of materials
will instantly lead to the formation of high-temperatureand high-density plasma. The expansion of the plasma
will be strongly suppressed, and the temperature will be
rapidly cooled down by the surrounding high-density andlow-temperature materials, resulting in a non-equilibrium
process that is much faster than conventional processes.
We focused on the non-linear and non-equilibrium
reaction field created near the focal point of ultrafast laser
pulses with a high peak power and addressed the nanoparticle (NP) synthesis of noble metals and their alloys inthe highly intense laser field. In this review, we describe
the distinguishing properties found for NPs fabricated byhighly intense laser irradiation of aqueous solutions ofmetallic ions, especially, the synthesis of stable colloidal
solutions of gold (Au) NPs without any dispersants, thecatalytic activity of alloy NPs, and the synthesis of solid–
solution quinary alloy NPs.

2. Experimental procedures
A schematic drawing of the experimental setup is shownin Fig. 1. Focused femtosecond laser pulses were irradiatedon aqueous solutions of metal ions held in a fused-silica
cuvette for a predetermined time. The laser pulses weregenerated from a regenerative amplifier of a mode-locked
Ti:sapphire oscillator. The center wavelength was 800 nm,
the pulse width was 100 fs, the maximum pulse energy was
6 mJ, and the maximum repetition rate was 1 kHz. The
laser pulses were delivered from the side of the cuvette andwere focused near the center of the cuvette by an asphericallens with a focal length of 8 mm and a numerical apertureof 0.5. The lens diameter of 10 mm was the same as thebeam diameter of the laser pulses. In Fig. 1, the drawing

corresponds to a stationary system, where the liquid sample
was held in the cuvette, whereas a flow system was available by circulating the liquid sample with a feed pump to
substantially increase the production rate of NPs (Muttaqin
et al., 2015). This was because the liquid flow was able
to remove the bubbles that were generated by the laser
irradiation of the liquid sample, as shown in Fig. 1, andinterrupted normal focusing of the laser pulses.
The intensity of light at the focus can be calculated to be
3 × 1018 W/cm2 if we ignore the aberration of the focusing
optics. However, the lens used in the experiment was not
optimized for this experimental condition. The diameterof the focus was estimated to be 175 μm mainly due tothe spherical aberration at the interfaces between air/glass
and glass/liquid, resulting in an intensity at the focus of
2.5 × 1014 W/cm2, which was sufficiently strong enough to
induce photodissociation and photoionization of the liquidsample.

3. Formation mechanism of noble metal andalloy nanoparticles in the highly intenselaser field
The nanoparticle synthesis of noble metals and their
alloys that we developed was not based on a conventional
morphological change of materials but a physicochemical
reaction induced by the highly intense laser field. The
process is accomplished by the reduction of metal ionswith solvated electrons and hydrogen radials, which are
generated by photodissociation and photoionization ofwater molecules. Below, the synthesis of gold (Au) NPs byhighly intense laser irradiation of an aqueous chloroauricacid solution is presented as a typical example. When an
aqueous chloroauric acid solution was irradiated, a bright
flash of plasma emission near the focal point and thegeneration of hydrogen and oxygen gas were observed.
With increasing irradiation time, the transparent aqueous
solution changed to red purple, which corresponded to
localized surface plasmon resonance (LSPR) of Au NPs
at approximately 520 nm. In fact, many spherical Au NPs
with an average size of 10 nm were observed by transmission electron microscopy (TEM). From these observations,the following mechanism for the nanoparticle synthesis
was inferred.

2H 2O (h)  2H 2O *  2H 2O   2e   OH •  H O  2e aq3  H O  H•  H O
e aq
3
2

k
2.3  1010 dm 3mol 1s 1
1
  OH •  OH 
(1)
e aq

Fig. 1 Schematic of the experimental setup.

(2)k
3.0 1010 dm 3mol 1s 1
2

(1)

(2)

(3)

(3)
111

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118
M   eaq
 M0

(4)

M   H•  H   M 0

(5)

(4)
M 0  M 02    M 0n

(6)

(5)
When an intense laser is used to irradiate an aqueous– ), hydrogen radicals (H•),
solution, solvated electrons (eaq(6)•
and hydroxy radicals (OH ) are generated by multi-photon
absorption and avalanche photoionization (Eqs. 1 and
2). According to a pump–probe experiment, this process
would be completed in several hundred femtoseconds.
Monte Carlo simulations predicted that the solvatedelectrons recombine on the picosecond order (Eqs. 2 and3), and the formation of hydroxy ions is more dominant(Thomsen et al., 1999). The redox potentials of a solvated electron and hydrogen radical are –2.77 VSHE and–2.10 VSHE, respectively, which are high enough to reduce
metal ions in aqueous solution, resulting in the formation ofneutral metal atoms (Eqs. 4 and 5) and NPs (Eq. 6) owing
to the nucleation and succeeding ripening process. Because
the reduction process completes on the picosecond order
as mentioned above, the particle growth is limited in ashort period just after every laser pulse. Additionally, theshort reaction time results in the reaction being localized
to a small area near the laser focus. In summary, metal
nanoparticle formation by “laser-induced nucleation” ischaracterized as reducing agent-free with a short reaction
time and localized reaction. Of note, the reaction free fromany reducing agents results in significant benefits, such as
simplification of the formation process and clean particle
surfaces.

All the spectra were obtained by subtracting the data forthe sample before the laser irradiation. At the beginning,
remarkable changes were not observed. After 3 min, theabsorbance at approximately 520 nm corresponding to the
LSPR of Au NPs appeared and increased with increasing
irradiation time, as indicated by the arrow in the figure.
This visible change of the LSPR rapidly decreased andstopped at 14 min. The peak absorbance corresponding to
the LSPR is plotted as a function of the irradiation time in
Fig. 3. A rapid rise of the LSPR absorbance from 3 min to
14 min is clearly visible. After 14 min of irradiation, the
LSPR absorbance gradually decreased.
The termination of the rapid increase of absorbance at
14 min suggested that the auric ions in the solution were
mostly exhausted by laser irradiation. Although reductionof auric ions was not further expected, a morphologicalchange in Au NPs can be expected upon extending the laser
irradiation. When laser irradiation was continued after the

4. Gold nanoparticles with high dispersion
stability without a dispersantFig. 2 UV–visible absorption spectra of the chloroauric acid solution ata concentration of 2.5 × 10 –4 mol/L measured every 30 s in situ duringlaser irradiation.

The progress of particle formation can be monitored
through the absorption peak of specific ions or the LSPR
of the Au NPs. Once the absorbance of a species of interest
becomes saturated, the reduction of metal ions is mostly
completed; thus, we can cease laser irradiation. For theirradiation of the chloroauric acid solution, the Au NPs
aggregated and precipitated sooner or later. However, when
the irradiation was continued after absorbance saturation,
the Au NPs showed morphological stability, and the colloidal solution remained in the dispersed state for at least
several months (Nakamura et al., 2013). Next, we discuss
the phenomenological change that occurred to the Au NPs
with increasing irradiation time.
Fig. 2 shows the UV–visible absorption spectra of
the chloroauric acid solution with a concentration of
2.5 × 10–4 mol/L recorded every 30 s during the laser irradiation. The repetition rate of the laser pulses was 30 Hz.

Fig. 3 Time variation of the LSPR peak absorbance in the UV–visible
absorption spectra of the chloroauric acid solution measured in situ
during laser irradiation.

112

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118

termination, the shape and size of the Au NPs were investigated by TEM observations. Fig. 4 shows the TEM imagesof the Au NPs fabricated by laser-induced nucleation withdifferent irradiation times. The Au NPs coalesced withothers until 14 min. Upon further irradiation, the particles
were partly dispersed, and the particle size became smaller.
At 60 min, the nanoparticles were well dispersed, and theparticle size became much smaller. The particle size variation with irradiation time is shown in Fig. 5. The particle

size variation is clearly observable in the TEM images.
Specifically, the dispersion and the mean size of the particles became smaller with irradiation time. The UV–visible
absorption spectra showed no significant difference after
14 min of irradiation, whereas the morphology of the Au
NPs drastically changed, as shown in the TEM images.
These findings suggested that the electronic property of the
Au NPs was affected by the excess laser irradiation.
We analyzed the long-time dispersion stability because
the Au NPs were well dispersed after 60 min, as shown in
Fig. 4(d). In Fig. 6, we show the absorption spectra of thecolloidal solution of Au NPs 1 day and 2 weeks after preparation with different irradiation times. Each inset shows

Fig. 4 TEM images of the Au NPs fabricated by laser-induced nucleation with irradiation times of (a) 9, (b) 14, (c) 20 and (d) 60 min.

Fig. 5 Mean particle size of the fabricated nanoparticles as a functionof irradiation time.

Fig. 6 Long-time variation of the UV–vis. absorption spectra of the colloidal solutions of Au NPs prepared by laser-induced nucleation for different
irradiation times of (a) 9, (b) 14, (c) 20, and (d) 60 min. Insets: photographs of the colloid solution (i) just after irradiation, (ii) 1 day later, and (iii) 2
weeks later.

113

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118

photographs of the solutions. For the irradiation times of
9 and 14 min, the LSPR peak became predominant 1 day
after irradiation. At this irradiation time, the reduction ofauric ions was not completed, and the Au NPs grew via aself-catalytic effect. The particles were aggregated 2 weeks
later, as shown in Figs. 6(a) and (b). For the irradiation
time of 20 min, the increase in the LSPR peak 1 day after
preparation became small likely because the reduction ofauric ions was almost competed, and further growth of theparticles was inhibited.
In contrast, the UV–visible absorption spectra of thecolloidal solution prepared with 60 min of irradiation time
showed no significant change even after 2 weeks, as shownin Fig. 6(d). This stable dispersion state was maintained
for at least several months. The zeta potential of the Au
NPs in suspension was approximately –30 mV, meaningthat the particle surface was negatively charged. A similar
result was been reported for Au NPs fabricated by PLAL
(Sylvestre et al., 2004), where the colloidal dispersion
stability of the Au NPs was attributed to the partial surface
oxidation and the transfer of negative charge from thechloride ions during the intense laser ablation of the bulk
Au in water. Additionally, fragmentation by the prolonged
irradiation, which effectively reduced the particle size,
should have contributed to the dispersion stability throughthe increase of the specific surface area of the NPs.

5. Structure of multi-elemental alloy
nanoparticles and their catalytic activity
Laser-induced nucleation can produce not only noble
metal nanoparticles (Nakamura et al., 2008; 2011) but also
alloy nanoparticles of noble metals from mixed aqueous
solutions with different noble metal ions, e.g., gold (Au)and silver (Ag) (Herbani et al., 2011). The compositional
distribution in the synthesized nanoparticles was uniform,
meaning that the nanoparticles were a solid solution(Herbani et al., 2012; Sarker et al., 2013). Most noble
metals (rhodium (Rh), palladium (Pd), Ag, iridium (Ir),
platinum (Pt), and Au) crystallize in a face-centered cubic(fcc) structure, except for ruthenium (Ru) and osmium(Os), which have a hexagonal closely packed (hcp) structure. Accordingly, their alloys can be solid solutions, butsome alloys are phase-separated. For example, the Au–Pt
alloy exhibits phase separation in a wide composition range
in bulk, as shown by its binary phase diagram. Despite thisphysical inclination in the bulk, laser-induced nucleation
can synthesize all-proportional solid–solution Au–Pt alloy
NPs from a mixed ion solution of chloroauric acid andchloroplatinic acid (Nakamura et al., 2012). The solid–
solution of the Au–Pt alloy is considered to be a metastablestate. Accordingly, it is presumed that the synthesis ofsolid–solution Au–Pt NPs is possible not by the conven-114

tional thermal equilibrium process but by laser-induced nucleation, which accompanies rapid cooling of the reaction
field. The synthesis of all-proportional solid–solution alloy
NPs has been achieved for other combinations of noble
metals (Sarker et al., 2015; Nakamura and Sato, 2015). Not
only binary but also ternary alloy NPs were synthesized(Sarker et al., 2014).
Because the properties of solid–solution alloy NPs of noble metals are not well known, it is attractive to determine
the unknown properties of those NPs. Below, we focus on
Rh–Pd–Pt NPs, which have been utilized as a three-way
catalyst for emission gas purification of automobiles, andshow the catalytic activity of solid–solution Rh–Pd–Pt
alloy NPs produced by laser-induced nucleation (Sarker etal., 2019).
A mixed aqueous solution of rhodium (III) chloride
trihydrate, palladium (II) chloride, and hydrogen hexachloroplatinate (IV) hexahydrate at a concentration of
2.5 × 10–4 mol/L was prepared. In this case, citric acid at
10 wt% was added to improve the particle size dispersion
for improved evaluation of the catalytic activity. The prepared solution was irradiated by laser pulses at a repetition
rate of 100 Hz for 30 min, which was much longer than
the time required for the reduction of noble metal ions inthe solution. The structure and composition of the NPs
obtained were analyzed by a scanning TEM with energy
dispersive X-ray spectroscopy (STEM–EDS).
The STEM images and elemental mappings of thefabricated NPs are shown in Fig. 7(a). Three elements distributed uniformly in the entire particle. The EDS analysis
revealed that the elemental composition was Rh29Pd35Pt36,
which was close to the initial mixing ratio of metallic ionsof Rh:Pd:Pt = 1:1:1 in the mixed aqueous solution. Theseobservations suggested that solid–solution alloy NPs wereformed and their composition reflected the initial mixing
ratios of noble metal ions in the aqueous solution.
The catalytic activity of the Rh–Pd–Pt alloy NPs wasevaluated through oxidation of carbon monoxide (CO).
The conversion ratio from CO to carbon dioxide (CO2)
was measured in a reaction chamber with 1 % CO and
0.5 % O2 in helium gas for pure metal and their alloy NPs
supported on γ–alumina particles. Fig. 8 shows the COconversion ratios as a function of reaction temperature forthe pure metal and their binary and ternary alloy NPs prepared by laser-induced nucleation. Among the pure metal
NPs, Rh was most active at low temperature. In contrast,
the catalytic activity of the Pt NPs was low owing to thewell-known surface poising and the adsorption of CO on
the particle surface.
The catalytic activities of binary and ternary alloy NPs
were improved compared with the Pt NPs but almost thesame as those of Rh and the Pd NPs. It has been reported
that Rh–Pt (Alayoglu and Eichhorn., 2008) and Pd–Ru(Kusada et al., 2014) alloy NPs show higher activity than

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118

Fig. 7 STEM–EDS mappings for (a) the Rh–Pd–Pt alloy NPs prepared by laser-induced nucleation from a mixed ion solution and (b) the Rh–Pd–Pt
alloy NPs after heat treatment.

Fig. 8 Catalytic CO conversion of the Rh, Pd, Pt, Rh–Pd, Rh–Pt, Rh–Pt,
and Rh–Pd–Pt NPs as a function of temperature. Reprinted from Ref.
(Sarker et al., 2019) under the terms of the CC-BY-NC 3.0 license. Copyright: (2019) The Authors, published by The Royal Society of Chemistry.

Fig. 9 Catalytic CO conversion of the alloy NPs before and after heat
treatment. Reprinted from Ref. (Sarker et al., 2019) under the terms of
the CC-BY-NC 3.0 license. Copyright: (2019) The Authors, published by
The Royal Society of Chemistry.

their pure metal NPs. This catalytic enhancement of the alloy NPs was attributed to the electron displacement owing
to the core–shell structure in the Rh–Pt NPs and the defects
due to the mismatch of crystal structures of bulk Rh (fcc)
and Ru (hcp) for Rh–Ru NPs. In contrast, the homogeneous
structure of the alloy NPs prepared by laser-induced nucleation could not contribute to the activity. This encouraged
us to compare homogeneous NPs with inhomogeneous
solid–solution alloy NPs, which can be formed by heat
treatment of solid–solution alloy NPs.
The STEM images of the heat-treated NPs and theelemental mappings are shown in Fig. 7(b). The elemental components, especially Pt, were inhomogeneously
distributed in the NPs after heat treatment compared to theas-prepared NPs, as shown in Fig. 7(a). Fig. 9 shows thecatalytic activities of the NPs with heat treatment. Clearly,
the catalytic activity of the heat-treated NPs increased at
low temperature as expected. This result explicitly verified
that the enhanced catalytic activities of the alloy NPs in thepreceding studies were intimately related to the inhomogeneity of the elemental distribution inside the NPs.
This method was able to form solid–solution alloy NPs
simply by mixing ion solutions of different noble metals.
In addition to binary and ternary alloy NPs, the formationof quaternary and quinary alloy NPs was achieved bylaser-induced nucleation. Fig. 10(a) shows a STEM–
HAADF image of the NPs fabricated in the mixed metal
ion solutions of Rh, Pd, Ir, Au, and Pt. Corresponding elemental maps by EDS are depicted in Figs. 10(b)–(f). Everyelement was uniformly distributed inside the particles, suggesting that quinary solid–solution alloy NPs were formed.
Observations using high-resolution transmittance electron
microscopy revealed that the NPs were polycrystalline. According to the definition (Miracle, 2019), the nanoparticles
synthesized here were of a high-entropy alloy because they
contained five elements. Because the crystalline structuresof Rh, Pd, Ir, Au, and Pt are unexceptionally fcc, as mentioned before, it is easy to assume that their solid–solution

115

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118

Fig. 10 (a) STEM–HAADF image of nanoparticles formed by laser-induced nucleation using the mixed metal ion solutions of Rh, Pd, Ir, Au and Pt.
(b)–(f) corresponding elemental EDS maps.

alloy NPs can be formed. However, their binary phase
diagrams suggest that six out of ten combinations are immiscible. Miscible combinations are limited to the Au–Pd,
Ir–Rh, Pd–Pt, and Pt–Rh systems, indicating the difficulties
involved in the formation of their solid–solution alloy NPs.
Thus, the non-thermal equilibrium process achieved by thelaser-induced nucleation may be a promising tool for theformation of high-entropy alloy NPs.

Nomenclature
EDS

Energy dispersive X-ray spectroscopy

fcc

face-centered cubic

HAADF

High angle annular dark fieldhcp

hexagonal close-packed

LSPR

Localized surface plasmon resonanceNP

Nanoparticle

6. Conclusion

PLAL

Pulsed laser ablation in liquid

STEM

Scanning transmission electron microscopy

We demonstrated the nanoparticle formation of noble
metals and their alloys in the highly intense laser field generated by tightly focusing ultrashort optical pulses in aqueous solution. This “laser-induced nucleation” is free from a
reducing agent because the highly intense laser irradiationof the aqueous solution was able to produce solvatedelectrons and hydrogen radials directly from water molecules, which act as strong reducing agents for metal ions.
Prolonged irradiation of chloroauric acid solution resulted
in the formation of an Au colloidal solution with a stabledispersive state over several months. Owing to the ultrafast
and non-thermal nature of the intense laser process, solid–
solution alloy NPs were formed even though the elements
were immiscible in the bulk. The solid–solution alloy NPs
with a homogeneous elemental distribution contributed tothe superior catalytic activity of the alloy NPs, which wereformed by a conventional chemical process and had an
inhomogeneous elemental distribution.
With the progress of laser technology, the intense laser
field will offer an extremely non-linear, non-equilibrium,
high-temperature and high-pressure field that has neverexisted on Earth. We are expecting that this unprecedented
state opens the door to ultimate technologies in both science and industry.

TEM

Transmission electron microscopykrate constant of reaction (dm3 mol–1 s –1)

λwavelength of light (m)VSHEredox potential for standard hydrogen electrode (V)116

References
Alayoglu S., Eichhorn B., Rh–Pt bimetallic catalysts: synthesis,characterization, and catalysis of core–shell, alloy, andmonometallic nanoparticles, Journal of the American
Chemical Society, 130 (2008) 17479–17486. DOI: 10.1021/
ja8061425
Castillejo M., Couris S., Koudoumas E., Martín M., Ionization andfragmentation of aromatic and single-bonded hydrocarbons
with 50 fs laser pulses at 800 nm, Chemical Physics Letters,
308 (1999) 373. DOI: 10.1016/S0009-2614(99)00636-3
Cornaggia C., Carbon geometry of C3H3+ and C3H4+ molecularions probed by laser-induced Coulomb explosion, PhysicalReview A, 52 (1995) R4328. DOI: 10.1103/physreva.52.
r4328
Cornaggia C., Schmidt M., Normand D., Laser-induced nuclear
motions in the Coulomb explosion of C2H2+ ions, PhysicalReview A, 51 (1995) 1431. DOI: 10.1103/physreva.51.1431
Herbani Y., Nakamura T., Sato S., Synthesis of near-monodispersed Au-Ag nanoalloys by high intensity laser irradiation

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118

of metal ions in hexane, The Journal of Physical ChemistryC, 115 (2011) 21592. DOI: 10.1021/jp205547t
Herbani Y., Nakamura T., Sato S., Synthesis of platinum-based
binary and ternary alloy nanoparticles in an intense laser
field, Journal of Colloid and Interface Science, 375 (2012)
78. DOI: 10.1016/j.jcis.2012.02.030
Kusada K., Kobayashi H., Ikeda R., Kubota Y., Takata M., Toh S.,
Yamamoto T., Matsumura S., Sumi N., Sato K., Nagaoka K.,
Kitagawa H., Solid solution alloy nanoparticles of immiscible
Pd and Ru elements neighboring on Rh: changeover of thethermodynamic behavior for hydrogen storage and enhanced
CO-oxidizing ability, Journal of the American Chemical
Society, 136 (2014) 1864. DOI: 10.1021/ja409464g
Miracle D.B., High entropy alloys as a bold step forward in alloy
development, Nature Communications, 10 (2019) 1805.
DOI: 10.1038/s41467-019-09700-1
Muttaqin, Nakamura T., Sato S., Synthesis of gold nanoparticle
colloids by highly intense laser irradiation of aqueous
solution by flow system, Applied Physics A, 120 (2015) 881.
DOI: 10.1007/s00339-015-9314-x
Nakamura T., Herbani Y., Sato S., Fabrication of solid-solution
gold–platinum nanoparticles with controllable compositions
by high-intensity laser irradiation of solution, Journal of
Nanoparticle Research, 14 (2012) 785. DOI: 10.1007/s11051012-0785-9
Nakamura T., Herbani Y., Ursescu D., Banici R., Dabu R.V.,
Sato S., Spectroscopic study of gold nanoparticle formation
through high intensity laser irradiation of solution, AIP
Advances, 3 (2013) 082101. DOI: 10.1063/1.4817827
Nakamura T., Magara H., Herbani Y., Sato S., Fabrication ofsilver nanoparticles by highly intense laser irradiation of
aqueous solution, Applied Physics A, 104 (2011) 1021. DOI:
10.1007/s00339-011-6499-5
Nakamura T., Mochidzuki Y., Sato S., Fabrication of gold
nanoparticles in intense optical field by femtosecond
laser irradiation of aqueous solution, Journal of Materials
Research, 23 (2008) 968. DOI: 10.1557/jmr.2008.0115
Nakamura T., Sato S., Green and facile synthesis of Pd–Pt alloy
nanoparticles by laser irradiation of aqueous solution, Journalof Nanoscience and Nanotechnology, 15 1 (2015) 426. DOI:
10.1166/jnn.2015.8846
Pearce S.R.J., Henleya S.J., Claeyssensa F., Maya P.W., Hallamb
K.R., Smitha J.A., Rossera, K.N., Production of nanocrystal-line diamond by laser ablation at the solid liquid interface,
Diamond Related Materials, 13 (2004) 661. DOI: 10.1016/j.
diamond.2003.08.027
Sarker M.S.I., Nakamura T., Herbani Y., Sato S., Fabrication of
Rh based solid-solution bimetallic alloy nanoparticles withfully-tunable composition through femtosecond laser irradiation in aqueous solution, Applied Physics A, 110 (2013) 145.
DOI: 10.1007/s00339-012-7467-4
Sarker M.S.I., Nakamura T., Kameoka S., Hayasaka Y., Yin
S., Sato S., Enhanced catalytic activity of inhomogeneous
Rh-based solid-solution alloy nanoparticles, RSC Advances,
9 (2019) 38882. DOI: 10.1039/c9ra06167c
Sarker M.S.I., Nakamura T., Sato S., Composition-controlled
ternary Rh–Pd–Pt solid-solution alloy nanoparticles bylaser irradiation of mixed solution of metallic ion, Journalof Material Research, 29 7 (2014) 856. DOI: 10.1557/jmr.
2014.62
Sarker M.S.I., Nakamura T., Sato S., All-proportional solid-solution Rh–Pd–Pt alloy nanoparticles by femtosecond laser
irradiation of aqueous solution with surfactant, Journalof Nanoparticle Research, 17 (2015) 259. DOI: 10.1007/
s11051-015-3056-8
Sylvestre J-.P., Poulin S., Kabashin A.V., Sacher E., Meunier
M., Luong J.H.T., Surface chemistry of gold nanoparticles
produced by laser ablation in aqueous media, The Journalof Physical Chemistry B, 108 (2004) 16864. DOI: 10.1021/
jp047134+
Talebpour A., Bandrauk A.D., Vijayalakshmi K., Chin S.L.,
Dissociative ionization of benzene in intense ultra-fastlaser pulses, Journal of Physics B: Atomic, Molecular andOptical Physics, 33 (2000) 4615. DOI: 10.1088/09534075/33/21/307
Thomsen C.L., Madsen D., Keiding S.R., Thøgersen J.,
Christiansen O., Two-photon dissociation and ionization ofliquid water studied by femtosecond transient absorption
spectroscopy, The Journal of Chemical Physics, 110 (1999)
3453. DOI: 10.1063/1.478212
Wang J.B., Zhang C.Y., Zhong X.L., Yang G.W., Cubic andhexagonal structures of diamond nanocrystals formed
upon pulsed laser induced liquid–solid interfacial reaction,
Chemical Physics Letters, 361 (2002) 86. DOI: 10.1016/
S0009-2614(02)00871-0

117

Takahiro Nakamura et al. / KONA Powder and Particle Journal No. 39 (2022) 110–118

Authors’ Short Biographies
Takahiro Nakamura
Associate Professor T. Nakamura received his Bachelor’s degree in Engineering in 1999, Master’s
degree in Engineering in 2001, and Doctorate in Engineering in 2004 from the Tohoku University.
He started his academic career with laser materials processing. He worked as an Assistant Professor(from 2005 to 2015) and as an Associate Professor (from 2015 to now) in Institute of Multidisciplinary Research for Advanced Materials, Tohoku University. His research topics cover broad area
in laser materials processing.

Yuki Yamazaki
Yuki Yamazaki received his Bachelor’s and Master’s degrees in Engineering from the Tohoku
University in 2016 and 2018, respectively. He is now working in IBM Japan Ltd.

Shunichi Sato
Professor S. Sato received his Bachelor’s degree in Science in 1981, Master’s degree in Engineering in 1983, and Doctorate in Engineering in 1992 from the Tohoku University. He started hisacademic career with laser application to bioscience and medicine, and expanded his interest to
materials science. He became Professor of Institute of Multidisciplinary Research for Advanced
Materials, Tohoku University in 2003. He has believed in the extreme potential of light and is trying
to explore its hidden peculiarities.

118

KONA Powder and Particle Journal No. 39 (2022) 119–129/https://doi.org/10.14356/kona.2022003

Review Paper

Influence of Anions and Cations on the Formation ofIron Oxide Nanoparticles in Aqueous Media †Hidekazu Tanaka
Department of Chemistry, Graduate School of Natural Science and Technology, Shimane University, Japan

Abstract
Recently, various types of functionalized metal oxide nanoparticles have been used for many applications becauseof their unique chemical and physical properties. To synthesize metal oxide nanoparticles, liquid-phase synthesis
techniques have been developed. The production process of metal oxide nanoparticles in aqueous media is
extremely complex because the formation, crystal structure, crystallinity, chemical composition, and morphologyof the particles are considerably dependent on the preparation conditions (e.g., anion and cation concentrations andspecies, additives, solution pH, reaction temperature, and reaction time). Accordingly, clarifying these effects isfundamental to accurately understand the formation mechanism of metal oxide nanoparticles to further develop
new functionalized nanoparticles. In this review, the influence of anions (Cl–, SO42–, and NO3–) and cations (Ni2+,
Cu 2+, and Cr3+) on the formation and structure of iron oxide nanoparticles in aqueous media is described.
Keywords: metal oxide nanoparticle, liquid-synthesis, particle formation, iron oxide particle, anion, cation

1. Introduction
In industries, various types of functionalized metal oxide
nanoparticles, such as iron oxide, silica gel, alumina, zincoxide, and titania, have been developed and used for many
applications (e.g., catalysis, adsorbent, biomedicine, magnetic data storage, agriculture, fuel cell, pigment, and sensor material) because of their unique chemical and physicalproperties (Iler R.K., 1979; Cornell R.M. and SchwertmannU., 1996; 2000; Fujishima A. et al., 1999; Rodríguez
J.A. and Fernández-García M., 2006; Chavali M.S. and
Nikolova M.P., 2019; Korotcenkov G. et al., 2019). To
further improve the particle properties, controlling theparticle shape and size, monodispersity, and crystallinity isnecessary. However, in general, the synthesis of high-quality nanoparticles, such as monodisperse single-crystal
nanoparticles, is considerably difficult (Matijević E., 1985;
Sugimoto T., 1987; 2001; Pelizzetti E., 2011). Metal oxide
nanoparticles can be produced using solid, liquid, and gasphase synthesis techniques. Among these, the liquid-phase
synthesis affords several advantages (Gutch A. et al., 2004;
Feng J. et al., 2015; Karatutlu A. et al., 2018): (1) low-cost
particle production can be performed; (2) surface active
nanoparticles can be obtained; (3) particles from a homoge-†

Received 28 July 2020; Accepted 1 October 2020
J-STAGE Advance published online 28 November 2020
Add: 1060 Nishikawatsu, Matsue, Shimane 690-8504, Japan
E-mail: hidekazu@riko.shimane-u.ac.jp
TEL/FAX: +81-852-32-6823

neous solution can be prepared; (4) preparation conditions(e.g., reaction temperature and time, anion and cation
concentrations, additives, solution pH, and raw materials)
can be easily controlled; (5) particle shape and size can be
regulated by the abovementioned preparation conditions
and method. Based on these benefits, various liquid-phase
synthesis techniques for the production of metal oxide
nanoparticles have been developed, and approximately
45 % of functionalized nanoparticles are synthesized
through these methods in the industry (Charitidis C.A. etal., 2014). The liquid-phase synthesis can be classified into
two approaches: “Top-down approach” and “Bottom-up
approach.” In the “Top-down approach,” nanoparticles aresynthesized by etching the macro-sized or micro-sized bulk
materials in aqueous media (e.g., wet milling, lithography,
laser ablation, and chemical etching). In the “Bottom-up
approach,” nanoparticles are prepared by assembling small
blocks, such as atoms and molecules, in aqueous media(e.g., sol-gel, precipitation, pyrolysis, and chemical reduction methods).
The formation and growth processes of metal oxide
nanoparticles in aqueous media have been investigated(Ostwald W.Z., 1900; LaMer V.K. and Dinegar R.H.,
1950; Reiss H., 1951; LaMer V.K., 1952; Feitknecht W.,
1959; Lifshitz I.M. and Slyozov V.V., 1961; Hsu P.M.,
1972; Hsu P.M. and Ragone S.E., 1972; Misawa T. et al.,
1974; Dousma J. et al., 1976; 1978; 1979; Murphy P.J. et al.,
1976; Blesa M.A. and Matijević E., 1989; Cornell R.M. and
Schwertmann U., 1996; 2000; Ishikawa T., 1997; Schultz
M. et al., 1999; Jolivet J-P., 2000; Kandori K., 2002; Tamura

Copyright © 2022 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

119

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

Fig. 1 Formation and growth processes of iron oxide particles from aqueous Fe3+ solution.

H., 2008; Thanh N.T.K. et al., 2014; Plote J., 2015). Fig. 1
shows the formation and growth processes of iron oxide
nanoparticles from aqueous Fe3+ solution.
Fe3+ + 6H2O → Fe(H2O)63+(1)

The Fe(H2O)63+ ions are hydrolyzed to generate Fe(OH)3+n(H2O)6–n ions (n = 1–6) via protolysis reaction (2).
Fe(H2O)63+ + nH2O → Fe(OH)n(H2O)6–n3+ + nH3O+ (2)Further, the Fe(OH)n(H2O)6–n3+ ions are condensed via
oxolation reaction (3).
>Fe–OH + HO–Fe< → >Fe–O–Fe< + H2O(3)Then, the >Fe–O–Fe< groups are hydrolyzed via olation
reaction (4).
>Fe–O–Fe< + H3O+ → >Fe–OH–Fe< + H2O(4)

Reactions (1)–(4) continuously proceed to yield multinuclear Fe3+ complex ions. These ions further grow to
produce an embryo through ion collisions in which thereaction continuously breaks down and reforms during
the reversible reaction stage. When the embryo exceeds
a certain critical size, it becomes a nucleus, which isconsiderably more stable. The generated nucleus is further
grown to form fine primary particles, which transform into
crystals via two possible routes: “aggregation mechanism”
and “ion diffusion growth mechanism”. In the former
route, aggregates are generated by the agglomeration ofprimary particles. During aging, the primary particles in theaggregates solidify into crystalline particles. In the lattermechanism, solute ions are diffused and deposited on the
primary particles to form crystalline particles. The growth
process of α-FeOOH particles is depicted in Fig. 2. In this120case, the primary particles composed of fine crystals are
regularly combined by –O– and –OH– bonds to crystallize
as α-FeOOH. Accordingly, the formation process of metaloxide nanoparticles is considerably complex and is not
fully understood. The formation, crystal structure, crystallinity, chemical composition, and particle morphology are
extremely dependent on the preparation conditions, suchas anion and cation concentrations and species, additive,
solution pH, and reaction temperature and time. Amongthese, anion and cation were observed to markedly affectthe formation and structure of iron oxides. The phase stability of γ-FeOOH was lowered by Cl– and SO42– (Sudakar
S. et al., 2003). Moreover, the increase of [SO42–]/[Cl–]ratio in the aqueous Fe2(SO4)3–FeCl3 solution accelerated
the α-FeOOH formation (Oh S.J. et al., 2002). Further, theaddition of SO42– and SO32– significantly impeded the formation and crystallization of β-FeOOH (Ishikawa T. et al.,2005; Kamimura T. et al., 2005; Tanaka H. et al., 2016a; b).
The crystallization and growth of α-FeOOH and β-FeOOH
particles were inhibited by adding Cu2+, Ni2+, Cr3+, andTi4+ (Inouye K. et al., 1968; 1972; Ishikawa T. et al., 2000;
2001; 2002; 2003; 2009; Nakayama T. et al., 2005; Tanaka
H. et al., 2013a; b). Accordingly, elucidating these effects

Fig. 2 Growth process of α-FeOOH crystal.

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

is fundamental to accurately understand the formation
mechanism of metal oxide nanoparticles.
In this review, the influence of anions and cations on
the formation and structure of iron oxide nanoparticles is
described based on our research. The iron oxide nanoparticles were synthesized in the presence of anions (Cl–, SO42–,
and NO3–) and cations (Ni2+, Cu2+, and Cr3+) (Tanaka H.
et al., 2013a; b; 2015; 2016a; 2018). The results can aid
in developing new functionalized nanomaterials using theliquid-phase synthesis technique.

2. Influence of anions on formation of ironoxide particles
The influence of anions on the formation of iron oxide
nanoparticles was examined by synthesizing the particles
from Fe3+ solutions containing Cl–, NO3–, and SO42–. A
mixture of aqueous FeCl3, Fe2(SO4)3, and Fe(NO3)3 solutions were aged at 50 °C for 48 h. Prior to aging, the solution pH was approximately 2. The generated precipitates
were filtered out, thoroughly washed with deionized-distilled water, and air-dried at 50 °C.
The amount of products formed is shown in Fig. 3.
This amount is increased by incrementing the quantity of FeCl3 added to the FeCl3–Fe(NO3)3 system. In
the Fe(NO3)3–Fe2(SO4)3, Fe2(SO4)3–FeCl3, and FeCl3–
Fe(NO3)3–Fe2(SO4)3 systems, increasing the quantity ofFe2(SO4)3 addition reduces the amount of formed products.
The amount of these products eventually become zero
when higher amounts of SO42– are added. These results
indicate that the formation of iron oxides is inhibited by theaddition of SO42–.
The major formation species of iron oxides is shown in
Fig. 4. Iron-oxyhydroxysulfate (Fe8O8(OH)6(SO4)·nH2O:
Schwertmannite) is formed by adding SO42–, however,
the addition of a large amount of SO42– prevents the generation of iron oxides. In contrast, β-FeOOH is mainly
yielded in the FeCl3–Fe(NO3)3 system, and α-FeOOH isonly generated in the Fe(NO3)3 system, indicating that the
FeCl3–Fe(NO3)3 system favors the formation of β-FeOOH

Fig. 3 Plots of amount of products formed in FeCl3–Fe(NO3)3–Fe2(SO4)3 system. Adapted with permission from Ref. (Tanaka H. et al.,2013a). Copyright: (2013) Elsevier B.V.

rather than α-FeOOH.
Transmission electron microscopy (TEM) images ofthe formed particles are shown in Fig. 5. The spherical
α-FeOOH particles with an average diameter of 358 nm are
generated in the Fe(NO3)3 system. In the FeCl3–Fe(NO3)3
system, the spherical α-FeOOH particles virtually diminish, and rod-shaped β-FeOOH particles are observed. Further, as the amount of added Cl– increases, the mean length
and width of β-FeOOH particles increase from 677 nm to
1.48 μm and from 130 to 238 nm, respectively. Hence, theincorporation of NO3– slightly suppresses the growth of
β-FeOOH particles. In the Fe(NO3)3–Fe2(SO4)3 system,
needle-like Schwertmannite particles with a mean length
and width of approximately 260 and 15 nm, respectively,
are mainly formed. By adding NO3–, the Schwertmannite
particles disappear, and irregular-shaped α-FeOOH particles with an average size of 68 nm are generated. In the
Fe2(SO4)3–FeCl3 system, increasing the amount of added
SO42– decreases the particle size of β-FeOOH and forms
Schwertmannite particles (mean length = 136 nm, mean
width = 49 nm). In the FeCl3–Fe(NO3)3–Fe2(SO4)3 system,
due to the Schwertmannite, only needle-like particles
with a length and width of approximately 310 and 40 nm
are recognizable. These facts reveal that the presence ofSO42– in the aforementioned system remarkably precludes
the formation of α-FeOOH and β-FeOOH particles andproduces needle-like Schwertmannite particles. Note that ahigher SO42– content in the solution inhibits the formationof particles. Thus, the effect of SO42– on the formation ofiron oxide particles is greater than that of Cl– and NO3–.
These results indicate that anions, such as SO42–, Cl–,and NO3–, affect the formation, crystallization, and particle growth of iron oxides, and the effect is in the order
SO42– >> Cl– > NO3–. The affinity of anions to Fe3+ canbe evaluated through the stability constant (log K) of Fe3+complexes with anions. The stability constant of Fe3+complexes with SO42– is 4.1 and is considerably larger thanthat with NO3– (1.0) and Cl– (0.6), indicating the strong

Fig. 4 Major iron oxides formed in FeCl3–Fe(NO3)3–Fe2(SO4)3 system.
( ) α-FeOOH, ( ) β-FeOOH, ( ) Schwertmannite, ( ) no precipitates. Adapted with permission from Ref. (Tanaka H. et al., 2013a).
Copyright: (2013) Elsevier B.V.

121

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

Fig. 5 TEM images of the particles formed in FeCl3–Fe(NO3)3–Fe2(SO4)3 system. Adapted with permission from Ref. (Tanaka H. et al., 2013a).
Copyright: (2013) Elsevier B.V.

coordination of SO42– with Fe3+ compared with NO3– andCl– (Sillen L.G. and Martell A.E., 1964). Hence, theSO42–-containing aqua Fe3+ complex [Fe(SO4)m(H2O)6–m]3+
is formed in the Fe(NO3)3–Fe2(SO4)3, Fe2(SO4)3–FeCl3
and FeCl3–Fe(NO3)3–Fe2(SO4)3 systems via hydrolysis
reaction (5).
Fe3+ + mSO42– + (6–m)H2O → [Fe(SO4)m(H2O)6–m]3+(5)Moreover, [Fe(SO4)m(H2O)6–m]3+ is hydrolyzed via protolysis reaction (6).
[Fe(SO4)m(H2O)6–m]3+ + nH2O
→ [Fe(OH)n(SO4)m(H2O)6–n–m]3+(6)

Consequently, when a small amount of SO42– is added,
the major product becomes Schwertmannite containing
SO42–. Upon increasing the amount of added SO42–, theSO42– content in the [Fe(SO4)m(H2O)6–m]3+ ions increases
and the number of active >Fe–OH groups is reduced,
resulting in the suppression of olation reaction (3). Accordingly, no precipitates are generated at higher SO42– contents
in the solution. In contrast, β-FeOOH is mainly producedin the FeCl3–Fe(NO3)3 system. The stability constantsof Fe3+ complexes with Cl– and NO3– are considerably
lower than that with SO42–. Hence, the addition of Cl– andNO3– prevents the progress of reactions (1)–(4), leading
to the formation of the amorphous precursor of α-FeOOH
and β-FeOOH particles during aging. It has been established that the isoelectric point (iep) of iron oxides andoxyhydroxides, such as α-FeOOH, β-FeOOH, γ-FeOOH,
Fe3O4, and α-Fe2O3, is a neutral pH, and aforementioned

122

materials have a positive surface charge in the acidic
solution (Cornell R.M. and Schwertmann U., 1996; 2000).
Moreover, the ionization energy of NO3– is larger thanthat of Cl– (Lang P.F. and Smith B.C., 2003). Therefore,
the added Cl– preferentially adsorbs on the surface of theamorphous precursor to form Cl–-containing β-FeOOH
particles. However, the decrease in the amount of added
Cl– reduces the size of β-FeOOH particles, indicating theinhibition of their growth as a result of the adsorption of
NO3– on the precursors.
To clarify the influence of anion and solution pH on theformation of iron oxide nanoparticles, the particles weresynthesized from the FeCl3–Fe2(SO4)3–Fe(NO3)3 system
at different OH–/3Fe3+ molar ratios. The OH–/3Fe3+ ratio
ranges 0–1.5 through the addition of NaOH solutions.
The pH titration curves of aqueous FeCl3, Fe2(SO4)3, andFe(NO3)3 solutions are shown in Fig. 6. All the curves arepractically identical, indicating that the solution pH is independent of the anions. At OH–/3Fe3+ = 0–1.0, the solution
pH becomes practically constant (i.e., 2–3) because of thereaction of Fe3+ with the added OH– to precipitate Fe(OH)3.
At OH–/3Fe3+ > 1.0, the pH level of the solution suddenly
increases because all the Fe3+ transforms into Fe(OH)3.
The major products synthesized at OH–/3Fe3+ = 0–1.5 areshown in Fig. 7. At OH–/3Fe3+ = 0.5, the hydrated ironoxide Fe2O3•nH2O particles are mainly produced in the
FeCl3–Fe(NO3)3 system. In contrast, the Fe2(SO4)3–FeCl3,
Fe(NO3)3–Fe2(SO4)3, and FeCl3–Fe2(SO4)3–Fe(NO3)3 systems enhance the α-FeOOH formation. This is causedby the transformation of Schwertmannite during aging
because this material is among the precursors of α-FeOOH(Cornell R.M. and Schwertmann U., 1996; 2000; TanakaHidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

iron oxide nanoparticles.

3. Influence of cations on formation of ironoxide nanoparticles

Fig. 6 pH titration curves of aqueous FeCl3, Fe(NO3)3 and Fe2(SO4)3
solutions. Adapted with permission from Ref. (Tanaka H., 2015). Copyright: (2015) The Society of Powder Technology, Japan.

H. et al., 2013a; 2015; 2016a; Muguruma et al., 2015).
The major products at OH–/3Fe3+ = 1.0 and 1.5 (pH levels
are approximately 7 and 14, respectively) are ferrihydrites(Fe5HO8·4H2O) and α-FeOOH, respectively. The foregoing means that raising the solution pH before aging lowers
the influence of anions on the structure and composition of

The influence of cations on the formation of iron oxide
nanoparticles was examined by synthesizing the α-FeOOH
particles with Ni2+, Cu2+, and Cr3+. Metal salts, such as
NiSO4, CuSO4, or Cr(NO3)3, and FeSO4 were dissolvedin O2-free deionized-distilled water, of which the metal/Fe
atomic ratio of the solution was 0–0.1. The aqueous NaOH
solution was added to the solution until the OH–/2Fe2+
ratio reached 0.05. The generated suspension was aged inbubbling air at 50 °C for 24 h. The resulting precipitate
was filtered out, washed with deionized distilled water, andair-dried at 50 °C.
X-ray diffraction (XRD) patterns of the products synthesized with Ni2+, Cu2+, and Cr3+ are shown in Fig. 8.
As shown in Fig. 8(A), with the addition of Ni2+, theintensity and position of α-FeOOH peaks remain virtuallyunchanged. As shown in Fig. 8(B), with Cu2+ addition, the
α-FeOOH peaks are weakened and broadened by increasing the Cu/Fe ratio. A similar tendency is observed withthe addition of Cr3+ as shown in Fig. 8(C). Besides, the
α-FeOOH peaks vanish at Cr/Fe ≥ 0.04 and broad peaks
ascribed to Schwertmannite are developed. Furthermore,

Fig. 7 Major product of the iron oxides formed at OH–/3Fe3+ = 0–1.5. ( ) α-FeOOH, ( ) β-FeOOH, ( ) Schwertmannite, ( ) no precipitates, ( )Fe2O3·nH 2O, ( ) Ferrihydrite. Adapted with permission from Ref. (Tanaka H., 2015). Copyright: (2015) The Society of Powder Technology, Japan.

123

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

Fig. 8 XRD patterns of the products synthesized in the presence of (A) Ni2+, (B) Cu 2+ and (C) Cr3+. metal/Fe: (a) 0, (b) 0.005, (c) 0.01, (d) 0.02, (e) 0.04,(f) 0.06, (g) 0.08, (h) 0.1. Adapted with permission from Ref. (Tanaka H. et al., 2018). Copyright: (2018) Elsevier B.V.

sharp peaks due to Natrojarosite NaFe3(SO4)2(OH)6 appear
at Cr/Fe ≥ 0.08. Hence, the addition of Cu2+ and Cr3+
inhibits the crystallization of α-FeOOH and a considerable amount of added Cr3+ impedes the transformationof Schwertmannite into α-FeOOH. The crystallite sizeof α-FeOOH, which is calculated using the Scherrer
equation, is plotted against the metal/Fe ratio in Fig. 9.
The crystallite size is 24.1 nm when metal/Fe = 0 and it
decreases as the Cu/Fe ratio increases up to 0.02, indicatingthat the crystallization of α-FeOOH is inhibited. The Cr3+
addition also reduces the crystallite size and its effect isslightly higher than that of Cu2+ addition. Nonetheless, noconsiderable influence is observed by Ni2+ addition. These
results indicate that the addition of Cu2+ and Cr3+ inhibits
the crystallization of α-FeOOH and the effect is in the order
Cr3+ > Cu2+ >> Ni2+.
In Fig. 10 is plotted the metal/Fe atomic ratio of theparticles estimated from the Ni, Cu, Cr, and Fe contents
against the metal/Fe ratio of the solution. It is clearly observed that the Cr/Fe ratio of the particles is considerablylarger than that of the solution. However, the Cu/Fe and Ni/

124

Fig. 9 Crystallite size of α-FeOOH vs. atomic ratio metal/Fe. Adaptedwith permission from Ref. (Tanaka H. et al., 2018). Copyright: (2018)
Elsevier B.V.

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

Fig. 10 Plots of atomic ratio metal/Fe in particles against atomic ratio
metal/Fe in solution. Adapted with permission from Ref. (Tanaka H. etal., 2018). Copyright: (2018) Elsevier B.V.

Fe ratios of the particles are lower than those of the starting
solutions. These indicate that the added Cr3+ is more easily
incorporated in the particles than Fe3+, in contrast, the uptake of Ni2+ and Cu2+ is difficult.
TEM images of the particles generated in the presenceof Ni2+, Cu2+, and Cr3+ are shown in Fig. 11. When metal/
Fe = 0, rod-shaped α-FeOOH particles with a length andwidth of approximately 270 and 40 nm, respectively, arerecognized. The morphology of α-FeOOH particles isunchanged by Ni2+ addition, indicating that the added Ni2+
has no considerable influence on the growth of α-FeOOH
particles. At Cu/Fe = 0–0.01, no significant change in themorphology of α-FeOOH particles is observed. At Cu/
Fe ≥ 0.02, the rod-shaped α-FeOOH particles transform
into irregular α-FeOOH particles with a size of approximately 65 nm. Similar to Cu2+ addition, with Cr3+ addition,
increasing the Cr/Fe ratio up to 0.01 substantially reduces
the size of α-FeOOH particles to approximately 50 nm andalters the rod-shaped particles into irregular ones. These
results indicate that the growth of α-FeOOH particles is
considerably suppressed by Cu2+ and Cr3+ addition. At Cr/
Fe ≥ 0.04, irregular-shaped Schwertmannite particles witha size of approximately 25 nm are observed. Furthermore,hexagonal Natrojarosite particles with a size of approximately 0.8 μm appear when Cr/Fe ≥ 0.06.
The formation and crystallization of iron oxide particles
considerably depend on the solution pH (Misawa T. et al.,
1974; Blesa M.A. and Matijević E., 1989; Cornell R.M.
and Schwertmann U., 1996; 2000; Tamura H., 2008).
The solution pH before aging is plotted as a function of
metal/Fe atomic ratio in Fig. 12. The solution pH before
aging is 7.0 at metal/Fe = 0 and is essentially not alteredby Ni2+ addition. Further, the solution pH before aging is
reduced by adding Cu2+ and Cr3+ up to metal/Fe = 0.02
and remains practically constant at approximately 4.5 and
4.0, respectively. This is due to the formation of Cu(OH)2

Fig. 11 TEM images of the particles generated with Ni2+, Cu 2+ and Cr3+. Adapted with permission from Ref. (Tanaka H. et al., 2018). Copyright: (2018)
Elsevier B.V.

125

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

Fig. 12 Plots of the solution pH before aging as a function of atomic
ratio metal/Fe. Adapted with permission from Ref. (Tanaka H. et al.,2018). Copyright: (2018) Elsevier B.V.

and Cr(OH)3 through the addition of NaOH solution because the reactions of Cu2+ and Cr3+ with OH– progress at
pH ≥ 4.2 and ≥ 4.0, respectively (Baes Jr C.F. and Mesmer
R.E., 1986). Hence, lowering the solution pH before aging
by adding Cu2+ and Cr3+ suppresses the crystallization andparticle growth of α-FeOOH. To verify this, α-FeOOH
particles were prepared at pH = 4.0 and 7.0 without metal
ion addition. The XRD patterns and TEM images of theobtained particles are depicted in Fig. 13. It is evident thatthe reduction in solution pH before aging significantly
weakens and broadens the α-FeOOH peaks. Moreover,the crystallite size of α-FeOOH obtained at pH = 4.0 is
7 nm less than that at pH = 7.0 (24 nm). Further, the rodshaped particles become irregular with a size of ca. 30 nm.

These results indicate that reducing the solution pH before
aging by adding Cu2+ and Cr3+ considerably prevents
the crystallization and particle growth of α-FeOOH. The
crystal structure of α-FeOOH consists of double chains ofedge-shared Fe3+ octahedron, as shown in Fig. 2 (Cornell
R.M. and Schwertmann U., 1996; 2000). The ionic radiiof octahedral Ni2+ (0.069 nm) and Cu2+ (0.072 nm) arelarger than that of octahedral Fe3+ (0.064 nm), hence, thesubstitution of Ni2+ and Cu2+ with Fe3+ in the α-FeOOH
crystal is difficult (Shannon R.D., 1976). The solution pH
before aging is markedly decreased by addition of Cu2+
and Cr3+, consequently impeding the growth of α-FeOOH
crystals and particles, nonetheless, Ni2+ addition exhibits
no distinct influence. In contrast, the added Cr3+ is easily
incorporated into the α-FeOOH crystal by substitution
with Fe3+ to form α-CrxFe1–xOOH solid solution because
the ionic radius of Cr3+ in the octahedron (0.063 nm) is
the same as that of Fe3+ (0.064 nm) (Shannon R.D., 1976).
Further, increasing the amount of added Cr3+ induces theformation of Cr3+-doped Schwertmannite particles. As
mentioned above, Schwertmannite is one of the precursorsof α-FeOOH. Therefore, the incorporation of Cr3+ into
Schwertmannite stabilizes its crystal structure, thus inhibiting its transformation into α-FeOOH. Consequently, theformation, crystallization, and particle growth of α-FeOOH
are markedly impeded by Cr3+, and the effect is in the order
Cr3+ > Cu2+ >> Ni2+.

4. Conclusions
Recently, various functionalized metal oxide nanoparticles with unique chemical and physical properties havebeen developed and applied in the fields of chemical

Fig. 13 XRD patterns and TEM images of α-FeOOH particles prepared at pH = 4.0 and 7.0. Adapted with permission from Ref. (Tanaka H. et al.,2018). Copyright: (2018) Elsevier B.V.

126

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

engineering, medicine, food, cosmetics, environment, etc.
The particle properties are extremely dependent on the
crystal structure, crystallinity, chemical composition, andparticle morphology. Therefore, nanoparticles with highcrystallinity, homogeneous chemical composition, uniform shape and size, and narrow particle size distribution
possess excellent chemical and physical properties. However, the synthesis of such particles is extremely difficult.
Hence, many researchers have investigated the synthesis ofhigh-quality nanoparticles using the liquid-phase synthesis
technique. The formation of nanoparticles is considerably
affected by a number of factors, such as the anion andcation concentrations and species, additive, solution pH,
and reaction temperature and time. To derive high-quality
nanoparticles, gaining insight on the fundamental principles of the formation mechanism and process of nanoparticles is necessary. Accordingly, a systematic study of theparticle formation is absolutely essential for the development of new functionalized nanoparticles.

Acknowledgements
The author profoundly expresses gratitude to Professor
Emeritus Tatsuo Ishikawa of Osaka University of Education
and Dr. Takenori Nakayama of Kobe Steel Co., Ltd., forsupporting this research. This study was partly supported
by Grants-in-Aid for Scientific Research (C) (20K05156
and 17K06862) the Next Generation Tatara Co-Creation
Centre (NEXTA), Shimane University. Here, NEXTA is established with Grant-in-aid for the Promotion of Regional
Industries and Universities from Cabinet Office, Japan.

References
Baes Jr C.F., Mesmer R.E., The Hydrolysis of Cations, Krieger
Publishing Company, Florida, 1986, ISBN: 978-0471039853.
DOI: 10.1002/bbpc.19770810252
Blesa M.A., Matijević E., Phase transformation of iron oxides,
oxyhydroxides, and hydrous oxides in aqueous media,
Advances in Colloid Interface Science, 29 (1989) 173–221.
DOI: 10.1002/chin.198935372
Charitidis C.A., Georgiou P., Koklioti M.A., Trompeta A.-F.,
Markakis V., Manufacturing nanomaterials: from research toindustry, Manufacturing Review, 1 (2014) 11. DOI: 10.1051/
mfreview/2014009
Chavali M.S., Nikolova M.P., Metal oxide nanoparticles andtheir applications in nanotechnology, SN Applied Sciences, 1(2019) 607. DOI: 10.1007/s42452-019-0592-3
Cornell R.M., Schwertmann U., The Iron Oxides, Wiely, 1996,
ISBN: 978-3527302741. DOI: 10.1002/3527602097
Dousma J., de Bruyu P.L., Hydrolysis-precipitation studies ofiron solutions. I. Model for hydrolysis and precipitationfrom Fe(III) nitrate solutions, Journal of Colloid andInterface Science, 56 (1976) 527–539. DOI: 10.1016/00219797(76)90119-3
Dousma J., de Bruyu P.L., Hydrolysis-precipitation studies ofiron solutions. II. Aging studies and the model for precipitation from Fe(III) nitrate solutions, Journal of Colloid andInterface Science, 64 (1978) 154–170. DOI: 10.1016/00219797(78)90345-4
Dousma J., de Bruyu P.L., Hydrolysis-precipitation studies of ironsolution. III. Adsorption of growth model to the formationof colloidal α-FeOOH from acidic solutions, Journal of
Colloid and Interface Science, 72 (1979) 314–320. DOI:
10.1016/0021-9797(79)90113-9
Dousma J., Ottelander D., de Bruyu P.L., The influence of sulfate
ions on the formation of iron(III) oxide, Journal of Inorganic and Nuclear Chemistry, 41 (1979) 1565–1568. DOI:
10.1016/0022-1902(79)80176-1
Dousma J., Van Den Hoven J.T.J., de Bruyu P.L., The influenceof chloride ions on the formation of iron(III) oxyhydroxide,
Journal of Inorganic and Nuclear Chemistry, 40 (1978)
1089–1093. DOI: 10.1016/0022-1902(78)80515-6
Feitknecht W., Studies of the influence of chemical factors on
the corrosion of metals, Chemistry and Industry, 36 (1959)
1102–1109.
Feng J., Biskos G., Schmidt-Ott A., Toward industrial scale
synthesis of ultrapure singlet nanoparticles with controllable
sizes in a continuous gas-phase process, Scientific Reports, 5(2015) 15788. DOI: 10.1038/srep15788 (2015)
Fujishima A., Hashimoto K., Watanabe T., TiO2 Photocatalysis:
Fundamentals and Applications, Tokyo Bkc, 1999, ISBN:
9784939051036.
Gutch A., Mühlrngweg H., Krämer M., Tailor-made nanoparticles via gas phase synthesis, Small, 1 (2004) 30–46. DOI:
10.1002/smll.200400021
Hsu P.M., Nucleation, polymerization, and precipitation of
FeOOH, Journal of Soil Science, 23 (1972) 407–419. DOI:
10.1111/j.1365-2389.1972.tb01671.x
Hsu P.M., Ragone S.E., Ageing of hydrolyzed iron(III) solutions,
Journal of Soil Science, 23 (1972) 17–31. DOI: 10.1111/
j.1365-2389.1972.tb01637.x
Iler R.K., The Chemistry of Silica: Solubility, Polymerization,
Colloid and Surface Properties and Biochemistry of Silica,
Wiley, 1979, ISBN: 9780471024040.
Inouye K., The role of copper (II) in the oxidation of ferrous
hydroxide colloid with special reference to the corrosionof iron in an SO2-containing environment, Journal of
Colloid and Interface Science, 27 (1968) 171–179. DOI:
10.1016/0021-9797(68)90024-6
Inouye K., Ishii S., Kaneko K., Ishikawa T., The effect of copper(II) on the crystallization of α-FeOOH, Zeitschrift für
Anorganische und Allgemeine Chemie, 391 (1972) 86–96.
DOI: 10.1002/zaac.19723910111
Ishikawa T., Formation and structures of iron oxides, Zairyo-toKankyo, 46 (1997) 411–417. DOI: 10.3323/jcorr1991.46.411
Ishikawa T., Synthesis, structure and modification of iron oxide
nanoparticles, Bulletin of The Iron and Steel Institute ofJapan, 14 (2009) 215–221.
Ishikawa T., Miyamoto S., Kandori K., Nakayama T., Influence of anions on the formation of β-FeOOH rusts,
Corrosion Science, 47 (2005) 2510–2520. DOI: 10.1016/j.
corsci.2004.10.016
Ishikawa T., Motoki T., Kato R., Yasukawa A., Kandori K.,
Nakayama T., Yuse F., Structures of β-FeOOH particles
formed in the presence of Ti(IV), Cr(III), and Cu(II) ions,
Journal of Colloid and Interface Science, 250 (2002) 74–81.
DOI: 10.1006/jcis.2002.8257
Ishikawa T., Motoyoshi N., Yasukawa A., Kandori K., NakayamaT., Yuse F., Influence of metal ions on formation of α-FeOOH
rust -single and multiple additions of Cu(II), Ni(II) and127

Hidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

Ti(IV)-, Zairyo-to-Kankyo, 50 (2001) 155–161. DOI:
10.3323/jcorr1991.50.155
Ishikawa T., Nakayama T., Approach to enhancement mechanismof resistance to corrosion of weathering steels by artificiallysynthesized rusts, Zairyo-to-Kankyo, 52 (2003) 140–154.
DOI: 10.3323/jcorr1991.52.140
Ishikawa T., Yamashita H., Yasukawa A., Kandori K., NakayamaT., Yuse F., Structures of Ti(IV)-doped α-FeOOH particles,
Journal of Materials Chemistry, 10 (2000) 543–547. DOI:
10.1039/A905433B
Jolivet J-P., Metal Oxide Chemistry and Synthesis: From
Solution to Solid State, Wiley, New York, 2000, ISBN: 9780471970569.
Kamimura T., Nasu S., Segi T., Tazaki T., Miyuki H., Morimoto
S., Kubo T., Influence of cations and anions on the formationof β-FeOOH, Corrosion Science, 24 (2005) 2531–2542. DOI:
10.1016/j.corsci.2004.10.014
Kandori K., Iron oxide particles, in: Hubbard A.T. (Eds.), Encyclopedia of Surface and Colloid Science, Marcel Dekker,
New York, 2002, pp. 3126–3469, ISBN: 978-0824707965.
Karatutlu A., Barhoum A., Sapelkin A., Chapter 1 - Liquid-phase
synthesis of nanoparticles and nanostructured materials,
in: Barhoum A., Makhlouf A.S.H. (Eds.), Emerging Applications of Nanoparticles and Architecture Nanostructures,
Elsevier, 2018, pp.1–28, ISBN: 978-0-323-51254-1. DOI:
10.1016/B978-0-323-51254-1.00001-4
Korotcenkov G., Thomas S., Sunny A.T., Velayudhan P.
(Eds.), Colloidal Metal Oxide Nanoparticles: Synthesis,
Characterization and Applications, Elsevier, 2019, ISBN:
9780128133576. DOI: 10.1016/C2016-0-03725-7
LaMer V.K., Nucleation in phase transitions, Industrial & Engineering Chemistry, 44 (1952) 1270–1277. DOI: 10.1021/
ie50510a027
LaMer V.K., Dinegar R.H., Theory, production and mechanismof formation of monodispersed hydrosols, Journal of theAmerican Chemical Society, 72 (1950) 4847–4854. DOI:
10.1021/ja01167a001
Lang P.F., Smith B.C., Ionization energies of atoms and atomic
ions, Journal of Chemical Education, 80 (2003) 938–946.
DOI: 10.1021/ed080p938
Lifshitz I.M., Slyozov V.V., The kinetics of precipitation fromsupersaturated solid solutions, Journal of Physics andChemistry of Solids, 19 (1961) 35–50. DOI: 10.1016/00223697(61)90054-3
Matijević E., Production of monodispersed colloidal particles,
Annual Review of Materials Research, 15 (1985) 483–516.
DOI: 10.1146/annurev.ms.15.080185.002411
Misawa T., Hashimoto K., Shimodaira S., On the mechanismof atmospheric rusting of iron and protective rust layer on
low alloy steels, Boshoku-Gijutsu, 23 (1974) 17–27. DOI:
10.3323/jcorr1974.23.1_17
Muguruma M., Tanaka H., Ishikawa T., Nakayama T., Influenceof metal ions on the transformation of artificial Schwertmannite rust particles into α-FeOOH, Zairyo-to-Kankyo, 64(2015) 235–239. DOI: 10.3323/jcorr.64.235
Murphy P.J., Posner A.M., Quirk J.P., Characterization ofhydrolyzed ferric ion solutions. A comparison of the effectsof various anions on the solutions, Journal of Colloid andInterface Science, 56 (1976) 312–319. DOI: 10.1016/00219797(76)90256-3
Nakayama T., Ishikawa T., Konno T.J., Structure of titanium-doped goethite rust, Corrosion Science, 47 (2005)
2521–2530. DOI: 10.1016/j.corsci.2004.11.030
Oh S.J., Kwon S.-J., Lee J.-Y., Yoo J.-Y., Choo W.-Y., Oxidation of Fe2+ ions in sulfate- and chloride-containing

128

aqueous medium, Corrosion, 58 (2002) 498–504. DOI:
10.5006/1.3277640
Ostwald W.Z., Über die vermeintliche Isomerie des roten undgelben Quecksilberoxyds und die Oberflächenspannung fester Körper, Zeitschrift für Physikalische Chemie, 34 (1900)
495–503. DOI: 10.1515/zpch-1900-3431
Pelizzetti E., Fine Particles Science and Technology: From Microto Nanoparticles, Springer, 2011, ISBN: 9789401066006.
Plote J., Fundamental growth principles of colloidal metal
nanoparticles -a new perspective, CrystEngComm, 17 (2015)
6809–6830. DOI: 10.1039/C5CE01014D
Reiss H., The growth of uniform colloidal dispersions,
Journal of Chemical Physics, 19 (1951) 482–487. DOI:
10.1063/1.1748251
Rodríguez J.A., Fernández-García M. (Eds.), Synthesis, Properties, and Applications of Oxide Nanomaterials, Wiley, 2006,
ISBN: 9780471724056. DOI: 10.1002/0470108975
Schultz M., Burckhardt W., Barth St., Investigations on thermallyforced hydrolysis and phase formation in aqueous iron(III)nitrate solutions, Journal of Materials Science, 34 (1999)
2217–2227. DOI: 10.1023/A:1004553019739
Schwertmann U. and Cornell R.M., Iron Oxides in the Laboratory: Preparation and Characterization, Wiely, 2000, ISBN:
978-3527296699. DOI: 10.1002/9783527613229
Shannon R.D., Revised effective ionic radii and systematicstudies of interatomic distances in halides and chalcogenides,
Acta Crystallographica, A32 (1976) 751–767. DOI: 10.1107/
S0567739476001551
Sillen L.G., Martell A.E., Stability Constants of Metal-Ion
Complexes, The Chemical Society, London, 1964, ISBN:
978-0851860190.
Sudakar S., Subbanna G.N., Kutty T.R.N., Effect of anions on thephase stability of γ-FeOOH nanoparticles and the magnetic
properties of gamma-ferric oxide derived from lepidocrocite,
Journal of Physics and Chemistry of Solids, 64 (2003)
2337–2349. DOI: 10.1016/S0022-3697(03)00270-1
Sugimoto T., Preparation of monodispersed colloidal particles,
Advances in Colloid and Interface Science, 28 (1987)
65–108. DOI: 10.1016/0001-8686(87)80009-X
Sugimoto T., Monodispersed Particles, Elsevier, 2001, ISBN:
9780444895691.
Tamura H., The role of rusts in corrosion and corrosion protectionof iron and steel, Corrosion Science, 50 (2008) 1872–1883.
DOI: 10.1016/j.corsci.2008.03.008
Tanaka H., Elucidation of atmospheric corrosion mechanism ofsteels by artificially synthesized iron rust particles, Journalof the Society of Powder Technology, Japan, 52 (2015)
398–404. DOI: 10.4164/sptj.52.398
Tanaka H., Hatanaka N., Muguruma M., Ishikawa T., NakayamaT., Influence of anions on the formation of artificial steel
rust particles prepared from acidic aqueous Fe(III) solution,
Corrosion Science, 66 (2013a) 136–141. DOI: 10.1016/j.
corsci.2012.09.011
Tanaka H., Hatanaka N., Muguruma M., Nishitani A., Ishikawa
T., Nakayama T., Influence of anions on the structure andmorphology of steel rust particles prepared by aerial oxidation of acidic Fe(II) solutions, Advanced Powder Technology,
27 (2016a) 2291–2297. DOI: 10.1016/j.apt.2016.09.004
Tanaka H., Inoue M., Ishikawa T., Nakayama T., Simulating studyof atmospheric corrosion of steels in a coastal industrial zone:
effect of SO32– on the formation of β-FeOOH rust particles
synthesized from FeCl3 solutions, Corrosion Science, 66(2016b) 241–245. DOI: 10.1016/j.corsci.2016.07.019
Tanaka H., Miyafuji A., Ishikawa T., Nakayama T., Influence ofNi(II), Cu(II) and Cr(III) on the formation, morphology andHidekazu Tanaka / KONA Powder and Particle Journal No. 39 (2022) 119–129

molecular adsorption properties of α-FeOOH rust particles
prepared by aerial oxidation of neutral Fe(II) solutions,
Advanced Powder Technology, 29 (2018) 9–17. DOI:
10.1016/j.apt.2017.09.015
Tanaka H., Miyafuji M., Kandori K., Ishikawa T., Nakayama T.,
Effect of Cu(II) on the formation, morphology and molecularadsorption properties of α-FeOOH rust particles preparedfrom acidic Fe(III) solutions, Corrosion Science, 66 (2013b)
337–342. DOI: 10.1016/j.corsci.2012.09.039
Thanh N.T.K., Maclean N., Mahiddine S., Mechanisms of
nucleation and growth of nanoparticles in solution, Chemical
Reviews, 114 (2014) 7610–7630. DOI: 10.1021/cr400544s

Author’s Short Biography
Hidekazu Tanaka
Hidekazu Tanaka received his Ph.D. from the Tokyo Metropolitan University in 1999. He worked
as a JSPS Research Fellow PD at the Osaka University of Education from 1999 to 2000. He joinedat the Shimane University as an Assistant Professor in 2000 and an Associate Professor in 2006. In
2014, he became a Professor of Graduate school of Natural Science and Technology at Shimane
University. His research interest is wet-synthesis of highly functionalized inorganic particles bycontrol of the particle morphology and modification of the surface structure focusing on the surfacefunctional groups.

129

KONA Powder and Particle Journal No. 39 (2022) 130–149/https://doi.org/10.14356/kona.2022015

Review Paper

High Performance Nickel Based Electrodes in State-of-the-Art
Lithium-Ion Batteries: Morphological Perspectives †Agus Purwanto 1,2*, Shofirul Sholikhatun Nisa 1,2, Ike Puji Lestari1,2,
Muhammad Nur Ikhsanudin 1,2, Cornelius Satria Yudha 1,2 and Hendri Widiyandari 2,3
1 Chemical Engineering Department, Faculty of Engineering, Universitas Sebelas Maret, Indonesia

2 Centre of Excellence for Electrical Energy Storage Technology, Universitas Sebelas Maret, Indonesia

3 Physics Department, Faculty of Mathematics and Natural Science, Universitas Sebelas Maret, Indonesia

Abstract
Li-ion batteries with “nickel” as the main material or the highest ratio material on the cathode or anode electrodehave attracted considerable attention. Nickel has high strength and corrosion resistance. Nickel has also beenutilized successfully as the cathode and anode materials. The specific capacity and energy and power density of thematerial increased with increasing nickel content. However, several problems have limited the use of nickel-based
Li-ion batteries. Problems such as cation mixing, the properties of nickel, and highly Ni-rich compounds leading
to side reactions, influence the electrochemical performance of Li-ion batteries. The morphology is another factor
affecting the electrochemical performance. Further studies will be needed to synthesize materials with the desired
morphology and determine how the morphology affects the electrochemical performance. In a morphologicalperspective, extensive morphological adjustments are a pathway to a long and stable life cycle. In this light, nickelbased electrodes are manufactured continuously and will always be considered for next-generation secondary
energy storage. The morphology of nickel-based active materials is one of the main factors determining the highperformance of Li-ion batteries.
Keywords: morphology, Li-ion batteries, nickel-rich electrode, anode and cathode

1. Introduction
Nickel is the main highlight among researchers andindustry. It is considered a versatile element because it isapplied in various materials and technologies. The metal
has high strength and corrosion resistance. Thus, it is often
essential in construction materials, such as well-known
stainless steels (Dewangan et al., 2015). Recently, nickel
has found new applications in electrochemical energy
storage that will permit increased mobility and flexibility.
Interestingly, with current environmental issues, such as
global warming and air pollution, nickel-based energy storage will be required in developing and developed countries(Ye et al., 2021).
Secondary batteries with nickel-derived active materials have been developed since the 19th century. Nickelcadmium is the first nickel-based rechargeable battery thatwas successfully commercialized back in the early 20th†*

Received 31 May 2021; Accepted 16 June 2021
J-STAGE Advance published online 18 September 2021
Corresponding author: Agus Purwanto;
Add: Jl. Ir. Sutami 36A, Surakarta, Central Java 57126, Indonesia
E-mail: aguspurwanto@staff.uns.ac.id
TEL/FAX: +62-271-662118

130

century. Since its discovery, poor electrochemical performance and treating highly toxic spent Ni-Cd batteries
have become major challenges. Its successor, Nickel-metal
hydride (NiMH), also faces problems limiting its application, such as high self-discharge and low cycle life. The
drawbacks of nickel-based energy storage have become
alarming. Therefore, during the shift to new technology,
Li-ion batteries, nickel-based electrodes were “temporally”
left behind (Elbert et al., 2010; Lee et al., 2009).
Since their successful commercialization, it was predicted that Li-ion batteries would dominate the energy
storage market. However, the dependence on cobalt-basedmaterials, such as LiCoO2, cannot endure (Nitta et al.,2015; Toprakci et al., 2010). Cobalt is toxic and its exploitation has caused more harm than good. Even withrelatively good stability, it has low real capacity because
full Li-ion storage capacity was limited to 50 % to avoid
explosions caused by thermal and design failure. In addition, cobalt is very expensive compared to other common
transitional metals. These problems have shifted theconcerns of researchers and industries back to nickel as anelectrode material (Kalyani and Kalaiselvi, 2005).
Nickel has been used successfully utilized as bothcathode and anode materials. Layered structured lithium

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

transitional metal oxides (LTMO) were recently consideredhigh-performance and high energy density cathode materials. Based on Fig. 1, the proportion of nickel in LTMOs
has increased gradually over the past two decades, e.g., thedevelopment of NMCs (lithium nickel manganese cobalt
oxide) and NCA (lithium nickel cobalt aluminum oxide)(Yan et al., 2020). While there is no classification of NCA,
NMC cathode materials are classified based on the composition of the transitional metals and the types can be seenin Fig. 1. Extensive efforts to increase the nickel content in
NMCs cathode materials have been reported. The specificcapacity, energy density, and power density of the material
increase with increasing nickel content. However, several
problems are still being faced during its implementation.
Nickel-rich cathode materials, such as LiNiO2, LiNi1–x–y
CoxMnyO2 (x + y < 4), and LiNi0.8Co0.15Al0.05O2, are often
produced with poor electrochemical properties because of
cationic exchange between Li+ and Ni2+ from their lattices,where the cell suffers high irreversible capacity loss during
its use (Lei et al., 2019a). Nickel-rich materials are also
hygroscopic, which means they attract water molecules
when not stored and handled properly. Highly reactive
nickel-rich compounds at elevated working voltages also
result in undesirable side reactions between the nickel-richcathodes and the aprotic carbonate-rich electrolyte, producing unwanted side products that cause a rapid decrease incapacity or lifetime. Studies have confirmed that the cation
mixing level can be reduced by the synthesis conditions anddoping process in a nickel-rich cathode. Hygroscopicity
can be overcome by proper storage conditions or coating ofmaterials (Huang et al., 2014). The unwanted side reactions
that occur during cell use can also be suppressed by coating
the materials. However, adding a coating to a nickel-richcathode is considered uneconomical because the coatingprocess requires additional processing and production (LuX. et al., 2019). Tailoring the particle morphology canalso reduce the reactivity of Ni-rich cathodes. In addition,different morphologies result in different electrochemical
behavior in Li-ion cells (Hwang et al., 2012).
Nickel-based anodes have undergone continuous devel-

Fig. 1

opment to replace existing carbonaceous anodes (Zuniga etal., 2019). Carbonaceous anodes have low gravimetric andvolumetric capacity. To obtain commercialized artificial
graphite, an extremely high heating process is necessary.
Even with excellent performance, Li dendrite formation isan alarming phenomenon in graphite anodes because it canpotentially cause battery failures. These concerns provethat state-of-the-art anode materials are urgently needed.
Metal-based anodes, specifically nickel-based anodes, suchas nickel oxides, nickel hydroxides, and nickel sulfides,
are being developed continuously. The high capacity, highconductivity, easy recycling and reuse, and high availability make the metal-based anodes economically attractive.
However, large capacity loss during the initial cycle often
occurred because the Li storage mechanism involves a conversion and alloying-dealloying process (Wang L. et al.,2018). This problem can be overcome by morphologicaltailoring.
As Ni-rich Li-ion batteries are the market giant for
current and future energy storage, an understanding of thefactors that affect the electrochemical performance of thecells is required. Accordingly, because the morphology ofthe particle affects the electrochemical performance, thispaper presents a review of nickel-based electrode synthesis
toward its electrochemical behavior based on a morphological perspective.

2. Particle morphology for nickel-based
anode material
Currently, various nickel-based materials have been
applied as the anode material in Li-ion batteries. Oxides,
hydroxides, sulfides, carbonates, and oxalates of nickel
as anode material are representative examples. The electrochemical performance of these materials is mostly improved because of their unique morphologies. This section
discusses the morphology of the nickel-based materials andtheir electrochemical performance.

The developments of LTMO-based cathodes.

131Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

2.1 Nanosheets nickel-based anode materials

2.3 Nanoplate nickel-based anode materials

Nanosheets Ni(OH)2 has been developed and successfully applied as an active material of Li-ion batteries.
Various precursors of Ni(NO3)2・6H2O and NiCl2・6H2O
provide uniform and ultra-thin nanosheet particle withparticle dimension range between 20–30 µm. Particle morphology from NiSO4・6H2O showing larger particle withdimension range between 30–50 µm. The electrochemical
performance of Ni(OH)2 are 1790/1157, 1945/1282, and2019/1358 mAh g–1 with columbic efficiencies 65, 66, and
67 % (Li Yanwei et al., 2017). Modification of Ni(OH)2 by
Al doping has been reported. The study showed the addition of Al slightly alter the particle dimension with specificcapacity of 681 mAh g–1 at 20 % Al content and capacity
retention of 50 % after 30 cycles (Li Y. et al., 2016).
Cycle ability of Ni(OH)2 can be improved by Ti3C2 lamination via hydrometallurgy method. In the study, Ni(OH)2/
Ti3C2 electrode material has Li capacity of 121.3 mAh g–1,
higher than pure Ni(OH)2 (117.6 mAh g–1) with stable
cycle performance after 1000 cycles (Li C. et al., 2020).
Double hydroxide metal transition, Nickel-cobalt, withultrathin graphene surface layer is an alternative to astable electrochemical cycle performance of nanosheets
Ni(OH)2 (Shi et al., 2017). Ni(OH)2 blending with PANI
and graphene oxide exhibited improved cycle ability with
only 15.6 % capacity drop after 2000 cycles (Ma et al.,2016). This technique also successfully implemented in
Ni-Co phosphates which had excellent cycling ability andstability after 9000 cycles (Li B. et al., 2017).

Nanoplate Ni(OH)2/Graphene anode material was produced by hydrothermal reaction of NiNO3, ammonia andgraphene at 150 °C for 12 h. It exhibited Initial specificcapacity of 1318 mA/g and average capacity loss of about
0.11 % after 100 cycles (Du et al., 2018).

2.2 Nanoflakes nickel-based anode materials
Nanoflakes Ni(OH)2 was obtained via precipitation andhydrazine assisted reduction process. Blended with rGO,
the material delivered high initial capacity of 1500 mAh g–1
and 1003 mAh g–1 after 40 cycles (Zhu et al., 2014). Nanoflake NiO as anode material was successfully obtainedby chemical liquid deposition in Ni-foam followed byatmospheric heat treatment at 350 °C. The material delivered discharge capacity of 1.94 mAh cm–2 and capacity
retention 71.1 % after 140 cycles (Ni et al., 2013). Anotherapproach to obtain nanoflake NiO is via chemical bathdeposition before being inserted into Ni foam. It exhibited
initial capacity of 700 mAh g–1 and 490 mAh g–1 after 50
cycles (Huang et al., 2009). Nanoflake NiS from hydrothermally treated NiCl2 and metal alloying was also reported.
The electrochemical performance test showed initial discharge capacity of 584.6 mAh g–1 and capacity retentionof 34.2 % after 30 cycles (Zhu et al., 2011). Flake-shaped
carbon-NiS was obtained also via hydrothermal processwith addition of glucose as carbon source. The material
initial and 20th discharge capacity was 575.4 mAh g–1 and200 mAh, respectively (Wang et al., 2013).

132

2.4 Nanorod nickel-based anode materials
SEM analysis of a NiS-graphene composite revealed
nanorod morphological particles. NiS-graphene with ananorod morphology was produced using the Hummers
method followed by thermal reduction. The NiS tographene mass ratio that indicates a nanorod morphology
was 2:1.
The electrochemical performance test revealed an initialdischarge capacity of 458 mAh g–1. This was smaller thanNiS:graphene = 1:1, which had been discussed elsewherein the sub-chapter nanosheet reported (Geng et al., 2014).
The NiS nanorod morphology also could be produced
using a solvothermal reaction. The raw material for the
Ni-source and S-source was nitrate-based and C2H5NS,
respectively. SEM showed that the concentration of thereactant solution affected the morphology of the particle.
All concentrations produced a nanorod morphology, buthigher concentrations resulted in a decrease in NiS particle
size. The electrochemical test revealed good performance.
The initial discharge capacity was 670 mAh g–1, and good
cycling stability was observed after 100 cycles (Long etal., 2016). Nickel oxalate (NiC2O4・2H2O) nanorod particles were synthesized using a hydrothermal method. The
temperature of the hydrothermal process influenced theparticle morphology. An urchin-like nanorod morphology
was observed when the reaction took place at 130 °C. On
the other hand, the ratio and size of the nanorod particles
increased when the reaction occurred at 170 °C. The initialdischarge capacity was 1109 mAh g–1 with cycling stabilityof 85 % (Oh et al., 2016). Nickel oxalate was also used as aprecursor material for NiO (Du et al., 2020).

2.5 Nanospike nickel-based anode materials
NiS with nano-spike morphology was obtained using ahydrothermal method in an autoclave reactor performed
at a temperature of 160 °C for 24 hours. Fig. 2a showsa nano-spike particle. The electrochemical performance
test was conducted on a coin cell-type cell with NiS as thecathode and Li-foil as the anode. The best initial discharge
specific capacity was 550 mAh g–1. Cycling stability after
100 cycles revealed 60 % capacity retention from its initial
capacity (Sonia et al., 2014). The NiS powder was modified
by adding a camphoric carbon solution to the raw material
to form “camphoric carbon wrapped NiS”. SEM and TEM

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

Fig. 2 (a) Nano-spike morphology of NiS material, reprinted with permission from Ref. (Sonia et al., 2014) Copyright (2014) Elsevier B.V. (b) NiS
flower-like particle, reprinted with permission from Ref. (Ma et al., 2015) Copyright (2015) Springer Nature Limited, (c) NiS Urchin-like particle,
reprinted with permission from Ref (Mi et al., 2013) Copyright (2013) RSC Publishing.

revealed nano-spike particles. The modified-NiS was produced using a hydrothermal method in an autoclave reactor
at 160 °C for 24 hours. The electrochemical performance
test showed an initial discharge capacity of 500 mAh g–1.
The test revealed 75 % capacity retention after 100 cycles,
showing good cycling stability performance. The useof camphoric carbon increased the cyclic performance(Sebastian et al., 2014).

2.6 Urchin and flower like material
NiS material with an urchin-like morphology could beobtained by adding cetyltrimethylammonium bromide(CTAB) as an assistant. The flower-like NiS particles weresynthesized using a hydrothermal method. Fig. 2b presents
an SEM image of a flower-like NiS particle. The raw
material for the Ni-source was a nitrate salt and NaSCN
for the S-source. The highest initial discharge capacity
was 6733 mAh g–1. The cycling stability was tested until
10 cycles, showing 85 % capacity retention (Ma et al.,2015). NiS with an urchin-like particle morphology wassynthesized from a nickel complex as a precursor using asolvothermal method. Fig. 2c shows the NiS urchin-likeparticle morphology. The electrochemical performance
was assessed using a coin-cell type cell. The initial discharge capacity of the battery was 597.3 mAh g–1 with avoltage window of 1.0–3.0 V (Mi et al., 2013).
Table 1 summarizes the summary of nickel-based anodemorphology and their electrochemical behavior. A nickelbased anode with a unique morphology showed excellent performance in Li-metal batteries. With small or
nanoscale size, each material can store Li, even withgood cycling ability. In contrast to the graphitic or carbonbased anode, the insertion of Li-ions uses a conversion
mechanism rather than an intercalation mechanism.
Fig. 3 shows the role of morphology towards the electrochemical properties of nickel-based anode material in
Li-ion batteries. Studies showed that the nanostructure
property of anode material has significant roles in improving the electrochemical performance. It offers a large

contact of electrolyte to the surface of the material which
is beneficial for high current applications. Some of thestructure such as nanorods, nanowalls, nanoflakes has arigid structure that is able to accommodate volume change
strain during prolonged cycle of charge and discharge at
relatively high current. However, the capacity value is not
only affected by the morphology, but also the type of material and its lithiation-delithiation mechanism which will not
be discussed deeply. The cycle stability of the anode is also
greatly improved by addition of 2D nano-material such asgraphene, reduced graphene oxide (rGO), and Ti3C2.
The main disadvantage of the conversion anode is thepoor initial coulombic efficiency caused by a permanent
Li reaction with some of the anode. In Li-metal batteries,
the high Li-loss during the first cycle can be compensatedfor by the abundant Li source of the Li anode. In full cells,
limited Li from the cathode materials can deteriorate theelectrochemical performance of the cells. Even with aunique morphology, the initial lithiation capacity of Li inconversion anodes is still much larger than the de-lithiation
capacity. However, efforts to increase the usability of
conversion-type materials for Li-ion full cells, such as a Lirich cathode material, material incorporation with carbon,
and pre–lithiation of conversion anodes, are still being
made (Qiu et al., 2018; Wei et al., 2020).

