ISSN 0288-4534

CODEN: KPPJAD

KONA

Powder andParticle Journal

No.37 (2020)

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

KONA Powder and Particle Journal No. 37 (2020)www.kona.or.jp

About this Journal

Editorial Board

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.

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)
J. Hidaka(Doshisha Univ., Japan)
E. Iritani(Nagoya Univ., Japan)
H. Kage(Kyushu Institute of Technology, Japan)
Y. Kang(Chungnam National Univ., Korea)
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)
Pradip(TCS, India)
F. Saito(Tohoku Univ., Japan)
Y. Sakka(NIMS, Japan)
H. Takeuchi(Gifu Pharmaceutical Univ., Japan)
W. Tanthapanichakoon (Tokyo Institute of Technology, Japan)
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)

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
Physical and chemical properties of cohesive powders need
to be considered in the powder processing and manufacturing operations of the industries treating particulate solids.
The dynamic behavior of the cohesive powder greatly depends on particle size and shape, degree of aggregation/
agglomeration, charge amount, wettability, friction, and conditions of exposed environment. In the characterization ofcohesive powders, various types of quasi-static method havebeen established and widely used, especially for powder
spreading in additive manufacturing and 3D printing. In contrast, powder rheometry instrument, which is important toevaluate the dynamic behavior of flowing powders, is limited. Review on this topic is discussed on pp. 3–18.

European / African Editorial Board
Chairman
G.M.H. Meesters(Delft Univ. of Technology, Netherlands)
F. Bourgeois(Univ. of Toulouse, France)
M.-O. Coppens(Univ. College London, UK)
L. Gradon(Warsaw Univ. of Technology, Poland)
A. Kwade(TU Braunschweig, Germany)
P. Milani(Univ. of Milan, Italy)
M.G. Rasteiro(Univ. of Coimbra, Portugal)
J.M. Valverde(Univ. of Seville, Spain)
Secretariat
S. Sander(KONA Europe e.V., Germany)
S. Wilk(KONA Europe e.V., Germany)
American Editorial Board
Chairman
B.M. Moudgil(Univ. of Florida., USA)
A.J. Hickey(Univ. of North Carolina, USA)
V. M. Puri
(Pennsylvania State Univ., USA)
R.K. Rajamani(Univ. of Utah, USA)
A.D. Rosato(New Jersey Institute of Technology, USA)
L.M. Tavares(UFRJ, Brazil)
Secretariat
C.C. Huang(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 2020

KONA Powder and Particle Journal No. 37 (2020) Contents<Editorial>
1

Editor's Preface<Review Papers>
3

Cohesive Powder Flow: Trends andChallenges in Characterisation and Analysis

Mojtaba Ghadiri, Mehrdad Pasha, WenguangNan, Colin Hare, Vincenzino Vivacqua, Umair
Zafar, Saeid Nezamabadi, Alejandro Lopez,
Massih Pasha and Sadegh Nadimi
19

Present Status of Air Filters and Explorationof Their New Applications

Myong-Hwa Lee, Hyun-Jin Choi, Mikio Kumita
and Yoshio Otani
28

Continuous Flow Synthesis of Nanoparticles
Using Supercritical Water: Process Design,
Surface Control, and Nanohybrid Materials

Akira Yoko, Gimyeong Seong, Takaaki Tomaiand Tadafumi Adschiri
42

Analysis of Industry-Related Flows by
Optical Coherence Tomography—A Review

Antti I. Koponen and Sanna HaavistoiKONA Powder and Particle Journal No. 37 (2020) 

64

Microbial Aerosols: Sources, Properties,
Health Effects, Exposure Assessment—A
Review

Rafał L. Górny
85 Review of Encapsulated Salt Hydrate CoreShell Phase Change Materials

Hui Wang, Yunfa Chen, Jianqiang Li, Lijiang
Guo and Minghao Fang
97

Nanoparticle Technology for Respiratory
Tract Mucosal Vaccine Delivery

Leah M. Johnson, Jeffrey B. Mecham, Frederick
Quinn and Anthony J. Hickey
114

Fluidised Bed Reactors for the
Thermochemical Conversion of Biomass andWaste

Stefano Iannello, Shane Morrin and
Massimiliano Materazzi

ii

Contents

KONA Powder and Particle Journal No. 37 (2020) Contents

132 Recent Progress on Mesh-free Particle
Methods for Simulations of Multi-phase
Flows: A Review

Mikio Sakai, Yuki Mori, Xiaosong Sun andKazuya Takabatake
145 Rheology and Sedimentation of Aqueous
Suspension of Na-montmorillonite in the
Very Dilute Domain

Yasuhisa Adachi, Yoko Tsujimoto Kawashima
and Muhamad Ezral Bin Ghazali<Original Research Papers>
166 Shape Controllable Synthesis of Silver
Particles by Selecting the Crystallization
RoutesJianmei Liu, Qiang Lin, Yu Zhou, Jinhui Dai
and Yongsheng Han

iii

KONA Powder and Particle Journal No. 37 (2020) 

176

Real-time in-situ Rheological Assessment ofSticky Point Temperature and Humidity of
Powdered Products

Johan C. Groen, Wim Kooijman, Djamilla vanBelzen, Gabrie M.H. Meesters,
Denis Schütz, Timothy Aschl and Patrick
Verolme187

Development and Validation of a Simplified
Laboratory Test to Design Vertical Stirred
MillsMaurício G. Bergerman and Homero Delboni
Junior195

Integrating Particle Microstructure,
Surface and Mechanical Characterization
with Bulk Powder Processing

Rodolfo Pinal and M. Teresa Carvajal
214

Preparation and Properties of Spherical
Natural Rubber/Silica Composite Powders
via Spray Drying

Siah Ying Tang, Prachaya Sopanon, Wiwut
Tanthapanichakoon and Apinan Soottitantawat

iv

Contents

KONA Powder and Particle Journal No. 37 (2020) 

224

Contents

Synthesis of Precision Gold Nanoparticles
Using Turkevich Method

Jiaqi Dong, Paul L. Carpinone, Georgios
Pyrgiotakis, Philip Demokritou andBrij M. Moudgil
233

NMR as a Tool to Characterize theAggregation Structure of Silica
Nanoparticles in a Liquid

Chika Takai-Yamashita, Emiko Sato and
Masayoshi Fuji
244 Production of Hematite Micro- andNanoparticles in a Fluidized Bed Process—Mechanism Study

Nadine Le Bolay, Rihab Lakhal and Mehrdji
Hemati258 Electrodynamic Sorting of Industrial Scrap
Metal

James R. Nagel, Dave Cohrs, Jacob Salgado and
Raj K. Rajamaniv

KONA Powder and Particle Journal No. 37 (2020) <Information Articles>
265 Book Review

268

The 53rd Symposium on Powder Technology

270 The KONA Award 2018
(Awardee: Prof. Dr. Mojtaba Ghadiri)

271 General Information

Selected research achievements for the KONA Award 2018: Recent work on DEM simulation of
powder spreading by a roller for additive manufacturing; spread layer uniformity is affected bytransient jamming for narrow gaps and size segregation within the heap (courtesy of Dr W. Nan).
(p.270)vi

Contents

KONA Powder and Particle Journal No. 37 (2020) 1–2/Doi:10.14356/kona.2020020

Editorial

Editor’s Preface
On Editorial Policy of KONA
Powder and Particle Journal
Kikuo Okuyama, Editor-in-Chief
Hiroshima University, Japan

It is my great pleasure to introduce the latest issue of KONA Powder and Particle Journal No. 37 (2020). As a tradition of every issue, this issue blends review articles and original research papers which have passed a rigorous review process led by the Editorial Boards of Asia/Oceania, Europe/Africa, and America. The articles in this issue
have been released as Advance Publication on J-STAGE (https://www.jstage.jst.go.jp/browse/kona/) since September 30, 2018. The entire issue is published on-line on the homepage of Hosokawa Powder Technology Foundation(https://www.kona.or.jp/jp/journal/index.html) and in 1,100 printed copies in January 2020.
It has always been our aim to deliver you the latest advancements in powder and particle technology, as we understand that powder and particles are inseparable from future manufacturing industry. Research related to powder
and particles has spread across a wide spectrum, from ceramics, electronic materials, to food and pharmaceuticals.
In-depth studies have been performed by researchers from diverse communities to understand the phenomena andprocesses concerning powder and particle technology. This trend is shown in the research papers on powder andparticle technology, of which the numbers are dramatically increasing throughout the decades. These papers havebeen published not only in main traditional journals of powder and particle technology but also journals in engineering, basic sciences, pharmacy, and medicine.
Technological advances which enable the powder and particles to be smaller yet more complex (i.e., highly integrated, functional, and having hierarchical structures, etc.) should be well communicated to other researchers andindustrial practitioners through high quality research papers and review articles. Review articles are especially important to fulfill the demands from researchers and engineers who are looking for reliable sources which summarize all this rapidly advancing research to understand the research trends, latest information, and future tasks in thespecific subjects. In this light, KONA Powder and Particle Journal aims to publish mainly review articles by theleading researchers. We strongly encourage leading researchers who have been studying powder/particles withbroad impacts to both scientific and industrial communities to contribute in our journal. Young researchers who received a Ph.D. degree on a topic closely related to powder/particles within several years are also welcome to contribute review articles based on their Ph.D. research.
Regardless of review articles and research papers, submission to KONA Powder and Particle Journal implies that
all authors have read and complied with the Journal’s policies on publication ethics. We only accept the manuscript
which has not been previously published, is not in press, and is not under consideration for publication elsewhere.
It is now possible to submit your manuscript online via Editorial Manager for KONA Online Paper Submission and

Copyright © 2020 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

1

Paper Review System. For all further information, please go to the Journal’s homepage on http://www.kona.or.jp/
journal/info.html. Publication in KONA Powder and Particle Journal is free of charge for the authors.
On May 1st 2019, the Japan’s Era name changed from Heisei to Reiwa, which means “beautiful harmony”. I hope
the change of era inspires us, as researchers, industrial practitioners, and editorial board of KONA Powder and Particle Journal, to strongly cooperate for the better advancements of powder and particle technology in a beautiful
harmony.

Reviewer Appreciation
I express our gratitude to the reviewers for the publication of this KONA Powder and Particle Journal. Thanks to
the generous contributions of the volunteer reviewers as well as the interest of researchers in our journal, the number of submission to this journal is increasing after the registration on the major international journal platforms andits level is further improving. Because of the limited space of this annual journal, the number of papers publishedthere is regrettably rather restricted. Therefore the papers of good quality need to be selected for the journal andfurther improved and refined by the reviewing.
The editorial team of 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 reviewer who may have inadvertently been omitted from this list. We are sincerely grateful to all who havebeen of any assistance to the publication of this journal.

FUJI, Masayoshi

MEESTERS, Gabrie M.H.

SAITO, Fumio

GRADOŃ, Leon

MUTTIL, Pavan

SAKAI, Mikio

HICKEY, Anthony

MYOJO, Toshihiko

TANAKA, Toshitsugu

IIJIMA, Motoyuki

NOMURA, Toshiyuki

TAVARES, Luís Marcelo Marques

IRITANI, Eiji

OGATA, Koichiro

TOKORO, Chiharu

ISHIGAMI, Toru

OGI, Takashi

VALVERDE, José Manuel

KANO, Junya

PURI, Virendra

YAMAMOTO, Tetsuya

KUROSE, Ryoichi

RAJAMANI, Raj

YOKOYAMA, Toyokazu

MATSUSAKA, Shuji

RASTEIRO, Maria da Graça

MATSUYAMA, Tatsushi

REN, Jie

Kikuo Okuyama
Editor-in-ChiefProf. Emeritus, Hiroshima University
October, 20192

KONA Powder and Particle Journal No. 37 (2020) 3–18/Doi:10.14356/kona.2020018

Review Paper

Cohesive Powder Flow: Trends and Challenges in
Characterisation and Analysis †Mojtaba Ghadiri 1*, Mehrdad Pasha 1, Wenguang Nan 2, Colin Hare 3, Vincenzino Vivacqua 1,
Umair Zafar 1, Saeid Nezamabadi 4,5, Alejandro Lopez 6, Massih Pasha 1,7 and Sadegh Nadimi 8
1

School of Chemical and Process Engineering, University of Leeds, UK
School of Mechanical and Power Engineering, Nanjing Tech University, China
3
Department of Chemical and Process Engineering, University of Surrey, UK
4
LMGC, Université de Montpellier, CNRS, France
5
IATE, CIRAD, INRA, Montpellier SupAgro, Université de Montpellier, France
6
University of Deusto, Spain
7
The Chemours Company, Wilmington, Delaware, USA
8
School of Engineering, Newcastle University, UK
2

Abstract
Powder processing and manufacturing operations are rate processes for which the bottleneck is cohesive powder
flow. Diversity of material properties, particulate form, and sensitivity to environmental conditions, such as
humidity and tribo-electric charging, make its prediction very challenging. However, this is highly desirable
particularly when addressing a powder material for which only a small quantity is available. Furthermore, in a
number of applications powder flow testing at low stress levels is highly desirable.
Characterisation of bulk powder failure for flow initiation (quasi-static) is well established. However, bulk flow
parameters are all sensitive to strain rate with which the powder is sheared, but in contrast to quasi-static test
methods, there is no shear cell for characterisation of the bulk parameters in the dynamic regime. There are only ahandful of instruments available for powder rheometry, in which the bulk resistance to motion can be quantified
as a function of the shear strain rate, but the challenge is relating the bulk behaviour to the physical andmechanical properties of constituting particles. A critique of the current state of the art in characterisation andanalysis of cohesive powder flow is presented, addressing the effects of cohesion, strain rate, fluid medium dragand particle shape.
Keywords: cohesive powder, bulk flow, characterisation, flowability, spreadability, additive manufacturing

1. Introduction
Particulate solids are ubiquitous in many manufacturing industries, ranging from pharmaceuticals, foods,
chemicals and minerals to additive manufacturing, whichis the fastest growing sector in high value manufacturing
and depends critically on powder spreading. Powder pro-

†
1
2
3
4
5
6
7
8

*

Received 28 August 2019; Accepted 24 September 2019
J-STAGE Advance published online 19 October 2019
Leeds LS2 9JT, United Kingdom
Nanjing 211816, China
Guildford, Surrey GU2 7XH, United Kingdom
860 Rue de St - Priest, 34090 Montpellier, France
2 place Pierre Viala, 34060 Montpellier, France
Avenida de las Universidades 24, Bilbao, 48007, Spain
1007 Market Street, Wilmington, Delaware, United States
Merz Court, Newcastle upon Tyne NE1 7RU, United Kingdom
Corresponding author: Mojtaba Ghadiri;E-mail: m.ghadiri@leeds.ac.uk
TEL: +44(0)113-343-2406 FAX: +44(0)113-343-2384

cessing and manufacturing operations are rate processes
for which the bottleneck is cohesive powder flow. Diversity of material properties and sensitivity to environmental conditions, such as humidity and tribo-electriccharging, make the prediction of powder flow very challenging. However, such prediction is highly desirable particularly when addressing a powder material for which
only a small quantity is available or when flow testing at
low stress levels is required.
Characterisation of bulk powder failure for flow initiation (quasi-static) is well established, although empiricism
is still the order of the day. There are in fact a large number of commercial devices as well as some developed inhouse, which can apply a compressive and shearing or atensile load to a powder bed and provide information on
bulk density, bulk cohesion, internal and wall angles offriction, unconfined yield stress and tensile failure stress,
all of which can be obtained as functions of applied loadand consolidation time. Examples of such instruments

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

3

Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

include: Schulze Ring Shear Tester (Schulze, 1994),
Brookfield Powder Flow Tester (Berry et al., 2014), Jenikeand Peschel Powder Testers, as reviewed by Schwedes
and Schulze (1990), Salerno Unconfined Compression
Tester (Parrella et al., 2008), Edinburgh Powder Tester(Bell, 2007), Environmental Caking Tester (Calvert et al.,2013), Ball Indentation Method (Hassanpour and Ghadiri,2007), SSSpin Tester of Material Flow Solutions Inc.
(Johanson, 2019), the shear cell of FT4 Powder Rheometer(Freeman Technology), Sevilla Powder Tester (Castellanos
et al., 2004), and the Calabria Raining Bed method(Girimonte et al., 2018). These testers all produce different
quantitative values of the bulk parameters, as the powder
response depends on the residual stress history and bulk
structure. Cohesive powders readily form clusters, thesize and packing density of which depend on the stresshistory (Li et al., 2018; Ku et al., 2015). Moreover, beyond
the quasi-­static regime the bulk flow parameters are allsensitive to shear strain rate (Tardos et al., 2003), but incontrast to quasi-static test methods, there is no shear cellthat can characterise the bulk parameters at high strain
rates, i.e. in the dynamic regime. There are only a handfulof instruments available for powder rheometry, the mostprominent ones being the FT4 Rheometer of Freeman
Technology, the powder cell of Anton Paar Modular Compact Rheometer and a Couette device, as described later
below. In these devices the bulk resistance to motion canbe quantified as a function of speed of shearing (strainrate) and is reviewed here. However, a challenge remains
to relate the bulk rheological characteristics, i.e. bulk friction and viscosity, to the physical and mechanical properties of constituting particles in order to predict the bulk
flow behaviour.
For free flowing (cohesionless) granular materials, thedimensionless group inertial number, I, has been proposed to account for the dependence of bulk internal friction coefficient, μ b, and apparent shear viscosity offlowing powder, η, on the shear strain rate:I  d p

p
P

(1)

where γ is shear strain rate (1/s), dp is particle size (m), ρp
is particle density (kg/m3), and P is hydrostatic pressure(N/m 2). It is noteworthy that the dimensionless shear
strain rate, γ0, proposed by Tardos et al. (2003), is a special case of inertial number, where the pressure is approximated by the stress exerted by the weight of a single
particle distributed over its projected area:0  

dpg(2)

where g is gravitational acceleration (m/s2). For cohesionless particles, Jop et al. (2006) propose the following form
for the bulk internal friction coefficient:

4


b


 2  1
 1 
P
I0 / I 1(3)

where τ is the shear stress, μ1 is the bulk friction coefficient in the quasi-static regime, μ2 is the asymptotic value
corresponding to large inertial numbers and I0 is a fitting
constant. Chialvo et al. (2012) propose a similar functional form with slightly different constants in the above
equation.
The apparent shear viscosity, η = τ/γ, generally follows
a typical shear-thinning Non-Newtonian trend, but the influence of particle shape, adhesive interactions and medium fluid drag has not yet been extensively analysed.
Rognon et al. (2008) modelled shear deformation ofdense cohesive granular material by Discrete Element
Method (DEM) using a simple cohesive force, which approximates the DMT theory (Derjaguin et al., 1975), together with a linear spring model for the normal force andCoulombic friction condition for the tangential direction.
Various features of the macroscopic bulk behaviour suchas bulk friction, microstructure, anisotropy and void fraction were analysed. More recently, Berger et al. (2015)
propose an extension for cohesive powders by defining acohesive inertial number:Ic I1  

(4)

where β is the ratio of cohesive contact force over thenormal stress and particle size, i.e. fc/(σn dp) for a two-­
dimensional geometry, α is a coefficient accounting forthe structure of the packing or the details of dissipation
mechanisms during flow. Its equivalence for bulk powdermaterials is the modified Bond number, describing the ratio of the adhesive force over the particle weight, i.e. fc/mg.
For a wide range of conditions, their simulation predictions for the dependence of bulk cohesion, following Coulomb’s law, are unified against the cohesive inertial
number. Their analysis prescribes the dependence of bulk
cohesion as well as bulk friction coefficient on the shear
strain rate. A method and device are therefore requiredfor validation of such simulation trends. As mentioned
above, there is no shear cell which can characterise thebulk parameters in the dynamic regime. There are only
three instruments available for powder rheometry: theCouette device (Tardos et al., 2003), the FT4 Powder Rheometer of Freeman Technology (Freeman, 2007), as analysed recently by a large number of workers, see e.g.
Bharadwaj et al. (2010), Hare et al. (2015), Nan et al.
(2017a-c), Wilkinson et al. (2017) and Vivacqua et al.
(2019) and the powder cell of Anton Paar Modular Compact Rheometer, as recently analysed by Salehi et al.
(2018). There are of course other instruments, such as
GranuDrum of GranuTools (Lumay et al., 2012), Hall
Flow Tester (ASTM B213-17) and Hosokawa Micron
Powder Tester (ASTM D6393-08), with the latter integrating

Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

several test methods into one instrument, giving indirect
measures of bulk behaviour under flowing conditions.
Recently, Ogata (2019) has reviewed the latest works on
the evaluation of flowability and floodability of powders
with a focus on the experimental methods. In the work reviewed here, we provide a complementary critique of current trends and challenges in the characterisation methods
and instruments, and analysis of dynamics of cohesive
powder flow with a focus on the rheological properties
and methods for their characterisation. The effects of particle size and shape, fluid drag, cohesion and strain rate
are covered.

2. Instruments for powder rheometry
Powders exhibit extreme dynamic flow behaviour fromhighly frictional to almost inviscid, as influenced by particle properties, the drag of the fluid medium and thestrain rate. We first review the state of the art in measurement of the bulk rheological response of cohesive powders, subjected to shear straining, followed by a critiqueof current understanding of the effects of particle properties and process conditions. The dynamic flow testers may
conveniently be classified into two categories: (i) thosewhich address powder rheometry by measuring the powder resistance to shearing as a function of shearing speed
by a rotating impeller or surface, and (ii) other dynamic
flow testers in which the flow behaviour and characteristics are indirectly inferred. In the first category the Couette device, powder cell of the Anton Paar Modular
Compact Rheometer and FT4 Powder Rheometer of Freeman Technology are placed. The rotating drum and Ball
Indentation Method (BIM) at high strain rates, are placedin the second category. We also include here a review of
powder spreadability testing by a blade in view of its increasing importance in additive manufacturing and its relation with powder flowability.

2.1 Powder rheometers2.1.1 Couette device

This is a simple device based on the design of a classic
liquid rheometer, consisting of two co-axial vertical cylinders in which powder is sheared in the annular gap between the two cylinders by rotating the inner cylinderwhilst keeping the outer cylinder stationary (Lun et al.,
1984; Tardos et al., 1998). Such a device is common for
rheological measurements of liquids, though was first reported for powders by Savage and Sayed (1984). It is necessary to ensure the powder is gripped at the wall toprovide a no-slip boundary condition and therefore ensurethat the entire bed is sheared, as such sandpaper is typically glued to the cylinder walls (Tardos et al., 2003). The

normal stress is adjusted simply by varying the mass of
powder above the sheared bed, referred to as the ‘overburden’. Sensors are placed at the outer wall that enable measurement of normal and shear stresses across the height ofthe sheared region.
A Couette device can be operated in ‘batch’ or ‘continuous’ mode; with a slow, downward axial flow of powder
being introduced in the latter, with the removed powder
being recirculated to the top, whilst no such axial flow is
induced in the former. Batch mode (no axial flow) results
in a near constant packing fraction regardless of the shear
rate induced by the Couette (Vidyapati, 2012), and consequently leads to shear stress remaining constant acrossthe range of shear rates (Langroudi et al., 2010). It should
be noted that the reported work is for large, granular media, and for fine, cohesive powder it could be expectedthat packing fraction would still vary with strain rate inbatch mode. In continuous mode, at low shear rates thepacking fraction is lower than that in the batch mode operation, and consequently so is the shear stress, however
an increase in shear rate results in dilation and a subsequent increase in shear stress as the flow approaches thecollisional regime. Experimental work reported by Savage
and Sayed (1984), Qin (2000), Klausner et al. (2000) andTardos et al. (2003) show the dependency of the shear
stress on the strain rate for a number of materials in thequasi-static, intermediate and dynamic regimes, where
there is a general agreement that the shear stress increases
with strain rate in the intermediate and dynamic regimes.
Tardos et al. (2003) defined approximate boundaries ofthe dimensionless shear strain rate for the quasi-static tointermediate (γ0 = 0.15 to 0.25) and intermediate to rapid(γ0 = 3) granular flow regimes, based on the dimensionless strain rate given by Eq. (2). Vidyapati et al. (2012)carried out DEM simulations of this device and showed
agreement with these boundaries, and indicated that the
number of enduring contacts reduces with increasingstrain rate, and increases with solid fraction and particle
friction.
Langroudi et al. (2010) expressed the bed stress ratiousing Eq. (5).


 a  b n(5)where τ and σ are shear and normal stresses, respectively,
and a, b and n are constants. This can be further generalised by substituting a = tan(ϕ), where ϕ is the internalangle of friction, thus at zero shear rate Eq. (5) reduces to
the Coulomb yield condition with no cohesion.
The vertical force due to gravity compressing the powder is not constant throughout the bed; varying significantly with depth since the cylinders are tall (Tardos etal., 1998). Contradictory trends of vertical and radialstress variations throughout the bed height have been5

Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

shown, with Tardos et al. (1998) finding the stress variedwith ρgz, Tardos et al. (2003) finding stress scaling with3tan(ϕ)ρgz, and Gutam et al. (2013) showing an exponential growth of stress with z. Furthermore, Gutam et al.
(2013) show that the direction of σrz switches at the onsetof shearing, and that the stress variation across the powder bed is dependent on the gap width. It is suggested that
this could be driven by a downward flow of particles near
the outer wall, due to the anisotropic bed fabric; an observation that shows that the strain field is not as simple asthat intended by the Couette design. Anisotropy of thebed fabric has been shown for much simpler systems ofstatic sand piles (Vanel et al., 1999) and during shear(Howell et al., 1999), and hence it is expected that thiswould indeed also be the case in the more complex
Couette flow. Furthermore, Gutam et al. (2013) state that
Couette is one of the few devices where gravity is perpendicular to the shear direction, which may have significant
effects on the rheology, however this is also true of bladedriven powder rheometers that are discussed further below. Another drawback of the Couette device is thepotential for wall slip at the rotating inner cylinder, andsteps should be taken to mitigate it. This device also requires a large quantity of powder, so it is not suitable for
instances where the powder quantity is scarce.

2.1.2 Powder cell of the Anton Paar modular compact
rheometer

The Anton Paar powder rheometer measures the torquerequired by an impeller blade to rotate at a fixed heightinside a powder bed. Different impeller shapes are available (cylindrical, including one having grooved surfaces,
blade, and a ring with radial fins) to investigate the resistance to shearing and influence of wall friction. The powder cell is a 50 mm diameter glass cylinder, having a
porous base plate for aeration. The torque sensor canmeasure a wide range (10 –8 to 0.3 Nm), making it possible
to accurately measure the torque whilst the powder is fluidised and sheared. In a standard test procedure the bladeis placed at 10 mm above the bottom of the cell and canbe rotated from a very slow speed of 0.001 to 500 rpm.
The powder bed can also be conditioned prior to torquemeasurement to remove any residual vertical friction due
to insertion of the impeller in the bed. Recently, Salehi etal. (2017), evaluated the Anton Paar powder cell for characterising flowability at low stresses using glass beads,
sand and alumina powder. They reported that the minimum torque necessary to rotate an impeller in a powder
bed depends on material properties, air flow rate, impeller
depth and shape of the impeller. Furthermore, Salehi et al.
(2018) compared torque measurements between different
sizes of glass beads and different impeller geometries andused DEM to analyse the dynamic behaviour of the powder. Differences between the temporal profiles of torque6of different impeller shapes are reported which might be
attributed to the differences in shearing surfaces and theformation of instantaneous high magnitude force chains.
Moreover, as the flow response is measured at a fixed position of the rotating component in the powder bed, theresults may not be representative for the whole powder
bed (e.g. due to a number of factors such as segregation,
local aeration, slipping, etc.). On the other hand, the vertical stress is constant throughout the measurement, whichis advantageous for analysis.