3. Nickel rich cathodes and their precursors
The synthesis of nickel-rich cathodes generally involves
two processes: the formation of nickel-rich cathode precursors and high-temperature lithiation. The formationof precursors often determines the morphology of the
final products, even after undergoing a long heat-treatment
process. In this section, the formation of secondary particles is not discussed because the secondary particles areoften related to the final morphology of the particle. The
mechanism for the formation of secondary particles will be
discussed in the next segment.

133

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149
Table 1

Preparation of Ni-based particle for anode material of Li-ion batteries.

Ni-based Materials

Methods

Modification

MorphologicalfeatureElectrochemical
Performance (Capacity/
Cycle/Rate)

Reference

Ni(OH)2

Precipitation—

Ultra-thinnanosheet

2019/1358 mAh g–1/0.1 C(Li Yanwei et al.,2017)

Ni(OH)2

Precipitation

Al-doping 20 %w/w

Nanosheet

681 mAh g–1/30
cycles/0.1 C(Li Y. et al., 2016)

Ni(OH)2

Hydrothermal

Ni(OH)2/
delaminated-Ti3C2

Nanosheet

121 mAh g–1/1000
cycles/0.1 C(Li C. et al., 2020)

Ni-Co-hydroxide

Hydrothermal

Combine Co-Ni
hydroxide

Nanosheet

373 mAh g–1/500
cycles/0.1 C(Shi et al., 2017)

Ni(OH)2

One-step in-situ
polymerization

GO/PANI blending Nanosheet

Capacity fading 15.6 %after 2000 cycles(Ma et al., 2016)

Ni(OH)2

precipitationrGO blending

Nano-flakes

1500/40 cycles/0.1 C(Zhu et al., 2014)

CLD and graft
growth under air
condition—

Nano-flakes

1.94 mAh cm–2/140(Ni et al., 2013)

NiO

CBD

—

Nano-flakes

700 mAh g–1/50
cycles/0.1 C(Huang et al.,
2009)

NiO

Hydrothermal

Graphene blending

Nanoplate1318 mAh g–1/100
cycles/0.1 C(Du et al., 2018)

NiO

Thermaldecomposition

Ni-foam as starting
material

Nanowalls

1020/704 mAh g–1/60
cycles at various rates(0.2-10C)(Wang et al., 2011)

NiS

Hydrothermal

Cladding carbon(C-NiS)

Flake-shape575.4 mAh g–1/30 cycles(Wang et al., 2013)

NiS/G (1:1)

Hummers method
continued withthermal reduction

Mass ratio NiS tographene

Nanosheet

887 mAh g–1/60
cycles/0.1 C(Geng et al., 2014)

NiS/G (2:1)

Hummers method
continued withthermal reduction

Mass ratio NiS tographene

Nanorod

458 mAh g–1/60
cycles/0.1 C(Geng et al., 2014)

NiS

Solvothermal

Reactant
concentration

Nanorod

670 mAh g–1/100 cycles(Long et al., 2016)

NiS

Hydrothermal

Reaction time
(24 h)

Nano-spike

550 mAh g–1/100
cycles/0.1 C(Sonia et al., 2014)

Camphoric carbon
wrapped -NiS

Hydrothermal

Addition ofcamphoric carbon

Nano-spike

550 mAh g–1/100
cycles/0.1 C(Sebastian et al.,
2014)

NiS

Hydrothermal

CTAB assistant

Flower-like6733 mAh g–1/10 cycles(Ma et al., 2015)(Mi et al., 2013)(Oh et al., 2016)

NiO

cycles/0.1 C

NiS

Solvothermal

Nickel complex
precursor

Urchin-like

597.3 mAh g–1

NiC2O4・2H2O

Hydrothermal

Reaction
temperature

Nanorod1109 mAh g–1

3.1 Nanosheets precursor to nickel-based cathodematerials
Nickel manganese cobalt (NMC)-based spherical precursors were assembled using a solvothermal method.
Ni(NO3)2・6H2O, Co(NO3)2・6H2O, and Mn(NO3)2 with a
mol ratio of 14:3:3 were dissolved in 50 mL of ethanol.
The operational conditions were RTP (Room temperature134

and pressure). A clear solution was placed in an autoclaveand heated to 160 °C for 12 hours. The precipitate was thenwashed with absolute ethanol and dried at 80 °C for 8 hours
in air. The morphology analysis shows microsphere flowerlike particles with diameters of approximately 2–6 µm. All
the microsphere flower-like particles were comprised ofnanosheets (Fu et al., 2014). Fig. 4a gives an example of ananosheet primary particle.

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

Fig. 3

Schematic illustration of the morphology effect on the Li-ion transport mechanism.

Fig. 4 (a) Nanosheet primary particle of NMC-based material, reprinted with permission from Ref. (Fu et al., 2014) Copyright (2014) ACS Publications, (b) Nanoflake primary particle of NMC-811 cathode material, reprinted with permission from Ref. (Mo et al., 2020) Copyright (2020) Elsevier
B.V., (c) Nanoplate primary particle of NCA cathode material, reprinted with permission from Ref. (Wang Q. et al., 2018) Copyright (2018) Electrochemical Science Group, (d) Nanorod primary particle of NMC cathode material, reprinted with permission from Ref. (Sun et al., 2019) Copyright (2019)
ACS Publications, (e) Needle-like particle of NCA-material, reprinted with permission from Ref. (Duan et al., 2018) Copyright (2018) Elsevier B.V.

3.2 Nanoflakes precursor to nickel-based cathodematerials
Ni-rich nano-flake particles, NMC-811 (LiNi0.8Mn0.1
Co0.1O2) hydroxide precursor, can be prepared using a
coprecipitation method. The raw materials for Ni, Mn,
and Co sources were diluted in a mixture of NaOH and
NH4OH. A calcination process was then performed underO2 atmospheric conditions at 750 °C for 12 hours. The secondary particle morphology was spherical and assembled
from cross-flake particles. The precursor was mixed with
LiOH and TiO2 to make a cathode material before sintering(Mo et al., 2020). Fig. 4b presents SEM images of a nanoflake particle. NMC-811 precursor synthesis is another way
to improve the performance of Li-ion batteries.

3.3 Nanoplate precursor to nickel-based cathodematerials
NCA (LiNi0.80Co0.15Al0.05O2) with a nanoplate morphology was obtained using sol-gel methods. The first research used raw materials: Ni(CH3COO)2・6H2O, Co(CH3
COO)2・4H2O, Al(NO3)3・8H2O, and LiCH3COO with amolar ratio of 10.5:8:1.5:0.5. All the ingredients were135

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

dissolved in ethylene glycol with a concentration of 0.5 M
and stirred for 8 hours at 85 °C. After the powder wasformed and dried, it was ground to reduce the particle
size, calcined, and sintered to prepare the cathode material(Wang Q. et al., 2018). Fig. 4c shows the nanoplate primary particles of the NCA cathode material. The second
study used a nitrate-based raw material for Li, Ni, Co, and
Al. C16H36O4Ti was used as the Ti doping source. All thematerials were dissolved in ethylene glycol and stirred for8 hours at 85 °C (Li J. et al., 2020).
NMC-622 (LiNi0.6Mn0.2Co0.2O2) is another cathode material with a nanoplate morphology that was obtained fromammonia-induced coprecipitation. The first step involved
mixing 12 M NH3・H2O/(Ni2+, Co2+, and Mn2+) at a molar
ratio of 6:1 for 30 minutes under inert conditions (using
N2). Subsequently, the metal salts were added to the firstsolution and stirred for four hours. Stirring was continued
at 95 °C for six hours to evaporate NH3 and allow precipitation. The slurry was filtered, washed, and dried in an
oven. Li2CO3, as the Li source, was added to a 7 % excess,calcined, and sintered to produce the Li-NCA cathodematerial (Liu et al., 2016). The NMC cathode material(LiNi0.70Mn0.15Co0.15O2) with increasing Li+ ion diffusion
showed good cycling ability. The manufacturing of thismaterial was through a coprecipitation method followed bya hydrothermal method. The Ni, Mn, and Co metal sourceswere acetate salts combined at a Ni:Mn:Co molar ratio of
0.7:0.15:0.15. All the materials dissolved, and NaOH wasadded as a precipitating agent under inert conditions (Ar).
The pH of the solution was maintained at 11. The solution
was then moved to another reactor and filled to 80 % of the
maximum volume. PVP (polyvinylpyrrolidone) was thenadded for the hydrothermal process, which was performed
at 150 °C for four hours. Subsequently, the temperature
was decreased naturally to ambient temperature. The
slurry was then filtered, washed, and dried [Ni0.70Mn0.15
Co0.15O2(OH)2]. The last steps were the calcination andsintering processes (Tian et al., 2016).

3.4 Nanorods precursor to nickel-based cathodematerials
The NMC-622 hydroxide precursor (Ni0.6Mn0.2
Co0.2(OH)2) as cathode material of Li-ion batteries wascomprised of nanorod particles (Fig. 4d). This precursor
was synthesized using a controlled coprecipitation method
in a continuous stirred tank reactor on a large scale witha volume of 200 L. The Ni, Co, and Mn sources were
sulfate salts dissolved in deionized water. NaOH and
NH3·H2O were added separately into the continuous
stirred tank reactor. The ammonium concentration was
controlled to 4–5 g/L, and the pH was 11.5–12. The solid/
precipitant formed was separated and dried in an ovenand producing Ni0.6Mn0.2Co0.2(OH)2. The precursor had

136

a micro-spherical morphology with a surface covered
with nanorod-like particles (Yang et al., 2019). A fullconcentration gradient (FCG) of the nanorod primaryparticle as a cathode material (LiNi0.54Mn0.30Co0.16O2)
was made from the [(Ni0.54Mn0.30Co0.16)(OH)2] precursor
material. The raw materials for Ni, Co, and Mn wereNiSO4·6H2O, CoSO4·7H2O, and MnSO4·H2O, respectively. A coprecipitation method was used to manufacture
the precursor. The base material with a molar ratio of
Ni:Mn:Co = 0.5:0.3:0.2 was added slowly to a Ni-richsolution containing Ni:Mn = 0.7:0.3. The homogenous
solution was moved into the tanks with a stirrer, and N2 wasintroduced to achieve inert conditions. NaOH solution and
NH4OH solution were added slowly to the tank as a chelating agent. The precursor was filtered and dried at 100 °C
until all moisture had been removed. (Noh et al., 2014).

3.5 Needle-like precursor to nickel-based cathodematerials
Needle-like particles were identified on the morphological test results of the NCA and NMC precursor for
Li-ion batteries. Ni0.815Co0.15Al0.035(OH)2 was mixed with
an NH4H2PO4 solution to form a homogenous slurry anddried naturally. After the mixture had dried completely,
Li2CO3 was added to the mixture. The mixture wassintered at 750 °C for 16 hours (O2 condition) to form
LiNi0.815Co0.15Al0.035O2. The resulting product was comprised of needle-like particles covered with NH4H2PO4(Tang et al., 2017). The Al-gradient composition to Ni
and Co metal sources was also promising as material
doping for the Ni0.815Co0.15Al0.035(OH)2 precursor. First, a
Ni0.815Co0.15Al0.035(OH)2 precursor was synthesized by acoprecipitation method with NH3·H2O as a chelating agent.
Al(NO3)3·9H2O was dissolved in distilled water to form ahomogenous solution, followed by the addition of a 32 %NaOH solution until a clear solution had formed. Distilledwater was then added to the mixture to control the concentration of [Al(OH)x]3-x. The pH of the solution was 12–13(Duan et al., 2016).
An Al-doped Ni-Co-hydroxide precursor [Ni0.90
Co0.07Al0.03(OH)2] exhibited uniform needle-like NCA
particles (Fig. 4e). The Ni and Co sulfate salts sourceswere used to synthesize the Ni0.928Co0.072(OH)2 precursor.
The Al-source was obtained from the Al-based material
dissolved in a 32 % NaOH solution to form Al(NO3)3. The
Ni0.928Co0.072(OH)2 precursor was then added to Al(NO3)3.
The mixture was stirred at 500 rpm and 60 °C with CO2.
The mixture was washed with deionized water and dried ina vacuum oven. Dried Ni0.90Co0.07Al0.03(OH)2 was mixed
with LiOH·H2O and sintered in oxygen to form LiNi0.90
Co0.07Al0.03O2 (Duan et al., 2018). The NCA material was
modified by replacing Al with W to increase the cyclingstability. The first step involved synthesizing [Ni0.9Co0.1]

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149
Table 2

Nickel-rich cathode precursors and their morphology.

Precursors

Metal Sources/Modification

Methods

Temperature (°C)/
Time/Condition

MorphologicalfeatureReference

NMC-OH

Nitrates

Solvothermal

160

Nanosheet(Fu et al., 2014)

NMC-811-OH

Sulfates

Precipitation

Nano-flake(Mo et al., 2020)

NCA

Ni-Co-Li-acetate
Al-nitrate

Sol-gel

85/8 h stirring

Nanoplate(Li J. et al., 2020)

NMC-622

Ni-Co-nitrate
Mn-Mn(Ac)2

Ammonia-induced
and coprecipitation

96/6 h ammonia
evaporation

Nanoplate(Liu et al., 2016)

NMC-7 1.5 1.5

AcetateHydrothermal

150/4 h process

Nanoplate(Tian et al., 2016)

NMC-622

SulfateCoprecipitation—

Nanorod(Yang et al., 2019)

NMC-FCG

Sulfate/NMC-532 solution
added into NM-73 solution

Coprecipitation

Nanorod(Noh et al., 2014)

NCA-OH

Commercial precursorNH4H2PO4 combined—

Needle-like(Tang et al., 2017)

Al-dopedNCA

Sulfate/Al doping

Coprecipitation

Needle-like(Duan et al., 2016)

NCA

Ni-Co-OH with addition of
Al-nitrate

60/500 rpm/CO2
condition

Needle-like(Duan et al., 2018)

NCW

Ni-Co-sulfate/replacement of
Al with W

Precipitation

Inert (N2)
condition

Needle-like(Ryu et al., 2019)

NMC-811

Commercial precursor + PVP

Pre-oxidized
process40

Needle-like(Zhang et al., 2018)

NMC-811

SulfateSolid statewith controlled
crystallization50

Needle-like(Yang G. et al.,2020)

Al-dopedNMC-811

Commercial precursor/Al
doping from nitrate source

80/sol phase

Needle-like(Du et al., 2021)(OH)2 using a precipitation method from the sulfate salts.
WO3 was then dissolved in distilled water and added
slowly to the Ni-Co precursor. Subsequently, the mixture
was washed, filtered, and dried. The process took place
under inert conditions (N2). LiOH was then added, and the
mixture was sintered to form LiNi0.90Co0.09W0.01O2. An
analysis of the surface morphology revealed needle-likeparticles (Ryu et al., 2019). NMC-811 needle-like primaryparticles could be realized using a pre-oxidized process(Zhang et al., 2018), solid-state method with controlled
crystallization and high-temperature operation (Yang G.
et al., 2020), and Al-doping to cover the surface of the
NMC-811-hydroxide precursor (Ni0.8Mn0.1Co0.1(OH)2)(Du et al., 2021). The pre-oxidized method was performedby mixing 0.005 g of polyvinylpyrrolidone (PVP) with
the NMC-81-hydroxide precursor and dissolved in distilled water. This was followed by the addition of 3 wt.%
Mn(NO3)2 to the mixture. The resulting mixture was heated
to 40 °C until the water had vaporized. LiOH·H2O wasthen added to the dried powder and sintered to produce
LiNi0.54Mn0.30Co0.16O2 doped with 3 % Mn(NO3)2 (Zhang
et al., 2018). The second method was controlled crystallization followed by a solid-state method. Ni, Mn, and Co

sulfate salts were dissolved in distilled water and stirredin a N2 atmosphere. Subsequently, a 2M NaOH solution
was added as a precipitation agent. The temperature wasmaintained at 50 °C and a pH of 11.2 (Yang G. et al., 2020).
Al doping was then performed. A dilute Al(NO3)3・9H2O
in citric acid solution with a molar ratio 1:1 was produced.
The mixture was stirred and heated until 80 °C to form asol phase. The NMC-811-hydroxide precursor was thenadded and stirred. The resulting solution was heated until
all the solvent had evaporated. The dried precursor was
mixed with LiOH·H2O and sintered to form LiNi0.80Mn0.10
Co0.10O2 (Du et al., 2021). Table 2 summarizes reported
morphologies of nickel-rich cathode precursors whichobtained through various synthesis techniques.

4. Nickel-rich cathode materials
4.1 Primary particles morphology of nickel-based
cathode material
A nanosheet morphology is found widely in electrodematerials, particularly Ni-rich material for Li-ion batteries.

137

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

NMC-811 (LiNi0.8Mn0.1Co0.1O2), as a Ni-rich cathode material, showed spherical morphology and provided a highrate and excellent cycling characteristics. In some cases,
however, the primary morphology represents anothertype of morphology. Xu et al. generated NMC-811 with ananosheet primary morphology and a spherical secondary
morphology. The modified coprecipitation method was
combined with a solid-state method to make radiallyaligned single-crystal primary particles (RASC-NMC).
This material used NMC-OH as a precursor. The crystal wasapproximately 50 nm in diameter with an average lengthof 300–1000 nm. The specific capacity based on chargedischarge analysis was 195.3 mAh g–1 at the 1st cycle. The
cycling stability revealed up to 95.5 % (172.7 mAh g–1) of
the initial capacity (195.3 mAh g–1) after 300 cycles (Xuet al., 2019). The nanosheet morphology of NMC-811 canalso be controlled by setting the ammonia concentration
during the coprecipitation method. Controlling the ammonia concentration helped improve the area of exposed{010} planes of NMC-811 (LiNi0.8Mn0.1Co0.1O2) material.
The electrochemical test showed an excellent capacity of
201.6 mAh g–1 at the first cycle at a current rate of 0.2 C
with capacity retention of up to 90 % after the 100th cycle(Su et al., 2018). Other NMC cathode materials were also
manufactured using different precursor materials andmethods. LiNi0.7Mn0.15Co0.15O2 was synthesized from a NiMn-Co spherical precursor using a solvothermal method.
This Ni-rich NMC cathode material exhibited a secondary
flower-like morphology assembled from nanosheets. The
electrochemical performance showed a specific capacityof 184.7 mAh g–1. The cycling data were taken between
1–100 cycles (Fu et al., 2014). The hydrothermal method
can modify the morphology of the NMC material. The
primary morphology was nanosheet particles, which werearranged into single spherical particles as second particles.
The specific capacity was 189.5 mAh g–1. After the 100th
cycle, the specific capacity decreased until 135.5 mAh g–1.
The capacity retention decreased to 73.0 % (Liu et al.,2019).
Ni-rich, NMC-811 cathode nano-flake particles can beprepared by modifying the NMC-OH precursors with theaddition of TiO2 and LiOH before sintering. TiO2 doping
helps improve the electrochemical performance and reducethe internal strain and the durability of the NMC-811
structure as a cathode material. The initial specific capacity
was 258 mAh g–1. The capacity decreased to 79 % whencharged under a 1 C current rate for 150 cycles (Mo et al.,2020). Nanoplate NCA (LiNi0.80Co0.15Al0.05O2) showed
excellent capacity. The best sintering conditions of theNCA-precursor were 750 °C for 12 hours. The highest
initial discharge capacity was 210.4 mAh/g at a current
rate of 0.1 C. The columbic efficiency was 88.1 %. The cell
was tested only until 40 cycles, but 90 % capacity retention
was achieved (Wang Q. et al., 2018). Ti doping of the138

LiNi0.80Co0.15Al0.05O2 cathode material improved the cycling stability considerably. The modified NCA with Sn doping was arranged chemically as LiNi0.80Co0.09Ti0.06Al0.05O2.
Good performance was achieved with a capacity retentionof 90.6 % after 500 cycles (Li J. et al., 2020).
NMC-622 (LiNi0.6Mn0.2Co0.2O2) with a nanoplate morphology showed excellent high-rate capability. The initial discharge capacity with a current rate of 0.2 C was
173 mAh/g. In further current rate tests at 20 °C, thecapacity retention was 67 % with a value of 77 mAh/g. The
cycling stability was tested until 100 cycles and reached
91 % (Liu et al., 2016). NMC-622 nano-rod morphology
showing good electrochemical performance with ~81 %capacity retention after 300 cycles (Yang et al., 2019).
Combination of two kinds of NMC cathode material thathave different molar composition of Ni, Mn, and Co showing good cycle with 70.3 % of capacity retention after 1000
cycles. This material is made by combining LiNi0.70Mn0.25
Co0.05O2 and LiNi0.58Mn0.25Co0.17O2. The final composition
is LiNi0.60Mn0.25Co0.15O2. Morphology analysis shows
spherical particle and the primary particle is rod-shapeparticle (Noh et al., 2013).
NH4H2PO4-doped NCA (LiNi0.815Co0.15Al0.035O2) with aneedle-like morphology electrochemical performance wastested. The initial discharge capacity of NCA with a 1 %mass was 195.3 mAh/g. This capacity was greater than thatof the pure NCA material with an initial discharge capacityof 172.3 mAh/g. The capacity retention was 70.2 % fromthe initial discharge specific capacity after 100 cycles (Tanget al., 2017). Another study of LiNi0.815Co0.15Al0.035O2
doped with an Al-gradient doped solution showing excellent electrochemical performance. The initial discharge
capacity was 187.5 mAh/g, and 93.4 % capacity retention
was achieved after 200 cycles (Duan et al., 2016). Al doping
was also performed to manufacture LiNi0.90Co0.07Al0.03O2.
The initial discharge capacity was 224.6 mAh/g and after
100 cycles, 93.4 % capacity retention was observed (Duanet al., 2018). Tungsten (W) was the alternative metal source
to replace Al. The presence of W greatly increased thecycling stability. LiNi0.90Co0.09W0.01O2 (NCW) exhibitedneedle-like primary particles. The initial discharge capacity was 231.2 mAh/g-1, which is greater than the NCA
cathode material (223.5 mAh/g). The cycling stability test
showed that the capacity of the NCW material was 92 %of the initial capacity. This result is more significant thanthe NCA material, with only 63 % of capacity retention(Ryu et al. (2019).). The effect of primary particles shapes
towards their electrochemical performance are summarizedin Table 3.

4.2 Secondary particles morphology of nickelbased cathode materials
The secondary particles of a Ni-rich cathode material

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149
Table 3The effect of nickel-rich cathode primary particles toward its electrochemical properties.

Material

Precursor/Modification

MorphologicalfeatureElectrochemical Properties(Capacity/Cycle/Rate)

Reference

NMC-811

NMC-811-OH/Modified
coprecipitation and solid-state

Nanosheet

195 mAh g–1/300 cycles/0.1 C(Xu et al., 2019)

NMC-811

NMC-OH/Modification of
Nanosheetammonia concentration controlled

201 mAh g–1/100 cycles/0.2 C(Su et al., 2018)

NMC-7 1.5 1.5

NMC precursor withsolvothermal method

Nanosheet

184.7 mAh g–1/100 cycles/0.1 C(Fu et al., 2014)

NMC-8.5 0.75 0.75

NMC precursor withhydrothermal method

Nanosheet

189.5 mAh g–1/300 cycles/0.2 C(Liu et al., 2019)

NMC-811

NMC-OH/TiO2 doping

Nano-flake

258 mAh g–1/150 cycles/1 C(Mo et al., 2020)

NCA

NCA-OH

Nano-flake

210.4 mAh g–1/40 cycles/0.1 C(Wang Q. et al.,2018)

NMC-622

NMC-OH

Nanoplate

173 mAh g–1/100 cycles/0.2 C(Liu et al., 2016)

Nanorod193.6 mAh g–1/300 cycles(Yang et al., 2019)(Noh et al., 2013)

NMC-622

NMC-OH

NMC-6 2.5 1.5Combination of NMC-7 2.5 0.5OH and NMC-5.8 2.5 1.7-OH

Rod-shape

206 mAh g–1/1000 cycles

NMC-5.4 3 1.6

Modification of Ni/Mn/Co
concentration gradient (FCG)

Nanorod183.7 mAh g–1/100 cycles(Noh et al., 2014)

NCA-8.15 1.5 0.35

NCA-OH/NH4H2PO4 doping

Needle-like

195.3 mAh g–1/200 cycles/0.1 C(Tang et al., 2017)

Needle-like

187.5 mAh g–1/200 cycles(Duan et al., 2016)

Needle-like

224.6 mAh g–1/100 cycles(Duan et al., 2018)(Ryu et al., 2019)

NCA-8.15 1.5 0.35
NCA-9 0.7 0.3

NCA-OH/Al-gradient-doped
NCA-OH/Al-doped

NCW-9 0.9 0.1

NCW-OH/Replacing Al with W

Needle-like

231.2 mAh g–1/200 cycles/0.1 C

NCA

Pre-oxidized method

Needle-like

175 mAh g–1/100 cycles(Zhang et al., 2018)

NCA

Solid state with controlled
crystallization

Needle-like

187.7 mAh g–1/100 cycles(Yang G. et al.,
2020)

NCA

Al-doping

Needle-like

171.4 mAh g–1/1000 cycles/1 C(Du et al., 2021)

consist of agglomerated primary particles that form a larger
and denser particle. Secondary particle formation reduces
the high surface area of primary particles if they are present
in singular particles (Barai et al., 2019). The reduction wasproven efficient in hindering unwanted reactions between
the active materials with the electrolyte (Qiu et al., 2017b;
Yudha et al., 2019). The morphology of the nickel-richcathode materials strongly depends on the synthesis process and the presence of additives that help control thesecondary particle shape.

4.2.1 Microsphere / spherical Particles
Coprecipitation of transitional metal with high-nickel
content is the most used technique to obtain micron-sized
spherical particles of the nickel-rich cathode. The sphericalmorphology of a particle was formed from the agglomeration of crystal nuclei into larger particles. The formationof large or secondary spherical particles is in accordancewith the Ostwald ripening mechanism, where the rateof crystal formation is in balance with the rate of crystal
dissolution (Seo and Lee, 2017). Extensive studies focusedon the effects of the synthesis parameters on the mor-

phology, such as pH, concentration, mixing speed, stirrer
type, reaction time, and precipitating agents (Zhu Q. et al.,2019). Hydroxide coprecipitation uses dissolved hydroxide
compounds, such as sodium hydroxide, lithium hydroxide,or potassium hydroxides, as the precipitating agent. An
ammonia solution is often introduced during the process
to reduce the reaction rate avoid uneven particle growth.
For hydroxide coprecipitation, the optimal pH to formhigh-density spherical secondary particles is 10–11 (Chenet al., 2018; Purwanto et al., 2018). The temperature during
the coprecipitation process also is a factor determining thefinal morphology. In most cases, hydroxide and carbonate
coprecipitation of nickel-rich cathode materials produced
dense micron-sized secondary particles, while oxalate
precipitation showed rock-like particles. Various chelating
agents were reported to replace ammonia during hydroxide and carbonate coprecipitation. Acid or base chelating
agents, such as EDTA, citric acid, sulfosalicylic acid, lactic
acid, or their conjugates, such as EDTA-2Na, and sodium
lactate, have been used as greener alternatives to ammonia.
The excessive use of ammonia can cause environmental
issues and health risks for humans and animals (Nam et139

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

al., 2015).
Quanzhong Zhu et al. (Zhu Q. et al., 2019) proposed
a formation mechanism for spherical or microspheres
secondary particle of Ni-rich cathode material in coprecipitation techniques. This began with crystal nuclei formation
during the initial precipitation of single-crystal primaryparticles. With time, these single-crystal particles agglomerate into polycrystalline grains. These polycrystalline
grains form initial secondary particles with rough surfaces
from the aggregated particles. Because the formation of
single-crystal nuclei occurs continuously, these primaryparticles are adsorbed onto the surface of the initial secondary particles. The process of single-crystal adsorption to theinitial secondary particle continues with time. The primaryparticles become smooth, and the secondary particles growwith dense properties due to a decrease in particle porosity.
In the nickel-rich cathode, the residence time to obtainsmooth micro-spherical particles increases with increasing
nickel content. The resulting microsphere particles alsoneed to be treated delicately during the lithiation process
because microsphere particles can be broken easily due tomechanical forces, such as the milling process.
In addition to coprecipitation, it was reported that thesol-gel, spray drying technique, and spray pyrolysis techniques can be adapted to produce micro-spherical particles.
For spray methods, spherical particles were formed by theformation of spherical droplets using a droplet maker, suchas nebulizer and spray nozzles (Kadota and Shirakawa,2021). The resulting droplets can be tuned easily. Thus,a more homogenous and consistent particle morphology
can be obtained. With the addition of additives to thespray solution, the produced particles can have a smoothmorphology. Table 4 lists the effects of chelating agentsfor nickel-rich cathode materials on their morphology andelectrochemical performance.
Based on Table 4 spherical shaped nickel-rich cathode materials have good electrochemical performances.
However, the perfectly shaped spherical particle withhigh density and relatively large particle size has higher
specific capacity, higher cycle retention and improved rateability. A High density and large secondary particle sizeof nickel-rich cathode material has better stability toward
undesired chemical reaction between electrolyte, whichsometimes has HF content, with the surface of the cathodeparticle that is related to its surface area. High density
spherical particles with narrow particle size distribution
also improve the overall density of the particle due to better packing factor. Thus, this type of particle has multiple
benefits compared to the other shape particles.
According to multiple researches, spherical particle withnarrow distribution can be obtained via coprecipitation
method which tightly controlled its process parameters.
Spherical particle with high tap density often achieved bya strict control of pH level, which depends on the compo-

140

sition of the metals, temperature of coprecipitation, flow
rates, retention time and more importantly ageing process.
Extensively large secondary particles can cause poor Li-ion
transfer during the charge and discharge process. Thus,
product optimization via control of particle size distribution is highly required knowledge for the development ofnickel-rich cathode materials.

4.2.2 Non-spherical/agglomerated particles
Several studies have reported the formation of sphericalNi-rich cathode materials, as listed in Table 4. In microsphere particles, however, micro-cracks in secondary
particles are often occurring. These micro-cracks increase
exposure to the internal areas of the particles, which promote unwanted reactions causing rapid capacity fading(Kleiner et al., 2015; Yoon et al., 2017). Furthermore, theyalso increase the bulk density of the overall particles. Somestudies stated that non-spherical particles are preferred
to avoid the formation of particle grain cracks. However,non-spherical particles with a low density are not preferredbecause they will also suffer from particle breakage during
the electrochemical charge-discharge process.
The formation of non-spherical/agglomerated nickelrich cathode material particles is often found in theliterature (Purwanto et al., 2020). Qiu et al. reported thatpolyhedral-shaped particles could be produced by oxalic
acid crystallization of NCA cathode material produce(Qiu et al., 2017a; 2017b). Using the same crystallization/
precipitating agent, Wu (Wu et al., 2015) claimed thatmicro-rod particles of NCA have better compaction factors
than spherical particles, which can avoid micro-cracks
even when it was cycled at high temperature. Zheng etal. precipitated Ni, Co, and Mn using ammonium oxalate,
producing a rod-shaped precursor. After high sinteringlithiation, however, the morphology of the precursor
changed from rod to rock-like particles (Zeng and Zhang,2020) A urea-assisted hydrothermal technique was developed to produce silkworm-like NMC811 particles, butslight particle cracking was observed (Fig. 5a,b,c) after thematerial was cycled 100 times (Lei et al., 2019b; Zhang etal., 2017). Therefore, micro-cracking and particle breakage
would likely occur when repeatedly used especially at highrate and high operating temperature.

4.3 Single crystal
Micron-sized single crystals of Ni-rich cathode havebeen successfully developed. Single crystal has a large energy density owing to its pore-free and high strength (Duanet al., 2017; Li et al., 2018). This particle was pioneered
because polycrystalline materials are prone to intergranularfracture during battery cell operation (Qian et al., 2020).
Although the polycrystalline particles are randomly
oriented, this intergranular fracture is caused by primaryLNO(LiNiO2)NFA(LiNi0.8Fe0.15Al0.05O2)
LNMO(LiNi0.9Mn0.1O2)

NMC-7 1.5 1.5(LiNi0.7Mn0.15Co0.15O2)
NMC-712(LiNi0.7Mn0.1Co0.2O2)
NMC-811

NMC-622

Spherical particles, 5–13 µm
Dense spherical particles, 6–21 µm
near-spherical particles, 200–500 nm
Quasi-spherical with 300–800 nm
primary particle
Dense spherical particles, 14–16 µm
Dense spherical particles, ~10 µm

Sodium lactate
Ammonia
Ammonia
Citric acid

Ammonia
Ammonia
Citric acid
Ammonia
Ammonia + NH4F

Coprecipitation

Coprecipitation
Coprecipitation

Sol-gelSpray pyrolysis
Coprecipitation
Coprecipitation
Sol-gelCoprecipitation

Coprecipitation

Ammonia
Ammonia
Ammonia
Ammonia

Coprecipitation

Coprecipitation

Coprecipitation
Coprecipitation

Spray pyrolysis

Spherical particle, ~3 µm
Spherical particle

Spherical particle, ~10 µm

Submicron particles from sphericalparticle breakage
Spherical particle, ~8–10 µm

Spherical particles, 1 µm
Spherical particles, 6–8 µm

Flame spray pyrolysis
Hydro/Solvothermal
Ethylene glycol

Dense spherical particles, ~12 µm

Coprecipitation-Spray Dry Ammonia

Spherical particles, 800 nm

Quasi-spherical particles, < 8 µm
Quasi-spherical particles, < 1.2 µm

Quasi-spherical particles, ~4 µm

Ammonia

Coprecipitation

Spherical and hollow particles,
10–50 µm
Dense spherical particles, 10–20 µm

Citric acid

Spherical particles, ~1 µm

Spray drying

Spray pyrolysis

Dense spherical particles, ~10 µm
Dense spherical particles, ~10 µm

Quasi-spherical
Spherical, 10–20 µm

Citric acid-Ethylene
glycol-DCCA

Coprecipitation
Coprecipitation

Dense spherical particles, ~4–8 µm

Urea
Glycerol

EDTA
Ammonia

Coprecipitation

Dense spherical particle, 4–6 µm

Flame spray pyrolysis
Spray drying

5-Sulfosalicylic acid

Coprecipitation

Dense spherical particles, 5–12 µm

Spherical/yolk shell particles, 1.1–1.6 µm

Ammonia

Coprecipitation

NCA

Morphological feature

Spray pyrolysis

Chelating agents/
Additives
Ammonia

Methods

Summary of Ni-rich cathode synthesis techniques toward its properties.

Cathode materials

Table 4172 mAh/g/94 % after 100 cycles at
1 C/143 mAh/g at 10 C
201 mAh/g/78 % after 100 cycles at
0.1 C/~120 mAh/g at 5 C
155 mAh/g/96 % after 30 cycles at 0.5 C/186 mAh/g/95 % after 10 cycles at
0.5 C/~50 mAh/g at 5 C
174 mAh/g/87 % after 100 cycles at
1 C/~70 mAh/g at 10 C—
185 mAh/g/95 % after 50 cycles at 0.2 C/164 mAh/g/-/205 mAh/g/86.24 % after 100
cycles/137 mAh/g at 5 C
202 mAh/g/96 % after 200 cycles at
1 C/~54 mAh/g at 10 C
202 mAh/g/94 % after 100 cycles at
2 C/~141 mAh/g at 10 C
~175 mAh/g/86 % after 100 cycles at
1 C/~130 mAh/g at 10 C
178 mAh/g/85 % after 25 cycles at 1 C/201 mAh/g/81 % after 100 cycles at
0.1 C/142 mAh/g at 10 C
197 mAh/g/93 % after 80 cycles at
1 C/173 mAh/g at 5 C
190 mAh/g/88 % after 100 cycles at
0.33 C/110 mAh/g at 1 C~220 mAh/g/86 % after 100 cycles at
0.5 C/~145 mAh/g at 10 C
197 mAh/g/94 % after 100 cycles at 0.2 C/216 mAh/g/80 % after 200 cycles at
1 C/121 mAh/g at 5 C

225 mAh/g/89 % after 49 cycles at
0.2 C/129 mAh/g at 1 C
124 mAh/g/81 % after 200 cycle at 0.5 C/200 mAh/g/91 % after 200 cycles at
1 C/130 mAh/g at 5 C
188 mAh/g/94 % after 100 cycles at 0.5 C/-

Electrochemical Performance (Capacity/Cycle/
Rate)
196 mAh/g/95 % after 50 cycles/150 mAh/g
at 2 C
206 mAh/g/80 % after 50 cycles at
55 °C/~130 mAh/g at 5 C 55 °C
203 mAh/g/90 % after 200 cycles at
1 C/174 mAh/g at 1 C
193 mAh/g/90 % after 100 cycles at 1 C/183 mAh/g/91 % after 100 cycles at
1 C/140 mAh/g at 5 C
218 mAh/g/100 % after 20 cycles at 0.1 C/-(Ma et al., 2020)(Mu et al., 2020)(Sun et al., 2013)(Muralidharan et al., 2020)(Li Yan et al., 2018)(Abram et al., 2019)(Gu et al., 2021)(Huang et al., 2019)(Yue et al., 2013)(Duan et al., 2020)(Tian et al., 2018)(Lu et al., 2014)(Zhang et al., 2012)(Dong et al., 2019)(Lee et al., 2016)(Fu et al., 2011)(Ronduda et al., 2020)(Xu et al., 2018)(Liang et al., 2014)(Park and Chan Kang, 2014)(Nurcahyani et al., 2020)(Zhang J. et al., 2020)(Yang et al., 2014)(Ju et al., 2010)(Xie et al., 2016)(Seo and Lee, 2017)(Xie et al., 2015)(Kim et al., 2014)(Hu et al., 2012)

Reference

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

141

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

particles pushing against each other, causing significant
pressure (Langdon and Manthiram, 2021). The methods
were used for the synthesis of precursors and cathodematerials including co-precipitation, molten salt and spraypyrolysis (Table 5). Xing Xu et al. succeeded in producing
radially aligned single-crystal hydroxide precursors of
NMC 811. The two aspects examined were optimizing theammonia concentration as a precipitating agent and thestirring speed. A high ammonia concentration (8 mol/L inthis study) can adjust and promote the direction of growthof the primary particles. A high stirring speed can resultin strong and homogeneous mechanical agitation, which
prevents the nucleation and re-agglomeration of small
secondary particles (Xu et al., 2019). Xinming Fan et al.
examined the morphology of the precursor and NMC
831106 material after sintering, as shown in Fig. 6.

The NMC precursors showed a good secondary flower
morphology. After sintering, the particles became micronsized particles with a smooth surface (Fan et al., 2020).
Another study, the synthesis of single-crystal Ni-rich with
NaCl flux was carried out. NaCl functions as a growth
flux for primary particles, reducing the temperature andsintering time (Bi et al., 2020; Lee et al., 2020). Jie Zhu etal. used spray pyrolysis method to produce a single crystal
NMC 811. The precursor was synthesized from a chloride
salt solution that was then aerosolized using an ultrasonicnebulizer and passed through a furnace tube at 800 °C. The
microsphere, fine size, and mesoporous precursors wereobtained from this method (Zhu et al., 2020).
Fig. 7 shows the effect of morphology of nickel-rich cath­ode towards its likability to pulverized during prolonged
charge-discharge process. In contrast to nickel-based

Fig. 5 (a,b) Silkworm like NMC811 particles before cycles and (c) after 100 cycles, reprinted with permission from Ref. (Lei et al., 2019b) Copyright(2019) Elsevier B.V.
Table 5Single crystal nickel-rich cathode materials.

SampleSynthesis
methodPrecursor

T (°C)

Particle
size (µm)

Specific capacity

Ref.

NMC-761410

Coprecipitationand molten salt

Hydroxide precursor

9003

182.3 mAh/g at 0.1 C(Bi et al., 2020)

NMC-811

Coprecipitation

Hydroxide precursor

740—

197.9 mAh/g at 0.1 C(Xu et al., 2019)

NMC-811

Spray pyrolysis

Oxide precursor

900

1–5

211 mAh/g at 0.1 C(Zhu et al., 2020)

NMC-811

Coprecipitation
or molten salt

850

1

—

(Zhu and Chen, 2019)

NMC-811

Coprecipitation

Hydroxide precursor

830

1–4

—

(Yang C. et al., 2020)

NMC-811

Commercial

Hydroxide precursor

800–960

1–1.5

194 mAh/g at 0.1 C(Zhao et al., 2019)

NMC-910603 Coprecipitation

Hydroxide precursor

820

1–2.5

203.8 mAh/g at 0.1 C(Lee et al., 2020)

NCA-880903

Coprecipitation

Hydroxide precursor

840

4–5

240 mAh/g at 0.1 C(Zhang H. et al., 2020)

LNO

Commercial

Hydroxide precursor

800

—

—

(Weber et al., 2020)

Fig. 6 Morphology and elemental distribution in single crystal NMC. SEM images of (a) precursor and (b,c) sintered single crystal NMC, reprinted
with permission from Ref. (Fan et al., 2020) Copyright (2020) Elsevier B.V.

142

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

Fig. 7

Schematic illustration of secondary particle cracking phenomena in various nickel-rich cathode material.

anode, over exposure of electrolyte with the surface ofnickel-rich cathode materials can promote the formationof inactive phases due to the reaction of nickel with electrolyte. On the exposed surface created due to particle
pulverization, a new SEI layer also occur which increase
the impedance and Li-ion mobility resistance, thus lower
the electrochemical properties. In Fig. 7, microcracks often
occurs in a particle with visible agglomeration of primaryparticles.

5. Current advances and future projection
Applications of lithium-ion batteries that require highspecific energy coupled with lower prices have encouraged
the development of nickel-based electrodes. The successfulof NCA and NMC materials, especially for electric vehicles,
has made researchers constantly develop these materials.
But, cobalt, which was originally doped for the material,
is reconsidered because of its relatively high price. Thus,
cobalt-free and nickel-rich materials were raised to be
popular in the future. Various attempts were made to obtainsuperior material, especially for the morphology of the material. Currently, several efforts were determined to directly
control the morphology of nickel containing particles using
scalable, continuous and rapid method such as via fastdrying, flash spray pyrolysis, vapor phase deposition, laser
techniques, plasma assisted techniques, and fast crystalli-zation. Thus, it opens a new opportunity to directly tune themorphology of nickel-based material that concern towards
the overall feasibility and economical aspect (Purwanto etal., 2018; L. Wang et al., 2018).
It has been mentioned in the previous section that themorphology of the cathode material directly affects theelectrochemical performance. Thus, efforts to get themost favorable morphology need to be done by modifying
the synthesis parameters. First, doping modifications arecarried out in order to make the morphology more regular(Ryu et al., 2019). Some dopant can affect the primaryparticle thereby increasing the stability of the cycle, previously assigned to cobalt. Second, the morphology for bothcobalt-free and Ni-rich materials is single crystal. Materials
with high nickel content have a limited life cycle due totheir greater surface-electrolyte reactivity and lower structural integrity. Single-crystal proved to be able to limit thesurface reactivity and cracking of these particles (Langdon
and Manthiram, 2021). However, single crystal materials
still face challenges in terms of irreversible structural degradation and longer ionic transport pathways. Small cracks
in single crystal can also block Li+ transport (Wang et al.,2021). These challenges may be interesting to research forthe future.

143

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

6. Conclusion
Thorough morphological analysis of nickel-based electrodes for Li-ion batteries was performed. Materials, suchas nickel oxide, nickel hydroxide, nickel oxalates, andnickel sulfide, can be applied to Li-ion batteries. However,unique morphological features, such as shapes and nano­scale sizes of such materials, are strongly required. The
nano-scaled unique morphology of the nickel-based anodecan suppress the large lithium irreversibility and increase
its electrical and electrochemical features.
Numerous studies on the morphological tuning of nickelrich cathode materials have been reported. Among othermorphologies, micron-sized spherical particles are largely
applied and used, even commercialized in Li-ion batteries.
However, spherical particles suffer from micro-cracking,which can cause rapid capacity decay and cell chemistry
failures. Non-spherical secondary polycrystalline particles
have also been studied; however, the particles still havemicro-cracking problems. A crack-free single-crystalline
morphology is currently the focus of research, and techniques to obtain such particles in a nickel-rich cathode arestill under development due to several problems:(1) High-temperature sintering, which favors the formation of the rock salt phase and large Li-loss;(2) Flux induced synthesis, which reduces the contact
between the oxidative atmosphere and is crucial forstable nickel-rich cathodes formation;(3) Post-production handling, such as milling and storage,
is necessary in low humidity areas for a high-nickel
content cathode.
In a morphological perspective, extensive morphological tuning for the race toward stable, long life cycle,
nickel-based electrodes are being performed continuously
and will always be considered for the next generation of
secondary energy storage. The morphology of nickel-based
active materials is one of the major determining factors forhigh-performance Li-ion batteries.

Acknowledgment
This paper is supported by Indonesia Endowment
Fund for Education (LPDP / Lembaga Pengelola Dana
Pendidikan) through Pendanaan Riset Inovatif Produk(Rispro) Invitasi grant no.PRJ-6/LPDP/2020.

References
Abram C., Shan J., Yang X., Yan C., Steingart D., Ju Y., Flameaerosol synthesis and electrochemical characterization of
Ni-rich layered cathode materials for Li-ion batteries, ACS
Applied Energy Materials, 2 (2019) 1319–1329. DOI:

144

10.1021/acsaem.8b01892
Barai P., Feng Z., Kondo H., Srinivasan V., Multiscale computational model for particle size evolution during coprecipitationof Li-ion battery cathode precursors, Journal of Physical
Chemistry B, 123 (2019) 3291–3303. DOI: 10.1021/acs.
jpcb.8b12004
Bi Y., Tao J., Wu Y., Li L., Xu Y., Hu E., Wu B., Hu J., Wang C.,
Zhang J.G., Qi Y., Xiao J., Reversible planar gliding andmicrocracking in a single-crystalline Ni-rich cathode, Science, 370 (2020) 1313–1318. DOI: 10.1126/science.abc3167
Chen T., Li X., Wang H., Yan X., Wang L., Deng B., Ge W.,
Qu M., The effect of gradient boracic polyanion-doping
on structure, morphology, and cycling performance of
Ni-rich LiNi0.8Co0.15Al0.05O2 cathode material, Journal ofPower Sources, 374 (2018) 1–11. DOI: 10.1016/j.jpowsour.
2017.11.020
Dewangan A., Patel A., Bhadania A., Stainless steel for dairy andfood industry: a review, Journal of Material Science & Engineering, 4 (2015) 1–4. DOI: 10.4172/2169-0022.1000191
Dong S., Zhou Y., Hai C., Zeng J., Sun Y., Shen Y., Li X., Ren X.,
Qi G., Zhang X., Ma L., Ultrathin CeO2 coating for improved
cycling and rate performance of Ni-rich layered LiNi0.7
Co0.2Mn0.1O2 cathode materials, Ceramics International, 45(2019) 144–152. DOI: 10.1016/j.ceramint.2018.09.145
Du F., Li X., Wu L., Hu D., Zhou Q., Sun P., Xu T., Mei C., Hao
Q., Fan Z., Zheng J., Tailoring the Al distribution in secondary particles for optimizing the electrochemical performanceof LiNi0.8Co0.1Mn0.1O2, Ceramics International, (2021). DOI:
10.1016/j.ceramint.2021.01.161
Du M., Li Q., Pang H., Oxalate-derived porous prismatic
nickel/nickel oxide nanocomposites toward lithium-ion
battery, Journal of Colloid and Interface Science, 580 (2020)
614–622. DOI: 10.1016/j.jcis.2020.07.009
Du Y., Ma H., Guo M., Gao T., Li H., Random oriented hexagonal
nickel hydroxide nanoplates grown on graphene as binder
free anode for lithium ion battery with high capacity, Chemical Physics Letters, 699 (2018) 167–170. DOI: 10.1016/j.
cplett.2018.03.056
Duan J., Dong P., Wang D., Li X., Xiao Z., Zhang Y., Hu G., A
facile structure design of LiNi0.90Co0.07Al0.03O2 as advanced
cathode materials for lithium ion batteries via carbonation
decomposition of NaAl(OH)4 solution, Journal of Alloys
and Compounds, 739 (2018) 335–344. DOI: 10.1016/j.
jallcom.2017.12.236
Duan J., Hu G., Cao Y., Tan C., Wu C., Du K., Peng Z., Enhanced
electrochemical performance and storage property of
LiNi0.815Co0.15Al0.035O2 via Al gradient doping, Journalof Power Sources, 326 (2016) 322–330. DOI: 10.1016/j.
jpowsour.2016.07.008
Duan J., Wu C., Cao Y., Huang D., Du K., Peng Z., Hu G.,
Enhanced compacting density and cycling performance of
Ni-riched electrode via building mono dispersed micronscaled morphology, Journal of Alloys and Compounds, 695(2017) 91–99. DOI: 10.1016/j.jallcom.2016.10.158
Duan J., Zhang R., Zhu Q., Xiao H., Huang Q., The effect ofcontrolling strategies of pH and ammonia concentration on
preparing full concentration gradient Ni0.8Co0.1Mn0.1(OH)2
via coprecipitation in a pilot-scale reactor, Energy Technology, 8 (2020) 1–12. DOI: 10.1002/ente.201901437
Elbert P., Onder C., Gisler H.J., Capacitors vs. batteries in a serial
hybrid electric bus, IFAC Proceedings Volumes (IFACPapersOnline), 43 (2010) 252–257. DOI: 10.3182/201007123-DE-2013.00020
Fan X., Hu G., Zhang B., Ou X., Zhang J., Zhao W., Jia H., Zou
L., Li P., Yang Y., Crack-free single-crystalline Ni-rich lay-Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

ered NCM cathode enable superior cycling performance oflithium-ion batteries, Nano Energy, 70 (2020) 104450. DOI:
10.1016/j.nanoen.2020.104450
Fu C., Li G., Luo D., Li Q., Fan J., Li L., Nickel-rich layered
microspheres cathodes: lithium/nickel disordering and electrochemical performance, ACS Applied Materials and Interfaces, 6 (2014) 15822–15831. DOI: 10.1021/am5030726
Fu C., Zhou Z., Liu Y., Zhang Q., Zheng Y., Li G., Synthesis andelectrochemical properties of Mg-doped LiNi0.6Co0.2Mn0.2O2
cathode materials for li-ion battery, Journal Wuhan University of Technology, Materials Science Edition, 26 (2011)
211–215. DOI: 10.1007/s11595-011-0199-z
Geng H., Kong S.F., Wang Y., NiS nanorod-assembled nanoflowers grown on graphene: morphology evolution and Li-ion
storage applications, Journal of Materials Chemistry A, 2
(2014) 15152–15158. DOI: 10.1039/c4ta03440f
Gu H., Wang J., Wang Z., Tong J., Qi N., Han G., Zhang M.,
Self-assembled porous LiNi0.8Co0.1Mn0.1O2 cathode materials with micro/nano-layered hollow morphologies for highpower lithium-ion batteries, Applied Surface Science, 539(2021) 148034. DOI: 10.1016/j.apsusc.2020.148034
Hu G., Liu W.M., Peng Z., Dua K., Cao Y.B., Du K., Cao Y.B., Synthesis and electrochemical properties of LiNi0.8Co0.15Al0.05O2
prepared from the precursor Ni0.8Co0.15Al0.05OOH, Journalof Power Sources, 198 (2012) 258–263. DOI: 10.1016/j.
jpowsour.2011.09.101
Huang B., Li X., Wang Z., Guo H., Xiong X., Synthesis of
Mg-doped LiNi0.8Co0.15Al0.05O2 oxide and its electrochemical behavior in high-voltage lithium-ion batteries, Ceramics
International, 40 (2014) 13223–13230. DOI: 10.1016/j.
ceramint.2014.05.029
Huang B., Liu D., Zhang L., Qian K., Zhou K., Cai X., Kang
F., Li B., An efficient synthetic method to prepare highperformance Ni-rich LiNi0.8Co0.1Mn0.1O2 for lithium-ion batteries, ACS Applied Energy Materials, 2 (2019) 7403–7411.
DOI: 10.1021/acsaem.9b01414
Huang X.H., Tu J.P., Xia X.H., Wang X.L., Xiang J.Y., Zhang L.,
Zhou Y., Morphology effect on the electrochemical performance of NiO films as anodes for lithium ion batteries, Journal of Power Sources, 188 (2009) 588–591. DOI: 10.1016/j.
jpowsour.2008.11.111
Hwang I., Lee C.W., Kim J.C., Yoon S., Particle size effect of
Ni-rich cathode materials on lithium ion battery performance, Materials Research Bulletin, 47 (2012) 73–78. DOI:
10.1016/j.materresbull.2011.10.002
Ju S.H., Kim J.H., Kang Y.C., Electrochemical properties of
LiNi0.8Co0.2–xAlxO2 (0 ≤ x ≤ 0.1) cathode particles preparedby spray pyrolysis from the spray solutions with and without
organic, Metals and Materials International, 16 (2010)
299–303. DOI: 10.1007/s12540-010-0421-0
Kadota K., Shirakawa Y., Particle preparation and morphology
control with mutual diffusion across liquid-liquid interfaces,
KONA Powder and Particle Journal, 38 (2021) 122–135.
DOI: 10.14356/kona.2021006
Kalyani P., Kalaiselvi N., Various aspects of LiNiO2 chemistry:a review, Science and Technology of Advanced Materials, 6(2005) 689–703. DOI: 10.1016/j.stam.2005.06.001
Kim C., Park T.-J., Min S.-G., Yang S.-B., Son J.-T., Effects ofiron doping at 55 °C on LiNi0.85Co0.10Al0.05O2, Journal of the
Korean Physical Society, 65 (2014) 243–247. DOI: 10.3938/
jkps.65.243
Kleiner K., Dixon D., Jakes P., Melke J., Yavuz M., RothC., Nikolowski K., Liebau V., Ehrenberg H., Fatigue of
LiNi0.8Co0.15Al0.05O2 in commercial Li ion batteries, Journalof Power Sources, 273 (2015) 70–82. DOI: 10.1016/j.

jpowsour.2014.08.133
Langdon J., Manthiram A., A perspective on single-crystal
layered oxide cathodes for lithium-ion batteries, Energy
Storage Materials, 37 (2021) 143–160. DOI: 10.1016/j.
ensm.2021.02.003
Lee J.H., Kim H.H., Wee S.B., Paik U., Effect of additives on
the dispersion properties of aqueous based C/LiFePO4 paste
and its impact on lithium ion battery high power properties,
KONA Powder and Particle Journal, 27 (2009) 239–245.
DOI: 10.14356/kona.2009022
Lee S.H., Sim S.J., Jin B.S., Kim H.S., High performancewell-developed single crystal LiNi0.91Co0.06Mn0.03O2 cathodevia LiCl-NaCl flux method, Materials Letters, 270 (2020)
127615. DOI: 10.1016/j.matlet.2020.127615
Lee S.W., Kim H., Kim M.S., Youn H.C., Kang K., Cho B.W.,
Roh K.C., Kim K.B., Improved electrochemical performanceof LiNi0.6Co0.2Mn0.2O2 cathode material synthesized by citricacid assisted sol-gel method for lithium ion batteries, Journalof Power Sources, 315 (2016) 261–268. DOI: 10.1016/j.
jpowsour.2016.03.020
Lei Y., Ai J., Yang S., Jiang H., Lai C., Xu Q., Effect of flowerlike Ni(OH)2 precursors on Li+/Ni2+ cation mixing andelectrochemical performance of nickel-rich layered cathode,
Journal of Alloys and Compounds, 797 (2019a) 421–431.
DOI: 10.1016/j.jallcom.2019.05.065
Lei Y., Ai J., Yang S., Lai C., Xu Q., Nb-doping in LiNi0.8
Co0.1Mn0.1O2 cathode material: Effect on the cycling stability
and voltage decay at high rates, Journal of the Taiwan
Institute of Chemical Engineers, 97 (2019b) 255–263. DOI:
10.1016/j.jtice.2019.02.006
Li B., Gu P., Feng Y., Zhang G., Huang K., Xue H., Pang H.,
Ultrathin nickel–cobalt phosphate 2D nanosheets for electrochemical energy storage under aqueous/solid-state electrolyte, Advanced Functional Materials, 27 (2017) 1605784.
DOI: 10.1002/adfm.201605784
Li C., Xue Z., Qin J., Sawangphruk M., Yu P., Zhang X., Liu R.,
Synthesis of nickel hydroxide/delaminated-Ti3C2 MXene
nanosheets as promising anode material for high performance lithium ion battery, Journal of Alloys and Compounds,
842 (2020) 155812. DOI: 10.1016/j.jallcom.2020.155812
Li F., Kong L., Sun Y., Jin Y., Hou P., Micron-sized monocrystalline LiNi1/3Co1/3Mn1/3O2 as high-volumetric-energy-density
cathode for lithium-ion batteries, Journal of Materials Chemistry A, 6 (2018) 12344–12352. DOI: 10.1039/c8ta03363c
Li J., Liu M., An J., Tian P., Tang C., Jia T., Butt F.K., Yu D.,
Bai W., Cao C., Feng X., The synergism of nanoplates with
habit-tuned crystal and substitution of cobalt with titanium in
Ni-rich LiNi0.80Co0.15Al0.05O2 cathode for lithium-ion batteries, Journal of Alloys and Compounds, 829 (2020) 154555.
DOI: 10.1016/j.jallcom.2020.154555
Li Yan, Li X., Wang Z., Guo H., Wang J., Spray pyrolysis
synthesis of nickel-rich layered cathodes LiNi1–2xCoxMnxO2(x = 0.075, 0.05, 0.025) for lithium-ion batteries, Journalof Energy Chemistry, 27 (2018) 447-450. DOI: 10.1016/j.
jechem.2017.11.025
Li Y., Pan G., Xu W., Yao J., Zhang L., Effect of Al substitution on
the microstructure and lithium storage performance of nickelhydroxide, Journal of Power Sources, 307 (2016) 114–121.
DOI: 10.1016/j.jpowsour.2015.12.129
Li Yanwei, Xu W., Xie Z., Zhang L., Yao J., Structure and lithium
storage performances of nickel hydroxides synthesized withdifferent nickel salts, Ionics, 23 (2017) 1625–1636. DOI:
10.1007/s11581-017-1983-3
Liang L., Du K., Peng Z., Cao Y., Duan J., Jiang J., Hu G., Coprecipitation synthesis of Ni0.6Co0.2Mn0.2(OH)2 precursor and145

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

characterization of LiNi0.6Co0.2Mn0.2O2 cathode material forsecondary lithium batteries, Electrochimica Acta, 130 (2014)
82–89. DOI: 10.1016/j.electacta.2014.02.100
Liu W., Hua W., Zheng Z., Zhong B., Zhang Z., Facile synthesisof hierarchical porous Ni-rich LiNi0.6Co0.2Mn0.2O2 cathodematerial with superior high-rate capability, Ionics, 22 (2016)
1781–1790. DOI: 10.1007/s11581-016-1710-5
Liu Y., Yao W., Lei C., Zhang Q., Zhong S., Yan Z., Ni-richoxide LiNi0.85Co0.05Mn0.1O2 for lithium ion battery: effect of
microwave radiation on its morphology and electrochemical
property, Journal of The Electrochemical Society, 166 (2019)
A1300–A1309. DOI: 10.1149/2.0151908jes
Long P., Xu Q., Peng G., Yao X., Xu X., NiS nanorods as cathodematerials for all-solid-state lithium batteries with excellent
rate capability and cycling stability, ChemElectroChem, 3(2016) 764–769. DOI: 10.1002/celc.201500570
Lu X., Zhang N., Jahn M., Pfleging W., Improved capacity retention of SiO2 -coated LiNi0.6Mn0.2Co0.2O2 cathode material for
lithium-ion batteries, Applied Sciences, 9 (2019) 3671. DOI:
10.3390/app9183671
Lu Z.G., Tan X.X., Tang Y.G., Zhou K.C., LiNi0.7Co0.15Mn0.15O2
microspheres as high-performance cathode materials forlithium-ion batteries, Rare Metals, 33 (2014) 608–614. DOI:
10.1007/s12598-013-0097-y
Ma L., Su L., Zhang J., Zhao D., Qin C., Jin Z., Zhao K., A controllable morphology GO/PANI/metal hydroxide composite
for supercapacitor, Journal of Electroanalytical Chemistry,
777 (2016) 75–84. DOI: 10.1016/j.jelechem.2016.07.033
Ma R., Zhao Z., Fu J., Lv H., Li C., Wu B., Mu D., Wu F., Tuning
cobalt-free nickel-rich layered LiNi0.9Mn0.1O2 cathode material for lithium-ion batteries, ChemElectroChem, 7 (2020)
2637–2642. DOI: 10.1002/celc.202000443
Ma Z., Yuan X., Zhang Z., Mei D., Li L., Ma Z.F., Zhang L., YangJ., Zhang J., Novel flower-like nickel sulfide as an efficientelectrocatalyst for non-aqueous lithium-air batteries, Scientific Reports, 5 (2015) 1–9. DOI: 10.1038/srep18199
Mi L., Chen Y., Wei W., Chen W., Hou H., Zheng Z., Large-scaleurchin-like micro/nano-structured NiS: controlled synthesis,
cation exchange and lithium-ion battery applications, RSC
Advances, 3 (2013) 17431–17439. DOI: 10.1039/c3ra42859a
Mo Y., Guo L., Jin H., Du B., Cao B., Chen Yigao, Li D., Chen
Yong, Building nickel-rich cathodes with large concentration
gradient for high performance lithium-ion batteries, Journalof Power Sources, 468 (2020) 228405. DOI: 10.1016/j.
jpowsour.2020.228405
Mu L., Kan W.H., Kuai C., Yang Z., Li L., Sun C.J., Sainio S.,
Avdeev M., Nordlund D., Lin F., Structural and electrochemical impacts of mg/mn dual dopants on the LiNiO2 cathode in
Li-metal batteries, ACS Applied Materials and Interfaces, 12(2020) 12874–12882. DOI: 10.1021/acsami.0c00111
Muralidharan N., Essehli R., Hermann R.P., Parejiya A., AminR., Bai Y., Du Z., Belharouak I., LiNixFeyAlzO2, a newcobalt-free layered cathode material for advanced Li-ion
batteries, Journal of Power Sources, 471 (2020) 228389.
DOI: 10.1016/j.jpowsour.2020.228389
Nam K.M., Kim H.J., Kang D.H., Kim Y.S., Song S.W., Ammoniafree coprecipitation synthesis of a Ni-Co-Mn hydroxide precursor for high-performance battery cathode materials, Green
Chemistry, 17 (2015) 1127–1135. DOI: 10.1039/c4gc01898b
Ni S., Li T., Lv X., Yang X., Zhang L., Designed constitutionof NiO/Ni nanostructured electrode for high performancelithium-ion battery, Electrochimica Acta, 91 (2013) 267–274.
DOI: 10.1016/j.electacta.2012.12.113
Nitta N., Wu F., Lee J.T., Yushin G., Li-ion battery materials:
present and future, Materials Today, 18 (2015) 252–264.

146

DOI: 10.1016/j.mattod.2014.10.040
Noh H.J., Chen Z., Yoon C.S., Lu J., Amine K., Sun Y.K., Cathodematerial with nanorod structure—an application for advanced
high-energy and safe lithium batteries, Chemistry of Materials, 25 (2013) 2109–2115. DOI: 10.1021/cm4006772
Noh H.J., Ju J.W., Sun Y.K., Comparison of nanorod-structured
Li[Ni0.54Co0.16Mn0.30]O2 with conventional cathode materials
for li-ion batteries, ChemSusChem, 7 (2014) 245–252. DOI:
10.1002/cssc.201300379
Nurcahyani C., Anjani A.E., Purwanto A., Yudha C.S., Hasanah
L.M., Dyartanti E.R., Nur A., Flame-assisted spray pyrolysis
of lithium nickel cobalt aluminum oxide leaching stream,
AIP Conference Proceedings, 2219 (2020) 030003. DOI:
10.1063/5.0003156
Oh H.J., Jo C.H., Yoon C.S., Yashiro H., Kim S.J., Passerini S.,
Sun Y.K., Myung S.T., Nickel oxalate dihydrate nanorods
attached to reduced graphene oxide sheets as a high-capacity
anode for rechargeable lithium batteries, NPG Asia Materials, 8 (2016) e270. DOI: 10.1038/am.2016.59
Park G.D., Chan Kang Y., Characteristics of precursor powders
of a nickel-rich cathode material prepared by a spray drying
process using water-soluble metal salts, RSC Advances, 4(2014) 44203–44207. DOI: 10.1039/c4ra08524h
Purwanto A., Yudha C.S., Ikhwan Muhammad K., Algifari B.G.,
Widiyandari H., Sutopo W., Synthesis of LiNi0.8Co0.15Al0.05O2
cathode material via flame-assisted spray pyrolysis method,
Advanced Powder Technology, 31 (2020) 1674–1681. DOI:
10.1016/j.apt.2020.01.035
Purwanto A., Yudha C.S., Ubaidillah U., Widiyandari H., Ogi T.,
NCA cathode material: synthesis methods and performanceenhancement efforts NCA cathode material: synthesis
methods and performance enhancement efforts, Materials
Research Express, 5 (2018) 122001. DOI: 10.1088/20531591/aae167
Qian G., Zhang Y., Li L., Zhang R., Xu J., Cheng Z., Xie S.,
Wang H., Rao Q., He Y., Shen Y., Chen L., Tang M., Ma
Z., Single-crystal nickel-rich layered-oxide battery cathodematerials: synthesis, electrochemistry, and intra-granularfracture, Energy Storage Materials, 27 (2020) 140–149. DOI:
10.1016/j.ensm.2020.01.027
Qiu H., Du T., Wu J., Wang Y., Liu J., Ye S., Liu S., Towards
deriving Ni-rich cathode and oxide-based anode materials
from hydroxides by sharing a facile co-precipitation method,
Dalton Transactions, 47 (2018) 6934–6941. DOI: 10.1039/
c8dt00893k
Qiu Z., Zhang Y., Wang D., Xia S., A ternary oxide precursor withtrigonal structure for synthesis, Solid State Electrochem, 21(2017a) 3037–3046. DOI: 10.1007/s10008-017-3643-y
Qiu Z., Zhang Y., Xia S., Yao Y., A facile method for synthesis of
LiNi 0.8Co0.15Al0.05O2 cathode material, Solid State Ionics,
307 (2017b) 73–78. DOI: 10.1016/j.ssi.2017.04.011
Ronduda H., Zybert M., Szczęsna-Chrzan A., Trzeciak T.,
Ostrowski A., Szymański D., Wieczorek W., Raróg-PileckaW., Marcinek M., On the sensitivity of the Ni-rich layered
cathode materials for li-ion batteries to the different calcination conditions, Nanomaterials, 10 (2020) 1–21. DOI:
10.3390/nano10102018
Ryu H.H., Park K.J., Yoon D.R., Aishova A., Yoon C.S., Sun Y.K.,
Li[Ni0.9Co0.09W0.01]O2: a new type of layered oxide cathodewith high cycling stability, Advanced Energy Materials, 9(2019) 1–7. DOI: 10.1002/aenm.201902698
Sebastian S.T., Jagan R.S., Rajagoplan R., Paravannoor A.,
Menon L.V., Subramanian K.R.V., Nair S.V., Balakrishnan
A., Lithium-ion storage performance of camphoric carbon
wrapped NiS nano/micro-hybrids, RSC Advances, 4 (2014)

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

11673–11679. DOI: 10.1039/c4ra00176a
Seo J., Lee J., Fast growth of the precursor particles of Li(Ni0.
8Co0.16Al0.04)O2 via a carbonate co-precipitation route andits electrochemical performance, Journal of Alloys andCompounds, 694 (2017) 703–709. DOI: 10.1016/j.jallcom.
2016.10.062
Shi J., Du N., Zheng W., Li X., Dai Y., He G., Ultrathin Ni-Co
double hydroxide nanosheets with conformal graphene coating for highly active oxygen evolution reaction and lithium
ion battery anode materials, Chemical Engineering Journal,
327 (2017) 9–17. DOI: 10.1016/j.cej.2017.06.080
Sonia T.S., Anjali P., Roshny S., Lakshmi V., Ranjusha R.,
Subramanian K.R.V., Nair S.V., Balakrishnan A., Nano/
micro-hybrid NiS cathodes for lithium ion batteries, Ceramics International, 40 (2014) 8351–8356. DOI: 10.1016/j.
ceramint.2014.01.041
Su Y., Chen G., Chen L., Li W., Zhang Q., Yang Z., Lu Y., Bao L.,
Tan J., Chen R., Chen S., Wu F., Exposing the {010} planes
by oriented self-assembly with nanosheets to improve theelectrochemical performances of Ni-Rich Li[Ni0.8Co0.1Mn0.1]
O2 microspheres, ACS Applied Materials and Interfaces, 10(2018) 6407–6414. DOI: 10.1021/acsami.7b18933
Sun H.H., Weeks J.A., Heller A., Mullins C.B., Nanorod gradientcathode: preventing electrolyte penetration into cathode particles, ACS Applied Energy Materials, 2 (2019) 6002–6011.
DOI: 10.1021/acsaem.9b01116
Sun Y.K., Lee D.J., Lee Y.J., Chen Z., Myung S.T., Cobalt-freenickel rich layered oxide cathodes for lithium-ion batteries,
ACS Applied Materials and Interfaces, 5 (2013) 11434–
11440. DOI: 10.1021/am403684z
Tang Z.F., Wu R., Huang P.F., Wang Q.S., Chen C.H., Improving
the electrochemical performance of Ni-rich cathode material
LiNi0.815Co0.15Al0.035O2 by removing the lithium residues
and forming Li3PO4 coating layer, Journal of Alloys andCompounds, 693 (2017) 1157–1163. DOI: 10.1016/j.jallcom.
2016.10.099
Tian C., Nordlund D., Xin H.L., Xu Y., Liu Y., Sokaras D., Lin F.,
Doeff M.M., Depth-dependent redox behavior of LiNi0.6Mn0.2
Co0.2O2, Journal of The Electrochemical Society, 165 (2018)
A696–A704. DOI: 10.1149/2.1021803jes
Tian J., Su Y., Wu F., Xu S., Chen F., Chen R., Li Q., Li J., Sun
F., Chen S., High-rate and cycling-stable nickel-rich cathodematerials with enhanced Li+ diffusion pathway, ACS Applied
Materials and Interfaces, 8 (2016) 582–587. DOI: 10.1021/
acsami.5b09641
Toprakci O., Toprakci H.A.K., Ji L., Zhang X., Fabrication andelectrochemical characteristics of LiFePO4 powders forlithium-ion batteries, KONA Powder and Particle Journal, 28(2010) 50–73. DOI: 10.14356/kona.2010008
Wang L., Sun Juncai, Sun Jing, Hydrothermal synthesis ofnanostructured NiS and its optimisation as cathode material
for rechargeable lithium battery, International Journal of
Nanomanufacturing, 9 (2013) 303–310. DOI: 10.1504/
IJNM.2013.056056
Wang L., Zhang G., Liu Q., Duan H., Recent progress in Zn-based
anodes for advanced lithium-ion batteries, Materials
Chemistry Frontiers, 2 (2018) 1414–1435. DOI: 10.1039/
c8qm00125a
Wang Q., Zhang L., Zhao P., Du Z., Facile synthesis of a highcapacity LiNi0.8Co0.15Al0.05O2 nanoplate cathode with a 010
orientation for lithium-ion batteries, International Journalof Electrochemical Science, 13 (2018) 10382–10389. DOI:
10.20964/2018.11.15
Wang X., Li X., Sun X., Li F., Liu Q., Wang Q., He D., Nanostructured NiO electrode for high-rate Li-ion batteries, Journal of

Materials Chemistry, 21 (2011) 3571–3573. DOI: 10.1039/
c0jm04356g
Wang Y., Wang E., Zhang X., Yu H., High-voltage “singlecrystal” cathode materials for lithium-ion batteries, Energy
and Fuels, 35 (2021) 1918–1932. DOI: 10.1021/acs.
energyfuels.0c03608
Weber R., Li H., Chen W., Kim C.-Y., Plucknett K., Dahn J.R., In
situ XRD studies during synthesis of single-crystal LiNiO2,
LiNi0.975Mg0.025O2, and LiNi0.95Al0.05O2 cathode materials,
Journal of The Electrochemical Society, 167 (2020) 100501.
DOI: 10.1149/1945-7111/ab94ef
Wei S., Di Lecce D., Brescia R., Pugliese G., Shearing P.R.,
Hassoun J., Electrochemical behavior of nanostructured
NiO@C anode in a lithium-ion battery using LiNi⅓Co⅓Mn⅓O2
cathode, Journal of Alloys and Compounds, 844 (2020)
155365. DOI: 10.1016/j.jallcom.2020.155365
Wu N., Wu H., Yuan W., Liu S., Liao J., Zhang Y., Facile synthesis of one-dimensional LiNi0.8Co0.15Al0.05O2 microrods asadvanced cathode materials for lithium ion batteries, Journalof Materials Chemistry A, 3 (2015) 13648–13652. DOI:
10.1039/C5TA02767E
Xie H., Du K., Hu G., Duan J., Peng Z., Zhang Z., Cao Y., Synthesis of LiNi0.8Co0.15Al0.05O2 with 5-sulfosalicylic acid as achelating agent and its electrochemical properties, Journalof Materials Chemistry A, 3 (2015) 1–21. DOI: 10.1039/
C5TA05266A
Xie H., Hu G., Du K., Peng Z., Cao Y., An improved continuous
co-precipitation method to synthesize LiNi0.80Co0.15Al0.05O2
cathode material, Journal of Alloys and Compounds, 666(2016) 84–87. DOI: 10.1016/j.jallcom.2016.01.064
Xu L., Zhou F., Kong J., Chen Z., Chen K., Synthesis of Li(Ni0.6
Co0.2Mn0.2)O2 with sodium DL-lactate as an eco-friendly
chelating agent and its electrochemical performances forlithium-ion batteries, Ionics, 24 (2018) 2261–2273. DOI:
10.1007/s11581-017-2363-8
Xu X., Huo H., Jian J., Wang L., Zhu H., Xu S., He X., Yin G.,
Du C., Sun X., Radially oriented single-crystal primarynanosheets enable ultrahigh rate and cycling propertiesof LiNi0.8Co0.1 Mn 0.1O2 cathode material for lithium-ion
batteries, Advanced Energy Materials, 9 (2019) 1–9. DOI:
10.1002/aenm.201803963
Yan W., Yang S., Huang Y., Yang Y., Guohui Yuan, A review
on doping/coating of nickel-rich cathode materials forlithium-ion batteries, Journal of Alloys and Compounds, 819(2020) 153048. DOI: 10.1016/j.jallcom.2019.153048
Yang C., Zhu Z., Wei W., Zhou L., Superior cycle stability ofsingle crystal nickel-rich layered oxides with micron-scale
grain size as cathode material for lithium-ion batteries,
International Journal of Electrochemical Science, 15 (2020)
5031–5041. DOI: 10.20964/2020.06.03
Yang G., Qin X., Wang B., Cai F., Gao J., Well-ordered spherical
LiNi0.8Co0.1Mn0.1O2 cathode material for lithium-ion batteries, Journal of Materials Research, 35 (2020) 51–57. DOI:
10.1557/jmr.2019.307
Yang H., Liu P., Chen Q., Liu X., Lu Y., Xie S., Ni L., Wu X.,Peng M., Chen Yanbin, Tang Y., Chen Yanfeng, Fabricationand characteristics of high-capacity LiNi0.8Co0.15Al0.05O2withmonodisperse yolk–shell spherical precursors by a facile
method, RSC Advances, 4 (2014) 35522. DOI: 10.1039/
c4ra04122d
Yang X., Tang Y., Zheng J., Shang G., Wu J., Lai Y., Li J., Zhang
Z., Tailoring structure of Ni-rich layered cathode enablerobust calendar life and ultrahigh rate capability for lithiumion batteries, Electrochimica Acta, 320 (2019) 134587. DOI:
10.1016/j.electacta.2019.134587

147

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

Ye Z., Qiu L., Yang W., Wu Z., Liu Y., Wang G., Song Y., Zhong
B., Guo X., Nickel-rich layered cathode materials for lithiumion batteries, Chemistry – A European Journal, 27 (2021)
4249–4269. DOI: 10.1002/chem.202003987
Yoon C.S., Jun D.W., Myung S.T., Sun Y.K., Structural stabilityof LiNiO2 cycled above 4.2 v, ACS Energy Letters, 2 (2017)
1150–1155. DOI: 10.1021/acsenergylett.7b00304
Yudha C.S., Muzayanha S.U., Hendri W., Iskandar F., Sutopo
W., Purwanto A., Widiyandari H., Synthesis of LiNi0.85
Co0.14Al0.01O2 cathode material and its performance in an
NCA / graphite full-battery, Energies, 12 (2019) 1886. DOI:
10.3390/en12101886
Yue P., Wang Z., Wang J., Guo H., Xiong X., Li X., Effect offluorine on the electrochemical performance of spherical
LiNi0.8Co0.1Mn0.1O2 cathode materials via a low temperature
method, Powder Technology, 237 (2013) 623–626. DOI:
10.1016/j.powtec.2012.12.061
Zeng T., Zhang C., An effective way of co-precipitating Ni2+,
Mn2+ and Co2+ by using ammonium oxalate as precipitant
for Ni-rich Li-ion batteries cathode, Journal of Materials
Science, 55 (2020) 11535–11544. DOI: 10.1007/s10853020-04753-w
Zhang C., Qi J., Zhao H., Hou H., Deng B., Tao S., Su X., Wang
Z., Qian B., Chu W., Facile synthesis silkworm-like Ni-richlayered LiNi0.8Co0.1Mn0.1O2 cathode material for lithium-ion
batteries, Materials Letters, 201 (2017) 1–4. DOI: 10.1016/j.
matlet.2017.04.121
Zhang H., Yang S., Huang Y., Xianhua H., Synthesis of
non-spherical LiNi0.88Co0.09Al0.03O2 cathode material for
lithium-ion batteries, Energy & Fuels, 34 (2020) 9002–9010.
DOI: 10.1021/acs.energyfuels.0c01692
Zhang J., Xu S., Hamad K.I., Jasim A.M., Xing Y., High retention
rate NCA cathode powders from spray drying and flame
assisted spray pyrolysis using glycerol as the solvent, Powder Technology, 363 (2020) 1–6. DOI: 10.1016/j.powtec.
2019.12.057
Zhang L., Dong T., Yu X., Dong Y., Zhao Z., Li H., Synthesis
and electrochemical performance of LiNi0.7Co0.15Mn0.15O2
as gradient cathode material for lithium batteries, Materials

Research Bulletin, 47 (2012) 3269–3272. DOI: 10.1016/j.
materresbull.2012.08.002
Zhang Q., Su Y., Chen L., Lu Y., Bao L., He T., Wang J., Chen
R., Tan J., Wu F., Pre-oxidizing the precursors of Nickel-richcathode materials to regulate their Li+/Ni2+ cation ordering
towards cyclability improvements, Journal of Power Sources,
396 (2018) 734–741. DOI: 10.1016/j.jpowsour.2018.06.091
Zhao Z., Huang B., Wang M., Yang X., Gu Y., Facile synthesisof fluorine doped single crystal Ni-rich cathode material for
lithium-ion batteries, Solid State Ionics, 342 (2019) 115065.
DOI: 10.1016/j.ssi.2019.115065
Zhu J., Chen G., Single-crystal based studies for correlating theproperties and high-voltage performance of Li[NixMnyCo1–x–y]O2 cathodes, Journal of Materials Chemistry A, 7
(2019) 5463–5474. DOI: 10.1039/c8ta10329a
Zhu J., Zheng J., Cao G., Li Y., Zhou Y., Deng S., Hai C., Fluxfree synthesis of single-crystal LiNi0.8Co0.1Mn0.1O2 boosts
its electrochemical performance in lithium batteries, Journalof Power Sources, 464 (2020) 228207. DOI: 10.1016/j.
jpowsour.2020.228207
Zhu L.Z., Han E.S., Cao J.L., Synthesis and characteristics of
NiS for cathode of lithium ion batteries, Advanced Materials
Research, 236–238 (2011) 694–697. DOI: 10.4028/www.
scientific.net/AMR.236-238.694
Zhu Q., Xiao H., Zhang R., Geng S., Huang Q., Effect of impeller
type on preparing spherical and dense Ni1–x–yCoxMny(OH)2
precursor via continuous co-precipitation in pilot scale: acase of Ni0·6Co0·2Mn0·2(OH)2, Electrochimica Acta, 318(2019) 1–13. DOI: 10.1016/j.electacta.2019.06.008
Zhu X., Zhong Y., Zhai H., Yan Z., Li D., Nanoflake nickelhydroxide and reduced graphene oxide composite as
anode materials for high-capacity lithium ion batteries,
Electrochimica Acta, 132 (2014) 364–369. DOI: 10.1016/j.
electacta.2014.03.132
Zuniga L., Gonzalez G., Chavez R.O., Myers J.C., Lodge T.P.,
Alcoutlabi M., Centrifugally spun α-Fe2O3/TiO2/carbon
composite fibers as anode materials for lithium-ion batteries,
Applied Sciences, 9 (2019) 4032. DOI: 10.3390/app9194032

Authors’ Short Biographies
Agus Purwanto
Agus Purwanto is a Professor at Chemical Department Sebelas Maret University, Indonesia. He
received his Ph.D. degree in Chemical Engineering from Hiroshima University, Japan. His researchinterest is in the synthesis and characterization of functional materials for energy storage and conversion. One of the research interests is the development li-ion battery materials, optimization andits application.

148

Agus Purwanto et al. / KONA Powder and Particle Journal No. 39 (2022) 130–149

Authors’ Short Biographies
Shofirul Sholikhatun Nisa
Shofirul Sholikhatun Nisa received her bachelor’s degree in 2019 from the Chemical Engineering
Department, Universitas Sebelas Maret. She continued her master’s studies at the same department
and university and is now in final year. She is very interested in the field of energy storage especially
Li-ion batteries. Currently, her research focus is on the synthesis of NMC materials, especially Nirich materials.

Ike Puji Lestari
Ike Puji Lestari is a master student at the Department of Chemical Engineering, Universitas Sebelas Maret. Previously she received her bachelor’s degree in the same department in 2019. Currently
she is working on a novel silicon based anode material for Li-ion batteries.

Muhammad Nur Ikhsanudin
Muhammad Nur Ikhsanudin received his bachelor’s degree in 2020 from the Chemical Engineering Department, Universitas Sebelas Maret. He continued his master’s studies at the samedepartment and university and is now in first year. He is very interested in the field of energy storage
especially Li-ion batteries. Currently, His research focus is on the anode-free Li-ion batteries.

Cornelius Satria Yudha
Cornelius Satria Yudha received his bachelor degree (2015) and master degree (2019) in chemicalengineering, Universitas Sebelas Maret. Currently, He is a young researcher at University Centre of
Excellence for Electrical Storage Technology (CE-FEEST), Universitas Sebelas Maret. His researchinterest is hydrometallurgical processing of novel material for state-of-the-art secondary energy
storage development.

Hendri Widiyandari
Hendri Widiyandari is a lecturer at Physics Department Sebelas Maret University, Indonesia, since
2018. Before that, she was a lecturer at the Department of Physics, Diponegoro University, Indonesia, from 1999 until 2017. She received her Ph.D. degree in Chemical Engineering from Hiroshima
University, Japan. Her research interest is in the synthesis and characterization of functional materials for energy storage and conversion. One of the research interests is the development of active
materials for Li-ion batteries.

149

KONA Powder and Particle Journal No. 39 (2022) 150–175/https://doi.org/10.14356/kona.2022017

Review Paper

Contribution of Particle Design Research to the Development ofPatient-Centric Dosage Forms †Hirofumi Takeuchi
Laboratory of Advanced Pharmaceutical Process Engineering, Gifu Pharmaceutical University, Japan

Abstract
A variety of dosage forms have been developed in order to achieve effective and safe drug delivery in topical orsystemic drug administrations. In this review, formulation research and process issues related to a popular oral
dosage form, the tablet, are introduced. Research on oral dosage forms, including orally disintegrating tablets(ODTs) and films (ODFs), which have recently been developed with an aim toward more patient-centric drug
therapy, is also introduced. Another trend in recent drug therapy is an increase in the number of large bioactive
molecules among the newly developed active pharmaceutical ingredients (APIs). To design dosage forms forthese APIs, novel dosage form design and administration routes are required. For this purpose, we have tried toeffectively use the polymer-coated liposomes in oral, pulmonary and ophthalmic administration. For example,
suitable polymers were introduced for the design of specific administration routes, such as mucoadhesive liposomes
for oral administration. The key point in these researches is the particle design for the component particles of final
dosage forms, both in the case of coarse powder particle design for formulating solid dosage forms and in the caseof colloidal particle design, such as the design of liposomes for peptide drug delivery.
Keywords: particle design, patient centric therapy, orally disintegrating tablets, drug delivery systems,
mucoadhesive liposomes

1. Introduction
One of the most important roles of dosage forms is
to deliver the drug into the body. The most common
delivery route is that of oral administration, in which thedrug is taken by mouth like food and then absorbed in
the digestive tract. The active pharmaceutical ingredient(API) is transported to the whole body via the systemic
blood stream. Since taking drugs by this route is similar
to eating food, the administration can be performed by thepatients themselves, and thus oral administration is said tobe the method with the best compliance and adherence ofthe patients. Of course, many other dosage forms are also
known, such as injections that are delivered directly into
the body, inhalants that allow local administration to thepharynx, and ointments or patches that are expected to act
mainly on the skin. These various dosage forms and theirnames are defined in the pharmacopoeia in each country. In
the current (17th edition) Japanese Pharmacopoeia, various
dosage form names are listed in each administration routes.
One of the reasons why many dosage forms are required†

Received 23 June 2021; Accepted 29 July 2021
J-STAGE Advance published online 2 October 2021
Add: 5-6-1 Mitahora-Higashi, Gifu 502-8585, Japan
E-mail: takeuchi@gifu-pu.ac.jp
TEL: +81-58-237-8572

150

is that the optimal and most efficiently administered dosage
form must be designed according to the characteristics
and therapeutic purpose of the API. Furthermore, in recent
years, the concept of dosage form design for drug administration has evolved, with increasing consideration for thepatients who are actually administered the drug—that is,the design of patient-centric dosage forms. Even in oral
administration, which is the most preferable administration
method for patients, there is an increasing demand forformulation development so that administration can be
carried out more easily. For example, orally disintegratingtablets (ODTs) that disintegrate in the oral cavity before
swallowing without or with a small amount of water are
more convenient for patients. Jelly-like formulations andoral films have also been developed to promote ease ofswallowing and administration.
One of the motivations underlying the development of
ODTs and other easy-to-take dosage forms is the growing
need for medical treatment of the elderly in aging societies,
but a growing interest in child-friendly administration
modalities has also been a factor. Regarding the former,
age-related aspiration is a life-threatening problem, andaspiration pneumonia is ranked as the leading cause ofdeath among the elderly. Although aspiration applies toall situations, including diet, the risk of aspiration should
be reduced as much as possible in the administration of

Copyright © 2022 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

therapeutic drugs. In recent years, there has also been agreat deal of interest in drug administration to children.
When there is no suitable tablet for pediatric dosing, tablets
are crushed in the pharmacy to match the prescription. In
addition to the labor this requires on the part of the pharma­cist, certain functions inherent to the formulation design,
such as sustained release, may be impaired by such pulver­
ization. In addition, the division may reduce the accuracyof the drug dose. Even if the pulverization proceeds without such problems, there is a concern that the receiving
child may not be able to take the powder well or may refuse
to take it entirely due to its unpleasant taste. Against thisbackground, the development of pediatric content formulations as well as the development of dosage forms that facilitate administration to children are underway. Examples ofsuch dosage forms include syrups that have been known fora long time, jelly preparations that are newly listed in theJapanese Pharmacopoeia, and oral film preparations. Also,
regarding the size of tablets, a mini tablet with a diameterof about 1 to 4 mm is available as one of the new dosage
forms.
The administration of drugs is classified into two types:
systemic administration, in which a drug is delivered
systemically through the bloodstream after administration,and topical administration, in which a drug is administereddirectly to the site where its effects are needed. In either
case, it is often necessary to deliver the drug into thebody more efficiently by using suitable dosage forms andformulations. Sustained-release preparations, in which thedrug is gradually released, are one of the delivery modes
considered in the preparation design. Orally administeredsustained-release preparations control the amount of drug
released on the preparation side to control the amount ofdrug delivered systemically. As a result, specific effects are
possible, such as preventing the blood concentration of the
drug from reaching a region where side effects may occur,and being able to increase the dose and thus reduce the number of doses. Coating is a typical preparation technique forachieving release control from the dosage forms. A matrixtype tablet, which is prepared with a material suitable forsustained release as the excipient, is also a commonlyused dosage form design that achieves release control(McGinity, 1997).
In the case of designing oral preparations of the mostcommon small molecule drugs, it is necessary to pay close
attention to the solubility of the drug. In oral administration, the first barrier for delivery into the body is the gastrointestinal tract, and thus the drug must dissolve quickly
before absorption there. A drug to be absorbed must passthrough epithelial cells in the gastrointestinal tract, andsome hydrophobicity of the drug molecules contributes tothis permeability. On the other hand, high hydrophobicityof the drug molecules will lead to weak solubility of thecrystal. It is well known that this balance between solubil-

ity and permeability needs to be taken into consideration(Amidon et al., 1995), and for some time attempts havebeen made to improve the solubility of poorly soluble drugs
in formulation. Such efforts have included miniaturizationof drug crystals and solid dispersion technology, and these
preparation technologies have been applied to many actual
preparations. In the former case, it can be easily imaginedthat the effective surface area at the time of dissolution isincreased and the dissolution characteristics are improvedby miniaturization. However, considering the individual
processes in the actual manufacture of the final product,
mixing the finely pulverized powder into the formulation
may lead to problems, including problems with mixing
uniformity or a decrease in fluidity during transportation.
The latter method, i.e., solid dispersion, has the advantage
of potentially achieving greater saturation solubility compared with miniaturization and thus has been anticipated asa useful technology for more than two decades. The biggest
issue is the storage stability of the drug in its amorphizedstate, and the choice of carrier used for the solid dispersion
and the mechanism of the amorphization are related.
In formulation design, along with paying attention to
the characteristics of the drug crystals, the technology forforming the final dosage form is an important research subject. For example, even in the case of tablet preparation, it
is essential to study particle design and formulation design
based on the characteristics of the materials (excipients,
disintegrants, binders, etc.) that make up the tablet shapehaving the pharmaceutically required functions. In addition, when special functions such as a significant reduction
in disintegration time are required, such as for orally disintegrating tablets, which have been actively developed inrecent years, more multifaceted research is required thanfor the prescription design of ordinary tablets. We havealso conducted research on particle design related to tablet
excipients, particle design of excipients and binders usefulfor the formulation design of orally disintegrating tablets,
and analysis of compression molding processes using suchparticles. In developing new dosage forms such as oral film
preparations (orodispersible films) and jelly preparations
that are expected to have similar functions, we have beenworking on the basic formulations and the processes of formulation design and preparation methods. For convenienceof handling and portability, we have also reported theconcept of easily re-dispersible powdered emulsion of oily
drugs (dry emulsions) (Takeuchi et al., 1991) or powderedjellies (dry jellies), which can be easily prepared by adding
water before use (Kakino et al., 2017).
On the other hand, in order to guarantee the quality of
final products, it is necessary to examine the validity ofthe production process. In addition, it is important to confirm the production process using the actual formulation
on a production process scale, because the occurrenceof unexpected locking obstacles such as sticking during

151Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

compaction of pharmaceutical powder formulation posesa major obstacle to production. To address these issues,
we have tried to analyze the compression process using atableting analyzer to detect tablet failures, and to understand the relationship between particle characteristics andsticking phenomena. In addition, these studies have led to
the recent study of continuous production. Research onthese formulation processes is essential for pharmaceuticalcompanies and has been extensively conducted, but so far,there have been only a small number of papers concernedwith conventional formulation research.
Targeting, in which the drug is selectively delivered
the desired site in the body, is a field of pharmaceutics
research. The development of a drug delivery system thatuses submicron-sized carrier particles to deliver drugs
to the target site started at late 1970’s (Couvreur et al.,1979). Liposomes were also anticipated to be candidates
for particulate drug carriers (Knight, 1981). These fineparticles for drug delivery are sometimes called colloidal
drug delivery systems (Kreuter, 1994). Active targeting,which utilizes the affinity of substances localized on thecell surface to achieve particle accumulation at the delivery site, has been of interest to many researchers. On theother hand, after administering such submicron particles
into the blood by injection, it is necessary to prevent theirdistribution to other unintended organs or sites for as longas possible. This has been especially important in the development and commercialization of liposome injections
containing anticancer agents such as doxorubicin. The
same principle applies to the case of topical administration,and the effect of the encapsulated drug depends on how the
movement of the microparticulate preparation is controlled
after administration. Looking at the development status ofdrugs in recent years, the size of drug molecules has clearly
been increasing. In particular, drugs modeled on hormones,
peptides, antibodies, etc., produced in the body have amolecular weight of several thousand to several hundred
thousand daltons. Similar to targeting, research on suchdrugs using a fine particle carrier to deliver them into thebody is also in progress.
Insulin is a typical drug with a high molecular weight.
Insulin is a substance that is originally produced in the bodyand has the function of lowering the glucose concentrationin the blood when its level is high. Insulin developed as acommercial product has saved the lives of many diabetic
patients. For type I diabetic patients who are deficient ininsulin, administration before each meal, i.e., just before
the glucose concentration in the blood rises, is the mosteffective treatment method. Injection is the most popularmethod of delivering insulin into the body, and selfinjection is also permitted. In addition, a prefilled syringetype of insulin in which the injection solution is pre-set
in a syringe has also been made available. The pain of
injection is alleviated by making the diameter of the needle

152

sufficiently small. A unit called a gauge (G) is used for the
thickness of the injection needle: the larger the G value, thethinner the needle. The needle for insulin injection is usually 30 G (outer diameter, 0.31 ± 0.02 mm) or more, whichis considerably thinner than the needle used for normal
blood sampling (21–23 G: outer diameter, 0.81–0.64 mm).
This is another example of pharmaceutical development
research progressing in consideration of the needs of actual
patients.
Injections are the most common dosage form for highmolecular weight drugs, and the development of morepatient-friendly optimal dosage forms is still being considered as an important research topic. In the case of insulin,
attempts to develop administration methods other thaninjection have included the commercial development ofa powder inhalant to deliver insulin into the body via absorption from the lungs. We have also conducted research
focusing on liposome particle design with the aim ofdeveloping novel delivery methods other than injection ofmacromolecular drugs. Among them, polymer-coated liposomes with a mucosal adhesion function have potential foruse in the development or oral administration preparationsof high molecular drugs. In addition to oral administration,
the usefulness of drug transpulmonary absorption using
liposomes has also been investigated. We have also suggested the possibility of using eye drops to deliver the drug
to the posterior segment of the eye.
As mentioned above, there are various aspects topharmaceutical formulation research. All the research wehave conducted in this field has a common theme: particle
design. Such design can range from powder particles tonanoparticles such as liposomes. That is, regardless ofthe final dosage form, the goal has been to control thecharacteristics of the basic powder particles and nanoparticles in order to develop the pharmaceutical function andcontribute to drug delivery. Moreover, keeping the goal ofadministration to humans in mind, we have aimed to design
dosage forms that will realize the gentlest possible drug
administration in actual patients. The author would like tointroduce some of the representative researches and theirbackground.

2. Formulation design for improving drug
dissolution and absorption
2.1 Micronizing drug crystals and dosage form
design
It is well known that the size of drug crystals affects thedissolution rate of drugs (Takeuchi, 2019). As the drug
dissolution rate is an important factor in preparing pharmaceutical tablets, it is not rare to pulverize or control the
drug crystal to an appropriate size in the manufacture ofHirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

tablets. In the case of pharmaceutical preparation of poorly
water-soluble drugs, a jet mill is often used in pulverizing
pharmaceutical crystals. Many active ingredients are organic powders and generally do not have a very high melting point. Therefore, when pulverization to a few microns
is required, there is often a concern that the crystal shape
may change due to heat generated during pulverization,and thus a jet mill that is relatively unlikely to generateheat is used.
Drug crystals that have been refined to submicron size(usually 100–200 nm in average particle size) are called
nanocrystals, and the state in which submicron-sized drug
crystals are dispersed in a liquid is called nanocrystal
suspension. In addition to improving the dissolution properties, submicron-sized particles exhibit gastrointestinal
retention due to tissue adhesion (Ponchel et al., 1997).
It has also been reported that the nanocrystal suspensionof drug improved its absorption extensibly in comparing
AUC (area under curve) values compared with the usual
preparation (Liversidge and Cundy, 1995). Regarding
the preparation methods, there are roughly two types ofmethods for refining drug crystals to submicron size: thebreakdown method and the build-up method. Well-known
breakdown technologies are 1) the pearl milling (bead/ballmilling) method (Liversidge et al., 2003), which prepares
particles by crushing them using a large number of beads
in a medium, and 2) the high-pressure homogenization
method (Müller and Peters, 1998; Keck and Müller, 2006),
which prepares micronized particles by passing themthrough narrow gaps at high pressure. These breakdowntype processes also have problems such as relatively long
operation time, concern about contaminants generated

from the medium, and high energy requirement. Elan’s
NanoCrystal® technology based on a breakdown method isknown a commercially widely used one.
Drug crystals that require improved dissolution properties often have problems with wettability, and even if
they are micronized by pulverizing, the effective specificsurface area at the time of dissolution does not increase as
expected. Conversely, the micronization may cause aggregation and lead to a decrease in the effective surface areafor dissolution. To solve this problem, we designed composite particles containing disintegrants by use of a spraydrying technique (Takeuchi et al., 1987a). When a poorly
water-soluble model drug tolbutamide and PCS® (partially pregelatinized starch), the latter of which has highsphericity, were formulated as disintegrants, the resulting
spray-dried particles were spherical and showed excellent
fluidity. Because the powder X-ray diffraction analysis ofspray-dried particles showed the existence of drug crystals
on the particles and the particle sizes of spray-dried particles were comparable to those of PCS particles, the structure of the spray-dried particles was estimated to consist of
the drug microcrystals embedded on the surface of PCS, as
shown in Fig. 1(A). The dissolution test revealed that theobtained composite particles had significantly improved
solubilizing property compared to the original drug crystalline powder and the spray-dried drug alone (Fig. 2). The
drug release rate depended on the drug formulating ratio
to core particle, PCS. When observed under a microscope,
the drug embedded particles were found to swell rapidly
upon contact with water, indicating that the prescribeddisintegrant worked effectively. A preparation of ordered
mixture-like composite particles of poorly-water soluble

Fig. 1 Particle design of poorly water soluble drugs for improving their dissolution properties (A) Drug embedding system with a disintegrant prepared by spray-drying technique for improvement of dissolution of poorly water soluble drugs and (B) Ordered mixtures of hydrophobic drug particles
with hydrophilic fine particles.

153

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

product administration group was 2-fold higher than that of
the usual crystallization product.

2.2 Solid dispersion particle prepared by spraydryingFig. 2 Dissolution profiles of a poorly water soluble drug, tolbutamide,spray-dried with a disintegrant, PCS® (Drug embedding system).

drug and hydrophilic excipient particles such as Neusilin®
(Fig. 1(B)) was also demonstrated with a dry mixing process by using a vibrating ball mill and a mechanical fusion
system (Mechanofusion®). The resultant dissolution profiles of the poorly water-soluble drug indomethacin (IMC)from the composite particles were 3-fold to 4-fold faster.
It is presumed that the particles having excellent hydrophilicity increased the hydrophilicity of the drug crystals
by coating their surface and increased the effective surface
area in drug dissolution.
As an attempt at nanocrystal preparation by the build-up
method, we tried to control the crystallization of a poorly
water-soluble drug using a Pure Nano high-pressure
crystallizer (manufactured by Microfluidics) in which thepoor solvent addition precipitation method was applied
to the precision mixing technique using a high-pressure
homogenizer (Takeuchi and Onodera, 2015). By increasing
the pressure of the reaction field, a high-strength shear
field is formed inside the reaction vessel, and the reactants
are mixed in a turbulent state in which the strong energy
dissipation mechanism is activated. In the case of crystallization, it was expected that a smaller size of crystals
could be obtained by this method compared with the usual
mixing operation with a normal stirrer. After preparing
a fine crystal suspension of phenytoin as a model of apoorly water-soluble drug and polyvinyl alcohol (PVA) as
a dispersion stabilizer, the crystal form, solubility, absorbability after oral administration, etc., of the crystals were
evaluated (Tahara et al., 2016). In the case of high-pressure
crystallization, the particle size was about half of that in
the case of normal crystallization. Moreover, there was nochange in the crystal form. The solubilizing property of the
prepared particles was remarkably improved. When eachphenytoin sample was orally administered to rats and thebioavailability was compared by the drug concentration inblood, the AUC value in the high-pressure crystallization

154

The term solid dispersion of a pharmaceutical preparation refers to a preparation in which the drug is dispersed
in a solid carrier in an amorphous state. More precisely, thedrug is dispersed as a molecule or a cluster in the carrier
solids. It is well known that drugs in the amorphous state
have excellent dissolution properties (Takeuchi, 2019).
However, the amorphous state is generally unstable, andcrystallization during storage is one of the strictly required
points for pharmaceutical preparations. From this point ofview, the selection of the carrier to be blended is important,and many studies have been conducted to determine thebest carriers. Furthermore, it has been pointed out that the
preparation process in which the drug is first dissolved andthe solvent is distilled off, has an energy problem. However, in recent years, the proportion of poorly soluble drugs
among the drugs developed has been extremely large,
and improvement of solubility has become an extremely
important issue. Thus, solid dispersions are one of theimportant methods for improving the dissolution propertyof poorly water-soluble drugs.
Research on solid solutions is often said to be the firstresearch on solid dispersion systems (Sekiguchi and Obi,
1961; Chiou and Riegelman, 1969; Simonelli et al., 1969),
but research on pharmaceutical preparations has been
actively conducted since the 1980s. In order to amorphize
drug crystals, it is important to use an appropriate carrier,and water-soluble polymers such as polyvinylpyrrolidone(PVP) have been studied as useful carriers (Corrigan et al.,
1983; 1984; Ford et al., 1986). We selected a spray-drying
technique to prepare solid dispersion particles, because
the resultant particles are spherical and tend to be freely
flowing. As a new carrier for preparing the solid dispersion
particles prepared by spray-drying, we used fumed silica(Aerosil®), which is insoluble in water but extremely hydrophilic, and is prepared by the spray method (Takeuchi
et al., 1987b).
Enteric coating polymer (Eudragit L and hydroxypropyl
methylcellulose phthalate (HPMCP)) was also examined
as a candidate for carriers. An attempt was made to prepare
solid dispersion particles by dissolving dilute ammonia
water in which the model drug tolbutamide was dissolved
and dispersing or dissolving each carrier. As a result of
evaluating the spray-dried particles prepared with a 1:1
ratio of drug: silica by powder X-ray diffraction, it wasclarified that the drug exists in an amorphous state in theparticles. Crystallization of the drug was observed when
the prescribed amount of silica for the drug was reduced,
indicating that the interaction between the drug and silica

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Fig. 3 Dissolution profiles of tolbutamide from spray-dried solid dispersion particles with silica or crystalline tolbutamide.

particle surface contributed to the amorphization. All of
the particles obtained from the characteristics of the spraydrying process were spherical and had excellent fluidity. As
shown in Fig. 3, the fastest drug dissolution was confirmed
for the solid dispersion particles prepared with a 1:1 ratioof drug: silica, in which complete amorphization of the
drug was confirmed. When the ratio of silica was reduced,
the elution rate was delayed according to the ratio, and at aratio of 5:1 it became almost the same as the raw crystallineof tolbutamide.
In order to confirm the usefulness of hydrophilic waterinsoluble particles as a carrier of solid dispersion, we
also evaluated porous silica (Sylysia®) prepared by a wet
method (Takeuchi et al., 2004a). When the ethanol solutionof tolbutamide was spray-dried alone, it became a metastable crystalline form II. In the evaporator method, when thesolvent was distilled off, it became a stable crystalline formI, suggesting that the resultant crystal form depends on thedrying rate. The spray-dried solid dispersion particles of
tolbutamide with porous silica were found to be in metastable form II. The metastable crystals with silica in the solid
dispersion particles were maintained even during the storage test period, confirming the importance of the presenceof the carrier. In addition, the dissolution of tolbutamide
in the solid dispersion particles is significantly faster thanthat of form II particles prepared by spray-drying without
silica. The hydrophilicity of the carrier silica improves thewettability of the solid dispersion particles, resulting in thegood dissolution.
In the case of indomethacin (IMC), an amorphous state
was obtained by spray drying its ethanolic solution regardless of the presence or absence of a carrier. As for the dissolution characteristics, the solid dispersion particles using
the porous silica Sylysia350 as a carrier showed extremely
rapid dissolution (Fig. 4). When similar indomethacin

Fig. 4 Dissolution profiles of IMC from solid dispersion particles with
Aerosil 200 or Sylysia 350.
＋: Original IMC, ×: Spray-dried IMC, ○: Solid dispersion particles with
Aerosil 200, ●: Solid dispersion particles with Sylysia 350.

solid dispersion particles were prepared using porous silica
having different pore diameters as a carrier, an amorphous
drug was confirmed with any of the silicas. However, when
the dissolution rates were compared, it was observed thatthe drug dissolution was higher in the case of Sylysia®350,
which has a larger pore size than Sylysia® 740 (Takeuchi etal., 2003b). When the specific surface areas of the two solid
dispersion particles were measured, the value decreased
remarkably in the case of Sylysia740, and it was presumed
that the pore entrance was closed by the precipitated drug.
Therefore, it was concluded that porous silica with a large
pore diameter effectively utilizes the pores to amorphize
the drug. It is important to pay attention to the prescription
ratio of silica and the drug as a carrier and the type of silica,
but it has been clarified that porous silica is useful as acarrier of a solid dispersion.

3. Design of orally disintegrating tablets andorally disintegrating films
3.1 Tablet preparation and particle design ofexcipients
Tablets are usually prepared by compression molding of
powder (compaction). Compaction consists of four steps:
filling → compression → depressurization → discharge.
The powder is discharged from the hopper into the die or
into the feeder around the die and then filled in the die. A
stirring feeder may be used for discharge from the hopper,
but the filling in the die is usually performed by the weightof the powder itself. Powder fluidity is an important factor
in these processes. In the next step, i.e., the compression
process, the particles are deformed by pressurization toincrease the binding force and form a molded product155

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175(tablet). Various factors are involved in the binding force
between particles. Because the binding force of a substanceby van der Waals force is dominant, when the number ofbonding points between particles in a tablet is increased,
the contact area at the bonding points will be increased, resulting in a stronger molded body. Therefore, particles withlarge plastic deformability are suitable for compaction. On
the other hand, particles with large elastic deformability are
not suitable for tablet preparation.
In addition to drug powders, various additive powders(excipients) are used in the preparation of pharmaceutical
tablets. One of the most important excipients is filler powder, which has a major influence on compactibility and thus
must be designed with care. The commercialization of filler
powders for direct tableting began in the 1960s. Lactose isa representative case of a filler that was introduced in the
1960s and has undergone substantial improvement. Lactose
is one of the most widely used filler powders for preparing
pharmaceutical tablets. The improved compactibility ofspray-dried lactose (DCL11) is due to amorphous part oflactose containing 15–20 % in the particle. Anhydrous
β-lactose (DCL21), which has better compactibility thana monohydrate (α-lactose) was also commercialized. Overthe decades that followed, the development of excipients
progressed. As shown in Table 1, many co-processed products of lactose and other substances have been developed
Table 1 Co-processed excipients with lactose.

Trade Name

Composition

Manufacturer

Ludipress

Lactose, PVP*1 (7 %)BASF

Cellactose

Lactose, Cellulose(25 %)

MegglePharmatose DCL40

β-Lactose, Lactitol(5 %)DMV Veghel

MicroceLac

MCC*2, Lactose

MeggleStarLac

Lactose, Maize starch

Roquette*1 PVP: polyvinyl pyrrolidone*2 MCC: micro crystalline cellulose

as products.
The amorphous forms affect the compressibility properties of powders as well as the dissolution property of theresultant dosage forms (Pikal et al., 1978; Vromans et al.,1986). However, the amorphous forms of solids can be easily transformed into more stable, crystalline forms by heatand moisture. Regarding amorphous lactose, studies on its
compactibility and the stability of amorphous substances
have been conducted from various viewpoints (Sebhatu etal., 1994; 1997; Buckton and Darcy, 1996). Stubberud andForbes (1998) showed the effects of the physical additionof PVP to amorphous lactose on the crystallization of theamorphous lactose by using a gravimetric system for monitoring the moisture sorption. Saleki-Gerhardt and Zografi(1994) studied that crystallization of amorphous sucrose in
the presence of other saccharides, such as lactose, trehalosesignificantly extended the induction time for crystallizationof sucrose.
We evaluated the properties of the particles obtained byprescribing NaAlg (sodium alginate) as a water-soluble
polymer in the range of up to 50 % for the purpose of stabilizing amorphous lactose (Takeuchi et al., 1999c; 2000b;
2000c). Fig. 5 shows the results of the thermal stability ofamorphous lactose measured by DSC. When no NaAlg or
1 % NaAlg was added, exothermic peaks indicating the
crystallization of amorphous lactose were observed. On theother hand, no exothermic peak was detected in the composite particles containing 10 % or more of NaAlg, indicating that the thermal stability was greatly improved. This
improvement in thermal stability was found to correlatewith an increase in the glass transition temperature (Tg) of
lactose detected from the DSC chart. It has been reported
that crystallization of amorphous lactose occurs when theTg value decreases below the storage temperature due tothe “plasticizing” effects of water molecules absorbed inlactose (Stubberud et al., 1996). The SD composite particles showed that higher relative humidity values wererequired for the initiation of crystallization depending on
the content of the sodium alginate: 57 % relative humidity

Fig. 5 DSC thermograms of (A) SD composite particles and (B) physical mixtures of 100 % amorphous lactose and sodium alginate. Sodium alginate
content in the mixtures: (a) 0 %, (b) 1 %, (c) 5 %, (d) 10 %, (e) 30 %, (f) 50 %.

156

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

for 10 % sodium alginate content and 60 % relative humidity for 30 % sodium alginate content. This increase in therelative humidity required to initiate the crystallization canbe attributed to either an increase in the Tg of the composite
particles or the absorption of moisture into the sodium
alginate.
When the compactibility of the composite particles
containing amorphous lactose and NaAlg was evaluated, as
shown in Fig. 6, excellent compactibility similar to that ofamorphous lactose was confirmed up to an amount of 10 %of NaAlg added. However, when the amount of NaAlg
was increased to 30 %, a significant decrease in tensile
strength was observed, indicating a decrease in compactibility. This change in compression characteristics was wellcorrelated with the change in Tg due to the compositingof NaAlg. The increase in Tg due to NaAlg compositing
indicates that the particles become rigid. In fact, when thesurface of the tablet is observed with a scanning electron
microscope, the fusion of the particles is apparent for theparticles with 10 % NaAlg added when compacted under
the same conditions, while the shape of the individual
particles is almost completely retained in the particles with
30 % addition of NaAlg (Fig. 7). The reason that the Tg ofFig. 6 Tensile strength of tablets prepared with spray-dried composite
particles of amorphous lactose containing sodium alginate (0–30 %).

lactose in the particles affects the moldability is that when
Lac-NaAlg is stored in a humidified state, the Tg decreases
and the hardness of the molded product also increases.
This result shows that the excellent plasticity of amorphouslactose decreases depending on the type and amount of
the polymer added, and as a result, the hardness of themolded product is greatly reduced. It has been shown thatthe type and content of the substance to be composited areimportant factors in order to stabilize the amorphous bodywhile maintaining the high moldability characteristics ofthe amorphous lactose.

3.2 Particle design for preparation of orally
disintegrating tablets
In the design of orally disintegrating tablets (ODTs),various studies have been conducted for the purpose ofachieving a tablet that disintegrates extremely rapidly
in the oral cavity before swallowing. The first commercialized product, Zydis®, was molded by lyophilizing asolution or suspension of a drug and excipients in a mold
(Seager, 1998). Zydis® does not have the strength requiredfor ordinary tablets; rather, the tablet form is maintained by
the container. Much research has also been done with theaim of preparing ODTs by using conventional tableting instruments (Sugimoto et al., 2006; Kuno et al., 2008; Okuda
et al., 2009). One of the methods is molding a powder layer
under wet conditions at a low pressure and then drying it
to obtain a tablet hardness close to that of a normal tablet.
Another method is to use maltose in the tablet formulationand crystallizing it by humidification and drying treatment
after molding to obtain interparticle binding force. A third
approach to increase the tablet hardness is to exploit thedifference in the melting point of saccharides, and to heat
the molded product at an appropriate temperature to promote the crystallization of only one sugar. All three methods have contributed to development of commercial ODTs.
As the demand for ODTs increases, technological development of a method for preparing ODTs using a normal
tableting machine is required. Particle design of excipientsis important for the preparation of ODTs by conventional
tableting processes. Mannitol is most often used as an

Fig. 7 Scanning electron micrographs of the upper surface of tablets compacted at compression pressure of 400 MPa: (a) 100 % amorphous lactose,(b) SD composite particles (SDCP) with 10 % sodium alginate, (c) SDCP with 30 % sodium alginate.

157

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Fig. 8

Schematic presentation of preparation of composite particle of sugar alcohol with porous silica for preparation of orally disintegrating tablets.

Fig. 9 Tensile strength of tablets of mannitol or erythritol by formulating corresponding composite particles prepared by spray-drying withsilica.
Conditions: compaction pressure, 100 MPa; tablet weight, 200 mg.
Formulation of tablets:
Original : Sugar alcohol + 1 % Mg-st
CP: Sugar alcohol + 20 % Sugar alcohol-CP + 1 % Mg-st
PM-1:
Sugar alcohol + 10 % spray-dried Sugar alcohol + 10 %silica + 1 % Mg-st
PM-2: Sugar alcohol + 10 % silica + 1 % Mg-st

excipient to obtain rapid disintegration properties. Erythritol is also an excellent excipient candidate because of its
solubility and refreshing sensation when dissolved. However, both are inferior in compactibility to lactose, which
is most commonly used in ordinary tablets. In the case oferythritol, a molded product cannot be obtained even bycompression at extremely high pressure.
For nearly a decade now, we have been conducting
research for the purpose of improving the moldability ofmannitol and erythritol. As shown in Fig. 8, we determined

158

that constituents of low formable powder, such as mannitol
and erythritol, can be spray-dried together with porous
silica to form a composite particle, and then an appropriate
amount of this composite particle can be mixed with theoriginal low formable powder to dramatically increase thecompactibility (Takeuchi et al., 2012). Fig. 9 shows the results of tablet hardness achieved using this composite particle method. It is well known that the hardness of tablets isincreased by adding an appropriate amount of silica to thetablet formulation, but in the case of mannitol, such an effect is hardly observed. When our new approach was used
to blend composite particles, the tablet hardness became ashigh as that of typical commercial tablets. For erythritol,which cannot be compression-molded by itself at a highpressure, the tablet hardness could be increased to someextent by mixing silica and separately spray-dried erythritol and tableting. By using the composite particle method,
the resultant tablet hardness was much improved. We havealso used the composite particle method to examine theformulation of specific ODTs. After adding various types
and amounts of disintegrants (2, 5, 10 % w/w) to the basic
formulation (a mixture of erythritol, erythritol-silica composite particles (10 % w/w) and magnesium stearate (0.2 %w/w)), a tableting test was performed. All the formulations
with the various disintegrants achieved good tablet hardness, but the disintegration time of tablets varied greatly
depending on the type of disintegrant. When the disintegrant was cross povidone, the resultant tablet showed thebest disintegration property at about 15 seconds.
When the crystallinity of erythritol in the composite
particles of porous silica-erythritol was evaluated to characterize this composite particle method, the powder X-ray

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Fig. 10 Scanning electron photographs of typical mannitol crystal and commercial products of mannitol for direct tableting.
(a) MNP (Mannit P), (b) MNQ (Mannit Q), (c) PK2 (Parteck M200), (d) PL2 (Pearlitol 200 SD), (e) GRR (Granutol R).

diffraction evaluation indicated no loss of crystallinity, but
the endothermic peak due to melting measured by DSC
shifted to the low temperature side (Tanimura et al., 2015).
This suggested that the crystal energy was high. Moreover,since the proportion of high-energy crystals and the degreeof improvement in compactibility were well correlated, it
was concluded that this high-energy erythritol contributed
to the improvement in compactibility. In fact, when thesilica: erythritol ratio was changed to 1:1, 1:2, or 1:3, the
1:2 composite particles showed the highest tablet hardness.
Like lactose, mannitol has also been studied as anexcipient, and product development centered on the granulation method has been conducted. So far, several types ofmannitol for direct tableting have been made commerciallyavailable from several excipient manufacturers. Scanningelectron micrographs of the mannitol particles are shownin Fig. 10. In each case, the component is pure mannitol,
but the production method alternates between spray-drying
and spray-drying granulation. Some particles, such as
Mannit Q, have a characteristic particle structure such as aspherical hollow, but the appearance of the other particles
in the electron microscopic photographs does not differ
substantially (Fig. 10). Crystallinity is almost the same.
These commercial products are larger than mannitol crystals and have an improved compactibility. As for Mannit
Q, it is presumed that the compactibility at compression
is improved because the Mannit Q particle is composed offine mannitol crystals, as can be confirmed by electron micrographs. Excipients for direct tableting require both highfluidity and excellent compactibility. When the fluidity ofsome mannitol products for direct tableting was evaluatedby the Carr’s index, it was confirmed that all of them had
characteristic values suitable for direct tableting.
Incorporation of a binder into a tablet formulation to
improve its compactibility is a common formulation design
method. In the formulation design of orally disintegratingtablets, it is necessary to pay sufficient attention to the type
and prescription amount of the binder for ODTs in order toobtain the tablet characteristic of an extremely short disintegration time. Increasing the amount of binder increases
tablet hardness, but leads to a delay in disintegration
time. This is considered to be due to water penetrating thetablet, causing the binder to dissolve and adopt a viscous
gel state, which delays the penetration of additional water
into the tablet. For example, hydroxypropyl cellulose

Fig. 11 Hardness of erythritol tablets prepared with a fine binder
partilces of HPC-L.
Formulation of tablets: erythritol (88.5 %), HPC-L (10 %) + Mg-st(1 %) + silica (0.5 %).

(HPC), which is a pharmaceutical additive widely used inJapan, has several grades used for granulation as a binder.
The grade with low viscosity achieved by decreasing themolecular weight is suitable for rapid disintegration oftablets. When using HPC as a binder for the mixing of otherpowders, the smaller the particle size of HPC, the betterthe dispersibility in the prescription powder, and thus thegreater the number of bonding points between the powders
and the greater the hardness of the tablets. We preparedfine particles of HPC using the spray-drying method andthe freeze pulverization method. By controlling the particle
size of HPC to an average of about 20 μm or less, tablets
having the desired characteristics could be prepared. The
hardness of the tablets increased remarkably when thespray-dried spherical HPC fine particles were formulated
into a tablet formulation (Fig. 11) (Tanimura et al., 2006).
In addition, by prescribing the lowest molecular weight andthus lowest viscosity HPC-SSL fine particles as a binder ina model ODT formulation, the desired disintegration of lessthan 30 seconds and a sufficiently high tablet hardness forpractical application could be achieved.
To realize an easier prescription design of ODTs, particle
design research has progressed in diverse directions. Development of commercial products such as premixed filler
formulations using other additives or composite particles
have been produced by excipient manufacturers to allow
direct tableting of ODTs using a tableting machine likethose used for ordinary tablets. Table 2 lists some of thecommercial products and their components.

159

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175
Table 2 Premixed or co-processed excipients with mannitol for directtableting of ODT.

Trade name

Formulation

F-MELT

Mannitol, xylitol, microcrystalline cellulose, cross povidone, Metasilicate alumic
acid magnesium or Anhydrous calcium
hydrogen phosphate

SmartEx

Mannitol, L-HPC, PVA

Ludiflash

Mannitol, Collidone CL-SF, Collicoat
SR30D

Pearitol FLASH

Mannitol, corn starch

Granfiller D

Mannitol, carmelose, cross-povidone

L-HPC: Low-substituted hydroxy propyl cellulose
PVA: poly vinyl alcohol

3.3 Design of orally disintegrating film
Oral film preparations are preparations having the samecharacteristics as ODTs. Accordingly, they are sometimes
referred to as ODFs (orally disintegrating films). Thesefilms are usually stamp-sized and thin as paper. Productdevelopment in Europe and the United States has been
more active than in Japan, and also the number of products
is larger there. In recent years, patient-centric concept hasreceived much attention in dosage form design. Some ofpharmaceutical companies are taking account of ODFs as
one of the useful dosage forms for sick or pediatric patients
who have difficulty in swallowing. In terms of regulation,
the ODF is one of the subclasses of dosage forms to beorally administered in the 17th edition of the JapanesePharmacopeia.
In parallel with the research on ODTs, we have focusedon ODFs as a dosage form having the same or more patientfriendly functions. A water-soluble polymer is used as abase corresponding to a filler for tablets; so far, pullulan
and hydroxypropyl methylcellulose (HPMC) have been
widely used as base polymers for commercial products.
In conducting a formulation study of ODFs by using
HPMC as a base in the film formulation, we found thatthe disintegration time could be dramatically shortenedby prescribing a small amount of micronized disintegrantlow-substituted hydroxypropyl cellulose (L-HPC) as a disintegrant (Takeuchi et al., 2013). It was also shown that thedisintegration characteristics could be improved by using
insoluble fine particles such as silica and microcrystalline
cellulose as well as L-HPC with different particle sizes andshapes in the film. (Takeuchi Y. et al., 2019). The larger
particles had a greater impact on disintegration, comparedto the smaller particles. However, the addition of larger
particles decreased the films’ tensile strength.
For the purpose of searching for an optimum formulation of ODFs, we also investigated the effect of the typeof base polymer on the characteristics of resultant ODFs

160

by using hydroxypropyl cellulose (HPC) and polyvinyl
alcohol (PVA) as well as the more commonly used HPMC.
HPC films were found to have suitable characteristics as abase of ODFs from the standpoints of disintegration andmechanical strength. The HPC films showed particularly
good mechanical properties. When model drugs were
formulated, these characteristics remained (Takeuchi Y. etal., 2018). HPC is also formulated in some commerciallyavailable films prepared with HPMC, probably as a plasticizer in the HPMC film formulation. As the mixing ratio of
HPC to HPMC is not disclosed, we examined the mixing
ratio of HPC and HPMC. While adding a small amount of
HPC (< 10 %) yielded films with a good plasticity, the mechanical properties of the films were significantly deteriorated when increasing amounts of HPC were prescribed to
HPMC, such as when a 1:1 ratio of HPC:HPMC was used.
This may be attributed to poor compatibility between thepolymers. PVA was highly flexible when made into a film
and had high refraction resistance. Since it is sticky, it isnecessary to take measures to mediate the stickiness. However, it was also confirmed that the film base was suitablefor drug encapsulation, because its mechanical property
values were not easily altered, even if a drug is added in theformulation. (Takeuchi Y. et al., 2020a).

4. Progress on the solid formulation
manufacturing process
4.1 Analysis of the powder compaction process
The powder properties required for the formulation oftablets with the desired functions were described above inthe sections 3.1 and 3.2. However, the tableting process also
has a great influence on the preparation of the compacted
product, and thus various studies have been conducted to
examine these effects of tableting. There are two main approaches for the preparation of tablets: (1) direct tableting,in which the drug powder and other excipient powder are
mixed, and (2) indirect tableting or granule compression,in which part or all of the powder is granulated and compressed in advance. In either case, the compaction process
consists of filling the die with powder, compressing, andthen discharging the tablet from the die after releasingpressure. A stress-displacement curve (Fig. 12(A)) can be
drawn by precisely measuring the displacement during
compression and the upper punch load over time for obtaining information on the compression characteristics ofthe powder. Depending on the type of powder, the displacement is reduced (expansion of the compacted product) after
the displacement is maximized at the maximum pressure of
the upper punch. This is due to elastic recovery of the compacted powder. The net energy required for compaction is
calculated by subtracting the energy for elastic recovery

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175(B) from the total energy required for molding (A + B).
The net energy is expressed as a ratio to the total energy
and used as an index of compactibility. The compression
equation most often used when evaluating compression
molding characteristics using a compression model is the
Heckel equation (1) (Heckel., 1961a; 1961b).

ln

1
 kP  Aε(1)Here, ε is the porosity of the powder layer, P is the compression pressure, and the pressure from the upper punch is(1) used for this measurement.
usually
As shown in Fig. 12(B), when the compression pressure
is increased, causing the compression to proceed and thepowder layer to begin undergoing plastic deformation, theincrease on the left side of the Heckel equation becomes
constant and appears as a straight line. This slope is k, andFig. 12 Analysis methods of compression properties of powders.
(A) Compression force-displacement curve (B) Heckel plot.

the reciprocal of the slope is used as the yield pressure (Py)as an index of plastic deformation.
Py = 1/k(2)

The compaction property of powders has been evaluatedwith various parameters such as yield pressure measured
by Heckel analysis (Humbert-Droz et al., 1983), stress relaxation (van der Voort Maarschalk et al., 1997) and elastic
recovery (Picker, 2001). In general, a powder with plastic
deformability is preferable for preparing a compacted
product as it increases the tablet hardness, while the property of elasticity works in the opposite way.
It is possible to estimate one of the tablet failures intableting, capping, by using these parameters. Capping, inwhich the contact surface of the tablet is peeled off with thepunch, is thought to be caused by any of several different
aspects of the compaction process. Higher elasticity ofcompacted powder is one of the main factors for capping
during compaction. The measurement of die wall pressure
may also be a useful method to evaluate the compaction
property of powders, because residual die wall pressurereflects the plastic property of the compacted powder in thedie (Carless and Leigh, 1974). Some papers have reported
that the residual die wall pressure is one of the main factors
for capping, with other factors being the elastic recovery
during decompression, the stress concentration due to die
wall pressure at decompression (Hiestand et al., 1977)
and the entrapped air in the tablet during the compaction
process (Tanino et al., 1995). Sugimori reported that capping occurs when a tablet is cracked by residual die wallpressure at the final stage of the decompression process(Sugimori et al., 1989a; 1989b).
In the studies mentioned above, the compression parameters were measured by using static compression
with a very slow compression speed. We evaluated thecompression molding process using a compaction analyzer(Tab All®) that can measure the pressure detected at eachsite on a single-shot tableting machine for analysis in a
dynamic compressed state similar to an actual tabletingmachine. Fig. 13 shows an example of the data underFig. 13 Upper and lower punch forces and residual die wall force profiles and punch displacement measured by a tableting analysis instrument(TabAll, Okada Seiko Co.).

161

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Fig. 14 Die wall force profile in compacting typical filler powders (A) lactose (B) mannitol (C) sorbitol for pharmaceutical tablets formulating
different amount of lubricant, magnesium stearate.

various loads during compaction. The load applied to thewall surface increases with the increase of the upper punchload and shows the maximum die wall pressure (MDP),
and then the pressure is reduced and the force detectedeven after the pressure is completely removed is called theresidual die wall surface pressure (RDP). The MDP value
increased when the compression pressure was changed
with the same powder. In addition, since the MDP value
differs greatly depending on the powder even at the same
compression pressure, it was proposed to evaluate by the
RDP/MDP value standardized by the MDP rather thandirectly comparing the RDP value. The RDP/MDP value
reflected the compacting property of pharmaceutical powders. For example, crystalline lactose and ascorbic acid,
which showed a capping tendency, showed relatively larger
RDP/MDP values (Takeuchi et al., 2004b). Fig. 14 shows
the results of measuring the residual die wall pressure
profile by changing the amount of the lubricant for lactose,mannitol, and sorbitol, which are excipients of three typicalpharmaceutical tablets (Takeuchi et al., 2005b). Sorbitol,which has the best compactibility, showed a low residual
wall pressure regardless of the prescription amount of the
lubricant. Mannitol, as well as lactose, tends to cause tablet
failures such as binding and capping depending on thetableting formulation and conditions. For example, if theprescription amount of the lubricant in the tablet formulation increases, the tablet failure tendency is depressed. The
decrease in RDP/MDP value with increasing the amount of
the lubricant was well correlated to this tendency.

162

In recent years, for the purpose of more practical analysis of tableting processes, a tableting simulator (Style
One®) capable of compression molding in a form closer tothat of a rotary tableting machine was developed. Not only
does the rotary tableting machine used for production havea faster compression molding speed than the single-punch
tableting machine, but also the size of instrument, theinstallation angle of machine parts such as rotating discs,
and often the compression rollers for compression molding(depending on the model of machine) have different characteristics between the rotary and single-punch tabletingmachine. These differences cause the compression time
and the interval of each compression molding process todiffer depending on the model of the tableting machine(Narang et al., 2010). In addition, in the process of drug
development, it is inevitable that the scale of the tabletingmachine will change, and it is necessary to set new tableting conditions each time. At that time, process parameters
are usually determined based on experience and trial anderror, and thus the development of a convenient method forsetting the parameters in these cases is strongly required.
The tableting simulator developed in recent years canreproduce the tableting process of various rotary tabletingmachines, and can obtain the compaction parameter valuesof various rotary tableting machines even though it is asingle-punch tableting machine.
Using this tableting simulator, evaluation of the effect of
the compression rate on tablet characteristics (Michaut etal., 2010) or evaluation of the pressure applied to the tablet

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

when the tablet is ejected from the die in the tablet ejection
process (Sun, 2015) has been reported. Takahashi et al.
conducted a series of experiments with the goal of efficiently optimizing the tableting conditions associated withchanges in the tableting machine that occur during scale-up
and technology transfer. Even if compaction is performed
under the same conditions by different types of tabletingmachines, the tablet characteristics will change. It was
found using a tableting simulator that the change in tableting speed was most critical to the change in compactibility
and thus tablet properties. As a new prediction model for
determining the optimum tableting conditions when changing the tableting machine, it was found that the area under
the curve (AUC) in the time-pressure profile considering
the compression time is an important parameter (Takahashi
et al., 2019). Based on this concept, a model for predicting
tableting conditions (locking pressure, rotation speed) wasconstructed, and its suitability was confirmed by comparing data from different locking machines (Takahashi et al.,2020). Utilizing these parameters, it will be possible tocompare parameters in the tableting process to standardize
them during scale-up or technology transfer.

4.2 Tableting failures on a production scale
In addition to the capping discussed in section 4.1, several other types of tablet failures occur, such as sticking,binding, and chipping. Among them, sticking, in which apart of the powder adheres to the surface of the punch, may
lead to serious problems in the production scale. It is conceivable that the number of tablets will increase, the surface of the punch will deteriorate due to long-term use, andthe adhesion of powder will proceed more easily. These
sticking obstacles not only affect the product quality, butalso lead to damage to the punch due to the application of
extremely high pressure to the punch. It seems reasonable
to consider that a possible reason for the sticking is thatthe bonding force between the particles in the powder bed
is weaker than that of powder on the surface of the punch.
In order to clarify the detailed mechanism responsible forthe sticking to avoid this tablet failure, several studies
have been conducted. These works have reported various
potential causes of the sticking, such as the physicaland mechanical properties of active powders (Naito andNakamichi, 1969; Danjo et al., 1993), water content,
hygroscopicity of the formulations, lubricant types andconcentrations, (Danjo et al., 1997; Waimer et al., 1999a;
Roberts et al., 2004), tableting tools and punch surface
shapes, and operating conditions (Newton et al., 2000;
Sixsmith and McCluskey, 1981; Waimer et al., 1999b;
Kakimi et al., 2010) such as engraving of the punched sur­face and finishing of the punched surface.
In order to prevent sticking during the production oftablets, it is conceivable that the amount of the binder

could be increased or both the amount of the binder andthe amount of the lubricant in the tablet formulation could
be increased. However, it may be difficult to change theformulation after fixing it for approval. On the productionside, attempts will be made to try to control tableting conditions such as the tableting speed or pressure. Recently,tableting machines companies or manufacturers of partsof machines such as punches and dies have proposed alternative methods to avoid these tablet failures. In one case,the surface treatment of the punch was developed for the
purpose of suppressing the adhesion between the powder
and the surface of the punch and avoiding sticking, andseveral kinds of punches with different surface treatments
are commercially available in Japan. As can be seen fromthe laser micrograph (Fig. 15), the surface of the punch isuneven, unlike the surface of a normal punch. The concept
is that the unevenness reduces the contact area with thepowder and reduces adhesion of the powder. We evaluatedthe effect of a punch surface treatment using these punches
and the effect of reducing adhesion using two types ofpharmaceutical crystals with different plastic deformability(Takeuchi Y. et al., 2020b). Using a single-shot tabletingmachine, tableting was performed up to several times, andthe amount of drug adhering to the surface of the punch
was quantified by HPLC. As a result, in the case of a drug
such as acetaminophen, which was evaluated to have low
plastic deformability as confirmed by the Heckel plot, theunevenness of the punch surface tended to reduce the drug
adhesion to the punch surface (Fig. 16). On the other hand,in the case of ibuprofen, which has a relatively large plastic
deformability, the amount of adhered drug was almost thesame regardless of the presence or absence of unevenness
on the surface of the punch. Rather, the tendency of increasing adhesion of P3, which has the largest unevenness,

Fig. 15 Three-dimensional surface roughness profiles of tableting
punch faces observed by a laser microscope.
Four types of punch, (a) P0, (b) P1, (c) P2 and (d) P3, were supplied by
TWO NINE JAPAN (Kyoto, Japan). P0 is a usual smooth surface punch
and the Sa (the arithmetical mean height of the assessed surface) value
measured by the laser microscope is 0.014. The surface roughness of the
top of punch P1-3 (surface treated punch) is P1 (Sa: 0.180 μm) < P2 (Sa:0.222 μm) < P3 (Sa: 0.304 μm).

163

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Fig. 16 Relationship between the adhesion amounts of formulated
acetaminophen powder on the punch surface and the number of tablet­ing. Compression pressure was 100 MPa. Data are expressed as mean ±SD (n = 3). The types of punch were explained in Fig. 15.

was observed to be the largest. These results suggested thatwhen the plastic deformability is large, the area of contactof the powder on the uneven punch surface during tabletingis large, and thus the adhesion tendency is increased.
As described above, pharmaceutical companies wantto avoid problems such as tableting failures during production, and thus predicting such problems at the time oftablet prescription design is an important goal. For thispurpose, Pitt et al. (Pitt et al., 2015) conducted a study
using the GTP-1® and proposed a criteria for feasibilityof tableting with a formulation. The proposed value of thestrength of tablet (TFS) as measured by GTP-1 is greaterthan 2 MPa in tableting at 200 MPa. They also proposedthat the discharge pressure (ES) should be smaller than
5 MPa. Osamura et al. (2016) systematically compared the
GTP-1 measurement results with the actual tableting results obtained with a rotary tableting machine to determine
TFS and ES. They tried to visually express the tabletingcharacteristics of the prescription by classifying them into
four areas as an index of compactibility and an index of
manufacturability. When the validity of this evaluation
system was verified using pharmaceutical excipients withknown tableting characteristics, the results reflected thecharacteristics of individual excipients (Fig. 17). Furthermore, it was also shown that even with a practical formulation, a series of formulations that may have an effect on
manufacturability, such as a change in the blending amountof a lubricant, can be examined and the effect can be visually confirmed (Osamura et al., 2017). They selected drugs
for which a sticking phenomenon was easily observed,
changed the blending amount of lubricant and tablet shape,and compared the results obtained using GTP-1 and arotary tableting machine. A good correlation between thetwo was obtained even for tablet formulations in which
different amount of the lubricant was formulated and/or fortablets prepared by using different punches having various
shapes. Using the same method, it was also demonstrated
that this estimation for tableting process using the GTP-1®

164

Fig. 17 Plots of compactibility and producibility for pharmaceutical
excipients based on the combination of TFS and Ejection stress measured with GTP-1®.

is feasible for indirect tableting with granulated drugs with
excipients to avoid sticking (Osamura et al., 2018).

5. Liposomal particle design for drug delivery
5.1 Polymer-coated liposomes for efficient drugdelivery
Phospholipids are constituents of cell membranes. The
surface of liposomal particles composed of phospholipid
bilayers can be easily modified with both positive andnegative charges by prescribing a small amount of charged
substance together with phospholipids in the preparation.
By prescribing an appropriate amount of cholesterol, thefluidity of and the degree of hydrophobicity of liposomal
particles can be controlled by controlling the prescribedamount. Furthermore, it has been reported that the surfaceof liposome particles can be modified with polymers,
surfactants, etc. (Sunamoto et al., 1984). Due to these characteristics, liposomes have been studied as drug carriers fortargeting drugs in the body after injection. As described in
the introduction of this manuscript, liposomal injectionsof anticancer agents have been developed as commercial
products. Liposomes have also been studied as drug carriers to avoid a barrier for entry into the body. Research
aimed at gastrointestinal absorption of insulin is a typicalexample of the latter type of application, and has beenstudied by multiple research groups since the mid-1970s(Patel and Ryman, 1976; Dapergolas and Gregoriadis,1976). However, the usefulness of liposomal formulations
for the enteral absorption of insulin has not been confirmed(Pateland Ryman, 1981; Shenfield and Hill, 1982).
We have been conducting studies with a goal of imparting various pharmaceutical functions by controlling thesurface properties of liposome particles. Fig. 18 showsHirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Fig. 18 Schematic presentation of typical polymer-coated liposomes.
(a) chitosan-coated liposome (CS Lip) (b) PVA-R coated liposome.

two typical polymer-coated liposomes designed for thispurpose. One is a comb-shaped coating formed by penetrating a hydrophobic moiety chemically bonded to awater-soluble polymer into a liposome lipid bilayer (theanchor ring method), and the other is a coating created by
the electrical interaction between a charged liposome surface and a polymer having the opposite charge. Regarding
the former, surface modification was demonstrated using a
polymer, PVA-R, in which an alkyl group was introduced
at the end of polyvinyl alcohol (PVA). The formation of the
thick polymer layer was confirmed by measuring the zeta
potential of the liposomes treated with several polymers
under different polymer concentrations (Fig. 19). The zeta
potential of the negatively charged liposomes became
neutral when the polymer concentration was increased.
Compared with the liposomes that physically absorbed
PVA, the stabilizing effect of the PVA-R-coated liposomes
was excellent due to their three-dimensional coating layer(Takeuchi et al., 1994; 1998).
PEGylated liposomes prepared by formulating polyethylene glycol conjugated phospholipids have been studied
extensively as targeting carriers for the anticancer drug
doxorubicin and commercial products for clinical use are
now available (Senior, 1987; Allen et al., 1989; 1991;
Papahadjopoulos et al., 1991). PVA-R-coated liposomes
were found to have a similar function to PEGylated liposomes, such as improving blood retention after intravenous
injection to deliver a drug effectively to cancer tissues inrats (Takeuchi et al., 1999a; 1999b; 2000a; 2001a,b,c).
PEG liposomes form a polymer layer on the surface prepared by formulating PEG conjugated phospholipids as aliposomal component, whereas the polymer layer of PVAR-coated liposomes is able to be formed after preparationof drug loaded liposomes.

Fig. 19 Zeta potential of liposomes coated with various polymers inphosphate buffer solution (pH 7.4).
Lipid composition of liposomes is DPPC:DCP = 8:2.
PVA-R and PAA-R are the PVA (polyvinyl alcohol) and PAA (polyacrylic acid) modified with hydrophobic moiety (R) in the molecules asshown in Fig. 18 (b).
Chitosan: degree of deacetylation = 85 %, molecular weight= ca.150,000.
PVA: degree of polymerization of PVA = 480. PAA: molecular weightof PAA = 250,000.

5.2 Mucoadhesive liposomes for oral
administration of peptide drugs
In order to improve the efficiency of gastrointestinal
absorption, it is conceivable to prolong the residence timeof the drug or the carrier containing the drug after oral
administration. This concept was discussed for potential
application to conventional dosage forms such as tablets or

165

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

granules in the 1980s (Guputa et al., 1990). In order to use
liposomes as a carrier for oral insulin administration, we
considered improving the retention of liposomal particles
in the intestinal tract by allowing their interaction with the
mucin layer on the inner surface of the digestive tract.
Polymer-coated liposome particles having a mucoadhesive function were prepared using chitosan (CS), which isprepared by deacetylating chitin and are reported to interact
with mucin when used as a topical dosage form (Nagai,1985). The mucoadhesive property of polymer-coated lipo­
somes was evaluated by using intestinal tubes separated
from rats. In this test, the number of liposomal particles
withdrawn from the liposomal suspension in the tube wascalculated by using a Coulter counter before and after incubation. The extent of adhesion to the mucous layer in theintestinal tube was expressed by the following equation.
Adhesive(%)


N 0  N15
 100
N0

(3)

were, N0 is the initial number of liposomal particles andN15 is the number of liposomal particles 15 min after in(3)cubation.
As shown in Fig. 20, the highest adhesion property of
CS-coated liposome (CS-Lip) was confirmed in this invitro test (Takeuchi et al., 1994). The affinity of CS-Lip
to the mucosa is presumed to be due to the electrostaticinteraction between the positive charge of the aminogroup of CS and the negative charge of mucin, which isa mucosal component. The physical interaction due to theentanglement of both polymers is also responsible for thisadhesion. The latter interaction was supported by the fact

Fig. 20 Adhesive % of polymer-coated liposomes to rat intestine
evaluated with the particle counting method.
Lipid composition: DPPC:DCP = 8:2. Polymer concentration: 0.75 %.
Dispersion medium: phosphate buffer solution (pH 7.4).
Properties of polymers used for coating liposomes are shown in Fig. 19.
The results are expressed as mean ± sd of three experiments.
Significantly different from the value for noncoated liposomes at
p < 0.01 (**) and p < 0.05 (*).

166

that negatively charged acrylic acid polymer (PAA)-coatedliposomes also showed the mucosal adhesion properties. It
is believed that the acid polymer (PAA)-coated liposomes
also showed the mucosal adhesion properties. It is believedthat the negative charge of PAA extends linearly without
shrinking the polymer and works effectively for entanglement with mucin.
CS-Lip encapsulating insulin was orally administeredin rats, and the blood glucose levels were measured toevaluate their effectiveness in enteral absorption. A significant decrease in the blood glucose level was observed
after administration of CS-Lip, confirming the enteralabsorption of insulin. The significant decrease in value wasmaintained up to 12 hours, suggesting the retention of theliposomal carrier in the intestinal tract due to the mucosal
adhesion property (Fig. 21) (Takeuchi et al., 1996). The
importance of the CS layer for mucosal adhesion and resultant insulin absorption was revealed by the fact that no
significant effect was observed under the same conditions
when liposomes having a positive charge were used as acarrier. The usefulness of polymer-coated liposomes forthe oral administration of peptide drugs was confirmed
by using another model peptide drug, calcitonin. A single
administration of calcitonin encapsulated in CS-Lip leadto a decrease in the blood calcium concentration in rats fora long period of time (Fig. 22) (Takeuchi et al., 2003a).
It was also clarified that the particle size is an importantfactor for drug absorption (pharmacological effect) withmucoadhesive liposomes, because the absorption increased
remarkably when the particle size was decreased to submicron size. Since these differences were considered to berelated to the behavior of liposomes in the gastrointestinal
tract, the intestinal tube was taken out after administrationof several types of liposomes containing a lipophilic fluorescent marker in rats and its cross section was observed

Fig. 21 Change in serum glucose level (%) after oral administration of
insulin (24 IU/rat) with the non-coated and polymer-coated liposomes.
Each value represents the mean.SE of four or five rats.;* : p < 0.05, ** : p < 0.01. Lipid composition: PPC:DCP = 8:2.
Polymer concentration: 0.75 %Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

with a confocal laser scanning microscope. It was confirmed that the CS-Lip had a longer residence time in theintestinal tract compared with the uncoated liposomes, andFig. 22 Profiles of plasma calcium levels after intragastric administration of sub-micron sized liposomes (ssLip) and sub-micron sizedchitosan coated liposomes (ssCS-Lip) containing calcitonin.
The measured mean particles sizes of ssLip and ssCS-Lip are 196.4 nm
and 473.4 nm, respectively. The formulation of liposomes is DSPC:
DCP:Chol. = 8:2:1. The concentration of chitosan for coating is 0.3 %.
* p < 0.05, ** p < 0.01, *** p < 0.001: significantly different from thelevel for calcitonin solution; † p < 0.05, †† p < 0.01: significantly different
from the level for ssLip (n = 3 in each case).

they adhered more to the upper part of the intestinal tract(Fig. 23(A), (B)). By reducing the particle size of CS-Lip
to the submicron size, the number of liposomes retainedin the intestinal tube was considerably increased, and theliposomal particles were observed to be penetrated into
the mucosa over time (Fig. 23(C)) (Takeuchi et al., 2001d;
2005a). It was also confirmed that CS in the CS-Lip moved
in the digestive tract together with liposomal particles(Thongborisute et al., 2006).
Following the demonstration of the usefulness ofliposomes with mucosal adhesion properties for the oral
administration of peptide drugs, studies on the characterization of the mucoadhesive properties of polymers werecarried out to understand the mucoadhesive mechanism.
Novel methods for evaluating mucoadhesive properties ofpolymers in vitro were also developed. The methods include a simple mucin particles method and Biacoa methodfor quantitative evaluation (Takeuchi et al., 2005c). In thelatter method, an interaction analyzer, Biacoa, based on
surface plasmon resonance is used to try to evaluate the
mucoadhesive property. We also tried to improve the mucosal adhesive property of polymers themselves by partly
modifying the molecules or conjugation of different typesof polymers. One of examples is chitosan-aprotinin (Werle
et al., 2009a; 2009b). Carbopol is a commercial product ofpolyacrylic acid, whose mucoadhesive property has beenFig. 23 Confocal laser scanning micrographs of various parts of intestinal tract at 120 min after intragastrical administration of (A) Lip (MLVs), (B)
CS-Lip (MLVs), (C) ssCS-Lip in rats and a schematical picture the rat intestinal sample for measuring the CLSM photos.
Lipid formulation of liposomes: DSPC:DCP:Chol. = 8:2:1. Mean particle size of liposomes: (A) 7.56 μm, (B) 3.58 μm, (C) 281.2 nm.
MLVs: multilamellar vehicles. CLSM: Confocal Laser Scanning Microscope.

167

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

reported. The mucoadhesive property of Carbopol was
found to be improved by conjugating with lectin or WGA(wheat germ agglutinin) (Werle et al., 2010; Makhlof et al.,2011a). It was also confirmed that simultaneous encapsulation of water-soluble absorption enhancers into liposomal
carriers greatly improved the absorption of calcitonin(Makhlof et al., 2011b). With respect to the absorption
control with these liposomal carriers, the mucoadhesivefunctions of CS-Lips were demonstrated to render themeffective as carriers for a small molecule, indomethacin,by measuring the actual absorption amount (Sugihara etal., 2012). Recently, we also confirmed the delivery of amodel hydrophilic macromolecule, dextran labeled withfluorescein isothiocyanate (FITC), with an average molecular weight of ca. 4000 daltons (FD-4) or more, to systemic
blood flow by absorption in the digestive tract after oral
administration with liposomal formulations. The absorption amount was greatly increased by very small when aFD-4 solution was administered. The amount of absorption
was greatly increased by simultaneously encapsulating anabsorption enhancer, spermine (Fig. 24). The simultaneousadministration of spermine dissolved in a FD-4 solution
had almost no effect on the absorption, indicating that it isimportant for the absorption enhancer to be delivered to theabsorption site in the gastrointestinal tract together with theabsorbed macromolecular drug. These absorption data are
well consistent with the pharmacological data shown abovein this section.
Comprehensively considering the behavior of liposome
particles in the gastrointestinal tract and absorption experiments, the absorption of peptide drugs in the gastro-Fig. 25168

intestinal tract by muco-adhesive micronized liposomes
represented by submicron-sized CS-Lip (ssCS-Lip) canbe represented schematically as shown in Fig. 25. As
predicted at the beginning of the study, the mucous membrane (mucosa) presents a large barrier to the absorption ofmacromolecular drugs in the gastrointestinal tract. CS-Lipsinteract with and retain the mucous layer on the epithelial
cell in the flow of the intestinal tract and penetrate moredeeply if the particles are small enough. We speculate thatsome of the particles are taken up by mucosal epithelial
cells as they are. Considering that the absorption enhancer
that was administered simultaneously with the particles

Fig. 24 Plasma FD-4 concentration profiles for 6 hours after oral
administration of several liposomal formulations containing FD-4 andFD-4 solution in rats.
FD-4: FITC-dextran, with an average molecular weight of ca. 4000
daltons. SPM: spermine. Dose of FD-4 is 32 mg/kg. n = 4–5, ** p < 0.01
and *p < 0.1 compared with CS Lip.

Possible mechanism of absorption of peptide drug entrapped in CS-Lips in the intestinal tube after oral administration.

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

worked effectively, it can be inferred that some macromolecular drugs are released in the mucous layer and permeate
tight junctions from there.

5.3 Transpulmonary administration of liposomal
drugs
Inhalation systems can be a useful drug delivery method
for both topical and systemic administration of drugs.
Several types of research have been conducted on suchadministration systems, because particle design including
nanoparticle engineering and characterization is importantto achieve the most efficient drug delivery (Johnson et al.,2020; Price et al., 2019). Kawashima et al. have also tried
to prepare suitable drug crystals and their formulations fordry powder inhalation systems (Kawashima et al., 1998a;
1998b). In terms of peptide drug administration, the lungis highly expected to be a suitable site for systemic administration of drugs. In fact, Exubera® and Afrezza® havebeen developed and marketed as powdered inhaled insulin
preparations. On the other hand, the lungs can be affectedby intractable diseases such as lung cancer and chronic
obstructive pulmonary disease, and research on new drug
treatments such as nucleic acid drugs is progressing. In
such cases, it is highly expected that the development of asuitable delivery system such as liposomes will be utilized
as a topical dosage form.
In comparing pulmonary administration with oral administration, the lungs are a closed system and there
are few degrading enzymes, so it is expected that pulmonary administration of peptide drugs will lead toabsorption. When calcitonin solution and various types ofpolymer-coated liposomes encapsulating calcitonin wereadministered intrapulmonarily, the effect of the coating
polymer on drug absorption was found to be different fromthat in oral administration, as shown in Fig. 26 (Murata etal., 2012). There was a difference in the degree, with thehighest absorption-enhancing effect being observed for the
PVA-R-coated liposomes. We conjectured that the PVA-Rcoated liposomes showed the highest absorption because
the PVA coating on the liposome avoided phagocytosisby alveolar macrophages and increased the retention time(Nakano et al., 2008). This idea was proved by measuring
the retention of these polymer-coated liposomes. In fact,
when we evaluated the retention of CS-Lips and PVA-Rcoated liposomes in the lungs, we found that a large numberof CS-Lips remained in the lung tissue and a large numberof PVA-R-coated liposomes remained in the bronchoalveolar lavage fluid (BALF). The finding that the retention of
PVA-R-coated liposomes was extended after pulmonary
administration was further confirmed by a non-invasive
method using an in vivo imaging system and a fluorescencemarker, indocyanine green (Murata et al., 2014). In the caseof PVA-R, the drug encapsulated in liposomes remained forFig. 26 Blood calcium concentration after intratracheal administration of calcitonin with polymer coated liposomes.
Experimental conditions
Animal Male Wistar rats (6 weeks), n = 4
RouteIntratracheal administration
Dose
125 IU/kg
Analysis Calcium E-test Wako

a longer period of time and then was gradually released into
the lungs, which lead to a sustained efficacy. In the caseof transpulmonary administration, a trial using the model
polymer drug FITC-Dextran confirmed that the absorption
actually occurs at the higher level than by oral administration. We have recently confirmed that FITC-Dextran (FD4), which has an average molecular weight of 4000, wasabsorbed even when administered as an aqueous solution.

5.4 Drug delivery to the posterior segment of theeye with liposomes
As a clearer example of the role of drug delivery systems
in the local administration of drugs, we attempted to delivera drug to the posterior segment of the eye by an instillation
centered on the retina. In recent years, with the rapid aging of the population in Japan, the incidence of posterior
ocular diseases such as glaucoma, diabetic retinopathy,
age-related macular degeneration (AMD), and retinitis
pigmentosa has rapidly increased, such that new and more
effective drug therapies are needed. VGF, a growth factor,
is known to have an important role in cell generation.
An anti-VEGF (vascular endothelial growth factor) thatsuppresses the generation of new, edema-induced bloodvessels appearing near the macula of the retina with highprobability has been developed. However, its delivery is
generally limited to invasive intravitreal injections. However, eye drops containing the anti-VGEF antibody andexerting suitable anti-inflammatory and antioxidant effects
are also available, and if these drops could be reliably
delivered to the posterior segment of the eye, they could
potentially be used to treat the above-named diseases.
For the purpose of evaluating the transfer of liposome
particles into the posterior segment of the eye after

169

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Fig. 27

Delivery of coumarin-6 with liposome to posterior part of eye confirmed by fluorescence microscopy observation.

instillation, a liposome suspension containing coumarin-6
as a fluorescent marker was instilled in mice, and the retina
was observed with fluorescent microscopy. In the case ofsubmicron-sized liposomal particles, the observation of thecoumarin-6 color was used to confirm that the particles had
reached their target (Fig. 27) (Hironaka et al., 2009). To
confirm that the size of the particles affected their ability tomove to the posterior part of the eye, a similar evaluation
was performed by using liposomal particles having different particle sizes ranging from the micron order to 100 nm.
The results showed that the smaller the particle size, thebetter the delivery efficiency (Inokuchi et al., 2010). Since
not only particle size but also the lipid composition was
found to affect the ability to reach the target, the hardnessof the liposome particles was also one of the factors.
To confirm the clinical effects of liposomal carriers ineye drop instillation, we tried to conduct animal experiments as a joint research project with a laboratory equippedfor ophthalmic evaluation. When liposomes encapsulating
edaravone, a free radical scavenger, were instilled intoa model mouse before light irradiation to induce retinal
photodamage, the liposomal formulation was confirmed
to be effective at preventing the subsequent photodamage (Hironaka et al., 2011). It was also clarified that
diclofenac, which is one of the NSAIDs (nonsteroidal antiinflammatory drugs), can suppress choroidal neovascularization due to retinal photodamage in mice when instilled
as a drug encapsulated in liposomes (Fujisawa et al., 2012;
Shimazawa et al., 2017). In either case, such a pharmaceutical effect in the retinal area was not observed when the170

solutions dissolving these drugs were instilled under thesame conditions for comparison, and it could be judgedthat the drug could be delivered to the vicinity of the retina
by the liposomal eye drop preparation. A newly developed
macromolecular API was also applied to this liposomal
system and confirmed to achieve a higher pharmacologicaleffect in mice (Taketani et al., 2016).
As with oral and transpulmonary administration, an
increase in the amount or duration in drug delivering bypolymer-coated liposomes was also investigated. PolyL-lysine (PLL) and polyarginine (PLA), which havebeen reported to have affinity for cells, were tested ascoating polymers, and the delivery efficiency of thesepolymer-coated liposomes to the posterior segment of theeye was assessed (Sasaki et al., 2013). The results showedthat the larger the molecular weight of the polymer, thegreater the effect. However, the efficiency decreased owing
to the aggregation of liposomes if the molecular weight ofthe polymer was too large. Thus, an optimum molecularweight existed, and this weight was determined to be
15,000 daltons in the case of PLL. Active targeting withpolymer-coated liposomes has been tested in this ophthalmic liposomal system. One of the targets is folic acidreceptors, and an enhancement in delivering efficiency has
been observed by modifying the surface of liposomes with
folic acid. The delivery of macromolecules to the posterior
part of the eye has also been attempted by using FITCdextran as a drug model, and the feasibility of this approach
was confirmed. Based on this finding, it is expected thatmacromolecular APIs such as siRNA and Bonac nucleicHirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

acid can also be delivered to the posterior segment of theeye. Further research is ongoing.

6. Conclusion
Research on formulation design and dosage form designfor drug delivery were described in this review. Regarding
the design of solid dosage forms, the particle design ofdrug crystals and several excipients have important roles
for the objective functions of the resultant dosage forms. It
is important to image the objective functions expected bypatients as a final goal of research. Regarding the deliveryof macromolecular drugs, colloidal drug carriers haveimportant roles, and the concept of particle design is also
important even for these colloidal particles. The suitable
design of submicron-sized particles such as polymercoated liposomes not only improves the efficiency in drugdelivery as a drug-targeting tool but also leads to the development of new drug delivery methods such as the oral
administration of peptide drugs. As briefly discussed inthis paper, it is necessary for pharmaceutical researchers toaccount for the actual needs of patients as well as the needsof the researchers and medical personnel. It is expectedthat several types of particle design research for a varietyof pharmaceutical materials will contribute to the design oftruly patient-friendly dosage forms to solve various issues
related to the unmet needs of patients.

References
Allen T.M., Hansen C., Martin F., Redemann C., Yau-Young A.,
Liposomes containing synthetic lipid derivatives of poly(ethylene glycol) show prolonged circulation half-lives in vivo,
Biochimica et Biophysica Acta (BBA)—Biomembranes,
1066 (1991) 29–36. DOI: 10.1016/0005-2736(91)90246-5
Allen T.M., Hansen C., Rutledge J., Liposomes with prolonged
circulation times: factors affecting uptake by reticuloendothelial and other tissues, Biochimica et Biophysica
Acta (BBA)—Biomembranes, 981 (1989) 27–35. DOI:
10.1016/0005-2736(89)90078-3
Amidon G.L., Lennernäs H., Shah V.P., Crison J.R., A theoreticalbasis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability, Pharmaceutical Research, 12 (1995) 413–420. DOI:
10.1023/A:1016212804288
Buckton G., Darcy P., Water mobility in amorphous lactose below
and close to the glass transition temperature, International
Journal of Pharmaceutics, 136 (1996) 141–146. DOI:
10.1016/0378-5173(96)04503-6
Carless J.E., Leigh S., Compression characteristics of powders:radial die wall pressure transmission and density changes,
Journal of Pharmacy and Pharmacology, 26 (1974) 289–297.
DOI: 10.1111/j.2042-7158.1974.tb09278.x
Chiou W.L., Riegelman S., Preparation and dissolution characteristics of several fast-release solid dispersions of griseofulvin,
Journal of Pharmaceutical Sciences, 58 (1969) 1505–1510.