2.1.3 FT4 powder rheometer of Freeman Technology

This instrument (referred to as FT4 herein) measuresthe mechanical work done by a twisted-shape impeller
while penetrating into a powder bed at given rotationaland downward translational speeds (Freeman, 2007). The
expended work is taken as a measure of flowability underdynamic condition. Two types of test can be carried out: adownward test and an upward test. In the downward test
the impeller rotates anticlockwise with its blade surface
facing downward, thus compressing and shearing thepowder bed. The work expended in this test has beentermed ‘Basic Flow Energy (BFE)’. In the upward test,
once the downward traverse is complete and the impeller
is close to the bottom of the bed, the rotation direction isreversed (clockwise) and the impeller cuts and lifts thepowder bed i.e. a dominant tensile and shearing action.
The work associated with this action per unit mass of thematerial is known as ‘Specific Energy (SE)’.
Nowadays, FT4 is used extensively in industry to provide a relative measure of the ease with which powder
flows. For example, Fu et al. (2012) reported that FT4
could be used to identify the importance of the effect ofparticle size and shape of three grades of lactose particles.
Li et al. (2018) attributed the torque fluctuation of highlycohesive powders to breakage of cohesive clusters.
Wilkinson et al. (2017) carried out a parametric evaluation of flowability as indicated by FT4 through statisticaland sensitivity analyses using DEM. A question which
naturally emerges is how the work expended on both penetrating and withdrawing the impeller is influenced byparticle properties, and whether it can actually reflectbulk rheological properties, such as bulk friction andshear viscosity. In recent years, a good number of attempts have been made to elucidate the correlation between the expended work and the bulk mechanical andrheological features of cohesive powders. Using silanisation to provide controlled bulk cohesion for otherwise
free flowing glass ballotini, Hare et al. (2015) showed thatthe expended work can be simulated by Discrete Element
Method (DEM). Several attempts have been made to link
the measured flow energy from FT4 to processes that thepowder experiences at high strain rates (Goh et al., 2018;
Mellin et al., 2017). However, no direct correlation has

Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

been consistently found. In another study, Li et al. (2018)
showed that cohesive powders exhibit cyclic torque in
FT4, and as cohesion increases, the cycle time increases,
whilst free-flowing powders act like liquids with no periodic response. It is noteworthy that powder flow in industrial operations is not necessarily actuated by a moving
impeller, and therefore the influence of the presence of theimpeller on the powder rheology cannot be ignored, due
to the potential of slip on the impeller tip and containing
walls, and the local aeration or jamming of particles in
the impeller-wall clearance. Nevertheless, to use FT4 andAnton Paar instruments as powder rheometers, it isclearly necessary to analyse the mechanics of powder flow
induced by the impeller and relate the expended work to
the bulk powder rheological characteristics. For this purpose, Ghadiri and co-workers have carried out a systematic study of the effects of cohesion, air drag and strain
rate, and particle shape on bulk powder rheology by analysing the stress and strain fields within FT4 using numerical simulations by a combined DEM-CFD approach (Nanet al., 2017a, b, c; Vivacqua et al., 2019). With current
computer power and memory, it is too challenging to use
fine cohesive powders with a complex shape in such simulations. For this reason, each effect of cohesion, air drag,and particle shape has been analysed separately as a function of strain rate using large particles for which experimental validation can be made. Salient features of theoutcomes of their analysis are summarised in section 3 on
the analysis of cohesive powder flow.

2.2 Other dynamic flow testers
2.2.1 Rotating drum

One of the most practical geometries used to study theflow properties of powders, or more generally granularmaterials, is the rotating drum (e.g. GranuDrum of
GranuTools and Revolution Powder Analyzer of Processtechnik). It is a free surface flow test under dynamic avalanching condition, contrary to shear testers, where apowder bed is subjected to a compressive load and the resistance to shearing is measured (Nalluri and Kuentz,
2010; Lumay et al., 2012; Yang et al., 2016). The free dynamic flow inside the rotating drum is similar to many industrial processes such as mixers, granulators, and heap
formation. The non-cohesive (or mildly cohesive) powder
flow inside the rotating drum is commonly defined as afunction of the Froude number Fr = RΩ2/g (where Ω is therotational speed and R is the drum radius). It can take on
one of a number of regimes such as slumping, rolling,cascading, cataracting and centrifuging. By measuring
the flowing angle or speed, all of these regimes can becharacterised (MiDi, 2004; Fischer et al., 2008; Morrison
et al., 2016). For cohesive powders, determining these parameters is difficult due to the irregular surface of theflow and the lack of a continuous regime. In this context,
some authors propose to measure the standard deviationof the fluctuations of the flow interface in order to characterise the cohesive powders (e.g. Alexander et al., 2006;
Lumay et al., 2012, 2016). However, such dynamic tests
are generally very challenging to interpret, as adhesive
contacts cause clump formation, and adhesion and particle friction have a coupled effect on flow. Although more
relevant to free-flowing powders, rotating drums are very
effective in causing segregation, adversely affecting thehomogeneity of the powder and hence rheological response.

2.2.2 Ball indentation method (BIM) at high strain
ratesThis test method was initially developed for quasi-static
testing of the flow resistance of a powder bed against thepenetration of a spherical indenter, which promotes shearing of the bed without further compression (Hassanpour
and Ghadiri, 2007). The flow resistance, expressed as
hardness, can be related to unconfined yield strength by
the constraint factor—a material dependent property—
which can be established by carrying out measurementsof hardness and unconfined yield strength under identicalconsolidation conditions. Zafar et al. (2017) have shown
the constraint factor to be independent of consolidationstress for a given material. This technique has the advantages of being applicable at low consolidation stresses andrequiring only a very small quantity of powder, whilst thedisadvantage is measuring hardness rather than unconfined yield strength directly.
The BIM has recently been extended to the dynamic
range by dropping a ball onto a powder bed and measuring its penetration depth (Zafar et al., 2019). The dynamic
flow resistance expressed by the dynamic hardness of thepowder bed surface, H, is determined byH

1 MV 22 U(6)where M is the mass of the indenter, V is the indenter velocity at impact and U is the volume of the crater formedby the indentation (Tirupataiah and Sundararajan, 1990).
On the face of it, dynamic indentation appears to be a relatively quick and simple approach for assessing powder
flowability under a wide range of strain rates. However, as
well as the disadvantages listed above, this technique isalso challenging to apply in practice and requires further
development. Moreover, dependence of the constraint factor on strain rate needs to be established if the powder
yield stress, rather than the flow resistance, is desired.
Since the indenter is fired at the sample at a given velocity (or released from a given height), the depth to which
it penetrates the powder bed is not directly controlled. It
has been shown for quasi-static indentation that the7Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

hardness should be measured in a given acceptable rangeof the penetration depths (Pasha et al., 2013; Zafar et al.,2017). So iterative refinement of test conditions may berequired in order to generate reliable flow measurement
results at higher strain rates. If the quasi-static hardness isknown a priori, then the penetration depth can be estimated for an indenter of given size, density and velocity,and hence a maximum velocity which enables reliablemeasurement can be determined. However, since the expectation is that flow resistance will vary with strain rate,
this approach can only provide an estimate of the upper
operational range. Other practical considerations of the
dynamic indentation test are the requirement to measurepenetration depth (to determine the crater volume) and theindenter velocity. A high-speed camera can serve both
functions. In order to explore a wider range of strain
rates, a variety of indenters of differing material and size
can be applied from a range of drop heights, as shown by
Tirapelle et al. (2019)

Fig. 1Discrete Element Method simulation and experimental
validation of spreading of gas-atomised metal powders
by a blade, showing empty patches and size segregation in the spread layer as a function of spreader gap
height. Narrow gaps cause transient jamming, as evident by empty patches. The frequency of formation andsize of empty patches can also be inferred, as shown in
Fig. 2. The particles are coloured based on their projected area equivalent circle diameter, blue (15–25 μm),
dark grey (25–35 μm), light grey (35–45 μm), and red(45–55 μm). The number density of the largest particles(shown in red) is the lowest for the smallest gap, as
predicted by Nan et al. (2018). The simulation results
are for four gap heights and the experimental one is ascanning electron micrograph for the smallest gap,
courtesy of Mr M.T. Hussein. Gap heights are normalised with respect to the characteristic particle size
below which 90 % of particles by number lie (D90).

Fig. 2Frequency of empty patches for each patch length as afunction of gap height (Nan et al. (2018), https://doi.
org/10.1016/j.powtec.2018.07.030. Copyright: (2018)
Elsevier B.V. under https://creativecommons.org/
licenses/by/4.0/.

2.2.3 Powder spreadability testers for additive
manufacturing

Characterisation of bulk cohesive powder flow has recently attracted increased attention for powder spreadingin additive manufacturing (AM). However, there is no
standard method for testing whether a given powder can
produce the required spread uniformity for further processing. Across the community, every possible characteristic of bulk mechanical properties is being analysed in an
attempt to characterise features of powder properties
which give uniform spreading (e.g. Nguyen et al., 2017;
Carrozza, 2017; Han et al., 2019). However, the recent
work of Nan et al. (2018) shows that uniform spreading isaffected by transient jamming and arching. Therefore,
spreadability and flowability are two different measuresof powder bulk flow characteristics, albeit inter-related.
The former refers to flow of powders in narrow gaps,
whilst flowability is more a measure of bulk behaviour,
i.e. not having boundary constraint. Nan et al. (2018)
characterised the physical and mechanical properties ofgas-atomised stainless steel powders for DEM simulationof powder spreading. They show that for spreading gaps
typically used in metal AM applications, empty patches/
spaces could be found within the spread particle layer, as
shown in Fig. 1, which adversely affects the uniformity ofthe spread powder layer. They find that the characteristic
particle size, D, for which 90 % particles by number havea diameter less than D, best describes the transient jamming condition. By using Eq. (7) for diagnosing theempty patches, the transient jamming is found to have afrequency in the range 10–100 Hz, as shown in Fig. 2. In
Eq. (7), ΣVp is the total volume of spread particles and thedenominator is the volume swept by the spreader blade. A
gap size, δ, that is less than about 3D causes transient8

Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

jamming, leading to empty patches.

Vp x   y  (   c )

 0.1

(7)

Nan and Ghadiri (2019) identify a critical spreading
speed above which the mass flow rate of powder throughthe gap is independent on the blade spreading speed.
Haeri (2017) identified the optimum blade tip shape to
produce a spread particle layer with volume fraction andsurface roughness comparable to a roller at the actual operation conditions. Geer et al. (2018) and Han et al. (2019)
measured the repose angle and pile bulk density of metal
powders, and then used DEM simulations to calibrate andcharacterise the sliding and rolling friction coefficient andsurface energy of the powder to be used in their simulations of the spreading process. Desai et al. (2019) also developed a DEM calibration method based on angle ofrepose testing and powder rheometry for AM, which was
designed around multiple characterization experiments
applicable to the spreading step. However, particle adhesion and sliding friction influence the repose angle in acomplex way, which is not yet fully understood and hence
calibration methods should be treated with caution. Morework is needed to identify and characterise factors which
influence spreadability of powders in AM and develop
appropriate instrument for its characterisation.

3. Analysis of cohesive powder flow
3.1 Effect of cohesion
The relative cohesivity of a powder is most commonlydescribed by the granular bond number, Bo, the ratio of
the attractive force (adhesive or cohesive) over particle
weight (Castellanos, 2005). Cohesion is commonly due tovan der Waals, liquid bridge and/or electrostatic forces.
There are extensive analyses of bulk cohesion reported in
the literature, but its influence on the dynamic flow behaviour has not been as widely investigated. Recently,
Hare et al. (2015) made large spherical glass beads (1.7–
2.1 mm) cohesive by silanising their surfaces and measured their surface energy by the Drop Test Method (Zafar
et al., 2014). They measured the work (basic flow energy)
required to penetrate the rotating impeller into the cohesive powder bed, and showed that this could also be quantitatively predicted by DEM using the elasto-plastic
adhesive model of Pasha et al. (2014). Bulk cohesion simply lifts up the baseline of powder resistance to bulk motion and the functional dependence on the shear strain
rate has the same trend, as recently analysed by Vivacqua
et al. (2019). They simulated the FT4 test using DEM forboth cohesive (two levels) and cohesionless contacts, using Luding’s contact model (Luding, 2008) and calculated

Fig. 3

DEM prediction of shear stress on the impeller blade of
the FT4 rheometer as a function of impeller blade tip
speed for glass beads for three adhesive indices according to the contact model of Luding (2008). Simulation
data are from Vivacqua et al. (2019): https://doi.
org/10.1016/j.powtec.2018.10.034. Copyright: (2019)
Elsevier B.V. under https://creativecommons.org/
licenses/by/4.0/.

the shear stress on the impeller blade as a function of theimpeller tip speed, as shown in Fig. 3. Clearly, at low
speeds the lines are parallel with the intercept with ordinate being a function of cohesion, and interestingly athigh speeds interparticle cohesion has little influence on
the shear stress acting on the impeller blades.
The above experimental observations are consistent
with the recent numerical analysis of Berger et al. (2015),
who used contact dynamics simulations to investigate cohesive shear flows at a wide range of strain rates. Theirsimulation predictions for the dependence of bulk cohesion, following Coulomb’s law, on the shear strain rate
shows a logarithmic decrease for a wide range of conditions. This effect was attributed to the reduction in the coordination number with increasing shear strain rate,
expressed in terms of inertial number.

3.2 Effect of shear strain rate and medium fluiddragAs the particles become finer, the effect of air drag becomes more pronounced at large shear strain rates. So,
this has to be taken into account in the analysis of fine cohesive powder dynamics. Guo et al. (2011a, 2011b) propose a dimensionless number made of the product of theArchimedes number and the ratio of particle envelop density over the fluid density (i.e. an air sensitivity index) toaccount for the influence of air drag in die filling. They
define a critical value of this group below which the fluiddrag effect is notable. However, this approach is more relevant to lean particle-fluid systems. Nan et al. (2017a,
2017b) used large particles (for faster simulation) with air

9Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

permeation from the base of the FT4 rheometer to provide
notable drag. In this way the effect of air drag and strain
rate could be analysed in reasonable time for glass beadsof 0.3–0.35 mm and polyethylene spheres of 0.5–0.6 mm
for permeating gas velocities ranging from no gas flow tonear fluidisation. The expended work for penetrating therotating impeller into the bed and gas pressure drop could
be both measured and predicted, thus providing further
validation of the simulations. In the absence of air, the expended work increases with the speed of the impeller, as
intuitively expected. An interesting outcome of their analysis is that the expended work scales with the potential
energy of the bed above the impeller height, except for the
top 10 mm, where the entrance effect of the blade is verystrong.
Nan et al. (2017a, 2017b) also analysed the stress andstrain fields in cells in front of the blade of FT4 rheometer.
Their work reveals the sensitivity of powder rheology toboth the strain rate and gas velocity. Their simulation results show that the normalised expended work (with respect to the potential energy of the bed mass above the
mid-position of the impeller blade) for all conditions including permeating air is actually a linear function of theprevailing normalised shear stress, with the latter in turnbeing a function of the strain rate and the prevailing pressure, as the latter changes with height. The most notableoutcome of their analysis is the prediction of the bulk
friction coefficient as a function of the inertial Number.
The effect of permeating air simply modifies the prevailing pressure on the particles, whereby increasing the permeating air speed reduces the pressure and therefore
increases the inertial number. By introducing the permeating air, the powder flow, which is initially in the quasi-­
static state, could transform into the intermediate or even
dynamic state, where the bulk friction coefficient isshown to increase almost linearly with the inertial number.
Bruni et al. (2007, 2005) and Tomasetta et al. (2012)used a mechanically stirred fluid-bed rheometer to study
the rheology of aerated and fluidised powders, which was
followed by Salehi et al. (2017, 2018). To keep the bed inquasi-static state, the rotational speed of the impeller andgas superficial velocity were chosen to have low values.
Based on the method of differential slices (Janssen’s approach) and the Mohr-Coulomb description of the powder
failure, they developed a model to describe the applied
torque. In their model, the effect of air drag on the powderstress was considered by subtracting the pressure gradient
force from the gravity force. The most interesting outcome of their work is that the applied torque of the impeller could be linked to the stress state of the powder.
However, as the powder bed was in quasi-static state,
their analyses did not reveal the response of powder rheology to the variation of the strain rate or flow regimes. In

10conclusion, the dynamic behaviour of fine cohesive powder affected by the fluid medium drag is still a very challenging task to analyse, but based on the above
observations, the trend shown in Fig. 3 for large cohesive
particle should also prevail for fine powders, subject totaking account of fluid drag effects.

3.3 Effect of particle shape
Granular flow is highly affected by particle shape due
to interlocking of the particles. High fidelity simulation ofparticle shape provides a complexity which is ill-affordedby the DEM approach, from the viewpoint of contact mechanics. Therefore, approximating to simple shapes is theorder of the day. There are a good number of approaches
for consideration of shape of particles in DEM simulations: clumped spheres, (Favier et al., 1999), elliptical(Rothenburg and Bathurst, 1991), polygonal (Cundall,1988), bonded assemblies of polygons (Potapov andCampbell, 1996), spherosimplices (Pournin et al., 2005),
super-quadrics (Williams and Pentland, 1992), and digitalisation of particles of arbitrary shapes by voxel packing(Jia and Williams, 2001). For particles with a roundedshape, the clumped sphere approach of Favier et al. (1999)
is commonly used. For example, Hare et al. (2013) used
this approach to show that the stress ratio in a shear box isgreater for rods than for spheres, though decreases as aspect ratio is increased from 1.25–2, remaining constantbeyond this due to alignment of the particles. Pasha et al.
(2016) simulated mixing of corn kernels by this method,showing that an adequate description of the effect of particle shape on particle velocity profile in a mixer could beachieved. Alizadeh et al. (2017) used X-Ray tomogramsof spray dried particles to construct clumped spheres andobtained reliable prediction of the repose angle and segregation of binary mixtures. Nan et al. (2017c) simulated therheological behaviour of rod-like particles in the FT4 rheometer, using the clumped-sphere approach. They reported the flow energy required for the FT4 impeller
penetrating the powder bed is much larger for rod-likeparticles than for spheres. This was attributed to the combined effect of the coordination number and excluded volume. They also proposed an empirical correlation for thebinary mixture of rodlike particles with aspect ratio
AR = lmax /lmin – 1 (i.e. AR = 1.5 and 3.0) and spherical particles (i.e. AR = 0.0). The flow energy was larger for
non-spherical particles than that of spherical particles,
due to interlocking between particles.
For crystalline solid structures with faceted shapes,
sharp edges and corners, it is inappropriate to use
clumped spheres. Recently, Vivacqua et al. (2019) usedbonded Polyhedra to construct faceted shapes in the DEM
simulation software package ROCKY-DEM, ESSS,
Brazil, and followed the same approach as Hare et al.

Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

Table 1

Polyhedra used by Vivacqua et al. (2019) for simulating faceted shapes. https://doi.org/10.1016/j.powtec.
2018.10.034. Copyright: (2019) Elsevier B.V. underhttps://creativecommons.org/licenses/by/4.0/.

Name

Numberof faces

Number of 3D
corners
shape

Deltahedron

16

10

Faced cylinder

12

20

Actual paracetamol shape25

44

Dodecahedron

1220

Truncated polyhedron

14

16(2015) and Nan et al. (2017c) to analyse the effect of faceted particle shape on the powder flow rheology for bothadhesive and non-adhesive particles using the FT4 rheometer. They investigated the effect of the shapes as illustrated in Table 1. The results obtained by Vivacqua et al.
(2019) are shown in Figs. 4 and 5. They agree qualitatively with the trend shown previously by Nan et al.
(2017a); the average shear stress is initially independent of
the strain rate, corresponding to the quasi-static value, but
starts increasing at large strain rates. The notable point isthat faceted shapes present much larger shear stresses,with vertices and edges influencing the resistance, butfollow the same trend as that of the spheres, with the baseline shifted to larger values of shear stress (as with the effect of cohesion discussed above). A similar trend alsoprevails when the interparticle adhesion is increased forthese faceted shapes. In both cases the normalised shear
stress (τ/ρp dp2γ2) obeys the following relationship with theinertial number for spheres (Eq. 8) and all faceted shapes,
shown in Table 1, unified and given by Eq. (9):
 0.481I 1.743
p d p 2 2(8)


 0.918I 1.754
p d p 2 2

(9)Thus, two rheological models with roughly the same
power index, but with different pre-exponential constants,
are obtained for cohesive spheres (Eq. 8) and faceted particles (Eq. 9). These equations point toward the possibilityof obtaining a unified rheological model incorporating theeffect of cohesion, strain rate and shape.
In a subsequent study by Lopez et al. (2019), powder
flow of faceted particles in screw feeders was analysed.
Analysis of the stresses in the screw based on the same

Fig. 4DEM prediction of expended work to penetrate the impeller blade of FT4 rheometer into a bed of faceted particles in the standard test method. Simulation data arefrom Vivacqua et al. (2019): https://doi.org/10.1016/
j.powtec.2018.10.034. Copyright: (2019) Elsevier B.V.
under https://creativecommons.org/licenses/by/4.0/.

Fig. 5

DEM prediction of shear stress on the impeller blade of
FT4 rheometer as a function of impeller blade tip speed
for spherical and deltahedra shape particles. Simulation
data are from Vivacqua et al. (2019): https://doi.org/
10.1016/j.powtec.2018.10.034. Copyright: (2019) Elsevier B.V. under https://creativecommons.org/licenses/
by/4.0/.

approach as Vivacqua et al (2019) showed a linear relationship in a logarithmic plot between the non-dimensional
shear stress and the inertial number for different cohesion
and strain rate levels. When both analyses are plotted in
the same graph, an overlap between the lowest shear ratesof the FT4 and the highest shear rates of the screw feeder
exists. This shows the close relationship between the flow
regimes in both devices for the same shear rates.
The apparent viscosity (η = τ/γ) follows a linear trendwith the inertial number on a log-log plot, with a negative
slope for both spheres and faceted particles indicating a
shear thinning behaviour. The slope obtained for cohesive
particles, however, deviates from the behaviour of11

Mojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

non-­cohesive particles for some strain rates. Lopez et al.
(2019) attributed the trend to transient jamming and clustering of the particles. Recently Macaulay and Rognon(2019) analyse the dynamics of cluster formation undershear deformation and concluded that cluster diffusivity
increases up to two orders of magnitude with increasingcohesion. In their work, they proposed a new relationshipbetween cluster size, its lifetime and cohesion for two dimensional flows under shear induced deformation.
Cohesion level and shape of the particles have a prominent effect on the regime transition. In the case of the latter, transition between the quasi-static regime and theintermediate regime occurs for smaller values of the shear
rate and higher stress values. On the other hand, if cohesion is first introduced and then increased for sphericalparticles, the average level of stress increases for the same
system, while the regime transition between the quasi-­
static and the intermediate flow regimes gradually disappears for increasing cohesion levels. Transition to therapid flow regime occurs for the same shear rate.
In conclusion, particle shape influences the angle offriction in bulk failure of particles and the presence ofvertices and edges in faceted shapes strongly influences
the resistance to shear deformation. Approximating real
crystal shapes by truncated polyhedron shapes provides aclose match in the shear deformation behaviour between
the two shapes, as shown for Paracetamol crystals by
Vivacqua et al. (2019). It appears that cohesion affects theincipient yield but does not influence bulk shear viscosity.

3.4 Powder mixtures
Formulated powder mixtures have long been used inindustry to provide product innovations as well as overcoming poor product performance due to segregation,
powder flow problems, tabletting issues and instabilities.
For example, multi-component detergent powders containing bleach activator and enzymes are prone to segregation. Issues related to tabletting and tablet strengthprevail in the pharmaceutical industry and are commonly
resolved by formulating the powder. Individual powder
components have their own flow characteristics and theirmixing ratio not only affects the product performance but
also the flow behaviour of the powder mixture. When theoverall mixture is too cohesive, the powder mixture flows
poorly and could be very difficult to handle in the required processes (e.g. discharge from silo). On the other
hand, if it is very free flowing, powder segregation could
result in non-uniformity of the product from batch tobatch. To address extreme cohesivity, the surfaces of cohesive active ingredients may be coated with very fine
powder, acting as spacers to improve the overall flow behaviour of the powder (Fulchini et al., 2017).
There have been several studies looking at improved

12

flowability of pharmaceutical active ingredients (APIs)
using dynamic powder flow testers. Qu et al. (2015) reported that coating the surface of cohesive ibuprofen withflow aids (i.e. silica or magnesium stearate) improves theflowability, as measured by the FT4 rheometer aeration
test. In their investigation, the total energy measured by
the rheometer for raw cohesive ibuprofen was considerably higher than for those coated with flow aids, for awide range of air velocities (0 to 30 mm/s).
In recent years, the interest in predicting the flow behaviour of multi-component mixtures has been increased.
In a recent work for example, Capece et al. (2015) developed a methodology for averaging the granular Bond
number for a powder mixture and linking that to the flow
function coefficient as measured by shear cell testing.
Their approach is applicable to the onset of flow. However, most of the reported works in the literature for dynamic powder flow are based on empirical approaches. In
an ongoing research programme entitled Virtual Formulation Laboratory, supported by the Engineering andPhysical Sciences Research Council, UK, (https://gow.
epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/
N025261/1), the dynamic flow behaviour of cohesive powder mixtures is under investigation based on the single
particle properties of the formulation components. Following a similar approach to that of Capece et al. (2015) it
is shown that by averaging the Bond numbers of individual components with different cohesion/ adhesion, sizeand density, the rheological characteristics of the mixture,i.e. bulk friction coefficient and apparent bulk viscosity
can be predicted as a function of the shear strain rate, expressed in the non-dimensional form by the inertial number.

4. Conclusions
For characterisation of cohesive powder flow under dynamic conditions only a handful of devices are available,
namely the FT4 Powder Rheometer, Anton-Paar Powder
Cell and Couette device. They act as a rheometer for powders, measuring the rheological response of powder undervarying shear strain rates. Experimental classification of
the flow regime has so far been established with the
Couette device, but wall slip and the presence of secondary flows pose a challenge to its use, in addition to lack ofcommercial availability. For rheometers the underlying
relationship between the torque and bulk rheologicalproperties, such as bulk friction and apparent shear viscosity, is imperative and has yet to be established.
Other dynamic testers include the rotating drum andball indentation method. The rotating drum is applicableto free surface flows and does not have the versatility tocontrol applied stresses; furthermore, it is difficult toMojtaba Ghadiri et al. / KONA Powder and Particle Journal No. 37 (2020) 3–18

interpret a relevant cohesion parameter from such tests.
Ball indentation is a relatively new test method which allows stress to be controlled and a range of strain rates tobe applied by manipulating indenter properties. However,its operating range is narrow, due to the limited acceptable indentation depth.
An increasingly important sector dealing with powders
operated at high strain rates is additive manufacturing (3Dprinting). There is currently great effort being put into relating the spreading performance in additive manufacturing to various flow testers. However, in contrast to flow
resistance in shear flows, additive manufacturing processes utilise a very thin powder layer in close proximity
to wall boundaries. As such the flow behaviour is strongly
influenced by transient jamming/arching. A different approach is needed to describe the rheology of spreading ofthin powder layers for the increased demand of powder
spreading in additive manufacturing.
The prediction of bulk rheological characteristics offine cohesive powders is still a grand challenge. Such
powders are in dynamic cluster forms, the size and packing density of which depends on the stress history that thepowder has experienced. The current research effort is
aimed at addressing the influence of particle properties onbulk rheological behaviour in a systematic way, but there
is still a long way to go to develop fully predictive tools.