DOI: 10.1002/jps.2600581218
Corrigan O.I., Holohan E.M., Sabra K., Amorphous forms ofthiazide diuretics prepared by spray-drying, International
Journal of Pharmaceutics, 18 (1984) 195–200. DOI:
10.1016/0378-5173(84)90119-4
Corrigan O.I., Sabra K., Holohan E.M., Physicochemical properties of spray dried drugs: phenobarbitone and hydroflumethiazide, Drug Development and Industrial Pharmacy, 9 (1983)
1–20. DOI: 10.3109/03639048309048541
Couvreur P., Kante B., Roland M., Guiot P., Bauduin P., Speiser P.,
Polycyanoacrylate nanocapsules as potential lysosomotropic
carriers: preparation, morphological and sorptive properties,
Journal of Pharmacy and Pharmacology, 31 (1979) 331–332.
DOI: 10.1111/j.2042-7158.1979.tb13510.x
Danjo K., Kamiya K., Otsuka A., Effect of temperature on
the sticking of low melting point materials, Chemical &Pharmaceutical Bulletin, 41 (1993) 1423–1427. DOI:
10.1248/cpb.41.1423
Danjo K., Kojima S., Chen C.Y., Sunada H., Otsuka A., Effect ofwater content on sticking during compression, Chemical &Pharmaceutical Bulletin, 45 (1997) 706–709. DOI: 10.1248/
cpb.45.706
Dapergolas G., Gregoriadis G., Hypoglycæmic effect ofliposome-entrapped insulin administered intragastricallyinto rats, The Lancet, 308 (1976) 824–827. DOI: 10.1016/
S0140-6736(76)91209-5
Ford J.L., The current status of solid dispersions, Pharmaceutica
Acta Helvetiae, 61 (1986) 69–88. https://pubmed.ncbi.nlm.
nih.gov/3520598/
Fujisawa T., Miyai H., Hironaka K., Tsukamoto T., Tahara K.,
Tozuka Y., Ito M., Takeuchi H., Liposomal diclofenac eye
drop formulations targeting the retina: formulation stability
improvement using surface modification of liposomes,
International Journal of Pharmaceutics, 436 (2012) 564–567.
DOI: 10.1016/j.ijpharm.2012.07.024
Gupta P.K., Leung S.-H.S., Robinson J.R., Bioadhesives/mucoadhesives in drug delivery to the gastrointestinal tract, in:Vincent Lenaerts, Gurny Robert (Eds.) Bioadhesive Drug
Delivery Systems, CRC Press, Florida, 1990, pp. 65–92,
ISBN 9780849353673.
Heckel R.W., Density-pressure relationships in powder compaction, Transactions of the Metallurgical Society of AIME, 221(1961a) 671–675.
Heckel R.W., An analysis of powder compaction phenomena,
Transactions of the Metallurgical Society of AIME, 221(1961b) 1001–1008.
Hiestand E.N., Wells J.E., Peot C.B., Ochs J.F., Physical processes of tableting, Journal of Pharmaceutical Sciences, 66(1977) 510–519. DOI: 10.1002/jps.2600660413
Hironaka K., Inokuchi Y., Fujisawa T., Shimazaki H., Akane M.,
Tozuka Y., Tsuruma K., Shimazawa M., Hara H., Takeuchi
H., Edaravone-loaded liposomes for retinal protection
against oxidative stress-induced retinal damage, European
Journal of Pharmaceutics and Biopharmaceutics, 79 (2011)
119–125. DOI: 10.1016/j.ejpb.2011.01.019
Hironaka K., Inokuchi Y., Tozuka Y., Shimazawa M., Hara H.,
Takeuchi H., Design and evaluation of a liposomal delivery
system targeting the posterior segment of the eye, Journal ofControlled Release, 136 (2009) 247–253. DOI: 10.1016/j.
jconrel.2009.02.020
Humbert-Droz P., Gurny R., Mordier D., Doelker E., Densification behaviour of drugs presenting availability problems,International Journal of Pharmaceutical Technology andProduct Manufacture, 4 (1983) 29–35.
Inokuchi Y., Hironaka K., Fujisawa T., Tozuka Y., Tsuruma K.,

171

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Shimazawa M., Takeuchi H., Hara H., Physicochemical
properties affecting retinal drug/coumarin-6 delivery fromnanocarrier systems via eyedrop administration, Investigative Ophthalmology & Visual Science, 51 (2010) 3162–3170.
DOI: 10.1167/iovs.09-4697
Johnson L.M., Mecham J.B., Quinn F., Hickey A.J., Nanoparticle
technology for respiratory tract mucosal vaccine delivery,
KONA Powder and Particle Journal, 37 (2020) 97–113. DOI:
10.14356/kona.2020013
Kakimi K., Niwa T., Danjo K., Influence of compression pressureand velocity on tablet sticking, Chemical and Pharmaceutical
Bulletin, 58 (2010) 1565–1568. DOI: 10.1248/cpb.58.1565
Kakino Y., Hishikawa Y., Onodera R., Tahara K., Takeuchi H.,
Gelation factors of pectin for development of a powder formof gel, dry jelly, as a novel dosage form, Chemical and Pharmaceutical Bulletin, 65 (2017) 1035–1044. DOI: 10.1248/
cpb.c17-00447
Kawashima Y., Serigano T., Hino T., Yamamoto H., Takeuchi
H., A new powder design method to improve inhalation
efficiency of pranlukast hydrate dry powder aerosols by
surface modification with hydroxypropylmethylcellulose
phthalate nanospheres, Pharmaceutical Research, 15 (1998a)
1748–1752. DOI: 10.1023/A:1011916930655
Kawashima Y., Serigano T., Hino T., Yamamoto H., Takeuchi H.,
Design of inhalation dry powder of pranlukast hydrate toimprove dispersibility by the surface modification with lightanhydrous silicic acid (AEROSIL 200), International Journalof Pharmaceutics, 173 (1998b) 243–251. DOI: 10.1016/
S0378-5173(98)00243-9
Keck C.M., Müller R.H., Drug nanocrystals of poorly soluble
drugs produced by high pressure homogenisation, European
Journal of Pharmaceutics and Biopharmaceutics, 62 (2006)
3–16. DOI: 10.1016/j.ejpb.2005.05.009
Knight C.G. (Ed.), Liposomes: From Physical Structure to Therapeutic Applications, Elsevier, Amsterdam (1981), ISBN:
9780444803207.
Kreuter K. (Ed.), Colloidal Drug Delivery Systems., Marcell
Dekker, New York (1994). ISBN: 9780824792145.
Kuno Y., Kojima M., Ando S., Nakagami H., Effect of preparation
method on properties of orally disintegrating tablets made byphase transition, International Journal of Pharmaceutics, 355(2008) 87–92. DOI: 10.1016/j.ijpharm.2007.11.046
Liversidge G.G., Cundy K.C., Particle size reduction for improvement of oral bioavailability of hydrophobic drugs: I. Absoluteoral bioavailability of nanocrystalline danazol in beagle dogs,
International Journal of Pharmaceutics, 125 (1995) 91–97.
DOI: 10.1016/0378-5173(95)00122-Y
Makhlof A., Fujimoto S., Tozuka Y., Takeuchi H., In vitro andin vivo evaluation of WGA–carbopol modified liposomes
as carriers for oral peptide delivery, European Journal of
Pharmaceutics and Biopharmaceutics, 77 (2011a) 216–224.
DOI: 10.1016/j.ejpb.2010.12.008
Makhlof A., Werle M., Tozuka Y., Takeuchi H., A mucoadhesive
nanoparticulate system for the simultaneous delivery ofmacromolecules and permeation enhancers to the intestinal
mucosa, Journal of Controlled Release, 149 (2011b) 81–88.
DOI: 10.1016/j.jconrel.2010.02.001
McGinity J.W. (Ed.), Aqueous Polymeric Coatings for Pharmaceutical Dosage Forms, 2nd ed., Marcel Dekker, New York
(1997), ISBN: 9780824797737.
Merisko-Liversidge E., Liversidge G.G., Cooper E.R., Nanosizing: a formulation approach for poorly-water-solublecompounds, European Journal of Pharmaceutical Sciences,18 (2003) 113–120. DOI: 10.1016/S0928-0987(02)00251-8
Michaut F., Busignies V., Fouquereau C., Huet de Barochez B.,

172

Leclerc B., Tchoreloff P., Evaluation of a rotary tablet press
simulator as a tool for the characterization of compaction
properties of pharmaceutical products, Journal of Pharmaceutical Sciences, 99 (2010) 2874–2885. DOI: 10.1002/
jps.22032
Müller R.H., Peters K., Nanosuspensions for the formulation ofpoorly soluble drugs: i. preparation by a size-reduction technique, International Journal of Pharmaceutics, 160 (1998)
229–237. DOI: 10.1016/S0378-5173(97)00311-6
Murata M., Nakano K., Tahara K., Tozuka Y., Takeuchi H.,
Pulmonary delivery of elcatonin using surface-modified
liposomes to improve systemic absorption: polyvinyl alcoholwith a hydrophobic anchor and chitosan oligosaccharide aseffective surface modifiers, European Journal of Pharmaceutics and Biopharmaceutics, 80 (2012) 340–346. DOI:
10.1016/j.ejpb.2011.10.011
Murata M., Tahara K., Takeuchi H., Real-time in vivo imaging
of surface-modified liposomes to evaluate their behavior
after pulmonary administration, European Journal of Pharmaceutics and Biopharmaceutics, 86 (2014) 115–119. DOI:
10.1016/j.ejpb.2013.09.006
Nagai T., Adhesive topical drug delivery system, Journal ofControlled Release, 2 (1985) 121–134. DOI: 10.1016/01683659(85)90038-0
Naito S., Nakamichi K., Studies on techniques of manufacturing
pharmacy. i. prediction of tableting troubles such as cappingand sticking. (i), Chemical & Pharmaceutical Bulletin, 17(1969) 2507–2514. DOI: 10.1248/cpb.17.2507
Nakano K., Tozuka Y., Takeuchi H., Effect of surface properties ofliposomes coated with a modified polyvinyl alcohol (PVA-R)
on the interaction with macrophage cells, International Journal of Pharmaceutics, 354 (2008) 174–179. DOI: 10.1016/j.
ijpharm.2007.08.046
Narang A.S., Rao V.M., Guo H., Lu J., Desai D.S., Effect of force
feeder on tablet strength during compression, International
Journal of Pharmaceutics, 401 (2010) 7–15. DOI: 10.1016/j.
ijpharm.2010.08.027
Newton J.M., Haririan I., Podczeck F., The influence of punch
curvature on the mechanical properties of compacted powders, Powder Technology, 107 (2000) 79–83. DOI: 10.1016/
S0032-5910(99)00173-4
Okuda Y., Irisawa Y., Okimoto K., Osawa T., Yamashita S., A
new formulation for orally disintegrating tablets using asuspension spray-coating method, International Journalof Pharmaceutics, 382 (2009) 80–87. DOI: 10.1016/j.
ijpharm.2009.08.010
Osamura T., Takeuchi Y., Onodera R., Kitamura M., TakahashiY., Tahara K., Takeuchi H., Characterization of tableting
properties measured with a multi-functional compaction
instrument for several pharmaceutical excipients and actual
tablet formulations, International Journal of Pharmaceutics,
510 (2016) 195–202. DOI: 10.1016/j.ijpharm.2016.05.024
Osamura T., Takeuchi Y., Onodera R., Kitamura M., Takahashi Y.,
Tahara K., Takeuchi H., Prediction of effects of punch shapes
on tableting failure by using a multi-functional single-punch
tablet press, Asian Journal of Pharmaceutical Sciences, 12(2017) 412–417. DOI: 10.1016/j.ajps.2017.05.001
Osamura T., Takeuchi Y., Onodera R., Kitamura M., TakahashiY., Tahara K., Takeuchi H., Formulation design of granules
prepared by wet granulation method using a multi-functional
single-punch tablet press to avoid tableting failures, Asian
Journal of Pharmaceutical Sciences, 13 (2018) 113–119.
DOI: 10.1016/j.ajps.2017.08.002
Papahadjopoulos D., Allen T.M., Gabizon A., Mayhew E.,
Matthay K., Huang S.K., Lee K.D., Woodle M.C., LasicHirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

D.D., Redemann C., Sterically stabilized liposomes:
improvements in pharmacokinetics and antitumor therapeutic
efficacy, Proceedings of the National Academy of Sciences,
88 (1991) 11460–11464. DOI: 10.1073/pnas.88.24.11460
Patel H.M., Ryman B.E., Oral administration of insulin by encapsulation within liposomes, FEBS Letters, 62 (1976) 60–63.
DOI: 10.1016/0014-5793(76)80016-6
Patel H.M., Ryman B. E., Systemic and oral administration ofliposomes, In: C.G. Knight (Ed.), Liposomes: From Physical
Structure to Therapeutic Applications, Elsevier, Amsterdam,
1981, pp. 409–441. ISBN: 9780444802347.
Picker K.M., Time dependence of elastic recovery for characterization of tableting materials, Pharmaceutical Development
and Technology, 6 (2001) 61–70. DOI: 10.1081/PDT100000014
Pikal M.J., Lukes A.L., Lang J.E., Gaines K., Quantitative
crystallinity determinations for β-lactam antibiotics bysolution calorimetry: correlations with stability, Journal of
Pharmaceutical Sciences, 67 (1978) 767–773. DOI: 10.1002/
jps.2600670609
Pitt K.G., Webber R.J., Hill K.A., Dey D., Gamlen M.J., Compression prediction accuracy from small scale compaction
studies to production presses, Powder Technology, 270(2015) 490–493. DOI: 10.1016/j.powtec.2013.10.007
Ponchel G., Montisci M.-J., Dembri A., Durrer C., Duchêne
D., Mucoadhesion of colloidal particulate systems in thegastro-intestinal tract, European Journal of Pharmaceutics
and Biopharmaceutics, 44 (1997) 25–31. DOI: 10.1016/
S0939-6411(97)00098-2
Price D.N., Kunda N.K., Muttil P., Challenges associated with thepulmonary delivery of therapeutic dry powders for preclinical testing, KONA Powder and Particle Journal, 36 (2019)
129–144. DOI: 10.14356/kona.2019008
Roberts M., Ford J.L., Rowe P.H., Dyas A.M., MacLeod G.S., Fell
J.T., Smith G.W., Effect of lubricant type and concentrationon the punch tip adherence of model ibuprofen formulations,
Journal of Pharmacy and Pharmacology, 56 (2004) 299–305.
DOI: 10.1211/0022357022827
Saleki-Gerhardt A., Zografi G., Non-isothermal and isothermal crystallization of sucrose from the amorphous state,
Pharmaceutical Research, 11 (1994) 1166–1173. DOI:
10.1023/A:1018945117471
Sasaki H., Karasawa K., Hironaka K., Tahara K., Tozuka Y.,
Takeuchi H., Retinal drug delivery using eyedrop preparations of poly-l-lysine-modified liposomes, European Journalof Pharmaceutics and Biopharmaceutics, 83 (2013) 364–369.
DOI: 10.1016/j.ejpb.2012.10.014
Seager H., Drug-delivery products and the Zydis fast-dissolving
dosage form, Journal of Pharmacy and Pharmacology, 50(2011) 375–382. DOI: 10.1111/j.2042-7158.1998.tb06876.x
Sebhatu T., Ahlneck C., Alderborn G., The effect of moisture
content on the compression and bond-formation propertiesof amorphous lactose particles, International Journal of
Pharmaceutics, 146 (1997) 101–114. DOI: 10.1016/S03785173(96)04777-1
Sebhatu T., Elamin A.A., Ahlneck C., Effect of moisture sorption
on tabletting characteristics of spray dried (15 % amorphous)
lactose, Pharmaceutical Research, 11 (1994) 1233–1238.
DOI: 10.1023/A:1018973923831
Sekiguchi K., Obi N., Studies on absorption of eutectic mixture. i.
a comparison of the behavior of eutectic mixture of sulfathiazole and that of ordinary sulfathiazole in man, Chemical &Pharmaceutical Bulletin, 9 (1961) 866–872. DOI: 10.1248/
cpb.9.866
Senior J.H., Fate and behavior of liposomes in vivo: a review ofcontrolling factors, Critical Reviews in Therapeutic Drug
Carrier Systems, 3 (1987) 123–193. PMID: 3542245.
Shenfield G.M., Hill J.C., Infrequent response by diabetic rats toinsulin-liposomes, Clinical and Experimental Pharmacology
and Physiology, 9 (1982) 355–361. DOI: 10.1111/j.14401681.1982.tb00819.x
Shimazawa M., Inoue Y., Masuda T., Onodera R., Tahara K.,
Shimizu Y., Mibe Y., Tsuruma K., Takeuchi H., Hara H.,
Topical diclofenac-loaded liposomes ameliorate laserinduced choroidal neovascularization in mice and nonhuman primates, Current Neurovascular Research, 14 (2017)
46–52. DOI: 10.2174/1567202614666161104115440
Simonelli A.P., Mehta S.C., Higuchi W.I., Dissolution rates ofhigh energy polyvinylpyrrolidone (PVP)-sulfathiazole coprecipitates, Journal of Pharmaceutical Sciences, 58 (1969)
538–549. DOI: 10.1002/jps.2600580503
Sixsmith D., McCluskey D., The effect of punch tip geometry
on powder movement during the tableting process, Journalof Pharmacy and Pharmacology, 33 (1981) 79–81. DOI:
10.1111/j.2042-7158.1981.tb13715.x
Stubberud L., Arwidsson H.G., Hjortsberg V., Graffner C., Watersolid interactions. iii. effect of glass transition temperature,
Tg, and processing on tensile strength of compacts oflactose and lactose/polyvinyl pyrrolidone, Pharmaceutical
Development and Technology, 1 (1996) 195–204. DOI:
10.3109/10837459609029894
Stubberud L., Forbes R.T., The use of gravimetry for the studyof the effect of additives on the moisture-induced recrystallisation of amorphous lactose, International Journal of
Pharmaceutics, 163 (1998) 145–156. DOI: 10.1016/S03785173(97)00382-7
Sugihara H., Yamamoto H., Kawashima Y., Takeuchi H., Effectiveness of submicronized chitosan-coated liposomes in oral
absorption of indomethacin, Journal of Liposome Research,
22 (2012) 72–79. DOI: 10.3109/08982104.2011.621128
Sugimori K., Mori S., Kawashima Y., Characterization of diewall pressure to predict capping of flat- or convex-faced
drug tablets of various sizes, Powder Technology, 58 (1989a)
259–264. DOI: 10.1016/0032-5910(89)80052-X
Sugimori K., Mori S., Kawashima Y., Introduction of new index
for the prediction of capping tendency of tablets, Chemical& Pharmaceutical Bulletin, 37 (1989b) 458–462. DOI:
10.1248/cpb.37.458
Sugimoto M., Narisawa S., Matsubara K., Yoshino H., Nakano M.,
Handa T., Development of manufacturing method for rapidly
disintegrating oral tablets using the crystalline transition of
amorphous sucrose, International Journal of Pharmaceutics,
320 (2006) 71–78. DOI: 10.1016/j.ijpharm.2006.04.004
Sun C.C., Dependence of ejection force on tableting speed—Acompaction simulation study, Powder Technology, 279(2015) 123–126. DOI: 10.1016/j.powtec.2015.04.004
Sunamoto J., Iwamoto K., Takada M., Yuzuriha T., Katayama
K., Polymer Coated Liposomes for Drug Delivery to Target
Specific Organs, in: Anderson J.M., Kim S.W. (Eds.), Recent
Advances in Drug Delivery Systems, Springer US, Boston,MA, 1984, pp. 153–162, ISBN: 978-1-4613-2745-5. DOI:
10.1007/978-1-4613-2745-5_10
Tahara K., Nishikawa M., Matsui K., Hisazumi K., Onodera R.,
Tozuka Y., Takeuchi H., In vitro and in vivo characterizationof drug nanoparticles prepared using PureNanoTM continuous
crystallizer to improve the bioavailability of poorly water soluble drugs, Pharmaceutical Research, 33 (2016) 2259–2268.
DOI: 10.1007/s11095-016-1964-7
Takahashi T., Toyota H., Kuroiwa Y., Yoshino H., Kondou H.,
Yamashita K., Hakomori T., Takeuchi H., Quantitative

173

Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

evaluation of different rotary tablet presses by compaction
velocity based on compaction simulation study, International
Journal of Pharmaceutics, 558 (2019) 157–164. DOI:
10.1016/j.ijpharm.2018.12.032
Takahashi T., Toyota H., Kuroiwa Y., Kondo H., Dohi M.,
Hakomori T., Nakamura M., Takeuchi H., Application ofnovel compaction indicator for the optimization of compaction conditions based on a compaction simulation study,
International Journal of Pharmaceutics, 587 (2020) 119574.
DOI: 10.1016/j.ijpharm.2020.119574
Taketani Y., Usui T., Toyono T., Shima N., Yokoo S., Kimakura
M., Yamagami S., Ohno S., Onodera R., Tahara K., Takeuchi
H., Kuroda M., Topical use of angiopoietin-like protein 2
RNAi-loaded lipid nanoparticles suppresses corneal neovascularization, Molecular Therapy—Nucleic Acids, 5 (2016)
e292. DOI: 10.1038/mtna.2016.1
Takeuchi H., Chapter 2.15-Solubility and Dissolution Rate, in:Higashitani K., Makino H., Matsusaka S. (Eds.), Powder
Technology Handbook (4th Edition), CRC Press, 2019,
pp. 171–178, ISBN: 9781315184258. DOI: 10.1201/b22268
Takeuchi H., Fuji Sylysia Chemical Ltd., Tablet and method for
producing the same, Jpn. Patent No. 5026675 (2012).
Takeuchi H., Handa T., Kawashima Y., Enhancement of the
dissolution rate of a poorly water-soluble drug (tolbutamide)
by a spray-drying solvent deposition method and disintegrants, Journal of Pharmacy and Pharmacology, 39 (1987a)
769–773. DOI: 10.1111/j.2042-7158.1987.tb05117.x
Takeuchi H., Handa T., Kawashima Y., Spherical solid dispersion
containing amorphous tolbutamide embedded in entericcoating polymers or colloidal silica prepared by spray-drying
technique, Chemical & Pharmaceutical Bulletin, 35 (1987b)
3800–3806. DOI: 10.1248/cpb.35.3800
Takeuchi H., Kojima H., Toyoda T., Yamamoto H., Hino T.,
Kawashima Y., Prolonged circulation time of doxorubicinloaded liposomes coated with a modified polyvinyl alcohol
after intravenous injection in rats, European Journal of Pharmaceutics and Biopharmaceutics, 48 (1999a) 123–129. DOI:
10.1016/S0939-6411(99)00029-6
Takeuchi H., Kojima H., Yamamoto H., Kawashima Y.,
Enhanced tumour accumulation of doxorubicin withpolymer-coated liposomes in rats, Pharmacy and Pharmacology Communications, 5 (1999b) 445–448. DOI:
10.1211/146080899128735144
Takeuchi H., Kojima H., Yamamoto H., Kawashima Y., Polymer
coating of liposomes with a modified polyvinyl alcohol andtheir systemic circulation and RES uptake in rats, Journalof Controlled Release, 68 (2000a) 195–205. DOI: 10.1016/
S0168-3659(00)00260-1
Takeuchi H., Kojima H., Yamamoto H., Kawashima Y., Evaluation of circulation profiles of liposomes coated withhydrophilic polymers having different molecular weights
in rats, Journal of Controlled Release: official journal of
the Controlled Release Society, 75 (2001a) 83–91. DOI:
10.1016/s0168-3659(01)00368-6
Takeuchi H., Kojima H., Yamamoto H., Kawashima Y., Evaluation of the anti-tumour activity of liposomal doxorubicincoated with hydrophilic polymers in tumour-bearing mice,
STP pharma sciences, 11 (2001b) 271–274.
Takeuchi H., Kojima H., Yamamoto H., Kawashima Y., Passive
targeting of doxorubicin with polymer coated liposomes intumor bearing rats, Biological and Pharmaceutical Bulletin,
24 (2001c) 795–799. DOI: 10.1248/bpb.24.795
Takeuchi H., Matsui Y., Sugihara H., Yamamoto H., KawashimaY., Effectiveness of submicron-sized, chitosan–coated liposomes in oral administration of peptide drugs, International

174

Journal of Pharmaceutics, 303 (2005a) 160–170. DOI:
10.1016/j.ijpharm.2005.06.028
Takeuchi H., Matsui Y., Yamamoto H., Kawashima Y., Mucoadhesive properties of carbopol or chitosan-coated liposomes
and their effectiveness in the oral administration of calcitonin
to rats, Journal of Controlled Release, 86 (2003a) 235–242.
DOI: 10.1016/S0168-3659(02)00411-X
Takeuchi H., Nagira S., Aikawa M., Yamamoto H., KawashimaY., Effect of lubrication on the compaction properties ofpharmaceutical excipients as measured by die wall pressure,
Journal of Drug Delivery Science and Technology, 15(2005b) 177–182. DOI: 10.1016/S1773-2247(05)50023-6
Takeuchi H., Nagira S., Yamamoto H., Kawashima Y., Design ofsolid dispersion particles of drug with fine porous carriers,
Journal of the Society of Powder Technology, Japan, 40(2003b) 157–162. DOI: 10.4164/sptj.40.157
Takeuchi H., Nagira S., Yamamoto H., Kawashima Y., Soliddispersion particles of tolbutamide prepared with fine silica
particles by the spray-drying method, Powder Technology,
141 (2004a) 187–195. DOI: 10.1016/j.powtec.2004.03.007
Takeuchi H., Nagira S., Yamamoto H., Kawashima Y., Diewall pressure measurement for evaluation of compaction
property of pharmaceutical materials, International Journalof Pharmaceutics, 274 (2004b) 131–138. DOI: 10.1016/j.
ijpharm.2004.01.008
Takeuchi H., Onodera R., Preparation of nano particles from aliquid phase and dosage form design, Funtai-Gijutsu, 7(6)(2015) 537–541.
Takeuchi H., Sasaki H., Niwa T., Hino T., Kawashima Y.,
Uesugi K., Kayano M., Miyake Y., Preparation of powderedredispersible vitamin e acetate emulsion by spray-drying
technique, Chemical & Pharmaceutical Bulletin, 39 (1991)
1528–1531. DOI: 10.1248/cpb.39.1528
Takeuchi H., Thongborisute J., Matsui Y., Sugihara H.,
Yamamoto H., Kawashima Y., Novel mucoadhesion tests
for polymers and polymer-coated particles to design optimalmucoadhesive drug delivery systems, Advanced Drug
Delivery Reviews, 57 (2005c) 1583–1594. DOI: 10.1016/j.
addr.2005.07.008
Takeuchi H., Yamakawa R., Nishimatsu T., Takeuchi Y.,
Hayakawa K., Maruyama N., Design of rapidly disintegrating drug delivery films for oral doses with hydroxypropyl
methylcellulose, Journal of Drug Delivery Science andTechnology, 23 (2013) 471–475. DOI: 10.1016/S17732247(13)50068-2
Takeuchi H., Yamamoto H., Kawashima Y., Mucoadhesive
nanoparticulate systems for peptide drug delivery, Advanced
Drug Delivery Reviews, 47 (2001d) 39–54. DOI: 10.1016/
S0169-409X(00)00120-4
Takeuchi H., Yamamoto H., Niwa T., Hino T., Kawashima Y.,
Mucoadhesion of polymer-coated liposomes to rat intestinein vitro, Chemical & Pharmaceutical Bulletin, 42 (1994)
1954–1956. DOI: 10.1248/cpb.42.1954
Takeuchi H., Yamamoto H., Niwa T., Hino T., Kawashima Y.,
Enteral absorption of insulin in rats from mucoadhesive
chitosan-coated liposomes, Pharmaceutical Research, 13(1996) 896–901. DOI: 10.1023/A:1016009313548
Takeuchi H., Yamamoto H., Toyoda T., Toyobuku H., Hino T.,
Kawashima Y., Physical stability of size controlled small unilameller liposomes coated with a modified polyvinyl alcohol,International Journal of Pharmaceutics, 164 (1998) 103–111.
DOI: 10.1016/S0378-5173(97)00404-3
Takeuchi H., Yasuji T., Hino T., Yamamoto H., Kawashima Y.,
Compaction Properties of Composite Particles Consisting of
Lactose with Sodium Alginate Prepared by Spray-Drying,Hirofumi Takeuchi / KONA Powder and Particle Journal No. 39 (2022) 150–175

Pharmaceutical Research, 16 (1999c) 1193–1198. DOI:
10.1023/A:1018937227794
Takeuchi H., Yasuji T., Yamamoto H., Kawashima Y., Temperature- and moisture-induced crystallization of amorphous lactose in composite particles with sodium alginate prepared byspray-drying, Pharmaceutical Development and Technology,
5 (2000b) 355–363. DOI: 10.1081/PDT-100100551
Takeuchi H., Yasuji T., Yamamoto H., Kawashima Y., Temperatureinduced crystallization and compactibility of spray driedcomposite particles composed of amorphous lactose andvarious types of water-soluble polymer, Chemical & Pharmaceutical Bulletin, 48 (2000c) 585–588. DOI: 10.1248/
cpb.48.585
Takeuchi Y., Ikeda N., Tahara K., Takeuchi H., Mechanicalcharacteristics of orally disintegrating films: comparison offolding endurance and tensile properties, International Journal of Pharmaceutics, 589 (2020a) 119876. DOI: 10.1016/j.
ijpharm.2020.119876
Takeuchi Y., Murase Y., Tahara K., Takeuchi H., Impact of surface
roughness of pre-treated punches and powder properties on
prevention of sticking during pharmaceutical tableting, Journal of Drug Delivery Science and Technology, 60 (2020b)
101999. DOI: 10.1016/j.jddst.2020.101999
Takeuchi Y., Nishimatsu T., Tahara K., Takeuchi H., Noveluse of insoluble particles as disintegration enhancers fororally disintegrating films, Journal of Drug Delivery Science and Technology, 54 (2019) 101310. DOI: 10.1016/j.
jddst.2019.101310
Takeuchi Y., Umemura K., Tahara K., Takeuchi H., Formulation
design of hydroxypropyl cellulose films for use as orally
disintegrating dosage forms, Journal of Drug Delivery
Science and Technology, 46 (2018) 93–100. DOI: 10.1016/J.
JDDST.2018.05.002
Tanimura S., Kawazoe H., Yamamoto H., Takeuchi H., Directcompaction of poorly compactable pharmaceutical powders
with spray-dried HPC-L, Journal of the Society of Powder
Technology, Japan, 43 (2006) 648–652. DOI: 10.4164/
sptj.43.648
Tanimura S., Tahara K., Takeuchi H., Spray-dried composite particles of erythritol and porous silica for orally disintegratingtablets prepared by direct tableting, Powder Technology, 286(2015) 444–450. DOI: 10.1016/j.powtec.2015.08.011
Tanino T., Aoki Y., Furuya Y., Sato K., Takeda T., Mizuta T.,
Occurrence of capping due to insufficient air escape duringtablet compression and a method to prevent it, Chemical& Pharmaceutical Bulletin, 43 (1995) 1772–1779. DOI:
10.1248/cpb.43.1772
Thongborisute J., Takeuchi H., Yamamoto H., Kawashima Y.,
Visualization of the penetrative and mucoadhesive propertiesof chitosan and chitosan-coated liposomes through the rat
intestine, Journal of Liposome Research, 16 (2006) 127–141.
DOI: 10.1080/08982100600680816
Van der Voort Maarschalk K., Zuurman K., Vromans H.,
Bolhuis G.K., Lerk C.F., Stress relaxation of compacts
produced from viscoelastic materials, International Journalof Pharmaceutics, 151 (1997) 27–34. DOI: 10.1016/S03785173(97)04889-8
Vromans H., Bolhuis G.K., Lerk C.F., Kussendrager K.D., Bosch
H., Studies on tableting properties of lactose. VI. Consolidation and compaction of spray dried amorphous lactose,
Acta Pharmaceutica Suecica, 23 (1986) 231–240. PMID:
3799215.
Waimer F., Krumme M., Danz P., Tenter U., Schmidt P.C., A novel
method for the detection of sticking of tablets, Pharmaceutical Development and Technology, 4 (1999a) 359–367. DOI:
10.1081/PDT-100101371
Waimer F., Krumme M., Danz P., Tenter U., Schmidt P.C., The
influence of engravings on the sticking of tablets. investigations with an instrumented upper punch, Pharmaceutical
Development and Technology, 4 (1999b) 369–375. DOI:
10.1081/PDT-100101372
Werle M., Makhlof A., Takeuchi H., Carbopol-lectin conjugate
coated liposomes for oral peptide delivery, Chemical andPharmaceutical Bulletin, 58 (2010) 432–434. DOI: 10.1248/
cpb.58.432
Werle M., Takeuchi H., Chitosan-aprotinin coated liposomes fororal peptide delivery: development, characterisation and invivo evaluation, International Journal of Pharmaceutics, 370(2009a) 26–32. DOI: 10.1016/j.ijpharm.2008.11.013
Werle M., Takeuchi H., Bernkop-Schnürch A., Modified chitosans
for oral drug delivery, Journal of Pharmaceutical Sciences, 98(2009b) 1643–1656. DOI: 10.1002/jps.21550

Author’s Short Biography
Hirofumi Takeuchi
Dr. Hirofumi Takeuchi is now Professor Emeritus and research Professor of Gifu Pharmaceutical
University (2019–). He received his B.S. (1979), M.S. (1981) and Ph.D. (1984) in pharmacy andpharmaceutical sciences from Kyoto University. He joined Gifu Pharmaceutical University (GPU)in 1984, and worked as Lecture, Associate Professor and Professor of pharmaceutical engineering.
He also worked as the dean of graduate school of GPU (2010–2011), dean of the faculty of GPU(2012–2013) and vice president of GPU (2014). He became the research Professor of Advanced
Pharmaceutical Process Engineering (APPEN) as well as Professor Emeritus of GPU after retirementin 2019.

175

KONA Powder and Particle Journal No. 39 (2022) 176–192/https://doi.org/10.14356/kona.2022010

Review Paper

The Development of Thin-Film Freezing and Its Application to
Improve Delivery of Biologics as Dry Powder Aerosols †Stephanie Hufnagel, Sawittree Sahakijpijarn, Chaeho Moon,
Zhengrong Cui and Robert O. Williams III *Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin, USA

Abstract
While the formulation of pharmaceuticals as liquids is common practice, powders are associated with enhanced
stability, avoidance of the cold chain, lower dosing requirements, and more convenient administration. Theseare particularly critical for proteins, as they are expensive and complicated to manufacture. Powders also have
improved aerosol properties for pulmonary delivery. Conventional techniques for formulating powders include
spray-drying, shelf freeze-drying, spray freeze-drying, and spray freezing into liquid, but they produce powders
with poor aerosol performance and/or activity due to suboptimal powder properties. Thin-film freezing (TFF)
is a new cryogenic technique that can engineer highly porous, brittle, powder matrices with excellent aerosol
performance properties and stability. Herein, we describe TFF in comparison to other cryogenic techniques.
Physical properties of TFF powders such as morphology, moisture sorption, stability, solubility, and dissolution,
as well as aerosol properties are discussed. In addition, factors that significantly affect the physical and aerosol
properties of dry powders prepared by TFF, such as solids content, drug loading, solvent system, excipient, and dry
powder delivery device, are analyzed. Finally, we provide evidence supporting the applicability of using TFF toprepare dry powder formulations of protein-based pharmaceuticals, enabling their cold chain-free storage as wellas efficient pulmonary delivery.
Keywords: thin-film freezing, dry powder, cryogenic technique, protein, pulmonary delivery

1. Introduction
Therapeutics intended for pulmonary delivery via inhalation are supplied as liquids or powders. While a majorityof them are developed as liquids, the preparation of drugs
into powders affords several benefits, particularly forproteins and other biologics. Pharmaceutical dry powders
are generally associated with enhanced stability, avoidanceof the cold chain, improved aerosol properties, lower
dosing requirements, and more convenient administration(Johnson, 1997). In particular, expensive biologics canbenefit from being prepared as powders, as the dry powder state typically extends the shelf life of biologics andreduces the cost burden of their transportation and storage.
Spray-drying (SD) and conventional shelf freeze-drying(shelf FD), as well as spray freeze-drying (SFD) and sprayfreezing into liquid (SFL) are techniques commonly em†*

Received 5 April 2021; Accepted 3 May 2021
J-STAGE Advance published online 26 June 2021
Corresponding author: Robert O. Williams III;
Add: 2409 West University Avenue, PHR 4.214 Austin, TX 78712,
USA
E-mail: bill.williams@austin.utexas.edu
TEL: +01-512-471-4681 FAX: +01-512-471-7474

176

ployed to prepare powders. Unfortunately, in the context of
biologics, all techniques cause aggregation, denaturation,
and/or loss of activity of the biologics to some degree. In
addition, these methods produce powders with low surface
area, low yield, and/or a broad particle size distribution(Engstrom et al., 2008), which are not ideal for pulmonary
delivery by inhalation, particularly of biologics.
Previously, we reported thin-film freezing (TFF) technology for pharmaceutical applications that can be applied
to generate highly porous, brittle, powder matrices withexcellent aerosol performance properties (Overhoff et al.,2007a). The resultant dry powder, upon sublimation of
the solvent in the frozen thin films, is ideal for pulmonary
delivery by inhalation. We have validated that the TFF
technology is directly applicable to inhaled delivery of various small and large molecules including proteins, such as
cytokines, enzymes (Engstrom et al., 2008), and more recently, antibodies. Currently, many therapeutics, including
most biologics, for pulmonary delivery are administeredby nebulization of a liquid. Unfortunately, nebulization
exposes therapeutics, especially biologics such as proteins,to stressful conditions that can damage them from shear orelevated temperatures applied during delivery. In addition
to the aforementioned limitations of liquids, the solution

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

for nebulization may contain excipients that are harmful
to the lungs. An alternative to nebulization of a liquid isadministration by dry powder inhalation, which addresses
many of the limitations of nebulization. While some powders are already approved by the US FDA for inhalation,
powders produced by TFF technology can minimize theflow-rate dependence of dry powder inhalers (DPIs), use ofcarriers (Ung et al., 2014), aggregation, denaturation, andsize distribution issues of molecules while improving thesurface area and yield. Overall, TFF offers an opportunity
to improve powder properties and thus aerosol performance and therapeutic efficacy of therapeutics, which canbe applied to biologics.
Biologic drugs continue to exist as a large proportion of
FDA-approved products, with 25 % of all new chemical
entities that were FDA-approved from 2015–2019 being
biologics (de la Torre and Albericio, 2020). Additionally,
biologics can be approved as biosimilars. Biologics are
particularly challenging to formulate due to their large molecular size and sensitive nature. Unlike small molecules,
biologics (e.g., proteins) must maintain primary, secondary,tertiary, and quaternary structures. They are expensive to
produce and pulmonary delivery may minimize the required dose, and therefore cost, while still assuring efficacy
and minimizing systemic toxicity, especially when they aredelivered locally to the lung to treat pulmonary disease. For
example, systemic delivery of antibodies, one of the largest
and most complex biologics, overall carries a risk of side
effects such as cytokine release syndrome (Guilleminault etal., 2014). Alternatively, inhaled antibodies are poorly systemically absorbed from the respiratory tract, providing an
opportunity for local delivery to the lungs (Guilleminault
et al., 2014). Of the thirty biologics that have undergone
clinical trials for pulmonary delivery, only five have beendelivered as a powder (Liang et al., 2020). Developmentof biologic formulations for pulmonary delivery has beenreviewed in detail (Fröhlich and Salar-Behzadi, 2021;
Liang et al., 2020). Herein we describe the developmentof the TFF technology, the process of TFF, and the generalcharacteristics of powders prepared using TFF. Then, we
discuss our experience in applying this technique to formulate protein dry powders for pulmonary delivery.

2. Thin-film freezing: the technique
2.1 The progression of cryogenic processdevelopment
Several techniques have been developed or transitioned
from other industries and applied to pharmaceuticals,
including SD, SFD, SFL, shelf FD, and TFF, in order toprepare powders. The latter four (i.e., SFD, SFL, shelf FD,
and TFF) are considered cryogenic techniques and havethe added benefit of avoidance of heat, which can directly
and indirectly (e.g., evaporation of water) lead to denaturation or degradation of proteins (Overhoff et al., 2009). In
cryogenic techniques, a liquid sample is frozen through theuse of a cryogen and then lyophilized to remove the frozen
solvent via sublimation.
Lyophilization alone, or shelf FD, is generally not
sufficient to produce stable particles with high surface
area (Engstrom et al., 2008) and submicron particle sizes,
which are both necessary for optimal aerosol performance.
Shelf FD involves placing the liquid formulation insidea lyophilizer, allowing the liquid to freeze as the shelftemperature is reduced, typically to around –40 °C to–55 °C. Afterwards, the pressure is reduced, sublimating
the solvent until a powder is formed. In this method, thecooling rate is slow, around 0.017 K/s, which allows time
for protein particles to grow, and achieving particles with adiameter less than a few microns and surface area greaterthan 1 m2/g is difficult (Engstrom et al., 2008). The powder
generated can be milled to improve the particle size andsurface area, but this can be mechanically stressful for proteins and lead to heterogeneous particle sizes with limitedyield. Therefore, the alternative processes SFD, SFL, andTFF have been utilized.
SFD involves spraying a liquid formulation into the gaseous vapor phase of a liquid cryogen. The cooling rate of
SFD is high, about 106 K/s. Unfortunately, SFD has a large
gas-liquid interface and shear stress, which can contributesignificantly to protein aggregation (Engstrom et al., 2008).
This technique produces porous powders with high surface
area; however, the particle size is large (Overhoff et al.,2009). A benefit of SFD is that different atomization nozzles and spray rates can be chosen to optimize the droplet
shape and size (Overhoff et al., 2009).
In order to minimize the gas-liquid interfacial area, theliquid formulation can be sprayed directly into the liquid
cryogen, known as SFL. While the freezing rate is slower
than that of SFD, about 103 K/s, SFL still adequatelyarrests the growth of crystals and has produced protein
powders with less adsorption, aggregation, denaturation,and higher enzymatic activity than those prepared using
SFD (Engstrom et al., 2008). SFL produces powders withimproved activity compared to SFD and shelf FD powders
due to the lower air-liquid interfacial area, slower coolingrate, and lower (but still adequately high) surface area.
Generally, the slower cooling rate results in a lower surface
area, which induces a lower chance of water adsorption,
improving stability (Overhoff et al., 2009).
TFF was developed to find a cooling/freeze rate andsurface area intermediate to that of shelf FD vs. SFD and
SFL. In TFF, the liquid cryogen is filled in a rotating metal
drum and a solution or suspension is dropped dropwise
from above the drum, where the droplets (e.g., 2–4 mm
in diameter) spread upon impact to form thin films

177Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192(~10–12 mm in diameter) that freeze at 102–103 K/s. A
metal blade then releases the frozen films from the drum as
it rotates, and the films are collected in a cryogen-cooled
receptacle situated below the blade/drum. The frozen films
are then transferred to a lyophilizer for solvent removal
by sublimation. TFF is less complex than SFD and SFL
because the liquid cryogen used to cool the metal drum
does not need to be sterile and the cooling rate of TFF
can be more easily controlled (Engstrom et al., 2008).
Furthermore, spray characteristics in SFD or SFL are more
complicated to control than drop characteristics during
TFF. TFF allows for the processing of more concentrated,viscous protein solutions because they do not need to beatomized. TFF has close to 100 % yield while that of SFD
is about 80 % (Engstrom et al., 2008). Powders produced
by TFF follow a similar surface area and stability trend as
SFL powders due to their similar cooling rates and relatively low air-liquid interface (Engstrom et al., 2008). TFF
is a promising technique for the formulation of biologics
as powders.

2.2 Modeling the TFF process
The cooling rate of cryogenic techniques is one of
the main parameters that contributes to the final powder
characteristics. As water freezes, liquid channels areformed between frozen molecules, with thinner channels
minimizing collisions between particles (e.g., proteins),
therefore preventing particle growth. During freezing, theviscosity of these channels increases, also contributing toslowed particle growth. If sugars are included as carriers,
the viscosity will be further increased (Engstrom et al.,2008). Generally speaking, the slower the cooling rate, thefewer the nucleated ice domains, leading to thicker channels and more collisions and protein aggregation. A slower
cooling rate also leads to phase separation, which can cause
crystallization of the active ingredient (Overhoff et al.,2009). However, there is a point at which loss of protein
activity can be attributed to a fast cooling rate (Overhoff
et al., 2009). Therefore, an intermediate cooling rate isfavorable. The rate of cooling in SFD, SFL, and TFF was
measured for comparison, showing that compared to SFD

Fig. 1

178

and SFL, TFF had a slower rate of cooling (i.e., 2 × 102 K/s
vs 3.8 × 106 and 7.2 × 103 for SFD and SFL, respectively)(Engstrom et al., 2008). These are all considerably fasterthan that of shelf FD (~1.7 × 10–2 K/s) (Engstrom et al.,2008). The large difference between SFD and TFF coolingrates has been explained by a two-orders-of-magnitude
smaller surface area/volume ratio and 20–30 times larger
film thickness of TFF compared to SFD. TFF has a slower
cooling rate than SFD and SFL but the cooling rate is sufficiently high to prevent or minimize particle growth. TFF
and its intermediate freezing rate may be one of the keys
to its optimal powder properties. The solute or suspension
concentration and processing temperature are additionalvariables to consider in the context of cooling rate. A highcooling rate coupled with a supersaturated solute leads toa larger number of smaller and more uniform nuclei thatare tightly packed, which helps to limit crystal growth. A
lower processing temperature in TFF can lead to a higher
degree of supercooling, therefore a larger number ofnuclei (Engstrom et al., 2007). The higher degree of supercooling and the larger number of nuclei prevent particle
growth during the freezing process, generating smaller ice
channels. As shown in Fig. 1, smaller ice channels were
produced when a lysozyme/mannitol (50:50 w/w) powder(TFF MAN/lysozyme (50:50 w/w)) was manufactured ata lower temperature of –100 °C as compared to at –50 °C.
Crystalline TFF voriconazole (VCZ) nanoaggregates withsmaller nanoparticle size were also generated by processing at a lower temperature than at a higher temperature(Moon et al., 2019a). In contrast, amorphous TFF tacrolimus brittle matrix powder (TFF TAC) showed larger
nanoaggregate structures when the processing temperature
was lower (–70 °C versus –130 °C), potentially due to thelack of droplet spreading and higher contact angle at thelower temperature (Sahakijpijarn et al., 2020b).
Engstrom et al. compared the specific surface area (SSA)of lysozyme powders prepared by SFD, SFL, and TFF.
At the same lysozyme concentration, the SFD powder
exhibited the highest SSA, while the TFF powder had thelowest SSA (Table 1) (Engstrom et al., 2008). The high
SSA of the SFD powder is related to the extremely rapid
cooling rate of SFD. The higher cooling rate results in more

Representative SEM images of TFF MAN/lysozyme (50:50 w/w) processed at (a) –50 °C or (b) –100 °C.

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192
Table 1 Specific surface area (SSA) and bulk density of processed and unprocessed drug powders.

Formulation

Process

Specificsurface area
(m 2/g)Bulk
density(g/mL)

Reference

Tacrolimus unprocessed powder

Unprocessed

0.53

—

(Sinswat et al., 2008)

Tacrolimus

TFF (–70 °C)

42.22 ± 3.02—

(Sahakijpijarn et al., 2020b)

Tacrolimus/lactose (50:50 w/w)

TFF (–70 °C)

143.13 ± 0.60—

(Sahakijpijarn et al., 2020b)

Tacrolimus/lactose (95:5 w/w)

TFF (–70 °C)

73.58 ± 5.14—

(Sahakijpijarn et al., 2020b)

Tacrolimus/mannitol (95:5 w/w)

TFF (–70 °C)

55.79 ± 6.49—

(Sahakijpijarn et al., 2020b)

Tacrolimus/trehalose (95:5 w/w)

TFF (–70 °C)

57.16 ± 1.96—

(Sahakijpijarn et al., 2020b)

Itraconazole unprocessed powder

Unprocessed

4.22

—

(Overhoff et al., 2007b)

Itraconazole/hydroxypropyl methylcellulose
phthalate (HP55) (1:4 w/w), 2 %w/v

TFF (–60 °C)

19.1

—

(Overhoff et al., 2007b)

Itraconazole/hydroxypropyl methylcellulose
phthalate (HP55) (4:1 w/w), 2 % w/v

TFF (–60 °C)

54.2

—

(Overhoff et al., 2007b)

Itraconazole/hydroxypropyl methylcellulose
phthalate (HP55) (1:4 w/w), 0.2 % w/v

TFF (–60 °C)

61.8

—

(Overhoff et al., 2007b)

Itraconazole/hydroxypropyl methylcellulose
phthalate (HP55) (4: w/w), 0.2 % w/v

TFF (–60 °C)

57.4

—

(Overhoff et al., 2007b)

Voriconazole unprocessed powder

Unprocessed

0.53 ± 0.08

7.86

(Beinborn et al., 2012a)

Micronized voriconazole

Micronization

3.46 ± 0.02

1.20

(Beinborn et al., 2012a)

Voriconazole

TFF (–40 °C)

9.38 ± 3.25

0.45

(Beinborn et al., 2012a)

Voriconazole/mannitol (50:50 w/w)

TFF (–70 °C)

16.3

—

(Moon et al., 2019b)

Voriconazole/PVP K25 (1:3 w/w)

TFF (–40 °C)

43.35 ± 5.67

0.05

(Beinborn et al., 2012a)

Physical mixture of Danazol/povidone K15(1:2 w/w)

Unprocessed

0.69

—

(Overhoff et al., 2007a)

Danazol/povidone K15 (1:2 w/w)

TFF (–70 °C)

25.93

—

(Overhoff et al., 2007a)

Lysozyme 50 mg/mL

TFF (–100 °C)

31 ± 0.1—(Engstrom et al., 2008)

Lysozyme 50 mg/mL

SFL

34 ± 2—(Engstrom et al., 2008)

Lysozyme 50 mg/mL

SFD

126 ± 5—(Engstrom et al., 2008)

Lysozyme 5 mg/mL

TFF (–100 °C)

73 ± 0.8—(Engstrom et al., 2008)

Lysozyme 5 mg/mL

SFL

114 ± 11—

(Engstrom et al., 2008)

Lysozyme 5 mg/mL

Shelf FD

4.4 ± 0.2—

(Engstrom et al., 2008)

rapid nucleation and particle growth prevention duringfreezing. Although TFF produces particles with lower
SSA compared to SFD and SFL, the cooling rate of TFF
is high enough to prevent particle growth and induce rapid
nucleation, thereby still forming particles with relatively
high SSA (e.g., 31–73 m2/g), especially when compared toshelf FD (e.g., 4.4 m2/g) (Table 1, Engstrom et al., 2008).
While the cooling rate can affect the SSA to a degree, SFL
and SFD have produced lysozyme powders with similar
SSAs > 100 m2/g despite having cooling rates that differ
by three orders of magnitude (Engstrom et al., 2007;2008). The cooling rate had a higher impact on the particle

size, as shown by SFL’s larger particle size compared to
SFD, particularly noticeable in high protein concentration
situations (i.e., 50 mg/mL) (Engstrom et al., 2008). Even
though TFF had a lower cooling rate, increasing the protein
concentration could supersede the cooling rate’s impact on
the particle size, as TFF powders also had a large particle
size at high concentrations. However, at a lower, more relevant protein concentration (i.e., 5 mg/mL), TFF allowed
for thinner unfrozen channels with high viscosity, leading
to a small particle size.
For TFF, the ability of the droplets to spread upon impact
and form films influences the cooling rate, with the droplet

179

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

spreading time being shorter than the freezing time. Generally, the film thickness is on the scale of 200–400 μm andthe diameter is around 10–12 mm (Engstrom et al., 2008).
Because the thickness is substantially smaller than the
diameter, the radial heat transfer is negligible and the heattransfer is considered to be one-dimensional (Engstrom
et al., 2008). Under the assumption of constant thermal
diffusivity, the heat transfer can be calculated using the
thickness of the film, the temperature of the film, the processing temperature of the drum, and the distance from the
top of the spread droplet (Engstrom et al., 2008). Using theheat transfer, the cooling rate can be determined. At 223 K,
a 220 μm thick film cooled in 2 × 102 ms with a coolingrate of 3.9 × 102 K/s, for example (Engstrom et al., 2008).
Film diameter was proportional to the droplet diameterand the processing temperature (Engstrom et al., 2008).
The processing temperature and parameters that affectthe droplet size (e.g., solvent system, drop diameter, drop
height) can be tailored for each application. As the processing temperature decreases, the droplet will freeze more
quickly, allowing less time for spreading into a film before
it becomes solid. While processing lactate dehydrogenase(LDH) protein with TFF, an average film thicknessesof 220 μm was formed at 223 K (–50 °C) and 320 μm
was formed at 133 K (–140 °C), respectively. The film
thickness was larger when the processing temperature waslower. For comparison, when the small molecule synthetic
steroid danazol was prepared using TFF, the resultant
film thickness ranged from 100–400 μm (Engstrom et al.,2008).
Infrared imaging was used to study the cooling of thinfilms prepared from an LDH protein solution. When a film
was formed at 223 K, it had a diameter of 12 mm with asmooth edge. The IR camera revealed that the cooling front
started at the edge of the film, moving inward. The film
came to thermal equilibrium at 1.6 s. When the same film
was processed at the lower temperature of 133 K, it hada smaller diameter of 10 mm and a jagged edge, the protrusions of which experiencing the coldest temperatures.
In this case, after the cooling front moved inwards, it thenreversed direction, causing a longer time of 3 s to reachthermal equilibration. While a low temperature is necessary to cause quick cooling, there is a limitation to how low
is favorable. While the edge of the film was thinner andmay cool at a different rate than the center of the film, thisdifference had no impact on the morphology throughout thefilm (Engstrom et al., 2008).
Thin films prepared by TFF demonstrated that the surface area/volume ratio decreased with an increasing droplet
diameter. Once frozen, this ratio was 31–46 cm–1. This issubstantially smaller than SFD or SFL (6000 and 600 cm–1,
respectively). Loss of protein functionality has been attributed to a high surface area/volume ratio. Alternatively,
SFL and TFF have a lower gas-liquid interfacial area than180

SFD and thus preserve protein functionality better due totheir ability to reduce protein adsorption to the interface
and thus aggregation (Engstrom et al., 2008).
Several variables describe the droplet spreading, including the density of the liquid (ρ), the impact velocity (V),the droplet diameter (D), and the interfacial tension of thedroplet in air (γ). Together, these variables can be used tomathematically describe the droplet spreading, or Weber
number (We), by Eqn (1):We  =  ρV 2D/γ

(1)When We is high (> 30), the droplets spread into acylindrical film, while when We is low (< 1), the droplets
undergo minimal spreading, and the droplets freeze asa spherical dome. These variables can be optimized to adegree: V can be controlled by the drop height, ρ can becontrolled through choice of excipients and concentrationof all components, and D can be controlled by the gauge ofneedle through which the droplets are generated. Engstrom
et al. compared the typical drop height (H) of 10 cm to ashorter H of 1 cm (Engstrom et al., 2008). When H was
10 cm, the resultant films were cylindrical and the We wasfound to be 97, while an H of 1 cm yielded spherical domes
and the We was 9.8 (Engstrom et al., 2008). A low H also
reduced the film diameter (~4 mm) (Engstrom et al., 2008).
Overall, TFF is the optimal cryogenic technique due
to its low gas-liquid interfacial area, intermediate coolingrate, sufficient surface area, small particle size, and controllable processing parameters such as temperature.

2.3 Characteristics of TFF powders
2.3.1 Particle morphology
Powder characteristics are generally described by their
particle size and the morphology of their nanostructures.
The particle size generally refers to the larger micron-ranged
structure that is important for adequate aerosolization andlung deposition. The morphology of the nanostructures,
however, provides more detailed information about theporosity, surface area, and freezing characteristics of thepowder. The particle morphology of powders prepared bycryogenic bottom-up technologies (i.e., starting from drugin solution or suspension) is generally porous. In manycases, small molecule compounds are changed from crystalline to amorphous form after the TFF process, producing
a nanostructured brittle matrix (Sahakijpijarn et al., 2020a;
2020b). In the brittle matrix, there are nanoparticles interconnected and agglomerated together as nanostructured
aggregates (Fig. 2(a)) and are generally irregularly shaped(Sahakijpijarn et al., 2020a). The brittle matrix structure is
not only observed in small molecule compounds, but also
in the case of biologics, such as lysozyme (Engstrom et al.,2008). Figs. 2(b), 2(c), and 2(d) show the morphology ofStephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

Fig. 2 Particle morphology of particles prepared by cryogenic methods. (a) TFF remdesivir with leucine (100 kx) (b) TFF lysozyme prepared at–50 °C (60 kx), (c) SFL lysozyme (60 kx), (d) SFD lysozyme (60 kx), (e) TFF VCZ with MAN (20 kx), (f) TFF VCZ with PVP K25 (10 kx). Reprinted
with permission from (a) MDPI: Pharmaceutics (Sahakijpijarn et al., 2020a) (b) Springer Nature: Pharm. Res. (Engstrom et al., 2008) (c–d) Elsevier:Eur. J. Pharm. Sci. (Yu et al., 2006) (e) ACS: Mol. Pharm. (Moon et al., 2019b) and (f) Elsevier: Eur. J. Pharm. Sci. (Beinborn et al., 2012a).

lysozyme particles that were prepared by TFF, SFL, andSFD, respectively (Engstrom et al., 2008; Yu et al., 2006).
Among these three techniques, all particles showedsimilar morphologies. Particle morphology is related toseveral factors, such as formulation composition, solids
content of solutions, solvent, and processing temperature(Moon et al., 2019a; Wang et al., 2014). In addition to thenanostructured brittle matrix, another particle morphology
was observed in the case of VCZ. The particle morphology
of TFF VCZ combined with mannitol (MAN) was a porous
matrix of micron-sized flat irregular-shaped VCZ particles
and irregular-shaped mannitol nanoparticles (Fig. 2(e))(Moon et al., 2019b). Atomic force microscopy showedthat the VCZ microparticles were packed by VCZ nanoaggregates (150–500 nm) (Moon et al., 2019b). Interestingly,
the particle morphology of TFF VCZ combined with povidone K25 (PVP-K25) is a brittle matrix of nanostructured
primary particles with a size of approximately 100 nm(Fig. 1(f)) (Beinborn et al., 2012a), which is a similar mor-

phology to other brittle matrix powders. The difference inparticle morphology of VCZ is related to the crystallinity
of VCZ in the formulations. Due to the low glass transition
temperature (Tg) of VCZ (1 °C), the inclusion of VCZ witha sufficient amount of a high Tg polymer (e.g., PVP) caninhibit the recrystallization during the drying cycle, resulting in an amorphous structure of VCZ (Beinborn et al.,2012a). In contrast, mannitol, a sugar alcohol, showed nointeraction with VCZ, resulting in the crystalline structureof VCZ in TFF VCZ-MAN.

2.3.2 Moisture sorption
Generally, moisture/water sorption depends on the polarity of surface chemical groups and the available surface
area (Newman et al., 2008). Although the highly porous nature of particles produced by TFF is beneficial with regard
to dispersibility and aerosolization, the high surface area of
porous particles can increase the tendency of water sorption compared to unprocessed powder. The hygroscopicity

181

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

of TFF formulations is also associated with the formulation
composition. The formulations that contain a large amountof hydrophilic material can increase the hygroscopicity of
the formulations (Sahakijpijarn et al., 2020b). Sahakijpijarn
et al. investigated the effect of the amount of lactose (LAC)
in the TFF formulations on the moisture sorption, which
was determined gravimetrically by dynamic vapor sorption(Sahakijpijarn et al., 2020b). The higher amount of lactose
resulted in higher moisture sorption. The moisture sorption
of TFF tacrolimus (TAC) formulations containing 0 %,5 %, and 20 % w/w lactose were 1 %, 2.5 %, and 9 % w/w
at 25 °C/80 % relative humidity (RH) (Sahakijpijarn etal., 2020b). According to the hygroscopicity classificationof the European Pharmacopoeia, TFF TAC formulations
containing lactose are classified as moderately hygroscopic
to very hygroscopic, while TFF neat TAC is classified asslightly hygroscopic (Newman et al., 2008). Moreover,mass loss due to surface moisture release during recrystallization was observed in a TAC formulation containing
50 % lactose, but not in other formulations (Sahakijpijarn
et al., 2020b).
Another study compared the moisture sorption of different sugar excipients (Watts et al., 2013). The formulations
containing lactose and raffinose had more weight gain at> 80 % RH than the formulations containing mannitol
without other excipients. Mannitol was crystalline after the
TFF process, while lactose and raffinose were amorphous(Watts et al., 2013). Amorphous materials generally tend toabsorb moisture more than crystalline materials (Newman
et al., 2008). Moreover, the effect of humidity on theaerosolization of low-density microparticles containing
different excipients was also investigated. It was reported
that water sorption to powder surface can both improveand reduce powder dispersibility. Capillary, electrostatic,
and Van der Waals forces are used to describe the cohesive
forces in powders, which play a major role in powderdispersibility (Watts et al., 2013). Capillary force is a predominant force at > 60 % RH, while electrostatic adhesion
force is a predominant force at low humidity (Watts et al.,2013). In lactose-based formulations, high humidity increased the plasticity of the brittle matrix, thereby reducing
the aerosol performance of the formulations. However, inmannitol-based formulations, moisture can improve thepowder dispersibility due to a reduction in electrostatic
charge (Watts et al., 2013).

2.3.3 Aerodynamic properties
TFF powders have been investigated for pulmonary drugdelivery using dry powder inhalers (DPIs). The powder
should have an appropriate mass median aerodynamic
diameter (MMAD) in the range of 1–5 μm to maximize
the delivery of the drug particles to the deep lungs. Powderdispersibility is controlled by the particle cohesive forces,
which are related to contact area and separation distance be-

182

tween particles (Weers, 2000). The highly porous, low-density particles with a large geometric particle diameter,
characteristics unique to the morphology of TFF powders,
demonstrate superior powder dispersibility, as they havehigher inter-particle separation distance, less contact area,and lower interparticle cohesive forces compared to the
traditional micronized (e.g., milled) powder (Sahakijpijarn
et al., 2020b). The highly porous and low-density brittle
matrices can be aerosolized and dispersed to small particlesof the same structure and density by the inhalation force
through a passive DPI (Watts et al., 2013).
The aerodynamic properties of TFF formulations are
dependent on the properties of the powder, which are
influenced by formulation compositions and processing
parameters. Excipients, such as sugars, are typically used
to improve the dispersibility of dry powder formulations(Chen et al., 2016). Lactose is widely used as an excipientin FDA-approved inhaled products, while other sugars(e.g., trehalose, sucrose) and amino acids (e.g., leucine, trileucine) have recently gained more interest for pulmonary
delivery (Pilcer and Amighi, 2010). Mannitol has been
approved in ARIDOLTM for the assessment of bronchial
hyperresponsiveness due to its induction of bronchoconstriction (Pharmaxis, 1964; Sahakijpijarn et al., 2020c).
In many cases, TFF formulations containing an optimal
amount of excipient exhibited high aerosol performance.
Beinborn et al. compared the aerosol performance of TFF
VCZ with micronized VCZ. The blended powder of inhalation grade, micronized VCZ and lactose (Inhalac® 70, 2 %w/w) exhibited 19.6 % fine particle fraction (FPF) and an
MMAD of 2.7 μm when it was emitted from a Handihaler®
at 60 L/min. Although TFF neat VCZ exhibited a larger
MMAD (4.2 μm), the FPF was about two times higher
compared to micronized VCZ and the MMAD was in theacceptable range (Beinborn et al., 2012a).
The effects of the type and amount of excipient and thedrug loading on the aerosol performance were investigatedin several studies. The drug loading and type of excipients were optimized to maximize the respirable dose forpulmonary delivery (Sahakijpijarn et al., 2020a). It wasreported that TFF remdesivir combined with leucine had alarger FPF and smaller MMAD for the whole range of drug
loading of remdesivir (20–80 % w/w) (Sahakijpijarn et al.,2020a). The formulations containing 80 % remdesivir with
20 % of different excipients (e.g., Captisol®, mannitol, lactose, leucine) showed good aerosol performance with FPFs
ranging from 64.21–82.71 % and MMADs ranging from
2.17–2.53 μm (Sahakijpijarn et al., 2020a). The aerosol
performances of formulations containing 95 % TAC withthe combination of 5 % w/w lactose, mannitol, or trehalosewere compared at 60 L/min using a Plastiape RS01 highresistance inhaler (Sahakijpijarn et al., 2020b). Lactosebased formulations exhibited higher FPFs and smaller
MMADs compared to mannitol- and trehalose-based

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

formulations (Sahakijpijarn et al., 2020b). Additionally,
it was reported that there was no significant differencein aerosol performance when the drug loading of TFF
TAC formulations was increased from 60 % to 95 %w/w (Sahakijpijarn et al., 2020b). This indicates that the
drug loading of TAC can be increased up to 95 % while
maintaining optimal aerosol performance (69.31 % FPF,
2.61 μm MMAD) (Sahakijpijarn et al., 2020b). Anotherstudy from Moon et al. investigated the drug loading andthe amount of mannitol in TFF formulations. When the
drug loading of VCZ was increased from 50 % to 97 %w/w, the FPF increased from 28.5 % to 40.8 % (Moon etal., 2019b). The small amount of mannitol in TFF VCZ
formulations functioned as a surface texture modifier,which can minimize the cohesive and adhesive forces
between particles, and subsequently, improve the aerosol
performance (Moon et al., 2019b). According to thesecases, particles prepared by TFF are aerosolizable witha small amount of excipient needed in the formulation,
providing the potential of TFF to prepare high drug loading
formulations for pulmonary delivery of drugs requiring ahigh dose, which can also lower the powder burden forthe patient. For large molecules such as nucleic acid-based
molecules and proteins, however, increasing the drug loading in the final dry powders to a certain level can lead to a
reduction of the aerosol performance properties of the dry
powders (unpublished data), likely due to an increase inparticle cohesive forces.

2.3.4 Stability, molecular interactions, andmiscibility
The stability of TFF powders was investigated in several
studies. It is well reported in literature that a crystalline
form is more stable than its amorphous counterpart. For example, VCZ/MAN (95:5 w/w) crystalline nanoaggregates
prepared by TFF were physically and chemically stable after storage at 25 °C/60 % RH for up to 13 months (Moon etal., 2019b). The MMAD and FPF of TFF VCZ/MAN (95:5w/w) did not change statistically after the storage (Moonet al., 2019b). In the case of amorphous drugs, TFF TAC/
LAC (95:5 w/w) was chemically and physically stable after
storage at 25 °C/60 % RH and 40 °C/60 % RH for up to 6
months without the need of a stabilizer (Sahakijpijarn et al.,2020b). The moisture content of powder affected the aerodynamic properties and physical properties of formulations
after storage. For example, when TFF TAC/LAC (95:5w/w) powder was encapsulated in #3 hydroxypropyl methylcellulose (HPMC) capsules and stored in a borosilicate
glass vial without desiccant, there was an increase in moisture content during storage, which led to a decrease in SSA
and MMAD (Sahakijpijarn et al., 2020b). Since amorphousmaterials are generally susceptible to water plasticization,
moisture on the particle surface resulted in a reduced brittle
fracture and increased particle density due to the collapseof the brittle matrix structure (Watts et al., 2013). Thechanges in particle morphology and powder properties had
detrimental effects on the aerodynamic properties, as thepowder showed a significant decrease in FPF and emitted
fraction (EF) and increase in MMAD (Sahakijpijarn etal., 2020b). However, the stability results suggested thata tightly closed container with desiccant helps to maintainand minimize the changes in the aerodynamic and physicalproperties of TFF powder (Sahakijpijarn et al., 2020b).
When TAC/LAC (95:5 w/w) powder was dried to remove
additional moisture absorbed during capsule filling andpacking and then stored in a sealed glass container withdesiccant, the physical and aerodynamic properties of
encapsulated powder did not significantly change over 6
months stored at 25 °C/60 % RH and only slightly changed
over 6 months stored at 40 °C/60 % RH (Sahakijpijarn etal., 2020b).
In the case of biologics, Thakkar et al. investigated thestability of a protein subunit vaccine dry powder preparedby TFF (Thakkar et al., 2017). It was reported that theparticle size distribution of reconstituted ovalbuminabsorbed aluminum hydroxide dry powder prepared with
2 % w/v trehalose did not significantly change after one
month of storage at RT, 30 °C, and 40 °C. After 3 monthsof storage at 40 °C, particle aggregation was slightly
detected, but was not found at other storage temperatures.
However, noticeable amounts of particle aggregates weredetected after 6 months of storage at RT, 30 °C, and 40 °C,
due to the visible buildup of moisture in the vials. The
ovalbumin-aluminum hydroxide vaccine powders werereconstituted after storage at various temperatures for 1 or
3 months and were used to immunize mice. Importantly,
there was no significant difference in the anti-ovalbumin
IgG levels among mice that were immunized with freshly
prepared ovalbumin-adsorbed aluminum hydroxide liquid
vaccine or with the TFF vaccine powders after 3 months ofstorage at the different temperatures. The Tg (~120 °C) of
the ovalbumin-adsorbed aluminum hydroxide dry powder
prepared by TFF was higher than the storage temperatures(i.e., RT, 30 °C, and 40 °C), allowing the vaccine powder
to remain chemically, physically, and immunogenicallystable at all temperatures up to 3 months (Thakkar et al.,2017). These samples were stored in a desiccator, but not
individually packaged in sealed pouches. With optimal
storage conditions, they would remain stable for a longer
period of time. This study showed the advantage of TFF in
producing a biologic powder that is stable when stored foran extended period of time without a requirement for cold
chain (Thakkar et al., 2017).
The interaction between a drug and an excipient witha high Tg generally improves the physical stability ofamorphous solid dispersions of small molecule drugs, aswell as the stability of biologics. The interaction between
drug and excipient can increase the Tg of the system,

183

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

resulting in a less molecularly mobile glassy state. In somecases, however, the interaction is not necessary to stabilize
the drug. For example, TAC, a high glass-forming ability
drug (GFA class III), showed no interaction with LAC
analyzed by ssNMR (Sahakijpijarn et al., 2020b). Although
two Tgs were detected by DSC, indicating TAC and LAC
were not molecularly dispersed, the analysis of domain
size by ssNMR showed that the two compounds had good
miscibility at a domain size of ~100 nm (Sahakijpijarn etal., 2020b). Despite phase separation and lack of interactions, TAC was physically stable, remaining amorphous
after storage at 40 °C/75 % RH for 6 months in a sealedcontainer and after exposure to 40 °C/75 % RH for 28 daysin an open container (Sahakijpijarn et al., 2020b).

2.3.5 Solubility and dissolution
The enhanced dissolution of a drug in a TFF formulationis generally associated with the brittle matrix nature of TFF
powders, and the matrix consists of the amorphous formsof the drug and the excipient. A dissolution test showedthat TAC combined with lactose (5 % w/w) released ahigher amount of drug within 6 hours compared to thephysical mixture of unprocessed TAC and lactose (~85 %and ~30 % drug release, respectively) (Sahakijpijarn etal., 2020b). The drug loading and the amount of lactose in
the formulation did not affect the rate and extent of drug
release, as there was no difference in dissolution profiles
between TFF TAC/LAC (50:50 w/w), TFF TAC/LAC(95:5 w/w), and TFF neat TAC (Sahakijpijarn et al., 2020b;
Sinswat et al., 2008). The enhanced dissolution of TFF
TAC formulations was associated with the enhanced solubility of the amorphous form of TAC. The amorphous formof a drug generally exists in a higher free energy state thanits crystalline counterpart, thereby enhancing its solubility
and dissolution rate (Trasi et al., 2017). It was reported
that the solubility of amorphous TAC was 35-times higher
than its crystalline solubility (Trasi et al., 2017). In anotherstudy, the dissolution of TFF remdesivir formulations
containing different excipients (i.e., Captisol®, mannitol,
lactose, and leucine) was compared with the dissolution
of TFF neat remdesivir and unprocessed remdesivir(Sahakijpijarn et al., 2020a). All TFF remdesivir formulations exhibited faster and higher dissolution of remdesivir
than unprocessed remdesivir (Sahakijpijarn et al., 2020a).
Similar to the TAC case, the increased dissolution rate andextent of remdesivir release are also related to the higher
solubility of amorphous remdesivir, compared to crystalline remdesivir (Sahakijpijarn et al., 2020a).
In several cases, the presence of a polymer as an excipient in a TFF formulation not only increases the rate andextent of dissolution, but also enhances and prolongs thesupersaturated dissolution. The concentration (C) of drug
dissolved in the media divided by the equilibrium solubility(Ceq) of the crystalline form yields the degree of supersat-

184

uration (C/Ceq) (Overhoff et al., 2008; Yang et al., 2008).
Yang et al. reported that the colloidal dispersion of TFF
itraconazole (ITZ)/MAN/lecithin (1:0.5:2 w/w/w) had a C/
Ceq of 22-times at 5 min and the highest value of 27-times
at 15 min in lung simulated fluid (Yang et al., 2008). After
3 h, the supersaturated ITZ concentration of TFF ITZ/
MAN/lecithin started to decrease to about 7-times, while
the physical mixture only reached 2-times at 15 mins andgradually decreased to a plateau of Ceq after 2 hours (Yanget al., 2008). For oral drug delivery, Overhoff et al. investigated the in vitro supersaturation dissolution of a TFF
tacrolimus-sodium dodecyl sulfate formulation (TFF TACSDS) and the commercial tacrolimus capsule, Prograf ®, inthe two-stage dissolution test in acidic conditions. It wasreported that TFF TAC-SDS exhibited a higher degree ofsupersaturation than Prograf ® after 2 hours (17-times C/
Ceq versus 14-times C/Ceq, respectively). Upon a pH shift
from 1.2 to 6.8, the TFF TAC-SDS also exhibited an increase in supersaturation level from 17-times to 22-times at
15 min after the pH shift, while Prograf ® did not maintaina high degree of supersaturation and started to precipitateout immediately after the pH shift. Although the degreeof supersaturation gradually decreased to 2.5-times C/Ceq
at 24 h after the pH shift, the area under the dissolution
curve (AUC) of the TFF TAC-SDS was higher than that of
Prograf ® under acidic and pH-shift conditions (Overhoff etal., 2008).
A benefit of formulating proteins as powders as opposed
to liquids is that powders are not limited by the solubilityof the protein in the dose (Johnson, 1997). The solubilityof proteins is directly related to adsorption at the air-liquidinterface and aggregation. Techniques that expose proteinsto a high liquid interfacial area (e.g., SD, SFD), often require the use of additional excipients, such as cyclodextrins(Ramezani et al., 2017), surfactants (Bhatnagar B. andTchessalov., 2020), ethanol (Johnson, 1997), or the utilization of acidic conditions (Liu et al., 1991). These excipients
may also be necessary to modulate the dissolution of theprotein. SFD bovine serum albumin (BSA) protein with orwithout trehalose was encapsulated in poly(D,L-lactideco-glycolide) (PLG) or PLG/poloxamer microspheres(Carrasquillo et al., 2001). Within 4 h in phosphate-buffered saline (PBS) at 37 °C, SFD BSA/PLG and SFD
BSA-trehalose/PLG released > 80 % of the protein, while
the inclusion of poloxamer (1:20 and 1:1 PLG/poloxamer)
extended the release over 1–2 days (Carrasquillo et al.,2001). Finally, due to their high porosity and high SSA,
dry powders of biologics, such as vaccines, prepared by
TFF can often rapidly dissolve upon contact with a diluent
without any agitation, which is advantageous if there is aneed to reconstitute a TFF dry powder. Of course, one can
expect that TFF dry powders can readily dissolve in lung
fluid once delivered into the lung.

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

2.4 Formulation and device considerations

properties with higher FPFs and smaller MMADs (Moonet al., 2019a).

2.4.1 Solids content
A few characteristics of TFF powders are affected bysolids content, the total amount of solids dissolved orsuspended in the liquid (e.g., active ingredient, carriers,
other excipients). In terms of aerodynamic properties, afeeding solution with less solids content generally produces more aerosolizable powders. When a comparison of
TFF VCZ nanoaggregates was made between 1 % and 3 %(w/v) solids content, 1 % was associated with a higher FPF
of 67.5 % compared to 48.5 % at 3 % (Moon et al., 2019a).
However, in some cases with an amorphous TFF brittle matrix powder, different solids content does not present significantly different aerodynamic properties (Sahakijpijarn
et al., 2020a; 2020b) or a higher solids content actually
produces improved aerosol properties (Beinborn et al.,2012b). The solids content can also influence the SSA.
High-potency, amorphous TFF TAC powders resulted
in about a 50 % larger SSA when the solids content was
0.75 % (w/v), as compared to 2.5 % (w/v) (Sahakijpijarn
et al., 2020b). However, crystalline TFF VCZ powders did
not show different SSAs when the solids content varied
from 0.1 to 10 % (w/v) (Beinborn et al., 2012b).
In addition to aerodynamic properties and SSA, the solids content is also an important parameter for manufacturing with regard to scale up. The formulations developed by
TFF are currently beginning Phase II clinical trials. Whena large amount of TFF powders, on the scale of multikilograms, is necessary, higher solids content will reduce
the total manufacture time of the powders.

2.4.2 Solvent system
Solvent systems used for TFF can significantly affect amorphicity, morphology, and aerosol performance.
Beinborn et al. showed that TFF VCZ-PVP K12 (1:2 w/w)
and TFF VCZ-PVP K30 (1:2 w/w) prepared with 1,4dioxane as a solvent were amorphous (Beinborn et al.,2012b). However, when binary solvent systems of 1,4dioxane and water (50:50 or 20:80 v/v) were used forthese compositions, both formulations were crystalline(Beinborn et al., 2012b).
When a binary solvent system of water and acetonitrile
is used for TFF, cryo-phase separation of the solvent system must be considered. A mixture of water and acetonitrile
phase-separates during the freezing if 35–88 % (v/v) acetonitrile is included in the mixture (Zarzycki et al., 2006).
When this cryo-phase separation occurs, a different morphology of powder formulations can be observed (Moon etal., 2019a). The mixture of water and acetonitrile not only
impacts cryo-phase separation, but also affects the aerosol
performance. In the case of TFF VCZ nanoaggregates,
the higher portion of water included in the binary solvent
system of water and acetonitrile enhanced aerodynamic

2.4.3 Excipients
Carrier sugars are the most common excipients in the
preparation of powders. Sugars raise the viscosity of theliquid thus slowing particle growth during rapid freezing.
Sugars can also enhance the stability. Inclusion of a sugarin the formulation can help water vitrify at a lower coolingrate, meaning the higher cooling rate of SFD and SFL are
not necessary.
In general, the characteristic porous particles preparedby TFF have high SSA and low bulk density. As shown in
Table 1, the bulk density of TFF neat VCZ powder is 17fold and 2.7-fold lower than that of unprocessed VCZ andmicronized VCZ powder, respectively. Similarly, the SSAs
of powders processed by TFF with or without an excipientwere 4-times higher than unprocessed neat drug powder(Table 1). Without excipient, TFF neat VCZ showed lower
SSA than TFF neat TAC (Beinborn et al., 2012a; Sinswat
et al., 2008), which is related to the crystallinity and theunique morphology of VCZ nano­aggregates. The inclusionof sugars can further improve the SSA of TFF powders
and is variable depending on the type and amount of sugar
used. At 95 % drug loading, TFF TAC formulations that
contained 5 % lactose (w/w) exhibited higher SSA compared to other formulations that contained 5 % w/w mannitol or 5 % trehalose (Sahakijpijarn et al., 2020b). A TFF
TAC formulation containing 50 % w/w lactose showed ahigher SSA than a TFF TAC formulation containing 5 %w/w lactose (Sahakijpijarn et al., 2020b).
In contrast, the effect of the amount of polymer as anexcipient on SSA is not the same as that of sugar excipients(Overhoff et al., 2007b). At 2 % w/w solids content, TFF
ITZ formulations containing 80 % w/w hydroxypropyl
methylcellulose phthalate (HP55) resulted in lower SSA
than the formulation containing 20 % HP55 (Overhoff etal., 2007b). However, at lower solids content (0.2 % w/w),
there was no significant difference in SSA between these
two formulations (Overhoff et al., 2007b). The higher levelof polymer in the solution can prevent the formation of
nanoparticles (Overhoff et al., 2007b), which produce alarger and less brittle structure. Overall, SSA is influenced
by several parameters, including type of excipient andexcipient loading, processing temperature, solids content,
and solvent system composition.

2.4.4 Drug loading
The degree of drug loading in TFF powders can influence the particle morphology, but potentially less so if thepowder is an amorphous brittle matrix (Sahakijpijarn etal., 2020a; Sahakijpijarn et al., 2020b). However, in thecase of crystalline TFF VCZ nanoaggregates, different
drug loadings significantly affected particle morphologies

185

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192(Moon et al., 2019b). TFF VCZ showed crystalline nanoaggregates when processed with mannitol as a single
excipient, which was phase-separated from VCZ (Moonet al., 2019b). While VCZ exhibits as nanoaggregates thatare a few micrometers in size, mannitol exhibits as a brittle
matrix powder that consists of particles that are smaller
than 150 nm (Moon et al., 2019b). As a result of the different morphologies of these two phase-separated crystalline
ingredients, a different ratio of VCZ and mannitol resulted
in significantly different particle morphologies (Moon etal., 2019b). More interestingly, due to generating smallmannitol nanoparticles, when VCZ loading is high (i.e.,
90–97 %), the phase-separated mannitol nanoparticles
reside on the flat surface of VCZ nanoaggregates and act
as a surface modifying agent (Moon et al., 2019b). This
reduces cohesive and adhesive energy of VCZ particles andenhances the aerodynamic properties of the powder.
Amorphous, brittle matrix TFF powders do not show
different morphologies with different levels of drug loading; however, the aerodynamic properties of these powders
still depend on drug loading for certain excipients anddrugs. For TFF TAC with lactose, 70–80 % (w/w) TAC
loading resulted in the highest FPF at the solids content of
0.75 % (w/v) (Sahakijpijarn et al., 2020b). In the case of
TFF-remdesivir with Captisol®, the powders with higher
drug loading aerosolized better than those with lower drug
loading (Sahakijpijarn et al., 2020a). In contrast, the higher
drug loading resulted in less aerosolizable TFF-remdesivir
powders with leucine, showing larger MMADs and lower
FPFs. However, when TFF-remdesivir was formulatedwith mannitol or lactose, 50 % and 80 % (w/w) drug loading exhibited similar FPF.

2.4.5 Loading dose and delivery device
The loading dose can also affect the aerosol performance. The aerosol properties of TFF VCZ nanoaggregateswere tested and compared with high resistance RS00 and
RS01 Plastiape devices (Moon et al., 2019a). When TFFVCZ nanoaggregates were filled into #3 HPMC capsuleswith 10, 15, or 20 mg, the high resistance RS00 Plastiape
device provided more consistent and enhanced aerosol
performance within these filling ranges. While FPF andMMAD were not significantly different between the threedoses, the 20 mg dose, with the capsule completely full,presented slightly lower aerosol properties than either the
10 or 15 mg dose.
The type of device used to deliver dry powder formulations is selected for its influence on its aerosol performance.
While TFF powder formulations exhibit aerodynamic
properties that are independent of flow rate, they are stillaffected by the type of resistance and device (Moon etal., 2019a; Sahakijpijarn et al., 2020b). The high dose
TFF TAC brittle matrix powder demonstrated consistent
MMAD and FPF in the range of flow rates between 30 and

186

60 L/min, which represented 1 and 4 kPa pressure drop,
respectively, with a high resistance RS01 Plastiape device.
However, when the same TFF TAC was aerosolized using
a low resistance RS01 Plastiape device, it was less aerosolizable and relied more on flow rate compared to high resistance RS01 Plastiape device (Sahakijpijarn et al., 2020b).
Interestingly, in the case of TFF VCZ nanoaggregates,
both low resistance RS00 and RS01 Plastiape devices
exhibit excellent aerosol properties (Moon et al., 2019a).
Low and high resistance RS00 Plastiape devices performbetter than the corresponding low and high resistance RS01
Plastiape devices. The most flow rate independent device
for TFF-VCZ nanoaggregates was the high resistance
RS00 Plastiape device, which creates smaller holes in thecapsule shell wall, likely facilitating deaggregation the TFF
nanoaggregates.

3. Applications of TFF: formulation of proteinsas powders for pulmonary delivery
3.1 The need for pulmonary delivery of proteins
into the lungs
Within the class of proteins, there are various types thathave their own unique characteristics. Several proteins
have been studied for delivery via the pulmonary routeas dry powders: proteins (e.g., insulin, calcitonin, BSA),
enzymes (e.g., dornase alpha, LDH, lysozyme), and antibodies (e.g., anti-IgE). The category of antibodies also
includes antibody fragments and nanobodies. Antibody
fragments typically consist of either the antigen binding
fragment (Fab) or crystallization fragment (Fc). One typeof antibody fragment is a domain antibody fragment (dAb),
which is the smallest functional antigen-binding region of
antibodies and are derived from a single variable regionof either the light (VL) or heavy (VH) chain (Holt et al.,
2003; Proudfoot et al., 2018). Antibody fragments can be
more susceptible to aggregation after freeze-thawing thanfull length antibodies (Wang et al., 2007). However, due totheir small size, they may have enhanced tissue penetration
and are relatively easier to manufacture (Nelson, 2010).
Nanobodies are proteins derived from heavy-chain only
antibodies (HCAb) found in Camelidae and are about one
tenth the size of an antibody. Finally, many vaccines areprotein-based. Protein therapeutics continue to become
more and more complex (e.g., antibody-drug conjugates)
and will require much care when developing them as morestable powders (Bodier-Montagutelli et al., 2018) .
Protein-based therapeutics are often administered byparenteral routes, such as intravenous, subcutaneous, orintramuscular injection. There is a need to deliver some
protein-based therapeutics directly to the lungs, largely due
to their low distribution to the lungs when administered

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

systemically, which means high doses are required
to achieve adequate lung distribution. For example,
Guilleminault et al. explored the delivery of cetuximab, ananti-epidermal growth factor receptor (EGFR) antibody,
via aerosolization into the lungs for the treatment of lungcancer. In mice with orthotopic lung tumors, aerosolizationof cetuximab in solution achieved substantially better
delivery of cetuximab to the lung tissues as compared to
intravenous administration, which led to a higher dose ofcetuximab distributing to the tumors in the lung (i.e., up to
4-fold higher as compared to intravenous injection at 2 h)(Guilleminault et al., 2014). Similar studies and results
were produced by Maillet et al. (Maillet et al., 2011). In
fact, two proteins have been approved for delivery via
the pulmonary route, including insulin for the treatment
of diabetes (i.e., for systemic distribution) and dornase
alpha, or Pulmozyme, a solution of recombinant humandeoxyribonuclease indicated for reducing lung infections
and improving lung function in patients with cystic fibrosis(i.e., for local lung distribution). Lungs have a high degreeof vasculature, high surface area, thin epithelium, highpermeability for large molecules, and fewer enzymes andhigher pH compared to the gastrointestinal tract (Liang etal., 2020). The respiratory route is also less invasive (i.e.,does not require a needle puncture or a trained health professional), has a faster onset of action, and minimizes systemic toxicity compared to the parenteral routes (Johnson,1997).

3.2 The need for dry powder formulation ofproteins for pulmonary delivery
Many medications are delivered to the lungs via nebulization, which is the aerosolization of liquid preparations
and direct inhalation of the mist/aerosols into the lungs.
Formulations for nebulization are prepared and stored ina liquid state, which is not ideal for proteins. Proteins are
generally less stable in a liquid formulation than in a dry
powder, and nebulization exposes proteins to harsh conditions, including shear stress and high temperatures exiting
the device (Bodier-Montagutelli et al., 2018) and a highair-liquid interfacial area, causing aggregation (Wang etal., 2007). The percent of functional LDH was measured to
be < 6 % after nebulization and could only be improved to
62 % with the use of a protectant (e.g., Tween 80, chitosan)(Albasarah et al., 2010). The most common nebulization
device is the vibrating-mesh nebulizer because of its ability
to deliver relatively high doses while being less destructive
than ultrasonic or jet nebulizers (Lightwood et al., 2013;
Maillet et al., 2008). Liquid formulations for nebulizationcan, and typically must, be customized for the specificmolecule and often require the use of a surfactant (e.g.,polysorbate, polyethylene glycol) or other stabilizer (BodierMontagutelli et al., 2018) and organic solvents, which

can be toxic to the lungs. Solubility of the formulation
excipients also limits how concentrated the dose can be,meaning a large dose may be necessary (Johnson, 1997).
Furthermore, nebulizer devices are less convenient forthe patient, and they often cannot be as easily transported
compared to DPI devices. Administration of a nebulized
protein usually requires several minutes of inhaling theaerosol. For example, Pulmozyme, when administeredwith the eRapid® Nebulizer system, should be inhaled for
1–5 minutes (Genentech, 2018). This is in contrast to a
DPI, which can deliver a full dose in a few seconds as abolus. There are benefits to nebulization, however, suchas fewer manufacturing steps (e.g., no drying) (BodierMontagutelli et al., 2018), but the overall aerosol per­formance of nebulizers is worse than DPI devices. For
example, tobramycin PulmoSphere dry powder administered via a DPI exhibited an emitted dose of 78.3 %,delivering 34.3 % of the total dose to the lungs, while thenebulized tobramycin product emitted 39.4 % of the dose,delivering only 5.0 % of the dose to the lungs (Newhouse
et al., 2003). The nebulized dose had to be administeredfor 15 min (Newhouse et al., 2003). Preparing proteinsas powders for delivery to the lungs can enhance aerosol
performance as well as the storage stability of them. Aggregation also occurs in lyophilized powders, however, it canbe minimized by inclusion of protectants (Yu et al., 2006).
Only a few protein-based therapeutics developed for
pulmonary delivery have been formulated as powders.
Human growth hormone (22 kDa protein) SD powder,infliximab (149 kDa antibody) SD powder, and influenza
subunit vaccine (225 kDa protein) SD and SFD powders
are in preclinical development (Liang et al., 2020). The
influenza subunit vaccine SD and SFD powders were foundto have FPFs of 37 % and 23 %, respectively (Saluja et al.,2010). A few are in the clinical development stage. For example, Novartis is developing CSJ117, anti-thymic stromal
lymphopoietin (46 kDa antibody fragment), as a dry powder for inhalation. They report having completed a phase
I trial in 2019, administering CSJ117 with a Concept1
single dose DPI to adult patients with mild, atopic asthma(NCT03138811). CSJ117 was well tolerated and reduced
allergen-induced bronchoconstriction compared to placebo(Gauvreau et al., 2020). Recruitment for a phase II trial
in adult patients with severe, uncontrolled asthma began
in 2020 (NCT04410523). UCB Pharma designed VR942,
a dry powder formulation of an anti-IL-13 antibody fragment, also known as CDP7766. A phase I clinical trial was
conducted in 2018 with a Multidose F1P DPI showingthat it was well tolerated for up to 10 days and achieved
inhibition of fractional exhaled nitric oxide (FeNO) as asecondary outcome (Burgess et al., 2018). Patents can befound detailing the Novartis and UCB Pharma products,
but it is difficult to determine which formulations wereused in clinical trials and their corresponding aerosol

187

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

properties (Morgan et al., 2019; Rondeau et al., 2017).
DAS181, or Fludase® is a 46 kDa sialidase fusion protein
in phase 1/II trials for parainfluenza by Ansun BioPharma(Zenilman et al., 2015). It is a dry powder delivered by
the Cyclohaler® DPI and its desired site of action is thecentral/upper respiratory tract and thus is designed to havean FPF of around < 10 % and MMAD 3–8 μm (Malakhov
and Li, 2014). Insulin is a small protein (5.7 kDa) that isused to treat diabetes mellitus. Two insulin dry powders forinhalation products, Afrezza® by MannKind and Exubera®
by Pfizer, were approved and commercialized. Exubera®
was ultimately discontinued due to patient and provider
dissatisfaction (Heinemann, 2008).
We have experimental evidence that TFF can be applied
to prepare dry powders of proteins or protein-containing
products while maintaining the activity of the proteins, andthe resultant dry powders have excellent aerosol properties
for lung delivery and can be potentially stored without cold
chain.

3.3 Protein dry powders engineered using TFF
technology
Over the years, we have successfully applied TFF
technology to prepare dry powders of proteins and proteincontaining products such as vaccines (Engstrom et al.,2008; Li et al., 2015; Moon et al., 2016; Thakkar et al.,2017). We have shown that protein dry powders preparedby TFF maintain their functional activity, have good aerosol performance properties, and have improved thermostability for potential cold chain-free storage.
For example, LDH was formulated into powders withtrehalose (1:120, w/w) as a carrier using shelf FD, SFD,
SFL, and TFF. For all except SFD, the activity of LDH in
the dry powders was 97–100 %, whereas SFD produced
an LDH powder with only 74–85 % activity (Engstrom etal., 2008). Around 20–30 % of protein was adsorbed to thegas-liquid interface in SFD, explaining the decrease in theactivity of the LDH (Engstrom et al., 2008). Lysozyme at
5 mg/ml or 50 mg/ml was also formulated into powders
using SFD, SFL, and TFF. Lysozyme powder preparedby shelf FD at 5 mg/ml showed an SSA of 4.4 ± 0.3 m2/g
(Table 1). Lysozyme powder produced via TFF at 5 mg/ml
had a high SSA (i.e., 45–73 m2/g) (Table 1, Engstrom etal., 2008). SFD can produce a powder with an even larger
SSA (i.e., 126 m2/g vs. 31–55 m2/g for TFF at 50 mg/ml)(Table 1, Engstrom et al., 2008). As mentioned earlier,Figs. 2(b), 2(c), and 2(d) show the morphology of thelysozyme particles that were prepared by TFF, SFL, andSFD, respectively (Engstrom et al., 2008; Yu et al., 2006).
All particles showed similar morphologies. Increasing theprotein concentration from 5 to 50 mg/mL deceased thesubmicron particle fraction from 81–92 % to 62–66 %. The
high concentration also produced more micron-sized parti-

188

cles, likely due to a higher degree of collisions contributing
to particle growth, but 5 mg/mL is more clinically relevant(Engstrom et al., 2008). TFF and SFL produced similarmorphologies when powders were examined by SEM,
with the particle size increasing with decreasing freezing
temperature. Again, the particle size was increased when
the protein concentration was increased. SFD was able toform smaller particles than SFL and TFF.
Lysozyme dry powders were also prepared by TFF withmannitol as the excipient (50:50, w/w), and the resultant
dry powders showed excellent aerosol properties, with
MMAD values within the range of 1–5 μm and FPF up to
65 % (Table 2). As mentioned earlier, increasing the solids
content in the lysozyme solution, from 1 % to 10 %, led toa reduction in the FPF.
Finally, dry powders of proteins or protein-containing
products prepared by TFF also have excellent thermostability. As mentioned earlier, Li et al. reported that vaccines
containing protein as antigens and an insoluble aluminum
salt as an adjuvant can be readily transformed from liquidsuspension into a dry powder without causing aggregationof the protein-adsorbed aluminum salt microparticles or adecrease in the immunogenicity of the antigen proteins following reconstitution of the dry powders (Li et al., 2015).
Due to the presence of the aluminum salt particles in thevaccines, the vaccines may not be subjected to accidental
slow freezing during distribution and storage, because slow
freezing causes particle aggregation and loss of vaccine
activity. Also, the protein antigens in the vaccines are generally unstable at high temperatures (e.g., RT). Therefore,
vaccines containing aluminum salts as adjuvants must be
kept in cold chain conditions (2–8 °C). The vaccine dry
powders prepared by TFF are not sensitive to repeated slow
freezing and thawing anymore. More importantly, a model
protein antigen-based vaccine adjuvanted with aluminum
oxyhydroxide that lost nearly all its immunogenicity after 3
months of storage at even 4 °C as a liquid did not show any
significant immunogenicity decrease after it was stored asa TFF powder at 40 °C for 3 months (Thakkar et al., 2017).
TFF is a technology that enables the engineering ofdry powder formulations of protein-based therapeutic
products and the resultant dry powders have good aerosol
Table 2 Aerosol performance properties of MAN/lysozyme TFF powders (Moon et al., 2016).