Acknowledgments
The support of the following research programmes isgratefully acknowledged: (i) Virtual Formulation Laboratory Grant of the EPSRC Future Formulation Programme(EP/N025261/1); (ii) Advanced Manufacturing Supply
Chains Initiative (AMSCI) and the Medicines Manufacturing Industry Partnership (MMIP), UK, through thefunding of the ‘Advanced Digital Design of Pharmaceutical Therapeutics’ (Grant No. 14060); (iii) the EPSRC Programme Grant: Friction: The Tribology Enigma (EP/R001766/1) ; (iv) Project ID 1502-607 funded through
ANR (the French National Research Agency) under the“Investissements d’avenir” programme with the reference
ANR-10-LABX- 001-01 Labex Agro and coordinated by
Agropolis Fondation, France, under the frame of I-SITE
MUSE (ANR-16-IDEX-0006).

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Authors’ Short Biographies
Mojtaba Ghadiri
Professor of Chemical Engineering at the University of Leeds, UK, with research activities on Particle Technology, and focusing on the link between bulk particulate solids
behaviour and single particle properties with the aid of simulations by combined DEM
and CFD. Application areas of interest are cohesive powder flow and fluidisation, size reduction and enlargement, environmental effects and electrical phenomena in particulate
systems. For details of the current projects, collaborators and publications please see thefollowing web pages: Group’s web page: http://ghadiri-group.leeds.ac.uk/.
Mehrdad Pasha
Mehrdad Pasha is a Research Fellow of Chemical Engineering at the University ofLeeds. His research focuses primarily on particle characterisation, powder flow, segregation/mixing, and coating, using state of the art experimental techniques and computational approaches (e.g. Discrete Element Method). Mehrdad has won several prizes
including: Award of Excellence in Modelling and Simulation at World Congress on Particle Technology, Brian Scarlet Award at Annual Meeting of International Fine Particle
Research Institute. His current research focuses on prediction of flow behaviour of formulated product at high strain rate conditions by consideration of single particle properties of individual components.

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Authors’ Short Biographies
Wenguang Nan
Wenguang Nan holds a Lecturer position at Nanjing Tech University, China. He received his PhD in 2017 from Xi’an Jiatong University, China. During his PhD studies, hereceived a funding from China Scholarship Council (CSC) to spend a year in Leeds
working with Professor Ghadiri as a visiting research student. He was also a visiting researcher in Professor Ghadiri’s group in 2018. His current research focuses on the powder spreading in additive manufacturing, and the rheology and constitutive law ofparticle flow.

Colin Hare
Colin Hare is a Lecturer of Chemical Engineering at the University of Surrey, UK.
His expertise are in powder flow, mixing/segregation, coating, particle breakage and the
Discrete Element Method. His research is primarily funded by industry and addresses
secondary processing of powder products, considering the role of particle properties andprocess conditions on product performance.

Vincenzino Vivacqua
I graduated in Chemical Engineering from Università della Calabria (Italy), where I
also completed my PhD in 2011. I have carried out postdoctoral research work at several
international institutions, namely the University of Leeds (UoL), Nottingham (UoN),
British Columbia (UBC), Università della Calabria (UNICAL) and Qatar University(QU). I am currently Particle Engineering Senior Scientist at Johnson Matthey, Billingham, UK. My research interests are related to several areas of particle technology andmultiphase flow, including powder flow, powder compaction, DEM modelling, fluidization and electrocoalescence.

Umair Zafar
Principal Scientist at Novartis, Basel, Switzerland and visiting research scholar at University of Leeds, UK. PhD in Particle Science & Engineering and having experience
across different industries and processes related with powder technology. Area of expertise are material characterisation (i.e. chemical, physical, surface, mechanical and analytical), establishing a relationship between microscopic and macroscopic properties andphenomena of particulate system, design, understanding particle-process-environment
interactions and development of novel techniques to mimic lab scale experiments to industrial conditions.

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Authors’ Short Biographies

Saeid Nezamabadi
Associate Professor in the Laboratory of Mechanic and Civil Engineering (LMGC) at
the University of Montpellier, France, with research activities on powders and granularmaterials, and focusing on the link between the rheology of granular media and single
particle properties with the aid of numerical simulations by combined continuum anddiscrete approaches. Application areas of interest are specially compressive and shear
behaviours of soft particle materials. For details of research works, please see my personal page (http://www.lmgc.univ-montp2.fr/perso/saeid-nezamabadi/) and our researchteam in LMGC (http://www.lmgc.univ-montp2.fr/perso/pmmd/).

Alejandro Lopez
Alejandro Lopez is a Lecturer in Applied Mechanics at the University of Deusto (Bilbao, Spain). His research focuses on CFD and DEM modelling of multiphase flows, erosion processes, cohesive powder flow and manufacturing processes, He worked as aManager in the service industry in Spain before deciding to pursue an academic career.
He received his PhD in Mechanical and Aerospace Engineering from the University ofStrathclyde (Glasgow, UK), specifically studying erosion processes with CFD. After his
PhD he joined Ghadiri Research Group (http://ghadiri-group.leeds.ac.uk/) before being
recruited for his current position.

Massih Pasha
Massih Pasha is a Particle Technology Consultant at The Chemours Company, providing technical consultation to the industrial and research facilities of Chemours and its
key customers in the area of particle science and technology. He received a PhD degreefrom the University of Leeds working on ‘Numerical Modeling of Cohesive Powder
Flow’. Massih is a Visiting Research Fellow at the University of Leeds and currently acts
as Vice Chairman of the Board of International Fine Particle Research Institute (IFPRI).
His area of expertise includes dry solids handling and processes such as powder flow,
mixing, size reduction, and agglomeration.

Sadegh Nadimi
Dr Sadegh Nadimi is a Lecturer (Assist. Prof) in the School of Engineering at Newcastle University and a Visiting Researcher at the University of Leeds. He holds a PhD in
Geotechnical Engineering from City, University of London and an MSc in GeotechnicalEngineering from Newcastle University. Following the award of his doctorate, Sadeghmoved to the University of Leeds as Post-doctoral Research Fellow to focus on tribologyof particulate solids, working with Prof Mojtaba Ghadiri and Prof Anne Neville. Sadegh
is committed to advancing fundamental engineering research and teaching.

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KONA Powder and Particle Journal No. 37 (2020) 19–27/Doi:10.14356/kona.2020001

Review Paper

Present Status of Air Filters and Explorationof Their New Applications †Myong-Hwa Lee 1, Hyun-Jin Choi 2, Mikio Kumita 3 and Yoshio Otani 3*
1

Kangwon National University, Korea
Korea Environment Institute, Korea
3
College of Science and Engineering, Kanazawa University, Japan
2

Abstract
There is an increasing demand of air filters with a high collection performance, i.e., high collection efficiency andlow pressure drop, for the application to indoor air cleaning. Air filters consisting of nanofibers have attracted
great interests since they may have a low pressure drop because of slip flow effect and high collection efficiency
due to enhanced interception effect. Although various nanofiber filters are available on the market, their collection
performance is not as high as expected by the conventional filtration theory because non-uniform packing offibers plays a significant role in the nanofiber filtration. In the present review, the present status of development ofhigh performance air filters are reviewed. We may use air filters not only for the removal of particles but also forthe classification of particles by selecting an appropriate filter by operating it under an optimized filtration
condition for classification. Other topics introduced in the present review are the applications of filters and metal
screen for aerosol classification and the use of centrifugal force for enhancing collection efficiency without
increasing the pressure drop.
Keywords: air filtration, quality factor, nanofiber filter, aerosol classification, measurement

1. Introduction
Air filtration is the simplest and the most economical
way of obtaining clean air. The first industrial applicationof air filter is dated back to AD 50 when woven cloths
were used to filter breathing air in a mine. Air filtration
theory for initial performance was established by Fuchs etal. and introduced in the treatise Fundamentals of Aerosol
Science (Kirsch and Stechkina, 1978). Many problems
were posed in this book but most of them still remain unresolved. Current research topics on air filtration may besummarized into the following three subjects:(1) Development of high performance air filters—highcollection efficiency and low pressure drop
(2) Change in collection performance with dust load—
prediction of filter life
(3) Collection of nanoparticles—thermal rebound of
sub-10 nm particles

†
1
2
3

*

Received 29 May 2018; Accepted 23 July 2018
J-STAGE Advance published online 30 September 2018
1 Kangwondaehak-gil, Chuncheon-si, Gangwon-do 24341, Korea
9F, Bldg. B, 370 Sicheong-daero, Sejong, 30147, Korea
Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan
Corresponding author: Yoshio Otani;
E-mail: otani@se.kanazawa-u.ac.jp
TEL: +81-76-234-4813 FAX: +81-76-264-6239

As for the first topic, nanofiber filters have attracted
great attention because of the development of various
manufacturing techniques of nanofibers (Choi et al., 2014;
Choi et al., 2017; Xia et al., 2018). First part of this review
will focus on the first topic. The second topic was recently
reviewed by Kanaoka (2018), to which the readers of thisreview may refer. The third topic was first introduced by
Wang and Kasper (1991) but the experimental verificationand the quantification of thermal rebound effect on thefiltration efficiency strongly rely on the development of ageneration method of well-defined nanoparticles and ameasuring method of sub-10 nm particles. The review on
the third topic has to be done after the development ofthese techniques.
We may use air filters not only for the removal of particles but also for classification of particles by selecting anappropriate filter media by operating it under an optimized filtration condition for classification. Other topics
introduced in the present review are the applications offilters and metal screen for aerosol classification and theuse of centrifugal force for enhancing collection efficiency without increasing the pressure drop.

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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2. Filtration theory of virgin air filtersby the following equations:

The mechanical collection mechanisms of air filters areηTf  ηD  ηR  ηDR(1)
Brownian diffusion, inertia, interception, and gravity.
The relative contribution of each collection mechanism to1 3ηD 2.7 Pe 2 3 1  0.39 K f  Pe1 3Kn(2)
the particle collection depends upon the physical properties of filter (fiber diameter, packing density, orientation
1
1
of fibers and internal structure of filter), and particle propηR
2 1  R ln 1  R  1  R 
erties (particle diameter, particle density, and the shape)
2K f
1 R
as well as the filtration conditions (filtration velocity,2  R R
pressure, and temperature) (Hinds, 1999; Stern et al., 2.86Kn(3)
1 R
1960; Wang et al., 2008). Fig. 1 shows the single fiber collection efficiency due to individual collection mechanisms
1 2
as a function of particle size. As seen in Fig. 1, the collec(4)ηDR  1.24 K f  Pe 1 2 R 2 3
tion efficiency curves due to individual collection mechanisms shift upward, i.e., an air filter becomes a higher
where ηTf is the single fiber collection efficiency of FMF,
performance filter with decreasing the fiber diameter.
ηD and ηR are the diffusion and interception single fiber
H EPA f ilter s composed of subm icron f iber scollection efficiencies, ηDR is the interaction term for dif(E > 99.97 % for 0.3 μm particles) remove particles
fusion and interception. Pe is the Peclet number defined
mainly by Brownian diffusion and interception, and theby Eq. (5), R is the interception parameter given by Eq. (6),collection efficiency is affected by the internal structure
Kn is the Knudsen number defined by Eq. (7), and Kf isof filter, such as the variance of fiber diameter, the inhothe hydrodynamic factor with the correction for slip flow
mogeneity factor, and the packing density. Kirsch andgiven by Eq. (8):Stechkina (1978) proposed the prediction method of
ud
HEPA filter based on the single fiber efficiency of Fan
Pe  f(5)
D
Model Filter (FMF) due to Brownian diffusion and interception. FMF is the filter in which monodispersed fibersd
are randomly packed and all of the fibers are placed perR p(6)dfpendicular to the air flow. Since the inhomogeneity factor
is defined as the ratio of pressure drop of FMF to that of a2λreal filter at Kn = 0, non-uniformity of fiber diameter, oriKn (7)df
entation of fibers to airflow and uneven packing of fibers
determine the inhomogeneity factor. Moreover, the slip
flow effect on fiber surfaces becomes significant as theKf 0.5ln α  0.52  0.64α  1.43 1  α Kn(8)fiber size decreases. The single fiber collection efficiency
where, u is the filtration velocity (here, we define it as theof FMF accounting for the influence of slip flow is given
interstitial velocity), df the fiber diameter, D the diffusivity of particles, dp the particle diameter, λ the mean freepath of air molecules, α the packing density of filter.
The pressure drop of an air filter is given by the following equation based on Darcy’s law.









p Fμu 0l(9)where F is the dimensionless drag, μ the viscosity, u0 thesuperficial velocity and l the fiber length in a unit filterarea: πd 2 l  αL /  f 
 4 

(10)

The drag coefficient, CD, is related to F by the following equation:
Fig. 120

Effect of fiber diameter on single fiber collection efficiency.


C Df

2F

Re

8π
K f Re(11)

Myong-Hwa Lee et al. / KONA Powder and Particle Journal No. 37 (2020) 19–27

where Re is the Reynolds number and Kf is the hydrodynamic factor given by Eq. (8).
For the prediction of collection efficiency of real fiber,
Kirsch and Stechkina (1978) introduced the variance offiber diameter, σ, and the inhomogeneity factor, δ. σ and δ
are given by the following equations when the fiber size
distribution follows a lognormal distribution.
σd f2  d f22
exp ln σ g   1
2
df

(12)



(13)

d
d
d fg exp 0.5 ln σ g 
f
f



2

 Δp f δ  Δp r  Kn0(14)where dfg is the geometric mean diameter of fibers, σg thegeometric standard deviation, and the superscripts f and rdenote respectively “FMF” and “real”.
The filter efficiency, E, is related to the single fiber collection efficiency of FMF by the following Eq. (15):E  1 P 4α
L ηTf 1  exp  π (1  α)(1  σ ) d f δ (15)

The filter quality factor, q, which is the measure of filter performance is defined by the following equation.
(η f / C D f )q   lnP / p 
( ρf / 2)u 2(16)

where ρf is the density of air. Fig. 2 shows the filter quality factor, which is calculated by using Eqs. (1)–(4) and(11) at u = 5 cm/s and α = 0.06. As seen in this figure, q
increases rapidly as the fiber diameter becomes smaller
than 0.1 μm, and reaches over unity at df = 10 nm. Fig. 2
is the reason that everybody tries to make fibrous filterswith nanofibers.

Fig. 2Filter quality factor as a function of fiber diameter.

3. Nanofiber filters
Many researchers made efforts to fabricate air filterswith low air resistance and high collection efficiency(Hung et al., 2011; Sambaer et al., 2011; Mei et al., 2012;
Uppal et al., 2013; Cho et al., 2013; Hassan et al., 2013;
Choi et al., 2014; Balgis et al., 2015; Wang et al., 2016;
Zhang et al., 2016; Zhao et al., 2017; Choi et al., 2017).
Most studies to fabricate nanofibers used an electrospinning process, which has a limitation of a low production
rate. Only a couple of works used a melt blowing process,which fabricated micro- or nanofibers by blowing a polymer melt through a nozzle at a high speed (Uppal et al.,2013; Hassan et al., 2013).
Low pressure drop can be achieved by inducing slip
f low around nanofibers. Several studies tried to prepare an air filter with low air resistance (Barhate andRamakrishna, 2007; Hosseini and Tafreshi, 2010; Hunget al., 2011; Shou et al., 2014; Balgis et al., 2015; Bao etal., 2016; Zhao et al., 2016). Hung et al. (2011) fabricatedNylon 6 nanofibers ranging from 94 to 220 nm in diameter, and Balgis et al. (2015) made polyacrylonitrile nanofibers with diameter of 36.5–300 nm. However, they did
not observe the reduction in pressure drop by slip effect.
Zhao et al. (2016) claimed that those studies did not consider the optimal range of fiber diameter and the effective
pore size. They fabricated PAN fibrous membranes withdiameters between 53 and 168 nm by electrospinning andstudied the effect of neighboring fibers on the pressure
drop from both experiments and numerical simulations.
They reported that the slip flow effect was found only under the very limited conditions, i.e., the fiber diameter between 60 to 100 nm and the effective pore size larger than
3.5 μm (Fig. 3). As shown in Fig. 3 the pressure drop at
the filtration velocity of 5.3 cm/s is as small as 10 Pa, andthe increase in pressure drop due to the decrease in fiber
diameter from 71 to 53 nm is only 3 Pa, which is not significant and they obtained these data only at the filtration
velocity of 5.3 cm/s and the particle size for the measurement of filtration efficiency was not specified. Moreover,the collection efficiency is as low as 45 % at which thecollection efficiency was determined mostly by the channeling flow through the pores and Brownian diffusion is
not the dominant collection mechanism. In order to provethe effect of slip flow, the authors should have used fibrous membranes with different thicknesses and measured the collection efficiency and pressure drop at
different filtration velocities and different particles sizes.
Consequently, it seems the verification of slip flow effecton the filter collection performance still remains unresolved.
High collection efficiency for submicrometer particles
can be attained by enhancing Brownian diffusion and interception, i.e., at a smaller Peclet number, Pe, and a21

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Fig. 3Fig. 4

Changes in pressure drop by fiber diameter, cited from Ref. (Zhao et al., 2016). Copyright: (2016) The
Author(s).
(a) Fiber diameter, (b) Pore size.

Image of sub-micrometer particles captured on nanofibers.

larger interception parameter, R, both of which resultsfrom a finer fiber (Podgorski et al., 2006; Wang et al.,2007; Yun et al., 2010; Wang et al., 2013; Choi et al., 2014;
Bao et al., 2016). Choi et al. (2014) showed that submicrometer particles were effectively collected in a poly­
urethane nanofiber filter due to increased interception (inFig. 4, particles ranging from 20 to 300 nm were evenly
captured in a filter with the diameter of around 180 nm).

4. Application of air filters to aerosol
classification
4.1 Inertial filter
The collection efficiency curve of an air filter is always
concave against the axis of particle size as shown in
Fig. 1, and the curves shift by changing the filter properties (fiber size, packing density, etc.) and the filtration
conditions (filtration velocity, pressure, temperature, etc.).
One extreme case is to use very high filtration velocity at

22

Fig. 5

Separation curves of Nanosampler with inertial filter
stage for separating 0.1 μm (Kanomax, Model 3182).

which only inertia is the dominant collection mechanism
and the collection of particles by diffusion is minimized.
This is the case of inertial filter (Otani, et al., 2007). The
measure of inertia is the Stokes number defined by:
Stk 

Cc ρpd p2u
9 μd f(17)

The representative length of a solid plate impactor isthe diameter of the nozzle in the order of tens of micrometers, but for the inertial filter, it is the fiber diameter sothat we can make Stk large enough to capture small particles at a relatively low air velocity through a nozzle.
Fig. 5 shows the separation curves of a cascade impactor(Nanosampler, Kanomax, Model 3182) in which an inertial impactor stage was added downstream of the solid
plate impactors. Since the inertial filter stage can separate
submicron particles at the ambient pressure, we may havean additional fraction of particles in submicron size.

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Fig. 6

Shapes of metal screens.
(a) df = 0.6 μm, do = 1.2 μm, (b) do = 2.5 μm, df = 1.2 μm.

4.2 Sieving of aerosol particles by metal screen
We found out that the bounce-off of particles on thesurface of fibers becomes significant at a high velocity
even for submicron particles, which degrades the classification performance of inertial filter. Therefore, the cutoff
size of particles upstream of inertial filter stage should be
carefully designed in order to minimize the bounce-off ofparticles at the inertial filter stage. Such bounce-off phenomena are more significant when metal screen was used
as a filter media. Recently, metal screens with uniform
micrometer openings Metal Mesh Device (MMD, Murata
Manufacturing Co., Ltd., see Fig. 6) were manufactured
by a precision plating technique, and applied to the determination of PM2.5 (Seto et al. 2014).
Although they obtained a good correlation between themass of captured particles on the metal screen with
2.5 μm opening and that of PM2.5, the mass of particles
collected on 2.5 μm opening metal screen does not always
reflect the mass of PM2.5 because PM2.5 are composed
mostly of submicron particles. They obtained a good correlation probably because the particle size distributions
were similar even when PM2.5 concentrations were different. By combining these two previous works, we came up
with an idea of “sieving of aerosol particles with metal
screen.” If the bounce-off of particles is inevitable, we
may enhance the particle bounce-off to achieve “no adhesion of particles.” If we could achieve “no adhesion ofparticles” onto metal screen, we may “sieve” aerosol particles by using uniform-opening metal screen solely by
the geometrical sizes of particles.
Fig. 7 shows the collection efficiency of PSL particles
through the metal screen with 2.5 μm opening at various
filtration velocities (Kawara et al., 2016). The stepwise
solid line in this figure is the ideal separation curve if
there would be no particle adhesion on the metal screen.
The collection efficiencies of 2.5 μm and 3.3 μm PSL particles are equal to unity at any filtration velocity, indicating that the metal screen can completely trap PSL
particles larger than the mesh opening. At the filtration

Fig. 7

Separation curve of metal screen.

velocity of 0.6 m/s, as the particle size decreases, the collection efficiency of particles smaller than the mesh opening decreases discontinuously at the particle size equal tothe mesh opening. At the filtration velocities of 3.0 and
10.6 m/s, the discontinuous drop in the collection efficiency at the particle size of mesh opening is more pronounced and the separation curve is very close to the ideal
one.
Fig. 8 shows the collection efficiencies of PSL particles
through the metal screens with 1.2, 1.8, 2.5, and 4.2 μm
openings at the filtration velocity of 3.0 m/s. We can see
from these figures that the collection efficiencies of particles larger than the mesh opening are equal to unity, indicating that we can completely trap particles larger thanthe mesh opening and that the cutoff size can be varied bychanging the mesh opening.
Although the collection efficiencies of PSL particles
smaller than the mesh opening are not equal to zero, i.e.,
we cannot completely suppress the adhesion of particles
onto the metal screen, we can roughly “sieve” aerosol
particles.

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Fig. 8Separation curve of metal screens with various openings at filtration velocity of 3 m/s.

4.3 Centrifugal filter
One of the big drawbacks of air filter is such that wecannot change the collection efficiency once an air filter isinstalled when the filtration velocity is constant. Can we
make the collection efficiency adjustable depending on
the air quality, i.e., particle size distribution and concentration?
Nakajima et al. (2015) proposed a new type of filter
named as “centrifugal filter” which collects aerosol particles by centrifugal force together with the conventional
mechanical collection mechanisms so that the centrifugal
filter can adjust the collection efficiency by changing therotation speed (Fig. 9).
The attempts to combine centrifugal force and mechanical collection mechanisms were made previously andthere are commercially available rotary filters (Sinto­
kogio, Ltd. 2015). The biggest difference between thecentrifugal filter proposed by the authors and the conventional rotary filters is such that in the centrifugal filter thecentrifugal force exerts particles in the direction perpendicular to the airflow. In the conventional rotary filters,
the centrifugal force exerts parallel to the airflow and thetargeted particle size of collection is mostly several tensof micrometers. By letting the centrifugal force act perpendicular to the airflow, the centrifugal filter possesses
many advantages over the conventional ones, i.e., depth

24Fig. 9

Two types of realizing centrifugal filter.

filtration with a long residence time of particles in the filter, and no shedding of particles into the filtered air.
Fig. 10 shows the collection efficiencies of centrifugal
filter against the particle diameter at the fixed filtration
velocity, u = 2.5 cm/s. SUS fiber filter with diameter,
df = 50 μm, was used as a filter media. As shown in theMyong-Hwa Lee et al. / KONA Powder and Particle Journal No. 37 (2020) 19–27

drop is determined mostly by the relative motion between
the air and fibers in the axial direction of flow. Consequently, the rotation of filter contributes mostly to the enhancement in collection efficiency while keeping thepressure drop as small as that of static filter.
Since the collection efficiency of the centrifugal filter isadjustable just by changing the rotation speed, it was successfully applied to classify different sizes of particles byscanning the rotation speed followed by the detection offiltered aerosol by a photometer in order to measure thesize distributions (Tanaka et al., 2017). The measurable
size range overlaps the range of optical particle counters
and the centrifugal filter can give the size distribution
based on the aerodynamic size.
Fig. 10 Collection efficiency of centrifugal filter.

5. Conclusion

Fig. 11 Pressure drop of centrifugal filter at the filtration velocity of 2.5 cm/s.

figure, the collection efficiency without rotation (bluesquares) is smaller than 10 % at the MPPS (most penetrating particle size) which is about 1 μm. The collection efficiency of particles larger than 0.5 μm is significantly
improved by rotating the filter. At the maximum rotation
speed of 3,000 rpm, the collection efficiency of 1 μm PSL
particles increases to 90 %.
Fig. 11 shows the pressure drops of centrifugal filter
consisting of fibers with different diameters as a functionof rotation speed at a fixed filtration velocity of 5.0 cm/s.
The fiber diameter is larger than 10 μm so that there is no
additional pressure drop to that of filter holder and you
can find that the increase in pressure drop due to filter rotation is not significant. The small increase in pressure
drop by rotating the filter is explained as follows. Whenthe filter rotates, the air embedded in the filter also rotateswith the fiber media. Therefore, no relative motion in thecircumferential direction of filter rotation between the airand fibers would be added, and therefore the pressure

Air filters have been used to obtain clean air but they
may have other applications of particle classification bytuning the collection efficiency curve by adjusting filter
properties and filtration conditions. The inertial filter is
one of the examples in which particles are collected solely
by inertia so as to make the filter as the inertial classifier.
At a very high filtration velocity, we may use metal screen
as a sieve for aerosol by suppressing the adhesion of particles. The centrifugal filter is another example to makeair filter as an aerosol classifier with variable cutoff sizes.
Air filters have varieties of applications, more than we
can think of, because any porous media can be used as afilter medium and we may use it under extreme filtration
conditions and combine it with various external force
fields. With the development of various techniques for
manufacturing fibers and porous media, now is the timeto think about new applications of air filters.

Acknowledgments
The authors’ works introduced in this review were partially supported by Eco-Innovation Project (Project number :2016-0001-0003) through the Ministry of Environment,
Republic of Korea.

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Authors’ Short Biographies
Myong-Hwa Lee
Dr. Myong-Hwa Lee is an Assistant Professor in the Department of Environmental
Engineering at Kangwon National University. He obtained his Ph.D. degree from
Kanazawa University and has worked more than 12 years in Korea Institute of Industrial
Technology on the development of air filter media and air pollution control devices.

Hung-Jin Choi
Dr. Hyun-Jin Choi is a Research Fellow in the Division of Public Infrastructure Assessment at Korea Environment Institute. He obtained his Ph.D. degree in Korea University and has worked for more than 10 years on the development of air filter media and air
pollution control technology. At present, he is working on the environmental impact assessment and the policy for air pollution control.

Mikio Kumita
Dr. Mikio Kumita is an Associate Professor in the Institute of Science and Engineering at Kanazawa University. He obtained his Doctor of Engineering degree in Chemical Engineering from Nagoya University. His research interests include the developmentof porous materials, sorption cooling and separation technologies.

Yoshio Otani
Dr. Yoshio Otani is the Vice President of Kanazawa University for international Affairs.
He obtained his Ph.D. degree from Syracuse University, USA and has worked for morethan 35 years in the field of air filtration and air pollution control. At present, he is thepresident of Japan Association for Aerosol Science and Technology.

27

KONA Powder and Particle Journal No. 37 (2020) 28–41/Doi:10.14356/kona.2020002

Review Paper

Continuous Flow Synthesis of Nanoparticles
Using Supercritical Water: Process Design,
Surface Control, and Nanohybrid Materials †Akira Yoko 1, Gimyeong Seong 2, Takaaki Tomai 3 and Tadafumi Adschiri 1,2,3*
1

WPI – Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, JapanNew Industry Creation Hatchery Center (NICHe), Tohoku University, Japan
3
Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, Japan
2

Abstract
A continuous flow reaction process in which a metal salt solution is rapidly mixed with high-temperature water
was employed to achieve rapid heating up to supercritical conditions. A quarter of a century has passed since thesupercritical hydrothermal method was first proposed. This paper introduces recent advances in science andtechnology related to the supercritical process. Process design, kinetics, reaction atmosphere (redox) control,
morphology control, organic modification of particles, nanocatalysts, and organic-inorganic hybrid materials arereviewed for promising applications of the supercritical process.
Keywords: supercritical hydrothermal synthesis, nanoparticle, surface organic modification, organic-inorganic
hybrid, nanocatalysts, nanofluids

1. Introduction
Understanding structural formation phenomena is essential for the fabrication and control of nanomaterials. The
classification of these phenomena is possible with the degree of non-equilibrium achieved during processes such as
supercooling and supersaturation (Adschiri T. and Yoko
A., 2018). The process of homogeneous nucleation, which
occurs when the degree of non-equilibrium is sufficiently
high, is suitable for the fabrication of nanoparticles withsmall particle size and narrow size distribution. However,
it is difficult to achieve a high degree of non-equilibrium.
In the supercritical hydrothermal method (Adschiri T.
et al., 1992), high supersaturation can be achieved by
rapid heating of a metal salt solution at room temperature
up to supercritical conditions due to the low solubilities ofions in supercritical water. The solubilities of polar materials are low because of the low dielectric constant of supercritical water. In other words, in supercritical waterionic materials are unstable while non-polar materials arestable. Rapid heating can be achieved by rapid mixing of
†
1
2
3

*

28

Received 8 June 2018; Accepted 26 June 2018
J-STAGE Advance published online 17 November 2018
2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
6-6-10 Aza-Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan
2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan
Corresponding author: Tadafumi Adschiri;
E-mail: tadafumi.ajiri.b1@tohoku.ac.jp
TEL/FAX: +81-22-217-6321

fluids using continuous flow reactors, and the low kinetic
viscosity of supercritical water accelerates mixing during
fluid flow. Thus, a low dielectric constant and low kinetic
viscosity are the key factors for supercritical hydrothermal synthesis, which cannot be obtained by conventional
low-temperature batch-type hydrothermal reactions.
The properties of water change continuously withchanges in temperature because first-order phase transitions do not occur beyond the critical point (374 °C,
22.1 MPa). Fig. 1 shows the temperature dependence ofwater properties, such as density, viscosity, and dielectric
constant. As can be seen in Fig. 1(a), the density of supercritical water is lower than that of liquid water but is muchhigher than that of steam (Wagner W. and Pruß A., 2002).
On the other hand, the viscosity of supercritical water is as
low as that of steam (Kestin J. et al., 1984). These physicalproperties of supercritical water are the origin of the characteristic transport properties, such as low kinetic viscosity. Fig. 1(b) shows the temperature dependence of thedielectric constant, which determines the character of solvents, and a significant change is observed in the supercritical region (Uematsu M. and Frank E.U., 1980). Fig. 1(c)shows the dielectric term in solvation energy from theOnsager model (Onsager L., 1936), which ranges between
0 and 0.5. The change in the dielectric constant around thecritical point, shown in Fig. 1(c), is an important factor
affecting the solubility and reaction rate of ionic reactions.
The solvent effects are significantly tunable by changing
the pressure around the critical temperature region, even

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Akira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

Fig. 2Phase behavior of organic compounds and high-­temperature compressed water (Yiling T. et al., 1991;
Schneide G.M., 1972).

M NO 3 x  xH 2O M OH x  xHNO 3

M OH x MO x 
2Fig. 1(a) Temperature dependence of the density and viscosity of water at 30 MPa (Wagner W. and Pruß A., 2002).
(b) Temperature dependence of the dielectric constantof water at 30 MPa (Uematsu M. and Frank E.U.,
1980). (c) Dielectric term in solvation energy in the
Onsanger model at various pressures.

under isothermal conditions.
In some cases of nucleation and growth (e.g., solidification of liquid), just aggregation of monomer atoms or
molecules occurs during nucleation and growth without
any chemical reaction. However, in the case of hydrothermal synthesis, hydrothermal reactions occur through thenucleation and growth stages. Hydrothermal reactions,which include hydrolysis and dehydration of metal ions,are represented by the following equations:

x
H 2O
2

(Eq. 1)(Eq. 2)

The reaction equilibria of these reactions shift to formhydroxides and oxides as the temperature increases. Particularly under supercritical conditions, a lower dielectric
constant and solubility of ionic species lead to hydrothermal reactions with high reaction rates. One should notethat water acts as a reactant and a solvent.
The phase behavior in supercritical water is anotherimportant aspect. As already explained, ionic materials
are destabilized in supercritical water and the solubilities
of inorganic materials are extremely low. Methods for estimating the solubility of ionic materials have been presented in previous studies (Helgeson H.C. et al., 1981;
Tanger J.C. and Helgeson H.C., 1988; Oelkers E.H. andHelgeson H.C., 1993; Sue K. et al., 2002; Lencka M.M.
and Riman R.E., 1993). In contrast to ionic materials,
nonpolar organic materials, which lead to phase separation in low-temperature water, are miscible with supercritical water. This phase behavior is important for in situ
organic surface modification. Fig. 2 shows the phase behavior of various organic compounds in water. A homogeneous phase can be formed at high temperature undercompression (Yiling T. et al., 1991; Schneide G.M., 1972).
Gaseous materials can also form a homogeneous phasewith high-temperature compressed water (Franck E.,
1981), as shown in Fig. 3. Due to the phase behavior, it ispossible to control the oxidative and reductive nature of
the reaction atmosphere.
Various studies on the supercritical hydrothermal synthesis method have been conducted in recent decades following the first proposal of the methodology (Adschiri T.
et al., 1992). Recent scientific and technological advancesof the supercritical process are reviewed in this paper.

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Akira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

Fig. 3Fig. 4

Continuous flow reactor setup for supercritical hydrothermal synthesis (Adschiri T. et al., 1992).

Fig. 5

Particle size of the obtained CeO2 nanoparticles withdifferent temperature and different Re. Reprinted withpermission from Ref. (Aoki N. et al., 2016). Copyright:(2016) Elsevier.

Phase behavior of gases and high-temperature compressed water (Franck E., 1981).

2. Process design and kinetics
One of the characteristic aspects of supercritical hydrothermal synthesis is the rapid reaction realized by the useof a continuous flow reactor, as shown in Fig. 4. In essence, the low kinetic viscosity of supercritical water is apositive factor to accelerate fluid mixing. Mixing of supercritical water and low-temperature water has long been
an important topic in supercritical hydrothermal synthesis
because the mixing states affect the quality of the synthesized nanoparticles (e.g., particle size and its distribution).
The rate of mixing should be high compared to the reaction rate. Various studies regarding the mixing state havebeen conducted, revealing that sufficient mixing can be
determined using the Reynolds number (Re) as an index
for the mixing state (Kawasaki S. et al., 2010a, 2010b,
2015; Sue K. et al., 2010, 2011). For example, Kawasaki etal. reported that Re > 4 × 104 was required based on results from experiments on various materials (Kawasaki S.
et al., 2010a, 2010b). The required mixing state differs depending on the materials because of the difference in thereaction rate for each material. The Damkӧhler number(Da), defined as the ratio of reaction rate to mass transferrate, was applied to determine the required mixing conditions for each target material (Aoki N. et al., 2016). Da
can be expressed as the following equation for first-order
reactions, where k denotes the reaction rate constant, ddenotes the diameter of the mixer, and u denotes the flow
velocity:

Da 

kd
.
u

(Eq. 3)The practical design of supercritical hydrothermal synthesis process systems necessitates the evaluation of thereaction rate. The reaction rate and particle size of the
products vary with different mixing conditions. Based on

30

fluid mixing studies, it is possible to conduct kinetics
studies for supercritical hydrothermal reactions under reaction control conditions without retardation of apparent
reaction rates caused by insufficient mixing (Aoki N. etal., 2016). Fig. 5 shows the particle sizes of the obtained
CeO2 nanoparticles at different temperatures and Re
during mixing. The particle size converged as Re increased, and similar convergence was observed for conversion of cerium ions. The reaction rate of cerium nitrateunder sufficient mixing conditions, i.e., reaction control
conditions, was studied through changing the residence
time by changing the reactor volume. It was reported thatthe reaction can be considered as a first order reaction for
cerium ion consumption. Acceleration of the reaction rate
was observed near the critical point (Aoki N. et al., 2016),
as shown in Fig. 6. The solvent effects of the dielectric
constant can be analyzed with various models. The following equation shows the Onsager-Kirkwood model. Here, kis the reaction rate constant, kg is the reference reaction
rate constant, μ‡ and μi represent the dipole moment in theAkira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

Fig. 6(Eq. 5)such as Fe, Co, and Ni. Low-temperature conditions arefavored for equilibrium because the reduction of metaloxides is an exothermic reaction. However, in terms of thephase behavior of hydrogen and water, higher temperature
conditions are favored because of the homogeneous phaseformation of hydrogen and water, as shown in Fig. 3. The
chemical potential of dissolved hydrogen in water ishigher than that of gaseous hydrogen. Thus, the reduction
reactivity of metal oxides is higher in water, compared to
the gas phase. Thus, near-critical conditions are appropriate for obtaining the metal state based on reaction equilibrium, phase behavior, and reactivity.
Metal and metal oxide nanoparticles can be synthesized
in a reductive atmosphere. Various metal nanoparticles
have been synthesized by loading formic acid, which
produces hydrogen during decomposition under high-­temperature conditions (Clercq M. le et al., 2001; Sue K.
et al., 2004; Ohara et al., 2007a; Arita T. et al., 2011a).
Thermodynamics (Arita T. et al., 2011a; Seong G. et al.,2011) and kinetics (Seong G. et al., 2014; Seong G., 2012)
studies found that synthesis with a batch reactor requiredlarger amounts of hydrogen than the theoretical amount,suggesting that reduction was retarded following the formation of large metal oxide particles. The use of a flow
reactor suppressed the growth of metal oxide particles before the reduction reaction, and metal nanoparticles wereformed when the theoretically predicted amount of hydrogen was used. Moreover, stability issues, such as surface
oxidation, were investigated with and without organic
modifiers. Iron-platinum metal alloy nanoparticles werealso successfully synthesized in this reaction system (Arita
T. et al., 2011b).
Valence control during nanoparticle synthesis is an important technique not only for metal particles but also forsome types of metal oxides. Metal ions must be reduced
to the appropriate valence state in order to form target
materials. For example, copper oxide nanoparticles weresynthesized using organic chelates as starting materials
and the ligands of those chelates as reducing agents. Mono-­phase Cu2O nanoparticles were obtained using [Cu(Gly)2]2
with the shortest ligand chain length (Togashi T. et al.,2010). Mono-phase CuAl2O2 was also successfully synthesized with control over the copper valence, using formic
acid as a reducing agent (Sato T. et al., 2008). Co-dopingof tin and zinc in indium oxide was also studied with thevalence control of tin to produce the target phase using
formic acid (Lu J. et al., 2016).

(Eq. 6)

4. Composite oxides

Arrhenius plot for the hydrothermal reaction of cerium
nitrate. Reprinted with permission from Ref. (Aoki N.
et al., 2016). Copyright: (2016) Elsevier.

transition state and the initial state, respectively, r‡ and ri
represent the molecular radius in the transition state andthe initial state, respectively, R is the universal gas constant, T is the temperature, and ε is the dielectric constant.

μi2 
 μ ‡2
 r ‡3   r 3  ε  1i  lnk  lnk g＋ RT 2ε  1 (Eq. 4)

When the polarity difference between the initial state
and transition state is large, the second term has a significant effect on the reaction rate. The destabilization effectsof ionic compounds emerge under low dielectric constantconditions, as shown in Fig. 1(c), and the reaction rate
constant becomes closer to that of gas-phase reactions (kgin Eq. 4).

3. Atmosphere control (redox control)
Supercritical water can be an oxidative medium because water can act as an oxidant. However, as explainedin the introduction, supercritical water can form a homogeneous phase with gaseous materials, which enables
control over the redox atmosphere. When hydrogen isused as a reductant, the following two reaction equilibria
should be considered:M NO 3 x x
H 2 
M xHNO 32

M  xH 2O xH 2  MO xConsidering the redox potentials, noble metals such as
Au and Pt can easily form. However, comparatively large
amounts of hydrogen are required to obtain base metals

Composite oxides are valuable for various applications.
Not only mono-component particles but also various composite oxides have been synthesized by the supercritical31

Akira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

hydrothermal method. For example, LiCoO2 and LiMn2O4
cathode materials have been synthesized for use inlithium-­ion batteries by the supercritical hydrothermal
method, and highly stable charge and discharge properties were recorded after several charge-discharge cycles(Adschiri T. et al., 2001). The high crystallinity of particles synthesized by supercritical hydrothermal synthesis
possibly leads to better stability for the mobility of lithium ions, compared to materials with the same composition obtained from conventional processes.
Tuning of reaction conditions such as temperature, pH,
heating rate, reaction time, and feeding ratio of starting
materials are essential to obtain a single-phase composite
oxide. Copper manganese oxide nanoparticles were synthesized using a batch reactor and a continuous flow reactor. Formation of byproducts was found to be suppressedwith a continuous flow reactor (Rangappa D. et al., 2008).
The results suggest that heating rates affect the structuralformation of the composite oxide phase. Yttrium aluminum garnet (YAG) nanoparticles were synthesized with acontinuous flow reactor, and it was shown that slow heating led to the formation of byproducts (Hakuta Y. et al.,1999).
The rapid reaction owing to high supersaturation
causes a metastable or non-equilibrium state in supercritical water. The formation of unique structures such as
metastable, highly doped, and deficient structures has
been reported (Hakuta Y. et al., 1998; Yamamoto K. et al.,2014, 2015; Zhu Y. et al., 2015; Yoko A. et al., 2014,2016a, 2016b, 2017). Barium hexaferrite could be synthesized in approximately 1 s in a continuous flow reactor
with excessive barium (Hakuta Y. et al., 1998). The synthesized barium hexaferrite was transformed to barium
di-ferrite and barium mono-ferrite after it was treated inbatch reactors under the same temperature and pressure
as the synthesis conditions, suggesting that the synthesized barium hexaferrite phase was a non-equilibrium
state. Recently, Gd-doped ceria nanocubes (Yamamoto K.
et al., 2014, 2015) and Cr-doped ceria (Zhu Y. et al., 2015)
were synthesized by the supercritical hydrothermal
method. High doping concentration, including non-­equilibrium composition, can be achieved through rapid
reactions in a flow reactor. Moreover, highly deficient
structure formation was reported for several types of perovskite oxides due to the difference in the precipitation
driving force (Yoko A. et al., 2014, 2016a, 2016b, 2017).

5. Organic modification
In addition to the synthesis of metal and metal oxide
nanoparticles, surface modification of those nanoparticles
in the reaction field during particle formation is also possible with supercritical hydrothermal synthesis. Table 1

32shows the various types of surface modified nanoparticles
reported by Adschiri group. Using in situ surface modification, particle size and shape control were achieved because the surfactant molecules can affect nucleation andgrowth, i.e., the interface energy can be tuned with organic molecules. Fujii et al. (2016) reported that the mod­ification density varies depending on the length ofmodifiers, resulting in particle size variation.
Control over nanoparticle morphology as a result of
crystal facet control was realized by the coexistence oforganic molecules during nanoparticle formation, e.g.,synthesis of CeO2 nanocubes (Zhang J. et al., 2007),
Co3O4 (Mousavand T., 2009), and CoAlO2 (Rangappa D.
et al., 2007a, 2007b), as shown in Fig. 7. Particle morphology was controlled by selecting the appropriate modifier species and the amount of them. Co-existence ofmodifiers can affect particle formation by decreasing thesurface energy of the nanocrystals. The surface stability
order of a CeO2 crystal, determined by the surface energyof each CeO2 crystal surface, is {100} > {110} > {111},
and the equilibrium shape of a CeO2 crystal without organic modification is octahedral with exposed {111} surfaces. Particularly in the case of CeO2, it is meaningful toexpose the {100} surfaces because of their high catalytic
activity, although it is difficult to expose such unstablesurfaces. On the other hand, organic modifiers can attach
to an unstable surface and stabilize the surface during
nanoparticle formation. As such, it is possible to fabricate
nanocubes by exposing the {100} surfaces. These controls
are effective for fine-tuning the properties of ceramic
nanocrystals. The applications of CeO2 nanocubes are
discussed in Section 8.
One of the significant factors enabling surface modification is the phase behavior of high-temperature waterand organic compounds, as explained in the Introduction
section. An experiment was conducted to confirm thephase behavior of the modifiers and water. Fig. 8 shows
the visualized reaction field of octanoic acid and Ce(OH)4
aqueous solution at different temperatures. At lower temperatures, phase separation of the organics and water wasobserved, and a homogeneous phase was formed at
330 °C (Adschiri T. et al., 2015).
Another important characteristic of surface modified
nanoparticles is dispersibility. Surface-modified nanoparticles disperse well in solvents, which cannot be realizedwith ex situ surface treatments. The dispersibility and stability of surface-modified nanoparticle dispersions due tocovalent surface modification are introduced in Section 7.
The important points of surface modification by supercritical hydrothermal synthesis are high modification density and covalent bonding on the metal oxide surface. As
modifiers, carboxylic acids, amines, phosphonic acids, aldehydes, alcohols, and catechols have been applied as shownin Table 1. The degree of modification can be analyzed by

Akira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

Table 1

Types of surface-modified nanoparticles synthesized by supercritical hydrothermal method.

Core particles

Modifiers

Ref.

AlOOH

n-Hexylaldehyde, n-Hexylamine

Mousavand et al., 2007a

ZnO

Hexanol, Hexanal, Hexylamine

Ohara et al., 2007b

α-Fe2O3n-Decanoic acid

Takami et al., 2007

Fe3O4

n-Decylamine

Takami et al., 2007

Fe3O4

3,4-Dihydroxyhydrocinnamic

Togashi et al., 2012

Iron oxides

Hexanoic acidArita et al., 2011aCo3O4

n-Decanoic acid, n-Decylamine

Mousavand et al., 2009

CeO2

Hexanedioic acid

Takami et al., 2008

CeO2

Hexanoic acid, Decanoic acid, Stearic acidArita et al., 2010a

CeO2

Adipic acid, Pimelic acid, Sebacic acid, Dodecanedioic acid

Taguchi et al., 2009

CeO2

Polyvinyl alcohol, Polyacryl acid

Taguchi et al., 2011

CeO2

L-Glutamic acid, L-Aspartic acid, L-Arginine

Litwinowicz et al., 2014

CeO2

Hexanoic, Octanoic, Decanoic, Dodecanoic, Tetradecanoic,
Hexadecanoic, Octadecanoic, Oleic acids

Taguchi et al., 2014

Cr-doped CeO2

Decanoic acid

Zhu et al., 2015

TiO2

Hexaldehyde

Mousavand et al., 2007b

TiO2Ethyl 11-diethoxyphos-phorylundecanoate

Arita et al., 2010b, 2010c

ZrO2

6-Phenylhexanoic acid, 3-Phenylpropionic acid

Takigawa et al., 2017

HfO2

3-Phenylpropionic acid

Hiyama et al., 2018

HfO2

Decylamine, Decanal, Decanoic acid

Saharaneshin et al., 2012b

Bi2O3

3-Phenylpropionic acid

Hiyama et al., 2018

Gd(OH)2

3,4-Dihydroxyhydrocinnamic

Singh et al., 2013

FePt

Oleic acidArita et al., 2011b

BaO·6Fe2O3

Oleic acid

Rangappa et al., 2010

CoAl2O4

Oleic acid, Decanoic acid

Rangappa et al., 2007aCoAl2O4

Hexanoic acid, 1-Hexylamine

Rangappa et al., 2007b

CuMn 2O4

Hexanoic acid, 1-Hexylamine

Rangappa et al., 2008

ITO (Indium Tin Oxide) Hexanoic acid

Lu et al., 2012

IZTO (Zn dope ITO)

Lu et al., 2016

Hexanoic acidthermogravimeter differential analysis (TG-DTA). The
modified state is analyzed using a Fourier transform infrared spectrometer (FT-IR) and nuclear magnetic resonance (NMR). The modification density is typically ashigh as 4–7 molecules per square nanometer, which isconsistent with the number of metal atoms exposed at theparticle surface. Fig. 9 shows an example of 1H NMR
spectra comparing decanoic acid and decanoic acid-modified CeO2 nanoparticles in CDCl3 (Arita T. et al., 2011c).
Obviously, the motion of the surfactants is restricted due
to binding on the nanoparticles. Chemical bond formation
by in situ modification of the supercritical method has

been confirmed.
Very recently, surface-modification of CeO2 nanoparticles synthesized in supercritical water was observed at
the atomic scale using state of the art aberration-correctedscanning transmission electron microscopy (STEM) imaging and electron energy loss spectra (EELS) techniques(Hao X.D. et al., 2018). It was observed that the surface of
the CeO2 nanoparticles was covered by carbon, based on
the composition distribution mapping of cerium, oxygen,and carbon, as shown in Fig. 10. Moreover, a single surfactant molecule can be detected using STEM analysis.
The modification state can be confirmed at the atomic

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Akira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

Fig. 7

TEM images of CeO2 nanocubes with and without modifiers (Zhang J. et al., 2007), Co3O4 nanocubes(Mousavand T. et al., 2009), BaFe12O19 nanocubes (Rangappa D. et al., 2010), and CuAlO2 nanocubes(Rangappa D. et al., 2007a, 2007b).

Fig. 8Visualized phase behavior of modifiers and aqueous Ce(OH)4 with increasing temperature (Adschiri T.
et al., 2015).

level by direct observation.
The effects of modifiers on nanoparticle structure arealso an interesting and significant topic. Stabilization ofoxygen vacancies due to the existence of organic modifiers was reported for CeO2 (Zhang J. et al, 2011a). The valence state of cations can also be affected by surface
modifiers. This result suggests that the effects of modifiers on nanoparticle structure cannot be neglected in somecases.

6. Cluster formation
Arranging individual nanocrystals into superlattices isa challenging topic for applications of nanoparticles.
Cluster synthesis has been achieved using the supercritical method. Modifiers with functional groups on bothends of a molecular chain, i.e., bifunctional compounds

34

Fig. 91

H NMR (400 MHz) spectra of decanoic acid-modified
CeO2 nanoparticles (5 mg) and free decanoic acid
(1 mg) in 500 μL of CDCl3. The numbering of carbon
is indicated in the upper left corner. Reprinted withpermission from Ref. (Arita T. et al., 2011c). Copyright:(2011) American Chemical Society.

Akira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

Fig. 10 STEM-EELS mapping of the surface modified CeO2 nanoparticles. Reprinted with permission from
Ref. (Hao X. et al., 2018). Copyright: (2018) John Wiley and Sons.

Fig. 11 SEM and TEM images of Gd(OH)3 nanoclusters. Reprinted with permission from Ref. (Singh V. et al.,2013). Copyright: (2013) The Royal Society of Chemistry.

such as dicarboxylic acid, were used to bridge between
nanoparticles (Takami S. et al., 2008), and it was foundthat the orientation of each nanoparticle was ordered.
Surface-modified nanoparticles might behave as building
blocks during superstructure formation. So far, the assembly of surface-modified CeO2 (Takami S. et al., 2008;
Litwinowicz A.A. et al., 2014) and Gd(OH)3 (Singh V. etal., 2013) nanoparticles has been reported. Fig. 11 shows
SEM and TEM images and selected area electron diffraction (SAED) patterns from the obtained Gd(OH)3 cluster(Singh V. et al., 2013). In this case, 3,4-dihydroxy hydrocinnamic acid (DHCA) was used as a bridge molecule inan alkaline medium. Dissociation of the functional groupand surface charge determined the interaction between
nanoparticles, and surface modifiers resulted in distinct
morphology changes. Nanocrystal ordering with specificorientation was observed from SAED patterns, suggestingthat inorganic meso-crystals can be formed with organic
molecules by applying this method. In addition, the formation of the characteristic secondary structure, composedof primary nanoparticles with preferential attachment oforganic molecules through aggregation of primary particles, was investigated (Sahraneshin A. et al., 2012a).
The design of nanoclusters can be developed using

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Fig. 12 Dispersion of surface decanoic acid-modified CeO2 nanoparticles in cyclohexane at different concentrations. Reprinted with permission from Ref. (Arita T. et al., 2012). Copyright: (2012) The Chemical Society of Japan.

optimized organic modifiers during supercritical hydrothermal synthesis. Newly designed nanoclusters are expected to broaden further the application of nanoparticles.

7. Nanoparticle dispersion
The dispersibility of nanoparticles is a key factor forindustry to make full use of nanoparticle characteristics.
As explained in Section 5, nanoparticles synthesized insupercritical water can be dispersed in solvents owing tosurface organic modification. Dispersed nanoparticle colloid systems or suspensions have been studied recently as
nanofluids (Ogi T. et al., 2017). Nanoparticles covalently
modified by organic molecules and synthesized by supercritical hydrothermal synthesis have also gained attention
due to their high dispersibility and stability.
By using appropriate solvents and modifiers, highly
concentrated nanoparticle dispersions up to 77 wt% can
be fabricated (Arita T. et al., 2012). Fig. 12 shows a picture of decanoic acid modified CeO2 nanoparticles in cyclohexane. The mono-dispersed colloids exhibit low
viscosity, even at high concentrations (Arita T. et al.,2012).
A new heat transfer film was developed by applying theorganic surface modification technique. High heat conductive materials such as silicon nitride and alumina werereacted with organic compounds, resulting in high affinity to polymer materials and high fluidity, even at loading
rates as high as 80 vol%. The fabricated heat transfer film
has thermal conductivity as high as 40 W/(mK). The implementation of a heat transfer film made of surface-­
modified nanoparticles in semiconductor packages wasdemonstrated, with the package maintaining high insulation and thermal conductivity. Fig. 13 shows a schematic
diagram of the thermally conductive hybrid materials(Adschiri T. et al., 2012).

36

Fig. 13 Schematic diagram of heat transfer film implementation for electronic devices. Reprinted with permission
from Ref. (Adschiri T. et al., 2012). Copyright: (2012)
The Japan Society of High Pressure Science andTechnology.