Formulation

MMAD
(μm)

GSD
(μm)

FPF
(%)

MAN/lysozyme 50:50 (w/w)
TFF 1 % (w/v)

2.820

3.864

65.029MAN/lysozyme 50:50 (w/w)
TFF 5 % (w/v)

3.913

3.552

40.478MAN/lysozyme 50:50 (w/w)
TFF 10 % (w/v)

3.546

2.825

34.150

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

properties and thermostability. Of course, even within dry
powder formulations, challenges that must continue to beaddressed are potential immunogenicity and toxicity tolungs due to concentrated doses. As previously described,
due to the acceptable aerosol properties of dry powders
prepared by TFF, dose and powder burden can be reduced.
TFF can also play a role in minimizing the immunogenicity
of protein-based products, as the ultra-rapid freezing
during TFF helps to minimize protein aggregation.

4. Conclusion
Thin-film freezing is an ultra-rapid cryogenic freezing
technique. It can be used to prepare powders with tunableproperties. Its intermediate cooling rate allows for the production of powders with high SSA, low aggregation, andsubmicron size particles. TFF is also a viable processing
method for creating protein dry powders for pulmonary
delivery. Proteins that are subjected to TFF and thensublimation to remove frozen solvent are able to maintaintheir structure and functionality. Dry powders of proteinsprepared by TFF also have good thermostability as well as
aerosol properties for pulmonary delivery.

Conflict of Interest Disclosure
Hufnagel, Moon, Sahakijpijarn, Cui, and Williams
are co-inventors on IP related to this review paper. The
University of Texas System has licensed this IP to TFF
Pharmaceuticals, Inc. Moon, Sahakijpijarn, and Williams
acknowledge consulting for TFF Pharmaceuticals, Inc.
Williams and Cui own equity in TFF Pharmaceuticals, Inc.

References
Albasarah Y.Y., Somavarapu S., Taylor K.M., Stabilizing protein
formulations during air-jet nebulization, International Journal of Pharmaceutics, 402 (2010) 140–145. DOI: 10.1016/j.
ijpharm.2010.09.042
Beinborn N.A., Du J., Wiederhold N.P., Smyth H.D., Williams
III R.O., Dry powder insufflation of crystalline and amorphous voriconazole formulations produced by thin film
freezing to mice, European Journal of Pharmaceutics andBiopharmaceutics, 81 (2012a) 600–608. DOI: 10.1016/j.
ejpb.2012.04.019
Beinborn N.A., Lirola H.L., Williams III R.O., Effect of process
variables on morphology and aerodynamic properties ofvoriconazole formulations produced by thin film freezing,
International Journal of Pharmaceutics, 429 (2012b) 46–57.
DOI: 10.1016/j.ijpharm.2012.03.010
Bhatnagar B., Tchessalov S., Advances in freeze drying of
biologics and future challenges and opportunities, in:
Ohtake S., Izutsu K.I. and Lechuga-Ballesteros D. (Eds.),
Drying Technologies for Biotechnology and Pharmaceutical

Applications, (2020) 137–177. 2020, pp.137–177, ISBN:9783527341122. DOI: 10.1002/9783527802104.ch6
Bodier-Montagutelli E., Mayor A., Vecellio L., Respaud R.,
Heuzé-Vourc’h N., Designing inhaled protein therapeutics
for topical lung delivery: what are the next steps?, Expert
Opinion on Drug Delivery, 15 (2018) 729–736. DOI:
10.1080/17425247.2018.1503251
Burgess G., Boyce M., Jones M., Larsson L., Main M.J., Morgan
F., Phillips P., Scrimgeour A., Strimenopoulou F., Vajjah P.,
Zamacona M., Palframan R., Randomized study of the safety
and pharmacodynamics of inhaled interleukin-13 monoclonal antibody fragment VR942, EBioMedicine, 35 (2018)
67–75. DOI: 10.1016/j.ebiom.2018.07.035
Carrasquillo K.G., Stanley A.M., Aponte-Carro J.C., De Jésus P.,
Costantino H.R., Bosques C.J., Griebenow K., Non-aqueous
encapsulation of excipient-stabilized spray-freeze dried
BSA into poly (lactide-co-glycolide) microspheres results inrelease of native protein, Journal of Controlled Release, 76(2001) 199–208. DOI: 10.1016/s0168-3659(01)00430-8
Chen L., Okuda T., Lu X.Y., Chan H.K., Amorphous powders forinhalation drug delivery, Advanced Drug Delivery Reviews,
100 (2016) 102–115. DOI: 10.1016/j.addr.2016.01.002
de la Torre B.G., Albericio F., The Pharmaceutical Industry in
2019. An analysis of FDA drug approvals from the perspective of molecules, Molecules, 25 (2020) 745. DOI: 10.3390/
molecules25030745
Engstrom J.D., Lai E.S., Ludher B.S., Chen B., Milner T.E.,
Williams III R.O., Kitto G.B., Johnston K.P., Formationof stable submicron protein particles by thin film freezing,
Pharmaceutical Research, 25 (2008) 1334–1346. DOI:
10.1007/s11095-008-9540-4
Engstrom J.D., Simpson D.T., Lai E.S., Williams III R.O.,
Johnston K.P., Morphology of protein particles produced byspray freezing of concentrated solutions, European Journalof Pharmaceutics and Biopharmaceutics, 65 (2007) 149–162.
DOI: 10.1016/j.ejpb.2006.08.005
Fröhlich E., Salar-Behzadi S., Oral inhalation for deliveryof proteins and peptides to the lungs, European Journalof Pharmaceutics and Biopharmaceutics, (2021) DOI:
10.1016/j.ejpb.2021.04.003
Gauvreau G., Hohlfeld J., Grant S., Jain M., Cabanski M., Pertel
P., Boulet L.-P., Cockcroft D., Davis B., Fitzgerald J., Efficacy and safety of an inhaled anti-TSLP antibody fragment in
adults with mild atopic asthma, Late breaking clinical trials
in airway diseases, (2020) A4207-A4207. DOI: 10.1164/
ajrccm-conference.2020.201.1_MeetingAbstracts.A4207
Genentech, Inc., Pulmozyme instructions for use, (2018),<gene.com/download/pdf/pulmozyme_IFU.pdf> accessed
19.05.2021.
Guilleminault L., Azzopardi N., Arnoult C., Sobilo J., Herve V.,
Montharu J., Guillon A., Andres C., Herault O., Le Pape
A., Diot P., Lemarie E., Paintaud G., Gouilleux-Gruart V.,
Heuze-Vourc’h N., Fate of inhaled monoclonal antibodies
after the deposition of aerosolized particles in the respiratory
system, Journal of Controlled Release, 196 (2014) 344–354.
DOI: 10.1016/j.jconrel.2014.10.003
Heinemann L., The failure of Exubera: are we beating a deadhorse?, Journal of Diabetes Science and Technology, 2 (2008)
518–529. DOI: 10.1177/193229680800200325
Holt L.J., Herring C., Jespers L.S., Woolven B.P., Tomlinson
I.M., Domain antibodies: proteins for therapy, Trends in
Biotechnology, 21 (2003) 484–490. DOI: 10.1016/j.tibtech.
2003.08.007
Johnson K.A., Preparation of peptide and protein powders forinhalation, Advanced Drug Delivery Reviews, 26 (1997)

189

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

3–15. DOI: 10.1016/s0169-409x(97)00506-1
Li X., Thakkar S.G., Ruwona T.B., Williams III R.O., Cui Z., A
method of lyophilizing vaccines containing aluminum salts
into a dry powder without causing particle aggregation or
decreasing the immunogenicity following reconstitution,
Journal of Controlled Release, 204 (2015) 38–50. DOI:
10.1016/j.jconrel.2015.02.035
Liang W., Pan H.W., Vllasaliu D., Lam J.K.W., Pulmonary delivery of biological drugs, Pharmaceutics, 12 (2020) 1025. DOI:
10.3390/pharmaceutics12111025
Lightwood D., O’Dowd V., Carrington B., Veverka V., Carr M.D.,
Tservistas M., Henry A.J., Smith B., Tyson K., Lamour S.,
The discovery, engineering and characterisation of a highly
potent anti-human IL-13 fab fragment designed for administration by inhalation, Journal of Molecular Biology, 425(2013) 577–593. DOI: 10.1016/j.jmb.2012.11.036
Liu W.R., Langer R., Klibanov A.M., Moisture-induced aggregation of lyophilized proteins in the solid state, Biotechnology
and Bioengineering, 37 (1991) 177–184. DOI: 10.1002/
bit.260370210
Maillet A., Congy-Jolivet N., Le Guellec S., Vecellio L., Hamard
S., Courty Y., Courtois A., Gauthier F., Diot P., Thibault G.,
Aerodynamical, immunological and pharmacological properties of the anticancer antibody cetuximab following nebulization, Pharmaceutical Research, 25 (2008) 1318–1326. DOI:
10.1007/s11095-007-9481-3
Maillet A., Guilleminault L., Lemarie E., Lerondel S., AzzopardiN., Montharu J., Congy-Jolivet N., Reverdiau P., Legrain B.,
Parent C., Douvin D.H., Hureaux J., Courty Y., De MonteM., Diot P., et al., The airways, a novel route for delivering
monoclonal antibodies to treat lung tumors, Pharmaceutical
Research, 28 (2011) 2147–2156. DOI: 10.1007/s11095-0110442-5
Malakhov M.P., Li T., Microparticle formulations for delivery to
the lower and central respiratory tract and methods of manufacture, US Patents (2014) US20140099380A1.
Moon C., Sahakijpijarn S., Koleng J.J., Williams III R.O.,
Processing design space is critical for voriconazole nanoaggregates for dry powder inhalation produced by thin film
freezing, Journal of Drug Delivery Science and Technology,
54 (2019a) 101295.
Moon C., Watts A.B., Lu X., Su Y., Williams III R.O.,
Enhanced aerosolization of high potency nanoaggregatesof voriconazole by dry powder inhalation, Molecular
Pharmaceutics, 16 (2019b) 1799–1812. DOI: 10.1021/acs.
molpharmaceut.8b00907
Moon C., Watts A.B., Williams III R.O., Thin film freezing for
production of an amorphous mannitol/lysozyme formulation
for inhalation: a comparison of freezing techniques, Respiratory Drug Delivery, 3 (2016) 611–616.
Morgan F.G., Main M.J., Palframan R., Kirke D., Inhalable
powder composition comprising il-13 antibody, US Patent,(2019) US20190247303A1.
Nelson A.L., Antibody fragments: hope and hype, MAbs, 2(2010) 77–83. DOI: 10.4161/mabs.2.1.10786
Newhouse M.T., Hirst P.H., Duddu S.P., Walter Y.H., Tarara T.E.,
Clark A.R., Weers J.G., Inhalation of a dry powder tobramycin PulmoSphere formulation in healthy volunteers, Chest,
124 (2003) 360–366. DOI: 10.1378/chest.124.1.360
Newman A.W., Reutzel-Edens S.M., Zografi G., Characterizationof the “hygroscopic” properties of active pharmaceuticalingredients, Journal of Pharmaceutical Sciences, 97 (2008)
1047–1059. DOI: 10.1002/jps.21033
Overhoff K.A., Engstrom J.D., Chen B., Scherzer B.D., Milner
T.E., Johnston K.P., Williams III R.O., Novel ultra-rapid

190

freezing particle engineering process for enhancement ofdissolution rates of poorly water-soluble drugs, European
Journal of Pharmaceutics and Biopharmaceutics, 65 (2007a)
57–67. DOI: 10.1016/j.ejpb.2006.07.012
Overhoff K.A., Johnston K.P., Tam J., Engstrom J.D., Williams
III R.O., Use of thin film freezing to enable drug delivery: areview, Journal of Drug Delivery Science and Technology, 19(2009) 89–98. DOI: 10.1016/s1773-2247(09)50016-0
Overhoff K.A., McConville J.T., Yang W., Johnston K.P., Peters
J.I., Williams III R.O., Effect of stabilizer on the maximum
degree and extent of supersaturation and oral absorption oftacrolimus made by ultra-rapid freezing, Pharmaceutical
Research, 25 (2008) 167–175. DOI: 10.1007/s11095-0079417-yOverhoff K.A., Moreno A., Miller D.A., Johnston K.P., Williams
III R.O., Solid dispersions of itraconazole and entericpolymers made by ultra-rapid freezing, International Journalof Pharmaceutics, 336 (2007b) 122–132. DOI: 10.1016/j.
ijpharm.2006.11.043
Pharmaxis, Ltd, ARIDOL package insert, (1964), <accessdata.
fda.gov/drugsatfda_docs/label/2010/022368S000lbl.pdf>
accessed 13.05.2021.
Pilcer G., Amighi K., Formulation strategy and use of excipients in pulmonary drug delivery, International Journalof Pharmaceutics, 392 (2010) 1–19. DOI: 10.1016/j.
ijpharm.2010.03.017
Proudfoot A., Bayliffe A., O’Kane C.M., Wright T., Serone A.,
Bareille P.J., Brown V., Hamid U.I., Chen Y., Wilson R.,
Cordy J., Morley P., de Wildt R., Elborn S., Hind M., etal., Novel anti-tumour necrosis factor receptor-1 (TNFR1)
domain antibody prevents pulmonary inflammation in experimental acute lung injury, Thorax, 73 (2018) 723–730. DOI:
10.1136/thoraxjnl-2017-210305
Ramezani V., Vatanara A., Seyedabadi M., Nabi Meibodi M.,
Fanaei H., Application of cyclodextrins in antibody microparticles: potentials for antibody protection in spray drying,
Drug Development and Industrial Pharmacy, 43 (2017)
1103–1111. DOI: 10.1080/03639045.2017.1293679
Rondeau J.M.R., Edwards M.J., Miller D., Huang D., Hemmig R.,
Knopf H.-P., Gupta K., Van Heeke G.A., Haubst N., Andlauer
B., Thymic stromal lymphopoietin (tslp)-binding antibodies
and methods of using the antibodies, International Patent(2017) WO2017042701A1.
Sahakijpijarn S., Moon C., Koleng J.J., Christensen D.J.,
Williams III R.O., Development of remdesivir as a dry
powder for inhalation by thin film freezing, Pharmaceutics,
12 (2020a) 1002. DOI: 10.3390/pharmaceutics12111002
Sahakijpijarn S., Moon C., Ma X., Su Y., Koleng J.J., DolocanA., Williams III R.O., Using thin film freezing to minimize
excipients in inhalable tacrolimus dry powder formulations,International Journal of Pharmaceutics, 586 (2020b) 119490.
DOI: 10.1016/j.ijpharm.2020.119490
Sahakijpijarn S., Smyth H.D.C., Miller D.P., Weers J.G.,
Post-inhalation cough with therapeutic aerosols: formulationconsiderations, Advanced Drug Delivery Reviews, 165–166(2020c) 127–141. DOI: 10.1016/j.addr.2020.05.003
Saluja V., Amorij J., Kapteyn J., De Boer A., Frijlink H., Hinrichs
W., A comparison between spray drying and spray freeze
drying to produce an influenza subunit vaccine powder
for inhalation, Journal of Controlled Release, 144 (2010)
127–133. DOI: 10.1016/j.jconrel.2010.02.025
Sinswat P., Overhoff K.A., McConville J.T., Johnston K.P.,
Williams III R.O., Nebulization of nanoparticulate amorphous or crystalline tacrolimus–single-dose pharmacokinetics study in mice, European Journal of Pharmaceutics andStephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

Biopharmaceutics, 69 (2008) 1057–1066. DOI: 10.1016/j.
ejpb.2008.01.037
Thakkar S.G., Ruwona T.B., Williams III R.O., Cui Z., The
immunogenicity of thin-film freeze-dried, aluminumsalt-adjuvanted vaccine when exposed to different temperatures, Human Vaccines & Immunotherapeutics, 13 (2017)
936–946. DOI: 10.1080/21645515.2016.1259042
Trasi N.S., Purohit H.S., Wen H., Sun D.D., Taylor L.S., Nonsink dissolution behavior and solubility limit of commercial
tacrolimus amorphous formulations, Journal of Pharmaceutical Sciences, 106 (2017) 264–272. DOI: 10.1016/j.
xphs.2016.09.016
Ung K.T., Rao N., Weers J.G., Clark A.R., Chan H.K., In vitro
assessment of dose delivery performance of dry powders
for inhalation, Aerosol Science and Technology, 48 (2014)
1099–1110. DOI: 10.1080/02786826.2014.962685
Wang W., Singh S., Zeng D.L., King K., Nema S., Antibody structure, instability, and formulation, Journal of Pharmaceutical
Sciences, 96 (2007) 1–26. DOI: 10.1002/jps.20727
Wang Y.B., Watts A.B., Williams III R.O., Effect of processing
parameters on the physicochemical and aerodynamic properties of respirable brittle matrix powders, Journal of Drug
Delivery Science and Technology, 24 (2014) 390–396. DOI:
10.1016/s1773-2247(14)50079-2
Watts A.B., Wang Y.B., Johnston K.P., Williams III R.O.,
Respirable low-density microparticles formed in situ fromaerosolized brittle matrices, Pharmaceutical Research, 30(2013) 813–825. DOI: 10.1007/s11095-012-0922-2
Weers J., Dispersible powders for inhalation applications, Innovations in Pharmaceutical Technology, 1 (2000) 111–116.
<http://iptonline.com/articles/public/IPTSEVEN111NP.pdf>
accessed 11.06.2021.
Yang W., Tam J., Miller D.A., Zhou J., McConville J.T., Johnston
K.P., Williams III R.O., High bioavailability from nebulized
itraconazole nanoparticle dispersions with biocompatible stabilizers, International Journal of Pharmaceutics, 361 (2008)
177–188. DOI: 10.1016/j.ijpharm.2008.05.003
Yu Z., Johnston K.P., Williams III R.O., Spray freezing into liquidversus spray-freeze drying: influence of atomization onprotein aggregation and biological activity, European Journalof Pharmaceutical Sciences, 27 (2006) 9–18. DOI: 10.1016/j.
ejps.2005.08.010
Zarzycki P.K., Wlodarczyk E., Lou D.W., Jinno K., Evaluationof methanol-water and acetonitrile-water binary mixtures as
eluents for temperature-dependent inclusion chromatography, Analytical sciences, 22 (2006) 453–456. DOI: 10.2116/
analsci.22.453
Zenilman J.M., Fuchs E.J., Hendrix C.W., Radebaugh C., Jurao
R., Nayak S.U., Hamilton R.G., Griffiss J.M., Phase 1 clinical
trials of DAS181, an inhaled sialidase, in healthy adults,
Antiviral Research, 123 (2015) 114–119. DOI: 10.1016/j.
antiviral.2015.09.008

Authors’ Short Biographies
Stephanie Hufnagel
Stephanie Hufnagel received her Pharm.D. degree in 2016 and her Ph.D. degree in Pharmaceutical
Sciences in 2021, both from The University of Texas at Austin, College of Pharmacy. Her primary
focus is the formulation of immuno-oncology agents, including both large and small molecules. She
currently works on the formulation of antibodies as dry powders.

Sawittree Sahakijpijarn
Sawittree Sahakijpijarn received her B.Sc. degree in Pharmaceutical Sciences from Chulalongkorn
University in 2012 and her Ph.D. degree in Pharmaceutical Sciences from The University of Texas atAustin in 2020. She currently works as a postdoctoral research fellow in the Division of Molecular
Pharmaceutics and Drug Delivery at The University of Texas at Austin. Her research focuses on
pulmonary delivery of small molecule and biological drugs.

191

Stephanie Hufnagel et al. / KONA Powder and Particle Journal No. 39 (2022) 176–192

Authors’ Short Biographies
Chaeho Moon
Chaeho Moon was born in South Korea and earned his Ph.D. degree in Molecular Pharmaceutics
and Drug Delivery at The University of Texas at Austin. He is currently working as a Postdoc at UTAustin to develop powder formulations for dry powder inhalations, as well as TFF powder formulations of vaccine, mAb, protein, peptide, and mRNA/LNP products.

Zhengrong Cui
Zhengrong Cui is a Professor at The University of Texas at Austin, College of Pharmacy. His
research interests lie in pharmaceutical drug and vaccine delivery. He also has extensive experiencein thin-film freeze-drying of biologics and their needle-free delivery. Dr. Cui has published extensively in the fields of pharmaceutics, vaccinology, and nanotechnology. He is an inventor on many
patents and patent applications. He serves as an editor to International Journal of Pharmaceutics.
Dr. Cui holds a Ph.D. degree in Pharmaceutical Sciences from the University of Kentucky, Collegeof Pharmacy. He is a Fellow of the American Association for Pharmaceutical Scientists.

Robert O. (Bill) Williams III
Robert O. (Bill) Williams III is the Johnson & Johnson Centennial Chair, Professor and Division
Head of Pharmaceutics at the College of Pharmacy, University of Texas at Austin. Dr. Williams is
Fellow of the American Association of Pharmaceutical Scientists, American Institute of Medical andBiological Engineering, and National Academy of Inventors. He was named Inventor of the Yearby the University of Texas at Austin. He has founded several pharmaceutical companies. He has
published over 220 peer-reviewed papers and co-edited books in pharmaceutical technology anddrug delivery. He is an inventor on over 60 patents. He is Editor-in-chief of AAPS PharmSciTech.

192

KONA Powder and Particle Journal No. 39 (2022) 193–207/https://doi.org/10.14356/kona.2022001

Original Research Paper

Grain-Size Effects on Mechanical Behavior and Failure ofDense Cohesive Granular Materials †Payam Poorsolhjouy 1 and Anil Misra 2*
1 Department of the Built Environment, Eindhoven University of Technology, The Netherlands

2 Civil, Environmental and Architectural Engineering Department, University of Kansas, USA

Abstract
The grain sizes can significantly influence the granular mechano-morphology, and consequently, the macro-scale
mechanical response. From a purely geometric viewpoint, changing grain size will affect the volumetric number
density of grain-pair interactions as well as the neighborhood geometry. In addition, changing grain size can
influence initial stiffness and damage behavior of grain-pair interactions. The granular micromechanics approach(GMA), which provides a paradigm for bridging the grain-scale to continuum models, has the capability ofdescribing the grain size influence in terms of both geometric effects and grain-pair deformation/dissipation effects.
Here the GMA based Cauchy-type continuum model is enhanced using simple power laws to simulate the effect ofgrain size upon the volumetric number density of grain-pair interactions, and the parameters governing grain-pairdeformation and dissipation mechanisms. The enhanced model is applied to predict the macroscopic response ofcohesive granular solids under conventional triaxial tests. The results show that decreasing grain-sizes can trigger
brittle-to-ductile transition in failure. Grain size is found to affect the compression/dilatation behavior as well as thepost-peak softening/hardening of granular materials. The macro-scale failure/yield stress is also found to have an
inverse relationship with grain-sizes in consonance with what has been reported in the literature.
Keywords: granular micromechanics, grain sizes, brittle to ductile, failure, yield, triaxial compression

1. Introduction
The macro-scale behaviors of dense cohesive granularmaterials are directly linked to the grain-scale through their
granular mechano-morphology, which is represented bytheir collective arrangements (microstructure) and their interaction mechanisms (micromechnics). The mathematicaldescription of macro-scale response of granular materials
must begin from the conception of grain-interactions.
From this point of departure, either discrete or continuum
descriptions can be elaborated. In discrete models, themacro-scale behavior is inferred by tracking the motionof each grain in response to the external action. Continuum models, in contrast, aim to describe behavior at a
spatial scale in which the grains and their motions remain
concealed within a material point of a continuous system.
While discrete analysis schemes can provide resultswith detailed description of grain motions, inter-granular†*

Received 30 April 2020; Accepted 8 July 2020
J-STAGE Advance published online 3 October 2020
Corresponding author: Anil Misra;
Add: 1530 W. 15th Street, Learned Hall, Lawrence, KS 66045-7609,
USA
E-mail: amisra@ku.edu
TEL: +1-785-864-1750

deformations, they are limited in their applicability tolarge-scale problems due to large computational cost, andthe challenges of grain-scale verification and validation.
On the other hand, classical continuum models, while computationally affordable, suffer from losing characteristicfeatures due to neglecting grain scale phenomena (in termsof both the microstructure and its evolution, as well as theinter-granular mechanisms). In this regards, it is noteworthy that higher-gradient continuum models represent a way
to capture the effect of microstructure and its evolution
during loading (Placidi L. and Barchiesi E., 2018; Placidi
L. et al., 2018a; 2018b), an approach that can be traced tothe early development in continuum mechanics (dell’IsolaF. et al., 2014; Eugster S.R. and dell’Isola F., 2017).
Granular micromechanics approach (GMA) provides aparadigm that bridges the grain-scale models to appropriate
continuum model (Nejadsadeghi N. and Misra A., 2020;
Poorsolhjouy P. and Misra A., 2019). In this approach,the constitutive relation for a continuum material point isderived by utilizing the directional average of variously
oriented grain-pairs. In this way, GMA incorporates datafrom the microstructure and micromechanical phenomena
at grain scale into the continuum model (Misra A. et al.,2020). It has been shown that by incorporating the grainpair interactions in different directions, GMA is able to

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

193

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

capture various behavior, that are difficult to attain withclassical continuum models, using computational demand
which is significantly lower than that associated withdiscrete models (Poorsolhjouy P. and Misra A., 2017).
In a form of GMA that leads to Cauchy-type continuum
model with coupled damage and plasticity, Helmholtz freeenergy density and dissipation potential functions for thecontinuum model are obtained as the volume averages ofcorresponding functions defined for the grain-pair. Grain
scale constitutive equations are calibrated to ensure that themodel replicates the observed behavior. Since the grainpair behavior is nonlinear, the grain-pair oriented in different directions undergo different unique loading paths as acontinuum material point experiences a macro-scale loading sequence. The consequence is that the response of the
granular system is highly loading-path dependent. Indeed,
when a macro-scale body is subjected to a loading-path,the variously oriented grain-pair can be in different loading
stages including loading, unloading, or reloading. The
material response, therefore, at any stage of loading is afunction of the entire loading history rather than the current
loading state.
Since grain-pair interactions are key in GMA-based
continuum models, the grain size effect can be incorporated
by considering its influence on the grain-pair behavior.
Here, we enhance the non-linear damage-plasticity grainpair interaction previously proposed for cementitious
materials by incorporating the effects of grain sizes. We
introduce simple scaling relationships, based on powerlaws, to describe the effect of grain size on grain-pair
stiffness, grain-pair damage dissipation, grain-pair branch
length, and the volumetric number density of grain-pairinteractions in the granular material system. Using these
relationships, size-effect relationships for macroscopic
response of the material (macroscopic stiffness tensor andthe Cauchy stress) are predicted. These results are calculated for parameters that are calibrated using experimental
data available in the literature. The predicted results showthat grain-sizes can influence brittle to ductile transitionand softening-hardening behavior. The results also showthat macro-scale failure stress under axisymmetric loading
scales with grain-sizes as has been observed from experiments on cohesive granular materials.

2. Granular Micromechanics Approach(GMA)
GMA can be categorized as a meso-scale approach thatbridges the gap between continuum models and discretemodels as is seen in Fig. 1. At the smallest scales, atomicmodels can be utilized provided the composition and initialstructures are known. Indeed, provided a faithful realization of the atomic structure, these models can yield results

194with high degree of exactness (i.e. fidelity). For examplesof their application to atomically complex materials thereader is referred to (Misra A. and Ching W.Y., 2013;
Qomi M.J.A. et al., 2014). These models however arecomputationally costly even with the present computationand memory capacities. Moreover, they are inapplicable tolarge systems with complex compositions, or disordered
and defective structures given the difficulties associatedwith the characterization and specification of such materials. In larger scales, discrete models are utilized to investigate the material behavior by simulating the interaction ofmacro-particles that comprise granular system (Gonzalez
M. and Cuitino A.M., 2012; Hentz S. et al., 2004; Misra
A. et al., 2018; Tavarez F.A. and Plesha M.E., 2007; Turco
E. et al., 2019). Discrete models consist of identifying thegrains in the material, their interacting neighbors, and the
behavior of the interaction. For these models one needs tobe able to define grains in a given volume of interest, theirshapes and sizes, their contacts with their neighbor grains,
their surface properties, etc. Moreover, this identificationneeds to be done at any loading increment, considering thefact that during loading all properties of grains and theircontacts will change due to the displacement, deformation,and rearrangement of grains. If the mechano-morphology
of a given granular materials can be faithfully reproduced
throughout a loading process, discrete models can be used
to extract high-fidelity results as depicted in Fig. 1 about
the micro-level response as well as the micro-macro correlation for the material (Gonzalez M. and Cuitino A.M.,
2012; Misra A. and Poorsolhjouy P., 2015b).
GMA incorporates data from the material microstructure
and micromechanics into the continuum model in a computationally affordable statistical manner. The antecedentsof the granular micromechanics approach may be traced tosecond quarter of the 20th century in works related to theestimation of wave velocities in granular beds in which the
Hertz solution for normal contact between elastic spheres
was used to find equivalent elastic moduli of regularly
arranged grain packing (see (Duffy J. and Mindlin R.D.,
1957; Hara G., 1935) and for a brief review (Misra A. etal., 2019)). This analysis served as the inspiration for thedevelopment of stress-strain relations for random packingof grains including certain statistical representation of thepacking geometry (Chang C.S. and Misra A., 1990; Digby
P.J., 1981; Misra A. and Chang C.S., 1993; Walton K.,
1987). In GMA, the exact evolution of grain trajectories
within the material point are not investigated. Instead, themacroscopic behavior of the granular system is derived byaveraging the behavior of grain-pair interactions in different directions. In our past works, we have presented a derivation of the GMA based model applicable to cementitious
granular materials in the framework of thermo-mechanics(Misra A. and Poorsolhjouy P., 2015a; Poorsolhjouy P. andMisra A., 2017). Here, this thermomechanical derivation

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

Fig. 1 Modeling Scales: Schematic graph showing the evolution of computational demand needed for modeling material behavior in different scales,
expanding from nanometers to centimeters.

of GMA is enhanced to account for the effect of grainsizes. The paper is structured as follows: In section 2.1,
a brief review of the general derivation of GMA withina thermo-mechanical viewpoint is presented for completeness. Section 2.2 focuses on the specifics of coupleddamage-plasticity laws at micro-scale for deriving thecorrect macroscopic behavior of the material (for a more
complete description of the micro-scale laws, the reader
is referred to (Misra A. and Poorsolhjouy P., 2015a;
Poorsolhjouy P. and Misra A., 2017)). In Section 2.3, therelationship between grain sizes on one hand and model
variables (including branch vector, density of grain-paircontacts, as well as stiffness and damage variables) on theother, have been discussed and size-effect laws are implemented within the model. Section 3 is devoted to results ofsimulations for samples of various grains sizes and under
different confinements. Particularly, effects of changing
grain sizes on failure and its type (brittle or ductile) has
been discussed. Finally, a summary and conclusion, alongwith an outline of continued research is presented in Section 4.

2.1 Thermo-mechanical derivation
The GMA hypothesizes that the deformation energy of a
volume of granular materials can be effectively expressedin terms of the deformation energies of all its grain-pairinteractions. As a consequence, the macro-scale Helmholtz
free energy density, W, and dissipation potential, ψ, can beobtained as volume averages of their grain-pair counterparts, which are expressed in terms of grain-scale variables
as (Misra A. and Poorsolhjouy P., 2015a; Poorsolhjouy P.
and Misra A., 2017)

1 Nc   p 
W  j ,  j , D j 
V  1(1a)

1 Nc
     j , D j , D j ,  jp ,  jp (1a) V  1

(1b)

W

where the summations go over all grain-pair interactions,superscript α refers to the αth grain-pair, total number of(1b)grain-pairinteractions is Nc, and the superimposed dots
imply time derivative. The grain scale kinematic variablesconsist of the relative displacement and the plastic relative
displacement between neighbor grains,  j and  jp . Here,
we note that in this model, the relative displacements
between grains represents the relative displacement between the centroids of each two neighboring[52] This[51] grains.
relative displacement can have various sources including
deformation of individual grains, or relative movement between grains centroids, or deformation concentrated at thecontacts, e.g. in Hertzian contact. These phenomena are notaddressed separately in this model and their collective effect is lumped into the relative displacement between grain
centroids. The same is true for plastic relative displacement
between grain centroids. In addition, the unitless grainscale damage parameter, D j , is a vector variable which
represents the loss of grain-pair stiffness coefficients. In theentire document, the summation convention over repeatedindices is implied, unless explicitly
noted otherwise.
[53]
In this analysis, we only account for the so-called
macro-displacements and do not introduce any additional kinematic descriptors or higher-gradient terms
and grain-spins/rotations that are necessary for complete
description of the complex granular systems (Misra A. andPoorsolhjouy P., 2016a; 2016b; Nejadsadeghi N. and MisraA., 2020; Poorsolhjouy P. and Misra A., 2019). In this case,195

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

the grain-pair relative displacement,  j , is related only tothe first gradient of macro-displacement field. With this inmind, the macro-scale Helmholtz free energy density, W,
and dissipation potential, ψ, can also[54]be defined as functions of macroscopic variables as follows

distributed linearly in the material point, the corresponding local variables defining the relative kinematics of
two neighbor grains, i.e. the relative displacement, δi,plastic relative displacement, ip , and the damage vector
specifying the loss of stiffness between the two grains,
Di, can be derived (Misra A. and Poorsolhjouy P., 2015a;
W  W ij , ijp , Dij (2a)Poorsolhjouy P. and Misra A.,[57]2017). Approximating the   ij , Dij , D ij , ijp , ijp (2b)displacement and plastic displacement of a grain using the
Taylor series expansion of the displacement and plastic
where the superscript p denote plastic, εij is the independent
displacement of its neighbor grain, allows us to define the(2a)kinematic variable (strain tensor), and Dij is the damage
relative displacement and relative plastic displacement(2b) which for a given direction, n , yields the damage
tensorbetween two neighbor grains (δi and ip ) as the product ofjvector, Di, i.e. Di = Dijnj. As standard in classical contintheir macroscopic counterparts (εij and ijp) with the branch
uum mechanics, the power density of internal forces is
vector. In other words, the displacements are written as
i



p


u


,
expressed as
the projections of their macroscopic[57]counterparts, in theij (i, j )ij ij where σij is the Cauchy
stress tensor. Using the Clausius-Duhem inequality and the
direction of the grain-pair interaction, [58]and then scaled byabove definitions, the following is obtained (Poorsolhjouy
the magnitude of the branch vector. In addition, based on[59][60]-入力あり
P. and Misra A.,
the definition of the macroscopic damage
tensor, Dij, the[55]2017)
grain-scale damage vector, Di, is given, by definition, as

 W
W 
    W
  pthe
product of the damage tensor and the direction of grain



D







0
 ij
 ij 
  ij  ijp ijp  ij
ij 
 Dij Dij pair interaction (i.e. as the projection of tensor, Dij, in the(3)
direction of the grain-pair).

pp(3)Since the equality in Eq. 3 should be satisfied for any (7)i 

Dij n jij l j ; iij l j ; Di
arbitrary set of kinematic variables, all three terms must simultaneously vanish. For the second and third terms, since
where lj is the branch vector joining the centroids of two
the coefficients are functions of the same kinematic varineighborgrains which is given as the product of the length(7)
ables, the weaker orthogonality condition can be sufficientof the branch vector, l, and the unit vector in the direction(Ziegler H., 1983). As a result, the following equations areof the contact, nj as lj = lnj. Substituting Eq. 6 and 7 into
obtained
Eq. 5 the expression for Cauchy stress can be rewritten as

 ij 

W

0
ij

1 Nc 
1 Nc 
f k kiljll
 fi l j
V  1
V 1



 ij
(4a)

 W
  D 0  ij(4a) Dij Dij 

(4b)

 W
  p(4c)0 p  p  ij 
(4b)



ij 
 ij
Further substituting Eq. 1a into Eq. 4a and applying
chain rule the following expression for the Cauchy stresscan(4c)be obtained

 ij

W
1 N c W  kijV  1 k ij

(5)

In Eq. 5 the derivative of grain-pair interaction energy
with(5)respect to the displacement is defined as the conjugate
force measure in the grain-scalef k 

W 
k

(6)

Assuming that the macroscopic variables includingpstrain, εij, plastic strain, ij , and damage tensor, Dij, are(6)

It is remarked here that the widely used Eq. 8 is valid
under specific assumptions as outlined in Eq. 7. Further,we(8)observe that based on the definition of the damage
vector and damage tensor (see Eq. 7) the partial derivative of the damage vector with respect to the damage
tensor is given as ∂Dk/∂Dij = nl∂Dkl/∂Dij = δiknj. In thesame way, the partial derivative of the rate of the damage
vector with respect to the rate of the damage tensor canbe derived as ∂Ḋk/∂Ḋij = nl∂Ḋkl/∂Ḋij = δiknj. The same
relationships can be formulated for the partial derivativeof plastic displacement with respect to plastic strain as,
kp / ijp ll  klp / ijp ik l j , and for their time rates,kp / ijp ll klp / ijp ik l j . It is therefore derived thatkp / ijp . SubDk / Dij D k / D ij and kp / ijp stituting this assumption, as well as Eqs. 1a and 1b into
[61]
Eqs. 4b and 4c, results in[62][63]N c  W      [64]D  
0

(9a)
 

  i 

D
D



i
i 
 1 

(9a)
[56]
196

(8)

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207
Nc W   



 p
0

 
 i  p
 p 
 

 1

i

(9b)

i

Now it should be noted that the summations in Eq. 9
should hold for any number of grain-pair interactions and(9b)the equality should be satisfied in a term-by-termthus,manner.

 W      0 D   D   Di ii     p
 W 
0     p  i 
i 
 i
(10a)
Combining Eq. 6 and 10 results in(10b)  W      W      fj 
j 
 Dj
 j D j  D j W     p
0


j 

 jp   j

(10a)

(10b)

(11)

which leads to the following micro-scale Clausius-Duhemtype inequality for the αth inter-granular interaction:(11)
f j j  W  d   0(12)where the grain-scale dissipation, dα, is defined as
(12)
 
   pd    D j 
j  0D j
 jpAt this juncture, it is useful to formulate the grain-pairenergy and dissipation functions in terms of grain-pairdisplacement decomposed into two components, one along
the vector connecting the two grain-centroids (branch
vector), termed as normal component, and the other in theorthogonal direction, termed as the tangential component(as depicted in the inset in Fig. 2). Accordingly, a local
Cartesian coordinate system, nst, is defined composed ofthree unit vectors: unit normal vector ni in the direction of
branch vector, li, and two orthogonal vectors lying in thetangential plane denoted as si and ti. The direction cosinesof these local coordinate axes are given asni  cos ,sin  cos ,sin  sin 
si   sin , cos  cos , cos  sin 
(15)
t
0,

sin

,
cos

i
(15)-1using
spherical coordinates (See Fig. 2). The normal and(15)-2
tangential(15)-3 components of a grain-pair are then given asn  i ni

w

(13)

and the time derivative of micro-scale free energy, Wα, isW W    W   p
(13)W     j 
Dj 
j
 j
D j
 jp

2.2 Grain-scale coupled damage-plasticity
relationships(14)

Thus, employing appropriate formulation for the Helmholtz energy, Wα, and dissipation potential, ψα, we can(14)completely
describe the grain-pair force-displacement
relationships (using Eq. 12) and in turn, the classical stressstrain behavior of a granular system (using Eq. 8).

 ; where i  ij l j
i si  2  iti  2 

(16)

It should be noted that the subscripts n and w, refer to normal
and tangential components and they do not represent(16)vector quantities. Summation convention, therefore, does
not apply to them. The grain free energy and dissipation
potential are written as the summations of their normal andtangential components, W  Wn  Ww and    n   w .
To account for damage and plasticity, the normal and tangential components of inter-granular free energy take thefollowing form (Misra[65]A. and Poorsolhjouy P., 2015a;
Poorsolhjouy P. and Misra A., 2017)

Fig. 2 Intergranular Force-Laws: (a) Grain-pair force-displacement curve in normal direction showing the tension-compression asymmetry typical ofcohesive grain interactions. (b) Grain-pair force-displacement curve in the tangential direction and inset schematic of an interface between two grains
and the global and local coordinate axes. Damage and stiffness parameters defining the grain-pair interactions are displayed on the graphs.

197

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

12Wn  En 1  Dn n   hnnp
2
(17)
1 
2
p




Ww  Gw 1  Dw  w   hw  w
2(17)-1
Where E n and Gw are the grain-pair elastic stiffness, hnandhw are the grain-pair generalized forces, and np and(17)-2
wp are the grain-pair plastic displacements in normal andtangential[66]directions,[67] respectively. Normal and tangential[68]
componentsofinter-granulardissipation
potential
are
[70]
[69]
represented by the sum of the dissipations due to damage[71]
and plasticity

 n Yn D n  Z n np  0(18)

 w Yw D w  Z w wp  0(18)-1
where
dissipation coefficients Y and Z denote generalized
forces that are conjugates of the inter-granular damage and(18)-2dissipation, respectively. The forms assumed inplastic
Eqs. 17 and 18 result in rate-independent form of damage
and plasticity as opposed to rate-dependent form that arealso relevant to certain granular systems (Giorgio I. and
Scerrato D., 2017; Misra A. and Singh V., 2014a; 2014b).
Substituting Eqs. 17 and 18 into Eqs. 10a and 10b rewritten
for normal and tangential directions one can find the dissipation coefficients, Y and Z, duals of inter-granular damage
and plastic displacements respectively.
Yn

1   2
1   2E n n  sign D n  ; Yw
Gw  w  sign D w 

2
2
(19a)



 p

Z n hhw sign wp 
n sign  n  ; Z w(19a)

Cijkl 1 Nc
kik l jll
V 1

(21)

where Nc is the total number of grain-pair interactions
within the material point. Total number of grain-pair inter(21)actions can be calculated as half of the product of the total
number of grains, N, and the mean coordination number, z.
Using two new parameters, namely the volumetric number
density of grain-pair interactions ρc = Nc/V and the directional density distribution of grain-pair contacts, ξ(θ,ϕ),this summation over all contacts can be transformed into an
integration over all different orientations as
π 2π

(19b)

Further, normal and tangential components of grain-pairforce vector can be found by substituting Eq. 17 into Eq. 7
(19b)
W 
 
f n
En 1  Dn  n

 k
n n
n
(20)
W 







fw
 k
Gw 1  Dw   w
w w
w
(20)-1The details of particular forms of the damage functions
Dn and Dw and related parameters that are applicable to(20)-2 granular materials have been described in details
cohesivein our previous work and is therefore not repeated here
(Poorsolhjouy P. and Misra A., 2017). Fig. 2 contains theforce-displacement relationships, as well as schematiccurves of the functional forms of the force-laws. Moreover,a selection of the major parameters used in the relationships
and their role in the force-displacement curves are depictedin the Fig. 2. The tension-compression asymmetry ofgrain-pair behavior and the post peak softening due to damage under grain-pair tension and shear is clearly illustrated.
The grain-pair tension-compression asymmetry is signif-

198

icant in induced anisotropy evolution in granular systems(Jia H. et al., 2017). Table 1 lists all the model parameters
and their numerical values used in this study. For moredetails and implementation of loading-unloading-reloading
criteria, ratio between failure force in normal compression
to that in normal tension (captured in parameter R), effectof grain-scale relative normal displacement on the grainscale damage parameter in shear direction (captured inparameters α1, α2, and α3), the effect of confinement on thecompressive behavior of grain-pair interactions (captured
in the parameter α4), as well as the incorporation of permanent deformation in grain-pair interactions (captured
in parameters βn and βw), the reader is referred to (Misra
A. and Poorsolhjouy P., 2015a; Poorsolhjouy P. and MisraA., 2017).
Substituting Eqs. 7 and 20 into the equation for Cauchy
stress (Eq. 8) and taking the strain tensor out of the summation, the equation for the fourth rank stiffness tensor canbe derived as

Cijkl = l 2 ρ c ∫ ∫ (k ik n j nl ) ξ (θ, φ)sin θdθdφ
θ = 0φ = 0

Table 1Model parameters used in this study.

(22)
Model Parameters

Value

T
Eno

3.5 kN/m

R

17.5[73] (table=9pt)

Gw

1 kN/mBn

7E-10 mBnc

3E-9 mBwo

1.5E-9 m

α1

10.5

α2

7

α3

0.01

α4

0.05 MPa–1

βn

0.0

βw

0.6

l0

10E-6 mρc

1E18 mm–3(22)

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

where l is the average value of grain-pair branch length
even for grains of similar composition and shapes
in the whole RVE. Using the same approach, the Cauchy d2 
 d2 
stress will also be derived in the integral form as 
(26)
E
E
and
G
G

 n  2  n 1  
 w  2  w 1  
d
d




1
1
π 2π
σ ij = l ρ c ∫ ∫ ( f i n j ) ξ sin θdθdφ(23)
where parameter β determines the relative scaling of grainθ =0φ =0pair initial (unloaded) stiffness coefficients depending on(26)
For more detailed description of the procedure used tograin-size.
Considering size-effect laws discussed in thetransform the summations into integration see (Misra A.
literature (Cordero N.M. et al., 2010; 2012; Fredrich J.T. etand(23)
Poorsolhjouy P., 2016c).
al., 1990), the numerical value of parameter β is expected
to be negative, that is the larger grains result in less stiff
2.3 Scaling laws for grain-size effectgrain-pair in comparison to smaller grains.
In addition, the complete force-displacement behavior
Let us consider two different granular materials whoseof a grain pair, particularly its failure behavior, will also beaverage grain sizes are d1 and d2, where without loss onscaled with the change of grain size. The following scaling
generality say d1 < d2, and the subscripts refer to the marelationships are introduced for those model parameters
terial type 1 and type 2. A set of size scaling relationshipsthat describe the relative displacement where the grain-pair
are hypothesized, inspired by the principles of renormalforces reach their peak
ization, to compare the two materials based upon physical d2 
 d2 


B
B
;
B
B








n 2
n 1
nc 2
nc 1  ;arguments. For example, it is reasonable to expect that the d1 
 d1 
average grain-pair branch length of material 2 is related to
(27)

d 
that of the material 1, through the following simple scalingBwo  2  Bwo 1  2  ; d1 
(in the subsequent equations (Eqs. 24–28) the subscripts 1
and 2 will refer to the two granular materials and are not
Based on experimental results in the literature, it istensor quantities)
evident that coarser grains show a more ductile behavior,(27) means they can store more energy. As a result, the
which
d 
l2  l1  2 (24)
damageparameter used in our model (in normal tension
 d1 
Bn, in normal compression, Bnc, and in tangential direction,
Similarly, the volumetric number density of grain-pairBwo) should be proportional to the grain size. That is, aginteractions, ρc, of the two types of granular materials
gregates of larger sizes will fail at a larger displacement.
(24)
can be related to each other through the following scaling
This implies that the size-effect parameter should have arelationshippositive value, γ > 0.
Fig. 3 presents an illustrative parametric study tod 
 c 2   c1  2 (25)
demonstrate
how the size-effect parameters influence the d1 
grain-pair behavior. The schematic curves in Fig. 3 present
Where the exponent, α, can vary widely depending notforce-displacement relationships for normal interaction of
only
grain-pairs, under tension, for varying grain-sizes and for(25)upon the average grain sizes but also the grain size
distributions as well as the packing density. The exponent,
varying size-effect parameters. The effect of the size-effectα, will also depend upon the problem dimension (that islaws on tangential interaction as well as the normal comwhether the granular material is a packing of 2D grains orpressive interactions is similar and not presented here for3D grains) and the grain geometry. For the ideal case of 3D
brevity. It is seen in Fig. 3a that negative β values lead to
packings of monodisperse spherical particles in a regular
stiffer behavior for smaller grains. It is also seen that byclosed-pack assembly, the exponent, α, will reach the lower
keeping β constant and increasing γ, smaller grains showbound of –3 (negative 3). It is evident that the value of thesmaller energy storage capacities and smaller failure stress.
exponent α should be negative since the volumetric number
Inversely, keeping β constant and increasing γ results indensity of grain-pair interactions is inversely related tolarger grains showing a more ductile behavior.
grain size. Calibrating the value will be complicated for
It is also observed (from both Figs. 3a and 3b) that for
random packings of cohesive particles with irregular gepositive values of γ, if γ = –β, smaller grains show larger
ometries and complex particle size distributions. However,stiffness, however, they fail at the same force value andsmaller displacement values compared to larger grains.
the exponent will be bound within the bound –3 < α < 0.
Further, the deformation behavior of grain-pair depends
Accordingly, larger grains have a more ductile behavior
not only upon the grain-shape, its surface characteristics
and a larger work of failure (more energy storage capacity)
as well as the cohesive mechanisms, but also on the size
which is in agreement with typical empirical observations
reported in the literature.
of the grain. While the grain size dependence of grain-pair
It is noted that here that the choice of parameter set
stiffness is complex, the following size scaling is expected199

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

Fig. 3 Parametric Studies: Investigating the effects of size-effect parameters on the behavior of contacts in normal tension. Force-displacement curves
for constant grain size and varying model parameters (a) and force-displacement curves for varying grain sizes with constant model parameters, (a).
Model parameters used in (b), β = –1 and γ = 1, are those used in the analysis. Normal interactions in tension are chosen as examples to show the effectsof size effect parameters on stiffness and damage.

for simulating the behavior of the specific material
investigated in this paper, was done by considering themacroscopic behavior of the material. At the macroscopic
level, combining (i) Eq. 20, which describes the mathematical form of the grain-pair stiffness coefficients as functionof the stiffness and damage parameters, (ii) Eq. 24, which
describes the effect of grain sizes on the magnitude of the
branch vector, and (iii) Eq. 26, which describes the effectof grain sizes on the volumetric number density of grainpair interactions and substituting them into Eq. 22 which
derives the macroscopic stiffness tensor, we can derive
the ratio between initial macroscopic stiffness tensor of amaterial with grain size of d2 to that of a material with grain
size of d1 as follows
  2
 2c 
kik n j nl  0  0


l2 

  ( ,  ) sin  d d Cijkl  2
2

 2


Cijkl 1l1 2 1c    kik n j nl   ( ,  ) sin  d d   0  0
1
2

2





d  d  d 
  2  2  2
 d1   d1   d1 

(28)
since
(28)the magnitude of the branch vector, l, is scaled linearly with size, volumetric number density of grain-pairinteractions, ρc, scales with grain size through exponent α,
and the initial stiffness coefficient of interacting grains at
the unloaded state is scaled by β. Accordingly, the initialmacroscopic stiffness tensor of a material with grain sized2 can be derived as a function of the stiffness tensor of thematerial with grain size of d1 as followsdCijkl  2  Cijkl 1  2 
 d1 

2   (29)

It should be noted that this simple close-form solution
is only available for the components of stiffness tensor at
(29)

200

the initial (virgin) state. Once the material is subjected toloading, every grain-pair will experience a unique historyof relative displacements according to its direction andtherefore its force-displacement relationship will be scaled
in a nonlinear manner dictated by Eq. 27. As a result, themacroscopic behavior, represented by the evolution ofmacroscopic tangent stiffness tensor, will be scaled bygrain size in a nonlinear fashion which depends on theloading path. In what follows, numerical results of the effects of changing grain size on the stress-strain behavior ofa specific granular material is presented to demonstrate theeffectiveness of the model and the scaling laws presented.

3. Results
Inspired by the experimental results presented in(Fredrich J.T. et al., 1990), the enhanced GMA basedmodel described in section 2 was applied to simulate theconventional triaxial behavior of cohesive granular materials for a range of grain sizes. The nominal grain sizes offor these simulations ranged from 0.02 m to 0.00001 m.
Furthermore, the confining pressure for these conventional
triaxial simulations ranged from 0.0 MPa to 400.0 MPa.
In these simulations, the parameter values used in ourprevious work on cohesive granular materials (Misra A.
and Poorsolhjouy P., 2015a; Poorsolhjouy P. and Misra A.,2017) are used (See Table 1).
Calibration of size-effect parameters was done by investigating their combined effect on the grain-scale behavior
as well as the macroscopic continuum level behavior. By
considering the physical meaning of each of the exponents,
as it was already discussed in Section 2.3, it is clear thatα < 0, β < 0, and γ > 0. However, the choice of the exact
value of the parameters is done based upon their combined effect in the overall behavior of the material and by
mimicking experimental results. In this paper, we calibratePayam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

model parameters based on the experimental results presented in (Fredrich J.T. et al., 1990). We first observe that,for the material under consideration, the initial stiffness
coefficients are inversely related to grain-sizes. Considering this and using Eq. 29, it is clear that for this material
we need to confine the size-effect parameters such that
2 + α + β < 0. However, it is also seen in (Fredrich J.T. etal., 1990) that this inverse relationship is not very strong
and therefore, |2 + α + β| should be a small number.
Once these the limits stated above are set, the calibrationof the exact values of the parameters, is done by comparing
the model results to the stress-strain curves for conventional
triaxial test under different confining pressures for materials with different grain sizes. Just like in the grain-scale(as shown in the parametric studies in Fig. 3), the effect ofsize-effect parameters on the macroscopic behavior of thematerial is also complicated. Accordingly, the choice of theparameters used in this study and for the material underconsideration (presented in Table 2) is done for deriving
an overall fit between the results. A detailed investigationof the influence of the various parameters remains a topic
for further research and investigation.
The simulated conventional triaxial compressive experiments are typically performed in two, sequential phases. In
the first phase, termed as the confinement phase, the material specimen is subjected to an incrementally increasinghydrostatic confinement to the desired confining pressure,
such that (σ11 = σ22 = σ33 = σconf). In the second phase, thematerial specimen is subjected to deviatoric loading byincrementally increasing the stress in the vertical direction.
In this deviatoric phase, the vertical strain, ε11, is increased
while the two horizontal stresses (σ22 and σ33) are kept
constant.
It is well known for cohesive granular materials that increasing confinement results in increasing the material tangential stiffness as well as the failure stress under triaxial
loading. The simulations described in this paper, show that
reducing grain-size can also result in increasing stiffness
and failure stress. For a clear visualization, the results ofthe triaxial compression simulations are categorized into
two cases: Case 1 for small confinements (0.0, 5.0, and
20 MPa), and Case 2 for large confinements (50, 100, 200,
and 400 MPa). This distinction has been made to highlightthe significant change in the nature of stress-strain relationship as the confinement becomes larger than a value lying
between 20 and 50 MPa. The different natures of the stress-

Table 2 Size effect parameters.

Size effect Parameters

Value (unitless)

α

–1.2

β

–1.0

γ

1.0

strain relationship are clear from the plots given in Figs. 4
and 5 for the two cases. In Fig. 4, we give the evolution of
the deviatoric stress, q = σ11 – σconf, as the applied verticalstrain, ε11, is increased for granular materials of different
grain sizes for the case of small confinements (< 20 MPa).
Further, in Fig. 5, we show the same set of results for
granular materials of different grain sizes for the case oflarge confinement (> 50 MPa). It is clear from Figs. 4 and5, that both the stiffness and strength increase as the grainsizes decrease. Moreover, this stiffening and strengthening
effects are greater at the higher levels of confinements asseen from Fig. 5.
More importantly, the results in Figs. 4 and 5 illustrate
the transition in the nature of stress-strain behavior from“brittle failure” to “ductile failure”. The observation that
failure behavior transforms from brittle to ductile withincreasing confinement is well-known from experiments(Bažant Z.P. et al., 1996; Mahboubi A. and Ajorloo A.,
2005; Sfer D. et al., 2002) as well as from simulations
using GMA that support the experimental results (Misra
A. and Poorsolhjouy P., 2015a). A clear peak in the
stress-strain relationship, defined by the point at which
the stiffness (slope of the stress-strain curve) reaches zero,
characterizes brittle failure. On the other hand, the lackof a peak but a clear change in slope of the stress-strain
curve characterizes a ductile failure. Granular materials
showing ductile response have a yield point (defined here
as the stress and strain point at which there is a significant
reduction in stiffness), followed by ideal plastic behavior ora hardening-type behavior.
As expected for a given grain size and changing confinement, the simulation results presented in Figs. 4 and
5 confirm the above observations. It is noteworthy, however, that the transition from brittle to ductile failure canalso be affected by decreasing the grain size for a given
confinement as explicated in both Figs. 4 and 5. Indeed,
if we examine the behavior for different grain sizes at
20 MPa confinement given in Fig. 4, we can observe thatfor grain sizes d > 0.0001 mm, there is a clear peak in the
stress-strain curves which implies a brittle failure. We notethat in this context, the term “brittle failure” signifies aloss of ability of the material to support additional stress.
The described “brittle failure” is distinct from the term
“brittle behavior”, which, as opposed to “ductile behavior”,
implies a low capacity to store energy (i.e. a low work of
failure). In contrast, for the same confinement (20 MPa), a“ductile failure” can be observed in Fig. 5 characterized bya yield point followed by strain-hardening for the material.
The transition between brittle and ductile failure happens
for material with smaller grain sizes of d ≤ 0.0001 at aconfining pressures between 5 MPa and 20 MPa (see Fig. 4
for d = 0.0001, 0.00002 mm and 0.00001 mm). For larger
grains, this transition is observed at confinement between
20 MPa and 50 MPa as seen from comparison of results in201

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

Fig. 4 Stress-Strain in Small Confinement: Evolution of the deviatoric stress, q = σ11 – σ 22, during triaxial loading (application of ε11) for initial confining pressures of 0.0, 5.0, and 20.0 MPa for all different grain sizes.

Figs. 4 and 5. This transition from brittle to “ductile failure” is also observed experimentally as seen in (Fredrich
J.T. et al., 1990).
The above observation can be further elucidated byinvestigating the evolution of failure stresses and yieldstresses with the grain-sizes. For the case of small confinements, we can identify a failure point as the peak of
the stress-strain curve. Fig. 6a gives a plot of the failure
deviatoric stress versus grain sizes for small confinements.
On the other hand, for large confinements, it is possible
to identify a yield deviatoric stress as the point of rapid
slope change of the stress-strain curve. In Fig. 6b, the yield
deviatoric stress is plotted against grain sizes for large
confinements.
For both the failure and yield stress we see a clear trendof inverse relationship with grain sizes from Figs. 6a202

and 6b. Interestingly, both failure stress and yield stressincrease proportionally with increasing 1/ d as a good
approximation (note the values of R-squared in the graphs).
It is remarkable that the same linear patterns describing the[72]on 1/ d has
dependency of the failure and yield values
been observed experimentally for granular geomaterials(Fredrich J.T. et al., 1990). The inverse relationship of[72] finite
yield stress with grain-size have been shown throughelement modeling using generalized continuum models(Cordero N.M. et al., 2012) as well as experiments (Jia D.
et al., 2003).
Finally, it is interesting to investigate the effect ofgrain-sizes on the evolution of lateral deformations during
triaxial tests. In Fig. 7, the evolution of volumetric strain(εv = εii = ε11 + ε22 + ε33) is plotted against the applied vertical strain, ε11, during the deviatoric phase. In these plots,

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

Fig. 5 Stress-Strain in Large Confinement: Evolution of the deviatoric stress, q = σ11 – σ 22, during triaxial loading (application of ε11) for initial confining pressures of 50, 100, 200, and 400 MPa for all different grain sizes.

the compressive volumetric stress is shown as positive as
is standard in granular mechanics. These results show that
increasing grain size (as well as increasing confinement)
result in a transition from dilation to compaction during
triaxial testing. Triaxial tests with low confinement experience compaction (compressive volume strain) over asmall interval of axial strain before transitioning to dilation(tensile volume strain). For larger confinement, however,the volumetric strain evolution tends towards compressive
region. In fact, for very large confinement, no dilation isobserved and the volume monotonically decreases as theloading progresses.
More importantly, these results show the clear effectof grain sizes on the volumetric strain evolution. As grain
sizes decrease, the volumetric strain evolves increasingly
to the tensile region. Indeed for the smallest grain size(d = 0.00001 mm) used in the simulations, the volumetricstrain if found to be tensile for all the simulated confinement levels. These results predict that granular materials
composed of small grains tend to be more dilative thanthose composed of large grains. Moreover, the dilative
behavior of small-grained materials appears to have limited
effect of confinement (particularly for the granular systemsimulated in this work). We note that in the present study,
the focus upon dense cohesive granular materials such as
rocks, concrete, and other cementitious materials, in which
the effect of initial density variation on the volumetricstrain is typically limited. It is noteworthy though that in
the present model the effect of initial porosity is incorporated within the parameters of grain-pair interactions.
Here, we have evaluated the effect of confining stresson volumetric strain for different grain sizes as shown in203

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

Fig. 6 Failure/Yield Stress vs. Size: Change of failure stress for lowly confined cases, σconf ≤ 20 MPa, and yield stress for highly confined cases, σconf> 20 MPa by change of grain size.

Fig. 7 Volumetric Strain Behavior: Evolution of volumetric strain during deviatoric loading for all different sizes and different initial confinements(0, 5, 20, 50, 100, 200, and 400 MPa). Curves for higher confinements (50 MPa to 400 MPa are too close to distinguish). Note that in these plots compression is taken as positive.

Fig. 7. The effect of initial porosity can also be evaluatedfor similar materials with varying initial porosities.

4. Summary and conclusions
The described work represents an effort to systematicallyinvestigate the influences that grain-sizes have upon themacro-scale or collective response of granular systems
with very large number (> 106) of grains. It was shown that204

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

the GMA based model for damage and plasticity of cohesive granular materials, which was previously derived andvalidated by the authors, can be enhanced to incorporate
the effects of grain size. To this end, a micromechanicalviewpoint is utilized to implement the grain-size effect. The
set of scaling laws was incorporated into the GMA basedmodel. These include scaling laws for: volume density ofgrain-pair interactions, grain-pair branch lengths, grainpair elastic stiffness in normal and tangential directions,and the grain-pair damage parameters in normal andtangential directions. In the presented modeling approach,these microscopic (grain-scale) scaling laws are found toprofoundly influence the macro-scale stress-strain responseof a granular system.
The derived model is applied to simulate triaxial compressive tests for cohesive granular materials for a rangeof grain sizes and confinements. The simulation results
demonstrate that reduction in grain size results in a stiffer
stress-strain behavior, a transition from brittle to ductile
type of failure characterized by peak or yield points in the
stress-strain curves, and an increase in the failure and yieldstresses. These effects, in some ways, mirror the behaviorof granular materials for a given grain-size with change
in confinement. It is remarkable, therefore, that changeof grain-sizes show similar variation in the material macro-scale behavior. Furthermore, the volumetric behaviorof the samples are also seen to depend, in addition to theamount of initial confinement, on the grain sizes. Samplesof smaller grain sizes demonstrate more tendency towards
dilation (tensile volume strain) compared to samples oflarger grain sizes. At very small grain sizes, no amount ofcompaction is sufficient to keep the volumetric strain incompressive domain. Future work will consider further
details of the effect of grain-size on deformation and failure
mechanism of granular system, including the formation ofshear, compression-tension or mixed-model localization
bands and their orientation with respect to the loading
directions.

Acknowledgements
This research is supported in part by the United States
National Science Foundation grant CMMI-1068528 andCMMI-1727433

Nomenclature
Bn, Bw

damage parameters in the normal and tangential
directions

Cijkl

fourth rank stiffness tensor

d1, d2

grain-sizes

Di , D n , D w

grain-pair damage vector and normal and tangential components

Dijcontinuum damage tensor

En

normal stiffness parameterf i , fn , f w

grain-pair force vector and normal and tangential
components

Gwtangential stiffness parameterkij, kn, kw

grain-pair stiffness tensor and normal and tangential components

li , lgrain-pair branch vector and branch lengthniunit vector in the direction of grain-pair branch
vectorN

total number of grainNctotal number of grain-pair interactions

R

compression-tension ratiosiunit vector on the plane orthogonal to grain-pairbranch vector forming

tiunit vector on the plane orthogonal to grain-pairbranch vector forming

W, Wn, Ww

macro-scale, normal and tangential grain-pair
Helmholtz free energy densityYgeneralized force conjugate to grain-pair damage

Z

generalized force conjugate to grain-pair plastic
displacements

αsize scaling parameter for grain-pair volumetricnumber density

α1, α2, α3, α4model parameters controlling damage

βsize scaling parameter for grain-pair initialstiffnessγ

size scaling parameter for grain-pair damage
parametersδi , δ n , δ w

grain-pair displacement vector and normal andtangential components

εij

infinitesimal strain tensor

ϕspherical coordinate

σij

Cauchy stress tensor

θspherical coordinateψ, ψn, ψwmacro-scale, normal and tangential grain-pairdissipation potential

ReferencesBažant Z.P., Xiang Y., Adley M.D., Prat P.C., Akers S.A., Microplane model for concrete: II: data delocalization and verification, Journal of Engineering Mechanics, 122 (1996) 255–262.
DOI: 10.1061/(ASCE)0733-9399(1996)122:3(255)
Chang C.S., Misra A., Packing structure and mechanical-propertiesof granulates, Journal of Engineering Mechanics, 116(1990) 1077–1093. DOI: 10.1061/(Asce)0733-9399(1990)

205

Payam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

116:5(1077)
Cordero N.M., Forest S., Busso E.P., Generalised continuum
modelling of grain size effects in polycrystals, Comptes
Rendus Mécanique, 340 (2012) 261–274. DOI: 10.1016/j.
crme.2012.02.009
Cordero N.M., Gaubert A., Forest S., Busso E.P., Gallerneau
F., Kruch S., Size effects in generalised continuum crystal
plasticity for two-phase laminates, Journal of the Mechanics
and Physics of Solids, 58 (2010) 1963–1994. DOI: 10.1016/j.
jmps.2010.06.012
dell’Isola F., Maier G., Perego U., Andreaus U., Esposito R.,
Forest S., The complete works of Gabrio Piola: Volume I:
Commented English Translation-English and Italian Edition,
Springer International Publishing, 2014, ISBN: 978-3-31900262-0
Digby P.J., The effective elastic-moduli of porous granular rocks,
Journal of Applied Mechanics-Transactions of the ASME, 48(1981) 803–808. DOI: 10.1115/1.3157738
Duffy J., Mindlin R.D., Stress-strain relations and vibrations of a
granular medium, Journal of Applied Mechanics, 24 (1957)
585–593.
Eugster S.R., dell’Isola F., Exegesis of the introduction and
Sect. I from “Fundamentals of the Mechanics of Continua”
by E. Hellinger, ZAMM—Journal of Applied Mathematics
and Mechanics, 97 (2017) 477–506. DOI: 10.1002/zamm.
201600108
Fredrich J.T., Evans B., Wong T.F., Effect of grain-size on brittle
and semibrittle strength—implications for micromechanicalmodeling of failure in compression, Journal of GeophysicalResearch-Solid Earth and Planets, 95 (1990) 10907–10920.
DOI: 10.1029/JB095iB07p10907
Giorgio I., Scerrato D., Multi-scale concrete model with
rate-dependent internal friction, European Journal of Environmental and Civil Engineering, 21 (2017) 821–839. DOI:
10.1080/19648189.2016.1144539
Gonzalez M., Cuitino A.M., A nonlocal contact formulation
for confined granular systems, Journal of the Mechanics
and Physics of Solids, 60 (2012) 333–350. DOI: 10.1016/j.
jmps.2011.10.004
Hara G., Theorie der akustischen Schwingungsausbreitung in
gekornten Substanzen und experimentelle Untersuchungen
an Kohlepulver, Elektrische Nachrichten Technik, 12 (1935)
191–200.
Hentz S., Daudeville L., Donze F.V., Identification and validation of a discrete element model for concrete, Journal ofEngineering Mechanics-Asce, 130 (2004) 709–719. DOI:
10.1061/(Asce)0733-9399(2004)130:6(709)
Jia D., Ramesh K.T., Ma E., Effects of nanocrystalline and ultrafine grain sizes on constitutive behavior and shear bands iniron, Acta Materialia, 51 (2003) 3495–3509. DOI: 10.1016/
S1359-6454(03)00169-1
Jia H., Misra A., Poorsolhjouy P., Liu C., Optimal structural
topology of materials with micro-scale tension-compression
asymmetry simulated using granular micromechanics,
Materials & Design, 115 (2017) 422–432. DOI: 10.1016/j.
matdes.2016.11.059
Mahboubi A., Ajorloo A., Experimental study of the mechanicalbehavior of plastic concrete in triaxial compression, Cement
and Concrete Research, 35 (2005) 412–419. DOI: 10.1016/j.
cemconres.2004.09.011
Misra A., Chang C.S., Effective elastic-moduli of heterogeneous
granular solids, International Journal of Solids and Structures,
30 (1993) 2547–2566. DOI: 10.1016/0020-7683(93)90165-4
Misra A., Ching W.Y., Theoretical nonlinear response of complex
single crystal under multi-axial tensile loading, Scientific

206

Reports, 3 (2013) 1488. DOI: 10.1038/srep01488
Misra A., Nejadsadeghi N., De Angelo M., Placidi L., Chiralmetamaterial predicted by granular micromechanics: verified
with 1D example synthesized using additive manufacturing,Continuum Mechanics and Thermodynamics, (2020) DOI:
10.1007/s00161-020-00862-8
Misra A., Placidi L., Turco E., Variational methods for discretemodels of granular materials, in: Altenbach H., Öchsner A.
(Eds.), Encyclopedia of Continuum Mechanics, Springer
Berlin Heidelberg, Berlin, Heidelberg, 2018, pp. 1–14,
ISBN: 978-3-662-53605-6. DOI: 10.1007/978-3-662-536056_172-1
Misra A., Placidi L., Turco E., Variational methods for continuum
models of granular materials, in: Altenbach H., Öchsner A.
(Eds.), Encyclopedia of Continuum Mechanics, Springer
Berlin Heidelberg, Berlin, Heidelberg, 2019, pp. 1–11,
ISBN: 978-3-662-53605-6. DOI: 10.1007/978-3-662-536056_343-1
Misra A., Poorsolhjouy P., Granular micromechanics modelfor damage and plasticity of cementitious materials
based
upon
thermomechanics,
Mathematics
andMechanics of Solids, (2015a) 1081286515576821. DOI:
10.1177/1081286515576821
Misra A., Poorsolhjouy P., Identification of higher-order elastic
constants for grain assemblies based upon granular micromechanics, Mathematics and Mechanics of Complex Systems, 3(2015b) 285–308. DOI: 10.2140/memocs.2015.3.285
Misra A., Poorsolhjouy P., Elastic behavior of 2D grain packing
modeled as micromorphic media based on granular micromechanics, Journal of Engineering Mechanics, 143 (2016a)
C4016005. DOI: 10.1061/(ASCE)EM.1943-7889.0001060
Misra A., Poorsolhjouy P., Granular micromechanics based
micromorphic model predicts frequency band gaps, Continuum Mechanics and Thermodynamics, 28 (2016b) 215–234.
DOI: 10.1007/s00161-015-0420-y
Misra A., Poorsolhjouy P., Granular micromechanics model ofanisotropic elasticity derived from Gibbs potential, Acta
Mechanica, 227 (2016c) 1393–1413. DOI: 10.1007/s00707016-1560-2
Misra A., Singh V., Nonlinear granular micromechanics model
for multi-axial rate-dependent behavior, International Journalof Solids and Structures, 51 (2014a) 2272–2282. DOI:
10.1016/j.ijsolstr.2014.02.034
Misra A., Singh V., Thermomechanics-based nonlinear ratedependent coupled damage-plasticity granular micromechanics model, Continuum Mechanics and Thermodynamics, 27(2014b) 787–817. DOI: 10.1007/s00161-014-0360-y
Nejadsadeghi N., Misra A., Extended granular micromechanics
approach: a micromorphic theory of degree n, Mathematics and Mechanics of Solids, 25 (2020) 407–429. DOI:
10.1177/1081286519879479
Placidi L., Barchiesi E., Energy approach to brittle fracture instrain-gradient modelling, Proceedings of the Royal Society
A: Mathematical, Physical and Engineering Sciences, 474(2018) 20170878. DOI: 10.1098/rspa.2017.0878
Placidi L., Barchiesi E., Misra A., A strain gradient variational
approach to damage: a comparison with damage gradientmodels and numerical results, Mathematics and Mechanicsof Complex Systems, 6 (2018a) 77–100. DOI: 10.2140/
memocs.2018.6.77
Placidi L., Misra A., Barchiesi E., Two-dimensional strain gradient damage modeling: a variational approach, Zeitschrift fürangewandte Mathematik und Physik, 69 (2018b) 56. DOI:
10.1007/s00033-018-0947-4
Poorsolhjouy P., Misra A., Effect of intermediate principal stressPayam Poorsolhjouy et al. / KONA Powder and Particle Journal No. 39 (2022) 193–207

and loading-path on failure of cementitious materials using
granular micromechanics, International Journal of Solids
and Structures, 108 (2017) 139–152. DOI: 10.1016/j.ijsolstr.
2016.12.005
Poorsolhjouy P., Misra A., Granular micromechanics based continuum model for grain rotations and grain rotation waves,
Journal of the Mechanics and Physics of Solids, 129 (2019)244–260. DOI: 10.1016/j.jmps.2019.05.012
Qomi M.J.A., Krakowiak K.J., Bauchy M., Stewart K.L.,
Shahsavari R., Jagannathan D., Brommer D.B., Baronnet
A., Buehler M.J., Yip S., Ulm F.J., Van Vliet K.J., Pellenq
R.J.M., Combinatorial molecular optimization of cement
hydrates, Nature Communications, 5 (2014) 4960. DOI:
10.1038/ncomms5960
Sfer D., Carol I., Gettu R., Etse G., Study of the behavior of
concrete under triaxial compression, Journal of Engineering

Mechanics-Asce, 128 (2002) 156–163. DOI: 10.1061/(Asce)0733-9399(2002)128:2(156)
Tavarez F.A., Plesha M.E., Discrete element method for modelling solid and particulate materials, International Journal
for Numerical Methods in Engineering, 70 (2007) 379–404.
DOI: 10.1002/nme.1881
Turco E., dell’Isola F., Misra A., A nonlinear Lagrangian particle
model for grains assemblies including grain relative rotations, International Journal for Numerical and Analytical
Methods in Geomechanics, 43 (2019) 1051–1079. DOI:
10.1002/nag.2915
Walton K., The effective elastic-moduli of a random packing of
spheres, Journal of the Mechanics and Physics of Solids, 35(1987) 213–226. DOI: 10.1016/0022-5096(87)90036-6
Ziegler H., An Introduction to Thermomechanics, 2nd edition,
North-Holland, Amsterdam, 1983, ISBN: 9780444598936.

Authors’ Short Biographies
Payam Poorsolhjouy
Payam Poorsolhjouy is an Assistant Professor in the Chair of Applied Mechanics at Eindhoven
University of Technology. His research interest is multiscale modeling and design of materials withcomplicated microstructure. He received his PhD in Civil Engineering with honors and as the Outstanding PhD graduate of the School of Engineering, from University of Kansas in 2016. He thenjoined Purdue University as a PostDoc working on multiscale material modeling. Prior to joining
TU/e he was a University Assistant at Graz University of Technology. He has co-authored multiple
journal papers and presented his research in various national and international conferences.

Anil Misra
Anil Misra is Professor of Civil Engineering and Associate Director of the Bioengineering
Research Center at the University of Kansas, Lawrence. He has more than 30 years of experiencein the area of multi-scale modeling, constitutive behavior of interfaces, granular soils and cement/asphalt concrete, and multi-modal material characterization using high-resolution techniques. He has
pioneered the method of granular micromechanics. He has co-edited four books, guest edited fivejournal special issue, and authored more than 300 papers in journals, edited books and conference
proceedings. He serves as a reviewer for multiple journals, extramural funding agencies and provides
consulting services to industry.

207

KONA Powder and Particle Journal No. 39 (2022) 208–218/https://doi.org/10.14356/kona.2022013

Original Research Paper

Verification of Polyhedral DEM with Laboratory Grinding
Mill Experiments †Alberto M. Puga 1, Nicolin Govender 2,3 and Raj K. Rajamani 1*
1 Department of Material Science and Engineering, University of Utah, USA

2 Department of Mechanical Engineering, University of Johannesburg, South Africa
3 Research Center Pharmaceutical Engineering GmbH, Austria

Abstract
The simulation of grinding mills with the discrete element method (DEM) has been advancing. First, it emerged asa method for studying charge motion with spherical balls and predicting the power draw of the mill. Subsequently,
studies on liner wear, charge motion with ellipsoidal and polyhedral shaped particles simulated with three
dimensional DEM followed. Further, the impact energy spectra computed in the DEM algorithm is leading to thedevelopment of models for the breakage of brittle particles in mills. The core elements in such simulations are theshape of particles in the mill charge and the power draw of the mill due to operating variables. To advance thefield, we present a set of experimental data and the corresponding DEM validation results for a 90 × 13 cm mill.
The DEM algorithm uses the volume-overlap method which is more realistic for multifaceted irregular particle
collisions. Further, we use the scanned shape of the rock media and multifaceted spherical shape for the grinding
media to represent as close as possible the actual charge in the mill. First, we present DEM validation for spherical
grinding media-only experiments, rock-only experiments, and a mixture of spherical grinding media and rocks, aswell as aluminum cubes only to represent the theme of particle shape. Finally, a discussion of the contact mechanics
parameters in the four modes of experiments is given. Since the feed ore to plant scale mills can vary in shape, millsimulations with scanned shape of typical particles are the future for more accurate results.
Keywords: DEM, discrete element method, polyhedral, simulation

1. Introduction
In hard rock mining and metal production, the grinding
unit operation follows stages of crushing mined ore. Naturally, occurring ores contain metal-bearing minerals. The
purpose of grinding is to liberate metal-bearing mineral
grains from the host particles. Next, the valuable mineralparticles are recovered in subsequent processes. Since thegrade of metal values in ores is in the range of one percent
or less, thousands of tons of ore are milled every hour. As
a result, the grinding mills are massive in size requiring a
few megawatts of power to operate. Being such an energy
consuming operation, grinding mills have been studied byresearchers around the world to improve energy efficiency.
Since the mills are massive in size, the tumbling environment inside the mill is very harsh, defying any attempt at
quantifying the charge dynamics with sensors. However,†*Received 10 March 2021; Accepted 16 June 2021
J-STAGE Advance published online 7 August 2021
Corresponding author: Raj K. Rajamani;
Add: William Browning Bldg, Salt Lake City, UT 84112, USA
E-mail: albertopuga15@gmail.com
TEL: +1-801-581-3107

208

laboratory-scale experiments have been done tactfully toprovide information on power draw and charge profiles ofmaterial inside the mill. One of the critical needs in millingis to understand charge flow inside the cylindrical millshell. Since the internal forces produced inside the charge
mass are the cause for particle size reduction, this study has
fallen under the realm of the numerical methods known as
the Discrete Element Method (DEM) (Tavares et al., 2020).
It provides a direct numerical simulation of the motion of
thousands of particles tumbling inside the cylindrical millshell, and besides, the forces acting on the particles can beused to model particle breakage. Djodjeric et al. (2006)
studied the competency of large pieces of rocks in an AG
mill with DEM. They presented charge pressure due tonormal forces acting on the bed of rock to account for the
breakage or non-breakage of rocks.

1.1 Grinding mills
Almost every mining plant operation employs eithera Semi-autogenous (SAG) or Autogenous (AG) mill,followed by ball mills. Since SAG and AG mills are capable of performing the size reduction of one or two-stage

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

crushing size reduction circuits, they are found extensively
in many mineral ore processing operations. The product of
SAG or AG mills is represented by size, called “transfersize”, which is in the range of few millimeters. Material
contained in these sizes is suitable for further size reduction
in ball mills to a size of 100–200 μm. Typical SAG mills
are 9–12 m in diameter. The top size of feed ore to SAG/
AG mills is around 10–35 cm. These mills usually operatewith a screen deck at the discharge end to recycle thecoarse portion of the material back into the mill.
AG mills take advantage of the weaker competence ofthe ore to break them. The ore particles impact directlyagainst the mill shell and break readily. This mode ofbreakage is called self-breakage, and only a few ore
deposits around the world are amenable for breakage in
AG mills. In SAG mills, in addition to self-breakage, thegrinding balls due to their greater density add to ball-torock impact breakage. Besides these two major modes ofimpacts, the grinding action includes attrition grinding or
chipping of sharp edges. The entire system of grinding
modes is influenced by design factors such as liners, lifters,
grate opening, operating conditions (mill filling and speed),and ore hardness.

1.2 DEM simulation of grinding mills
It is apparent from the foregoing that real-world particles
are irregular in shape. However, early numerical DEM
studies began with spherical shapes, partly because they
are the easiest to model collisions numerically (Mishra andRajamani, 1990; 1992; Cleary, 2001; Cleary et al., 2003;
Morrison and Cleary, 2004). Although, researchers in the
DEM field recognized the importance of particle shape,
yet the cost of computational time-restricted them to basic
spherical shape and its close variants. The earliest of thesewere shapes generated with superquadrics algebra. During
milling, particles with high angularity lose their sharp edge
readily mainly due to chipping and abrasion, not to mention
these sharp edges are the weakest in the modes of breakage.
Hence, superquadrics in a preliminary sense were well
adapted to simulate such rounded particles. Rothenburg
and Bathurst (1991) presented a DEM algorithm for contact detection and collision of elliptical particles in the simulation of micromechanics of granular assemblies. Hopkins
et al. (1991) used polygonal shape particles to create a
two-dimensional of rocks and sea ice blocks to simulate
the formation of multilayers floes. Potapov and Campbell(1996) created a three-dimensional technique to simulate
the brittle solid fracture by “gluing” together convex
polyhedral particles. Realizing the need for non-sphericalshapes in DEM, Latham et al. (2008) published a libraryof three-dimensional shapes. Cleary (1998) was the firstauthor to introduce superquadrics for the DEM simulationof grinding mills. This author (Cleary, 1998) described thesimulation of a 5-m diameter ball mill in detail including
particle segregation, collisional force distributions, andliner wear. Delaney et al. (2010) went a step further using
superquadrics in the simulation of particle breakage incomminution processes: a set of smaller particles were
packed inside a superellipsoid, and the superellipsoid wasmade to break upon experiencing a certain energy limit
releasing the smaller particles representing the breakage ofthe larger ellipsoid. Besides the spherical grinding media
in ball mills, a shape termed “cylpebs” was developed to
produce improved media packing in the tumbling millcharge. Kiangi et al. (2013) used DEM simulation sphericaland multi-faceted polyhedron shapes to predict the loadand power draw in a pilot-scale mill filled with spheres andcylpebs. Xu et al. (2019) using the superellipsoid particle
model studied the effect of spherical and cuboidal particles
on the wear of a mill. Realistic DEM simulations of plantsize grinding mills require particle filling in the millions.
Govender et al. (2015) showed how graphic processing
unit (GPU) computation can speed up 3D DEM simulationof mill charge. The framework for such high-performancecomputing is described in Govender et al. (2016). This wasfollowed by the introduction of irregular shaped particles
such as scaled hexagonal prisms, truncated tetrahedra,
cubes, and other shapes in GPU-based DEM computing.
Govender et al. (2018a) presented the grinding mill simulation of regular polyhedral particles such as cube, tetrahedra,hexagonal prism, Biluna, and mixed polyhedral particles.
This study investigated the role of particle angularity andaspect ratio on power draw. In particular, the normal andshear energy dissipation components on the power draw
were shown to differ depending on the shape of the particle.
Particle shape and angularity contribute to interlocking andshear slippage between particles (Govender et al., 2018b)
for the study of particle mixing. The next logical choicefor irregular particles was a cluster of spheres or clumped
spheres. Like superquadrics, this object too was amenable
to easier collision detection (Latham et al., 2008), since atthe time of contact only a pair of spheres in the outermost
periphery of colliding objects are involved. Hence, theproblem reverts to spherical particle collision. This clusterof spheres particles model is adopted in the commercial
software EDEM (2011).
There have been numerous studies of DEM applied tothe simulation of grinding mills. Some have even appliedsmoothed particle hydrodynamics (Cleary et al., 2006;2008) to describe the motion of ore particle slurry alongwith the motion of larger DEM particles. The single mostadvance in DEM modeling of grinding mills is the use ofcollision energy spectra (number of collisions of an energy
class versus collision energy) to predict the breakage
rate of brittle ore particles (Tavares and Carvalho, 2009).
Tavares and Carvalho (2009) described the breakage
rate of coarse particles taking into account direct impact

209

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

breakage of particles by grinding media as well as theweakening of particles by repeated collisions. In a review
paper on this subject, Tavares (2017) describes the evolution of microscopic particle breakage rate models fromthe 1980s to recent advances such as the detailed modelsof breakage probabilities as a function of impact energy,
body and surface breakage, mass of powder caught ineach collision, weakening or damage of particles due torepeated collisions, and the incorporation of these models
in DEM. In this manuscript, we present a DEM simulationof non-spherical or polyhedral shaped particles tumbling ina laboratory-scale mill. In particular, the scanned polyhedral shapes of rock particles are used in DEM simulation.
This study demonstrates that mill power draw can bemodeled directly with a mixture of spherical and polyhedral particles. Laboratory-scale measurements of powerand captured images of charge motion are compared with
DEM simulation done with Blaze-DEM GPU framework
software. The method of modeling irregular particles ispresented followed by experimental and simulated results.
The novelty of this study lies in the fact that the introduction of real rock shapes mixed in with spheres allows
improved charge motion representation in DEM simulationof grinding mills. We show the actual scanned polyhedra
shapes can lead to accurate prediction of the power draw
and charge motion in the tumbling mill. This work paves
the way forward for the simulation of plant scale SAG/AG
mills using actual large rock shapes passing through thesemills.