8. Catalytic reaction
Metal and metal oxide nanoparticles synthesized by thesupercritical hydrothermal method can be used in several
catalytic applications. As explained in Section 5, morphology controls are possible by using surface organic
modification. In the case of CeO2, {100}-exposed CeO2
nanocubes were obtained in the presence of organic modifiers. The role of organic molecules here is to expose certain crystal surfaces. However, these molecules canhinder catalytic reactions at the surface. Thus, surfactants
need to be removed for the modified structures to be used
as catalysts, and as-synthesized particles are calcined toremove organic modifiers before the nanoparticles wereused as catalysts. It should be noted that the cubic shape
was maintained, even after being calcined at 300 °C.
The oxygen storage capacity (OSC) of synthesized
CeO2 nanoparticles has also been measured. It was foundthat OSC was significant at temperatures as low as
150 °C, whereas oxygen mobility was observed for ordinary, non-facet-controlled CeO2 at approximately 400 °C(Zhang J. et al., 2011a). In addition, 5 mol% Cr-doped
CeO2 nanocubes were synthesized, exhibiting higher OSC
than undoped CeO2 nanocubes (Zhu Y. et al., 2015). As
explained in Section 4, the supercritical hydrothermal
method can be applied for high-concentration doping of
metal oxide nanoparticles to further improve theseAkira Yoko et al. / KONA Powder and Particle Journal No. 37 (2020) 28–41

9. Conclusion

Fig. 14 Photographs and UV-vis spectra for lignin before andafter hydrothermal reactions with and without facet-­
controlled CeO2 nanocatalysts. Reprinted with permission from Ref. (Seong G. et al., 2017). Copyright:(2017) Elsevier.

nanocatalysts.
Catalytic conversion of lignin was studied under hydrothermal conditions with facet-controlled CeO2 nanocubes(Seong G. et al., 2017, 2018). As for the chemical recoveryof phenolic compounds from lignin, polymerization of
those phenolic compounds as lignin decomposition products is a key issue to be solved. Degradation of lignin
with CeO2 nanocubes was achieved alongside polymerization suppression. This occurs because aldehydes wereoxidized rapidly, which can act as a bridge moleculeduring polymerization with phenolic compounds. Fig. 14
shows photographs and UV-vis spectra for a lignin aqueous solution before and after the reactions. The UV spectra at 280 nm are attributed to the phenolic compounds,suggesting that larger amounts of phenolic compounds
can be recovered with CeO2 nanocubes. Similar reactions
were conducted for biomass waste from the paper industry (black liquor) and heavy oil. Black liquor and bitumen
decomposition with CeO2 nanocubes was observed, andhydrogen formation by water reforming with the partiallyreduced ceria was detected in both cases.
These reforming reactions are endothermic. Significant
decrease in reaction temperatures can be achieved by using new catalysts, which enables the efficient use of low-­temperature waste heat for the endothermic reforming
reactions. Exposing specific active crystal faces, doping
metals at high concentrations, and forming nanoclusters
are expected to maximize catalytic activity. Further devel­
opment of catalyst design is promising for use in a varietyof catalytic reactions.

In this paper, recent advances in supercritical hydrothermal synthesis have been presented. Process kinetics
and design are significant factors controlling the properties of the reaction products. Surface modification is a key
technique that can be used to fabricate nanoparticle dispersion and control crystal facet exposure. Results onparticle structure characteristics, such as non-equilibrium
states, deficient structures, and strong bonding throughmodification, have broadened new technological fields
and facilitated the development of new catalysts and hybrid materials. Further studies are necessary to implement
the technology in particle and powder engineering applications.

Acknowledgements
This study is supported by the grants from the Japan
Society for the Promotion of Science (JSPS); KAKENHI(Grant Number, JP16H06367), the New Energy and Industrial Technology Development Organization (NEDO),
and WPI – Advanced Institute for Materials Research(WPI-AIMR), Tohoku University established by World
Premier International Research Center Initiative (WPI),
Ministry of Education, Culture, Sports, Science andTechnology (MEXT), Japan.

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Authors’ Short Biographies
Akira Yoko
Dr. A. Yoko received his Ph.D. from The University of Tokyo in 2017. Regarding his
thesis, he won the Dean’s Award for Outstanding Achievement, Graduate School of
Frontier Sciences, The University of Tokyo in 2017. In 2017, he moved to Tohoku University and he is Assistant Professor of WPI – AIMR from 2018. He has been studying
nanoparticle formation in supercritical water. Recently, he also works on theoretical researches of nanoparticle structure and property.

Gimyeong Seong
Assistant Prof. G. Seong received his Bachelor’s and Master’s degrees in Engineeringfrom Sogang University, Seoul, Republic of Korea in 2006 and 2008, respectively. In
Oct. 2008, he moved to Japan and transferred to Tohoku University, where he began to
study on the synthesis of metal nanoparticles using supercritical fluid, and he received
his Doctorate in Engineering in 2012. After two years of postdoctoral research, he became an Assistant Professor of NICHe, Tohoku Univ. in 2014. Currently, he focuses his
research on various nanomaterials including metal oxides as well as metal nanoparticle
synthesis using supercritical fluid technology.

Takaaki Tomai
Prof. T. Tomai received his Ph.D from The University of Tokyo in 2008.
In 2010, he moved to Tohoku University as Assistant Professor of IMRAM, and became Associate Professor of IMRAM in 2017. He has been studying on the materials
science and engineering using supercritical fluids.

Tadafumi AdschiriProf. T. Adschiri received his Doctorate in Engineering from The University of Tokyoin 1986. In 1989, he moved to Tohoku University and began studying reactions in supercritical fluids for biomass conversion, chemical recycling of wastes, organic reactions,and materials synthesis. He became Professor of IMRAM in 2002, and since 2007, he isProfessor of WPI – AIMR, Tohoku University. He has been awarded many prizes, including the Minister’s awards of MEXT, Japan. Currently, he is a member of the Science
Council of Japan (23rd and 24th terms) and the President of the Society of Chemical Engineers, Japan.

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KONA Powder and Particle Journal No. 37 (2020) 42–63/Doi:10.14356/kona.2020003

Review Paper

Analysis of Industry-Related Flows by Optical
Coherence Tomography—A Review †Antti I. Koponen 1* and Sanna Haavisto 2
1
2

VTT Technical Research Centre of Finland Ltd., Finland
Spinnova Ltd., Finland

Abstract
Optical Coherence Tomography (OCT) is a light-based imaging method capable of simultaneously capturing theinternal structure and motion (1D, 2D or 3D) of various opaque and turbid materials with a micron-level spatial
resolution. Depending on the OCT technology, axial scanning rates can vary in a range of tens to hundreds ofkHz. The actual imaging depth significantly depends on the optical properties of the material and can vary frommicrometers to a few millimeters. From the viewpoint of industrial applications, OCT technology is very
appealing. Due to its resolution, speed, and ability to deal with opaque materials, it fills an apparent gap in
available measurement methods. Nonetheless, OCT has not to date seen widespread growth in the industrial field.
This has been at least partly due to a lack of commercial devices compact and flexible enough to adapt toindustrial needs. The recent emergence of more generic commercial OCT devices has considerably lowered thethreshold for adapting the technique. The utilization of OCT for structural analysis, also outside the medical field,
has been thoroughly discussed in scientific literature. Therefore, in this paper, we will mainly concentrate on
applications of OCT that also utilize its capability of performing velocity measurements. The emphasis will be onindustrially motivated problems such as rheology, microfluidics, fouling and turbulence.
Keywords: optical coherence tomography, OCT, industrial applications, microfluidics, rheology, fouling

1. Introduction
Research, process development and operation as wellas process quality control depend greatly upon our ability
to collect information with measurements, through which
engineers hope to get answers to the questions “what andwhy?”. The enormous developments that have taken placein the process industry during the last twenty years havebeen mainly related to improvements in accuracy, reliability, and speed of measurement techniques. The ultimate goal of process engineers is the ability to performthe measurements in situ, online and in real time. However, due to a lack of existing online techniques, one often
has to settle for offline measurements.
There are a number of measurement technologies andapproaches available today, each one with their respective
advantages. Optical measurement systems, such as an interferometer, optical displacement meter, moiré inspection,
†
1
2

*

42

Received 14 May 2018; Accepted 5 July 2018
J-STAGE Advance published online 17 November 2018
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: +358-20-722-2596

stereoscopy, and holography, are some of them with several advantages. Firstly, they are noninvasive and nondestructive methods which afford flexibility in setting up
measuring systems. Secondly, one is not limited topointwise measurements, as full-field measurements are
possible. This feature is essentially inherent, e.g. in CCD
imaging. For many applications, the number one benefitof optical measurement methods is their capability forhigh-speed sampling. Optical sensors also have the advantage of high precision in comparison, e.g. with ultrasonic, electromagnetic, and electrostatic sensors. They arewidely used in industry, e.g. for end-product quality,
material surface, topography, defect detection, 3D dimension measurement, and color inspection.
Optical Coherence Tomography (OCT) is a rather new
member of the family of optical sensors (Drexler andFujimoto, 2008; Popescu et al., 2011). OCT is capableof measuring the internal structure of various semi-­transparent materials with a micron-level spatial resolution, as illustrated in Fig. 1a. Depending on the OCT
technology, axial scanning rates can vary in a range oftens to hundreds of kHz. The actual imaging depth signifi­
cantly depends on the optical properties of the materialand can vary from micrometers to a few millimeters. The
OCT technique was invented in the late 1980s. It mainly

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Antti I. Koponen et al. / KONA Powder and Particle Journal No. 37 (2020) 42–63

Fig. 1a) 3D structural OCT image of microfibrillated cellulose (MFC) suspension in a pipe with a diameter of
8.6 mm. Image taken with permission from Haavisto et al. (2015a). b) Marangoni effect (spontaneous
flow due to evaporation of alcohol) in a droplet of wine as imaged with Doppler OCT (unpublished).

evolved in the medical field, especially in ophthalmology
in the 1990s. Later, it attracted attention for applicationin other fields as well. Applications of OCT—also outsideof the biomedical field—have been reviewed in (Wiesauer
et al., 2005a; Stifter, 2007; Song and Harding, 2012;
Kawasaki, 2013; Yoshizawa, 2015).
While online sensors are still scarce, the applicabilityof OCT for structural analysis for industrial purposes has
been demonstrated in numerous cases. These include
crystallization processes in polymers (Hierzenberger,2014), liquid sorption in paper (Fabritius, 2007), thermal
degradation of epoxy resin composites (Awaja et al.,2009), automotive coatings (Lawman et al., 2017a), nanocomposites (Schneider et al., 2016), polymer-fiber composites (Stifter et al., 2008), quality control of film coating(Koller et al., 2011; Nemeth et al., 2012; Markl et al.,2014a; Markl et al., 2015a; Markl et al., 2015b), andLCD-display production (Shirazi et al., 2016; Wijesinghe
et al., 2017). An important functional extension of OCT,
namely polarization-sensitive OCT (Boer et al., 2017), hasbeen used, e.g. for the analysis of stress fields of various
materials (Stifter et al., 2003; Wiesauer et al., 2005b;
Wiesauer et al., 2007; Heise et al., 2010; Stifter et al., 2010).
Markl et al., (2014b), discuss general aspects related to theinline quality control of moving objects with OCT.
In addition to structural analysis, the capability of measuring flow velocities is often vital for industrial purposessuch as process development and process control. While
there are robust indicators for measuring average volumetric flows, e.g. in pipes, the availability of instruments
for measuring local velocities is more limited. Various
techniques that can provide information on velocity fields
are presented, e.g. in Chaouki et al. (1997) and Powell(2008). If the medium is transparent and there is opticalaccess, one can apply, e.g. PIV or LDA techniques. For
turbid media, however, only Ultrasound Velocity Profiling(UVP), has gained broader use in industry (Takeda,2012). Other methods, such as Nuclear Magnetic Resonance Imaging (MRI) and various tomographic methods
are widely used on a lab scale, but their industrial use isstill very limited. Another option for velocity field measurements is Doppler OCT (Drexler and Fujimoto, 2008).
DOCT combines the Doppler principle with OCT toobtain velocity information simultaneously with structural imaging (see Fig. 1b). It was first used in ophthalmology for the quantitative imaging of blood flow invessels in vivo. Recently, the use of DOCT has finallyspread outside of biomedicine, but it is still in its infancy
for industrial applications.
In principle, from the viewpoint of industrial applications, OCT technology should be very appealing. Due to
its resolution, speed, and ability to deal with opaque materials, it fills an apparent gap in the available measurement methods. Nonetheless, OCT has not to date seen
large growth in the industrial field. This has been at least
partly due to a lack of commercial devices compact andflexible enough to adapt to industrial needs. The recent
emergence of more generic commercial OCT devices
such as Telesto SD-OCT Systems by Thorlabs have somewhat decreased this bottleneck. While they cannot beat theperformance of state-of-the-art laboratory-built devices,
the commercial OCT devices have lowered the thresholdfor adapting the technique considerably.
As discussed above, the utilization of OCT for structural analysis, also outside the medical field, has beenthoroughly reviewed in scientific literature. Therefore, inthis paper, we will mainly concentrate on OCT applications that utilize its capability of performing velocity
measurements. The emphasis will be on industrially motivated problems such as rheology, microfluidics, fouling,
and turbulence. We hope this paper will encourage more
people to adopt this emerging field of measurement technology for solving additional R&D problems.

2. Optical coherence tomography
OCT employs low-coherence spectroscopy and interferometry to determine the optical properties of the sample as a depth-dependent reflectivity profile (Drexler andFujimoto 2008; Popescu et al., 2011; Leitgeb et al., 2014;
Hong, 2018). The short coherence length of the employedbroad bandwidth light source is utilized for axial sectioning. 2D slice images (B scans) or 3D volumes can be constructed by employing scanners to acquire a series ofaxial scans (A scans) at different lateral locations.

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Fig. 2

In time domain OCT (TD-OCT), the reference mirror moves during the measurement, and at a given moment the signal is
obtained from a unique position. The different interfaces within the sample lead to a peak in the degree of interference represented as a peak in the signal intensity graph. In Fourier domain OCT (FD-OCT), the reference mirror is fixed, and the detector arm of the interferometer uses a spectrometer instead of a single detector. The spectrometer measures spectral
modulations produced by interference between the sample and reference reflections.

In the first realization of OCT, i.e. time domain OCT(TD-OCT), the light from a low-coherence source is split
into two paths by a coupler, directing it along two different arms of an interferometer (see Fig. 2). One arm is designated as the reference arm, while the other is the sample
arm. When the light exits the fiber end of either arm, it iscontrolled by various optical components (mirrors, lenses,etc.) to control specific beam parameters such as shape,
depth of focus, and the intensity distribution of the light.
In the reference arm, the light is back-reflected by a reference mirror, and it returns into the interference system,
propagating along the same path it came from, only in the
opposite direction. The same process applies for the lightin the sample arm, the only difference being that thebeam is backscattered by the sample. In an inhomogeneous sample, different structures within the sample will
have different indices of refraction, and light will bebackscattered when it encounters an interface between
materials with different refractive indices. The returning
light from both arms recombines at the coupler generating
an interference pattern, which is recorded by the detector.
For a particular position of the reference mirror, the lightpropagating in the reference arm travels a certain opticaldistance and forms the corresponding interference pattern
only with light that traveled the same optical distancealong the sample arm, including the portion of the distance traveled inside the sample. Therefore, when the reference mirror is translated along the propagation directionof light for different positions of the mirror, the returningreference generates interference patterns with light backscattered from corresponding depths within the sample.
In this way, the dependence on the depth of the intensityof light backscattered from beneath the sample surface
can be measured.
In Fourier (or spectral) domain OCT (FD-OCT), the44light echoes are collected simultaneously from all axial
depths and are detected as modulations in the source
spectrum with all the spectral components captured
simultaneously (see Fig. 2). The technique is called Fourier domain OCT because the interference pattern is recorded in the spectral domain for each lateral position,and the final information is reconstructed via Fouriertransform. The main difference between these two technologies is that the reference arm in an FD-OCT system
has a static mirror instead of a moving one as in TDOCT. This feature eliminates the moving mirror and thelimitations imposed by the inertia of that mechanical device. Due to the elimination of the mechanical translation,
FD-OCT systems are capable of higher data acquisition
speeds than TD-OCT systems.

3. Doppler optical coherence tomography
Due to the high imaging speed of OCT, structural
2D/3D imaging can be used for obtaining velocity information through a PIV-type analysis to determine two/
three velocity components (Shen et al., 2011; Chen et al.,2013; Mujat et al., 2013; Zhou et al., 2016). It is also possible to obtain velocity information from the speckle noiseof the structural data with autocorrelation analysis (Pretto
et al., 2016). When the velocity information is retrieved
simultaneously with structural imaging, the method is referred to as Doppler OCT (DOCT), or OCT velocimetry.
Conventional OCT is based on measurement of the amplitude of the backscattered light. In DOCT, depth localized
phase shift is also measured.
The early approaches of measuring the OCT phaseshift were based on time domain techniques (Wang et al.,
1995; Chen et al., 1997a; Chen et al., 1997b; Proskurin etAntti I. Koponen et al. / KONA Powder and Particle Journal No. 37 (2020) 42–63

al., 2003a). Interference fringes are then detected if thesample arm distance in an interferometer matches the reference arm length within the temporal coherence length.
This deﬁnes the axial resolution, which is inversely related to the spectral bandwidth of the light source. A simple method to detect the Doppler-shifted time domain
OCT signal is to record the full fringe signal and calculate
the local frequency shift within a small window that is
slid across an A-scan. This approach is, however, computationally very expensive, and cannot be used for real-time ﬂow measurements. In addition, the spatial
resolution is inversely dependent on the frequency resolution of the Doppler system. An alternative method uses
phase-sensitive Doppler analysis, offering the advantage
of decoupling of the spatial and frequency resolution. In
this case, the phase changes are measured between two
consecutive A-scans.
Nowadays, Fourier domain DOCT has largely replaced
time domain DOCT due to its much higher imaging speed
and better sensitivity (Liu and Chen, 2013; Leitgeb et al.,2014). In Fourier domain DOCT, the phase changes aremeasured between two A-scans, and the full depth structure is encoded in parallel by the recorded spectral interference pattern, and reference arm scanning is not needed.
There are two variants of Fourier domain DOCT:
Spectrometer-­based Fourier domain DOCT (FD-DOCT)and swept-source DOCT (SS-DOCT). In the ﬁrst case,the spectral interference pattern is recorded with a spectrometer in a parallel way, whereas in the second, the interferogram is acquired as a function of time using awavelength-tuning source at the interferometer entrance(Hendargo et al., 2011; Leitgeb et al., 2014). The SSDOCT method has certain advantages in the near infrared
region above 1 μm, where detector arrays are expensive(Lexer et al., 1997). In addition, SS-DOCT systems may

Fig. 3

improve acquisition speed. The introduction of Fourier
domain mode-locked (FDML) swept sources made A-scanrates of several hundreds of kHz available for the ﬁrst
time (Huber et al., 2006, 2007). A recent review of SSOCT can be found in Alibhai et al. (2018).
In a DOCT measurement, the measured target velocity
in a y-directional A-scan isv( y) Δφ( y) fλ,
4πn cos α(1)where f is the scanning rate, Δφ(y) is the measured phaseshift at position y, λ is the central wavelength, n is the medium refractive index (n = 1 for air), which is included
due to the light velocity depending on it, and α is the angle between the measurement beam and the velocity vector (see Fig. 3a). The values of the phase shift are
restricted between –π and π. The theoretical maximum
measurable velocity is thus

vmax 

fλ.
4n cos α(2)

The maximum measurable velocity can be increased bydecreasing the measurement angle α between the DOCT
beam and the velocity vector. The relative error due to theangle is then in proportion to Δα (Takeda, 2012).
tan α
Due to inherent noise (and possible velocity fluctuations)a series of phase-shift measurements gives a histogram ofphase shifts (see Fig. 4a and 4b). The width of the histogram has been analyzed in detail in Szkulmowska et al.
(2008). If the phase shifts exceed the boundaries they arewrapped by –2π (see Fig. 4c). The situation is similar todata sampling where frequencies exceeding the Nyquist
frequency (half of the sampling frequency) are aliased
among the measured low-­f requency data.

a) The DOCT measurement gives the component v of the velocity vector U in the direction of the measurement beam. b) The DOCT measurement arrangement for a pipe flow. The average flow direction isparallel to the pipe axis. c) A closer look at the measurement optics. Here U is the real velocity, v is thecomponent of velocity in the direction of the measurement beam, v’ is the velocity value given by the
DOCT device, and nf is the refractive index of the medium. The angle α is obtained by applying Snell’s
law of refraction to the two interfaces.

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Fig. 4

Measured histograms of phase shifts (gray). The solid lines are Gaussian fits to the histograms. a) Static sample.
b) Moving sample. c) Sample is moving close to the theoretical maximum velocity. The phase-shift histogram iswrapped.

The phase shift Δφ used in Eq. (1) is usually a temporal
average of instantaneous phase shifts to decrease thesignal-­to-noise ratio, resulting in a higher sensitivity tovelocity. The average can be calculated either by averaging directly over the phase-shift histogram or (preferably)by fitting a Gaussian distribution to it. Before averaging,an unwrapping procedure can be applied to correct thehistogram aliasing at large phase shifts (Ghiglia and Pritt,
1998; Werkmeister et al., 2012). This makes it possible tomeasure velocities that exceed the theoretical maximal
velocity given by Eq. (2). Phase unwrapping is an essential process for accurate phase profile reconstruction.
Various methods for improving the accuracy of OCT
phase wrapping have been discussed in Xia et al. (2017).
Just like Doppler ultrasound methods, in its basic form,
DOCT is only capable of measuring a single velocity component of the flow velocity vector in the beam direction.
Two or three velocity components can naturally be obtained by using dual/triple-beam methods (Werkmeister
et al., 2012; Trasischker et al., 2013; Kumar et al., 2014;
Leitgeb et al., 2014). The absolute value of the velocity
vector can be determined by monitoring the bandwidth
broadening of the Doppler spectrum (Ren et al., 2002;
Piao et al., 2003; Proskurin et al., 2003a), combining
spectral and time domain methods (Grulkowski et al.,2010), autocorrelation function of the backscattered light(Wang and Wang, 2010; Weiss et al., 2013), or characterization of the time scale of random fluctuations of the
dynamic scattering component (Srinivasan et al., 2012).
Moreover, all three velocity components can be obtainedby introducing a variable scan bias in the OCT system(Huang and Choma, 2014).
The methods for obtaining more than just the beam directional component of the flow velocity described above
are often technically challenging or require investment inseveral DOCT devices. Fortunately, the main direction of
the flow is known a priori in many industrially relevantgeometries. In such cases, the absolute values of the velocity vectors can be obtained quantitatively. Indeed, oneof the advantages of the OCT when compared, e.g. toultrasound technologies, is the possibility to measure the46

measurement angle α directly from 2D or 3D structural
images (Michaely et al., 2007; You et al., 2014; Haavisto
et al., 2015b; You et al., 2017).
Fig. 3b shows as an example a measurement setup of
pipe flow. From Fig. 3c, we get the real axial velocity inthe pipe to beUv'
nf2 sin β,(3)where β is the DOCT measurement angle (the angle between the camera axis and pipe surface normal), v’ is thevelocity value 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 resolution and scanning speed of state-of-the-art
lab devices are currently below one micrometer and hundreds of kilohertz, respectively. The imaging depth in
optimal conditions can vary a lot depending on the technology used. Typically, it is a couple of millimeters. The
performance of available commercial devices is naturally
more modest. In our work, e.g. we usually used a commercial FD-DOCT (Telesto I, Thorlabs, Inc.). Fig. 14
shows a set-up where this device was combined with arheometer. The central wavelength λ of the device is
1,325 nm, and the A-scan rate can be either 5.5, 28 or
91 kHz. The theoretical maximum velocity Eq. (2) inbeam direction (α = 0), measurable with Telesto I, is thus
3.1 cm/s. As an example, in our pipe flow studies, themeasurement angle β varied typically between 2°–5° (seeFig. 3). With these measurement angles, the maximum
measurable velocity Umax varies in the direction of flow,
e.g. for water (nf = 1.33) between 0.2–0.5 m/s. The axial
resolution of the device is approximately 5 μm in air andthus ca. 3.7 μm in water; the lateral resolution is 7–20 μm,
depending on the optics used. The maximum pixel
amount of 512 per A-scan provides, in optimal conditions,a maximum imaging depth of 1.9 mm in water.
Fig. 5 shows a laminar velocity profile of water in a pipewith a diameter of 8.6 mm measured with Telesto I SDOCT (the exact wall position was determined by fitting aAntti I. Koponen et al. / KONA Powder and Particle Journal No. 37 (2020) 42–63

Fig. 6Laminar velocity profile of water in a pipe measured
with Telesto I SD-OCT (solid line). The dashed line indicates the theoretical laminar profile calculated fromthe flow rate measurement. The mean velocity profile
is based on an ensemble of 50,000 A scans. Imagetaken with permission from Haavisto et al. (2015b).

Examples of measured DOCT velocity profiles (dashedlines) in a pipe flow of MFC (consistency 0.4 %—blue,
1 %—red, 1.6 %—green) together with corresponding
DOCT amplitude signals (solid lines). The DOCT amplification was tuned for each consistency separately to
optimize the quality of the velocity signal. The measurement was performed with Telesto I SD-OCT(Haavisto, 2018).

second-order polynomial to the mean velocity profile at
the wall). Typically for velocity profiling, sequential axial
A-scans were recorded over a certain period in a single
physical position. The result is compared, in Fig. 5, with acorresponding theoretical profile calculated from the flowrate measurement. The measurement angle β (see Fig. 3)
was determined directly from a B-scan structural image
composed of 4,096 A-scans in a spatial range of 5.00 mm,
and there was no fitting between the two data sets. The
agreement between the two data sets is excellent—DOCT
can obviously be used for quantitative velocity measurements out-of-the-box without the need for calibration (seealso Haavisto et al., 2017).
The real measurement depth depends on the material
properties. If the medium scatters too much, the beam
weakens quickly when it travels in the medium, and theintensity of backscattering light is low. On the other hand,
if the scattering level is too low, the amount of observedbackscattered light also drops quickly when the distancefrom the probe increases. For transparent materials suchas pure water, one needs to add extra light-scattering
tracer particles. For this purpose, we used a coffee
creamer, as it disperses easily in water and the size of thefat droplets is typically 0.2–1 μm (Kirk and Othmer,2008) and they follow the flow faithfully. An intralipid
solution can also be used (Lauri et al., 2011a). The amountof creamer added (ca. 0.5–1 %) was adjusted to balance
between the DOCT signal intensity and its penetration
depth. In Haavisto et al. (2017) the measurement depth ofTelesto I was about 1.2 mm for 1 % creamer and 0.01 %xanthan gum water solutions, and 0.4 % softwood and
0.4 % microfibrillated cellulose (MFC) suspensions. Obviously, the maximum measurable velocity can limit themeasurement depth considerably.
Fig. 6 shows an example of measured DOCT velocity
profiles together with the corresponding DOCT amplitude
signals for three consistencies of MFC in a pipe flow.
From Fig. 6, we see that the penetration of the amplitude
signal decreases rapidly with increasing MFC consistency. We also see that while the increasing consistency
decreases the measurement depth of the velocity profile,the deterioration is not as dramatic as for the amplitude
signal. Note the rapid decrease of the amplitude signal
when approaching the wall. This is probably due to a
combination of device optics and a real depletion layer
created at the wall.
The most popular target for DOCT measurements by
far has been the ﬂow of blood in real and artiﬁcial bloodvessels (Bonesi et al., 2010; Drexler et al., 2014; Leitgeb etal., 2014; You et al., 2014; Carlo et al., 2015; Kim et al.,2015; Chen et al., 2017; Kashani et al., 2017; Spaide et al.,2017). Other biomedical applications of DOCT have been,e.g. cilia-driven flow (Jonas et al., 2011; Huang and Choma,2015) and temporal deformation of tissues (Lawman etal., 2017b). The development of OCT technology is driven
by medical applications, and new modifications and algorithms are regularly published. These works often also
have high relevance outside biomedicine—in addition todeveloping the methods, they give advice on how experiments should be performed and data analyzed, and give agood general picture of the possibilities OCT offers. However, in this paper, we will concentrate on DOCT applications that are related to industrial flows. Here, the mostimportant applications have so far been microfluidics,
fouling, and rheology. Moreover, a few studies on turbulent flows can also be found.

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4. Microfluidics
Microfluidics is the science and technology of systems
that process or manipulate small amounts of fluids using
channels with dimensions of tens to hundreds of micrometers. In addition to using continuous flow, microfluidic
devices can also operate with droplets. The use of microfluidics offers a number of useful capabilities: Small sizeof samples, high sensitivity, low cost, and short analysis
time. Among the most important applications of microfluidic technologies is analysis. The goal is the developmentof a lab-on-a-chip for various applications. Here, all thefunctionalities of an entire laboratory are integrated
within a single microfluidic chip (Whitesides, 2006).
Microfluidic devices have also proven promising in certain types of manufacturing processes (Schoenitz et al.,2015). Droplet-based microfluidics (Shang et al., 2017),
e.g. can be used for synthesizing microcapsules, microparticles, and microfibers applicable, e.g. to pharmaceuticals, cosmetics, and foods.
Accurate control of microfluidic processes requires resolving ﬂow dynamics with micron-scale spatial resolution. Flow characterization in microﬂuidic channels andlab-on-a-chip devices is important not only for optimizing
the efﬁciency and design of devices but also for validating
models of computational ﬂuid dynamics (CFD). Althoughseveral techniques exist for both the direct and indirect
measurement of fluid velocity fields, there are only a few
measurement methods available that are non-invasive,
give both structural and velocity information, are able togive 1D, 2D or even 3D data, have micron-scale spatial
resolution, are applicable to opaque heterogeneous fluids,
and are able to provide reliable data very close to solidboundaries. DOCT is currently the only measurement
method which fulfills all of these requirements (Ahn etal., 2008; Huang and Choma, 2015).
The usefulness of DOCT velocity measurements has
been demonstrated for pressure-driven flows in microchannels of various sizes and geometries (Proskurin etal., 2003b; Bukowska et al., 2013; Lauri et. al., 2015). In
Cito et al. (2012), capillary-driven ﬂow, which is used

Fig. 748

widely in healthcare and diagnostic applications, wasstudied in a circular microchannel (see Fig. 7). So far, theﬂow behind the meniscus has been difficult to study experimentally. In that paper, DOCT was used to conﬁrm
the presence of a recirculation pattern in a moving meniscus predicted by numerical simulations. Such a measurement would be practically impossible with othermeasurement methods.
The capability of OCT to provide both structural andvelocity information makes it very attractive for analyzing the mixing of components. The microfluidic flows areusually laminar, and typically in the Stokes regime(Reynolds number Re << 1). In this regime, fluids mix
only via diffusion, which is a rather slow mechanism andmakes reactions within microfluidic devices harder toachieve. In Ahn et al. (2008), the effect of secondary
flows on mixing was studied with OCT inside a meandering square microchannel micromixer (see Fig. 8). Here,the flow fields and structural patterns of two-liquid mixing were measured, and it was found that the efficiency of
two-liquid mixing was rather low. Mixing could beclearly increased when air bubbles were injected into thesystem. OCT imaging revealed that air bubbles provoked
an alternating pair of counter-rotating and toroidal vortices which improved the two-liquid mixing. Those vortices were very similar to vortices created behind a moving
meniscus (see Fig. 7). Xi et al. (2004) used OCT to study
three representative microﬂuidic mixers: A Y channel
mixer, a 3D serpentine mixer, and a vortex mixer. It was
found that light-microscopy images lead to an overestimation of the mixing efﬁciency, an effect that was eliminated with OCT imaging. Overall, OCT was found to
signiﬁcantly improve the characterization of 3D micro­
ﬂuidic device structure and function.
Aqueous two-phase systems (ATPS) provide a highyield and high-purity process for the separation and purification of biomolecules. Since ATPS droplets can beobtained by phase separation between two immiscible
aqueous solutions of distinct polymers, monitoring thephase separation is critical to permit evaluation of the performance of an ATPS droplet-based microfluidic system.

a) Schematic of capillary-driven ﬂow in a microchannel. b) Contours of the y-component of the velocity
vector obtained with DOCT of a capillary-driven ﬂow of an aqueous suspension of polystyrene beads ina glass microchannel with a diameter of 200 μm. Notice that the pipe is slightly tilted to eliminate refraction of the DOCT beam on the pipe surface. Image taken with permission from Cito et al. (2012).

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Fig. 8a) A meandering square microchannel. The cross-sectional dimensions of the channel are
600 μm × 600 μm. b) On the left: Cross-sectional structural OCT image before mixing of water (black)and polystyrene suspension (bright). In the middle and on the right: Cross-sectional mixing patterns after the first loop for two Reynolds numbers. The OCT images were taken at the position shown with theshort dashed line in Figure c). The mixing efficiency is seen to be rather low. c) The measured flow velocity in the cross-plane direction on a symmetric plane cutting the loop into two halves. The cross-­
sectional velocity field shows a pair of counter-rotating vortices indicated in the inset. The OCT image
was taken at the dashed line seen at the bottom of the figure. Image taken with permission from Ahn etal. (2008).

Fig. 9Time-lapse OCT images of a rehydrating droplet. Cross-sectional (top) and volumetric (bottom) images
show the process of rehydration. Image taken with permission from Lee et al. (2016).

In Lee et al. (2016), OCT was used successfully to investigate real-time changes of the volumetric droplet morphology under various fluidic and rehydration conditionsof an ATPS system. The analysis was performed with 3D
OCT images of the droplets (see Fig. 9).
Manukyan et al. (2013) studied internal ﬂows in a drying sessile polymer dispersion droplet on hydrophilic andhydrophobic surfaces. Trantum et al. (2013) studied the“coffee ring effect” by tracking particle motion and accumulation in evaporating droplets. We have succesfully
performed similar measurements, as can be seen in
Fig. 1b.
Despite its apparent advantages, the number of OCT-­
related publications is still rather low in microfluidics, but
we expect this to change in the near future. This view is
supported by the fact that 3D printing is currently emerging strongly in microfluidics (Bhattacharjee et al., 2016).
3D printing enables the production of very complex

microfluidic devices. Their development will necessitate
the availability of highly detailed experimental data on
their microscopic flow conditions, which currently only
OCT can provide.

5. Fouling
The fouling of plant surfaces and the subsequent cleaning needed is a signiﬁcant and often also a costly problem
in various fields of the process industry (Bott, 1995; Dürr
and Thomason, 2010). Filters, membranes and heat exchangers are especially sensitive to it, but the accumulation of deposits can take place on any surface when theconditions are favorable. Fouling is also a problem in
micro­structured devices (Schoenitz et al., 2015).
Fouling begins at the instant a material comes into contact with a ﬂuid. During this period, the conditioning ﬁlm

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forms. The makeup and formation of this conditioning
ﬁlm directly relates to the further development of fouling.
Conditioning ﬁlm development is followed by a rapid accumulation of deposit growth. Next, a pseudo steady-state
period takes place when accumulation is almost constant.
Finally, the surface can become fouled to the point that it
can no longer be used effectively. Fouling is a function
controlled by a variety of parameters, including the geometry of the system, surface material, interface temperature, deposit temperature, free stream velocity, and ﬂuid
characteristics. While fouling is often a purely physicochemical process, biofilm formation is also a common
reason behind it (Kukulka et al., 2004).
At present, the mechanisms of fouling are not yet wellunderstood. Monitoring the development of the conditioning ﬁlm and the subsequent deposition process is thus
very important in order to understand and ultimately control fouling. However, deposit thickness, which is typically only a few tens of micrometers, is challenging tomeasure in situ. A review of the applications and principles of different methods of visual observation that havebeen applied to fouling (excluding OCT) can be found in
Shirazi et al. (2010).
Just as for microfluidics, OCT offers many advantages
for the analysis of fouling. It has a high spatial resolution,and in addition to providing structural information, it alsooffers information on flow conditions, which is highly
important for a deeper understanding of the fouling process. Moreover, as fouling processes are rather slow, theability of OCT to provide 3D data can be fully utilized.
For these reasons, OCT has been used in several works on
fouling. We will present a few examples below—a comprehensive review on the use of OCT in biofilm research
can be found in Wagner and Horn (2017).
The potential of OCT for fouling analysis is well manifested in Wagner et al. (2010), where the development of
biofilms in a funnel was studied with varying flow conditions (see Fig. 10). A heterogeneous structure was detected for the bioﬁlm cultivated in laminar conditions. In
turbulent conditions, the biofilm structure was found to
be more homogeneous, and the porosity was clearly lower.
The authors also noticed that confocal laser scanningmicro­scopy (CLMS) does not necessarily provide an
accurate representation of the bioﬁlm structure at themesoscale. Additionally, the typical characteristic parameters obtained from CLMS image stacks can largely differ
from those calculated from OCT images.
Bioﬁlm rheology was studied in situ in real time inBlauert et al. (2015). The bioﬁlms were grown in a ﬂow
cell set-up at low shear stress and their deformation wasstudied under high shear stress (see Fig. 11). The measurement set-up allowed the calculation of many rheological parameters such as shear modulus, Young’s modulus,
and strain; the values obtained were on a similar level to50

Fig. 10

OCT-images of biofilms developed on a funnel wallin laminar (a and b) and turbulent (c and d) flow conditions. The dimensions of the 3D images are
4 mm × 4 mm × 1.6 mm. The two red orthogonalslices underline the porous bioﬁlm structure. Imagesb) and d) represent xz-planes in the middle of the images. Spatial resolution is ca. 20 μm. Image taken withpermission from Wagner et al. (2010).

Fig. 11 OCT images of a biofilm in a shear stress experiment.
Flow is from left to right. a) The initial structure of
the biofilm. b) The structure two seconds after theflow started. The white line represents the initialstructure. Scale bar equals 250 mm. The spatial resolution is ca. 7 μm. Image taken with permission from
Blauert et al. (2015).

those in other studies. Moreover, viscoelasticity was analyzed in stress–strain experiments and was in good agreement with values reported in the literature.
Weiss et al. (2016) studied the localized and simultaneous measurement of bioﬁlm growth and local hydrodynamics in a microﬂuidic channel (see Fig. 12). In addition
to the fouling film, they measured the longitudinal ﬂow
velocity component parallel to the imaging beam, and thetransverse ﬂow velocity component perpendicular to theimaging beam with the DOCT autocorrelation function.
Based on the measured velocities, they were able to calculate the shear rates inside the ﬂow channel. They found aclear relation between the measured bioﬁlm structure andﬂow conditions as the bioﬁlm growth progressed.
Membrane technology has been applied in numerous
ﬁelds such as water/wastewater treatment and seawater

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Fig. 12 Cross-sectional image of channel morphology andcorresponding transverse and longitudinal ﬂow velocities in a (y, z)-plane. Flow direction is in the positive
x direction. The ﬁrst row shows the channel morphology, the second row shows the transverse ﬂow velocity
and the third row shows the longitudinal ﬂow velocity.
The columns show the data 24 and 48 hours after
starting the experiment. Image taken with permission
from Weiss et al. (2016).

desalination due to its capability for producing a vast
amount of water of high quality. However, membrane ﬁltration is inevitably associated with membrane fouling.
Gao et al. (2013) used OCT to characterize the velocity
proﬁles normal to the membrane surfaces, inside a unit
cell of the spacer in a modiﬁed membrane ﬁltration module. The orientation of the spacer was varied with respect
to the bulk ﬂow direction. A series of DOCT images
demonstrated the subtle interactions between the ﬂuid andthe spacer ﬁlaments; these characterization results werethen used to interpret the performance variation of the reverse osmosis process with the same spacer conﬁgurations. In Gao et al. (2014), DOCT was applied to theanalysis of fouling in a laboratory-scale membrane ﬁltration system. Both the growth of the fouling layer and thevelocity proﬁles of the ﬂuid ﬁeld were measured as illustrated in Fig. 13. The characterization results revealed forthe ﬁrst time the evolution of the morphology of the cakelayer under different microhydrodynamic environments.
This study demonstrated that DOCT-based characterization is a powerful tool for investigating the dynamic processes during membrane fouling. More recent membrane
fouling studies utilizing OCT can be found in Han et al.
(2018) and Park et al. (2018).
OCT is the emerging imaging technique of the last decade in fouling. It enables a major step forward in bioﬁlm
research as it allows the monitoring of the fouling ﬁlm
structure in real time in situ under operational conditions.
As OCT—unlike any competing measurement technique—also gives information on the flow, it facilitates

Fig. 13 DOCT images of fouling (2 g/l bentonite microparticles) in a channel with a spacer. The primarycross-section scanned by DOCT is parallel to the direction of the bulk ﬂow, as indicated by the red areain the upper left schematic. The images obtained in the primary cross-section include the following: a)y-component of the velocity vectors in the channel at t = 0 min, b) the structural image in the channel at
t = 0 min, and c) the structural image in the channel at t = 60 min. The fouling layer can be seen clearlyon the top of the membrane. The direction of the bulk ﬂow is denoted by the arrows. The membranesurface is indicated by the dashed-dotted curve, and the filament cross-sections are circled with dashedlines. Image taken with permission from Gao et al. (2014).

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the analysis of the ﬂuid-structure interaction of foulingsystems on a micron scale. Furthermore, the OCT data
can be combined with numerical modeling by extracting
structural templates from the biofilm images to be utilized as boundary conditions to solve Navier-Stokes andmass-transport equations (Li et al., 2016).

6. Rheology
The success of a wide range of commercial products
and industrial processes depends on meeting specific flow
requirements. Architectural and industrial coatings,
molded plastics, adhesives, personal care products andcosmetics, inks, cement, drilling muds, ceramic slips, solder pastes, papermaking suspensions, foodstuffs, andmedicines are examples of complex fluids whose successful processing and commercial viability depends on having the “right” rheological properties (Eley, 2005).
Rheology is defined as the study of the deformation ofmatter, primarily in the liquid state, but also as ‘soft solids’ or solids under conditions in which they respond witha plastic flow rather than deforming elastically in responseto an applied force. Rheology generally accounts for the
behavior of fluids by characterizing relations between
stresses, strains and strain rates either by experiments orby theoretical analysis. The experiments are typically
performed either in oscillatory or continuous shearing
conditions. In the former case, one obtains the viscoelastic properties of the medium, such as dynamic moduli, asa function of frequency and amplitude, and in the latter
case, one obtains the viscosity as a function of shear
stress or shear rate (Barrat and Hansen, 2003).
The rheology of simple fluids is rather straightforward
and well understood from a practical point of view. Theirflow behavior can be characterized either by a single
temperature-dependent coefficient of viscosity (Newtonian fluids) or by relatively simple relations between the

stress and the strain rate (non-Newtonian fluids). Furthermore, these material properties can be directly measured
using conventional rheological methods where the interpretation of the measured data is usually based on an assumed flow behavior of the fluid. These simplifying
assumptions, such as Couette-type flow and no-slip
boundary condition, are reasonable for simple Newtonianand non-Newtonian fluids. Unfortunately, only a small
group of fluids exhibit such simple behavior.
The actual observed flow behavior of many practically
relevant fluids is very complicated and shows, e.g. hysteresis, thixotropy, shear banding, unstable behavior, andspontaneous formation of a lubrication/depletion layer
close to solid boundaries (Barnes, 1995). The mechanisms
underlying these complicated and poorly understood phenomena in these complex fluids are related to the presenceof a mesoscopic length scale which is caused by the internal structure of the material. This is the case, e.g. forpolymer/fiber suspensions for which the consistency, orientation, elongation, and flocculation of the polymers/fibers considerably affect their bulk and boundary layer
behavior.
The intricate rheology of complex fluids, coupled withthe optical turbidity and measurement difficulties withconventional rheometric techniques, render them challenging to study in conditions relevant to real processing.
To date, this has been mainly due to the lack of experimental techniques that would allow the direct measurement of flows and internal structures of complex, opaque
fluids especially in the immediate vicinity of the wall
(typically, within a few tens of micrometers from thewall). OCT now provides a remedy for this long-standing
grievance (Haavisto et al., 2014; Malm, 2015).
Rheo-OCT is a measurement set-up (Fig. 14) where
OCT has been combined with a conventional rheologicaldevice such as a rotational rheometer (Harvey and Waigh,2011), a capillary/pipe viscometer (Lauri et al., 2011b), or
an elongational rheometer (Dufour et al., 2005). It allows

Fig. 14 a) A set-up of Rheo-OCT—Telesto I SD-OCT combined with a TA instruments rheometer with a plateplate geometry. The OCT imaging direction can be changed by using a transparent upper/lower plate. b)
A schematic of a Rheo-OCT set-up for a concentric-cylinder geometry (bob and cup) with transparent
outer geometry.

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Fig. 15 a) Opaque margarine with wall slip. b) Transparent polyacrylamide particles in water (0.1 % w/w) withshear banding. In both cases, a rotational plate-plate geometry was used. Image taken with permission
from Harvey and Waigh (2011).

Fig. 16 Different flow regimes for 1 % microfibrillated cellulose suspension in a concentric-cylinder rotationalrheometer: a) Complete slip on the stationary wall. b) Slip and rolling flocs on both walls. c) Slip flow
and rolling flocs on the moving wall. The gap is 1.0 mm. The average velocity profiles are marked witha white line. Image taken with permission from Haavisto et al. (2015a).

the use of truthful flow behavior based on direct experimental observation instead of the often unrealistic andfallacious assumed flow behavior as the basis for interpreting and analyzing the results from rheometric measurements. Rheo-OCT captures various perturbative
effects encountered in rheological experiments such as
defective sample loading, wall depletion, slip flow, andshear banding (Harvey and Waigh, 2011; Jaradat et al.,2012; Saarinen et al., 2014; Malm et al., 2014). For examples see Figs. 15, 16 and 17.
An important possibility afforded by Rheo-OCT is local
rheological measurements, i.e. calculating the local viscosities in the fluid using the formulaμ  y 

τ ( y)γ  y ,(4)where γ  y  dv / dy is the local shear rate derived fromthe measured velocity proﬁle v(y), and τ(y) is the local
shear stress obtained either from a pressure difference
measurement (capillary or pipe ﬂow geometry) or from atorque measurement (rotational rheometer). Rheo-OCT
can, e.g. be used to eliminate the effect of wall slip on therheological analysis by calculating the shear rate in the

middle region of the rheometer from the measured velocity profile (Haavisto et al., 2015a). Note that Rheo-OCT
can also be used for quantitative rheological analysis insuch a case where the measurement depth of OCT does
not span the whole flow geometry. In Haavisto et al.
(2015b), a flow of water in a pipe with a diameter of
8.6 mm was used to demonstrate the use of DOCT in
combination with pressure loss measurement for determining the viscosity of water in both laminar and turbulent flow. The viscosity was calculated from the formula
μOCT ΔPD,
4LγOCT(5)where L is the pipe length, D is the pipe diameter, ΔP isthe pressure loss, and γOCT is the shear rate of the fluid in
the vicinity of the pipe wall. As Fig. 18 shows, the accuracy of the measurement is very good in the laminarregion, and reasonably good in the turbulent region, considering the low viscosity of the water. A corresponding
rheological analysis based on velocity profiling and equations (4) and (5) was performed successfully in Lauri etal. (2017) for an aqueous suspension of microfibrillated
cellulose with a concentration of 0.5 wt%.

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Fig. 17 a) Rheogram of an oscillatory experiment for a 0.5 % MFC + 0.11 % CMC suspension in a concentric-cylinder rheometer geometry (gap is 1.0 mm). b) Velocity profile in the gap in the linear viscoelastic (LVE) region (strain 0.78 %). c) Velocity profile in the gap outside the LVE region (strain 12 %). The
frequency is 1.0 Hz, and the maximum speeds of the surface of the moving cylinder are thus 0.05 and0.75 mm/s. In both cases, the velocity profile was measured during the cycle when the absolute value ofthe shear rate was highest. The stationary wall is at 0.0 mm and the moving wall at 1.0 mm. With thelower strain, the velocity profiles are approximately linear close to the stationary wall, but they are
somewhat asymmetric. There is some shear banding and slip flow at the moving wall. With the higher
strain, the velocity profiles are approximately symmetric. There is shear banding and strong slip flow onboth walls. The velocity profile is linear in the middle of the gap. Notice that the velocity profiles were
calculated from successive structural 2D images (Haavisto, 2018).

Fig. 18 Viscosity of water measured with a combination ofpressure loss measurement and DOCT. The dash-­dotted line shows the theoretical viscosity of thewater. The dashed line shows the onset point of turbulence, Re ~ 2300. Image taken with permission from
Haavisto et al. (2015b).

When the size of the ﬂow geometry exceeds the maximum measuring distance of OCT, the measurements canalso be performed by hybrid multi-scale velocimetry.
Here OCT measurements are complemented (see Fig. 19)
by measuring the outer ﬂow velocity proﬁle with, e.g.
UVP or MRI techniques (Salmela et al., 2013; Haavisto etal., 2017; Kataja et al., 2017). The hybrid multi-scale
velocimetry can provide very detailed experimental infor-

54

mation on the rheology of various complex fluids in awide range of flow rates. It enables not only the analysisof the macroscopic (bulk) behavior of the working fluids,
but also gives simultaneous information on their walllayer dynamics, both of which are needed for analyzing
and solving practical fluid-flow-related problems (seeFig. 20). In particular, wall layer dynamics, inaccessible
with UVP/MRI but obtained with DOCT, have great importance for understanding the flow behavior of complex
fluids.
Microrheology is a relatively new rheology technique
where the local and bulk mechanical properties of a complex fluid are extracted from the motion of probe particles
embedded within it (Waigh, 2016). In passive microrheology, particles are forced by thermal fluctuations andlinear viscoelasticity is probed, whereas active microrheology involves forcing probes externally and can be extended out of equilibrium to the nonlinear regime. The
advantages of microrheology are: The very small size ofthe samples, the capability to measure rheological properties with high frequencies, and the ability to study materials such as polymer solutions with probes spanning someof the characteristic microscopic length scales (e.g. approaching the inter-chain separation or mesh size of gels).
Due to its ability to analyze opaque materials, the wide
frequency range, and relatively high resolution, DOCT isa very promising tool for microrheology (Sharma et al.,2008; Blackmon et al., 2016; Chu et al., 2016).

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Fig. 19 a) Velocity profiles of 1.0 % microfibrillated suspensions in a pipe flow combined from DOCT and UVP
measurements. The labels of different profiles give the total low rate [ml/s]. The vertical dashed line indicates the centerline of the tube. b) The velocity values from DOCT, appearing in a) as dark symbols
near the wall, shown in more detail. The labels of different profiles give the wall shear stress [Pa]. Image taken with permission from Kataja et al. (2017).

Fig. 20 a)–b) Measured viscosity μ(y) in a pipe (D = 19 mm) flow as a function of the distance y from the tube
wall for a) 0.4 % bleached softwood kraft (BSK), calculated using DOCT and UVP velocity profiles,
and b) for 0.4 % microfibrillated cellulose (MFC) calculated using DOCT and MRI velocity profiles.
The wall layer, where there appears to be a consistency profile, has been indicated with a verticaldashed line. c)–d) Viscosity vs. shear rate for the c) BSK as measured by UVP (circles) and DOCT
(crosses), and d) for MFC as measured by MRI (circles) and DOCT (crosses). The DOCT data points
originate from the wall layer, and the UVP/MRI data from the inner parts of the pipe, i.e. from theyielding and plug regions. Additionally, the power law fits to the UVP/MRI data, and reference data for
BSK obtained from Silveira et al. (2002) are shown. Image taken with permission from Haavisto et al.
(2017).

DOCT obviously offers great potential for rheologicalanalysis. Moreover, combining DOCT data with structural information, also given by DOCT, opens truly unprecedented research prospects for the study of therheology of opaque ﬂuids (Koponen et al., 2018). The extension to polarization sensitivity makes it possible for
OCT to also study birefringent materials (Park et al.,
2003; Ju et al., 2013).

7. Turbulent flows
Turbulence is a flow regime in fluid dynamics characterized by chaotic changes in pressure and flow velocity.
It is in contrast to a laminar flow regime, which occurs
when a fluid flows in parallel layers, with only diffusive
disruption between those layers. In general terms, in turbulent flow, unsteady vortices of many sizes appear andinteract with each other. This increases the viscous shear

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Fig. 21 Stationary velocity proﬁles taken across a T-shaped junction. a) Initial ﬂow distribution at the end of theinlet arm. b) Velocity ﬂow distribution across the T junction. c), d) Turbulent ﬂow proﬁles in the left
and right outlet arms, respectively. The red and blue colors introduce minimum and maximum rates ofthe velocity of ﬂow, respectively. e) The T-shaped micro vessel is 1.8 mm in diameter. Image taken withpermission from Bonesi et al. (2007).

stresses and the energy consumption, e.g. in pipe flow.
Turbulence is involved in many processes in the processindustry. It is not only a nuisance, but turbulence also has
the ability to mix and transport species, momentum, andenergy much faster than is done by molecular diffusion
and is therefore employed in, for example, chemical reactors to make them perform better. It is of great importanceto have a detailed understanding of the turbulence whenindustrial processes and devices are developed. Typically,
this work is done with a combination of computational
f luid dynamics and experiments (Batchelor, 2000;
Hjertager et al., 2003).
DOCT is in principle capable of performing measurements with a high enough temporal and spatial resolution
to visualize the turbulent eddies. However, the measurable velocity region is rather limited for the most popular
realization of DOCT, the FD-OCT, and phase wrapping isoften a problem. As discussed above, in laminar flows,
even then it is possible to retrieve the actual velocity valueby phase-unwrapping methods, if the phase wrapping is
not too big. This is, however, problematic in turbulent
flows, as the velocity fluctuations can exceed the measurable velocity region considerably. Moreover, the basic
measurement set-ups of DOCT see only one velocity
component, whereas turbulence is always a 3D phenomenon. While there are various ways to improve the method
to measure two or even three velocity components simultaneously (as discussed above), to this day they appear not
to have been applied for the quantitative analysis of turbulence.
Despite its current limitations, a few studies can befound where DOCT has been applied for turbulent flow
analysis—mainly for obtaining temporally averaged profiles. Bonesi et al. (2007) used DOCT for monitoring

56

turbulent velocity proﬁles in micro-channels. They observed, e.g. the transition from laminar to turbulent ﬂow
velocity proﬁles in a T-shaped micro-vessel junction (seeFig. 21). Villey et al. (2010) used TD-OCT and a zerocrossing algorithm to obtain velocity maps in a 1.0-mm
capillary free from phase aliasing or other common OCT
artifacts. In Haavisto et al. (2017), DOCT was combinedwith MRI to measure the mean velocity profiles of turbulent flow of pure water and a xanthan gum solution in a
19-mm pipe. The combined velocity profiles obtained
were in excellent agreement with their theoretical counterparts (see Fig. 22).
The flow instabilities of solutions of high molecularweight DNA were investigated with DOCT in a parallel
plate rheometer in Malm and Waigh (2017). At lower
DNA concentrations and low shear rates, the velocity
fluctuations were well described by Gaussian functions,and the velocity gradient was uniform across the rheometer gap, which is expected for Newtonian flows. As the
DNA concentration and shear rate were increased, there
was a stable wall slip regime followed by an evolving wall
slip regime which was finally followed by the onset ofelastic turbulence (see Fig. 23).