2. DEM Computing
The simulation of few thousands of particles in DEM
is relatively less cumbersome and can be done readily insingle-core central processing units (CPU). For hundredsof thousands of particles, parallel computing on multi-coreCPUs can be done in a reasonable time frame. However,when millions of particles are simulated, it takes several
days of computing for a mere 1 second of real-time on
CPUs. Hence, the next step in the development of the DEM
framework is the use of graphic processor unit (GPU)computing that has become readily available in the last ten
years and which is going to increase in popularity due tomany software advances. Today’s GPU offers 24–48 GBof memory and hence handling millions of particles is not
a problem. However, DEM requires more severe memorytransactions compared to mere numerical computations.
These transactions become an order of magnitude higher
when computing with polyhedral particles with the numberof faces as large as thirty-two. Hence, DEM algorithms
must be extremely efficient even with GPU computing.

210

2.1 Blaze-DEM framework
Blaze-DEM is a GPU-based computational framework
for the discrete element methodology (Govender et al.,2016). The evolution of this code has been described inprevious publications and we present a few details about
the simulation results here. The first feature is that the simulation object geometry can be represented using typicalCAD geometry (STL format). This feature is especially
useful in importing, for simulation, mill geometry with liners, lifters, grate plates, and pulp lifters in STL format. The
code implements “world” objects, to indicate the process
vessel under simulation, in this case, a primitive cylinder.
Besides, the world object accommodates STL files depicted
in triangulated geometry. Next, volume objects in the code
can accommodate liners, lifters, grate plates, and pulp
lifters. Finally, the material object includes steel spheres
and rock particles of different shapes and solid densities.
These objects are represented as convex polyhedral shapes
joined by planes.
Contact detection is a key feature of DEM. The usualapproach is to compute the distance between the center ofmass of two colliding objects comparing it to the distance
between the two foremost colliding surfaces. Blaze-DEM
uses a unique approach named “ray-tracing” in which independent rays (computational threads) are projected fromeach vertex of polyhedron or center of mass of spheres
to check if there is contact with the other surfaces. The
ray-tracing algorithm is common in computer graphics.
This approach is very convenient to detect contact between
two polyhedra since polyhedron is just a collection of
surfaces. More details of contact detection involving broad
phase, narrow phase, and detailed phase of contact detection are found in Govender et al. (2018).

2.2 Contact mechanics
The mechanics used in the collision between two polyhedra is much different from that commonly used in a pairof colliding spheres. With spheres, the virtual penetration
distance is the primary quantity from which forces are
estimated in various ways. Herewith polyhedra, the forces
are calculated from overlapping volumes (Govender et al.,2018). The advantage of contact volume is that both thedirection and magnitude of forces can be resolved withan energy-conserving contact scheme (Govender et al.,2019). The contact scheme is illustrated with a cube and apolyhedral particle colliding with a larger cube, shown in
Fig. 1. The intersecting volume is a convex hull formed by
the vertices at the intersections between the cube’s edges
and polyhedron surfaces.
Computing the volume of a convex hull, with a computationally efficient algorithm is not a trivial task. The detailsof volume computing are given in Govender et al. (2018a;

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

Fig. 1 Intersecting vertices of overlap and volume overlap between
cubes and polyhedron.

2018b; 2018c). First, the bounding surfaces and theirrespective normal are determined. Using Green’s theorem,
the triple integral of the volume is computed with double
integration as a summation over the computed areas.
The simulation shown here involves a few hundreds ofpolyhedral rock particles and multifaceted steel spheres. As
detailed above, even for a few hundred particles, contact
detection, and computing intersecting volume becomesan intensive computational task. Besides, the simulations
were carried out for eight complete revolutions of the millcylinder. These computations took a few hours of computing time with an Intel Core i7-6850K 3.6 GHz with an
NVIDIA GeForce RTX 2060 GPU.
Normal Contact: The well-known linear viscoelastic
spring dashpot model is found to reproduce grinding millresults (Rajamani et al., 2000). The spring force that storesenergy and the dissipative force that dissipates energy are
given by Eqn. (1) and Eqn. (2), respectively.
1

Fn spring  (K n Δν 3 )nˆ(1)

Fn dash  Cn VR nˆ nˆ

(2)

where
(1) Kn is the spring stiffness ( ms ), n̂ is the normal
direction along which the force acts, Cn is the damping(2)
coefficient( Ns ), ν is the intersecting volume and VR ism
the relative velocity between contacting (22)polyhedra. In the(21)
simulation results presented here following refinement ofspring constant Kn and dashpot constant Cn were used.
(23)
meff
Kn  2ln(ε) 2 + π 2(3)t contactCn (3)2ln ε K n meff
2(4)ln ε + π 2

Ft spring  K t Vt Δt +Ft '(6)

Ftdashpot  min C tVt , μFnspring+dashpot  +Ft '

(7)

(6)

where Ft ' is the tangential force existing in the contact
at the previous time step, but projected onto the current(7)
tangential
plane and Vt is the relative tangential velocity.
It should(24)be mentioned implementing history dependence
in GPU architecture is a formidable task since contact detection among millions of particles is done with a hashingalgorithm. It is nearly impossible to synchronize a particular previous instant contact with the current one in hashingalgorithms.
Power Calculation: The verification of DEM prediction
for grinding mills relies on mill power prediction. In addition, a comparison of the experimental charge profiles withsimulated profiles offers additional proof. Unfortunately,
measurement of stresses on mill shells or lifters is only possible under very particular conditions in the laboratory andpilot-scale mills. The total energy consumed in a collision
is simply the energy dissipated in the numerous collision
events. Therefore, the power is calculated by summing all
the dissipated energy over one full revolution of the mill,
given by Eqn. (8).
k

1

(8)

E  i (F dashpot Δx)

The Fdashpot force defined in Eqn. (2) and Eqn. (7),respectively, and ∆x refers to the distance over which the(8)dissipative
force acts in each collision. In this intersecting
1
volume approaching ∆x in the value Δν 3 . Finally, the estimated power is given by Eqn. (9).
E

(9)

P
t rev

where ϵ is the coefficient of restitution, and meff is the effective(4)mass of colliding bodies, which is given by Eqn. (5).
1  1meff  
+

m
m
 1
2 

‘break contact’ or terminate contact calculations when thenormal force changes direction and is turned inward toward
the contact. However, by limiting the contact time, conservation of energy is maintained. Contact time is usuallychosen as multiples of computational time steps dependingon the properties of the pair of materials in contact.
Tangential contact: Although there are many variationsof the spring-dashpot model for tangential contact, the best
one that produces consistent mill simulation results in thehistory-dependent tangential contact proposed by Cundall
and Strack (1979). The current time step tangential force iscalculated by Eqn. (6) and Eqn. (7).

(25)

where trev is the time for one revolution. It is customary to
run the simulation to about eight revolutions and take the(9) power over the last few revolutions.
average(5)

The common practice in contact force calculations is to%%%%%%%%%%%%%%%%%%%%(5)211

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

3. Experiment work and Blaze-DEM
validation
In this paper, we validate the volume-based polyhedral
contact model with a history-dependent tangential model
via experiments in a tumbling mill. First, we show thevalidation for the mill running with spherical steel balls,
next with rocks, and finally with a mixture of steel balls androcks. In addition, an experiment with aluminum cubes isalso included for model validations.

3.1 Experimental setup
We used a laboratory-scale slice of a mill fitted witha clear plexiglass front plate for capturing the motion of
the charge with a camera. The mill is 90 cm in diameterand 13 cm in internal length (15 cm including front andback plates). The mill is fitted with eight square lifters
with a cross-section of 4 × 4 cm. The grinding media were
5.08 cm steel balls of density 7859 kg3 . The irregular oremparticles had a length dimension in the range of 3 and 5 cm
and a height dimension in the range of 3 and 4 cm. The millis fitted with a torque sensor on the drive shaft attached to(26)

the cylinder to measure the power drawn by the charge.
Thus, the energy losses in the electric motor, are avoided.
Ore particles: Rocks from a local quarry were used inthese experiments. These rocks were chosen for their highhardness because they did not break during experiments
retaining the integrity of their shape. To characterize theshape of the rocks, four rocks were chosen randomly,
shown in Fig. 2. Although it is possible to map the threedimensional shape with laser scanners, we needed to havefewer faces in the polyhedral representation. Otherwise,
the simulation would take unusually long compute times.
The rocks were placed in a three-dimensional graduatedcardboard axis frame. First, the rocks were triangulatedwith a pen as well as possible. Next, the x, y, and z coordinates were measured with a ruler and the axis frame.
Finally, the polyhedral particle was reconstructed in CAD
software. We only expect to get an approximate polyhedron representation of the rock’s shape. Fig. 2 shows thereconstructed polyhedral shapes. It is our view that a muchhigher shape resolution is not necessary for tumbling mill
predictions. These shapes are referred to as PolyA, PolyB,
PolyC, PolyD, PolyE, and PolyF in the simulations. The
kg
measured density of the rock was 2636 m 3 . Grinding
balls: The diameter of the balls was 2 in and only one single
size was used in all the experiments.

(26)

4. Experimental results and DEM validation

Fig. 2 Four random rock particles a, b, c, and d on the left, and theirpolyhedral representation on the right.

212

As a prelude to experimental results in milling, it isuseful to understand the general picture of the charge shapeinside the mill. Due to the presence of lifters, the charge incontact with the mill shell moves at the same velocity as themill shell except for slippage of charge in between the lifters. The particles leaving from the shell at the shoulder ofthe mill executed a parabolic trajectory. These trajectories
meet the mill shell on the other side of the mill. To describe
different locations on the mill shell, we use the ubiquitousmathematical notation depicted (on Fig. 3) of angle increasing counterclockwise from the x-axis, reaching 90° at
the positive y-axis, and gradually increasing to 180° at thenegative side of the x-axis followed by 270° at the negative
y-axis, where the mill’s center is the origin for the x-axis
and y-axis frames. At a higher percentage of critical speeds,
the particles leaving the shoulder may strike in the vicinityof 180° or even higher at 150°.
The fully cascading charge shape has a bi-linear shapefor the free surface above the charge. The free surface starts
in between 210° and 240° marks, termed “toe”, rising at
a shallow angle, to the inflection point near the center ofthe mill, and then the charge rises steeply to the shoulder
position, which is around 30° to 60° mark. This profile isentirely directed by the mill filling volume. Between themill shell and charge surface, there is a layer travelingAlberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218
Table 1 Simulation parameter for Case 8, P2P indicates particle-particle
and P2W indicates particle-wall settings.

Parameter

Symbol Value

Unit

Normal Particle StiffnessKn

4 × 106

N/m

Tangent Particle StiffnessKt

3 × 106

N/m

Damping Coefficient

C

0.01

Coefficient of Restitution (P2P)

ε

0.85

Static Friction (P2P)

μs

0.7

Kinetic Friction (P2P)

μk

0.7

Coefficient of Restitution (P2W)

0.7

Static Friction (P2W)

0.6

Kinetic Friction (P2W)

0.6Time Step∆t

1 × 10 –4

sFig. 3 Description of the definition of shoulder and toe in the charge
profile.

upward followed by layers cascading downward. Between
these two layers, there are a few layers of particles that arenearly stationary.
Next, we show a set of experimental results and DEM
simulation comparisons for mill charge flow and powerdraw. The experiments were run with balls only, rocks
only, and then a mixture of balls and rocks. Finally, an experimental run with aluminum cubes is shown. The DEM
simulation requires 10 sets of parameters for the respective
Fig. 4 (a) Simulation velocity profile and (b) experimental results forCase 8 (25 % balls, 31.8 rev/min).
contact mechanics between balls, rocks, and the mill shell.
In each of the experiments shown here a table of the contact
parameter is also included. A discussion of this parameterat a steady-state.
set is given at the end of this section.
Case 11: This case is a mixture with 354 rock particles
Case 8: This case contains 190 steel spherical balls(12 %) and 99 5 cm steel balls (13 %) for a total mass ofrevwhich contribute to 25 % volume filling of the mill for a to66.3 kg. The mill speed was set at 25.1 min . Table 2 gives
tal mass of 97.4 kg. The density of the steel sphere was set
the DEM parameters used in the simulation. Fig. 5(a)revto 7800 kg3 . The mill speed was set at 31.6 min . Table 1
shows the image of the charge and Fig. 5(b) depicts themgives the DEM parameters used in the simulation. Fig. 4(a)DEM profile colored by particle type. In this case, theshows the image of the charge velocity profile for the DEM
spherical particle too was modeled (27)
as a 32-equisided
simulation, and Fig. 4(b) shows the image of the charge
polyhedron. Due to repeated impacts, the steel spheres(27)(26)With the mill filling being all steel
in the mill.
spheres, thebecome non-round over time. Hence, we capture the shape
two charge profiles match very well at the toe, shoulder,of the sphere that looks like a soccer ball with the 32-sided
and belly positions. There were a few balls cataracting in
polyhedron. Such representations of the%%%%%%%%%%%%%%%%%%
shapes, adds to thethe actual experiment. The balls are hitting above the toe
accuracy of the particle trajectories. The two profiles agree
region and between 180° to 270°. This characteristicof thewell regarding the toe position, shoulder position, and the%%%%%%%%%%%%%%%%%%%%%
profile is also seen in the DEM simulation, which is a clear
belly of the charge. Also, few particles cataracting is wellindication of the simulation accuracy. The experimental
matched between experiment and DEM simulation. Due
power is 1762 ± 30 W, whereas the DEM simulation preto a very high degree of angularity in the rock particles,
dicts 1609 ± 40 W.
the charge seems to lock up with each other and hence
We now present the simulation results for the polyhedral
we see a steeper shoulder position than normal. The DEM(rock) particles alone or in a mixture with spherical steel
simulation captures this behavior. The DEM power drawballs, comparing the power draw and charge profiles. Theof 1,010 W ± 5 compares well with the experimental value
experimental mill reaches a steady-state in two full revoluof 1105 W.
tions of the mill and hence all the results presented here are
Case 1: In these experiments, a low-level filling of rocks

213

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218(15 %) made up of 434 pieces was used. The mill speed
rev
was set at 27.4 min . Fig. 6(a) shows the image of the experimental mill charge and Fig. 6(b) is the corresponding
DEM simulation snapshot. Once again, the two charge
profiles agreed quite well. In both the experimental and(27) is confined between 240° mark (toe)simulation, the charge
and 30° marks (shoulder). Further, Fig. 6(a) shows five toeight rock particles that are carried up by the square lifter,
above the shoulder of the cascading charge. These rock particles then follow
the parabolic trajectory downward. We%%%%%%%%%%%%%%%%%%%%%
see exactly similar transport by the lifter in the simulation
too. Although not perfect, the nearly close charge profile
structure between the experiment and DEM simulation, in

Table 2 Simulation parameter for Case 11, P2P indicates particle-particle
and P2W indicates particle-wall settings. * Rock/Spheres values.

Parameter

Symbol Value

Normal Particle StiffnessKn*2/4(× 106) N/m

Tangent Particle StiffnessKt*1/3(× 106) N/m

Damping CoefficientC0.001/0.1

Coefficient of Restitution (P2P)

ε0.4/0.85

Static Friction (P2P)

μs

0.2

Kinetic Friction (P2P)

μk

0.2

Coefficient of Restitution (P2W)

0.7

Static Friction (P2W)

0.6

Kinetic Friction (P2W)

0.6Time Step∆t

1 × 10 –5

Unit

this case, shows that the friction part of the contact model
is bearing out the trends. This case stands in contrast to milloperating with only spherical steel spheres, wherein DEM
simulation has produced picture-perfect results coinciding
with experimental work (Venugopal (2001), Govender etal. (2015)). Finally, the DEM power 482 W ± 30 compares
well with the experimental value of 424 W.
Case 20: In this experiment, a very high filling madeup of 1031 rock particles (35 % filling) was run to test theability of DEM simulation to predict higher power draw,
which in turn involves numerous polyhedra collisions. The
primary purpose of these experiments work is to verify
the volume of contact mechanics used in the Blaze-DEM
code. Table 3 gives the DEM parameters used in the simulation. Fig. 7(a) shows the experimental mill snapshot andFig. 7(b) shows the snapshot from DEM simulation. Dueto the high load, the shoulder of the charge is almost at
the 80° mark. The speed of the mill too was very high set
rev
at 33.6 min or 75 % of mill critical speed. The simulation
tracks the overall structure of the central body of the charge
including the toe and shoulder. However, the simulated
charge is slightly expanded compared with the experimen(27)%%%%%%%%%%%%%%%%%%%%%

sFig. 6 (a) Experimental and (b) DEM result for Case 1 (15 % rocks,
rev
27.4 min ).
Table 3 Simulation parameters for Case 1, P2P indicates particle-particle
and P2W indicates particle-wall settings.

(51)

Fig. 5 (a) Experimental profile and (b) DEM results for Case 11 (12 %rocks, 13 % balls, 25.1 rev/min).

214

Parameter

Symbol Value

Unit

Normal Particle StiffnessKn

2 × 106

N/m

Tangent Particle StiffnessKt

1 × 106

N/m

Damping Coefficient

C

0.01

Coefficient of Restitution (P2P)

ε0.4

Static Friction (P2P)

μs

0.5

Kinetic Friction (P2P)

μk

0.2

Coefficient of Restitution (P2W)

0.7

Static Friction (P2W)

0.6

Kinetic Friction (P2W)

0.6Time Step∆t

5 × 10 –5sAlberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

Fig. 7 (a) Experimental and (b) DEM charge profile for Case 20: 35 %rocks, 33.6 rev/min.
Table 4 Simulation parameters for Cases 4c and 6c, P2P indicates theparticle-particle and P2W indicates particle-wall settings.

Parameter

Symbol Value

Unit
N/m
N/m

Normal Particle StiffnessKn

6 × 106

Tangent Particle StiffnessKt

3 × 106

Damping Coefficient

C

0.01

Coefficient of Restitution (P2P)

ε0.8

Static Friction (P2P)

μs

0.6

Kinetic Friction (P2P)

μk

0.6

Coefficient of Restitution (P2W)

0.7

Static Friction (P2W)

0.6

Kinetic Friction (P2W)

0.6Time Step∆t

5 × 10 –5

Fig. 8 (a) Experimental and (b) DEM charge profiles for Case 4c: 25 %revfilling with 25 mm aluminum cubes at 29.2 min .

stal frame. This is attributed to the representation of therock particles with only four polyhedral shapes depicted
in Fig. 2. A more comprehensive sample from the 1031
particles, could have provided more accurate modeling of
the charge. Yet, in milling, we are interested mainly in the
cascading and cataracting charge motion and mill power.
Hence, the results presented here verify the ability of thepolyhedral contact algorithms at best. The computed powerdraw of 796 ± 10 W compares well with the experimental
power draw of 856 W.
Case 4C: A mill charge of cubes is an obvious choicefor DEM verification since the entire mass is made up of
cubes. In previous experiments, although we used irregularrock particles, we had to model only a few rock shapes as
polyhedrons for the sake of expediency. Hence, there isa difference between experimental results and simulation
results due to the variations in the rock shape. In thisexperiment, the entire charge was made up of 25.4 mm
aluminum cubes, with a density of 1800 kg3 . These cubesmwere identical in shape since they were cut from a rod ofsquare cross-section (25.4 × 25.4 mm). Table 4 gives theDEM parameters used in the simulation. Fig. 8(a) shows(26)

the mill operating with 884 aluminum cubes at a mill speed
revof 29.2 min . There is a much closer resemblance between
the experimental charge profile and(51)the simulated profile(Fig. 8(b)), simply because all the particles are identicalin shape. The shoulder and toe position agree very well.
(27)
The cataracting
stream from the shoulder also shows good
agreement. Similarly, the cubes striking the toe region too
is well predicted. The experimental power is 711 ± 11 W,
whereas the DEM simulation predicts 752 ± 72 W.
Case %%%%%%%%%%%%%%%%%%%%%
6C: in this experiment, the number of cubes wasincreased to 1061, making up a mill volume filling of
30 %. Here too, we see excellent agreement between DEM
polyhedral model and experimental profiles, as shown in
Fig. 9. The computed power draw of 752 ± 37 W agrees
with experimental values of 740 ± 11 W.

4.1 Contact mechanics parameters
The parameters used in the simulation deserve an explanation here in the milling study. The four main parameters
are the two spring constants and the two dashpot constants,
normal and tangential, respectively. The spring constants
mainly control the time of contact, i.e number of time steps
the particle pair interpenetrate before disengaging. The
dashpot constant controls the energy dissipated (computed
as contact force reduction) during the entire duration ofcontact between a pair of particles. A reasonable choice of
these four parameters produces acceptable simulation results with DEM. A point to note here is that, in a majority ofcases published in the literature, DEM simulation target has
been bulk charge motion simulation as inflow discharge

215

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

from a silo, motion over a conveyor chute, mixing vessels,
rock-scooping buckets, and many others. In all these simulations principally the metric in bulk particle velocity, forthe simulation to resemble measured experiments. In fact,
in most such cases, approximate agreement of bulk flow isshown between simulation and DEM results.
Milling, on the other hand, requires correct predictionof charge motion as well as mill power draw, so the fourparameters mentioned earlier, have to reach a compromise
between accurately predicting charge motion and power. In
this compromise, the dashpot constants play a critical role.
In addition, the spring constants determine the energy dissipated in each collision since they determine the duration of
the collision event. Suffice it to say, there is no unique set ofcontact parameters that will universally describe a system.
In any particular system, a set of parameters is arrived atthrough trial and error carried over numerous experiments

and simulations.
Table 5 shows the contact parameters used in the simulation shown in this manuscript. They range from balls only,
rocks only to a combination of rock and balls followed byaluminum cubes. In this particular set of experiments, thespring constant (normal/tangential) for balls only (4 × 106,
3 × 106) and rocks only (2 × 106, 1 × 106) seems to predictwell for the mixture of balls and rocks (4 × 106/2 × 106,
3 × 106/1 × 106). The same trend is noticed with the coefficient of restitution values. The static and kinetic friction
values trigger minor changes in the energy of collisions.
This level of perfect agreement between rock, ball, androck+ball parameters is fortuitous and may not hold goodfor all kinds of variations in mill operations. Nevertheless,the magnitude of the constants shown in Table 5 describes
laboratory milling operation both in two-dimensional andthree-dimensional simulations. This order of magnitude inparameters when carried on to large mill simulations (9 mdiameter × 3.5 m length) also produces reasonable power
results. In summary, the parameter set in DEM is still an
ongoing open question.

5. Conclusion
It is shown that volume-of-contact contact mechanics isable to successfully predict the motion of charge in a laboratory-scale mill. The polyhedral particle model helps inmodeling rock and ball assembly that is commonly encountered in mineral ore grinding plant operations. The actualrock shapes, especially in the size range of 0.2–0.4 m canbe scanned and modeled as irregular polyhedra. In addition, GPU-based codes such as Blaze-DEM enables one
to study mill discharge through grate slots and pulp lifters,
simply because such codes can handle millions of particles.

References

Fig. 9 (a) Experimental and (b) DEM charge profiles for Case 6C:
rev
30 % filling with 25-mm aluminum cubes at 29.2 min .

Cleary P.W., Recent advances in DEM modelling of tumbling

Table 5 Summary of simulation parameters used during the simulation, where (b) ball only, (r) rock only,(b&r) mixed ball and rock, and (a) aluminum cubes.

(51)

216

Case #

6, (b)

1, (r)

20, (r)11, (b&r)

4C, (a)6C, (a)

ε

0.85

0.4

0.4

0.85/0.4

0.8

0.8

μs

0.7

0.7

0.7

0.2

0.8

0.6

μk

0.7

0.7

0.7

0.2

0.8

0.6

Kn(106)

4

2

2

4/2

6

6

Kt(106)

3

1

1

3/1

3

3

% mill filling

15

15

35

25

25

30

Speed

31.6

27.4

33.7

25.1

29.2

29

rev
min

(51)

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

mills, Minerals Engineering, 14 (2001) 1295–1319. DOI:
10.1016/s0892-6875(01)00145-5
Cleary P.W., Morrisson R., Morrell S., Comparison of DEM andexperiment for a scale model SAG mill, International Journalof Mineral Processing, 68 (2003) 129–165. DOI: 10.1016/
s0301-7516(02)00065-0
Cleary P.W., Predicting charge motion, power draw, segregation
and wear in ball mills using discrete element methods,
Minerals Engineering, 11 (1998) 1061–1080. DOI: 10.1016/
s0892-6875(98)00093-4
Cleary P.W., Sinnott M., Morrison R., Prediction of slurrytransport in SAG mills using SPH fluid flow in a dynamic
DEM based porous media, Minerals Engineering, 19 (2006)
1517–1527. DOI: 10.1016/j.mineng.2006.08.018
Cleary P.W., Sinnott M.D., Morrison R.D., DEM prediction ofparticle flows in grinding processes, International Journal
for Numerical Methods in Fluids, 58 (2008) 319–353. DOI:
10.1002/fld.1728
Cundall, P.A., Strack, O.D.L., A discrete numerical model for
granular assemblies, Geotechnique, (1979) 47–65. DOI:
10.1680/geot.1979.29.1.47
Delaney G.W., Cleary P.W., Sinnott M.D., Morrison R.D., Novelapplication of DEM to modelling comminution processes,
IOP Conference Series: Materials Science and Engineering,
10 (2010) 012099. DOI: 10.1088/1757-899x/10/1/012099
Djordjevic N., Morrison R., Loveday B., Cleary P., Modelling comminution patterns within a pilot scale AG/SAG
mill, Minerals Engineering, 19 (2006) 1505–1516. DOI:
10.1016/j.mineng.2006.07.003
EDEM, User Guide, DEM solution Ltd., Edinburgh, Scotland,
UK Copyright © (2011). <http://tm.spbstu.ru/images/2/28/
EDEM2.4_user_guide.pdf> accessed 30.07.2021.
Govender N., Rajamani R.K., Kok S., Wilke D.N., Discrete element simulation of mill charge in 3D using the BLAZE-DEM
GPU framework, Minerals Engineering, 79 (2015) 152–168.
DOI: 10.1016/j.mineng.2015.05.010
Govender N., Wilke D.N., Kok S., Blaze-DEMGPU: Modular high performance DEM framework for the GPUarchitecture, SoftwareX, 5 (2016) 62–66. DOI: 10.1016/j.
softx.2016.04.004
Govender N., Rajamani R., Wilke D.N., Wu C.-Y., Khinast J.,
Glasser B.J., Effect of particle shape in grinding mills usinga GPU based DEM code, Minerals Engineering, 129 (2018a)
71–84. DOI: 10.1016/j.mineng.2018.09.019
Govender N., Wilke D.N., Pizette P., Abriak N.-E., A study ofshape non-uniformity and poly-dispersity in hopper discharge of spherical and polyhedral particle systems using theBlaze-DEM GPU code, Applied Mathematics and Computation, 319 (2018b) 318–336. DOI: 10.1016/j.amc.2017.03.037
Govender N., Wilke D.N., Wu C.-Y., Tuzun U., Kureck H., A
numerical investigation into the effect of angular particle
shape on blast furnace burden topography and percolation
using a GPU solved discrete element model, Chemical
Engineering Science, 204 (2019) 9–26. DOI: 10.1016/j.ces.
2019.03.077

Govender N., Wilke D.N., Wu C.-Y., Rajamani R., Khinast J.,
Glasser B.J., Large-scale GPU based DEM modeling of
mixing using irregularly shaped particles, Advanced Powder Technology, 29 (2018c) 2476–2490. DOI: 10.1016/j.
apt.2018.06.028
Hopkins M.A., Hibler III W.D., Flato G.M., On the numericalsimulation of the sea ice ridging process, Journal of Geophysical Research: Oceans, 96 (1991) 4809–4820. DOI:
10.1029/90jc02375
Kiangi K., Potapov A., Moys M., DEM validation of media shapeeffects on the load behaviour and power in a dry pilot mill,
Minerals Engineering, 46–47 (2013) 52–59. DOI: 10.1016/j.
mineng.2013.03.025
Latham J.-P., Munjiza A., Garcia X., Xiang J., Guises R., Threedimensional particle shape acquisition and use of shapelibrary for DEM and FEM/DEM simulation, Minerals
Engineering, 21 (2008) 797–805. DOI: 10.1016/j.mineng.
2008.05.015
Mishra B.K., Rajamani R.K., Motion analysis in tumbling mills
by the discrete element method, KONA Powder and Particle
Journal, 8 (1990) 92–98. DOI: 10.14356/kona.1990016
Mishra B.K., Rajamani R.K., The discrete element method for thesimulation of ball mills, Applied Mathematical Modelling, 16(1992) 598–604. DOI: 10.1016/0307-904x(92)90035-2
Morrison R.D., Cleary P.W., Using DEM to model ore breakage
within a pilot scale SAG mill, Minerals Engineering, 17(2004) 1117–1124. DOI: 10.1016/j.mineng.2004.06.016
Potapov A.V., Campbell C.S., A three-dimensional simulation ofbrittle solid fracture, International Journal of Modern Physics
C, 07 (1996) 717–729. DOI: 10.1142/s0129183196000594
Rajamani R.K., Mishra B.K., Venugopal R., Datta A., Discreteelement analysis of tumbling mills, Powder Technology, 109(2000) 105–112. DOI: 10.1016/s0032-5910(99)00230-2
Rothenburg L., Bathurst R.J., Numerical simulation of idealized
granular assemblies with plane elliptical particles, Computers
and Geotechnics, 11 (1991) 315–329. DOI: 10.1016/0266352x(91)90015-8
Tavares L.M., André F.P., Potapov A., Maliska C., Adapting
a breakage model to discrete elements using polyhedral
particles, Powder Technology, 362 (2020) 208–220. DOI:
10.1016/j.powtec.2019.12.007
Tavares L.M., A review of advanced ball mill modelling, KONA
Powder and Particle Journal, 34 (2017) 106–124. DOI:
10.14356/kona.2017015
Tavares L.M., de Carvalho R.M., Modeling breakage rates ofcoarse particles in ball mills, Minerals Engineering, 22(2009) 650–659. DOI: 10.1016/j.mineng.2009.03.015
Venugopal R., Rajamani R.K., 3D simulation of charge motion
in tumbling mills by the discrete element method, Powder
Technology, 115 (2001) 157–166. DOI: 10.1016/s00325910(00)00333-8
Xu L., Luo K., Zhao Y., Fan J., Cen K., Influence of particle
shape on liner wear in tumbling mills: a DEM study,
Powder Technology, 350 (2019) 26–35. DOI: 10.1016/j.
powtec.2019.03.033

217

Alberto M. Puga et al. / KONA Powder and Particle Journal No. 39 (2022) 208–218

Authors’ Short Biographies
Alberto Puga
Alberto Puga completed his Bachelor’s degree in Mechanical Engineering from the Universityof Utah in Salt Lake City, in 2015. In 2016, he joined the Department of Metallurgical Engineering
at the University of Utah in Salt Lake City as MS student. Later, he transferred to pursue a PhD in
Metallurgical Engineering with an emphasis in mineral processing. As a student, he was a research
assistant in comminution projects involving breakage mechanics in ball mills. He worked as a teaching assistant for the mineral processing and statistics courses. Because of his interaction with thestudents, he was awarded the “Teaching Assistant of the Year” in the department.

Nicolin Govender
Dr. Nicolin Govender is a principal scientist at Mondelez International in the position of global
lead for granular material physics and GPU/HPC computing for the creating of digital twins. Prior
to this, he held the prestigious EU Marie Curie Research Fellowship in the Department of Chemicaland Process Engineering at the University of Surrey. Dr. Govender is the primary investigator (PI)of the NVIDIA GPU Research Centre for Discrete Element Particle Modeling, which he establishedin 2013 with the support for NVIDIA, specializing in GPU computing of particle systems. He has
been working on GPU clusters since the advent of general-purpose GPU computing in 2008 and is anesteemed international expert in the field. He has solely developed the open source GPU-based DEM
code “Blaze-DEM”, that is hosted by Elsevier, which is used by a growing number of institutes,
nationally and internationally.

Raj K. Rajamani
He has been on the research and teaching faculty position at the University of Utah since 1979.
Currently he is Professor of Material Science and Engineering. Dr. Rajamani’s research interests
include: Breakage rate of mineral particle in ball mills and scale-up to plant scale mills, computational Fluid Dynamic study of hydrocyclones, Discrete Element Simulation of mineral ore
grinding mills and electrodynamic sorting of auto-shredder scrap stream to recover aluminum andcopper. Dr. Rajamani received the Antoine M. Gaudin Award, presented by the Society of Mining,
Metallurgy and Exploration Engineers Inc. in the year 2009. The award plaque reads, “For his
seminal work in the application of discrete element methods in the modeling of charge motion insemi-autogenous and ball mill grinding, and for his contribution to the basic science of comminution
and classification.”

218

KONA Powder and Particle Journal No. 39 (2022) 219–229/https://doi.org/10.14356/kona.2022004

Original Research Paper

Smart Mechanical Powder Processing for Producing Carbon
Nanotube Reinforced Aluminum Matrix Composites †Behzad Sadeghi 1, Genlian Fan 1*, Zhanqiu Tan 1, Zhiqiang Li 1, Akira Kondo 2 and Makio Naito 2
1 State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, China
2 Joining and Welding Research Institute (JWRI), Osaka University, Japan

Abstract
The central concern in the fabrication of carbon nanotube (CNT) reinforced metal composites is the well balance
between uniform dispersion and structural integrity of CNTs. Rapid and uniform self-assembly of CNTs andspherical Aluminum (Al) particles into a core-shell structure is realized by a smart mechanical powder processing.
The factors influencing the dispersion uniformity and structural integrity of CNTs during the processing arestudied, including the size of Al particles, mixing speed and mixing time. It is revealed that a size of 35 μm
is preferred for the Al particles to tear apart the CNT clusters and obtain a uniform dispersion of CNTs on Al
surface. Different composite states, CNTs are singly dispersed, thickly wrapped, or embedded in the Al particles,
can be obtained by changing the mixing speed. Well coordination between the CNT dispersion homogeneity andstructural integrity could be achieved under suitable processing condition. Therefore, it can be adopted as anefficient and intelligent technology to achieve the desired performance in CNT/Al composites.
Keywords: dispersion, structural integrity, high-shear pre-dispersion, CNTs reinforced metal matrix composite,
smart powder processing

1. Introduction
During the past two decades, significant progress has
been achieved in the fabrication of carbon nanotubes reinforced metal matrix composites (MMCs). Regardless ofthe material type and fabrication technique, the balance between the uniform dispersion of CNTs in the Al matrix andits structural integrity is vital prerequisite that needs to beconsidered (Fan G.L. et al., 2014; Wei H. et al., 2014). How
to realize the rapid, efficient, and uniform dispersion of
CNTs in the Al matrix is one of the key factors restricting
the industrial application of CNT/Al and alloy composite
materials. It is well known that fine powders are not able toflow freely due to the strong inter-particle cohesion, mainly
ascribed to the Van der Waals forces for dry, neutral, and inert particles (Deng X. and Davé R.N., 2017b; Eggersdorfer
M.L. et al., 2010), dominating the particle weight. The
situation can be more serious when the reinforcement
is one-dimensional, namely tubular and flexible such as
CNTs (Han Y. et al., 2015; Narh K.A. et al., 2008; Zhang
K. and Choi H.J., 2014). The unique geometry, along with†*

Received 14 October 2020; Accepted 17 December 2020
J-STAGE Advance published online 20 February 2021
Corresponding author: Genlian Fan;
Add: 800 Dongchuan Road, Shanghai, Shanghai 200240, China
E-mail: fangenlian@sjtu.edu.cn
TEL: +86-21-5474 5872 FAX: +86-21-3420 2749

large specific surface area and significant Van der Waals
force, strongly affects the dispersion status of CNTs.
In addition, the structural integrity of CNTs is considered
to be another key factor affecting the strengthening effectby interfacial reaction and the formation of harmful products. Therefore, the MMCs community, especially those
CNTs reinforced Aluminum composites, have significant
concerns in overcoming the dilemmas associated withdispersion and structural integrity. From this point of view,
these factors should be taken into account when designingappropriate preparation processes.
Presently, many CNT/Al composite preparation methods
can meet the requirements of CNTs reinforced Al Matrix
Composite, but each has its shortcomings. Melt casting
and thermal spraying can realize the rapid preparation oflarge block materials with a high content of CNTs. Still, it
is difficult to solve the dispersion of CNTs and the control
of interface reaction (Baig Z. et al., 2018). Great efforts
have also been made in the field of both large plastic deformation technologies such as accumulative roll bonding(ARB) (Salimi S. et al., 2010), high-pressure torsion (HPT)(Asgharzadeh H. et al., 2014; Tokunaga T. et al., 2008),
friction stir processing (FSP) (Johannes L.B. et al., 2006;
Sadeghi B. et al., 2018b; Sadeghi B. et al., 2018d) andsolid-phase powder metallurgy (PM) techniques (Sadeghi
B. et al., 2018a). One could be found that PM based techniques are effective and low cost, so that bring into a clear

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

219

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

insight to solve the dilemma mentioned above. The PM
based methods include high-energy ball milling (Esawi
A.M.K. et al., 2009; Sadeghi B. et al., 2020; Sadeghi B. etal., 2019), flake powder metallurgy (Flake PM) (Fan G.L.
et al., 2014; Jiang L. et al., 2012), liquid phase ball milling(Chen B. et al., 2015; Jiang L. et al., 2012), nanoscaledispersion method (Kwon H. et al., 2009; Noguchi T. etal., 2004), molecular level mixing (Cha S.I. et al., 2005;
Nam D.H. et al., 2012), in-situ growth of CNTs combinedwith low-energy ball milling (He C., 2007; Cao L.L. et al.,2012; Yang X. et al., 2013) and so on (Baig Z. et al., 2018).
However, whether wet ball milling or in-situ growth isused as the initial dispersion method of CNTs, it is a timeconsuming and high energy consumption method, which
is challenging to match with industrial production. Therefore, it is of great significance to study an effective predispersion way for the preparation of CNT/Al composite
with high performance. Precisely, despite recent advancesin powder-based processing techniques such as Flake PM(Fan G.L. et al., 2014; Jiang L. et al., 2011; Jiang Y. et al.,2019; Tan Z. et al., 2011), there is still a challenging effort
to achieve the extraordinary balance between dispersion
and structural integrity of CNTs through Al matrix. In sum,it seems that PM is still the best macro quantitative preparation method for controllability and operability, but there
is still much room for improvement.
Recently, various dry particle coating technologies havebeen developed for advanced material production throughcovering the surface of larger core (host) particles with fineshell (guest) particles by mechanical forces, which were induced through four different mechanical devices (Foppoli
A.A. et al., 2017; Sharma R. and Setia G., 2019). All of
those are well designed to prompt de-agglomeration ofcohesive nanopowders (NP) to facilitate the NP dispersion(Bhaumik S., 2015; Naito M. et al., 2009; Wei D. et al.,2002). Among these technologies, Mechano Fusion® (MF)system as a smart powder process (Naito M. et al., 2009)has attained a considerable amount of attention to produce
the composite powders with desired tailor-made properties
for advanced MMCs (Chen M. et al., 2018; Ghoroi C. et al.,2013; Naito M. et al., 2009). Comparing to the wet-based(Jiang L. et al., 2012; Sadeghi B. et al., 2012a; Sadeghi B.
et al., 2012b; Zhou S.-M. et al., 2007) and gas-based (HeC. et al., 2007; Yang X. et al., 2016) coating techniques,
the smart powder process can produce advanced composite materials with minimum energy consumption andenvironmental impact in a dry environment. In principle,
the MF system is expected to achieve the dry and uniform
composite of nano-sized CNTs and micron-sized metal
powders. Still, CNTs are different from ordinary nanoparticles because of their complex structure and could be
easily intertwined and clustering. In such circumstances,
opening the clusters and wrapping on the surface of metal
powder by mechanofusion is a challenging issue. Very

220

recently, Chen et al. (Chen M. et al., 2018) demonstrated
that dry particle coating (also termed as high-shear predispersion) combined Flake PM route not only improves
the dispersion efficiency of CNTs in the ball milling
process but also well-preserves the structural integrity of
CNTs comparing to other PM routes (Chen M. et al., 2018;
Chen M. et al., 2019). Nevertheless, the effect of hostparticle size and the operation conditions on the dispersion
and structural integrity of CNTs were not demonstrated.
Considering the low cost, simplicity, and low energy
consumption of the processing, there is a great potential
to transit it from laboratory to large-scale commercial
applications. Therefore, there is a pressing need to develop
a better understanding of the factors that affect the coating
effectiveness of the high-shear pre-dispersion process.
Many factors may affect the composite effects of particles, and subsequently, dry coating effectiveness, including
host particle size, mixing speed and time. Very recently,
Zheng et al. (Zheng K. et al., 2020) studied the effects ofparticle properties such as their sizes, stiffness and surface
energies on the coating effectiveness and demonstrated thatthe host particle size has no significant effect on the coating
quality when it is orders of magnitude larger than that ofguest particles. They also reported that increasing processing intensity led to guest particles bouncing off of host particles, indicating poor coating performance. It was reported
that the discharge efficiency of LiNi0.5Mn1.5O4 cathodecould enhance by the CNT coat provided by the mechanofusion method (Hwang T. et al., 2016). Narh et al. (Narh
K.A. et al., 2008) studied dry coating of polymer powder
particles with de-agglomerated CNTs and reported an
acceptable extent of the CNT dispersity. Chen et al. (Chen
M. et al., 2019) could effectively tailor the pre-dispersion
state of CNT/6061Al composite powders by controlling thehigh-shear process speed. No comprehensive research has
mentioned that host particle size and operating conditions(mixing time and speed of high-shear pre-dispersion process) simultaneously affect the dispersion and structural integrity degree in CNT/Al composite powders. To this end,
the current study is trying to uncover the various aspects ofthe pre-dispersion and structural integrity degree of CNTs
in the Al matrix composite. It should be interesting to notethat the dispersion and binding mechanisms involved in thehigh-shear pre-dispersion process depend on the initial sizeof host particles and guest particles (Ötles S. et al., 2009;
Wei D. et al., 2002; Zheng K. et al., 2020). However, it iswell known that the contact surface between powder materials is subjected to extremely high local temperature andpressure, resulting in unique phenomena between host andguest or among fine particles or even generating mechanical stress (Naito M. et al., 2009).
In this study, an environmentally friendly and smart
powder processing technology, the namely high-shear
pre-dispersion process is successfully adopted to fabricate

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

1.5 wt.% CNT/Al composite powders. Specifically, the effects of host particle size, mixing time, and rotational speedof powder mixing process on the balance of dispersity andstructural integrity of CNTs in final composite powders andconsequently composite effects are discussed.

2. Experimental
2.1 Raw materials
Atomized near-spherical Al powders with a various
average diameter of 2, 5, 10, 15, 35, 70 μm, and industrial
multi-walled CNTs with a diameter of about 10–20 nm,
length of about 0.5–2 μm and purity of more than 95 % arechosen to explore the size dependence in the high-shear
pre-dispersion process. Fig. 1a shows the original shapeof 35 μm-Al powder have a round surface. A small numberof tiny Al particles are attached on the surface, and size
distribution is relatively narrow. Fig. 1b–c show the initial
CNTs, which are in the form of particles with a size of tensof microns. Long and entangled CNTs can be seen at higher
magnifications. Fig. 1d shows the Raman spectrum of raw
CNTs. It is well-known that there are two characteristic
peaks at 1346 cm–1 and 1570 cm–1, which are called D peakand G peak, respectively (Cavaliere P. et al., 2019; Kwon
H. and Leparoux M., 2012; Sadeghi B. et al., 2018c; Zhao
Q. and Wagner H.D., 2004). Former is attributed to defects
in the hexagonal graphite layer structure, resulting in thein-plane vibration. The latter is related to a single-photon
emission generated by the tangential tensile mode of theFig. 1graphite layer plane (Loa I., 2003; Zhao Q. and Wagner
H.D., 2004). The ratio of two peaks (ID/IG) is usually used
to characterize the graphitization degree of CNTs. The
lower the ratio, the fewer the defects of CNTs and thehigher graphitization degree is. So it is useful to track thechanging trend of the structural integrity of CNTs (Chen
M. et al., 2019). The ID/IG value of raw CNTs is about 0.95.

2.2 Preparation of CNT/Al composite powder
1.5 wt.% of CNTs were processed with Al powder ofdifferent diameters in a prototype of MF system (MECHANO FUSION®) from Hosokawa Micron Corporation,
Japan (Naito M. et al., 1993). As illustrated in Fig. 2a, it
has a container diameter of 80 mm and the clearance/gap
between the rotor and container is of 2 mm. The powder
mixture was first processed at the speed of 300 rpm for
2 min to homogenize and then processed at the designatedspeed (1000–4000 rpm) for different times (5–15 min) toobtain composite powders.

2.3 Characterization
The morphology of the powder is observed by Sirion
200 field emission scanning electron microscope (FESEM)
at the working voltage of 20 kV. The influence of the process condition on the structural integrity of CNTs is characterized by Raman spectroscopy (SENTERRA R200-L),
by using the 532 nm line of an Ar+ laser as the excitation
source.

FESEM of (a) spherical 35 μm-Al powders, (b) raw CNTs, (c) magnification of CNTs in (b), (d) Raman spectrum of raw CNTs.

221

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

Fig. 2 Illustrations of (a) prototype of Mechano Fusion® system (Naito M. et al., 1993), (b) the working principle of CNTs dispersion on Al powder
in MF system.

3. Result and discussion
The main working principle of the MF system is to use
the centrifugal force generated by the high-speed rotationof the rotor and the gravity effect of the material itself tomake the material pass through the clearance between therotor and the container at high speed. The mutual shear
force and impact force between the materials make thesmaller particles adhered onto the more considerable materials, to realize the core-shell structured composite particles(Naito M. et al., 2009; Qu L. et al., 2015). In the case of
CNTs and Al particles, as illustrated in Fig. 2b, the CNTs
as the guest particles should be first torn apart by the shear
forces of Al particles (host particles) into smaller particles
or even individual CNTs, and then adhered onto the surfaceof Al particles. The repeating collision between Al particles
made CNTs uniformly dispersed on the surface of Al particles, forming a Al/CNTs core-shell structured composite
powder. Therefore, the dispersion status is mostly affectedby the particle size or mass ratio between host/guest particles, the processing speed and time.

3.1 Effect of Al particle size
The average particle size of the initial Al powders not
only determines the surface area of the powders but also
determines the mass ratio between the particles and CNTs.
On the one hand, the smaller the average particle size of
Al powder is, the larger the corresponding surface area
is, which is more conducive to the uniform distribution of
CNTs; on the other hand, the smaller the mass of a single Alparticle is, the weaker its impact energy on CNTs clusters
will be. Precisely, smaller Al particles provide lower collision energy but higher surface area, which in turn controls
the type of contacts and interparticle adhesion force (DengX. and Davé R.N., 2017a) and subsequent dispersion of
CNTs.
Fig. 3 shows FESEM of CNT/Al composite powder

222

obtained by mixing 1.5 wt.% CNTs with Al powder ofdifferent particle sizes at 2500 rpm for 10 min. As one cansee, the shape of Al particle is not significantly changed
during the high-shear pre-mixing process as reported(Chen M. et al., 2018). The main reason for this was dueto the fact that the processing condition applied was still
below the limit of Al particle deformation. For the smaller
Al particle size, namely 2, 5 μm, the de-agglomeration anddispersion of CNTs hardly occurred. Most CNTs remainedin clusters (indicates by yellow arrows in Fig. 3a–b); only
very few individual CNTs were attached on the surface of
Al particles (Fig. 3d–e). When the particle size increased to10, 15 μm, more individual CNTs were attached on the surface of Al particles, while a small number of clusters still
existed. Further increasing the particle size to 35, 70 μm,
only tiny flattened CNT clusters can be occasionally found,indicating almost all the CNTs were torn apart and attachedon the surface of Al particles. That is, the larger the particle
size of the Al particle is, the more CNTs are attached to thesurface. The larger the mass or volume of Al particles is,the easier it is to wrap CNTs on the surface. The initial sizeof the CNTs clusters is of tens of microns, and so the collision force exerted from those small Al particles (smaller
than 10 μm) are not high enough to tear the CNT clusters
apart. Still, on the contrary, these collisions made the CNT
clusters more solid than initial CNTs. Therefore, there is asize limit that the pre-dispersion of CNTs on the Al surface
can be applied.
Further observation of the micromorphology of theAl particle surface shows that the degree of the surface
smoothness is changed in larger sizes of Al particle.
The surface of the Al particle is no longer smooth, and acertain number of pits appear, which should be related tothe significant improvement of the impact force between
the larger Al particles. The small Al particles that initiallyattached on the surface of big particles were flattened andstuck on the Al surface, making a rougher surface (Fig. 3i)with CNTs embedded in the surface pits. By and large,

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

Fig. 3 FESEM of pre-mixed CNT/6061Al composite powders with different particle sizes processed at 2500 rpm for 10 min, (a, d) 2 μm, (b, e) 5 μm,(c, f) 10 μm, (g, j) 15 μm, (h, k) 35 μm, (i, l) 70 μm. Arrows indicate the presence of the CNT clusters.

under the current mixing conditions, Al particles with theaverage size above 35 μm can provide the appropriate levelof pre-dispersion of CNTs and complete the pre-dispersion
process well. Considering that the essential purpose of the
pre-dispersion process is to reduce the pressure of subsequent powder milling, to shorten the time required for CNT
dispersion, as well as keeping the structural integrity of
CNTs, the Al powders with 35 μm particle size is preferred.

3.2 Effect of pre-dispersion speed (rotational
speed) on CNT dispersion
It is well known that the force acting on the powder
blend generally increases with rotational speed (Naito M.
et al., 1993). The higher the speed, the more robust anduseful the interaction force can be produced between thematerials and subsequently affect the flowability of theprocessed powder. As described in the previous section, the35 μm Al powder succeeds in completing the task of opening the CNT clusters completely at 2500 rpm. Therefore, it
is considered to alter the pre-dispersion speed further andobserve its effect on the dispersion status.
Fig. 4 shows the FESEM of CNT/Al composite powder
after mixing 35 μm Al powder with CNTs for 10 min atdifferent rotational speeds. Big and flattened CNT clusters
can be easily observed at low rotational speed (1000 rpm,

Fig. 4a), but the amount and size of CNT clusters progressively decreased with the increasing rotational speed
up to 2000 rpm. A thick layer of dispersed CNTs can beobserved on Al particle surface at 2000 rpm, as shown in
Fig. 4f. With the increase of mixing speed to 2500, 3000,
4000 rpm, small Al chips were attached on the surface of
Al particles, and only a small number of CNT ends canbe observed on the surface of Al particles, as shown in
Fig. 4j–l. It can be deduced that with the increase of speed,
CNTs show a gradual “in-depth” change process from thesurface to the interior of the Al particle, which is completed
by the embedding of CNTs into Al chips and the mutual
grinding of Al powders.
The above results depict the trend that de-agglomerationand dispersion of CNTs increase as a function of increasing
rotational speed. This is because as the rotational speed
increases, the intensity of collisions between Al particles
and CNT clusters violently increases when passing throughthe clearance between the rotor and container. Because of
severe shear, friction, and compression forces, big CNT
clusters are quickly torn apart and broken into the smaller
ones. And then the small CNT clusters adhered on thesurfaces of Al particles were further de-agglomerated anduniformly dispersed throughout the surface of Al particles
by the repeating collision between Al particles throughout
the processing time.

223

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

Fig. 4 FESEM images of Al at CNT composite powders processed by high-shear pre-dispersion process with various rotational speed, (a, d)1000 rpm; (b, e) 1500 rpm; (c, f) 2000 rpm; (g, j) 2500 rpm, (h, k) 3000 rpm, (i, l) 4000 rpm. The yellow arrows indicate the CNT clusters.

The tentative conclusion to be drawn is that by changing
the mixing speed (rotational speed), the type of contacts
between CNTs (as guest) and Al particles (as host) can
be changed to strongly affect the dispersity status. On the
one hand, at too slow rotational speeds, guest-guest (CNT
clusters) and host-host (Al-Al) contacts remain due toinsufficient mechanical forces. And on the other hand, athigh rotational speeds, CNTs both in the form of cluster
and individual are embedded in Al particles (host-guest
contact). The former results in the remaining of CNT cluster, and the latter causes heterogeneity dispersion of CNTs
in Al particles. Therefore, it can be inferred that the best
condition for uniform dispersion of CNTs is that CNTs are
singly dispersed throughout the surface of Al particles at amoderate rotational speed.
Additionally, it is shown that when rotational speed
increases from 2500 rpm to 4000 rpm, small Al particles
attached on the surface of bigger ones were gradually stuck
and probably embedded in Al particles, generating Al particles with a bigger size and smoother surface (Fig. 4h–i),compared to lower rotational speeds (Fig. 4a–b).

3.3 Effect of pre-dispersion time on CNTs
dispersion
The mixing process of CNTs and Al powder is the process of gradually opening and coating CNTs clusters on
the surface of Al powder. The efficiency of the dry particle
coating process is determined by the total mass, mass ratio,
mixing speed and mixing time. Among these affecting pa-

224

rameters, mixing time not only has a significant influence
on dispersity status and structural integrity of CNTs but
also leads to alteration of the appearance of Al powder.
To study the effect of mixing time on the dispersion status of CNTs during the high-shear pre-dispersion process,the Al powder and CNTs with a medium particle size of
35 μm are selected as the primary materials. According
to the tailored objectives, two different rotational speedsof 1500 rpm and 2500 rpm are chosen to do the mixing
process at different mixing times of 5, 10 and 15 min.
Fig. 5a–c show that the CNTs on the surface of Al particles
can be observed under 1500 rpm for different mixing times.
After a short mixing time (5–10 min, Fig. 5a–b), CNTs
coated onto the Al surfaces are discrete, and by increasing
the mixing time, a continuous film-like CNT coating is
gradually formed (15 min, Fig. 5c). Also, the length of
CNTs decreased from 0.5–2 μm to 0.2–0.5 μm, indicatingthat CNTs clusters were cut short during the opening process due to shear and compression stresses. For the mixing
time of 15 min, no CNT clusters can be observed, whichindicates that CNTs have been completely attached on thesurface of Al particles. Fig. 5d–f show the CNT dispersion
status at 2500 rpm for various mixing times. After 5 minprocessing, we can see that more CNTs are attached on
the surface than mixed at the speed of 1500 rpm for thesame time. With the increase of processing time, most
CNTs are embedded underneath the Al chips, which should
be attributed to the presence of the enormous impact,
compression, and shear forces between the Al particles
when they passed through the clearance between the rotorBehzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

Fig. 5 FESEM images of CNT/Al composite powders premixed at (a–c) 1500 rpm and (d–f) 2500 rpm for different time: (a, d) 5 min, (b, e) 10 min,(c, f) 15 min.

and container. Due to such severe shear and compression
stress, a long-time mixing may result in the embedding ofsome CNT clusters underneath Al chips before they were
fully de-agglomerated and spread over the surfaces. It
could increase the responsibility of subsequent ball milling
dispersion at the expense of more structure damage of
CNTs under high energy ball milling dispersion. It can,therefore, be used to suggest an optimum mixing time toachieve uniform distribution of individual CNTs onto thesurface of Al particles without embedding them and thus,
the improvement of pre-dispersion efficiency.

3.4 Pre-mixing speed dependence of structural
integrity
The good maintenance of structural integrity of CNTs
is considered to be one of the main factors that should beconsidered during the processing, although some results
showed that in the absence of a significant interface reaction, the failure of the tubular structure on the surface of
CNTs can enhance the interface bonding between CNTs
and Al matrix, its bearing capacity and strengthening effect(Chen B. et al., 2014; Ci L.J. et al., 2006; Kwon H. et al.,2013).
As shown in Fig. 6, compared with the ID/IG value(0.95) of the initial CNTs powder, it is found that themechanofusion pre-dispersion process had little damage
to the structural integrity of CNTs. With the increase ofrotational speed, the ID/IG value first increased to about
1.01 and then decreased to about 0.96 at 2800 rpm. The
decrement of the ID/IG value indicates less damage. This isvery likely that, the pre-dispersed CNTs are rapidly embedded underneath the surface of the Al chips at high speed,
resulting in a better protection of CNTs (Chen M. et al.,2019). Therefore, it can be concluded that CNTs are just cut
short efficiently without much structural integrity damage
during the pre-dispersion process. The structural integrity
is much better preserved than those traditional ball millingFig. 6 Raman spectrum of pre-dispersed CNT/Al composite powder at
different rotational speeds.

dispersion process.
To sum up, for the raw CNT clusters with dozens of
microns, the size of Al particles should over 15 μm, as toprovide sufficient impact energy to tear apart the clusters
via mechanical forces under the MF system. Changing therotational speed can obtain different composite states. With
the increase of speed, CNTs show a gradual “in-depth”
change from the surface to the interior of the Al particles,
which is completed by the embedding of CNTs into Al
chips and the mutual grinding of Al powders. However,
the effect of their combination with the subsequent powder
milling process needs to be considered to select the best
pre-dispersion process parameters. Chen’s work (Chen M.
et al., 2019) shows that only by pre-dispersion at moderate
speed, in which CNTs are well de-agglomerated and partially embedded in Al matrix, can provide a controllable
balance between the CNT dispersity and structural integrity
protection compared with the other processing conditions.

225

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

4. Conclusion
The smart powder processing based on the Mechano
Fusion® system can realize the rapid composite of CNTs
and Al powders. The particle size of Al powders, the mixing speed and time have a significant influence on the dispersion status. For the raw CNTs with dozens of microns,
there is a size and speed limit to provide sufficient impact
to tear apart the clusters and coat them onto the surface of
Al particles. Considering the dispersion uniformity andsurface area of Al powders to bear CNTs, the size of 35 μm
Al powder and the speed around 2000–2500 rpm are preferred. The efficiency of processing is very high and undersuitable speed, 15 min is sufficient to obtain a uniform
dispersion of CNTs all over the surfaces of Al particles.
The CNTs were cut short, but structural integrity was notseverely damaged. Therefore, a high-shear pre-dispersion
process as a smart mechanical powder processing is arelatively simple and environmentally friendly approach to
produce CNT/Al composite powder with the desired balance between dispersion and structural integrity of CNTs
in metallic matrix.

Acknowledgements
This work was supported by the National Natural
Science Foundation of China (Nos. 51671130, 51871149,
51971206), Shanghai Science and Technology Committee(No. 19ZR1474900) and JWRI International Research
Collaboration.

References
Asgharzadeh H., Joo S.-H., Kim H.S., Consolidation of carbon
nanotube reinforced aluminium matrix composites byhigh-pressure torsion, Metallurgical and Materials Transactions A, 45 (2014) 4129–4137. DOI: 10.1007/s11661-0142354-6
Baig Z., Mamat O., Mustapha M., Recent progress on thedispersion and the strengthening effect of carbon nanotubes
and graphene-reinforced metal nanocomposites: a review,
Critical Reviews in Solid State and Materials Sciences, 43(2018) 1–46. DOI: 10.1080/10408436.2016.1243089
Bhaumik S., Principles and applications of mechanical dry coating—review and state-of-the-art, 5, Master of Science, New
Jersey Institute of Technology, 2015. https://digitalcommons.
njit.edu/theses/223/
Cao L.L., Li Z.Q., Fan G.L., Jiang L., Zhang D., Moon W.J., Kim
Y.S., The growth of carbon nanotubes in aluminum powders
by the catalytic pyrolysis of polyethylene glycol, Carbon, 50(2012) 1057–1062. DOI: 10.1016/j.carbon.2011.10.011
Cavaliere P., Sadeghi B., Shamanian M., Ashrafizadeh F., Al-based
nanocomposites produced via spark plasma sintering: effectof processing route and reinforcing phases, in: Cavaliere P.
(Ed.) Spark Plasma Sintering of Materials: Advances in Pro-226

cessing and Applications, Springer International Publishing,
Cham, Switzerland, 2019, pp. 161–190. ISBN: 978-3-03005327-7. DOI: 10.1007/978-3-030-05327-7
Cha S.I., Kim K.T., Arshad S.N., Mo C.B., Hong S.H., Extraordinary strengthening effect of carbon nanotubes in metalmatrix nanocomposites processed by molecular-level mixing,
Advanced Materials, 17 (2005) 1377–1381.
Chen B., Jia L., Li S., Imai H., Takahashi M., Kondoh K., In
situ synthesized Al4C3 nanorods with excellent strengthening effect in aluminum matrix composites, Advanced
Engineering Materials, 16 (2014) 972–975. DOI: 10.1002/
adem.201400232
Chen B., Li S., Imai H., Jia L., Umeda J., Takahashi M., Kondoh
K., An approach for homogeneous carbon nanotube dispersion in Al matrix composites, Materials & Design, 72 (2015)
1–8. DOI: 10.1016/j.matdes.2015.02.003
Chen M., Fan G., Tan Z., Xiong D., Guo Q., Su Y., Zhang J., Li
Z., Naito M., Zhang D., Design of an efficient flake powder
metallurgy route to fabricate CNT/6061Al composites,
Materials & Design, 142 (2018) 288–296. DOI: 10.1016/j.
matdes.2018.01.044
Chen M., Fan G., Tan Z., Yuan C., Xiong D., Guo Q., Su Y., Naito
M., Li Z., Tailoring and characterization of carbon nanotube
dispersity in CNT/6061Al composites, Materials Scienceand Engineering: A, 757 (2019) 172–181. DOI: 10.1016/j.
msea.2019.04.093
Ci L.J., Ryu Z.Y., Jin-Phillipp N.Y., Ruhle M., Investigation of theinterfacial reaction between multi-walled carbon nanotubes
and aluminum, Acta Materialia, 54 (2006) 5367–5375. DOI:
10.1016/j.actamat.2006.06.031
Deng X., Davé R.N., Adhesion and friction of dry-coated nanorough particles, Powder Technology, 314 (2017a) 20–27.
DOI: 10.1016/j.powtec.2016.07.035
Deng X., Davé R.N., Breakage of fractal agglomerates, Chemical
Engineering Science, 161 (2017b) 117–126. DOI: 10.1016/j.
ces.2016.12.018
Eggersdorfer M.L., Kadau D., Herrmann H.J., Pratsinis S.E.,
Fragmentation and restructuring of soft-agglomerates undershear, Journal of Colloid and Interface Science, 342 (2010)
261–268. DOI: 10.1016/j.jcis.2009.10.062
Esawi A.M.K., Morsi K., Sayed A., Gawad A.A., Borah P.,
Fabrication and properties of dispersed carbon nanotube–
aluminum composites, Materials Science and Engineering:A, 508 (2009) 167–173. DOI: 10.1016/j.msea.2009.01.002
Fan G., Jiang Y., Tan Z., Guo Q., Xiong D.-B., Su Y., Lin R.,
Hu L., Li Z., Zhang D., Enhanced interfacial bonding andmechanical properties in CNT/Al composites fabricated byflake powder metallurgy, Carbon, 130 (2018) 333–339. DOI:
10.1016/j.carbon.2018.01.037
Fan G.L., Xu R., Tan Z.Q., Zhang D., Li Z.Q., Development of
flake powder metallurgy in fabricating metal matrix composites: A review, Acta Metallurgica Sinica-English Letters, 27(2014) 806–815. DOI: 10.1007/s40195-014-0148-x
Foppoli A.A., Maroni A., Cerea M., Zema L., Gazzaniga A., Dry
coating of solid dosage forms: an overview of processes andapplications, Drug Development and Industrial Pharmacy, 43(2017) 1919–1931. DOI: 10.1080/03639045.2017.1355923
Ghoroi C., Han X., To D., Jallo L., Gurumurthy L., Davé R.N.,
Dispersion of fine and ultrafine powders through surface
modification and rapid expansion, Chemical Engineering
Science, 85 (2013) 11–24. DOI: 10.1016/j.ces.2012.02.038
Han Y., Zhang X., Yu X., Zhao J., Li S., Liu F., Gao P., Zhang Y.,
Zhao T., Li Q., Bio-inspired aggregation control of carbon
nanotubes for ultra-strong composites, Scientific Reports, 5(2015) 11533. DOI: 10.1038/srep11533

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

He C., Zhao N., Shi C., Du X., Li J., Li H., Cui Q., An approachto obtaining homogeneously dispersed carbon nanotubes in
Al powders for preparing reinforced Al-matrix composites,
Advanced Materials, 19 (2007) 1128–1132. DOI: 10.1002/
adma.200601381
Hwang T., Lee J.K., Mun J., Choi W., Surface-modified carbon
nanotube coating on high-voltage LiNi0.5Mn1.5O4 cathodes
for lithium ion batteries, Journal of Power Sources, 322(2016) 40–48. DOI: 10.1016/j.jpowsour.2016.04.118
Jiang L., Li Z., Fan G., Cao L., Zhang D., The use of flake powder
metallurgy to produce carbon nanotube (CNT)/aluminumcomposites with a homogenous CNT distribution, Carbon,
50 (2012) 1993–1998. DOI: 10.1016/j.carbon.2011.12.057
Jiang L., Li Z.Q., Fan G.L., Zhang D., A flake powder metallurgy
approach to Al2O3/Al biomimetic nanolaminated composites
with enhanced ductility, Scripta Materialia, 65 (2011)
412–415. DOI: 10.1016/j.scriptamat.2011.05.022
Jiang Y., Wang D., Liang S., Cao F., Zou J., Xiao P., Effect of
local alloying on interfacial bonding in laminated copper
matrix composites reinforced by carbon nanotubes, Materials
Science and Engineering: A, 748 (2019) 173–179. DOI:
10.1016/j.msea.2019.01.013
Johannes L.B., Yowell L.L., Sosa E., Arepalli S., Mishra R.S.,
Survivability of single-walled carbon nanotubes during friction stir processing, Nanotechnology, 17 (2006) 3081–3084.
DOI: 10.1088/0957-4484/17/12/044
Kwon H., Estili M., Takagi K., Miyazaki T., Kawasaki A.,
Combination of hot extrusion and spark plasma sinteringfor producing carbon nanotube reinforced aluminum matrix
composites, Carbon, 47 (2009) 570–577. DOI: 10.1016/j.
carbon.2008.10.041
Kwon H., Leparoux M., Hot extruded carbon nanotube reinforced
aluminum matrix composite materials, Nanotechnology, 23(2012) 415701. DOI: 10.1088/0957-4484/23/41/415701
Kwon H., Takamichi M., Kawasaki A., Leparoux M., Investigation of the interfacial phases formed between carbon
nanotubes and aluminum in a bulk material, Materials Chemistry and Physics, 138 (2013) 787–793. DOI: 10.1016/j.
matchemphys.2012.12.062
Loa I., Raman spectroscopy on carbon nanotubes at high pressure,
Journal of Raman Spectroscopy, 34 (2003) 611–627. DOI:
10.1002/jrs.1035
Naito M., Abe H., Kondo A., Yokoyama T., Huang C.C., Smartpowder processing for advanced materials, KONA Powder
and Particle Journal, 27 (2009) 130–143. DOI: 10.14356/
kona.2009013
Naito M., Kondo A., Yokoyama T., Applications of Comminution
Techniques for the Surface Modification of Powder Materials, ISIJ International, 33 (1993) 915–924. DOI: 10.2355/
isijinternational.33.915
Nam D.H., Cha S.I., Lim B.K., Park H.M., Han D.S., Hong S.H.,
Synergistic strengthening by load transfer mechanism andgrain refinement of CNT/Al–Cu composites, Carbon, 50(2012) 2417–2423. DOI: 10.1016/j.carbon.2012.01.058
Narh K.A., Agwedicham A.-T., Jallo L., Dry coating polymer
powder particles with deagglomerated carbon nanotubes
to improve their dispersion in nanocomposites, Powder
Technology, 186 (2008) 206–212. DOI: 10.1016/j.powtec.
2007.12.004
Noguchi T., Magario A., Fukazawa S., Shimizu S., Beppu J., Seki
M., Carbon nanotube/aluminium composites with uniform
dispersion, Materials Transactions, 45 (2004) 602–604. DOI:
10.2320/matertrans.45.602
Ötles S., Lecoq O., Dodds J.A., Dry particle high-impact
coating of biopowders: coating strength, Particulate Sci-

ence and Technology, 27 (2009) 352–361. DOI: 10.1080/
02726350902993987
Qu L., Morton D.A., Zhou Q.T., Particle engineering via
mechanical dry coating in the design of pharmaceutical solid
dosage forms, Current Pharmaceutical Design, 21 (2015)
5802–5814. DOI: 10.2174/1381612821666151008151001
Sadeghi B., Cavaliere P., Nosko M., Trembošová V., Nagy Š.,
Hot deformation behaviour of bimodal sized Al2O3/Al nanocomposites fabricated by spark plasma sintering, Journal of
Microscopy, (2020). DOI: 10.1111/jmi.12947
Sadeghi B., Cavaliere P., Roeen G.A., Nosko M., ShamanianM., Trembošová V., Nagy Š., Ebrahimzadeh N., Hot rollingof MWCNTs reinforced Al matrix composites produced via
spark plasma sintering, Advanced Composites and Hybrid
Materials, 2 (2019) 549–570. DOI: 10.1007/s42114-01900095-7
Sadeghi B., Sarraf-Mamoory R., Shahverdi H.R., Surface modification of LiMn2O4 for lithium batteries by nanostructured
LiFePO4 phosphate, Journal of Nanomaterials, 2012 (2012a)
743236. DOI: 10.1155/2012/743236
Sadeghi B., Sarraf-Mamoory R., Shahverdi H.R., The effectof LiFePO4 coating on electrochemical performance ofLiMn2O4 cathode material, Iranian Journal of Chemistry andChemical Engineering (IJCCE), 31 (2012b) 29–34. https://www.sid.ir/en/journal/ViewPaper.aspx?id=276841
Sadeghi B., Shabani A., Cavaliere P., Hot rolling of sparkplasma-sintered pure aluminium, Powder Metallurgy, 61(2018a) 285–292. DOI: 10.1080/00325899.2018.1478779
Sadeghi B., Shamanian M., Ashrafizadeh F., Cavaliere P.,
Rizzo A., Friction stir processing of spark plasma sinteredaluminum matrix composites with bimodal micro- andnano-sized reinforcing Al2O3 particles, Journal of Manufacturing Processes, 32 (2018b) 412–424. DOI: 10.1016/j.
jmapro.2018.03.013
Sadeghi B., Shamanian M., Cavaliere P., Ashrafizadeh F.,
Effect of processing parameters on the microstructuraland mechanical properties of aluminum–carbon nanotube
composites produced by spark plasma sintering, International
Journal of Materials Research, 109 (2018c) 900–909. DOI:
10.3139/146.111686
Sadeghi B., Shamanian M., Cavaliere P., Ashrafizadeh F.,
Sanayei M., Szpunar J.A., Microstructural and mechanicalbehavior of bimodal reinforced Al-based composites
produced by spark plasma sintering and FSP, International
Journal of Advanced Manufacturing Technology, 94 (2018d)
3903–3916. DOI: 10.1007/s00170-017-1144-x
Salimi S., Izadi H., Gerlich A.P., Fabrication of an aluminum–
carbon nanotube metal matrix composite by accumulativeroll-bonding, Journal of Materials Science, 46 (2010)
409–415. DOI: 10.1007/s10853-010-4855-z
Sharma R., Setia G., Mechanical dry particle coating on cohesive
pharmaceutical powders for improving flowability—areview, Powder Technology, 356 (2019) 458–479. DOI:
10.1016/j.powtec.2019.08.009
Tan Z., Li Z., Fan G., Li W., Liu Q., Zhang W., Zhang D.,
Two-dimensional distribution of carbon nanotubes in copper
flake powders, Nanotechnology, 22 (2011) 225603. DOI:
10.1088/0957-4484/22/22/225603
Tokunaga T., Kaneko K., Horita Z., Production of aluminummatrix carbon nanotube composite using high pressure
torsion, Materials Science and Engineering: A, 490 (2008)
300–304. DOI: 10.1016/j.msea.2008.02.022
Wei D., Dave R., Pfeffer R., Mixing and characterization ofnanosized powders: an assessment of different techniques,
Journal of Nanoparticle Research, 4 (2002) 21–41. DOI:

227

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

10.1023/A:1020184524538
Wei H., Li Z.Q., Xiong D.B., Tan Z.Q., Fan G.L., Qin Z., Zhang
D., Towards strong and stiff carbon nanotube-reinforced
high-strength aluminum alloy composites through a microlaminated architecture design, Scripta Materialia, 75 (2014)30–33. DOI: 10.1016/j.scriptamat.2013.11.014
Yang X., Liu E., Shi C., He C., Li J., Zhao N., Kondoh K.,
Fabrication of carbon nanotube reinforced Al composites
with well-balanced strength and ductility, Journal of Alloys
and Compounds, 563 (2013) 216–220. DOI: 10.1016/j.
jallcom.2013.02.066
Yang X., Zou T., Shi C., Liu E., He C., Zhao N., Effect ofcarbon nanotube (CNT) content on the properties of in-situ
synthesis CNT reinforced Al composites, Materials Scienceand Engineering: A, 660 (2016) 11–18. DOI: 10.1016/j.
msea.2016.02.062
Zhang K., Choi H.J., Smart polymer/carbon nanotube nanocomposites and their electrorheological response, Materials, 7(2014) 3399–3414. DOI: 10.3390/ma7053399
Zhao Q., Wagner H.D., Raman spectroscopy of carbon-nanotubebased composites, Philosophical Transactions of the Royal
Society of London Series A: Mathematical, Physical andEngineering Sciences, 362 (2004) 2407–2424. DOI: 10.1098/
rsta.2004.1447
Zheng K., Kunnath K., Ling Z., Chen L., Davé R.N., Influenceof guest and host particle sizes on dry coating effectiveness: when not to use high mixing intensity, Powder
Technology, 366 (2020) 150–163. DOI: 10.1016/j.powtec.
2020.02.059
Zhou S.-M., Zhang X.-B., Ding Z.-P., Min C.-Y., Xu G.-L., Zhu
W.-M., Fabrication and tribological properties of carbon
nanotubes reinforced Al composites prepared by pressurelessinfiltration technique, Composites Part A: Applied Scienceand Manufacturing, 38 (2007) 301–306. DOI: 10.1016/j.
compositesa.2006.04.004

Authors’ Short Biographies
Behzad Sadeghi
Dr. Behzad Sadeghi is currently a Postdoctoral Researcher at Shanghai Jiao Tong University,
China. He received his PhD in 2018 from Isfahan University of Technology, Iran. He also worked at
Salento university, Italy from 2016 to 2017. His research mainly focuses on microstructure-property
relationships and understanding the underlying deformation mechanisms in advanced engineering
materials especially aluminum matrix composites.

Genlian Fan
Dr. Genlian Fan is an Associate Professor at Shanghai Jiao Tong University. She received her BS
degree and PhD degree from Xi’an Jiaotong University in 2003 and 2009, respectively, followed bypostdoctoral research at Shanghai Jiao Tong University. She has authored and coauthored over 80
papers. Her research interests include nanocarbon reinforced metal matrix composites, smart powder
processing of the advanced composites.

Zhanqiu Tan
Dr. Zhanqiu Tan is an Assistant Researcher in Shanghai Jiao Tong University. He received his
Ph.D. degree in Materials Science and Engineering from Shanghai Jiao Tong University in 2014,
and completed the postdoctoral research here in 2014–2016. He has authored and coauthored over
60 papers. His current research focuses on the high-performance nanocarbon reinforced aluminum
matrix composites for light-weight structural applications.

228

Behzad Sadeghi et al. / KONA Powder and Particle Journal No. 39 (2022) 219–229

Authors’ Short Biographies
Zhiqiang Li
Prof. Zhiqiang Li is a Professor at Shanghai Jiao Tong University. He received his BS (1996), MS(1998) and PhD (2001) degrees from Harbin Institute of Technology. He worked in State Key Lab
of Metal Matrix Composites in Shanghai Jiao Tong University since 2002. His research interests
focus on the bioinspired fabrication techniques, architecture design, and carbon-based metal matrix
nanocomposites. He has authored and coauthored more than 100 journal publications and held over
20 patents.

Akira Kondo
Dr. Akira Kondo received BS and MS degrees in chemical engineering from Nagoya University,
Japan in 1989 and 1991, respectively. He received PhD degree in material science from Osaka University in 1999. He was with Hosokawa Micron Corp. from 1991 to 2005, where he engaged in the
R&D of powder processing technology. He became a specially designated researcher at the Joining
and Welding Research Institute (JWRI), Osaka University in 2005, and is engaged in the R&D of
powder processing for advanced materials.

Makio Naito
Prof. Makio Naito is a Professor at the Joining and Welding Research Institute (JWRI), Osaka
University in Japan. He served as the President of The Society of Powder Technology, Japan from2015 to 2019. His publications cover a wide range of studies in the fields of advanced materials andnovel powder processing and characterization. He has received several prestigious awards including
the Richard M. Fulrath Award from the American Ceramic Society (ACerS) in 2002 and the KONA
Award in 2019. He has been a Fellow of the ACerS since 2010, and serves on the ACerS Board of
Directors from 2020.

229

KONA Powder and Particle Journal No. 39 (2022) 230–239/https://doi.org/10.14356/kona.2022016

Original Research Paper

Correlating Granule Surface Structure Morphology andProcess Conditions in Fluidized Bed Layering Spray
Granulation †Maike Orth *, Paul Kieckhefen, Swantje Pietsch and Stefan Heinrich
Institue of Solids Process Engineering and Particle Technology, Hamburg University of Technology, Germany

Abstract
A workflow for developing a multidimensional, linear correlation between the process conditions during
fluidized bed spray granulation and the surface morphology of the resulting granules is presented. Spray coating
experiments with Cellets®500 particles and sodium benzoate solution were performed in a lab-scale fluidized bed
varying liquid spray rate, fluidization air flow rate, fluidization air temperature, spray air temperature and sprayatomization pressure. To characterize the surface structure, the surface roughness of the coated particles wasquantified using confocal laser-scanning microscopy. The roughness was correlated to the process conditions, andthe resulting correlation was rigorously analyzed for the importance and co-linearities of the individual processparameters using a principal component analysis. The surface roughness is strongly dependent on the spray rateof the coating solution, the fluidization air temperature and the atomization pressure at the nozzle. In general, wetprocess conditions and large droplets with a low initial velocity favor the formation of particles with a rough surface
structure, while dry conditions and fine droplets with a high velocity result in granules with a smooth and compact
coating layer.
Keywords: fluidized bed spray granulation, coating, surface roughness, laser-scanning microscopy, productproperty correlation

1. Introduction
1.1 Motivation
Fluidized bed spray granulation is a key process usedin various industries for the production of high-quality
granular solids. The processing of particles in a fluidized
bed with liquid injection allows the production of a wide
variety of particles for different applications. Products fromspray granulation include pharmaceuticals, food powders,fertilizers and detergents, among others. The variation ofprocess conditions is used to obtain defined product properties like certain sizes, shapes or structures, which thendefine the application properties like flowability, stability
or taste and odor masking (Dewettinck and Huyghebaert,
1999). A coating can also be applied to protect the corefrom environmental influences and prevent oxidation or
moisture absorption (Werner et al., 2007). Controlled re†*

Received 14 May 2021; Accepted 6 August 2021
J-STAGE Advance published online 25 September 2021
Corresponding author: Maike Orth;Add: Denickestraße 15, 21073 Hamburg, Germany
E-mail: maike.orth@tuhh.de
TEL: +49-40-42878-4279 FAX: +49-40-42731-3621

230

lease of active substances is another application in which
the structure of the coating is essential (Turton, 2008; Tzika
et al., 2003). A detergent, for example, requires a shortrelease time, whereas fertilizers should usually be released
at a defined rate over a longer time period.
To induce particle growth, a solid-containing liquid
is sprayed onto the fluidized particles. The size increase
occurs via either agglomeration or layering granulationor coating. In the case of agglomeration, the liquid acts
as a binder between the primary particles. When two wet
particles collide, a liquid bridge forms and solidifies after
the liquid evaporates due to the hot fluidization gas. Thus,
agglomerates are formed by connecting several primaryparticles via solid bridges (Fries, 2012). In layering granulation or coating, the droplets come into contact with theparticle surface, where they spread and form a liquid filmaround the particle. Due to evaporation of the liquid, thisfilm becomes a solid shell. By repeating these steps, several
coating layers can be added to the particle (Uhlemann and
Mörl, 2000). Usually, the application of thin layers onto theparticle surface is defined as coating, whereas granulationrefers to a layering growth resulting in an onion-like structure (Rieck et al., 2015). In this work the particle growth
due to layering is defined as granulation.

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

The formation of a coating layer during the fluidized bed
spray granulation depends on several micro-processes thatare affected by the process conditions. The deposition andspreading of droplets on the particles depend on propertiesof the particle surface—such as roughness and chemicalcomposition—as well as the droplet characteristics. The
latter includes not only the size and velocity of the droplets, but also coating solution properties like viscosity andsurface tension. Another important micro-process is theevaporation of the liquid due to the heated fluidization
gas, which is strongly influenced by the drying conditions(Fries, 2012; Uhlemann and Mörl, 2000). Depending on
the chosen material system, additional phenomena likecrystallization or penetration of the solution into the poresof porous particles can occur and influence the granuleproperties (Hoffmann et al., 2015; Uhlemann and Mörl,
2000). The knowledge of the effect of different process parameters on the micro processes in the fluidized bed and theresulting granule structures is invaluable for the productionof tailor-made particles.