8. Some limitations of OCT
Just like all measurement methods, OCT also has its
limitations. The penetration depth, even in optimal conditions, may be too low for some applications and especiallyin highly scattering materials, it can be very limited. In
Aigner et al. (2014), e.g. the flow characteristics ofglass-fiber-reinforced polymers were directly analyzed ina real production process for an elongational rheometry.

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Fig. 22 Turbulent velocity profiles of a) pure water and b) xanthan gum solution measured with DOCT and
MRI in a pipe with a diameter of 19 mm in the dimensionless variables u+ and y+. The dashed line andthe dash-dotted line show the theoretical linear viscous sublayer profile and the logarithmic law of thewall, respectively. Due to the drag reduction of the xanthan gum, the MRI data exceed the logarithmiclaw of the wall at y+ ≅ 15 before becoming parallel to it. Image taken with permission from Haavisto etal. (2017).

Fig. 23 a) Power spectral density (PSD) of the velocity fluctuations of elastic turbulence measured in a plateplate rheometer for three different concentrations of low salt DNA solutions, with an applied shear rateof 60 s –1. Two separate power law behaviors are observed. b) Color map of shear-normalized velocity as
a function of the normalized distance across the rheometer gap and time after the startup of shear witha shear rate of 60 s –1. Intermittent fluctuations in the velocity are observed. Note that elastic turbulence
is a fresh topic of research, and a theoretical explanation for the observed peculiar behavior of PSD—it
is clearly lowest at the intermediate concentration—does not yet exist. Image taken with permission
from Malm and Waigh (2017).

Because of air bubbles and the high consistency of scattering glass fibers, DOCT measurements turned out to bevery difficult. In its basic form, DOCT gives only one
component of the velocity vector. While it is possible toget more components with special techniques, these are
not necessarily easy to perform. Fortunately, one velocity
component is often enough for a meaningful flow analysis. Moreover, flow field analysis can often be performed
for structural images to obtain two or even three velocity
components. OCT needs optical access to the measured
target, and the medium has to carry light-scattering particles. Obviously, this may limit its use for certain applications. Particles that are optically too dense can even block
the penetration of the OCT signal deeper into the medium.
This produces straight dark lines in the OCT images.
Multiple scattering in the studied medium reduces image

contrast and resolution, and distorts the measured velocity
profiles, especially in highly scattering media (Kalkman
et al., 2010; Lauri et al., 2011a). This effect can be decreased by using complex averaging. The conventional
OCT averaging method (“magnitude averaging”) calculates the magnitude-squared Fourier-transformed spectral
fringes before averaging and thus is insensitive to changes
in phase. Another option is to average the complex-­
valued, Fourier-transformed, spectral-fringe signals before calculating the magnitude. Complex averaging
increases the dynamic range by reducing the noise floor
while maintaining similar signal values when comparedto magnitude averaging (Thrane et al., 2017).

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9. Conclusions
OCT is obviously a very attractive tool for structuraland flow analysis. However, the number of industrial applications of DOCT in structural and flow analysis is stillrather limited. This is probably due to the thus far small
number of DOCT devices available outside the medical
field. There are now commercial, general-purpose DOCT
devices available, but their prices are still rather high,which limits the spread of DOCT technology to other applications. Nevertheless, the many advantages of DOCT
technology, i.e. high resolution, high speed, ability towork with opaque fluids, and simultaneous detection ofvelocities and structure are a combination that cannot be
obtained through other measurement methods. Moreover,the existing commercial devices are very compact andportable, which makes their application easy for new
problems. So, although DOCT activities are still dominated by various biomedical applications, we expect theuse of DOCT to increase in numerous industrial ﬁelds inthe near future.

Acknowledgements
The Academy of Finland (project 288694) is gratefully
acknowledged for supporting this work. This project hasreceived funding also from the European Union’s Horizon
2020 research and innovation programme under grant
agreement No 713475 (Spinnova Ltd). We also want tothank Mr. Juha Salmela and Dr. Markko Myllys for taking the OCT image Fig. 1b), and Mr. Roope Lehto for its
visualization.

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Authors’ Short Biographies
Antti Koponen
Antti Koponen prepared a Ph.D. thesis on simulations of fluid flow in porous media
and obtained his Ph.D. degree in 1998 from the University of Jyväskylä (Finland). In
2003, Koponen obtained a docentship in applied physics at the University of Jyväskylä.
Principal scientist Antti Koponen has worked at VTT Technical Research Centre of Finland Ltd. since 2001. His work focuses on the rheology of complex fluids and flows incomplex geometries. Recently, Koponen has worked extensively with the novel OCTbased rheological analysis of complex fluids (Rheo-OCT).

Sanna Haavisto
Sanna Haavisto is currently a Product Development Specialist at Spinnova Ltd., developing environmentally friendly fibre technology. She is also finalizing her PhD at the
University of Jyväskylä where she obtained her master’s degree (industrial physics) in2004. Until 2014, Sanna Haavisto was employed at VTT Technical Research Centre of
Finland as a senior scientist. Her work was mainly focused on experimental research of
the flow properties and rheology of complex fluids, including novel OCT-based rheological measurements (Rheo-OCT).

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KONA Powder and Particle Journal No. 37 (2020) 64–84/Doi:10.14356/kona.2020005

Review Paper

Microbial Aerosols: Sources, Properties, Health Effects,
Exposure Assessment—A Review †Rafał L. Górny
1

Laboratory of Biohazards, Department of Chemical, Aerosol and Biological Hazards,
Central Institute for Labour Protection – National Research Institute, Poland

Abstract
Microorganisms are ubiquitous in the environment. Wherever their sources are present, the particles can bereleased into the air forming microbiological aerosols. Although most of their particles cause no harm to the
exposed individuals, some of their propagules may have infectious or allergenic potential and may carry toxic or
irritant substances and components. Their inhalation usually poses a significant health risk and is responsible fornumerous adverse outcomes, from allergic reactions, infections and toxic responses to various nonspecificsymptoms. This review article provides fundamental background information on the role of microorganisms in
the environment, defines and characterizes environmental sources of microbial aerosols, describes microbial
abilities for airborne transport and comments on their role in atmospheric processes, discusses their physical andbiological characteristics which result in adverse health outcomes observed in exposed individuals. The paper
characterizes comprehensively numerous sampling and analysis techniques involved in the quantitative andqualitative evaluation of microbial aerosols together with their practical applications, presents strategies appliedin the assessment of harmful microbial agents formed by bioaerosols, explains the ways of creating hygienic
standards (understood here as reference/threshold limits) for microbiological aerosols conditioned by both medical
and environmental determinants, and comments on their usefulness in the control and protection of environmentand health.
Keywords: microbial aerosols, sources, properties, health effects, analysis, exposure assessment

1. Microorganisms in the environment
From among different organisms, microbes are thosethat dominate earth habitats. Microorganisms are not only
omnipresent but they are essential to all other life forms.
They are a primary source for nutrients and the major recyclers of dead matter back to available organic form.
Along with all other animals and plants, the human condition is deeply affected by microbes. Compared to thehuman population (~6 × 109), the population of, e.g. terrestrial ecosystem bacteria is significantly higher (> 1030).
The human body is inhabited by more bacterial cells (1014)
than its own cells (1013). Being aware of these populationdifferences and using the most advanced analytical techniques, it is possible to recognize and characterize notmore than 9 % of the total microbial species only (i.e.
~158,760 out of ~1,830,000 including viruses, bacteria,

†
1

64

Received 15 May 2018; Accepted 16 January 2019
J-STAGE Advance published online 21 March 2019
Czerniakowska 16 Street, 00-701 Warsaw, Poland
E-mail: ragor@ciop.pl
TEL: +48-22-623-4677 FAX: +48-22-623-3693

algae, fungi, lichen, and protozoa). Microorganisms are
essential to human survival, health and disease, and hence
their environmental abundance and diversity are of greatpractical importance (Bisen et al., 2012). Since the 1970s,
enormous analytical progress has moved us from the ageof phylogenetic analyses (that take into account physicaland metabolic characteristics of organisms) to the molecular future, which also determines evolutionary relationships. A look at the world of organisms through theirgenomes has reformulated our perception of the natural
system. Life’s diversity seen as comprising 3 domains, i.e.
bacteria, archaea and eucarya, has been dramaticallybroadened taking into account both community and ecosystem interrelations (Hug et al., 2016; Whose and Fox,
1977; Woese et al., 1990). The genome-based approach allowed building the tree of life that today includes 92
named bacterial and 26 archaeal phyla as well as 5 eukaryotic supergroups. Despite these impressive numbers, however, the functional diversities of classified organisms and,what is even more important, their influence on the immunological system of exposed individuals in the form ofan ‘airborne cocktail of particles’ remain so far unknown.

Copyright © 2020 The Author. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Rafał L. Górny / KONA Powder and Particle Journal No. 37 (2020) 64–84

2. Sources of microbial aerosols and factors
influencing their environmental spread
Microbial aerosols (i.e. airborne particles of microbiological origin) are usually naturally present in the environment. They are ubiquitous both indoors and outdoors.
Their environmental presence is associated with different
geographic regions, climate zones, continents or populations of plants and animals. Their major outdoor sources
are located on the earth surfaces and are formed by continental (soils, plants including crops and forests, wetlands,
deserts, land ice, urban, etc.) as well as natural and anthropogenic water reservoirs. As an example, Table 1 reveals approximate bacterial concentrations in near-surface
air of various ecosystems (Burrows et al., 2009). Terrestrial
ecosystems (e.g. cultivated soils, plant surfaces, mineralincluding desert dusts) are usually the most productive inthis context.
The comparison of the global bioaerosol emission between terrestrial and water ecosystems is difficult due tolimited knowledge of the latter. There are several processes that favor microbial particle release from the water
including eruption of rising bubbles through the sea-­
surface microlayer or wind ejection of spume drops fromthe breaking wave crest. Nevertheless, terrestrial emission
processes are usually much more productive than those of
aquatic sources (Aller et al., 2005; Blanchard et al., 1981;
Elbert et al., 2007; Hultin et al., 2011; Veron, 2015).
Microbial aerosol sources are also widespread in indoor
environments. They can derive from industrial and non-­industrial settings and differ significantly in terms of theiremission efficiency. In the first case, the most effective
occupational aerosolization processes (being responsible
for microbial aerosol concentrations up to 1012 cfu m–3)

Table 1 Total bacterial concentrations in near-surface
air of various ecosystems.
Ecosystem

The highest estimate [# m–3]

Coastal

1.3 × 105Crops

1.7 × 105

Deserts

3.8 × 104

Forests

8.8 × 104

Grasslands

8.4 × 105

Land ice

1 × 104Seas

8 × 104

Shrubs

8.4 × 105

Tundra5.6 × 104

Wetlands

8 × 105

Urban

9.2 × 105

are: silo loading/unloading, animal feeding in broiler
houses, piggeries as well as different dust-releasing tasks
in composting plants, granaries, animal food stores, malthouses, and reloading of stored moldy raw materials(Dutkiewicz and Jabłoński, 1989). Against this background, non-industrial indoor sources are less productive
and usually closely connected with the presence andphysical activity of humans (including numerous physiological processes such as breathing, talking, sneezing,
coughing or scratching as well as movement and dust, including microbial dust residues, resuspension). Such typesof emissions are usually able to create microbial concentrations of about 103 cfu m–3; however, some chamber bioaerosol studies revealed that even one person under seatedconditions is able to release up to 106 biological aerosol
particulates per hour into the air and the origin of such a
microbial cloud can be assigned to the individual thatemits it (Bhangar et al., 2016; Meadow et al., 2015). Also,
indoor water reservoirs such as aquariums, toilets, sinks
or even washing machines may load the air with highnumbers of both saprophytic and pathogenic microorganisms. Such emissions (reaching usually 103–104 cfu m–3)
may result not only in contamination of surrounding surfaces but pose a real threat to exposed individuals throughinhalation of different pathogens (including Bacillus, Aeromonas, Campylobacter, Clostridium, Escherichia, Klebsiella, Staphylococcus, Salmonella, Pseudomonas, Serratia,
Shigella bacterial genera and molds) (Barker and Jones,
2005; Best et al., 2012; Getto et al., 2011; Lai et al., 2018;
O’Toole et al., 2009; Pastuszka et al., 1996; Stapleton etal., 2013).
As the locations of microbial aerosol sources are (in an
obvious way) not spatially uniformly distributed and theirproductivity differs, both temporal (including diurnal,
seasonal, and annual) and environmental changes in bioaerosol structure are observed. Moreover, microbial
sources do not release bioaerosol particles continuously as
numerous physical (temperature, relative humidity, availability of water and nutrients, radiation, environmental
oxygen presence, etc.) and biological (individual species
properties, growth in microbial consortium) factors influence such a process. Hence, all of the above results influctuations of quantitative and qualitative composition of
airborne microorganisms (Burge, 1995; Lighthart andStetzenbach, 1994; Macher, 1999).
From the above-listed physical factors, one of the major
factors is temperature. It directly affects the rate of microbial metabolism, reproduction, and culturability. It also
correlates with a number of important meteorological andclimatic variables (e.g. air turbulence, time of day andseason) that may affect concentrations of microorganisms
in the air. In turn, the role of relative humidity as a factor
influencing microbial aerosol is often emphasized in theliterature; however, the empirical data do not adequately

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define the range of environmental conditions that are favorable for this parameter. The environmental results ofthe bacterial aerosol test are ambiguous and the relative
humidity is assessed as marginal and once significant(Krzysztofik et al., 1994; Nevalainen, 1989; Pasanen et al.,2000). For both of these parameters, however, their proper
environmental levels are strictly connected with specificmicrobial strains determining the issues of survival in theair, (if deposited) conditioning the possibilities to colonize
the surfaces and as such should be individually considered (Burrows et al., 2009; Stetzenbach, 1997).
Regarding radiation, each type acts destructively on
microbial particles. Sunlight has a known bactericidal effect due to the part of the spectrum that includes short,violet and ultraviolet waves. For example, the vegetative
bacterial forms (including Mycobacterium tuberculosis)
die after several hours of irradiation, especially in thesummer. Also, artificial (xenon) radiation with the same
wavelength spectrum as solar light reduces the quantityof viable microorganisms (which was shown in laboratory
experiments with Escherichia coli or Serratia marcescens
aerosols) (Carroll et al., 2016; Hurst, 1997). Ultraviolet
rays (with wavelengths from 250 nm to 280 nm), just asother high-energy radiation types (such as gamma and Xrays), penetrate into microbial cells and induce a numberof reactions, including those with free radicals. Such processes damage the structure of nucleic acids, proteins,carbohydrates, lipids, and cell membranes, leading tochanges in cell functioning and/or death. The influence oflong-wave radiation (infrared, microwaves) carrying alower energy potential is usually reduced to its impact on
temperature and by that on water relations in the cell;
however, the direct (‘microwave’) effect on nucleic acids
was also observed (Cox and Wathes, 1995; Górny et al.,2007).
Microorganisms have different requirements for the atmospheric presence (or absence) of oxygen. Depending on
the degree of oxygen tolerance, they are divided into fourgroups: absolute or relative anaerobes, microaerophiles(tolerant anaerobes), and absolute aerobes. The influenceof oxygen on microbial aerosols may reveal both toxic
and protective effects. The positive effect of oxygen is hypothesized based on laboratory experiments with the suppression of activity of toxic substances, whereas the
toxicity is due to its enzymatic reduction inside the cell tohydrogen peroxide and toxic free radicals (O2–). Aerobes
and relative anaerobes are protected against these products by the presence of superoxide dismutase or catalase
enzymes. The oxygen toxicity to the microbial cell depends on the degree of cell hydration and is observed at a
relative humidity below 65–70 % when the oxygen content is about 30 % (further increase in oxygen content nolonger produces an additional toxic effect) (Cox andWathes, 1995; Carroll et al., 2016).

66

3. Presence and transport of microbial
particles in the atmosphere
Wherever microbial sources are present, these particles
can be released into the air forming biological aerosols.
They can be both actively (e.g. by breathing, coughing) andpassively (through meteorological processes) emitted to theatmosphere from almost all surfaces (Jones and Harrison,2004). When airborne, microbial particles (as their non-­biological counterparts) are primarily carried by air
streams. In such a state, they may be present solely as microbial particles, may form aggregates with both biologicaland non-biological particles or simply be attached to (usually bigger) dust particles or fibers. The sizes of the formed
structures condition the aerodynamic behavior influencing
their half-life times (see below). Microbial particles are not‘ideal’ spherical and smooth structures, and in the overwhelming majority of cases are asymmetric with rough or
porous surfaces. All this makes the physical dimensions of
microbial particles different from their aerodynamic diameters influencing their stability in the air. Independentof the air turbulence (that are almost always present in theenvironment), microbial particles are constantly removed
from the air due to gravitational sedimentation, interception, impaction or precipitation processes, ending in bothcases in deposition on surfaces as ‘free’ microbial particles
or inside water droplets or ice crystals (Górny et al., 2017;
Gregory, 1973; Lacey, 1991; Madelin and Johnson, 1992;
Reponen et al., 1998, 2001; Tong and Lighthart, 2000).
Dry deposition plays the major role in the removal of
airborne microbial particles with diameters bigger than
10 μm; however, they rarely penetrate deeper into the respiratory tract. For microbial particles, important fromthe human health perspective (i.e. inhalable particulates
below 10 μm in diameter), ‘wet’ processes of bioaerosol
sweeping from the atmosphere are of a fundamental importance (Després et al., 2012). Due to them, such microbial particles are usually present in large numbers in the
troposphere (especially in the planetary boundary layer);
however, both their vertical (beyond the troposphere) andhorizontal (between environments, e.g. land and water,
continents or climate zones) long-range transport is possible and observed. Such transport over geographic barriers
supports dissemination of reproductive structures and bythat allows also the transfer of genetic material within
micro­biocenosis and between the microbiocenoses of different ecosystems. In many aspects, the environmental
transport of microbial propagules resembles those of dust
particles (e.g. Bovallius et al., 1978; Jeon et al., 2011;
Prospero et al., 2005), and over the last two decades,
many models have been created to precisely describe thecomplexity of this phenomenon (e.g. Ganio et al., 1995;
Helbig et al., 2004; Jarosz et al., 2004; Skelsey et al.,2008; Sofiev et al., 2006; Wilkinson et al., 2012).

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4. Microbial contribution to the atmosphericprocesses
When microbial aerosols are released into the air, they
can be transported between different ecosystems and are
influenced during this process by climate and seasonalchanges, life cycles, aging, chemical and physical interactions, and variations in microbial populations (Fröhlich-­
Nowoisky et al., 2016; Huffman et al., 2013; Sesartic etal., 2012). Microbial particles already in the airborne state
above ground may undergo frontal uplift, convection or
further turbulence, driving them even above the troposphere (Lindemann et al., 1982). The presence of microbial particles has already been confirmed at very highaltitudes reaching into the stratosphere (Rogers andMeier, 1936; Shivaji et al., 2006; Wainwright et al., 2003)
and mesosphere (Imshenetsky et al., 1978), and by thatmicrobial particulates may affect numerous atmosphericprocesses. They may act as cloud condensation nuclei(CCN) or ice nuclei (IN) responsible for the formation ofcloud droplets, ice crystals and precipitation, and thus influence the hydrological cycle and climate. Biological
CCN or IN may be present as both viable and non-viablemicrobial cells and conidia, their structural fragments anddetached macromolecules. For example, many gram-­
negative bacterial species from Pseudomonas, Pantoea,
and Xanthomonas genera act as IN through both theircells and outer membrane proteins. The bacterium Pseudomonas syringae is now available as the commercial
product for use in cloud seeding (e.g. Franc and Demott,1998; Fröhlich-Nowoisky et al., 2016; Hill et al., 2014;
Huffman et al., 2013; Kozloff et al., 1991; Lundheim andZachariassen, 1999; Möhler et al., 2007; O’Sullivan et al.,2016; Pouleur et al., 1992; Šantl-Temkiv et al., 2015; Sattler
et al., 2001).
For both viable and non-viable microbial particles, theatmosphere in not only the environment allows theirtransport but influences and modifies their basic physical,
chemical, and biological features as well. For example,
the atmospheric fragmentation of microbial particles may
affect their transport and abilities to serve as CCN or IN(Diehl et al., 2001; Morris et al., 2004). Also, coating formation on microbial particles by organic and inorganic
materials may influence their basic biological features andreactivity. Certain chemical reactions that influence primary structural and functional cell compounds may reorganize both the molecular arrangement and immunologicalreactivity of microbial aerosol particles (e.g. ozone andnitric oxide reveal the ability to increase the allergenicity
of airborne mold conidia proteins) (Gruijthuijsen et al.,2006; Lang-Yona et al., 2016). Although the air is themain environment for the spread of microorganisms, it isa biotope unfavorable to their survival. A lack of sufficient nutrients, numerous physical and chemical stressors

often result in sudden changes in microclimate, radiation,and osmotic parameters. Together with the imbalance between oxidants and antioxidants in the surroundings, they
may influence the metabolic activity and even viability of
microbial cells. Atmospheric conditions are not conducive
to maintain the metabolic activity of microbial particles(except for a few experiments with cloud water dropletsand microorganisms being airborne for an extended period of time) (Amato et al., 2005, 2007; Dimmick et al.,
1975; Vaïtilingom et al., 2013). On the other hand, theseunfavorable atmospheric conditions may (to some extent)
provoke a substantial shift among microbial particles
leading to microbiome reformulation through relative selection and/or evolutionary changes. However, it should
be clearly stated that the influence of the airborne state on
microorganism behavior is so far not well understood andstill requires more studies.

5. Behavior and dynamics in the air
In the physical sense, microbiological agents can betreated as solid particles. Several physical (size, shape,density, electrical charge), chemical (composition, hygroscopicity), and biological (breathing pattern, route ofbreathing, anatomy of the airways) factors condition their
behavior both in the air and, if inhaled, in the lungs(WHO, 2002). The basic and one of the most importantcharacteristics of microbial particles is their diameter. The
sizes of microbial aerosol particles range from ~0.02 μm
up to tens of micrometers. Bioaerosol particles are rarely
spherical and, when studied, their usually irregular shapes
are characterized using certain equivalents of particle diameter (in aerobiology, the most frequently used are aerodynamic and optical approximations). It is worth
mentioning here that data from remote measurements (seebelow) suggest that microbial particles usually tend toform aggregates larger than 2.5 μm in diameter (Ho J.,2014). Both equivalent diameters may be significantly distinct from their physical dimensions. As examples, one
can mention here the dimensions of Bacillus subtilis endospore-forming gram-positive rods and Cladosporium
cladosporioides fungal conidia, whose physical sizes of
0.7–0.8 × 1.5–1.8 μm and 3–7 × 2–4 μm correspond withaerodynamic diameters of 0.9 μm and 1.8 μm, respectively(Kulkarni et al., 2011; Macher, 1999; Reponen 1994).
To be inhaled, microbial particles must be airborne fora sufficient period of time. In the vast majority of environmental situations, when the air is almost permanently
turbulent, such a time frame is characterized by the ‘halflife’ term. In brief: as rarely spherical, the sedimentation
velocity of airborne microbial particles depends inter alia
on the square of the particle diameter. Hence, according
to Stokes’ law, for microbial particles of 100, 10, 3, 1, and67

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0.5 μm, the expected half-life times are 5.8 sec, 8.2 min,
1.5 h, 12 h, and 41 h, respectively (Kulkarni et al., 2011;
Martinez, 2002).

Table 2Viability of microbial particles in the air and on surfaces.
Viability/persistence

Biological agent

6. Stability in the air and on surfaces
As already mentioned, the air – being deprived of nutrient sources, with constantly changing moisture content,
and a wide range of different stress factors—on the wholedisfavors microbial survival. Despite these disadvantages,
microbial particles are capable of preserving their viability
and, with it, also all related biological properties (including infectivity, toxicity, allergenicity, etc.) much longer
than bigger organisms. Table 2 presents a few examples
of survival times for microorganisms representing different groups of biological agents that are important fromthe human health perspective (Burge, 1995; Flannigan,
1994; Kramer et al., 2006; Mandrioli et al., 2003; Neira etal., 2016; Yang, 1994). If deposited on surfaces, the microbial particles may also maintain their viability for a long
period of time and, when resuspended in the air, may stillpose a serious threat to the exposed individuals. As theinhalation of immunologically active particles can be responsible for numerous adverse health conditions, the relationship between their stability on surfaces and viability
in the air is of great importance from the exposure assessment point of view.

7. Biological properties
A microbial aerosol has a dual nature, i.e. physical likeother particulates or fibrous aerosols, and biological, i.e. it
possesses specific features characteristic for these typesof airborne particulates only. As mentioned earlier, micro­organisms may be present in the air as viable (i.e. having
the ability to reproduce/replicate or possessing metabolic
activity under given conditions) or non-viable particles(deprived of the capacity to form progenies, being, e.g.
dead or unable to reproduce neither from whole cells nor
from their fragments). Conditio sine qua non for micro­organisms to be infectious is their viability (which in contrast to allergenicity and toxicity can also be maintainedby both non-viable cells and their fragments). Moreover,in the environment, viable microorganisms are under theconstant influence of numerous disruptive and/or stressfactors. Their interference may end in genotype (mutations) and phenotype changes, evolution and relative selection, which can equip microbes with features andproperties (e.g. bacterial mutants resistant to antibiotics ordisinfectants, fungi resistant to fungicides, etc.) hitherto
not possessed (Després et al., 2012; Dutkiewicz andJabłoński, 1989).