1.2 Previous works
The influence of process parameters on different particle
properties has been investigated in several previous works.
In most of these studies, either a small set of parameters
was chosen or a one-factor-at-a-time approach was used,meaning that interaction between the parameters is notconsidered. Rieck et al. (2015) and Hoffmann et al. (2015)
investigated the influence of the drying conditions on thelayer porosity for the coating of glass and γ-Al2O3 particles
with sodium benzoate. Their experiments were carriedout in top-spray configuration at different fluidization air
inlet temperatures and spray rates of the coating solution.
The overall drying conditions were described by a drying potential, which was correlated to the shell porosity
measured by X-ray micro-tomography. For both glass and
γ-Al2O3, a linear decrease of the porosity was observedwith increasing drying potential, characterized by a higher
air temperature and lower spray rate.
The drying conditions were also examined by Hampel(2015). Cellulose particles (Cellets®200) were coated withsodium benzoate in a Wurster fluidized bed process andqualitatively analyzed afterwards regarding their surface
morphology via scanning electron microscopy. The varied
parameters were the gas inlet temperature, the spray rate of
the coating solution and the fluidization air mass flow rate.
The increase of the gas temperature led to the formation ofa more compact coating, whereas the increase of the gas
mass flow resulted in a higher shell porosity. No unambiguous change in surface morphology was observed whenvarying the mass flow of the coating liquid.
Tzika et al. (2003) observed non-uniform coatings andserious surface defects for fertilizer particles that were

coated with a polymer latex at very low or very highfluidization air velocities. This poor coating quality was attributed to the low frequency at which the particles entered
the coating zone for the low air velocity and to the reduced
time in the coating zone per pass in addition to frequentcollisions of the particles with each other and the wall forthe high velocity. The best coating quality was achieved bychoosing an intermediate air fluidization flow rate.
The continuous granulation of sodium benzoate in ahorizontal fluidized bed with sieve-milling circuit wasinvestigated by Diez et al. (2018). Similar to Rieck etal. (2015) and Hoffmann et al. (2015), Diez et al. (2018)
produced particles with a compact and smooth surface athigh air temperatures and low liquid spray rates, whereas
low temperatures and high spray rates resulted in a higher
surface roughness.
Schmidt et al. (2017) performed coating experimentswith γ-Al2O3 particles and a suspension of limestone,hydroxy propyl methyl cellulose and water at different
atomization pressures of the top-spray nozzle used for the
injection of the suspension. The shell porosity was found to
decrease with increasing pressure.
The surface morphology and layer thickness of particles
coated in a fluidized bed were also studied by Depypere etal. (2009) and Perfetti et al. (2010). Depypere et al. (2009)
coated glass particles with sodium caseinate and gelatinehydrolysate in bottom-spray configuration and in top-spray
configuration at three different nozzle heights. The coatings
were analyzed via confocal laser-scanning microscopy.
For sodium caseinate coatings, the coating thickness anduniformity decreased with increasing distance between thenozzle tip and the fluidized bed, meaning that the particles
from the bottom-spray set-up had the most homogeneous
coating while the highest top-spray nozzle position resulted
in a wider layer thickness distribution. With gelatine hydrolysate as coating material, however, the highest coating
quality was achieved at the lowest nozzle position in topspray configuration.
Perfetti et al. (2010) used X-ray micro-tomography tocharacterize polymer-coated sodium benzoate and cellulose particles that were coated with polyvinyl alcohol andhydroxy propyl methyl cellulose in a top-spray fluidized
bed. The coating layer thickness was determined withdifferent methods based on the two-dimensional andthree-dimensional particle structures obtained from thetomography data. Most results were in good agreementwith the theoretical thickness as well as with each other.
Furthermore, the micro-CT allowed the measurement ofseveral structural parameters of the coating shell, including
surface density, porosity and pore volume.
In these previous works, the coating quality was either
evaluated qualitatively or a one-dimensional approach
was used to correlate individual parameters or the drying potential with the surface morphology. However, a231

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

multidimensional correlation between process conditions
and granule surface morphology is yet to be developed.
Such a correlation is crucial as individual parameters are
not able to reflect all the parameters involved during fluidized bed spray granulation. For example, it was alreadyshown that the shell porosity is influenced by the atomization pressure, but this value is not included into the drying
potential. Thus, a correlation is needed that indicates theinfluencing parameters qualitatively and quantitatively.

1.3 Structure
To develop a multidimensional, linear correlation thatconnects the process parameters and the granule surface
roughness, coating experiments were carried out in a labscale fluidized bed. As a result of the literature study andprevious investigations, the liquid spray rate, the fluidization gas flow rate and inlet temperature, the spray air temperature and the spray atomization pressure were chosen asvarying parameters. To investigate the influence of these
five process parameters within a reasonable amount of runs
while still obtaining a significant result, the experiments
were statistically planned. The resulting granules wereanalyzed regarding their surface roughness via laserscanning microscopy. Therefore, a 3D-profile of the particle
surface was created which was then evaluated in a definedmeasurement area. The roughness was correlated to theprocess parameters and the resulting linear correlation was
rigorously analyzed for the importance and co-linearities ofthe parameters using a principal component analysis.

2. Materials and methods

sodium benzoate was used. Sodium benzoate is a white,
crystalline powder with a good solubility in water that isused as a preservative in the food industry.

2.2 Coating experiments
The coating experiments were carried out in the
ProCell® 5 LabSystem with the fluidized bed processchamber GF3 (Glatt, Germany), which is shown in Fig. 1.
The diameter at the gas inlet of the chamber is 180 mm.
For the injection of the coating solution, a two-fluid nozzle
of type 970-S4 (Schlick, Germany) with an orifice size of
1.2 mm was installed in bottom-spray configuration in thecenter of the sieve plate distributor (mesh size 105 μm).
The solution is conveyed to the nozzle with a peristaltic
pump (Medorex TB, Germany) and compressed air is used
to atomize the liquid into fine droplets. The experiments
were performed batch-wise with an initial bed mass of 2 kgof Cellets®500 per batch. For each run, 1 kg of the 30 wt%
sodium benzoate solution was injected into the processchamber.
As previously mentioned, five parameters were varied:
the spray rate of the coating solution ṁl, the fluidization
air volume flow Vair , the fluidization air inlet temperature
Tin, the spray air temperature Tat and the spray atomizationpressure pat. The different values that were set for eachparameter are shown(11) in Table 2. The limits were chosen insuch a way that a broad range was covered while the stability of the process was still maintained. An overview ofthe experiments, including the process parameters, average
bed temperature, theoretically expected outlet air temperature after evaporation of the water and surface roughness

2.1 Materials
For all experiments, Cellets®500 (Harke Pharma GmbH,Germany) with a diameter between 500 and 710 μm wereused as primary particles. Cellets® consist of microcrystalline cellulose and are often utilized as pharmaceutical
excipient. Because of their non-porous surface, no droplet
imbibition occurs during the coating process. The material
provides a smooth surface and high sphericity. In addition,
the Cellets® are chemically inert and insoluble in water,which makes them suitable for coating experiments with asalt solution. Table 1 lists the main properties of the particles. As coating material, an aqueous solution with 30 wt%

Fig. 1

Scheme of the experimental fluidized bed set-up.

Table 2 Process parameters and values used in coating experiments.

Table 1 Properties of Cellets®500.

ṁ1 [g/min] Vair [m3/h]

Tin [°C]

Tat [°C]pat [bar]

Sauter diameter

639

μm

Sphericity

0.96

–

10

80

50

20

0.5

Surface roughness

1.5

μm

15

105

85

70

1.75

Solid density

1445

kg/m3

20

120

3.0

(41): table-cell

232

130

120

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

data, is provided on J-STAGE Data website.

2.3 Design of experiments
A design of experiments approach is used to investigate
the effects of multiple input variables on a response at thesame time. In this case, the effect of the process parameterson the surface roughness was investigated. By planningthe experiments statistically, interactions between theparameters can be considered while the number of runs is
reduced compared to the full factorial experimental plan.
For the granulation experiments in this work, a three-level
experimental plan including the five parameters listed inTable 2 was created using the statistics software Minitab
18 (Minitab, USA). For each parameter an upper and lower
limit was defined. In addition, the mean value of these limits was chosen as the third level. Since the three-level full
factorial approach consisted of 243 experiments, the response surface methodology with central composite design
was used instead. Choosing the half fraction of the thereby
obtained design resulted in a total of 29 experiments.

2.4 Surface roughness measurement
2.4.1 Confocal laser-scanning microscopy
In a conventional optical microscope, the entire sample
is illuminated by a light source, so the photodetector, where
the light reflected from the sample forms an image, detects
not only the sample itself but also unfocused planes in the
background. In contrast, only a small part of the sample
is illuminated at each time in confocal laser-scanningmicroscopy. The surface of a sample can be scanned bymoving the position of the focal point on the sample surface. By scanning the image area within the field of view,
a two-dimensional image at a given height is captured.
This scan is repeated several times with the objective lensat different Z-axis positions in order to reconstruct thethree-dimensional structure of the sample and gather height
information. The confocal laser technology allows for theacquisition of images with a large depth of field that are infocus across the entire screen (Keyence, 2015).

2.4.2 Roughness quantification
The surface roughness was measured using the 3D Laser
Scanning Confocal Microscope VK-X160K (Keyence,
Japan). The microscope uses a two-way light source withlaser light and white light. The light emitted from thelaser light source is focused on the sample surface by theobjective lens with a magnification of 10×, 20×, 50× or
100×. Based on the detected height information and laser
intensity, a 3D-profile of the particle surface is constructed.
The relatively short measurement time compared to othersurface morphology characterization methods, like X-ray
micro-tomography, as well as the possibility to quantify thesurface structure make the laser-scanning microscopy theideal analysis method for this work.
To quantify the surface morphology of the coated particles, the surface roughness was evaluated. Roughness consists of a sequence of peaks and valleys forming a complex
shape due to their difference in height, depth and intervals(Keyence, 2015). A wide variety of parameters, based either on lines or areas on the surface, can be used to describe
the roughness. These parameters are defined in DIN EN
ISO 4287:2010-07 (2010) and DIN EN ISO 25178-2:2012(2012). In this work, the arithmetical mean height Sa, oneof the most commonly used roughness quantifiers, wasused to characterize the roughness. The arithmetical meanheight is a surface-based parameter which describes theaverage height difference of each point on the surface fromthe mean height of the particle surface within a definedmeasurement area A:
Sa 

1∬ h x, y  h dx dy
A A

(1)

The measured 3D-profiles of the coated particles weresmoothed using a Gauss filter to reduce measurement(1)
noise. Additionally, the surface shape was corrected withimage processing to avoid an influence of the particle shapeon the measured roughness. The surface-based arithmeticalmean height was evaluated at 50× magnification over thewhole surface area that was covered by the microscope. For
each sample three particles were analyzed at three different
positions on the surface of each particle.
To validate the observations regarding the surface morphology, particles from two experiments with extremely
different process conditions—due to the parameters being
set to either their minimum or maximum values in theseruns—were analyzed with a scanning electron microscope(type: Supra VP55, Zeiss, Germany).

3. Results and discussion
3.1 Regressing process parameters and granuleroughness
A linear regression model is fitted to the roughness datausing the ordinary least squares method. This allows forthe pre-factors for a linear equation connecting the fivevaried process parameters to the surface roughness to be
determined. With a principal component analysis, principal
components that reduce the variance in a data set can be
identified.
To perform the principal component analysis, a matrix
A is created in which each column contains the data forone experiment, including process parameters during thecoating experiment as well as the granule surface roughness. Afterwards, the eigenvalues and eigenvectors of233

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

the corresponding covariance matrix Cov(A) = AAT aredetermined. The distribution of the residual decreases with
the number of included components. Fig. 2 shows how
the residual distribution changes when a certain numberof principal components is included in the model. It canbe seen that the distribution of the residual can be reduced
to a reasonable range by including four components in themodel. To avoid over-fitting of the model, the componentsthat correspond to the lowest eigenvalues are dropped andonly statistically significant parameters are considered.

3.2 Linear correlation for the surface roughness
During the fluidized bed spray granulation, the particle surface structure formation is dependent on several
micro-processes occurring within the droplets and at thesolid-liquid interface. The droplet characteristics and theinteraction of solid and liquid on the other hand are influenced by the process variables that determine the overall
state of the fluidization air as well as the conditions in thespray zone and the drying zone of the fluidized bed. Using
the previously described approach to create a linear model
connecting the chosen process parameters to the granulesurface roughness, the following correlation for the arithmetical mean height is obtained:
S a  8.718  0.085m l  0.038Tin  0.843 pat

however, did not show a significant effect on the surface
structure and were therefore removed from the model.
As the signs in Eqn. (2) suggest, a high surface roughness is achieved at low fluidization air temperatures, low
atomization pressures and high spray rates of the coating
solution. Conversely, at high air temperatures, high spraypressures and low liquid spray rates, particles with smoothand compact surfaces are produced. These observations are
confirmed by the SEM images of the granules in Fig. 3. As
predicted by the model, the particle coated at ṁl = 20 g/min,
Tin = 50 °C and pat = 0.5 bar has a significantly rougher
and more uneven surface than the particle coated at ṁl =10 g/min, Tin = 120 °C and pat = 3.0 bar.
As depicted in Fig. 4, the roughness values predictedby the linear model show an overall good agreementwith the measured data. Only the two highest roughness
values are overestimated by the correlation and lie significantly below the 45°-line. With increasing roughness theparticle structure becomes more irregular, which makes(2)

According to the correlation, the surface roughness
Sa (2)
depends on three of the five investigated parameters:
the fluidization air temperature Tin in °C, the atomizationpressure pat in bar and the liquid spray rate ṁl in g/min. The
spray air temperature and the fluidization air volume flow,

Fig. 2 Normalized residual distribution in dependence of number ofincluded principal components (eigenvectors).

Fig. 3 SEM images of Cellets®500 particles coated with sodium benzoate at different process conditions. Left: ṁ1 = 10 g/min, Vair = 130 m3/h,
Tin = 120 °C, Tat = 20 °C, pat = 3.0 bar; right: ṁ1 = 20 g/min, Vair = 80 m3/h, Tin = 50 °C, Tat = 20 °C, pat = 0.5 bar.

(31): fig-caption
234(31): fig-caption

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

the characterization of the overall surface morphology
challenging. Furthermore, there are few data points at highroughness values, which makes the fitting of the modeldifficult in this roughness range. For values below 9 μm,
where most of the data points lie, the model shows a goodfit. Moreover, it has to be considered that, while the surface
structure analysis via laser-scanning microscopy is an improved characterization method in terms of measurement
time compared to the X-ray tomography and scanningelectron microscopy approaches used in previous studies,
the amount of analyzed granules is still very low comparedto the whole particle bed for each experiment.
An advantage of the linear model is the easy interpretation since the influence of each variable on the response canbe directly seen in the correlation. This allows for the analysis of the individual process parameters and their impact

on the formation of the coating and the resulting surface
morphology. In the following sections, the influence of thethree primary influencing factors on the surface structure isdiscussed in detail.

In Fig. 5, the partial dependence of the surface roughness on the spray rate of the sodium benzoate solution isshown. The higher roughness at an increased spray rate
predicted by the linear model is confirmed by the laserscanning microscope images in Fig. 6. At the maximum
spray rate of 20 g/min, a rough and irregular surface wasformed, whereas the particles from the experiment withthe lowest spray rate of 10 g/min and otherwise similarparameters have a smooth surface without any noticeable
peaks. This dependence of the roughness on the spray rate

Fig. 4 Surface roughness predicted by the linear model in Eqn. (2)compared to the surface roughness measured via confocal laserscanning microscopy.

Fig. 5 Partial dependence of the surface roughness on the liquid sprayrate. The crosses mark the experimentally investigated spray rates.

3.2.1 Influence of the liquid spray rate

Fig. 6 Laser-scanning microscope images of Cellets®500 particles coated with sodium benzoate at different process conditions. Within each column
all remaining process parameters were the same for both experiments.

235

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

can be explained by the crystallization of sodium benzoate
in the evaporating solution droplets on the particle surface.
At low spray rates, the drying conditions in the fluidized
bed are intense due to the low amount of liquid in the process chamber. In this case, the liquid evaporates quickly,
causing a high over-saturation of sodium benzoate in theshrinking droplet. Due to the short drying time, nuclei
formed in the droplets do not have enough time to growinto larger crystals. These precipitated nuclei form a dense
coating with a smooth surface. High spray rates, however,cause a large temperature drop over the fluidized bed due tothe high amount of liquid that evaporates. This effect can beobserved in the theoretical outlet air temperature given on
J-STAGE Data website, that corresponds to the decreased
fluidization air temperature after passing the particle bed
due to the evaporation of the water in the process chamber.
Consequently, at high spray rates and therefore moderate
drying conditions, the slow evaporation of water and longdrying time of the droplets allow the growth of larger
sodium benzoate crystals on the particle surface, resulting
in a rough and irregularly shaped coating. This crystalline
surface structure formed under wet process conditions
is especially apparent in the SEM images in Fig. 3. The
dependence of the crystallization of sodium benzoate on
the drying conditions during fluidized bed coating was also
observed by Rieck et al. (2015) and Hoffmann et al. (2015).

idization air has a major impact on the drying conditions
during the granulation process. Due to the reduced relative
humidity, the heated air can absorb a higher amount ofwater, which results in a high drying rate. Under these
conditions, small crystal seeds are precipitated from thedroplets due to the fast evaporation and short drying
time rather than growing into larger crystals. The smoothsurface that is formed under intense drying conditions at
the highest investigated temperature of 120 °C is depicted
in Fig. 5. Conversely, the particles coated at 50 °C andotherwise similar parameters show a rough surface withmany visible peaks and valleys. At these moderate drying
conditions, due to the lower air temperature, crystal growthis enhanced as previously explained, and the larger crystals
form a rougher and irregular surface. This observationis confirmed by the SEM images in Fig. 3, in which thesurface morphology of the right particle is clearly definedby sodium benzoate crystals, whereas no such crystal structures are visible on the left particle’s surface.

3.2.3 Influence of the atomization pressure

As shown in the partial dependence plot in Fig. 7, anincrease in the fluidization air inlet temperature results ina lower roughness and therefore smoother particle surface.
Just like the liquid spray rate, the temperature of the flu-

The partial dependence of the surface roughness on
the atomization pressure in Fig. 8 shows a decreasingarithmetical mean height with increasing pressure. This
trend is also apparent in the microscope images in Fig. 5,
in which the surface formed at the minimum pressure of
0.5 bar is significantly rougher than the surface of theparticle coated at the maximum atomization pressure of
3.0 bar. The droplet characteristics during granulation arestrongly influenced by the nozzle parameters. The pressureof the spray air determines the droplet size as well as theinitial droplet velocity. At higher pressures the shear stressacting on the injected liquid is also higher, which causes

Fig. 7 Partial dependence of the surface roughness on the fluidization
air inlet temperature. The crosses mark the experimentally investigatedtemperatures.

Fig. 8 Partial dependence of the surface roughness on the spray atomization pressure. The crosses mark the experimentally investigatedpressures.

3.2.2 Influence of the fluidization air inlet
temperature

236

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

the formation of finer droplets with high velocity. Oncea droplet collides with a particle, this high velocity leads
to a homogeneous spreading of the droplet on the particle
surface. The fast and even spreading of the droplets before
the water completely evaporates leads to the formation of asmooth and uniform coating. Furthermore, existing surface
defects can be filled by the small liquid droplets, whichfurther increases the smoothness of the surface. In contrast, the larger droplets produced at low nozzle pressures
have a lower velocity upon impact with the particles, thus
spreading in a less homogeneous way and creating a more
uneven coating.
Besides the spray air pressure, the droplet characteristics
are dependent on the properties of the spray solution, likeviscosity and surface tension. The surface tension, alongwith the solid-vapor and solid-liquid interfacial energy,
determine the contact angle of a droplet on the particle
surface, which characterizes the wetting behavior andindicates, how well a liquid spreads on a solid surface.
The viscosity influences the flow behavior of the coating
solution and therefore the spreading velocity of the dropletson the particle surface. Due to the evaporation of the liquidin the fluidized bed, the viscosity of a droplet is not constant and increasing with the decreasing water content andtherefore increasing solid concentration within the droplet.
In combination with the droplet size and velocity thesefactors strongly influence the deposition of the dropletson the particle surface and therefore the resulting granulemorphology.

4. Conclusions
To investigate the influence of process conditions on
surface morphology, fluidized bed spray granulation experiments were performed with different process parameter
combinations according to a statistical experimental plan.
To characterize the surface structure, the roughness wasmeasured via confocal laser-scanning microscopy. Compared to the surface characterization methods used in mostprevious works, this roughness analysis is advantageous
in terms of measurement time and the possibility of quantifying the morphology. To connect the surface structure
to the process parameters, a linear model was fitted to theroughness data. A principal component analysis was used
to identify the principal components with significant impact on the roughness.
It can be concluded that the surface roughness is primarily influenced by the drying conditions in the fluidized
bed and the properties of the injected liquid droplets. The
former depends on the spray rate of the coating solution,
which determines the amount of liquid introduced into theprocess chamber per time step, and the inlet temperatureof the fluidization air, which impacts the amount of waterthat the air can absorb. It was shown that moderate drying
conditions lead to the formation of a coating with a roughsurface, whereas particles with a smooth surface were
produced at high drying rates. This dependence of theroughness on the drying parameters is explained by the
crystallization of sodium benzoate. Apart from the properties of the coating solution, the droplet characteristics areaffected by the spray atomization pressure at the two-fluid
nozzle in such a way that finer droplets with a higher initial
velocity are formed at higher pressures. Consequently, asmooth surface was observed for particles coated at highatomization pressures, while a decrease in atomizationpressure led to higher roughness values.
The correlation obtained in this work allows the prediction of the surface roughness for any combination of
the five investigated process parameters. To improve theprediction of product properties in fluidized bed spraygranulation and gain a further understanding of the process,the work flow presented in this study can be applied toother material systems, in which different micro-processes
and parameters might be important for the surface structureformation, as well as different apparatus geometries andconfigurations.
Future studies will be concerned with the applicationof different granulator geometries, like spouted beds thatare used for coating (Pietsch et al., 2018), and scale-up topilot-scale granulators with different mixing times (Diez etal., 2019), as well as utilization of the CFD-DEM method(Kieckhefen et al., 2020) to correlate mixing times andparticle-scale drying conditions with the resulting surface
structures.

Acknowledgements
Maike Orth acknowledges funding from the German
Research Foundation within the DFG Graduate School
GRK 2462 “Processes in natural and technical ParticleFluid-Systems (PintPFS)” (Project No. 390794421). Paul
Kieckhefen acknowledges funding from BASF SE.

Nomenclature
measurement area for surface roughness (μm 2)
height at one point of the particle surface (μm)
mean height of the particle surface (μm)
hṁ1liquid spray rate (g/min)spray atomization pressure (bar)
pat
(21):
spray air temperature (°C)
Tat Nomenclature
fluidization air inlet temperature (°C)
Tin
Vair
fluidization air flow rate (m3/h)Ah(22): Nomenclature
237

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

Data Availability Statement
The experimental data from spray granulation experiments and surface roughness measurements is available
publicly in J-STAGE Data (https://doi.org/10.50931/data.
kona.16656814).

References
Depypere F., Van Oostveldt P., Pieters J.G., Dewettinck K.,
Quantification of microparticle coating quality by confocal
laser scanning microscopy (CLSM), European Journal of
Pharmaceutics and Biopharmaceutics, 73 (2009) 179–186.
DOI: 10.1016/j.ejpb.2009.04.007
DIN EN ISO 4287:2010-07, Geometrical Product Specifications(GPS)—Surface Texture: Profile Method—Terms, Definitions and Surface Texture Parameters, DIN (Deutsches
Institut für Normung e.V.), Berlin, 2010.
DIN EN ISO 25178-2:2012 Geometrical Product Specifications(GPS)—Surface Texture: Areal—Part 2: Terms, Definitions
and Surface Texture Parameters, DIN (Deutsches Institut für
Normung e.V.), Berlin, 2012.
Dewettinck K., Huyghebaert A., Fluidized bed coating in foodtechnology, Trends in Food Science & Technology, 10 (1999)
163–168. DOI: 10.1016/S0924-2244(99)00041-2
Diez E., Kieckhefen P., Meyer K., Bück A., Tsotsas E., Heinrich
S., Particle dynamics in a multi-staged fluidized bed: particle
transport behavior on micro-scale by discrete particle modelling, Advanced Powder Technology, 10 (2019) 2014–2031.
DOI: 10.1016/j.apt.2019.05.025
Diez E., Meyer K., Bück A., Tsotsas E., Heinrich S., Influence ofprocess conditions on the product properties in a continuous
fluidized bed spray granulation process, Chemical Engineering Research and Design, 139 (2018) 104–115. DOI:
10.1016/j.cherd.2018.09.032
Fries L., Discrete particle modeling of a fluidized bed granulator (Dissertation), Cuvillier Verlag, 2012. ISBN:9783954042456.
Hampel N.A., Diskontinuierliches und kontinuierliches Pelletcoating im Wurster-Wirbelschichtprozess (Dissertation),
Otto-von-Guericke-Universität Magdeburg, 2015. http://dx.doi.org/10.25673/4340
Hoffmann T., Rieck C., Bück A., Peglow M., Tsotsas E., Influence238

of granule porosity during fluidized bed spray granulation,
Procedia Engineering, 102 (2015) 458–467. DOI: 10.1016/j.
proeng.2015.01.189
Keyence, 3D Laser Scanning Confocal Microscope VK-X250K/
X260K, VK-X150K/X160K, VK-X120K/X130K: User’s
Manual, 2015.
Kieckhefen P., Pietsch S., Dosta M., Heinrich S., Possibilities
and limits of computational fluid dynamics-discrete element
method simulations in process engineering: a review ofrecent advancements and future trends, Annual review ofchemical and biomolecular engineering, 11 (2020) 397–422.
DOI: 10.1146/annurev-chembioeng-110519-075414
Perfetti G., Van de Casteele E., Rieger B., Wildeboer W.J.,
Meesters G.M.H., X-ray micro tomography and image
analysis as complementary methods for morphological characterization and coating thickness measurement of coatedparticles, Advanced Powder Technology, 21 (2010) 663–675.
DOI: 10.1016/j.apt.2010.08.002
Pietsch S., Kieckhefen P., Heinrich S., Müller M., Schönherr M.,
Kleine Jäger F., CFD-DEM modelling of circulation frequencies and residence times in a prismatic spouted bed, Chemical
Engineering Research and Design, 132 (2018) 1105–1116.
DOI: 10.1016/j.cherd.2018.01.013
Rieck C., Hoffmann T., Bück A., Peglow M., Tsotsas E., Influenceof drying conditions on layer porosity in fluidized bed spraygranulation, Powder Technology, 272 (2015) 120–131. DOI:
10.1016/j.powtec.2014.11.019
Schmidt M., Bück A., Tsotsas E., Shell porosity in spray fluidized
bed coating with suspensions, Advanced Powder Technology, 28 (2017) 2921–2928. DOI: 10.1016/j.apt.2017.08.020
Turton R., Challenges in the modeling and prediction of coatingof pharmaceutical dosage forms, Powder Technology, 181(2008) 186–194. DOI: 10.1016/j.powtec.2006.12.006
Tzika M., Alexandridou S., Kiparissides C., Evaluation of themorphological and release characteristics of coated fertilizer
granules produced in a Wurster fluidized bed, Powder
Technology, 132 (2003) 16–24. DOI: 10.1016/S00325910(02)00345-5
Uhlemann H., Mörl L., Wirbelschicht-Sprühgranulation,
Springer Berlin Heidelberg, Berlin, Heidelberg, 2000, ISBN:9783642631252. DOI: 10.1007/978-3-642-57004-9
Werner S.R.L., Jones J.R., Paterson A.H.J., Archer R.H., Pearce
D.L., Air-suspension particle coating in the food industry:
Part I—state of the art, Powder Technology, 171 (2007)
25–33. DOI: 10.1016/j.powtec.2006.08.014

Maike Orth et al. / KONA Powder and Particle Journal No. 39 (2022) 230–239

Authors’ Short Biographies
Maike Orth
Maike Orth is a doctoral student at the Institute of Solids Process Engineering and Particle Technology at the Hamburg University of Technology. There, she obtained her M.Sc. in Process Engineering with distinction in 2019. During her Master’s studies, she spent one semester at the Universityof Waterloo, Canada. Her research interests include particle formulation in fluidized beds, particle
characterization and CFD-DEM simulations of fluidized bed spray processes.

Paul Kieckhefen
Paul Kieckhefen is a is a doctoral student at the Institute of Solids Process Engineering and Particle Technology of the Hamburg University of Technology. There, he obtained a M.Sc. in Process
Engineering with distinction in 2018. He interned at BASF in the departments of Chemical andProcess Engineering in 2016 and Digitalization in Research & Development in 2017. He performed
research stays in the group of Prof. Pirker at the Johannes-Kepler University in Linz, Austria. His
research interests comprise efficient simulation methods that describe multiphase flows, time-scale
extrapolation methods and product-property prediction approaches using multi-scale simulations.

Swantje Pietsch
Dr.-Ing. Swantje Pietsch is a senior engineer in the Institute of Solids Process Engineering andParticle Technology at Hamburg University of Technology. She obtained her PhD in 2018 on theexperimental and numerical investigations of fluidization behavior and liquid injection in threedimensional prismatic spouted beds. Her research is focused on particle formulation in fluidized beds
and CFD-DEM simulations of these processes.

Stefan HeinrichStefan Heinrich obtained his diploma in Process Engineering and a doctoral degree at the University Magdeburg. After positions as Assistant and Junior Professor and a Habilitation, he became
Full Professor at the TUHH and director of the Institute of Solids Process Engineering and Particle
Technology in 2008. He is editor of Advanced Powder Technology and Particuology, chairman of theWorking Party on Agglomeration and Bulk Solids Technology of VDI-ProcessNet and of the EFCE
Working Party on Agglomeration. His main research interests are fluidized bed technology, mainly
for drying and particle formulation, particle simulation methods as well as contact, deformation andbreakage mechanics of particles. He received the DECHEMA-Prize 2015.

239

KONA Powder and Particle Journal No. 39 (2022) 240–250/https://doi.org/10.14356/kona.2022007

Original Research Paper

Carbonation Kinetics of Fine CaO Particles in a Sound-Assisted
Fluidized Bed for Thermochemical Energy Storage †Federica Raganati and Paola Ammendola *Istituto di Scienze e Tecnologie per l’Energia e la Mobilità Sostenibili (STEMS) - CNR, Italy

Abstract
The calcium-looping process, relying on the reversible calcination/carbonation of CaCO3, is one of the mostpromising solution to perform thermochemical energy storage (TCES) for concentrating solar power (CSP)
plants. Indeed, CaO precursors such as limestone can rely on the high energy density, low cost, large availability
and nontoxicity. In this work, the study of the sound-assisted carbonation of fine CaO particles (< 50 μm) for
TCES-CSP has been furthered. In particular, a kinetic study has been performed to analyze the effect of theparticular carbonation conditions to be used in TCES-CSP applications, i.e. involving carbonation under high CO2
partial pressure and at high temperature. All the experimental tests have been performed in a lab-scale soundassisted fluidized bed reactor applying high intensity acoustic field with proper frequency (150 dB–120 Hz). The
carbonation kinetics has been analyzed by applying a simple kinetic model, able to properly describe the fast (underkinetic control) and slow (under diffusion control) stage of the reaction. In particular, the reaction rate, the intrinsic
carbonation kinetic constant and the characteristic product layer thickness have been evaluated, also highlighting
their dependence on the temperature between 800 and 845 °C; a value of 49 kJ mol–1 has been obtained for theactivation energy. Finally, a good agreement between the conversion-time profiles, evaluated from the applied
kinetic models, and the experimental data has been obtained.
Keywords: calcium looping, fine particles, Concentrating Solar Power (CSP), Thermochemical Energy Storage(TCES), sound-assisted fluidization, kinetics

1. Introduction

which can be evaluated as a function of the temperature (T)according to (Stanmore and Gilot, 2005):

One of the main challenge for a short-term wider
utilization of solar energy, which is characterized by an
intrinsic intermittency, is represented by energy storage(Ammendola et al., 2020). In this framework, the calciumlooping (CaL), performed in fluidized bed reactors, isattracting growing research interest for thermochemicalenergy storage (TCES) in concentrating solar power (CSP)
plants, in light of the high energy density, small costs,
non-toxicity, and large availability of natural CaO precursors (Chacartegui et al., 2016; Ortiz et al., 2018). It is basedon the cyclic calcination/carbonation of CaCO3:
0 
CaCO 3  CaO  CO 2 H rxn
178 kJmol 1(1)

The thermodynamics of the system is strongly dependent(1)on the CO2 partial pressure (PCO2) (Ortiz et al., 2019),†*

Received 2 March 2021; Accepted 26 April 2021
J-STAGE Advance published online 26 June 2021
Corresponding author: Paola Ammendola;
Add: Piazzale Tecchio 80, 80125 Naples, Italy
E-mail: paola.ammendola@stems.cnr.it
TEL: +39-081-7682-237 FAX: +39-081-5936-936

24020474 Peq 
Py eq 4.137  10 7 exp  

T 


(2)

eq
The equilibrium PCO ( PCO 2 ) of the carbonation2
calcination reaction, calculated according to Eq. (2), is(2) in Fig. 1 between 650 and 1000 °C, at different inlet
plotted
CO2 molar ratio (yCO ).
2eq
It is clear from Fig. 1 that[31]increasing values of PCO 2 at
a constant temperature or decreasing values of the temeq
perature at a constant PCO 2 favors the carbonation reaction
thermodynamically, i.e. thus yielding larger values of CaO[31]
carbonation conversion.
It is important to highlight that the optimal operating
conditions of the CaL[31]process and, therefore, also the CaO
multicycle performance, deeply depend on the particularapplication (Ortiz et al., 2018). In particular, high CO2
partial pressure and temperature (≥ 800 °C) can be used
to perform carbonation in order to obtain high global
efficiency for energy storage and electricity production in
CSP plants (Ortiz et al., 2018). In contrast, relatively low
temperature (~750 °C) and CO2 partial pressure can be
adopted to perform the calcination; this can be achieved

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

Fig. 1 Equilibrium pressure of CO2 as function of the temperature for
the CaO-CaCO3 system at different inlet CO2 molar ratio (yCO ).
2using either steam or helium, namely a gas that can beeasily separated from CO2 (Karasavvas et al., 2018). As
discussed by (Chacartegui et al., 2016), this reduction of
the calcination temperature would allow, on the one hand,to limit the sorbent deactivation over repeated cycle (i.e.
increased residual effective conversions with respect toconventional CaL for CCS), and, on the the other, to use
less expensive solar receivers. Lower calcination temperatures decrease the radiative losses, thus enhancing the efficiency of the process. Clearly, if He is used for calcination
the He/CO2 gas mixture exiting from the calciner must be
subjected to a separation step, which can be performed
quite easily using selective membranes thanks to the different molecular size of He and CO2. Another crucial point
to take into account is the necessity to have a process withfree CO2 emissions. In this framework, a viable solution,
proposed by (Chacartegui et al., 2016), is to realize thelooping process according to a closed cycle scheme: thecarbonator will be fed with a pure CO2 stream with a rate
remarkably larger than the stoichiometric rate needed forthe carbonation reaction. Then, the CO2 in excess exiting
the carbonator will be used as heat carrier fluid in a closed
Brayton cycle and finally sent to a compression stage before being stored for the subsequent cycles. Clearly, beinga closed cycle entails that there is no need for a continuous
feed of any fresh gas stream, which is especially importantin the case of the expensive He (Chacartegui et al., 2016).
The strong reduction of the CaO carbonation conversion
with cycling operations, caused by sintering and poreplugging, is still one of the main drawbacks and open
challenges in CaL (Benitez-Guerrero et al., 2018; Ortiz etal., 2019; Sarrión et al., 2018). In this context, it has been
showed that the carbonation conversion can be enhanced
by using fine CaO particles, thus also increasing the obtainable energy density, thanks to the maximization of theavailable sorbent surface (i.e. the surface which is actuallyin direct contact to the gaseous phase) and to the hindranceof the intrinsic loss of CaO multicyclic activity (DuránMartín et al., 2020). However, the fluidization of fineparticles is difficult; it is characterized by agglomeration,
channeling and plugging (Raganati et al., 2018; Raganati
and Ammendola, 2021) caused by the strong interparticle
forces (Raganati et al., 2017; Seville et al., 2000). In thisframework, the acoustic vibrations have been proved topromote and improve the fluidization of fine particles dueto the dynamic break-up of the large particle clusters, thus
also increasing the gas/solids contact efficiency (Raganati
et al., 2020a, 2015). Besides this, sound waves can also
promote other phenomena at the interface between thegaseous and the solid phase, such as acoustic streaming(Valverde, 2013), which also contributes to improve themass and heat transfer rates (Raganati et al., 2020a). In fact,
we demonstrated in a previous work that the carbonation
performances of fine limestone particles under TCES-CSP
operating conditions can be remarkably improved by theapplication of high intensity acoustic fields (Raganati etal., 2020a). Besides the multicycle carbonation conversion,
also the carbonation kinetics is crucial for the reactor design, especially for the scale-up of thermal processes.
This work represents a further development of theabove-mentioned research activity on the carbonation
reaction of fine CaO particles (< 10 μm) for TCES-CSP.
In particular, considering that the carbonation reaction(i.e. multicyclic CaO conversion and reaction kinetics) isremarkably affected by the operating conditions (carbonation thermodynamics and kinetics are strongly dependent
on temperature and pressure), a kinetic study has been
performed to point out the effect of the particular operating
conditions to be applied for TCES-CSP, namely involving
high CO2 partial pressure and high temperature carbonation. A lab-scale sound-assisted fluidized bed reactor has
been used to perform all the experimental tests, applying
acoustic fields of proper intensity (150 dB) and frequency(120 Hz). The carbonation kinetics has been studied using asimple kinetic model, able to properly describe the fast andslow stage of the of the reaction, thus obtaining valuable
data for designing and operating the carbonation reactor.
In particular, the evaluation of the reaction rate, activationenergy and the characteristic product layer thickness has
been performed.

2. Experimental
2.1 Materials and their fluidization behavior
A limestone provided by OMYA with a Sauter diameterof 3.61 μm and density of 2.71 g cm–3, namely belonging
to Group C of Geldart’s classification, has been usedas sorbent. Further details regarding both the chemicophysical characterization and the fluid-dynamic behavior
can be found elsewhere (Raganati et al., 2020a). Briefly,
the limestone particles are characterized by a natural

241

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

tendency to form large agglomerates (tens of microns)
and by a relatively low BET specific surface area (S0) of
1.6 m2 g–1, according to the typical values of natural limestones (Raganati et al., 2020a).
With reference to the fluid-dynamic behavior, as discussed by (Raganati et al., 2020a), the powder cannot
be properly fluidized under ordinary conditions due toagglomeration and channeling; i.e. the pressure drops arealways lower than the material weight per unit area, thus
meaning that the bed is not completely fluidized, as typicalof cohesive powders. More specifically, the predominanceof the interparticle forces over weight and drag forces
causes the individual particles to stick to each other andform agglomerates (agglomeration), which causes, in turn,a remarkable worsening of the permeability of the bed by
the fluidizing gas (channeling and plugging). In contrast
to this, the application of the acoustic perturbation makes
it possible to remarkably enhance the fluidization quality;
indeed, a regular pressure drop curve has been obtained.
This improvement of the fluidization behavior is due to thefact that the propagation of the sound wave inside the bed
causes a continuous break-up of the large particle agglomerates into smaller fluidizable structures. More specifically,
the internal cohesive forces are counteracted by the external drag and inertial forces generated by the acoustic perturbation. In particular, according to the cluster/sub-cluster
oscillators model discussed by (Raganati et al., 2017), theclusters break-up into smaller sub-clusters at the contact
points between them, namely where the collision energy
generated by the sound wave overcome the cohesive interparticle force. In line with these theoretical considerations,
it has been obtained that under sound assisted conditions
the fine limestone particles can be properly fluidized as
agglomerates which are interested by a dynamic break-up
and re-aggregation mechanism. In particular, the fluidizing agglomerate size (30–80 μm), i.e. the real size of thefluidizing structures, is always bigger than the nominal
size of the powder (3.61 μm, the Sauter diameter obtained
from the granulometric analysis), regardless of the applied
acoustic parameters.
With reference to the effect of the sound parameters, it
has been found that increasing the SPL (sound pressurelevel) value from 120 to 150 dB has a beneficial effect on
the fluidization quality, thus meaning that acoustic fieldwith higher intensity should be employed to maximize thefluidization quality. Indeed, both the fluidizing aggregate
size and the minimum fluidization velocity are always
decreased by passing from 120 to 150 dB. This is due to theenhancement of the energy introduced inside the bed when
the SPL is increased, which implies that the break-up mechanism becomes more and more efficient. Indeed, when the
SPL is increased from 120 to 150 dB, the size of the fluidizing agglomerates is reduced, thus resulting in the decreaseof the minimum fluidization velocity. Sound frequency,

242

on the contrary, has been found to have a non-monotonic
effect on the fluidization quality. Indeed, both the fluidizing
aggregate size and the minimum fluidization velocity arecharacterized by a nonlinear relationship with the soundfrequency, i.e. an optimum value of frequency equal to120 Hz can be observed. This behavior has been explained
considering that the frequency directly affects the relative
motion between clusters and sub-clusters, which, in turn,promotes the break-up and re-aggregation mechanism. In
particular, for too high values of frequency, the propagationof the acoustic wave through the bed of particles is poor
due to the increased sound absorption coefficient, which is
proportional to the square of sound frequency. Hence, fora sound source positioned at the top of the fluidization column, the upper part of the bed absorbs most of the acoustic
energy and only a very attenuated sound wave manages toreach the bottom part of the bed. Consequently, the disruption of the large agglomerates present at the bottom of the
bed is very weak, thus causing a reduction of the fluidization quality, i.e. an increase of the minimum fluidization
velocity. Contrarily, for too small sound frequencies,
there is no relative motion between larger agglomerates
and smaller sub-agglomerates, which also leads to a weak
break-up mechanism and poor fluidization quality.
Finally, also the effect of the temperature on the fluidization behavior has been analyzed by (Raganati et al., 2020a)
performing test at different temperatures (25–850 °C),
pointing out that increased fluidization difficulty is encountered as the temperature is increased. This result has been
explained referring to the fact that interparticle forces areintensified at higher temperatures. Then, as more and moreparticles tend to adhere to one another, larger fluidizing
agglomerates (passing from 30 to 80 μm when temperature
is increased from 25 to 850 °C) result from the intensification of the interparticle forces. Consequently, the minimum
fluidization velocity is also increased when temperature isincreased from 25 to 850 °C, as a result of the increased
fluidizing agglomerates size.

2.2 Experimental apparatus and procedure
In this work, sound-assisted (150 dB–120 Hz) fluidization tests have been performed to experimentally study the
kinetics of the carbonation reaction of fine natural CaO
particles at operating conditions relevant in the CaL-CSP
integration for TCES. Optimal parameters of the acoustic
field, i.e. those providing the best fluidization quality, havebeen chosen according to the results obtained from thefluid-dynamic characterization of the limestone (Raganati
et al., 2020a), briefly summarized in the Section 2.1.
All the experimental tests have been performed in alab-scale sound-assisted fluidized bed (40 mm ID) atatmospheric pressure. Further details regarding the soundgeneration system have been reported in previous works

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250(Raganati et al., 2020a). The gas feed has been preparedusing N2 and CO2 cylinders (99.995 % vol.); two mass
flow controllers (Brooks 8550S) have been used to set/
control the inlet flowrates. A heating jacket (Tyco Thermal
Controls GmbH) has been used to heat the column up to
the desired temperature. The temperature of the reactor ismonitored and controlled by means of a type K thermocouple linked to a PID controller. The outlet CO2 concentration is continuously monitored by means of an analyzer
provided with an infrared detector (ABB AO2020, URAS
14) (Raganati et al., 2020b). Before the carbonation tests,
a pre-treatment of the limestone particles was performed;
in order to obtain pure CaO, the CaCO3 sample (100 g)
is calcined (T = 900 °C) under sound-assisted fluidization
conditions (150 dB–120 Hz) for 2 h and using N2 as fluidizing gas (115 NL/h, corresponding to a superficial gas
velocity of 2.5 cm/s, i.e. about five times the minimum
fluidization velocity of the sorbent material (Raganati etal., 2020a)). On the basis of the fluid-dynamic characterization, optimal parameters (intensity and frequency) of
the acoustic perturbation have been selected (Raganati etal., 2020a). Then, the sample is carbonated under soundassisted fluidization conditions (150 dB–120 Hz) using
CO2 (70 vol% CO2 in N2) as inlet gas flowrate (115 NL/h)and at different temperatures (800 °C, 815 °C, 830 °C,
845 °C and 860 °C) until the sorbent is completely saturated. The CaO conversion (X) has been calculated fromthe amount of CO2 reacted with CaO, which, in turn, hasbeen evaluated from the measured outlet CO2 concentration profiles (Raganati et al., 2020a).

3. Carbonation kinetics
The carbonation involves the reaction of a solid reactant(CaO) with a gaseous reactant (CO2) to produce anothersolid (CaCO3) (Khawam and Flanagan, 2006).
In particular, the carbonation reaction takes place in
two stages with two different kinetic regimes (Raganati
et al., 2020a). At the beginning, the carbonation occurs
fast under the control of by the kinetics of the chemical
reaction between the CO2 molecules and the CaO (StageA) (Raganati et al., 2020a). After this initial kineticallycontrolled period, the free sorbent particle surface is covered by a thin layer of carbonate; therefore, the diffusion of
CO2 molecules through this solid layer starts to control thereaction (stage B) (Raganati et al., 2020a). In this context,
the product layer thickness is a very important factor to
analyze the shift from the fast to the slow reaction stages(Alvarez and Abanades, 2005).
The reaction rate is evaluated as the time evolution of theconversion degree, X(t), which can assume characteristic
shapes (Li Z. et al., 2012). Then, the kinetic analysis aims
to examine these shapes and explain them by means ofphysical fundamental mechanisms (Khawam and Flanagan, 2006).
The reaction rate (dX/dt) can be written as:dX r T  f  X 
dt(3)

where r(T) (min–1) is the temperature-dependent reaction
rate and f(X) is the reaction model describing the reaction(1) (3) By integrating Eq. (3), the integral form of themechanism.
kinetic model g(X) can be obtained:tg X   

0dX t
f X 

(4)

After the time evolution of the carbonation degree has
been evaluated experimentally, the reaction kinetics can be(2) (4)analyzed by selecting the most appropriate apparent kinetic
model to fit the experimental data (Ashraf and Olek, 2018;
Khawam and Flanagan, 2006).
The most important feature of these models is thatthey lump together all the mass transfer resistances, suchas external diffusion, diffusion in the pores, and surface
reaction (Khawam and Flanagan, 2006; Sun J. et al., 2008).
Then, the selected kinetic model is used to experimental
data in order to calculate an apparent global kinetic rate
(Ammendola et al., 2021; Khawam and Flanagan, 2006;
Sun J. et al., 2008). By definition, an apparent kinetic rateis different from the intrinsic reaction rate, which will bedependent on a number of experimental variables and/or
sorbent morphological features (Goodbrake et al., 1979;
Khawam and Flanagan, 2006; Sun J. et al., 2008). Clearly,
the use of apparent kinetic models holds the advantage to
be more simple, i.e. all the reaction steps can be accounted
in one expression (Salaudeen et al., 2018). However, thesemodels are scale-dependent due to the influence of transport phenomena (Khawam and Flanagan, 2006; Sun J. etal., 2008).
So far, several apparent models have been developed forthe carbonation reaction, based on different mechanistic
assumptions (Fedunik-Hofman et al., 2019a). In this framework, Lee (Lee, 2004) proposed a model equation for theapparent kinetics of the CaO carbonation in differential andintegral form:
2

dX
X 

 r 1 dt
X u (5)

X ut
X t (3) (5) X u / r  t(6)where r (min–1) is the apparent reaction rate and Xu isthe ultimate CaO carbonation conversion; with the time(4) (6)evolution of the carbonation reaction, the reaction becomes slower since the carbonate product layer starts toform, thus hampering the access of CO2 molecules to theresidual CaO and leading to values of ultimate conversions

243

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250< 100 %. Then, the reaction rates of the two carbonation
stages (stage A and B), rA and rB, can be determined by data
fitting, using the linear form of Eq. (6):1
1 1
1
   Xr  t  Xu

(7)

In particular, a bi-linear plot will be obtained, i.e. twolines with different slopes depending on whether the(5) (7)reaction
is either under kinetic control (stag A) or under
diffusion control (stage B). Then, rA and rB are evaluatedfrom the slope of the plot, whereas, the ultimate conversion
at the end of stage A and B, XuA and XuB, can be calculated
from the intercept of the plot (Lee, 2004). Since the carbonation reaction may be incomplete, the extent of conversion,α, is also used; it is evaluated as X/Xu.
The coefficient of correlation, R2, assuming values
between 0 to 1, and the sum of squares errors function(SSE) (Foo and Hameed, 2010), where the lower the SEE
value the better the fitting quality is, have been calculated
to assess the fitting quality of the kinetic model to theexperimental data. In particular, SSE can be calculated
according to:


SSE

in

  X mod  X exp 
i 1

i

i

2

(8)

ning of the reaction (stage A) whereas the reaction is large;
therefore, reaction is under kinetic control (Sun P. et al.,2008); ii) the reaction rate, rA, evaluated from the slope ofthe linear plot, as discussed above, is extended to represent
the true rate at the zero conversion point (i.e. rA = r0) (SunP. et al., 2008).
The reaction rate at the beginning can be written in
power law as (Sun P. et al., 2008):
dX
eq n
 3rA  M CaO k s PCO 2  PCO
 S0
2
dt t  0(10)eq
where PCO 2  PCO 2  is the reaction thermodynamic driving
force, n is the reaction order and ks is the intrinsic chem(8)
(10) rate constant. ks can be calculated using theicalreaction
Arrhenius equation:[33]

ks  k 0exp  E



RT



(11)

being E the activation energy and k0 the pre-exponential
factor.
(9)
(11) to Sun P. et al. (2008), the reaction is zeroAccordingeq
order (n = 0) for PCO 2  PCO 2  > 10 kPa. Considering that
PCO of 0.7 atm has been used for all the tests performed in2
this work, the assumption that the reaction order is zero isalways valid. Then, considering Eq. (11), Eq. (10) can be[33]
re-written in logarithmic
form as:where Xexp and Xmod are the experimental and modeled
carbonation conversion degree, respectively, and n is the(8) of experimental points.
number(12)
ln r1 ln M CaO k 0 S 0 / 3  E
RTAccording to several works available in the literature(Alvarez and Abanades, 2005; Biasin et al., 2015; Criado
Hence, fitting Eq. (12) with the values of rA, obtained
et al., 2018; Li Z. et al., 2012a,b), the conversion, XuA, at
at the different investigated temperatures, E and k0 can be(12)which the reaction shifts from stage A (i.e. kinetic control)
calculated.
to stage B (diffusion control) is also linked to the thicknessof product layer. Hence, the effect of the temperature
on XuA has been linked to the variation of the product4. Results and discussions
layer thickness with the carbonation temperature. In fact,
XuA represents the value of the CaO conversion degree
The results obtained in terms of time evolution of CaO
specifically corresponding to the critical product layer
carbonation conversion at different temperatures are rethickness (Alvarez and Abanades, 2005). As discussed in
ported in Fig. 2.
(Alvarez and Abanades, 2005), knowing the value of XuA,
Clearly, the CaO carbonation rate varies with the evoluthe product layer thickness at the end of stage A, h, can betion of the conversion degree, i.e. the reaction is kineticallyevaluated as:controlled at very small conversion values (stage A),
whereas it is diffusion-controlled at larger conversion
M
X uA VCaCO
3(9)values (stage B). In particular, the reaction proceedsh
S 0 M CaO
relatively fast at low levels of conversion degree, withM
where MCaO is the molecular weight of CaO, VCaCOisthethe temperature strongly affecting the initial rates. After3
molar volume of CaCO3 and S0 is the CaO specific surface
this initial stage, with the carbonation reaction going on
(7)
(9)
area.
and the conversion increasing and becoming closer to the
As proposed by in (Sun P. et al., 2008), the[32]grain model
ultimate conversion value, Xu, at which no more significant
has been used to calculate the intrinsic reaction rate conconversion is obtained at each temperature, the carbonation
stant (ks), which is an intrinsic feature of the material, ofrate gets close to zero. More specifically, the dense productthe carbonation reaction in the stage A (i.e. the kineticallylayer forming on the pore wall hinders the diffusion of thecontrolled period). The main assumptions of this model
CO2 molecules through it and, therefore, the reaction conare: i) the diffusion resistance can be neglected at the begintinues to take place under diffusion control.

244

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

The tight link between the carbonation rate and thetemperature has been more evidently highlighted plotting
the extent of carbonation (α) (Fig. 1(b)), i.e. removing theeffect of Xu which is itself temperature dependent.
Fig. 3 shows the plots of the experimental values of 1/X
vs 1/t for the different temperatures. Then, the apparent
reaction rates (rA and rB) and the ultimate conversion (XuA
and XuB) have been evaluated (Fig. 3) from the slope andintercept of the two linear segments of the plot. In par-ticular, XuA and XuB have been calculated as the values ofcarbonation conversion corresponding to the change of theslope and for 1/t tending to 0, respectively. It is clear thatthe experimental data reported in Fig. 3 follow a bi-linear
pattern. The two different linear segments of the plots confirm the existence of stage A and stage B of the carbonation
reaction, occurring under two different rate-controls (i.e.
kinetic and diffusive controls).
As regards the fast kinetically controlled stage (stage A),
it is evident, from the analysis of Fig. 4(a), that that the reaction rate does not monotonically increase with increasing
temperatures. Indeed, increasing the temperature from 800
to 850 °C, rA, i.e. the rate of the fast carbonation stage, isincreased according to the reaction kinetics being typicallyfavored by increasing values of temperature. However,for temperature larger than 850 °C the carbonation rate

Fig. 2 Time evolution of the conversion degree (X) (a) and carbonation
extent (α) (b) experimentally measured at different temperatures.

Fig. 3 Plot of 1/X versus 1/t for the experimental carbonation conversion data.

Fig. 4 Apparent kinetic rates (r), ultimate carbonation conversion
degree (Xu) and carbonation extent (αu) of the stage A (a) and stage B (b)of the carbonation reaction and thickness (h) of the CaCO3 product layer(h) (c) as functions of the temperature.

245

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

decreases.
Therefore, rA reaches a maximum value at a certain temperature (845 °C); above this temperature, i.e. approaching
the equilibrium temperature (870 °C), it gradually decreases. In accordance to thermodynamic principles and asclearly shown Fig. 1, the carbonation reaction occurs, at aeqcertain temperature, for values of PCO larger than PCO 2 . In2eqparticular, at a fixed CO2 partial pressure, PCO 2 increases
when the temperature is increased (Eq. (2)), thus leadingeq
to a decrease of PCO 2  PCO 2  , i.e. the thermodynamic[31]
pressure driving force; therefore, as typical of exothermic[31]
reactions, the carbonation reaction has the tendency to
become thermodynamically unfavored with increasing[33]
temperatures (Fedunik-Hofman
et al., 2019b; Sedghkerdar
et al., 2015; Sun P. et al., 2008; Yin et al., 2014). In otherwords, increasing the temperature at fixed PCO , the reverse2
reaction (calcination) tends to be favored thermodynamically as the equilibrium temperature is approached(870 °C) (Fedunik-Hofman et al., 2019b; Sedghkerdar etal., 2015; Sun P. et al., 2008; Yin et al., 2014).
This experimental evidence agrees with the data reportedin (Ortiz et al., 2018) and (Kyaw et al., 1998) for the CaO/
CaCO3 system when operated at the high temperatures
useful for TCES, i.e. near equilibrium conditions. Clearly,
the evidence that, at TCES-CSP operating conditions, thefast carbonation rate does not show a monotonic increasing
trend when the temperature is increased is very important.
In particular, the temperature (845 °C) at which thereaction rate can be maximized is a key point for real applications. Indeed, it must be considered that the selectionof the plant operating temperatures needs to be the resultof a compromise between the kinetic and thermodynamic
requirements. On the one hand, working at higher carbonation temperatures will enhance the power generation
efficiency, in line with the second law of thermodynamics(Ortiz et al., 2018). But, on the other hand, working at temperatures approaching the thermodynamic equilibrium will
eventually hinder the carbonation kinetics.
Also regarding stage A, of the carbonation reaction(namely the kinetics-controlled stage), it can be inferredfrom the corresponding linear segment of the plot (Fig. 3)that the ranges of data characterized by a linear correlation
become narrower and narrower as the temperature is decreased from 845 °C (i.e. before the trend inversion causedby the thermodynamic equilibrium approach) to 800 °C.
On the contrary, at lower values of temperature, the rate of
the fast carbonation stage depends more on the diffusion
limitation, thus moving away from the kinetic control evenat lower values of carbonation conversion (Fig. 3). In fact,
the carbonation reaction occurs mostly under kinetic control, i.e. almost up to the ultimate conversion (XuB), as thetemperature is increased up to 845 °C, with less effect ofthe diffusion-controlled stage. This is also clearly inferablefrom Fig. 4(a), showing that the carbonation conversion

246

achievable at the end of the kinetic-controlled stage (XuA),
namely when the CaO conversion levels start to moveaway from the kinetic control, increases when the temperature is increased up to 845 °C. In contrast, XuA decreases
with a further increase of the temperature. This agrees with
the increase of the reaction rate when the temperature isincreased up to 845 °C and with its decrease for larger values of the temperature. This same trend is also obtained forthe extent of carbonation, α, which means that increasing
the temperature up to 845 °C leads to an increase of thefraction of lime reacted in the fast kinetic-controlled stage,i.e. the fast carbonation stage provides a larger contribution
to the global carbonation conversion.
The obtained non-linear dependence of ra on the temperature has been also linked to the critical product layer
thickness, i.e. the values of product layer thickness at theend of stage A (Alvarez and Abanades, 2005), being maximum at 1000 °C (Fig. 4(c)). Evidently, the product layer
thickness increases (from 301 to 342 nm) when the carbonation temperature is increased from 800 to 850 °C, namely
for temperatures sufficiently away from the equilibrium
temperature (i.e. before the inversion of the reaction ratecaused by the thermodynamic limitations (Sun P. et al.,2008)). This result agrees with previous works available
for the CaO/CaCO3 system even under different operation
conditions (Abanades and Alvarez, 2003; Alvarez andAbanades, 2005; Biasin et al., 2015; Criado et al., 2018;
Li Z. et al., 2012a,b; Mess et al., 1999). The explanation ofthis result can be found in a mechanistic kinetic study recently performed by Alvarez and Abanades (2005). The effect of the reaction temperature on the carbonation reaction
has been studied through images of the CaO and CaCO3
surfaces reacting with CO2, obtained using atomic force
microscopy. It was pointed out that larger product islands
formed at higher carbonation temperatures, as a result of
the diffusion of product molecules or ions becoming fasterat higher temperatures (Alvarez and Abanades, 2005).
Therefore, a bigger product layer tends to form at higher
temperatures, thus enhancing the CO2 carrying capacity ofCaO (Alvarez and Abanades, 2005).
As regards the slow carbonation stage, a monotonic
increase with increasing temperatures has been observed(Fig. 4(b)), in agreement with the diffusion of CO2 molecules within the carbonate layer becoming more efficientat higher temperatures. It can also be inferred, from theanalysis of Fig. 4(b), that, as the temperature is increased
up to 845 °C, the carbonation reaction achieves greater
conversion levels, even though, according to the thermodynamic principles, the carbonation reaction should
be favored, thus resulting in greater conversion levels at
lower temperatures. In fact, according to thermodynamics, higher final conversion should be achieved at lower
temperatures. This is due to the exothermicity of the carbonation reaction and is in agreement with the fact that theFederica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

thermodynamic driving force of the carbonation reaction
PCO2  PCOeq 2  is reduced as the temperature gets close to
the equilibrium temperature. However, even though incontrast to thermodynamic predictions, this result, which
agrees with results previously reported on CaO carbonation[33](Bhatia and Perlmutter, 1983), is due to the enhancement of
CO2 diffusion through the carbonate product layer at higher
temperatures (Rouchon et al., 2013). On the contrary, atlower temperatures the diffusion becomes slower, thus
hindering the achievement of larger ultimate conversions
within reasonable time frames (Rouchon et al., 2013).
Clearly, an excessive increase of temperature eventuallyends up in decreasing the final conversion degree as thethermodynamic limitations outbalance the enhanced CO2
diffusional mobility.
Then, values of the rates obtained in the chemical reaction control regime (rA) have been used to evaluate theintrinsic rate constant (ks) and its temperature dependence
between 800 and 850 °C, namely before the reaction rateis inverted due to thermodynamic limitations (Sun P. et al.,2008). In particular, the activation energy of the reaction,
E, and the pre-exponential factor, k0, have been calculated(Fig. 5), thus obtaining the dependence of the intrinsic rate
constant, ks, on the temperature in the temperature range of
800–850 °C:

k s  3.56  10 2 exp 49.19 / RT 

(13)

The obtained activation energy (E = 49.19 kJ mol−1)(13)
for(11)
the carbonation
reaction of the fine CaO is in line withdata reported in the literature (Lee, 2004; Salaudeen et al.,2018).
%%%%%%%%%%%%%%%%%%%%%%%
Using the kinetic parameters obtained in the two carbonation reaction stages, the time evolution of the carbonation
conversion has been evaluated, thus validating the results
obtained from the kinetic analysis. In particular, the plotsobtained applying the model equation, using the kinetic
constants obtained in the stage A and B of the reaction,
are shown in Fig. 6 in comparison with the experimental

Fig. 5ln (rA) vs 1/T (Eq. (12)) for the carbonation reaction.

curves. Clearly, using the kinetic parameters obtained in
the chemical reaction controlled regime makes it possible
to fairly predict the initial stage of conversion, whereas,using the kinetic parameters obtained in the diffusion
controlled regime makes it possible to predict well the laststage of conversion.
Therefore, there is not a unique kinetic constant able toproperly describe the entire carbonation reaction, i.e. overthe entire time frame. Indeed, there is always a period oftime in which the carbonation reaction is influenced by boththe chemical reaction between the CO2 molecules and the
CaO surface and by the diffusion of CO2 through the solid
layer. Considering that the proposed model can separately
describe the two stages of the carbonation reaction with arather good accuracy (i.e. the experimental data of the stage
A and stage B agree well with the predicted values), thecombination of the two different predictions, i.e. using theparameters separately obtained in the two control regimes,
makes it possible to fairly describe the carbonation reactionin the entire time frame.

5. Conclusions
The carbonation kinetics of fine CaO particles (< 10 μm)
has been investigated for TCES-CSP at realistic operating
conditions, namely at high CO2 partial pressure and temperature (800–845 °C). Tests have been performed in alab-scale sound-assisted fluidized bed and the carbonation
kinetics has been analyzed using a simple apparent kinetic
model. Then, the reaction rate, activation energy and thecharacteristic product layer thickness have been evaluated.
The main conclusions and observations derived from thekinetic study are:
● At operating conditions functional for TCES-CSP applications, the rate of the fast carbonation reaction does not
monotonically increase with the temperature. Indeed, thereaction rate reaches a maximum at 845 °C; above thistemperature, i.e. approaching the equilibrium temperature, it gradually decreases.
● XuA, i.e. the carbonation conversion at the end of thestage A, also increases when the temperature is increased
up to 845 °C; on the contrary, it decreases when thetemperature is increased further, in line with the trend
observed for the reaction rate. This has been also related
to the critical carbonate product layer, h, at the end ofstage A, which also increases (from 301 to 342 nm)
when the temperature is increased up to 845 °C.
● The rate of the slow carbonation reaction monotonicallyincreases with increasing temperatures, due to the enhancement of the diffusion of CO2 molecules within the
carbonate layer at higher temperatures.
● As the temperature is increased from 800 up to 845 °C,
the carbonation reaction achieves higher ultimate

247

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

Fig. 6 Comparison between the experimental and theoretical values of X predicted using the kinetic parameters obtained in the kinetic (stage A) anddiffusion (stage B) rate control regimes. Carbonation temperature: (a) 800, (b) 815, (c) 830, (d) 845, (e) 860 °C.

conversion levels, in contrast to thermodynamics predicting greater conversion levels at lower temperatures.
On the contrary, the final conversion degree is decreased
for temperatures larger than 845 °C due to the fact thatthe thermodynamic limitations outbalance the enhanced
CO2 diffusional mobility.
● The intrinsic carbonation kinetic constant and its temperature dependence have been also evaluated between
800 and 845 °C; a value of 49 kJ mol–1 has been obtained for the activation energy.
The proposed model can separately describe the twostages of the carbonation reaction; therefore, the carbonation reaction can be fairly described in the entire time248

frame combining the two different predictions, i.e. using
the parameters separately obtained in the two controlling
regimes.

Acknowledgements
This work has been done in the framework of the project
SOCRATCES, which has received funding from European
Union’s Horizon 2020 research and innovation programme
under the Grant Agreement no.727348.

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

NomenclatureE

activation energy of the intrinsic kinetic rate of
the fast carbonation reaction

f(X)
g(X)
h

MCaO

reaction kinetic model
integral form of the reaction kinetic model
thickness of the CaCO3 product layer at thetransition between the fast and slow reaction
periods
pre-exponential factor of the intrinsic kinetic
rate of the fast carbonation reaction
molecular weight of CaO

PCO
2
eq
PCO
2

CO2 partial pressure
equilibrium CO2 partial pressure

S0
t
[51]
rA
rB
X
XuA

CaO specific surface per unit mass
time
apparent reaction rate of stage A (min–1)
apparent reaction rate of stage B (min–1)
carbonation conversion degree (–)
ultimate carbonation conversion degree at theend of stage A (–)
ultimate carbonation conversion degree at theend of stage B (–)
CaCO3 molar volume

k0

XuA
M
VCaCO
3

Greek lettersαextent of carbonation conversion (–)[52]

References
Abanades J.C., Alvarez D., Conversion limits in the reaction of
CO2 with lime, Energy & Fuels, 17 (2003) 308–315. DOI:
10.1021/ef020152a
Alvarez D., Abanades J.C., Determination of the critical productlayer thickness in the reaction of CaO with CO2, Industrial& Engineering Chemistry Research, 44 (2005) 5608–5615.
Ammendola P., Raganati F., Landi E., Natali Murri A., Miccio
F., Kinetics of the carbonation reaction of an SrO-Al2O3
composite for thermochemical energy storage, Chemical
Engineering Journal, 420 (2021) 129618. DOI: 10.1016/j.
cej.2021.129618
Ammendola P., Raganati F., Miccio F., Murri A.N., Landi E.,
Insights into utilization of strontium carbonate for thermochemical energy storage, Renewable Energy, 157 (2020)
769–781. DOI: 10.1016/j.renene.2020.05.048
Ashraf W., Olek J., Carbonation activated binders from pure calcium silicates: reaction kinetics and performance controlling
factors, Cement and Concrete Composites, 93 (2018) 85–98.
DOI: 10.1016/j.cemconcomp.2018.07.004
Benitez-Guerrero M., Valverde J.M., Sanchez-Jimenez P.E.,
Perejon A., Perez-Maqueda L.A., Calcium-looping performance of mechanically modified Al2O3-CaO composites forenergy storage and CO2 capture, Chemical Engineering Journal, 334 (2018) 2343–2355. DOI: 10.1016/j.cej.2017.11.183
Bhatia S.K., Perlmutter D.D., Effect of the product layer on the
kinetics of the CO2-lime reaction, AIChE Journal, 29 (1983)
79–86. DOI: 10.1002/aic.690290111

Biasin A., Segre C.U., Strumendo M., CaCO3 crystallite evolution
during CaO carbonation: critical crystallite size and rate
constant measurement by in-situ synchrotron radiation X-ray
powder diffraction, Crystal Growth and Design, 15 (2015)
5188–5201. DOI: 10.1021/acs.cgd.5b00563
Chacartegui R., Alovisio A., Ortiz C., Valverde J.M., Verda V.,
Becerra J.A., Thermochemical energy storage of concentrated solar power by integration of the calcium looping
process and a CO2 power cycle, Applied Energy, 173 (2016)
589–605. DOI: 10.1016/j.apenergy.2016.04.053
Criado Y.A., Arias B., Abanades J.C., Effect of the carbonation
temperature on the CO2 carrying capacity of CaO, Industrial
and Engineering Chemistry Research, 57 (2018) 12595–
12599. DOI: 10.1021/acs.iecr.8b02111
Durán-Martín J.D., Sánchez Jimenez P.E., Valverde J.M., Perejón
A., Arcenegui-Troya J., García Triñanes P., Pérez Maqueda
L.A., Role of particle size on the multicycle calcium looping
activity of limestone for thermochemical energy storage,
Journal of Advanced Research, 22 (2020) 67–76. DOI:
10.1016/j.jare.2019.10.008
Fedunik-Hofman L., Bayon A., Donne S.W., Kinetics of solid-gas
reactions and their application to carbonate looping systems,
Energies, 12 (2019a) 2981. DOI: 10.3390/en12152981
Fedunik-Hofman L., Bayon A., Donne S.W., Comparative kinetic
analysis of CaCO3/CaO reaction system for energy storage
and carbon capture, Applied Sciences (Switzerland), 9(2019b) 5–9. DOI: 10.3390/app9214601
Foo K.Y., Hameed B.H., Insights into the modeling of adsorption
isotherm systems, Chemical Engineering Journal, 156 (2010)
2–10. DOI: 10.1016/j.cej.2009.09.013
Goodbrake C.J., Young J.F., Berger R.L., Reaction of betadicalcium silicate and tricalcium silicate with carbon dioxide
and water vapor, Journal of the American Ceramic Society, 62(1979) 168–171. DOI: 10.1111/j.1151-2916.1979.tb19046.x
Karasavvas E., Panopoulos K.D., Papadopoulou S., VoutetakisS., Design of an integrated CSP-calcium looping foruninterrupted power production through energy storage,
Chemical Engineering Transactions, 70 (2018) 2131–2136.
DOI: 10.3303/CET1870356
Khawam A., Flanagan D.R., Solid-state kinetic models: basics
and mathematical fundamentals, Journal of Physical Chemistry B, 110 (2006) 17315–17328. DOI: 10.1021/jp062746a
Kyaw K., Kubota M., Watanabe F., Matsuda H., Hasatani M.,
Study of carbonation of CaO for high temperature thermalenergy storage, Journal of Chemical Engineering of Japan, 31(1998) 281–284. DOI: 10.1252/jcej.31.281
Lee D., An apparent kinetic model for the carbonation of calciumoxide by carbon dioxide, Chemical Engineering Journal, 100(2004) 71–77. DOI: 10.1016/j.cej.2003.12.003
Li Z., Fang F., Tang X., Cai N., Effect of temperature on the
carbonation reaction of CaO with CO2, Energy & Fuels, 26(2012a) 2473–2482. DOI: 10.1021/ef201543n
Li Z., Sun H., Cai N., Rate equation theory for the carbonation
reaction of CaO with CO2, Energy and Fuels, 26 (2012b)
4607–4616. DOI: 10.1021/ef300607z
Mess D., Sarofim A.F., Longwell J.P., Product layer diffusion
during the reaction of calcium oxide with carbon dioxide,
Energy and Fuels, 13 (1999) 999–1005. DOI: 10.1021/
ef980266f
Ortiz C., Valverde J.M., Chacartegui R., Perez-Maqueda L.A.,
Carbonation of limestone derived CaO for thermochemicalenergy storage: from kinetics to process integration inconcentrating solar plants, ACS Sustainable Chemistry& Engineering, 6 (2018) 6404–6417. DOI: 10.1021/
acssuschemeng.8b00199

249

Federica Raganati et al. / KONA Powder and Particle Journal No. 39 (2022) 240–250

Ortiz C., Valverde J.M., Chacartegui R., Perez-Maqueda L.A.,
Giménez P., The calcium-looping (CaCO3/CaO) process forthermochemical energy storage in concentrating solar power
plants, Renewable and Sustainable Energy Reviews, 113(2019) 109252. DOI: 10.1016/j.rser.2019.109252
Raganati F., Ammendola P., Sound-assisted fluidization fortemperature swing adsorption and calcium looping: a review,
Materials, 14 (2021) 672. DOI: 10.3390/ma14030672
Raganati F., Ammendola P., Chirone R., Role of acoustic fields
in promoting the gas-solid contact in a fluidized bed of fineparticles, KONA Powder and Particle Journal, 32 (2015)
23–40. DOI: 10.14356/kona.2015006
Raganati F., Chirone R., Ammendola P., Effect of temperature
on fluidization of Geldart’s group A and C powders: roleof interparticle forces, Industrial & Engineering Chemistry
Research, 56 (2017) 12811–12821. DOI: 10.1021/acs.
iecr.7b03270
Raganati F., Chirone R., Ammendola P., Gas–solid fluidizationof cohesive powders, Chemical Engineering Research and
Design, 133 (2018) 347–387. DOI: 10.1016/j.cherd.2018.
03.034
Raganati F., Chirone R., Ammendola P., Calcium-looping forthermochemical energy storage in concentrating solar power
applications: evaluation of the effect of acoustic perturbationon the fluidized bed carbonation, Chemical Engineering Journal, 392 (2020a) 123658. DOI: 10.1016/j.cej.2019.123658
Raganati F., Chirone R., Ammendola P., CO2 capture by temperature swing adsorption: working capacity as affected by temperature and CO2 partial pressure, Industrial & Engineering
Chemistry Research, 59 (2020b) 3593–3605. DOI: 10.1021/
acs.iecr.9b04901
Rouchon L., Favergeon L., Pijolat M., Analysis of the kinetic
slowing down during carbonation of CaO by CO2, Journal of
Thermal Analysis and Calorimetry, 113 (2013) 1145–1155.
DOI: 10.1007/s10973-013-2950-5
Salaudeen S.A., Acharya B., Dutta A., CaO-based CO2 sorbents:

a review on screening, enhancement, cyclic stability, regeneration and kinetics modelling, Journal of CO2 Utilization, 23(2018) 179–199. DOI: 10.1016/j.jcou.2017.11.012
Sarrión B., Perejón A., Sánchez-Jiménez P.E., Pérez-Maqueda
L.A., Valverde J.M., Role of calcium looping conditions on
the performance of natural and synthetic Ca-based materials
for energy storage, Journal of CO2 Utilization, 28 (2018)374–384. DOI: 10.1016/j.jcou.2018.10.018
Sedghkerdar M.H., Mostafavi E., Mahinpey N., Investigation of
the kinetics of carbonation reaction with CaO-based sorbents
using experiments and aspen plus simulation, Chemical
Engineering Communications, 202 (2015) 746–755. DOI:
10.1080/00986445.2013.871709
Seville J.P.K., Willett C.D., Knight P.C., Interparticle forcesin fluidisation: a review, Powder Technology, 113 (2000)
261–268. DOI: 10.1016/S0032-5910(00)00309-0
Stanmore B., Gilot P., Review—calcination and carbonation oflimestone during thermal cycling for CO2 sequestration,
Fuel Processing Technology, 86 (2005) 1707–1743. DOI:
10.1016/j.fuproc.2005.01.023
Sun J., Bertos M.F., Simons S.J.R., Kinetic study of accelerated
carbonation of municipal solid waste incinerator air pollution
control residues for sequestration of flue gas CO2, Energy andEnvironmental Science, 1 (2008) 370–377. DOI: 10.1039/
b804165m
Sun P., Grace J.R., Lim C.J., Anthony E.J., Determination of
intrinsic rate constants of the CaO–CO2 reaction, Chemical
Engineering Science, 63 (2008) 47–56. DOI: 10.1016/j.
ces.2007.08.055
Valverde J.M., Acoustic streaming in gas-fluidized beds ofsmall particles, Soft Matter, 9 (2013) 8792. DOI: 10.1039/
c3sm50780g
Yin J., Qin C., Feng B., Ge L., Luo C., Liu W., An H., Calcium
looping for CO2 capture at a constant high temperature,
Energy & Fuels, 28 (2014) 307–318. DOI: 10.1021/
ef401399c

Authors’ Short Biographies
Federica Raganati
Federica Raganati received her degree in Chemical Engineering from the University Federico II
of Naples (Italy) in 2010 and her PhD in Chemical Engineering from the same university in 2014.
She has a permanent position as researcher at the Istituto di Scienze e Tecnologie per l’Energia e la
Mobilità Sostenibili (STEMS) of the Consiglio Nazionale delle Ricerche (CNR). Her main research
topics are the set-up of innovative fluidized bed reactor configurations, the reduction of CO2 emissions through post-combustion capture processes and the energy storage through thermochemical
processes. She is the author of 3 patents and about 80 papers published in peer-reviewed international
journals or proceedings of national/international conferences.

Paola Ammendola
Paola Ammendola received her degree in Chemical Engineering from the University Federico II
of Naples (Italy) in 2003 and her PhD in Chemical Engineering from the same university in 2006.
She has a permanent position as researcher at the Istituto di Scienze e Tecnologie per l’Energia e la
Mobilità Sostenibili (STEMS) of the Consiglio Nazionale delle Ricerche (CNR). Her main research
topics are the sound-assisted fluidization of cohesive powders, the set-up of innovative catalytic
systems and the use of fluidized bed reactors for clean energy production and the study of renewableenergy sources (solar energy and biomass). She is the author of 5 patents and about 150 papers published in peer-reviewed international journals or proceedings of national/international conferences.

250

KONA Powder and Particle Journal No. 39 (2022) 251–261/https://doi.org/10.14356/kona.2022018

Original Research Paper

Biodegradable PLGA Microsphere Formation Mechanisms inElectrosprayed Liquid Droplets †Moe Tanaka 1, Ayaka Ochi 1, Aiko Sasai 1, Hiroyuki Tsujimoto 1, Hitomi Kobara 2,
Hiromitsu Yamamoto 3 and Akihiro Wakisaka 2*
1 Pharmaceutical/Beauty Science Research Center of the Hosokawa Micron Corporation, Japan
2 National Institute of Advanced Industrial Science and Technology (AIST), Japan
3 School of Pharmacy, Aichi Gakuin University, Japan

Abstract
Microspheres composed of poly (lactic-co-glycolic acid) (PLGA) were formed in liquid droplets using theelectrospray technique. The structure of the microspheres was controlled by changing the electric voltage of theelectrospray. PLGA microspheres with porous structures and micro-sized nanocomposite particles comprising
PLGA nanosphere aggregates were formed at 5.0–7.0 kV and 2.5–3.5 kV, respectively. The structural change wasrelated to the extent of evaporation of the solvent from the droplets during their flight. When the evaporation wascompleted in the relatively small droplets, the microspheres with porous structures were formed in the droplets. To
study the mechanism, we observed the effects of the electric voltage of the electrospray, PLGA concentration, flight
distance of the droplets, and molecular weight of PLGA on the structure of the PLGA particles. The novelty of thisstudy is the analysis of the size and structure of the PLGA microparticles, which were controlled by the electrospraytechnique. Therefore, this research has important implications for the structural design and preparation of
nanocomposite particles.
Keywords: electrospray, emulsion solvent diffusion method, poly (lactic-co-glycolic acid), porous microparticle,
nanosphere

1. Introduction
The emulsion solvent diffusion (ESD) method in water
devised by Kawashima et al. (Kawashima et al., 1982;
1998) is an established method for producing drug-loadedpoly (lactic-co-glycolic acid) (PLGA) nanospheres. PLGA
and the drug are dissolved in a mixture of acetone andethanol and dropped into a stirred polyvinyl alcohol(PVA) aqueous solution. Nano-sized emulsion droplets areformed by spontaneous emulsification associated with therapid diffusion of acetone into the external aqueous phase
after dropping. Then, mutual diffusion of the solvents
causes PLGA and the drug to precipitate as the solubility
decreases. At this time, the external PVA phase is adsorbed
onto the surface of the emulsion droplets and prevents thecoalescence of emulsion droplets. This principle makes
this method suitable for the production of ~200-nm-sizeddrug-loaded PLGA nanospheres, with a uniform particle†*

Received 21 June 2021; Accepted 17 August 2021
J-STAGE Advance published online 9 October 2021
Corresponding author: Akihiro Wakisaka;
Add: 1-1-1 Umezono, Tsukuba, Ibaraki 305-8560, Japan
E-mail: akihiro-wakisaka@aist.go.jp
TEL: +81-29-861-8088 FAX: +81-29-861-8252

size distribution, and it has been researched extensively as
a new drug delivery system (DDS) technology (Kimura etal., 2008; Nakano et al., 2009; Hara et al., 2008; Tsujimoto
et al., 2007a; 2007b).
In this study, the ESD method was scaled (crystallizer
size, 100 L) at the Pharmaceutical/Beauty Science ResearchCenter of the Hosokawa Micron Corporation. The following steps were completed: (1) mass production of PLGA
nanospheres loaded with useful ingredients for cosmetics
and quasi-drugs (Charlesworth et al., 1960), and manufacturing and sale of unique skincare products and hair growthformulas containing these PLGA nanospheres; (2) development of a Good Manufacturing Practice (GMP) production
method (Tsujimoto et al., 2004; 2007b) for ~80-nm-sized
PLGA nanospheres that can undergo sterile pressure
filtration (Tsukada et al., 2009), for use in injectable
pharmaceutical formulations. The study developed a production method for the practical use of PLGA nanospheres.
However, there were issues in applying the ESD method
regarding (1) the formation of PLGA microspheres and (2)the formation of PLGA nanocomposites. For example, inthe manufacture of the PLGA microspheres, it is difficult
to apply methods other than a W/O/W emulsion solvent
evaporation method (in-liquid drying method) (Toguchi et

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

251

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261
Table 1 Chemical properties of PLGA used in experiments.

Sample A

Sample B

Sample C

Average molecular weight

5,000

20,00050,000

Ratio of lactic acid and glycolic acid

75:25

75:25

75:25

Manufacturer

FUJIFILM Wako Pure
Chemical Corporation

FUJIFILM Wako Pure
Chemical Corporation

MITSUI Chemicals, Inc.

al., 1991; Okada et al., 1997) using a strong solvent (chloroform, dichloromethane); however, the method carries ahigh environmental load. Regarding PLGA nanocomposites, an example of typical use is dry powder inhaler (DPI)
formulations. Microcomposite particles comprised of drugloaded PLGA nanospheres possess both the flowability(capsule fillability and alveolar delivery) and redispersibility into nanospheres (absorption into alveolar tissue)
required of DPI formulations (Tsujimoto et al., 2005;
Yamamoto et al., 2004; 2007). However, the manufacturing process requires the formation of PLGA nanospheres
using the conventional ESD method and a subsequentmechanical compounding process (Yamamoto et al., 2004;
2007) which can be time consuming and labor intensive.
Therefore, a new manufacturing process is desirable.
The electrospray fine particle preparation method is
attracting attention because particle size can be controlled
by varying the electrostatic potential between the counterelectrode and liquid (Kobara et al., 2019). In this study, asa novel method, we used an electrospray of the PLGA solution onto the surface of the PVA aqueous solution phase.
From the results obtained, it can be inferred that, unlike inthe conventional ESD method, it is possible to control theparticle size from submicron to several micrometers withthe same solvent composition without using a chlorinatedsolvent. In particular, it was found that the characteristic
PLGA microspheres, such as PLGA microspheres with aporous structure and micro-sized nanocomposite particles,
comprising PLGA nanosphere aggregates, can be producedby changing the preparation conditions. This result is
important for the structural design and preparation of nanocomposite particles when applying PLGA microspheres as
various platforms for DDS.
We would like to report herein this paper the mechanism
for the PLGA microspheres formed in the electrosprayedliquid droplets, and the structure-controlling factors suchas electric voltage, concentration of PLGA, flight distanceof the electrosprayed droplets and molecular weight of
PLGA.

2. Experimental
2.1 Apparatus and method
In this experiment, three types of PLGA (Sample A,

252

Fig. 1 Schematic picture of experimental setup for the PLGA particle
formation with electrospray.

B: Fujifilm Wako Pure Chemicals, Sample C: Mitsui
Chemicals) were used without further purification. Table 1
lists the basic chemical properties of the materials. Sample
B (molecular weight (MW): 20,000 Da) was used for theexperiments except for the experiment concerning theeffect of the molecular weight.
Fig. 1 shows a schematic of the experimental setup for
the PLGA particle formation. A glass beaker (cylindricalshape, outer diameter of 53 mm, height of 70 mm) was
filled with 50 ml of 0.25 wt% PVA aqueous solution, andplaced on a temperature-controlled stirrer. A stainless-steel
nozzle (outer diameter of 0.26 mm, inner diameter of
0.13 mm) was situated above the PVA aqueous solution
surface. The distance between the nozzle tip and PVA
aqueous solution surface was set to 20 mm as the standard
condition. A high voltage for the electrospray was supplied
between this nozzle and the counter electrode through ahigh-voltage DC power supply unit (HJPQ-10P3, HJPQ10N3 (Matsusada Precision Inc.)). Because the counterelectrode was in the aqueous solution, the surface of theaqueous solution acted as the counter electrode for theelectrospray, as shown in Fig. 1.
For the preparation of PLGA particles, PLGA (33 mg/ml)
was dissolved in an acetone/ethanol mixture with a 2:1
volume ratio. The PLGA solution was pumped with a constant flow rate of 0.03 ml/min using a microsyringe pump
(YSP-101, YMC Co., Ltd.) to the electrospray nozzle,
which was supplied with a high voltage. The concentrationof the PLGA solution (33 mg/ml) was the same as that usedin the conventional ESD method.
At the nozzle tip, the PLGA solution was fragmented
into charged droplets according to the electrospray

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

principle. The charged droplets were continuously sprayedonto the surface of the PVA aqueous solution, which
was gently stirred using a magnetic stirrer (stirrer size:
8 × 25 mm, cylinder type, and 800 rpm).
For each experiment, the PLGA solution was electrosprayed at 0.03 ml/min for 60 min, i.e., 1.8 ml of PLGA
solution was sprayed onto the surface of the PVA aqueous
solution. This experiment was conducted at room temperature (288–293 K). After spraying, the PLGA particles
suspended in the PVA solution were analyzed using the following procedures: (i) centrifugation of the PVA solution
containing PLGA particles (48,000 × g, 4 °C, 30 min); (ii)removal of supernatant; (iii) redispersion with purified wa-

ter and observation with a scanning electron microscope.
Fig. 2 shows a typical SEM image of the PLGA particles
produced using Run 4 (Table 2). The Feret diameters of theparticles were measured from the SEM images (magnification: 500–2000×). The average particle size was calculated
by measuring the Feret diameters of 20–30 particles.

2.2 Liquid droplets generated by electrospray
The PLGA solution was electrosprayed in a strong electric field between the nozzle tip and counter electrode. The
electrospray was started at 2.5 kV, and the electric voltage
was increased slowly, while the PLGA solution was fed
into the strong electric field at 0.03 ml/min through thenozzle, as shown in Fig. 3. At 2.5 kV, a Taylor cone andrelatively large liquid droplets, which fragmented fromthe Taylor cone, were observed (Fig. 3(a)). The formationof the Taylor cone, which is a characteristic of the electrospray, indicates that the electrospraying was accurately
performed. The liquid droplets were generated by theelectrostatic repulsion between the electric charges formedon the Taylor cone, which is called “coulombic explosion.”
Coulombic explosion can occur several times when the
charge density is increased, owing to solvent evaporationfrom the droplets. With the increase in electric voltage,
from 2.5 kV to 7.0 kV, the size of the liquid droplets decreased, owing to more coulombic explosion events. Whenthe electric voltage was higher than 3.5 kV, multiple Taylor
cones were formed (Figs. 3(b), (c), (d)). The droplet size
was too small to be observed through a high-speed camera

Fig. 2 An example of Feret diameter measurement using a SEM imageof Run 4.
Table 2 Experimental conditions.

Run

Voltage(kV)Distance of
nozzleinterface(mm)

Spray rate
(ml/min)Type ofPLGA

PLGA concentration(mg/ml)Ratio of PLGA
concentration to
standard concentration of 33 mg/ml

Ratio ofacetone andethanol

Particle size
(μm)

1

+2.0

20

0.03

B

33

×1

2:1

–

2

+2.5

20

0.03

B

33

×1

2:1

6.19 ± 0.40

3

+3.5

20

0.03

B

33

×1

2:1

3.13 ± 0.83

4

+5.0

20

0.03

B

33

×1

2:1

2.04 ± 0.40

5

+7.0

20

0.03

B

33

×1

2:1

1.86 ± 0.54

6

+5.0

20

0.03

B

3

× 1/10

2:1

–

7

+5.0

20

0.03

B

7

× 1/5

2:1

–

8

+5.0

20

0.03

B

17

× 1/2

2:1

1.83 ± 0.70

9

+5.0

20

0.03

B

67

×2

2:1

3.44 ± 0.39

10

+5.0

20

0.03

B

133

×4

2:1

4.83 ± 0.43

11

+5.0

10

0.03

B

33

×1

2:1

1.52 ± 0.14

12

+5.0

40

0.03

B

33

×1

2:1

3.65 ± 0.44

13

+5.0

20

0.03

A

33

×1

2:1

1.30 ± 0.70

14

+5.0

20

0.03

C

33

×1

2:1

4.08 ± 0.40

Run 4: Criteria condition of this experiment.

253

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

Fig. 3 Photographs taken with high speed camera of electrospray pattern according to the supplied voltage. The video is available publicly at
https://doi.org/10.50931/data.kona.17030060(Photron, 100,000 fps). When the voltage was increased
above a certain level, the size of the liquid droplet was
assumed to be ≤ 10 μm based on the high-speed camera
resolution. The video demonstrating the electrospray patterns, is provided on J-STAGE Data website.

2.3 Particleization of PLGA using electrospray
When the droplets of the PLGA solution were generated via the electrospray, the solvent in the droplets wasvaporized. This increased the PLGA concentration during
the flight of the droplets from the nozzle tip to the surfaceof the PVA aqueous solution. The solidification to form the
PLGA particles was related to this condensation process. To
investigate the effect of condensation on the electrosprayedliquid droplets and particleization, the following experimental conditions were observed, as listed in Table 2: (i)electrospray electric voltage (Run 1, 2, 3, 4, 5); (ii) PLGA
concentration (Run 4, 6, 7, 8, 9, 10); (iii) distance between
the nozzle tip and surface of the PVA aqueous solution(Run 4, 11, 12); (iv) molecular weight of PLGA (Run 4, 13,14). In each experiment, Run 4 was considered the standard
condition, because the PLGA particles formed in Run 4
reflected the original characteristics of the electrospray.
Other experimental conditions, such as the flow rate of the
PLGA solution, aqueous PVA solution (concentration andvolume), and stirring conditions, were fixed.

3. Experimental results and discussion
3.1 Effect of electric voltage of the electrospray on
the formation of PLGA particles
In the conventional ESD method, the PLGA solution
with the acetone/ethanol mixed solvent (volume ratio of
2:1) is mixed with water, containing PVA as a stabilizer.
The ESD method uses the difference in solubility of PLGAin the acetone/ethanol mixture and water. PLGA is highly
soluble in the acetone/ethanol mixture. In contrast, PLGA
is hardly soluble in water. Therefore, precipitation of
PLGA occurs when the two solutions are mixed, which

254

results in the formation of nanospheres. In this study,
electrospray was used to mix these two solutions; however,
evaporation of the solvent from the electrosprayed droplets
was found to play an important role in particleization, as
discussed below.
As shown in Fig. 1, the PLGA solution with the acetone/ethanol mixed solvent was electrosprayed, and theresulting liquid droplets traveled to the surface of the PVA
aqueous solution through the electric field. PLGA particles
were formed in the aqueous PVA solution owing to themixing of the two solutions. The microscopic structuresof the resulting particles were observed through SEM.
As shown in Fig. 4, the PLGA particle formation process
was classified into three groups, depending on the electric
voltage of the electrospray.
Group I at low electric voltages, 0 to +2.0 kV: PLGA
nanospheres similar to the nanospheres formed in theconventional ESD method were observed (Figs. 4(a), (b)).
Group II at intermediate electric voltages, +2.5 kV to+3.5 kV: Microparticles composed of PLGA nanospheres
were observed (Figs. 4(c), (d)).
Group III at high electric voltages, +5.0 kV to +7.0 kV:
Microspheres with porous structures were observed(Figs. 4(e), (f)).
The effect of the supplied electric voltage on the structure of the PLGA particles is schematically depicted inFig. 5.
In Group I, electrospraying was performed at low
electric voltages. Relatively large droplets of the PLGA
solution were fed into the PVA aqueous solution. The droplets were diffused into the PVA aqueous solution, which
resulted in the formation of the PLGA nanospheres owing
to the decrease in solubility of PLGA through interaction
with water. This mechanism is the same as that of the conventional ESD method, reported previously (Kawashima
et al., 1998).
In Group II, electrospraying was performed at electric
voltages of +2.5 kV to +3.5 kV, and electrospray-generated
fine droplets were formed. The solvent molecules of acetone and ethanol were evaporated out of the liquid dropletsof the PLGA solution during the flight of the droplets fromthe nozzle to the surface of the PVA aqueous solution.

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

Fig. 4

Scanning electron micrographs of the PLGA particles (granules) prepared by changing the electric voltage for the electrospray.

Fig. 5

Schematic illustration of the formation process of PLGA particle by the conventional ESD method and the electrospray method.

Owing to the evaporation of the solvent molecules, thePLGA concentration increased, which solidified the PLGA
partially in the droplets and especially on the surface of theliquid droplets. The diffusion of PLGA into the aqueous
solution became difficult owing to the solidification on thesurface of the liquid droplets; microparticles composed of255

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

nanospheres were formed. When the droplets landed on thesurface of the aqueous solution, the interaction of PLGA
with water was limited to the partially solidified liquid
droplets. This led to the formation of microspheres throughthe aggregation of PLGA nanospheres. In Fig. 4(c), theSEM image, which was magnified 30,000 times, showsa microsphere formed through the aggregation of PLGA
nanospheres. The specific surface area of the microspheres
was measured using the gas adsorption method, and foundto be larger than that of the microspheres in Group III,
as listed in Table 3. The microspheres in Group II had
nanocomposite structures. The size of the microparticles
formed in Group II was in the range of 2–10 μm. Thissize of the microparticles was in good agreement with thatof the electrosprayed liquid droplets, suggesting that one
microparticle was formed per liquid droplet.
In Group III, owing to high electric voltages (+5.0 kV
to +7.0 kV), much smaller liquid droplets were generated.
During the flight of the droplets, the solvent molecules ofacetone and ethanol evaporated, leading to the precipitationof PLGA, and microspheres with a porous structure wereformed. In Fig. 4(e), the SEM image, which was magnified
100,000 times, shows such a microsphere with a porous
structure. The size of the microspheres in Group III was
smaller than that in Group II. This was in agreement withthe decrease in the size of the liquid droplets at higher
electric voltages. This also supports the hypothesis that one
microsphere of PLGA was formed per liquid droplet.
In the conventional ESD method, the number of microspheres formed was negligible. In contrast, by using
Table 3 Specific surface area of PLGA particles.

Run

2

4

8

Voltage (kV)

+2.5

+5.0

+5.0

PLGA concentration (mg/ml)

33

33

17

Specific surface area (m 2/g)

107

80

162

Fig. 6256

electrospray, microspheres were formed when the solvent
molecules were evaporated out of the electrosprayed liquid
droplets.

3.2 Effect of PLGA concentration on theformation of PLGA particles
As shown in Figs. 4 and 5, the formation of PLGA
microspheres was promoted by the solidification of theelectrosprayed liquid droplets through the evaporation of
the solvent molecules. To verify the mechanism in Fig. 5,
the effect of the PLGA concentration on the formationof PLGA particles was examined. The concentrations of
PLGA in the acetone/ethanol mixture (volume ratio: 2:1)
were 3, 7, 17, 33, 67, and 133 mg/ml. The concentration
used in the experiments on the effect of the electric voltage(Fig. 4) was 33 mg/ml. The SEM images of the resulting
PLGA particles are shown in Fig. 6.
It was observed that the particle structures were dependent on the PLGA concentration; they were classified into
three categories. At lower concentrations (3 and 7 mg/ml),
microspheres were not formed. Instead, film-like structures
were formed. At suitable concentrations of 17, 33, and
67 mg/ml, porous microspheres were generated. At higher
concentrations, such as 133 mg/ml, microspheres wereformed, but they did not have porous structures. They weredense and partially dimpled.
The observed effect of concentration is schematicallyillustrated in Fig. 7. At lower concentrations (Fig. 7(a)),
during the flight of the electrosprayed liquid droplets,
the solvent molecules were evaporated out of the liquid
droplets; however, the concentration of PLGA, required
for solidification, was insufficient to form the outer shellstructure. Owing to the hydrophobicity of the PLGA solution, the electrosprayed fine droplets were eager to stay on
the surface of the aqueous PVA solution (Fig. 1). Thus,
the nanospheres resulting from the interaction of PLGA in

Scanning electron micrographs of the PLGA particles (granules) prepared at various PLGA concentration.

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

the droplets with water on the surface of the PVA aqueous
solution were present on the surface of the PVA aqueous
solution. The resulting nanospheres aggregated on thesurface of the PVA aqueous solution to form a thin film
structure. Note that the acetone/ethanol solvent was alsopresent around the surface of the aqueous PVA solution.
This acetone/ethanol mixture may have contributed to theformation of the PLGA thin-film structure. It was assumed
that the aggregating PLGA nanospheres were transformed
into thin-film structures through the partial dissolution of
the acetone/ethanol mixture.
At suitable concentrations, porous microspheres wereformed; moreover, the porosity and size of the microspheres decreased and increased, respectively, with increasing PLGA concentration (Figs. 6(c), (d), (e)). Thiswas in agreement with the measurements of the specificsurface area, which is listed in Table 3. When the PLGA
concentration in the solution was increased from 17 to
33 mg/ml, the specific surface area decreased from 162
to 80 m2/g. This indicates a decrease in porosity with an

Fig. 7increase in the PLGA concentration. Furthermore, thesize of the microspheres increased with increasing PLGA
concentration in this concentration range. This is related tothe increase in size of the liquid droplets with the increasein the concentration. Because the viscosity of the PLGA
solution increased with increasing PLGA concentration(Table 4), the size of the electrosprayed liquid droplets also
increased.
At higher concentrations, such as 133 mg/ml, porous
structures were difficult to generate. Moreover, numerous
PLGA molecules in the droplets formed denser structures.
We observed that porous structures were generated for a
specific range of PLGA concentrations. This also supports
the hypothesis that one microsphere was formed per liquid
droplet. Various studies on particle formation in emulsion
droplets in a liquid have been conducted (Mersmann, 1998;
Kawashima et al., 2002; Yoshizawa, 2004). However, theparticle formation mechanism in the proposed electrospray method is better equipped to create various particle
structures than the particle formation mechanisms reported

Schematic illustration of the formation process of PLGA particle by changing PLGA concentration.

Table 4 Relation of the PLGA concentration to the viscosity of PLGA solution.

PLGA concentration (mg/ml)

0

3

7

17

33

67

133

PLGA concentration ratio to standard concentration of 33 mg/ml–

× 1/10

× 1/5

× 1/2

×1

×2

×4

Viscosity of PLGA solution (cP)

0.44

0.46

0.46

0.51

0.65

1.05

2.61

257

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

Fig. 8 Scanning electron micrographs of the PLGA particles (granules) prepared by changing the spray distance between nozzle tip and water
surface.

Fig. 9Scanning electron micrographs of the PLGA particles (granules) prepared by various polymers with different molecular weight.

previously. This is because the solvent diffuses from theemulsion droplets in the liquid and evaporates from thesurface of the droplet in the air.

3.3 Effect of flight distance of the electrosprayed
droplets on the formation of PLGA particles
Fig. 8 shows the results of particle formation by changing the distance between the nozzle tip and surface of the
PVA aqueous solution. When the distance was increased,
the droplet size also increased owing to the decrease in theelectric field. The SEM images (Fig. 8) show that larger
particles with porous structures were produced as the distance increased. Although the size of the droplet increased,
solidification in the air occurred during long-distance
flights.

3.4 Effect of PLGA molecular weight on theformation of PLGA particles
PLGA with a molecular weight of 20,000 Da wasused. The size of the PLGA particles, resulting from theelectrospray method, depended on the molecular weightof PLGA. Fig. 9 shows the observed SEM images of the258

Table 5 Relation of the PLGA average molecular weight to the viscosityof PLGA solution.

Type of PLGA

A

B

C

Average molecular weight (Da)

5,000

20,00050,000Viscosity (cP)

0.55

0.65

0.71

PLGA particles, generated from the PLGAs with molecularweights of 5,000, 20,000, and 50,000. Porous structures
were observed for these three molecular weights, and theaverage diameter increased with an increase in the molecular weight. Because the viscosity and solubility also changewith the molecular weight, the effect of the molecularweight was studied more systematically.

4. Conclusions and future prospects(1) We found that PLGA microparticles were formedin the liquid droplets using the proposed electrospraytechnique. Porous PLGA microparticles and microparticles
composing PLGA nanospheres, which cannot be producedby the conventional ESD method, were generated. The formation mechanism of these PLGA particles was classified
into three categories depending on the extent of solvent

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

evaporation from the droplets. (i) The evaporation of thedroplets was completed in the air, leading to the formationof microspheres with a porous structure. (ii) Owing to
the evaporation of the solvent from relatively large
droplets, solidification began on the surface of the droplets,
leading to the formation of microparticles composed ofnanospheres. (iii) The evaporation was insufficient forsolidification in large droplets, leading to the formationof nanospheres similar to those in the conventional ESD
method.
(2) If these microparticles can be loaded with drugs, they
can be used for solid pharmaceutical preparations. The possibility of application in DPI and subcutaneous injection
formulations will be the subject of future studies.
(3) Currently, we are also investigating the following
subjects: (i) the mass production procedure of PLGA
microparticles using electrospray; (ii) the size-distribution
control of PLGA nanospheres using electrospray in a liquidmedium instead of air. We will report these results in the
future.

Acknowledgements
We would like to thank T. Iwakami of AIST for his technical assistance with the experiments. We would also liketo thank Hitachi High-Tech Corporation for the FE-SEM
images magnified 30,000 times in Fig. 4(c) and 100,000
times in Fig. 4(e).

Nomenclature
AIST
CE
DC
DDS
DPI
ESD
FE-SEM
HV
MW
PLGA
PVA
SEM

National Institute of Advanced Industrial Scienceand Technology
Counter ElectrodeDirect Current
Drug Delivery System
Dry Powder Inhaler
Emulsion Solvent Diffusion.
Field Emission Scanning electron Microscopy
High Voltage power supply
Molecular Weight
poly (Lactic-co-Glycolic acid)
Poly Vinyl Alcohol
Scanning Electron Microscopy

Data Availability Statement
The video data from electrospray experiments is available publicly in J-STAGE Data (https://doi.org/10.50931/
data.kona.17030060).

References
Charlesworth D.H., Marshall Jr. W.R., Evaporation from drops
containing dissolved solids, AIChE Journal, 6 (1960) 9–23.
DOI: 10.1002/aic.690060104
Hara K., Tsujimoto H., Tsukada Y., Huang C.C., KawashimaY., Tsutsumi M., Histological examination of PLGA nanospheres for intratracheal drug administration, International
Journal of Pharmaceutics, 356 (2008) 267–273. DOI:
10.1016/j.ijpharm.2007.12.041
Kawashima Y., Imai M., Takeuchi H., Yamamoto H., Kamiya K.,
Development of agglomerated crystals of ascorbic acid by
the spherical crystallization technique for direct tableting,and evaluation of their compactibilities [Translated], KONA
Powder and Particle Journal, 20 (2002) 251–262. DOI:
10.14356/kona.2002028
Kawashima Y., Okumura M., Takenaka H., Spherical crystallization: direct spherical agglomeration of salicylic acid crystals
during crystallization, Science, 216 (1982) 1127–1128. DOI:
10.1126/science.216.4550.1127
Kawashima Y., Yamamoto H., Takeuchi H., Hino T., Niwa
T., Properties of a peptide containing dl-lactide/glycolide
copolymer nanospheres prepared by novel emulsion solvent
diffusion methods, European Journal of Pharmaceutics andBiopharmaceutics, 45 (1998) 41–48. DOI: 10.1016/s09396411(97)00121-5
Kimura S., Egashira K., Nakano K., Iwata E., Miyagawa
M., Tsujimoto H., Hara K., Kawashima Y., Tominaga
R., Sunagawa K., Local delivery of imatinib mesylate(STI571)-incorporated nanoparticle ex vivo suppresses vein
graft neointima formation, Circulation, 118 (2008) S65–S70.
DOI: 10.1161/circulationaha.107.740613
Kobara H., Nakatsuka K., Wakisaka A., Size-selected synthesisof metal nanoparticles by using electrospray in a liquidmedium, Colloids and Surfaces A: Physicochemical andEngineering Aspects, 581 (2019) 123836. DOI: 10.1016/j.
colsurfa.2019.123836
Mersmann A., Crystallization and precipitation, KONA Powder
and Particle Journal, 16 (1998) 60–67. DOI: 10.14356/
kona.1998009
Nakano K., Egashira K., Masuda S., Funakoshi K., Zhao G.,
Kimura S., Matoba T., Sueishi K., Endo Y., Kawashima Y.,
Hara K., Tsujimoto H., Tominaga R., Sunagawa K., Formulation of nanoparticle-eluting stents by a cationic electrodeposition coating technology: efficient nano-drug delivery via
bioabsorbable polymeric nanoparticle-eluting stents in porcine coronary arteries, JACC: Cardiovascular Interventions,
2 (2009) 277–283. DOI: 10.1016/j.jcin.2008.08.023
Okada H., One- and three-month release injectable microspheresof the LH-RH superagonist leuprorelin acetate, Advanced
Drug Delivery Reviews, 28 (1997) 43–70. DOI: 10.1016/
s0169-409x(97)00050-1
Toguchi H., Ogawa Y., Okada H., Yamamoto M., Once-amonth injectable microcapsules of leuprorelin acetate,
Yakugaku Zasshi, 111 (1991) 397–409. DOI: 10.1248/
yakushi1947.111.8_397
Tsujimoto H., Hara K., Huang C.C., Yokoyama T., Kawashima Y.,
The applications of biodegradable poly lactide-co-glycolide(PLGA) nano-spheres for pulmonary and transdermal drugdeliveries, Foods & Food Ingredients Journal of Japan, 5(2005) 437–448.
Tsujimoto H., Hara K., Tsukada Y., Huang C.C., Kawashima Y.,
Arakaki M., Okayasu H., Mimura H., Miwa N., Evaluationof the permeability of hair growing ingredient encapsulated

259

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

PLGA nanospheres to hair follicles and their hair growing
effects, Bioorganic & Medicinal Chemistry Letters, 17(2007a) 4771–4777. DOI: 10.1016/j.bmcl.2007.06.057
Tsujimoto H., Hara K., Yokoyama T., Yamamoto H., Takeuchi H.,
Kawashima Y., Akagi K., Miwa N., Huang C.C., Percutaneous absorption study of biodegradable PLGA nano-spheres
via human skin biopsies, Journal of the Society of Powder
Technology, Japan, 41 (2004) 867–875. DOI: 10.4164/
sptj.41.867
Tsujimoto H., Tsukada Y., Hara K., Kawashima Y., New particle
design and its preparation of NFkB decoy oligodeoxynucleotide (NDON) loaded PLGA nanospheres for gene delivery,
Journal of the Society of Powder Technology, Japan, 44(2007b) 453–458. DOI: 10.4164/sptj.44.453
Tsukada Y., Hara K., Bando Y., Huang C.C., Kousaka Y.,
Kawashima Y., Morishita R., Tsujimoto H., Particle size
control of poly(DL-lactide-co-glycolide) nanospheres forsterile applications, International Journal of Pharmaceutics,

370 (2009) 196–201. DOI: 10.1016/j.ijpharm.2008.11.019
Yamamoto H., Hoshina W., Kurashima H., Takeuchi H.,
Kawashima Y., Yokoyama T., Tsujimoto H., Engineeringofpoly(DL-lactic-co-glycolicacid)
nanocomposite
particles for dry powder inhalation dosage forms ofinsulin with the spray-fluidized bed granulating system,
Advanced Powder Technology, 18 (2007) 215–228. DOI:
10.1163/156855207780208592
Yamamoto H., Kurashima H., Katagiri D., Yang M., Takeuchi
H., Kawashima Y., Yokoyama T., Tsujimoto H., Poly(lactic-co-glycolic acid) nanosphere composite preparedwith Mechanofusion® dry powder composition system for
improving pulmonary insulin delivery with dry powder inhalation, Journal of Pharmaceutical Science and Technology,
Japan, 64 (2004) 245–253. DOI: 10.14843/jpstj.64.245
Yoshizawa H., Trends in microencapsulation research, KONA
Powder and Particle Journal, 22 (2004) 23–31. DOI:
10.14356/kona.2004009

Authors’ Short Biographies
Moe Tanaka
Moe Tanaka received her bachelor’s degree in pharmacy in 2019 from Osaka University of
Pharmaceutical Sciences. As a pharmacist and researcher, she has joined the Pharmaceutical /Beauty
Science Research Center in Material Business Division of Hosokawa Micron Corporation in 2019and engaged in the research and development of skincare and haircare products containing PLGA
particles. Her current research interests are in formulation design using PLGA and its application tofunctional cosmetics.

Ayaka Ochi
Ayaka Ochi received her bachelor’s degree in 2018 and master’s degree in fermentation chemistryin 2020 from Ehime University, Japan. As a researcher, she has joined the Pharmaceutical /Beauty
Science Research Center in Material Business Division of Hosokawa Micron Corporation in 2020.
Her current research interests are in skincare and aging care utilizing PLGA nanosphere technology
and the development of functional cosmetics as an application of those technologies.

Aiko Sasai
Aiko Sasai is the vice director of the Pharmaceutical /Beauty Science Research Center in Material Business Division of Hosokawa Micron Corporation. She earned her Ph.D. degree in material
engineering from Iwate University, Japan in 2009. Since joining Hosokawa Micron Corp. in 2009,
she has been engaged in research on PLGA nanoparticles, and has been developing many cosmetics
applying PLGA nanoparticle technology.

260

Moe Tanaka et al. / KONA Powder and Particle Journal No. 39 (2022) 251–261

Authors’ Short Biographies
Hiroyuki Tsujimoto
Hiroyuki Tsujimoto is an operating officer of Hosokawa Micron Corp. He received Ph.D. degree
in industrial chemistry from Chuo University in 2001. He introduced innovative PLGA nanospheretechnologies developed by Prof. Yoshiaki Kawashima of Gifu Pharmaceutical University in 2001.
After that, he developed the PLGA nanosphere’s applications by participating in 11 government projects. He has authored or coauthored more than 250 technical articles, including 48 refereed journal
articles and 22 book chapters. In addition, he has received 11 awards from academia and industry
segments on the practical realization of PLGA nanospheres for cosmetics and DDS.

Hitomi Kobara
Hitomi Kobara is a senior researcher of National Institute of Advanced Industrial Science andTechnology (AIST). She has studied generation/transformation processes of gas-phase particles andreceived Ph.D. degree in engineering from Kanazawa University, Japan in 2004. She also has studied
electrospray to supply liquid fine particles acting as ultra-small reaction fields, named Femtoreactor®.
She has been engaged material synthesis and evaluation using the Femtoreactor® system.

Hiromitsu Yamamoto
Hiromitsu Yamamoto is a Professor in the Laboratory of Pharmaceutical Engineering at Aichi
Gakuin University. He received Ph.D. of Pharmacy from Gifu Pharmaceutical University (supervised
by Prof. Yoshiaki Kawashima) in 1999. He started research on peptide drug delivery systems using
particle carriers as an Assistant Professor at Gifu Pharmaceutical University in 1995. In 2006, hemoved to the faculty of school of Pharmacy at Aichi Gakuin University, where he is engaged inresearch on pharmaceutical engineering based on powder technology and particulate design. He has(co-) authored more than 130 peer-referred papers, 14 review papers and 13 patents.

Akihiro Wakisaka
Akihiro Wakisaka is a guest researcher of National Institute of Advanced Industrial Science andTechnology (AIST). He received Doctor of Science, Ph.D. from University of Tsukuba in 1988. Hestarted studying the electrospray as an interface of the mass spectrometer to measure the cluster-levelstructures of solutions in 1995, and then investigated the application of the electrospray to the chemical reaction control. He has organized 6 publicly funded projects (JST and NEDO) concerning about
the practical application of the electrospray from 2013 to the present.

261

KONA Powder and Particle Journal No. 39 (2022) 262–269/https://doi.org/10.14356/kona.2022011

Original Research Paper

Continuous Synthesis of Precision Gold Nanoparticles
Using a Flow Reactor †Jiaqi Dong 1, Jonathan Lau 2, Spyros A. Svoronos 3 and Brij M. Moudgil 1*
1 Center of Particulate and Surfactant Systems, Department of Materials Science and Engineering, University of Florida, USA
2 Department of Mechanical Engineering, University of Florida, USA
3 Department of Chemical Engineering, University of Florida, USA

Abstract
Nanoparticle synthesis using flow chemistry has the potential to enhance the large-scale accessibility of precisionengineered nanomaterials at lower prices. This goal has been difficult to achieve primarily due to reactor foulingand the lack of efficient reagent mixing encountered, especially in those scaled-up systems. The present study
aimed to overcome the two challenges by integrating a liquid-liquid biphasic segmented flow system with static
mixing. This strategy was applied to the synthesis of gold nanoparticles (AuNPs) using citrate reduction chemistry.
It was demonstrated that reactor fouling was eliminated by implementing the biphasic flow strategy. As a result,the overall mean particle size of the as-synthesized AuNPs was measured to be 15.5 nm with a polydispersity
index (PDI) of 0.07, and with the reproducibility of ± 6.4 %. The biphasic flow system achieved a reaction yield of
88.7 ± 1.1 % reliably with a throughput of 60 mL/hour up to 8 hours.
Keywords: gold nanoparticles, continuous nanoparticle synthesis, flow chemistry, liquid-liquid biphasic flow,
segmented flow

1. Introduction
Nanoparticle synthesis using flow chemistry has attracted significant attention in the last decade because of
its potential for automated, low-cost production of highprecision nanomaterials with minimal downtime(Nightingale et al., 2014; Stitt, 2002). The majority of
the research in flow synthesis involved the study ofsingle-phase flow in microfluidic systems, in which miscible fluids are continuously introduced into chip-based
microfluidic cells under specific flow conditions (Wagner
et al., 2008). However, reactor fouling (Schoenitz et al.,2015; Wagner et al., 2004), inefficient mixing (Song etal., 2003b), relatively broad residence time distribution(Trachsel et al., 2005), and relatively low throughput aresome of the major challenges encountered in bench-top
single-phase microfluidic reactors. They present a great
barrier to the precision control over the properties of thesynthesized nanoparticles, especially when the systemis scaled up. These challenges must be overcome before
technology transfer to the industry can occur.

†*

Received 7 April 2021; Accepted 18 May 2021
J-STAGE Advance published online 22 July 2021
Corresponding author: Brij M. Moudgil;
Add: Gainesville, FL 32611, USA
E-mail: bmoudgil@perc.ufl.edu
TEL: +1-352-846-1194 Fax: +1-352-846-1196

262

For these reasons, the present work aims to develop
a chemical flow reactor that allows the continuous synthesis of high-precision metal nanoparticles with higher
throughput. Ultimately, the goal is to generate a knowledge
base that would be valuable to flow synthesis of precision
nanoparticles on a broader scale.

2. Methods
2.1 Chemistry of gold nanoparticle synthesis
The chemical reaction known as the Turkevich method(Turkevich et al., 1951) was used to synthesize AuNPs.
For the conventional batch reaction, a specific volume of 1.0 wt% (34.0 mM) trisodium citrate dihydrate(Na3C6H5O7 · 2H2O, or NaCt, Sigma-Aldrich) solution
was injected into the solution of 0.25 mM gold chloride(HAuCl4, Sigma-Aldrich) at 100 °C under ambient pressure and with vigorous agitation. The molar ratio of NaCt
to HAuCl4 is the primary factor that determines the final
size and size distribution of the AuNPs (Dong et al., 2020;
Frens, 1973). The effects of other parameters were studied with more details in the literature (Polte et al., 2010;
Wuithschick et al., 2015).

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 39 (2022) 262–269

Fig. 1used.

The layout of the flow reactor system. Note: the diagram is not drawn to scale. The cross junction does not represent the actual fluid junctions

2.2 Flow reactor design and setup
The layout of the flow system is illustrated in Fig. 1. The
reagents were freshly prepared and stored in individual media bottles (FisherbrandTM Sterile PETG). The continuous
synthesis was initiated by introducing the reagents into thetubular reactor using independent piston pumps (Syrris,
FRX) with a precisely controlled volumetric flow rate(± 0.01 mL/min). The reagents were joined, mixed, andheated as they flow through the reactor in which the particle
synthesis occurred. The reactor temperature was controlledusing an oil bath on a hotplate (Syrris, FRX). The pressure
inside the reactor was controlled using a needle valve(IDEX, PEEK P-447) as a back-pressure regulator at theoutlet of the reactor. The absorption spectrum of the assynthesized particles was recorded inline when the sample
passes through a quartz flow cell (FireflySci, Inc.) in thelight chamber of a UV-visible spectrophotometer (Ocean
Optics, USB2000+ UV-VIS). Finally, the nanoparticles
were collected in centrifuge tubes for further analysis.
The flow reactor integrated an aluminum framework
and polymer tubing in a temperature-controlled oil bath,as illustrated in Fig. 2. The framework was made of6061 aluminum (McMaster-Carr, sheet aluminum 6.35 mm
thick 30 cm × 13 cm; threaded rod 6.35 mm diameter,
20 cm length; matching hex nuts and washer 6.35 mm
screw size). Aluminum was selected because of its
temperature tolerance (≤ 150 °C) for long-time service,high corrosion resistance, nonmagnetic nature, andgood machinability. Perfluoroalkoxy tubing (PFA, ColeParmer, 3.18 mm OD, 1.59 mm ID) was selected due to its
chemical compatibility, temperature tolerance (≤ 260 °C),
pressure rating (≤ 40.8 bar), and better optical transparency
as compared to TeflonTM, polytetrafluoroethylene (PTFE).

2.3 Single-phase continuous flow system
In a typical single-phase flow AuNP synthesis experiment, NaCt (1.7 mM) and HAuCl4 (0.54 mM) solutions

Fig. 2

Schematic of the flow reactor (framework and tubing).

were continuously introduced into the flow reactor in parallel. The solutions were merged using a Y-junction (IDEX,PEEK P-514), as shown in Fig. 3. The mixture was heated
to 100 °C as it flowed through the reactor. The volumetricflow rate of each solution (1 mL/min) was kept constant sothat the residence time (8.7 min) ensured that particle synthesis was complete before the sample exited the reactor.
The pressure inside the reactor was maintained at 3 bar tominimize bubble formation that would impact the concentration and disrupt the steady-state flow condition. The
AuNP suspension was sampled with a 30-min time interval
for particle size characterization. Each experiment wascontinued for 4 hours, and each experiment was repeatedthree times on different dates.

2.4 Biphasic segmented flow system
The liquid-liquid biphasic segmented flow system, as
shown in Fig. 4, involved the parallel introduction of two
immiscible liquids. The liquid that preferentially wets thesurface of the channel is the continuous phase; the other263

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 39 (2022) 262–269

Fig. 3 Schematic of the Y-junction and flow field in single-phasic flow experiment. System: volumetric flow rate ratio of NaCt to HAuCl4 = 1:1; total
flow rate = 2.00 ± 0.02 mL/min, reaction temperature = 100 ± 1 °C, pressure = 3 ± 1 bar, molar ratio of NaCt to HAuCl4 = 3.2, Reynolds number ≈ 90.

completed in the mini-reactor in approximately 5 seconds
due to the presence of recirculating flow field (Baroud etal., 2010; Bringer et al., 2004; Tice et al., 2003). The detailof the mixing time calculation is provided in the Supplementary Material Section 1. The collected mixture of oil
and aqueous AuNP suspension was centrifuged (Eppendorf
5810R, 2000 RCF for 20 min) to expedite the phase separation between oil and water.

2.5 Particle characterization
Fig. 4 Experimental setup showing the generation of biphasic segmented flow. The yellow and blue dye represent HAuCl4 and NaCt
solutions, respectively. System: volumetric flow rate ratio of NaCt to
HAuCl4 to silicone oil = 1:1:2; total flow rate = 2.00 ± 0.04 mL/min,reaction temperature = 100 ± 1 °C, pressure = 3 ± 1 bar, molar ratio of
NaCt to HAuCl4 = 3.2, Capillary number ≈ 0.021, Reynolds number ≈ 45
in the laminar flow region.

The mean particle size and size distribution of the collected AuNP samples were characterized using dynamic
light scattering (DLS, Malvern Zetasizer Ultra). All measurements were taken at room temperature (22 °C).

3. Results and discussion
liquid carried by the continuous phase is the dispersed
phase. Segmented flow, also referred to as slug flow in theliterature (Baroud et al., 2010; Nightingale and Demello,2013), is different from droplet flow in which the dispersed
droplets exhibit an average size smaller than the channel’s
inner diameter.
In the biphasic flow experiments, silicone oil (Fisher
ChemicalTM, viscosity = 45–55 mm2/s) was selected because of its low surface tension (21.3 ± 0.3 mN/m atambient temperature (Svitova et al., 2002)), temperaturestability (decomposition temperature > 250 °C), and it
is chemically inert. As illustrated in Fig. 4, silicone oil
was introduced from both sides of the cross-junction(IDEX, ETFE P-723). Droplets of aqueous reactants weregenerated when the aqueous solution was merged withsilicone oil. Each aqueous droplet became an individualmini-reactor that was carried by silicone oil. Despite therelatively slow diffusion-limited mixing in the laminar flow
region (Re ≈ 45), ninety percent of reagent mixing could be

264

3.1 Single-phase flow AuNP synthesis
In general, the AuNP samples synthesized in the singlephase flow experiments did not agree with the reference
values of particle size and size distribution (18.1 ± 3.5 nm
by intensity distribution (Dong et al., 2020)) based on the
DLS measurements as given in Fig. 5 (UV-vis spectrum
analysis and DLS data of individual trials are provided in
Supplementary Material Section 2.). The AuNP samples
generally exhibited a larger mean particle size (26.9 nm)
than the reference value as a consequence of fouling.
Besides, the AuNP size increased and became morepolydispersed after 90 min. The detection of sub-10 nm
nanoparticles suggested the presence of secondary nucleation in the bulk phase. It is possibly caused by a local
decrease in the molar ratio of NaCt to HAuCl4 in the bulk
phase (Dong et al., 2020), which is due to the imbalanced
consumption and competition of reactants from fouling.

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 39 (2022) 262–269

3.1.1 Reactor fouling
The increase in the mean particle size and broadening of
the size distribution could be attributed to reactor foulingwhich is an uncontrolled material deposition or growth
process on the reactor surface, as shown in Fig. 6. Reactor fouling was identified by the change in color and thedecrease in optical transparency of the PFA tubing as theexperiment progressed. A clean PFA tubing has a translucent and greyish appearance, as illustrated in Fig. 6(a). A
black haze could be observed on the tubing 30 min after
the experiment began. The transparency of the surface decreased over time. Eventually, the interior surface became
covered in purple, red, or gold materials, as highlighted inFig. 6(b). The observation agreed with Huang et al. (2018),
who investigated the deposited materials using X-ray photoelectron spectroscopy and infrared spectroscopy. Theirresults suggested that the deposited material consisted ofmetallic gold, unreacted gold, and citrate-gold complex.
The fouling was observed only at the bottom section of
the reactor. It was noticed that the residence time of thefouling section matched with the extent of the chemical
reaction (approx. 2.5 min at 100 °C). Based on this observation, it was hypothesized that fouling was caused byheterogeneous nucleation on the reactor surface during thesynthesis reaction of AuNPs.
The following experiments were conducted to investigate the proposed hypothesis. First, the flow rate was doubled while keeping other parameters constant. The result
showed that the length of the section that exhibited fouling
was doubled. In the second experiment, the flow directionin the reactor was changed by switching the inlet and theoutlet of the reactor. As expected, the section that exhibitedfouling was relocated near the new inlet (upper section)with the same length. In the third experiment, 500 mL of
colloidal AuNPs (15 nm in diameter) were synthesized in abatch reactor. The AuNP suspension was then circulated in
the flow reactor at the same temperature (100 °C), pressure(3 bar), and flow rate (2 mL/min) for 12 hours. The absorption spectrum of the suspension was continuously monitored; it showed minimal change during the experiment,
and no fouling was observed. The colloidal concentrationof AuNPs was estimated using the Beer-Lambert law in
Fig. 7, which suggested less than 2 % loss of nanoparticles
due to adsorption on the reactor surface. The results indicated that once the AuNP synthesis reaction was complete,
the citrate stabilized AuNPs would not cause fouling.

3.1.2 Strategies to mitigate foulingFig. 5 The DLS measurements of the AuNP samples showed varying particle size and size distribution as a function of time in the
single-phase flow experiments. Note: each sample was a pool of collection over 30 min intervals, e.g., Sample 210 was collected from 210 min
to 240 min. The measured values represented the particle size and size
distribution of the major peak of each sample.

Fig. 6 (a) The clean reactor before the experiment. (b) Reactor fouling
was observed at the bottom section of the reactor in the single-phaseflow experiments. Note: the fouling can be cleaned by flushing aquaregia, followed by deionized water through the reactor after it is cooled
to room temperature.

Various strategies were reported in the literature to mitigate reactor fouling (Schoenitz et al., 2015), for instance,increasing the flow rate, i.e., shear force at the solidliquid interface (Wagner and Köhler, 2005; Yang et al.,2007); increasing the electrostatic repulsion between thesurface and the depositing materials by tuning pH (Wagnerand Köhler, 2005); modifying the wettability of the reactor
surface (Wagner and Köhler, 2005); and implementing
coaxial fluid injection (Baber et al., 2015). A few of theseFig. 7 The colloidal concentration of the fully synthesized and stabilized AuNPs exhibited minimal change while circulating in the flow
reactor for 12 hours. System: temperature (100 ˚C), flow rate (2 mL/min), pressure (3 bar), initial concentration (45.1 ppm).

265

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 39 (2022) 262–269

strategies were investigated, including the test of different
reactor materials (glass vs. TeflonTM), different surface
roughness, and increasing the flow rate up to 5 mL/min.
However, these methods were found to be ineffective in thepresent study. An alternative strategy (Shestopalov et al.,2004) involving the biphasic flow system was investigatedto overcome fouling.

was 15.5 ± 4.1 nm (from the intensity distribution of DLS
measurements), which agreed with the reference value(18.1 ± 3.5 nm (Dong et al., 2020), p ≈ 0.26). The particle
size distribution, represented by the error bar in Fig. 9, also
showed a significant improvement in the precision of thenanoparticles (tabular data is provided in the Supplementary Material Section 2 and on J-STAGE Data website).

3.2 Biphasic flow AuNP synthesis

3.2.2 Reaction yield

When silicone oil was introduced in the flow system,
it was noticed that fouling was no longer visible during
the AuNP synthesis, as shown in Fig. 8. The reason was
suspected to be the elimination of direct physical contact
between the aqueous phase and the reactor surface due tothe presence of the oil phase (Shestopalov et al., 2004).

3.2.1 Particle size and size distribution
The AuNP synthesis in the biphasic segmented flow
system resulted in much better reproducibility than the
single-phase flow system, as demonstrated in Fig. 9. The
overall mean particle size from the biphasic experiments

The reaction yield was calculated from the experimental
and the theoretical colloidal concentration. The experimental concentration of the AuNP samples was estimated basedon the Beer-Lambert law and the calibration curve using
UV-vis absorption spectrum and ICP-MS data (Dong et al.,2020). The theoretical concentration was calculated withthe assumption of 100 % conversion from the reactant to
the product in the AuNP synthesis reaction.
In the biphasic flow experiments, the colloidal concentration of AuNPs resulted in a constant value of
46.5 ± 0.5 ppm, which was approximately 88 % of thetheoretical value compared to a maximum of 83 % in
the single-phase experiments, as shown in Fig. 10. The
decrease in the yield in the single-phase reaction systems
can be attributed to reactor fouling that alters the physicaland chemical nature of the surface (PFA) so that hetero­geneously nucleation on the reactor surface becomes morefavorable.

3.2.3 Reliability of the biphasic flow system

Fig. 8 Reactor fouling was not observed within (a) 2.5 hours or (b) 8hours in the biphasic flow experiments (aqueous reactants dispersed insilicone oil).

Fig. 9 The DLS measurements of the mean particle size of the AuNPs
synthesized in biphasic flow experiments was reproducible and consistent with the reference value (18.1 ± 3.5 nm). The particle size distribution is presented for each trial by showing the highest standard deviationof the data points of that trial. The raw DLS data is available publicly at
https://doi.org/10.50931/data.kona.15022002

266

A biphasic flow experiment was continuously run
for over 8 hours without reactor fouling, as shown in
Fig. 8(b). The DLS data plotted in Fig. 11 shows that themean particle size of the AuNP samples was maintained
at 16.9 ± 3.7 nm, which was consistent with the reference
value (18.1 ± 3.5 nm (Dong et al., 2020), p ≈ 0.59) and theprevious biphasic experiment results (15.5 ± 4.1 nm). The

Fig. 10 The colloidal concentration of the AuNP samples from thebiphasic flow experiments was maintained constantly and reproduciblyat 46.5 ± 0.5 ppm, which was approx. 88 % of the theoretical value.

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 39 (2022) 262–269
Table 1 Comparison of polydispersity index (PDI) of the AuNP
samples synthesized using the biphasic flow system under specificconditions.

Fig. 11 The DLS measurements of particle size and size distributionof the AuNP samples collected in an uninterrupted biphasic flow experiment. System: molar ratio of citrate to gold (3.2), temperature (100 ˚C),pressure (3 bar), flow rate (2 mL/min), volumetric flow rate ratio of oil
to water (1:1), residence time (8.7 min).

colloidal concentration was also maintained at the samevalue, 46.4 ± 0.7 ppm, equivalent to a percentage yield of
87.5 ± 1.3 %.

3.2.4 Precision (size distribution) of AuNP
The precision of nanoparticles, i.e., size distribution, wasquantified using the polydispersity index (PDI) (ISO13321,
1996; Malvern, 2011). PDI can be calculated using Eq. (1)(NanoComposix, 2015). The average PDI of the samples
synthesized in biphasic flow experiments (0.12 ± 0.02)
was lower by nearly one order of magnitude than the single-phase flow experiments (1.02 ± 0.43).
 Standard deviation 
PDI   Mean particle size 

2(1)

The improvement of particle size precision in the biphasic flow system can be attributed to the enhanced reagents(1) efficiency due to the recirculating flow field inside
mixingeach aqueous segment (Song et al., 2003a). The timerequired to complete the reagent mixing in each droplet
depends on the channel size, the droplet size, and the traveled distance. The average mixing time was estimated to beapproximately 5 seconds. Detailed calculation is provided
in the Supplementary Material Section 1.
The mixing by diffusion generally becomes less efficient as the reactor channel size increases (Stitt, 2002).
To overcome this challenge, an inline static mixer was
implemented. Based on the concept of packed bed column
reactors, a packed bed static mixer (PBSM) was fabricatedby filling yttria-stabilized zirconia beads (80 µm in diameter) in the PFA tubing. The PBSM was installed ahead of
the fluid junction that introduced silicone oil, as illustrated
in the graphic abstract. Statistical analysis indicated that
the PDI of the AuNP samples was reduced by an additional

PDI

SD

Reference value, batch method

0.065

0.009

Without static mixing, Fresh oil

0.119

0.021

With static mixing, Fresh oil

0.068

0.008

With static mixing, Recycled oil

0.079

0.018

40 % with the implementation of the PBSM (p ≈ 2E-9), as
shown in Table 1.
For the purposes of developing a greener and moresustainable process, preliminary experiments using recycled silicone oil were conducted. The used silicone oil
was separated from the aqueous phase using a separation
funnel, then cleaned by centrifugation and vacuum filtration, and reused in the subsequent experiments. Using therecycled silicone oil resulted in a 16 % increase in PDI (p≈ 4E-3) while the mean particle size remained unaffected(p ≈ 0.37). It was noticed that the samples generated fromthe experiments using the recycled oil had a higher degreeof oil contamination possibly due to thermal degradation of
the silicone oil.

4. Conclusions
In the present study, gold nanoparticles (AuNPs) were
continuously synthesized in a flow reactor using citrate
reduction chemistry. Reactor fouling was a major problem in the single-phase experiments, which affected theconsistency, reproducibility, and precision control of the
AuNP size, size distribution, and reaction yield. The main
reason for fouling was ascribed to the occurrence of theheterogeneous nucleation reaction in the vicinity of thereactor surface, leading to growth and accumulation ofmaterials there. The fouling problem was solved by introducing a water-immiscible silicone oil to the system that
preferentially wetted the reactor surface. Compared withthe single-phase flow system, the AuNPs produced in thebiphasic flow experiments exhibited significantly narrower
size distribution (PDI: 0.07 ± 0.01), higher and more consistent yield (approx. 88 %), and reproducibility of ± 6.4 %to the mean particle size.
Future research is suggested for inline particle functionalization using secondary reactors and further scale-up of
the present reactor system. It could be achieved by increasing the overall flow rate, increasing the chemical concentration, and utilizing parallel channels. One of the major
challenges encountered in the scaled-up flow system wasinefficient reagent mixing. For precision AuNP synthesis, it
was critical to ensure that the mixing was completed before

267

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 39 (2022) 262–269

the reaction began. Other challenges could be maintaining
the flow stability at a higher flow velocity, maintaining thestability of AuNPs, and homogenizing the heat and masstransfer and pressure across parallel channels. Overall,
the knowledge base developed in the present study should
enable designing scalable systems for commercially viablelarger-scale production of precisely engineered nanomaterials.

Acknowledgment
This work was primarily supported by the National
Science Foundation (NSF Award No. 1602032) and our industrial partner OndaVia, Inc. Any opinions, findings, andconclusions or recommendations expressed in this material
were those of the author(s) and did not necessarily reflect
the views of the NSF or OndaVia, Inc. The authors wantto acknowledge and express gratitude to Paul Carpinone(formerly University of Florida, UF), Gary Scheiffele(UF), and Bahar Basim (formerly UF) for their advice andassistance.

Data Availability Statement
The raw DLS data is available publicly in J-STAGE Data
(https://doi.org/10.50931/data.kona.15022002).

References
Baber R., Mazzei L., Thanh N.T.K., Gavriilidis A., Synthesis ofsilver nanoparticles in a microfluidic coaxial flow reactor,
RSC Advances, 5 (2015) 95585–95591. DOI: 10.1039/
c5ra17466j
Baroud C.N., Gallaire F., Dangla R., Dynamics of microfluidic
droplets, Lab on a Chip, 10 (2010) 2032–2045. DOI:
10.1039/c001191f
Bringer M.R., Gerdts C.J., Song H., Tice J.D., Ismagilov R.F.,
Microfluidic systems for chemical kinetics that rely on
chaotic mixing in droplets, Philosophical Transactions of
the Royal Society A: Mathematical, Physical and Engineering Sciences, 362 (2004) 1087–1104. DOI: 10.1098/
rsta.2003.1364
Dong J., Carpinone P.L., Pyrgiotakis G., Demokritou P., Moudgil
B.M., Synthesis of precision gold nanoparticles using
Turkevich method, KONA Powder and Particle Journal, 37(2020) 224–232. DOI: 10.14356/kona.2020011
Frens G., Controlled nucleation for the regulation of the particle
size in monodisperse gold suspensions, Nature PhysicalScience, 241 (1973) 20–22. DOI: 10.1038/physci241020a0
Huang H., Toit du H., Besenhard M.O., Ben-Jaber S., Dobson
P., Parkin I., Gavriilidis A., Continuous flow synthesisof ultrasmall gold nanoparticles in a microreactor using
trisodium citrate and their SERS performance, Chemical
Engineering Science, 189 (2018) 422–430. DOI: 10.1016/j.

268

ces.2018.06.050
ISO13321 I.S., Methods for determination of particle size distribution part 8: photon correlation spectroscopy, International
Organisation for Standardisation (ISO), 1996.
Malvern, Dynamic light scattering—common terms defined,
Malvern Guides, 2011 (2011) 1–5.
NanoComposix, NanoComposix’s guide to dynamic light scattering measurement and analysis, NanoComposix, 1.4 (2015)
1–8.
Nightingale A.M., Demello J.C., Segmented flow reactors fornanocrystal synthesis, Advanced Materials, 25 (2013)
1813–1821. DOI: 10.1002/adma.201203252
Nightingale A.M., Phillips T.W., Bannock J.H., De Mello J.C.,
Controlled multistep synthesis in a three-phase droplet reactor, Nature Communications, 5 (2014) 3777. DOI: 10.1038/
ncomms4777
Polte J., Ahner T.T., Delissen F., Sokolov S., Emmerling F.,
Thünemann A.F., Kraehnert R., Mechanism of gold nanoparticle formation in the classical citrate synthesis method
derived from coupled in situ XANES and SAXS evaluation,
Journal of the American Chemical Society, 132 (2010)
1296–1301. DOI: 10.1021/ja906506j
Schoenitz M., Grundemann L., Augustin W., Scholl S., Foulingin microstructured devices: a review, Chemical Communications, 51 (2015) 8213–8228. DOI: 10.1039/c4cc07849g
Shestopalov I., Tice J.D., Ismagilov R.F., Multi-step synthesisof nanoparticles performed on millisecond time scale in a
microfluidic droplet-based system, Lab on a Chip, 4 (2004)
316–321. DOI: 10.1039/b403378g
Song H., Bringer M.R., Tice J.D., Gerdts C.J., Ismagilov R.F.,
Experimental test of scaling of mixing by chaotic advection in droplets moving through microfluidic channels,
Applied Physics Letters, 83 (2003a) 4664–4666. DOI:
10.1063/1.1630378
Song H., Tice J.D., Ismagilov R.F., A microfluidic systemfor controlling reaction networks in time, Angewandte
Chemie—International Edition, 42 (2003b) 768–772. DOI:
10.1002/anie.200390203
Stitt E.H., Alternative multiphase reactors for fine chemicals: aworld beyond stirred tanks?, Chemical Engineering Journal,
90 (2002) 47–60. DOI: 10.1016/S1385-8947(02)00067-0
Svitova T., Theodoly O., Christiano S., Hill R.M., Radke
C.J., Wetting behavior of silicone oils on solid substrates
immersed in aqueous electrolyte solutions, Langmuir, 18(2002) 6821–6829. DOI: 10.1021/la020006x
Tice J.D., Song H., Lyon A.D., Ismagilov R.F., Formation ofdroplets and mixing in multiphase microfluidics at low valuesof the Reynolds and the capillary numbers, Langmuir, 19(2003) 9127–9133. DOI: 10.1021/la030090w
Trachsel F., Günther A., Khan S., Jensen K.F., Measurement ofresidence time distribution in microfluidic systems, Chemical
Engineering Science, 60 (2005) 5729–5737. DOI: 10.1016/j.
ces.2005.04.039
Turkevich J., Stevenson P.C., Hillier J., A study of the nucleationand growth processes in the synthesis of colloidal gold,
Discussions of the Faraday Society, 11 (1951) 55–75. DOI:
10.1039/DF9511100055
Wagner J., Kirner T., Mayer G., Albert J., Köhler J.M., Generationof metal nanoparticles in a microchannel reactor, Chemical
Engineering Journal, 101 (2004) 251–260. DOI: 10.1016/j.
cej.2003.11.021
Wagner J., Köhler J.M., Continuous synthesis of gold nanoparticles in a microreactor, Nano Letters, 5 (2005) 685–691. DOI:
10.1021/nl050097t
Wagner J., Tshikhudo T.R., Köhler J.M., Microfluidic generation

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 39 (2022) 262–269

of metal nanoparticles by borohydride reduction, Chemical Engineering Journal, 135 (2008) S104–S109. DOI:
10.1016/j.cej.2007.07.046
Wuithschick M., Birnbaum A., Witte S., Sztucki M., Vainio U.,
Pinna N., Rademann K., Emmerling F., Kraehnert R., Polte
J., Turkevich in new robes: key questions answered for themost common gold nanoparticle synthesis, ACS Nano, 9(2015) 7052–7071. DOI: 10.1021/acsnano.5b01579
Yang S., Zhang T., Zhang L., Wang S., Yang Z., Ding B., Continuous synthesis of gold nanoparticles and nanoplates with
controlled size and shape under UV irradiation, Colloids andSurfaces A: Physicochemical and Engineering Aspects, 296(2007) 37–44. DOI: 10.1016/j.colsurfa.2006.09.017

Authors’ Short Biographies
Jiaqi Dong
Jiaqi Dong received his B.S. in Materials Science and Engineering from the Illinois Institute ofTechnology in 2013. He then attended the University of Florida as a graduate student and received
his M.S. in Materials Science and Engineering in 2016. Currently, he is a Ph.D. candidate under thesupervision of Dr. Brij Moudgil and Dr. Bahar Basim at the Center for Particulate and Surfactant
Systems (CPaSS). His current research focus is metallic nanoparticle synthesis and functionalization
using flow chemistry.

Jonathan Lau
Jonathan Lau is currently a student at the University of Florida. He is expecting to complete a B.S.
in Mechanical Engineering in 2022. He has conducted undergraduate research under the supervisionof Ph.D. candidate Jiaqi Dong and Dr. Brij Moudgil at the Center for Particulate and Surfactant Systems (CPaSS). His current research interests are fluid flow and computational fluid dynamics. He has
previous industry experience with GE Aviation in 2019, Cummins in 2021, and Texas Instruments
in 2021.

Spyros A. Svoronos
Dr. Spyros A. Svoronos is the Harry & Bertha Bernstein Professor of Chemical Engineering at
the University of Florida. He received his B. A in Chemistry from Oberlin College and his M.S.
and Ph.D. degrees in Chemical Engineering from the University of Minnesota. His current researchinterests are in modeling and optimization of a variety of processes, including bioreactors andnanoparticle synthesis. In addition, he is developing low-cost Arduino-controlled experimental
equipment for teaching laboratories. He has published more than 70 technical papers and has been
awarded four patents.

Brij M. Moudgil
Dr. Brij M. Moudgil is a Distinguished Professor of Materials Science and Engineering at the
University of Florida. He received his B.E from the Indian Institute of Science, Bangalore, India, andhis M.S. and Eng.Sc.D degrees from Columbia University, New York. His current research interests
are in surfactant and polymer adsorption, dispersion and aggregation of fine particles, adhesion,and removal of microbes from surfaces, synthesis of functionalized nanoparticles, anti-scaling andsurfactant mediated corrosion inhibitors, photocatalytic degradation of hazardous microbes, andnanotoxicity. He has published more than 400 technical papers and has been awarded over 25 patents.
He is a member of the U.S National Academy of Engineering.

269

KONA Powder and Particle Journal No. 39 (2022) 270/https://doi.org/10.14356/kona.2022006

Addition/Correction

Author Correction: Analysis of Industry-Related Flows by
Optical Coherence Tomography—A Review †Antti I. Koponen 1* and Sanna Haavisto 2
1 VTT Technical Research Centre of Finland Ltd., Finland
2 Spinnova Ltd., Finland

Correction to: KONA Powder and Particle Journal No. 37 (2020) 42–63, https://doi.org/10.14356/kona.2020003,
published on 10 January 2020.

On page 45 the sentence after Eq. (2) should be: The
maximum measurable velocity can be increased by increasing the measurement angle α between the DOCT
beam and the velocity vector.
On page 45 Fig. 3c should be:

On page 46 the paragraph related to Eq. (3) should be:
Fig. 3b shows as an example a measurement setup of pipe
flow. From Fig. 3c, we get the real axial velocity in thepipe to be
U

vnf
sin β

(3)

where β is the DOCT measurement angle (the angle between the camera axis and pipe surface normal), v is thevelocity given by the DOCT device, and nf is the refractive
index of the monitored medium. Similar reasoning also
works, e.g., for plate-plate and bob and cup rheometer
geometries.
The mistakes were found by the authors after the paper
was published online. The authors apologize for the inconvenience to readers and editors by this oversight. The
results and conclusions of this paper were not affected by
the errors.
Fig. 3 c) A closer look at the measurement optics. Here U is the real velocity, v is the component of velocity in the direction of the measurement
beam, and nf is the refractive index of the medium. Angle α is obtainedby calculating first angle δ by applying the Snell’s law of refraction to
the two interfaces.

†

1
2

*

Received 18 February 2021; Accepted 24 February 2021
J-STAGE Advance published online 20 March 2021
P.O. Box 1603, FIN-40401 Jyväskylä, Finland
Palokärjentie 2-4, FIN-40320 Jyväskylä, Finland
Corresponding author: Antti I. Koponen;
E-mail: antti.koponen@vtt.fi
TEL: +358-20-722-2717 FAX: +358-20-722-2720

270

Copyright © 2022 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (https://creativecommons.org/licenses/by/4.0/).

KONA Powder and Particle Journal No. 39 (2022) 271–274/https://doi.org/10.14356/kona.2022022

Information Article

Book Review“Synthetic Nano- and Microfibers”, edited by
R. Martijn Wagterveld, Jan C.M. Marijnissen,
Leon Gradon and Arkadiusz Moskal

WETSUS, 2020, 256 p.
ISBN: 978-1-71663-242-6,
DOI: 10.20850/9781716632426
The book can be downloaded for free:https://osf.io/487wv/download

Global production of fibrous material is significantly growing with expectation of reaching 145 million metric tons
in 2030. Production includes mostly synthetic polymers fibers, cotton fibers and man-made cellulosic (viscose) fibers.
A smaller contribution comes from animal-made fibers (wool, silk). The main uses of fibrous material are in clothing,household and furnishing, industrial construction, automotive and other.
Increasing consumption of fabric material causes the accumulation of single fibers into the natural environment.
Significant numbers of fibers are discharged into wastewater from washing clothes, deposition from atmosphere orby other ways of transport. Fibers are now the most prevalent type of anthropogenic particles found by microplastic
pollution surveys around the world. Substantial concentration of fibers has been detected in surface water, deep-sea
and fresh water ecosystems. As a consequence, fibers are present in food, drinking water, human lungs and digestive
tracts of aquatic animals. Currently, there is great concern for the release of plastic nano-and micro fibers and microparticles (microplastics) to the natural environment for which nobody knows, so far, the ultimate consequences forhealth and ecological homeostasis.
The potential risk introduced by the presence of fibers in the environment induces significant interests of researchers in this problem as becomes clear from an increasing number of publications related to microplastics. The aforementioned challenges were the source of inspiration for organization a workshop.
During November 4 and 5, 2019, a group of scientists from different parts in the world met at Wetsus, the European
Centre of Excellence for Sustainable Water Technology in Leeuwarden the Netherlands, to discuss all known aspectsof synthetic nano- and microfibers. This includes the morphology, physicochemical properties, production and originof nano/micro fibers entering the atmosphere, water and food chain; the potential consequences of inhalation andingestion for human health, and exposure and ingress via life cycle for aquatic biota; analytical and measurement
methods; techniques to clean air and water, and protection means against inhalation or other ways to enter the humanbody. The group of top-experts from different disciplines, but all involved with small fibers, gathered to share theirview from scientific, technical and health perspective, presented their subject of expertise, contributed to the discussion and made their contribution into a chapter for the book: “Synthetic Nano- and Microfibers”.
The chapters in this book have been placed in a logic sequence, starting with the statement of the problem, properties of small fibers, fibrous particle identification, via environmental and health issues, and ending with possible
cleaning methods. It is very evident that still much is not known and that in each discipline more must be investigated.
For almost each sub-research program reliable on-line measuring techniques are indispensable. We assume that thisbook presents the state of the art and will give directions on how to proceed to answer the many remaining questions.
It is indisputable that it is essential to work together with all involved subdisciplines.

271

Table 1 Contents
Preface.......................................................................................xi

Kämpf, Sabine Plitzko, Wendel Wohlleben,

Day OneBurkhard Stahlmecke, Martin Wiemann, Andrea Haase

1

Plastic and the Planet: How to take care of the

7.1

Introduction.....................................................................56

next generation................................................................3

7.2

Risk banding and material properties required for

By: Maria Westerbos
2

Micro- and nanofibers: aerodynamics andHARM risk banding........................................................57
7.2.1 Length.............................................................................59

physicochemical aspect...................................................5

7.2.2 Respirability....................................................................61

By: Arkadiusz Moskal, Tomasz R. Sosnowski

7.2.3 Thickness (Rigidity)........................................................61

2.1

Introduction.......................................................................5

7.2.4 Biopersistence.................................................................65

2.2

Fiber dynamics in the viscous fluid...................................5

7.2.5 Release propensity (dustiness)........................................66

2.3

Modeling of the dynamics of fibrous particles in

7.2.6 Dust agglomeration.........................................................67

viscous fluid....................................................................117.2.7 WHO-fiber concentration................................................68

2.4

Micro- and nanofibers on the air/liquid interface...........12

7.3

2.5

Fibrous-like particles and lung fluids..............................14

2.6

Conclusions.....................................................................16

7.4

Matrix for risk banding...................................................71

3

Production of nano- and microfibers from

7.5

Application in risk prediction for MWCNT...................73

Summary of human risk banding for high aspectratio materials..................................................................71

synthetic and natural polymers - Nanofibers

7.6

Conclusions and outlook.................................................74

technology......................................................................19

7.7

Acknowledgements.........................................................75

By: Michał Wojasiński, Tomasz Ciach

8

Deposition of synthetic fibers in human

3.1

Introduction.....................................................................19

3.2

Meltblowing....................................................................20

3.3

Electrospinning...............................................................21

3.4
3.5

respiratory tract............................................................81
By: Yung Sung Cheng, Wei-Chung Su, Yue Zhou
8.1

Introduction.....................................................................81

Solution blow spinning...................................................24

8.2

Materials and Methods....................................................83

Centrifugal spinning........................................................27

8.2.1 Human nasal airway cast................................................83

3.6

Conclusion......................................................................28

8.2.2 Human respiratory airway casts......................................83

3.7

Acknowledgement..........................................................29

8.2.3 Fiber materials................................................................84

4

Questions and answers about synthetic fibers in

8.3

Experimental setup..........................................................88

wastewater treatment...................................................35

8.4

Sample preparation, fiber counting and length

8.5

Results and discussion....................................................91

By: Heather A. Leslie, Edited by R. Martijn Wagterveld
5

Measurement of nano- and microfibers in watermeasurement...................................................................90

and air: Physical and chemical methods.....................37

8.5.1 Fiber deposition efficiency in the human nasal airway...91

By: Louk Peffer, R. Martijn Wagterveld,

8.5.2 Comparison of nasal deposition between fibers andJan. C.M. Marijnissen
6compact particles............................................................93

Measurement of nanofibers in the breathing air........41

8.5.3 Fiber Deposition in the Human Oral Airway..................95

By: George Biskos, Jan C.M. Marijnissen

8.5.4 Fiber deposition in the tracheobronchial airways...........98

6.1

Introduction.....................................................................41

8.5.5 Empirical model for fiber deposition in the nasal

6.2

Online physical characterization of nanofibers...............426.2.1 Optical Sizing..................................................................42

airway............................................................................100
8.5.6 Empirical model for fiber deposition in the oral

6.2.2 Electrostatic Classification..............................................43
6.2.3 The Fiber Aerosol Monitor.............................................46

airway............................................................................101
8.5.7 Empirical model for fiber deposition in the

6.2.4 Aerodynamic classification.............................................46
6.3

tracheobronchial airway................................................102

Integrated systems for determining the size and8.5.8 Fiber exposure index.....................................................103

shape of aerosol nanoparticles........................................47

8.6

6.4

Online chemical analysis................................................49

Day Two

6.5

Conclusions and future perspectives...............................50

9

7

A human risk banding scheme for high aspect-272

Micro and nanoplastics in the aquatic environment
with special reference to synthetic fibers.................. 111

ratio materials...............................................................55
By: Dirk Broßell, Asmus Meyer-Plath, Kerstin

Conclusions...................................................................104

By: A. Dick Vethaak, C. Martínez-Gómez
9.1

Introduction................................................................... 111

9.2

Sources, pathways and sinks.........................................112

11.2

Background.................................................................158

9.2.1 Major sources of MNPs................................................112

11.3

Analytical imaging techniques for nanoparticles/

9.2.2 Sources of fibrous MNPs..............................................113
9.2.3 Pathways and sinks.......................................................113
9.3

fibers in tissues............................................................159
11.4

Composition of aquatic micro- and nanoplastic
debris.............................................................................113

9.3.1 Debris polymers............................................................114

Select case studies of nanoparticle-tissue interactions....................................................................................164

11.5

Synopsis......................................................................171

12

The intake of synthetic fibers into the human

9.3.2 Chemical additives........................................................114

body, by food, water and air....................................175

9.3.3 Adsorption of chemical contaminants..........................114

By: Ingeborg M. Kooter, Heleen Lanters,

9.3.4 Eco-corona, biofilm and biofouling..............................115

Wilma Middel, Harrie Buist

9.4
9.5

Factors that control degradation and fate of

12.1

polymeric material........................................................115

12.1.1 The origin of plastics..................................................175

Introduction.................................................................175

Physical and chemical quantification and12.1.2 Plastics, blessing or curse...........................................175

characterization of MNPs.............................................116

12.1.3 What are microplastics and microfibers......................175

9.5.1 Analysis of microplastics in aquatic matrices...............116

12.1.4 Are microplastics and synthetic microfibers

9.5.2 Analysis of microplastic fibers and nanoplastics..........117

a threat to human health?............................................176

9.5.3 Uncertainties in aquatic MNP measurements...............117

12.1.5 Reading guide.............................................................177

9.6

Occurrence of microplastics in aquatic systems...........118

12.2

Sources of synthetic microfibers.................................178

9.6.1 Microplastics in abiotic matrices..................................118

12.3

External exposure to synthetic microfibers.................182

9.6.2 Microplastics in aquatic biota.......................................11912.3.1 Introduction.................................................................182

9.7

Uptake and effects of MNPs on aquatic biota...............122

12.3.2 Air...............................................................................182

9.7.1 Uptake...........................................................................122

12.3.3 Water...........................................................................183

9.7.2 Physical effects..............................................................123

12.4

9.7.3 Chemical-mediated effects of MNPs............................128

12.4.1 Introduction.................................................................187

Human exposure routes...............................................187

9.7.4 Microbial effects of MNPs............................................129

12.4.2 Inhalation pathway......................................................187

9.7.5 Potential ecological effects of MNPs............................130

12.4.3 Oral pathway...............................................................187

9.7.6 Field evidence and ecological relevance oflaboratory studies..........................................................130

12.4.4 Dermal pathway..........................................................190
12.5Internal exposure and human uptake routes................190

9.8

Key conclusions............................................................130

12.5.1 Introduction.................................................................190

9.9

Key knowledge gaps and research priorities................131

12.5.2 Uptake via inhalation..................................................191

10

Micro(nano)plastics in aquatic organisms,

12.5.3 Uptake via ingestion...................................................193

transferability of knowledge from nanowires........147

12.5.4 Uptake via the skin......................................................194

By: Martina G. Vijver, Willie Peijnenburg,

12.6

Conclusion..................................................................194

Fazel Abdolahpur Monikh

13

An overview of the effects of synthetic

10.1

Introduction.................................................................147

micro(nano)fibers following exposure,

10.2

Aims of the chapter.....................................................148

with a focus on humans............................................201

10.3

Human exposure to micro(nano)plastics through

10.4
10.5
10.6

By: Stephanie Wrightfood.............................................................................148

13.1

Introduction.................................................................201

Responses attributed to additives in

13.2

Inferences from fiber toxicology.................................201

micro(nano)plastics.....................................................149

13.3

Plausible toxic properties of synthetic fibers..............202

Understanding responses attributed to MNPs in

13.4

Occupational epidemiology of synthetic fibers...........204

laboratory setting........................................................149

13.5

In vivo evidence..........................................................205

Transferability of knowledge on nanowires to

13.5.1 Mammalian models.....................................................205

micro(nano)fibers........................................................151

13.5.2 Human studies.............................................................205

10.7

To summarize and recommend...................................153

13.6

A potential for chemical effects?.................................206

11

Health effects of synthetic fibers and nanoparticles:

13.7

Discussion...................................................................206

11.1

Advanced electron microscopy to determine

13.8

Conclusions, limitations and future work...................207

nanoparticle and nanoplastic in vivo......................157

14

Mechanics of fibrous particles immersed in

By: Uschi M. Graham, Günter Oberdörster

selected flow conditions............................................ 211

Introduction.................................................................157

By: Rafał Przekop, Leon Gradoń

273

14.1

Introduction.................................................................211

15.1

Introduction.................................................................227

14.2

Modelling of fibrous particle deposition in a fibrous

15.2

Nano- and microfibers in aquatic ecosystems.............227

15.3

Techniques to remove nano- and microfibers.............229

filter.............................................................................213
14.2.1 The effect of gas velocity and fiber orientation on
deposition efficiency...................................................214
14.2.2 The effect of particle volume and slenderness ratioon the deposition efficiency........................................215
14.2.3 Effect of collectors orientation....................................217

15.3.1 Separation at source....................................................229
15.3.2 Waste water treatment plants......................................230
15.3.3 Alternatives to conventional treatment techniques.....231
15.3.4 Approaches for nanofiber removal..............................234
15.4

Future perspective for waste water treatment.............235

14.2.4 Flexible aggregate model............................................217

15.5

Conclusion..................................................................235

14.3

Lattice-Boltzmann modelling.....................................220

16

Workshop Summary and Conclusions....................237

14.4

Results and discussion................................................221

By: Stephanie Wright, Uschi M. Graham,

14.5

Conclusions.................................................................222

Arkadiusz Moskal

15

Cleaning water from nano- and microfibers..........227

Index ....................................................................................241

By: R. Martijn Wagterveld, Inez J.T. Dinkla

Author’s Short Biography
Jan Marijnissen
Jan C.M. Marijnissen is a former Associate Professor and Head of the Aerosol Laboratory at
Delft University of Technology, the Netherlands, and a PERC visiting Professor at the University of
Florida, USA. He is a visiting Professor at the University of Nairobi, Kenya. He has been an advisor
for Wetsus, European Centre of Excellence for sustainable water technology in Leeuwarden, theNetherlands and is an advisor for the University of Applied Science in Leeuwarden, the Netherlands.
Jan Marijnissen received a Master degree from Delft University of Technology and a Ph.D. degree
in environmental engineering from the University of Minnesota, U.S.A.. He has more than 45 yearsof experience in the field of mine-ventilation and aerosol science and technology and is especiallyinvolved in the development of advanced aerosol measuring instrumentation, air cleaning methods
and the production of particles via aerosol routes. He has (co)authored many articles, is co-editorof eight books on aerosols, and holds several patents. He is a member of several associations and aformer president of the European Aerosol Assembly.

274

KONA Powder and Particle Journal No. 39 (2022) 275/https://doi.org/10.14356/kona.2022023

Information Article

The 8th APT (Asian Particle Technology Symposium) 2021
Held in Osaka
The 8th APT (Asian Particle Technology Symposium) 2021
was held at Grand Front Osaka from Monday, October 11th toThursday, October 14th, 2021. This APT was launched mainlyby the Japanese Society of Powder Technology, Japan in order topromote the development of the powder technology in Asia andthe exchange of researchers in this field. The first meeting washeld in December 2000 in Bangkok, the capital of Thailand. It has
been held about once every three years, but this is the first time itis held in Japan. The Hosokawa Powder Technology Foundation
supported this symposium as part of its grant projects of the fiscal
year 2021.
In the opening remarks on the first day, Professor Satoru
Watano, Osaka Prefecture University, the chairperson of thesymposium, reported that the venue of this symposium had to bechanged just before holing it due to the sudden official decision to
use the reserved facility for the vaccination to control the COVID
pandemic. He explained about the situation which required to takethe style of hybrid conference using both face-to-face and online
communication. He announced that despite such strict conditions,
there were more than 300 presentations and more than 400 applications for participation from home and abroad. The symposium
began with the plenary lecture by Professor Makio Naito of Osaka
University. At the symposium, the lectures and research presentations were given for four days using five hall/rooms, until after 6
o’clock in the evening on the longest day, and there was also a live
question-and-answer session with active discussions.
At this symposium, the “Young KONA Award” was set foryoung researchers under the age of 40 as part of the 30th anniversary specific projects of the Hosokawa Powder Technology Foundation. About 40 presentations applied for this award, which werereviewed on the second day. From these applicants, six researchers
were selected as the awardees. The whole process concerning thisaward was managed by the Organizing Committee of this symposium, from application reception to screening and awarding, under
the auspices of the Hosokawa Powder Technology Foundation.
Then, before the closing on the 14th, the final day, there was anaward ceremony in the main hall of the venue. President Yoshio
Hosokawa handed each award winner a letter of presentation anda supplementary prize.
In the closing remarks, the Chairperson Professor Watano
reported that most of the research presentations were made asscheduled and it was a great success. Although it was difficult for
researchers overseas to attend face-to-face meeting, they could
join the symposium virtually. It was then announced that the next
symposium would be held in Brisbane, Australia in three years,
and the next chairpersons sent online invitation messages.

The venue for the symposium, Grand Front Osaka.
The conference room was on the second basement
floor.

Lecture scene, opening remarks being given by
Chairperson Prof. Watano.

Young KONA Award presentation ceremony. President of Hosokawa Powder Technology Foundation,
Mr. Hosokawa (center left in the photo), Symposium
Chairperson, Prof. Watano (center right in the photo)and six winners.

275

KONA Powder and Particle Journal No. 39 (2022) 276/https://doi.org/10.14356/kona.2022024

Information Article

The KONA Award 2020
The KONA Award 2020 was presented to Dr. Brij M. Moudgil, Distinguished Professor of Materials Science and Engineering at the University of Florida, USA. Overall goal of his research program has been to develop science and technology
platforms for the design and synthesis of nanostructured material with targeted performance and safety specifications. Specifically, controlling nano and atomic scale forces between particles, and synthesis of functionalized particles has formed
the foundation for targeted advances in minerals, advanced materials, biomedical, microelectronics, health & hygiene,
energy, agriculture, sensor, nanotoxicity and antimicrobial coating technologies.
He has served as Director of the Particle Engineering Research Center (PERC - formerly the National Science Foundation
Engineering Research Center for Particle Science & Technology) since its inception in 1994. He has also served as Associate Vice President for Interdisciplinary Research Programs at UF from 2004 to 2012, with the primary responsibilities
of promoting new interdisciplinary research teams, evaluating over 160 university centers and institutes, and serving as
a liaison with several U.S. funding agencies. He has been invited as an evaluator of individual and team funded research
proposals and interdisciplinary research centers, by funding agencies across the continents.
Dr. Moudgil has strongly supported and enthusiastically promoted particle technology related research and education opportunities, and challenges. He has invited world class research scholars to PERC from all over the globe and has mentored
several visiting young scientists and post-doctoral students including several of them from Japan. He feels truly privileged
to have had the opportunity to work with a talented group of students, research scientists & staff, visiting research scholars,
faculty colleagues, domestic and international collaborators, and industry researchers. He is proud of his team members
achievements – a number of whom continue to make pioneering research and leadership contributions in the private sector
and in the academic institutions alike. Over the years, he has forged strategic alliances for research and education between
UF-Particle Engineering Research Center and the other institutions that have common vision and complimentary expertisein particulate systems including University of Leeds, UK; Kyoto University, Japan; University of Melbourne, Australia;
Delft University of Technology, The Netherlands; Indian Institute of Technology-Bombay, India, and CMRDI, Cairo, Egypt.
He has been invited as a plenary and keynote speaker at conferences and seminars in Japan, Europe, India, South Korea,
Egypt, South America and Australia. He has authored/co-authored 13 books and has been awarded 31 patents. He hasserved as 2006 President of the Society for Mining, Metallurgy and Exploration, Inc. (SME). His contributions have beenrecognized with several honors and awards including the NSF Presidential Young Investigator Award (NSF-PYI), APT
Distinguished Paper Award, Fellow of the National Academy of Inventors (NAI), Fellow of the American Association
for the Advancement of Science (AAAS), Fellow of the Indian National Academy of Engineering (INAE), Distinguished
Alumnus Award of the Indian Institute of Science, Bangalore (IISc), and Member of the National Academy of Engineering(NAE), USA. Overall, Dr. Brij M. Moudgil has made pioneering contributions to particle and powder technology researchand education and is most deserving of the prestigious KONA award.

Selected research achievements for the KONA Award 2020: Interfacial engineering of particulate system for enhanced performance.

276

KONA Powder and Particle Journal No. 39 (2022) 277/https://doi.org/10.14356/kona.2022025

Information Article

General Information
History of the Journal
The KONA journal (currently called “KONA Powder andParticle Journal”) was first published in 1983 by the Council of
Powder Technology, Japan (CPT), which had been established in1969 by Hosokawa Micron Corporation as a nonprofit organization
to promote powder technology, in order to introduce excellent
Japanese papers to the world. From the issue of No.8, the CPT
changed its editorial policy to internationalize the KONA journal
and to incorporate papers by authors throughout the world. In
response to this change, three editorial blocks have been organizedin the world: Asian-Oceanian, American and European. The issues
from No.1 (1983) to No.12 (1994) of the KONA were published by
the CPT and the issues from No.13 (1995) by the Hosokawa Powder
Technology Foundation. The policy and system have not changed
even after the Hosokawa Foundation has taken over the publicationfrom the CPT. From the issue of No.27 (2009), publication oftranslated papers has been terminated and only original papers
have been published.
Aims and Scope
KONA publishes review and original research papers in a broad
field of powder & particle science and technology, ranging fromfundamental principles to practical applications. The papers on critical reviews of existing knowledge in special areas are very welcome.
The submitted papers are published only when they are judged
by the Editor to contribute to the progress of powder science andtechnology, and approved by any of the three Editorial Committees.
The paper submitted to the Editorial Secretariat should not havebeen previously published.
Category of Papers•	Invited articles
	
Review papers and feature articles invited by the KONA
Editorial Committees.
• Contributed papers
	Original review papers and some limited number of original
research papers of high quality submitted to the KONA
Editorial Committees, and refereed by the reviewers and editors.
Submission of Papers
It is now possible to submit your paper online via Editorial
Manager® for KONA Online Paper Submission and Peer Review
System. For all further information, please go to the journal’s
homepage on http://www.kona.or.jp/jp/journal/info.html.
Publication in KONA is free of charge.
Publication Schedule
KONA is published annually. The publication date is around
January 10th.
Subscription
KONA is distributed free of charge to senior researchers atuniversities and laboratories as well as to institutions and libraries
in the field throughout the world. The publisher is always glad toconsider the addition of names of those, who want to obtain thisjournal regularly, to the mailing list.
Instructions to Authors(1) Language
All submissions should be written in good English. Authors may
choose either British or American English, provided that the chosen
style is used consistently. Authors from non-English-speaking countries
are encouraged to use a professional English editing service toproofread their manuscript.

(2) Data Repository Information

In order to promote open data discoverability and use of research
outputs, this journal encourages authors to submit the data files
supporting your manuscript work, which can be deposited in thejournal’s J-STAGE Data site <https://jstagedata.jst.go.jp/kona> after
acceptance of the paper through the peer-review process.
These data may describe observations, experiments, modeling or
analyses and may take the form of databases, simulations, movies,
large figures or as otherwise appropriate.
If you have any questions or would like more information, pleasecontact the KONA Editorial Office (contact_zainq@hmc.hosokawa.com).

(3) Manuscript format•	Electric files should be submitted to the Editorial Secretariat byonline. Authors’ short biography with less than 100 words perperson and color photographs of all the authors should be
attached to the final version.
•	The structure of manuscripts should follow the following order;
title, authors, affiliations, abstract, graphical abstract, keywords,
main text, (acknowledgement), (appendix), (nomenclature), references. The items with parentheses are not mandatory.
•	Full postal addresses must be given for all the authors. Indicate
the corresponding author by the asterisk mark“*” after thename. Telephone and fax numbers and e-mail address should
be provided for the corresponding author.
•	Abstract should not exceed 200 words.
•	G raphical abstract should be a concise, visual summary of thearticle which will be displayed in the contents list both online
and print.
•	The appropriate number of keywords is 5 or 6.
•	The maximum pages printed in KONA are supposed to be:
15 for an original paper and 25 for a review paper.
•	Symbols and units should be listed in alphabetical order with
their definition and dimensions in SI units.
•	The color figures will appear in color both on the KONA
Website (http://www.kona.or.jp) and also in the paper version.
•	Concerning references, the alphabetical system should be
adopted. Please use reference management software such as
Endnote to manage references as far as possible.
List: References should be arranged first alphabetically andthen further sorted chronologically if necessary. More than one
reference from the same author(s) in the same year must be
identified by the letters “a”, “b”, “c”, etc., placed after the yearof publication.
Examples:- Reference to a book:trunk Jr. W., White E.B., The Elements of Style, fourth ed.,S
Longman, New York, 2000.

- Reference to a chapter in an edited book: ettam G.R., Adams L.B., How to prepare an electronic version ofM
your article, in: Jones B.S., Smith R.Z. (Eds.), Introduction to theElectronic Age, E-Publishing Inc., New York, 2009, pp.281–304.

- Reference to a journal publication:
 suji Y., Tanaka T., Ishida T., Lagrangian numerical simulation ofTplug flow of cohesionless particles in a horizontal pipe, Powder
Technology, 71 (1992) 239–250. DOI: 10.1016/0032-5910(92)88030-L

Text: All citations in the text should refer to:
1. 
Single author: the author’s name (without initials, unlessthere is ambiguity) and the year of publication;
2. Two authors: both authors’ names and the year of publication;
3. Three or more authors: first author’s name followed by “etal.” and the year of publication.
Citations may be made directly (or parenthetically). Groups ofreferences should be listed first alphabetically, then chron­ologically.
Examples:“ as demonstrated (Hidaka J. et al., 1995; Tsuji Y., 1992a,
1992b, 1993). Mori Y. and Fukumoto Y. (2002) haverecently shown ....”(4) Copyright and permission•	The original paper to be submitted to KONA has not been
published before in any language or in any journals or media; it
is not submitted and not under consideration for publication inwhole or in part elsewhere.
•	Authors are responsible for obtaining permission from the
copyright holders to reproduce any figures, tables and photos
for which copyright exists.
•	The KONA Journal applies the Creative Commons Attribution
License to all works published by the Journal. Copyright stays
with the agreed copyright owner, and the Hosokawa Powder
Technology Foundation is granted the exclusive right to publish
and distribute the work, and to provide the work in all forms
and media.
•	Users of the journal will be able to reuse the contents in any
way they like, provided they are accurately attributed. No
permission is required from either the authors or the publisher.

Free electronic publication of KONA is available at http://www.kona.or.jp277

Analytical Innovation in Particle Size Analysis
Mikro Air Jet Sieve® MAJSx2• CFR 21 Part 111 registration audit trail• 12 language options• Compatible with multiple balances & printers• Comparative ‘overlay’ of analysis results• VVacuum
acuum pressure displayed in multiple formats• Slit wand boost rotation speed for difficult materials

CONTACTCONTACT US TODAY
TODAY
ODA
www.hmicronpowder.com • (908) 273-6360 • help@hmps.hosokawa.com

Process Technologies for Tomorrow