68

In the air

On inanimate
surfaces

Influenza virus

Up to 21 days

Up to 11 days

Staphylococci

About 3 days

From 7 days to
7 months

Streptococci

Up to 48 hours

From 1 day to
6.5 months

Escherichia coli

Up to 60 minutes

From 90 minutes
to 16 months

Legionella
pneumophila

Up to 15 minutes

Not detected

Aspergillus andPenicillium conidia

Up to 22 years

Up to 22 years

Dust mite allergens

Up to few months Up to few months

8. Causative role in adverse health effects
Microbiological aerosols are of the greatest epidemiological importance. Although most of the bioaerosols areharmless constituents of normal environments, some of
their particles may be infectious agents or allergens, may
carry or produce toxic and/or irritant substances or metabolites. Taking into account the health effects provokedby airborne microbial particulates, the difference between
outdoor and indoor environments seems to play a significant role. In an outdoor environment, except in periods ofsnow cover, microorganisms are always present. Except
for intensively emitting sources, their concentrations are
not usually high, as spatial effect result in their more orless uniform dispersion. Once disseminated in the ambient air, microbial aerosols may find their way into the indoor environment. Here, a lack of ventilation and otherdispersal or elimination mechanisms, together with thesubstantial amount of time people spend indoors, create
harmful conditions from the health perspective. Global
estimates reveal that in an occupational environment only,
each year several hundred million workers have been exposed to microbial agents in concentrations harmful totheir health. The social costs of such exposure are significant, reaching billions of dollars (Cox and Wathes, 1995;
Crook, 2007).
Among microbial aerosol particles, one can find: infectious agents, allergens, toxins and other biological compounds that are able to provoke similar toxic effects (e.g.
endotoxins, β-glucans), carcinogens (e.g. mycotoxins), andbiologically active (submicrometric and nanometric) fragments of microorganisms. All these particles may perform a causative role of many adverse health conditions

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from allergic reactions, infections and toxic reactions toother non-specific symptoms known in scientific literature as ‘sick or tight building syndrome’ (SBS or TBS),‘building-related illnesses’ (BRIs) or ‘mucous membrane
syndrome’ (MMS). Regarding those non-specific reactions, accompanied usually by a dry cough, eye, nose andthroat irritations, they may not necessarily involve immune responses or inflammatory mediators because inmost cases, the observed adverse effects are a result of
mixed exposure to both toxins and allergens. Aerosols
composed of infectious microorganisms may attack the
respiratory tract and, in more generalized cases, otherbody organs as well. When among airborne microbial
contaminants, non-viable ones—usually together with
their fragments—are present, such exposure may lead tochronic or acute illnesses. Such non-infectious microbial
particulates, if abundantly present in the environment,
may also sensitize exposed individuals (Bunger et al.,
2004; Douwes et al., 2003; Falkinham, 2003; Fogelmark
et al., 1991; Roy and Milton, 2004; Roy and Reed, 2012;
Shahan et al., 1994).
During the inhalation of microbial aerosols, both theupper and lower airways are exposed. The diseases (if theyoccur) most often appear within the part of respiratory
tract into which the particular microbial agent penetrates
and deposits. For example, the influenza virus (representing the Orthomyxoviridae family) together with otherrhino-, adeno-, and coronaviruses that are responsible forthe common cold usually infect the upper respiratory
tract. Also, sensitization diseases (such as allergic rhinitis
or sinusitis) are located in the upper airways (Lopardo etal., 2012; Louie et al., 2005; May S. et al., 2012). In turn,lower respiratory tract diseases (such as bronchitis or
pneumonia) are mainly provoked by aerodynamically bigger structures such as bacteria (e.g. Legionella spp.,
Streptococcus spp., Haemophilus influenzae); however,nanometric particles such as avian influenza (H5N1; virionof 80–120 nm in diameter) or parainfluenza viruses canalso infect the lower respiratory tract (Dasaraju and Liu,
1996; Hall, 2001). The lower airways (especially the bronchi and alveoli) are also a target for numerous viable bacterial cells and spores, fungal conidia, and non-viablemicrobial allergenic and toxic particulates responsible
for chronic diseases such as asthma, chronic obstructive
pulmonary diseases, and hypersensitivity pneumonitis(Bettoncelli et al., 2014; O’Connor et al., 2013; Reynolds
et al., 2013; Sferrazza Papa et al., 2014; Takemura et al.,2008).
Microbial aerosols are ubiquitous and, as such, should
also gain special attention indoors. Such closed spaces,
quite often harboring a wide spectrum of microbiota,
characterize high concentrations of bioaerosols and assuch pose a real risk to human health. The observed diseases, however, are often hard to attribute to specificmicro­bial agents as they usually constitute only a part ofa particulate cocktail together with other allergens derived from organic chemistry products (Blais-Lecours etal., 2015; May S. et al., 2012).

9. Inhalation and deposition mechanisms
Microbial aerosols may affect human health in several
ways, i.e. due to their inhalation or direct contact with theskin and mucous membrane of the eye. Inhalation is amajor route of entry for microbial pathogens and the possible adverse reactions can affect both upper and lower
respiratory tracts. The type of interactions between
micro­bial aerosol particles and human cells depends ontheir place of deposition and is conditioned by their retention time in the airways.
Microbial aerosol particles can be deposited due to several mechanisms (Fig. 1): larger particles—by inertial
impaction, sedimentation, and if resembling fibers (likechains of fungal conidia)—by interception; smaller particles—by diffusion. Electrostatic effects may enhance ormodify the deposition of charged particles of any size.
As already mentioned, the settling velocity of particles
with diameters above 10 μm is big enough to prevent theirinhalation (except the cases when exposed individuals arein the immediate vicinity of the active emission source).
Microbial particles with smaller diameters (represented
usually by vegetative cells, spores, conidia, their fragments, aggregates entirely formed by microbial particles

Fig. 1

Schematic view of major mechanisms of particle deposition in the respiratory tract.

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or consisting of microbial and other non-biological aerosols) may penetrate into the respiratory tract. From them,
about 80 % of particles between 5–10 μm in diameter are
stopped by the nasopharynx. Here, the air entering the
airways has the highest velocity and their anatomic formation supports and facilitates both the inertial impaction
and centrifugal condensation processes. For particles resembling fibers (such as chains of fungal conidia), theircapture is realized due to interception. When inspired air
leaves the nasopharynx and then turns downward into thelower stages of the respiratory tract, its velocity decreases
and directional changes are less abrupt, allowing the separation of smaller particles between 0.5–5 μm in diameter. Particles within that size range are separated from theair stream by impaction and sedimentation, and theirdeposition probability is directly proportional to the residence time. Finally, the finest particles with diameters
below 0.1–0.5 μm are removed from the air and subsequently deposited almost entirely by Brownian motion
and diffusion. This process is inversely proportional tothe diameters of driven particles and is usually bolsteredby electrostatic forces. Very small aerosol particles withdiameters of about 0.01 μm have negligible inertia andthey may start to behave as highly reactive gases, diffusing dynamically through the walls of the respiratory
tracts. It is worth mentioning here that some of the microbial aerosol particles are highly hygroscopic. During theirpassage through the airways, they face significant changesof both the air stream temperature and humidity (the latter parameter may reach almost 100 %). In such circumstances, the aerodynamic diameters of microbial particles
may expand, resulting in their deposition. These hygroscopic changes are most pronounced for particles between
0.5–2 μm in diameter and its increase may reach 20 %.
This fact can have a significant impact on both the magnitude of the actual exposure and on the dose of inhaledparticles and should always be considered when microbial
exposure assessment is to be performed (Clarke, 1990;
Cohen et al. 1998, 2000; Lippmann, 1986; Reponen et al.,
2001; Spengler and Wilson, 1996; Utell and Samet, 1996;
Walton, 1977; Wang, 2005).
In contrast to the deposition of particles, which is apurely physical phenomenon, lung clearance is a biological process. There are four major mechanisms by which
deposited particles are removed from the airways: transport by mucociliary escalators to the pharynx followed byentry into the gastrointestinal tract, incorporation by alveolar macrophages followed by mucociliary escalatortransport or lymph nodes, entry into lymph nodes via
lymphatic vessels, and dissolution followed by absorption
into the blood circulation. The particle clearance efficiency is different in specific airway regions. Particles
stopped in extrathoracic regions are removed by wiping,sneezing or blowing, and these processes usually take70

minutes; those trapped in tracheobronchial parts are removed with the mucus flow and the average time necessary for that ranges from less than an hour to two days;
finally, removal of insoluble particles caught in the lower
respiratory tract (alveolar region) is much slower taking
hundreds of days; highly soluble particles may dissolve
almost immediately after their deposition (Foster andCosta, 2011; Gehr and Heyder, 2000; Spengler and Wilson,
1996; Utell and Samet, 1996; Wang, 2005).
The place of particle deposition and their retention in
the respiratory tract determine the type and severity ofinteractions between the inhaled microorganisms and exposed tissues. Particles of: 10 μm in diameter or bigger(usually microbial aggregates with other non-biologicalparticulates) may be responsible for eye and/or nose irritations; 5–10 μm in diameter (e.g. bigger fungal conidia
or multiparticle microbial aggregates) may elicit asthmatic
reactions; 5 μm or smaller (e.g. individual fungal conidia,
bacterial cells or spores, their fragments as well as small
aggregates of microbial and dust particles) may induce
allergic alveolitis-type reactions (Horner et al., 1995;
Owen et al., 1992). Lessons learned from both experimental and field studies revealed that the physiologic impactof ‘fine’ (including microbial) particles of 2.5 μm in diameter or smaller (e.g. actinomycetal spores, majority ofindoor mold conidia) has been associated with negative
health results. Adverse respiratory effects in exposed human populations include an increase in asthmatic episodes, a rise in the prevalence of chronic bronchitis andchronic obstructive pulmonary disease. These particles
may also negatively impact the cardiovascular system;
however, their deleterious role here is still poorly understood (Cohen et al. 1998, 2000; Foster and Costa, 2011;
Gehr and Heyder, 2000; Spengler and Wilson, 1996;
Walton, 1977; Wang, 2005).

10. Exposure assessment measures
To properly evaluate the health hazards, an appropriate
conceptual framework must be built and applied coveringboth the physical (how many microbial particles are in aparticular volume of the air; how many microbial agentsare in or on other non-biological, i.e. particulate and/or fibrous aerosol, particles; what is the particle size distribution) and biological characteristics (which microbial agent
is present, how many agents are viable and non-viable,
how many agents are immunologically reactive, howmany of them are necessary to cause adverse reactions) of
aerosolized microbial agents. To reach that goal, both theidentification and characterization of microbial aerosol
particles should be performed precisely and accurately.
Despite the constantly expanding knowledge within thisfield, a clear link between the dose of microbial pollutants

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and the subsequently provoked response for the majorityof these agents cannot be conclusively confirmed. Among
the rationales behind this is the inappropriateness of analytical methods related to and used in assessment of the
exposure to microbial aerosols.

11. Microbial aerosol sampling and analysis
Compared to other aerosols, microbial aerosol sampling requires special handling procedures. Traditional
sampling methods (i.e. filtration and impaction, including
impingement) and analysis (cultivation) focus on the evaluation of viable microbial propagules including conidia,
spores and vegetative cells. Such an approach excludes
the meaning of both non-viable particles and/or their fragments and consequently underestimates the real exposure,measuring only a small part of available particles. The
quantitative and qualitative results of these methods (regardless of whether they are carried out as stationary or
personal measurements) are additionally biased by the
sampling time (relatively short in the majority of cases)
and numerous environmental, spatial or temporal alterations. Even characterization of the microbial source, performed usually by surface sampling (using transparent
sticky tape, swabs or contact plates) or, much less often,
by source strength evaluation (based on aerosolization
techniques that use a perpendicular or swirling air stream
for the release of microbial propagules) cannot precisely
estimate the magnitude of microbial particle emission
into the air (Després et al., 2012; Górny and ŁawniczekWałczyk, 2012; Hung et al., 2005; Kulkarni et al., 2011;
Macher, 1999; Yang and Heinsohn, 2007).
Samplers utilizing inertial forces have been broadly applied for microbial aerosol measurements. Among them,the most common are: single-stage and cascade impactors
as well as slit samplers (if the impaction stage consists ofslits instead of circular holes). Especially cascade impactors in their six-, seven-, eight- or ten-stage forms haveoften been utilized as a reference device for the collectionof culturable microorganisms, providing a precise separation of sampled particles due to the well-established cutoff sizes of particular impactor stages. These impactors
are available in both stationery (e.g. Andersen type) andpersonal (e.g. Marple type) models. Particle separationfrom the air by centrifugal force as a special case of inertia but with a radial geometry has also been successfully
applied for microbial aerosol particle collection. On theother hand, impingers (such as AGI-30 or BioSampler)
combine the collection of airborne particles by impaction
into a liquid with particle diffusion within the liquid bubbles. Compared to impactors, impingers offer a significant
extension of sampling times and increase of collection
efficiency, preserving at the same time a vast majority of

biological properties of the microbial aerosol particles(Crook, 1995a, b; Kulkarni et al., 2011). Non-inertial collection techniques represented by sedimentation or filtration have also been frequently applied for microbial
aerosol sampling. More sophisticated devices such as
electrostatic samplers and thermal precipitators have beendeveloped which enable the ‘gentle’ collection of microbial aerosol particles while preserving their viability
during the sampling process and at the same time enhancing their collection efficiency (Kethley et al., 1952;
Mainelis et al., 1999, 2001, 2002; Orr C. et al., 1956; Tan
M. et al., 2011).
Traditional microbiological methodology utilizes cultivation methods and microscopic analysis to describe both
the diversity and concentration of microorganisms in collected airborne samples. Although these are already‘older’ methods, they are still to this day successfully
used in aerobiological studies. On the other hand, however, cultivation methods have serious limitations as they
are dedicated to the detection of viable (understood usually as culturable) microbial agents, neglecting the remaining load of particulates of microbial origin including
viable but non-culturable and dead microbes as well as
their fragments. It should be clearly stated here that the
majority of airborne particles of microbial origin, evenwhen viable, is non-culturable and unable to form newcolonies on an appropriate medium (Amann et al., 1995;
Colwell, 2000; Cox and Wathes, 1995; Hung et al., 2005;
Rappé and Giovannoni, 2003; Roszak and Colwell, 1987;
Staley and Konopka, 1985; Wainwright et al., 2004; Yang
and Heinsohn, 2007). Hence, by definition, the inference
about air pollution based on cultivation methods significantly reduces the value of real exposure. The hitherto
obtained results show that the percentage of culturable
microbial particulates in the total microbiota did not exceed ~25 % for bacteria and ~17 % for fungi, being usually between 0.03 % and 1 % (Bridge and Spooner, 2001;
Chi and Li, 2007; Gołofit-Szymczak and Górny, 2010;
Heidelberg et al., 1997; Lighthart, 2000). Among thefactors influencing these numbers are those of technical(collection method, sampling time, collection/growth
medium, incubation conditions), biological (microbial
strain; type of sampled propagules, i.e. vegetative cells,
spores, conidia), and environmental origin (e.g. temperature; relative humidity; time of day; season; climate zone;
geographic region; type of natural reservoirs such as
water, soil, forest, desert, etc.; presence of plant and animal populations, etc.) (Amato et al., 2007; Dutkiewicz andJabłoński, 1989; Griffin et al., 2006; Shahamat et al.,
1997; Stewart et al., 1995; Tong and Lighthart, 1999;
Wang Z. et al., 2001; Wang C.-C. et al., 2007, 2008).
Since construction of the first optical microscope at theend of the 16th century, microscopic techniques still tothis day play an important role in microbiological studies,71

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including those related to biological aerosols. They allow
the observation and assessment of the size of both large
micrometric and smaller objects with submicro- andnanometric dimensions. They also enable observation of
their internal structure. At the same time, they provide
the opportunity not only to qualitatively identify the viable and non-viable microorganisms, but also to assess thenumber of such agents from vegetative cells, spores or conidia through the particles that are their structural elements, to small infectious agents such as viruses. Brightfield or light microscopes are usually used for simple observations of particulate shapes and sizes as well as tocount microorganisms. The particles in the samples canbe observed in the transmitted light (for transparent specimens) or in the reflected light (for opaque ones), in a lightor dark field or in polarized light to increase their contrast
and make their details visible in more precise way. They
can be also stained using, e.g. methylene blue, crystal violet, safranin, fuchsine or other differential stains to allow
classification of microbial particles into groups of species.
On the other hand, a phase-contrast microscope is used
when the microbial particulates are nearly invisible andan alternative mounting medium is not possible or permissible. Such microscopes do not require sample staining but offer detailed examination of the internal structureof observed particulates. A variety of light microscopy is
fluorescence microscopy which uses an ultraviolet ornear-ultraviolet source of illumination that causes fluorescent particle compounds to emit light. Direct count methods, applied also to aerobiological studies to, e.g. countthe number of ‘total’ microbial particles (i.e. viable andnon-viable together), today constitute one of the mostwide-spread analytical techniques. The application of awide range of f luorochromes (e.g. acridine orange,
4’,6-­diamidino-2-phenylindole, 5-cyano-2,3-ditolyl tetrazolium chloride or fluorescein isothiocyanate), selectively
bounded to the studied cell structure or coupled with specific antibodies or molecular probes, allows the locationof individual structures in a cell and observation of selected physiological processes. Currently, the majority of
the fluorescent microscopes are the ‘epi’ ones (i.e. where
the light source is mounted above the specimen) equippedwith digital cameras which allow recording the image directly in a digital form. The automatic acquisition of images together with their analysis makes the examination
time shorter and the use of several fluorochromes enables
the simultaneous measurement of multiple parameters(Bartoszek and Rosowski, 2017; Després et al., 2012;
Francisco et al., 1973; Harrison et al., 2005; Hernandez etal., 1999; Hobbie et al., 1977; Jensen et al., 1994; Karlsson
and Malmberg, 1989; Kepner and Pratt, 1994; Macher,
1999; Pöhlker et al., 2011). Electron microscopy uses abeam of electrons instead of light. In a scanning electron
microscope (SEM), the sample surface is scanned with a72collimated electron beam. Electron signals, obtained as aresult of the electron stream interaction with the surfaceof the examined object, are collected by appropriate detectors and transformed into images. The high-vacuum
mode is fundamental for each SEM mode of work. It allows obtaining the magnification of sample images up to
10,000,000 × . On the other hand, use of the low-vacuum
mode prevents the accumulation of a charge on the surface of the examined sample, which allows good quality
images for non-conductive samples to be obtained. Inturn, the environmental mode enables the imaging ofsamples of solids, suspensions and non-dehydrated biological preparations and carrying out experiments underdynamic change conditions. SEM in aerobiological studies is usually used to characterize the size and shapes ofindividual microbial particulates, describe their ability toform aggregates, and bind to other aerosol particles orfibers. Also, taxonomical characterization of microbial
aerosols is possible to a certain degree based on morphological criteria. On the other hand, in transmission electron
microscope (TEM), the stream of high-energy electrons
produced by the electron gun is directed to the thin (i.e.
several dozen to several hundred nanometers) sample
where it may be reflected, absorbed or penetrate through.
In the transmission mode, electrons are used to create theimage of the sample structure. Reflected electrons inscanning mode are utilized to characterize the object surface. TEM allows high-resolution images to be obtained.
With the limit of about 0.1 nm, TEM enables observationof the arrangement of atoms in the examined sample.
Finally, atomic force microscopes (AFM) use a scanningprobe (cantilever) to examine surfaces, registering theforce affecting it in the function of its position. The forces(mainly van der Waals ones) between the cantilever tip
and the sample cause deflection of the measuring lever,which leads to imaging of the topography of the examinedmaterial. In the tapping mode, the cantilever tip is in contact with the sample surface for a short time and, in thisway, is able to visually reproduce the image of soft anddelicate samples like microbial ones (Bartoszek andRosowski, 2017; Jensen et al., 1994; Jonson et al., 2014;
Karlsson and Malmberg, 1989; Macher, 1999).
In many cases, the above-mentioned laborious andtime-consuming analyses, often requiring the involvement of highly qualified analysts and expensive research
instruments, are simply not possible. In such cases, numerous constituents or metabolites of microorganisms
can be measured as a surrogate of environmental microbial exposure. So far, several chemical tracers have been
introduced as surrogates of different microbial contaminants (e.g. endotoxins for gram-negative bacteria; muramic
acid from peptidoglycans for gram-positive bacteria; ergosterol, N-acetylhexosaminidase, and (1→3)-β-D-glucan
for fungal biomass). Also, numerous instrumental andRafał L. Górny / KONA Powder and Particle Journal No. 37 (2020) 64–84

bioanalytical techniques corresponding to the selected
microbial constituents have been practically tested. For
example: for the qualitative and quantitative assessmentof endotoxins in environmental samples, a wide palette ofin vitro analyses are proposed including a few modifications of the Limulus test, recombinant Factor C assay as
well as liquid or gas chromatography (used alone or coupled with mass spectrometry, GCMS). In turn, the measurements of muramic or diaminopimelic acids asmarkers of peptidoglycans that are structural components
of bacterial cell wall can be done using GCMS. Also, detection of β-glucans can be realized by applying four different assays: modified Limulus test, inhibition enzyme
immunoassay, enzyme-linked immunosorbent assay, andmonoclonal antibody-based two-site enzyme immunoassay. Markers for the assessment of fungal biomass include
also ergosterol analysis by GCMS, extracellular polysaccharides measured with specific enzyme immunoassays,
and N-acetylhexosaminidase activity assessment (method
based on a fluorescence labeled substrate which can becleaved by the enzyme found in fungi). Moreover, secondary products of fungal metabolism, i.e. mycotoxins,
can be measured using different variants of thin-layer
chromatography, gas chromatography with or without
mass spectrometry or high-pressure liquid chromatography. These two latest techniques can be also successfully
applied in quantitative analyses of volatile organic compounds (VOCs), which can be suitable markers of fungal
growth (Demirev and Fenselau, 2008; Després et al.,2012; Douwes et al., 1999; Griffith and DeCosemo, 1994;
Hung et al., 2005; IOM, 2004; Macher, 1999; Miller andYoung, 1997; Pöschl, 2005; Reeslev et al., 2003; Reponen
et al., 1995; Rylander et al., 2010; WHO, 2009). Evaluation of the pros and cons of the above-listed methods
clearly shows that although the analysis of chemicalmarkers provides quite precise quantitative information, it
does not supply us with data regarding the biodiversity of
microbial particles. Nowadays, such a gap in knowledge
can be fortunately fulfilled by a spectrum of different molecular techniques enabling precise identification of micro­bial strains that form bioaerosols (see below).
As none of the above-described methods offers real-­time detection of microbial aerosols, numerous opticaltechniques were introduced to overcome this limitation.
Among them are those utilizing light scattering, condensation, and fluorescence of microbial particles. Some ofthese methods offer both the measurement and separationof microbial particulates beginning from nanometer sizes.
Amid the instruments operating on the above-describedprinciples are optical (utilizing light scattering) particle
counters (e.g. Grimm 11A; allowing the measurements ofparticle sizes, mops, within the range of 0.25–32 μm) and
condensation (alcohol vapor) nuclei counters (e.g. P-TRAK;
mops of 0.01–2 μm) as well as aerodynamic (combining

analyses of the particle aerodynamic diameters and theirlight-scattering intensities; e.g. DSP Aerosizer; mops of 0.2–
200 μm) and scanning mobility particle sizer spectrometers (e.g. SMPS; mops of 1–1000 nm based on differential
mobility analysis). In turn, the electrical low-pressure impactor (ELPI) allows combining the quantitative controlof microbial propagules with rapid real-time descriptionof their size distribution (mops of 0.006–10 μm). In ELPI,
like in many other volumetric devices, the sampling process is inseparably connected with certain measurement
limitations. The impaction of particles onto hard surfaces,
their bounce and subsequent reaerosolization, friction
during passage through the instrument, desiccation cansignificantly affect the precision of the assessment andcontrol of microbial aerosols. These facts should always
be kept in mind when sampling biological particles (Hunget al., 2005; Jonsson et al., 2014; Kulkarni et al., 2011;
Macher, 1999).
The instruments utilizing fluorescence as a method of
detection are based on the phenomenon that all biologicalparticles containing fluorophores originate from aromatic
amino acid residues (intrinsic constituents of almost all
proteins). Tryptophan, tyrosine, and phenylalanine are theamino acids capable of emitting fluorescence induced by
UV light, and this phenomenon can be utilized for the detection of microbial aerosols. Techniques based on the
fluorescence phenomenon enable recognition of microbial
particles both on a laboratory scale and over areas of tensof square kilometers. Such devices can successfully form
the core of monitoring systems to be used over, e.g.
crowded spaces (Eng J. et al., 1989; Harrison and Chance,
1970; Iwami et al., 2001; Jonsson et al., 2014; Kell et al.,
1991; Li J.K. et al., 1991).
Among the first commercial applications utilizing induced fluorescence were the fluorescence aerosol particle
sensor (FLAPS) and the ultraviolet aerodynamic particle
sizer, UV-APS, the instruments dedicated to real-time
analysis of biological aerosols. FLAPS technology wasdeveloped in the early 1990s and was based on an aerodynamic particle sizer with laser added to excite fluorescence of the sized particles. In its latest version, it uses a
CW laser diode for both excitation and optical sizing. The
system analyses individual particles in the size range of
0.8–10 μm, offering exceptional discrimination of microbial aerosol particulates including bacteria, fungi, viruses,
and toxins. Its performance was broadly confirmed inlaboratory, military, working and non-occupational applications. On the other hand, the UV-APS (that is technically a newer version of FLAPS II) measures the real-time
fluorescence of airborne particles (after excitation by apulsed UV laser) and simultaneously provides a number
size distribution and scatter light intensities for them. The
instrument is able to discriminate particles within 0.8–15 μm aerodynamic size range and has so far been applied73

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to investigate bioaerosol emission sources, microbial particulate properties in laboratories, clean rooms, hospitals
and other indoor (including industrial and built) and outdoor settings in both urban and rural environments(Brosseau et al., 2000; Delort and Amato, 2018; Després
et al., 2012; Hairston et al., 1997; Jonsson and Kullander,2014). The wideband integrated bioaerosol sensor (formerly named wide-issue bioaerosol sensor, WIBS) combines the optical detection and sizing of total aerosol
particulates using a continuous wave CW laser and fluorescence detection resulting from UV pulsed excitationfrom two xenon flash lamps. During measurement, the instrument collects five different types of information including optical particle size, particle asymmetry, andfluorescence from three channels. WIBS is capable ofprocessing up to 125 particles/s and its performance wasalready successfully tested in urban and tropical locations(Delort and Amato, 2018; Després et al., 2012; Gabey etal., 2011; Jonsson and Kullander, 2014; Kaye et al., 2005).
Like epifluorescence microscopy, flow cytometry has
been successfully applied to the real-time control of microbial particles in the air. The evaluated particles canfluoresce naturally or may gain this feature after specificstaining. Being transported in a particle-free medium (e.g.
deionized water) at laminar flow, they are excited by a laser beam. The fluorescence emitted by the flowing objects
and the light dispersed on them are measured by photon
detectors, which regarding microorganisms, offer e.g. total, viable and non-viable particle quantification as well asdelivering data about their sizes and taxonomical classification (Chen and Li, 2005, 2007; Delort and Amato, 2018;
Ho J. and Fisher, 1993; Lange et al., 1997; Prigione et al.,2004)
Mass spectrometry (MS) techniques have also been
adapted for microbial aerosol analysis; however, such particles must be converted into a vapor state before entering
the mass spectrometer. One of the successfully employed
MS techniques is matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF). MS can analyse bothbulk amounts and single microbial aerosol particles.
MALDI-TOF identifies microorganisms, determining
their unique proteomic fingerprints. Their characteristic
spectrum patterns are used to reliably and accurately
identify a particular microorganism by matching thousands of reference spectra of microbial strains. Both rapid
detection and accurate identification have decided on theusefulness of MS techniques in microbial aerosol studies
including both bacterial and fungal pollutants (Jonsson
and Kullander, 2014; Kim et al., 2005; Kleefsman et al.,2008; Madsen et al., 2015; van Wuijckhuijse et al., 2005).

74

12. Qualitative techniques and analyses for
microbial propagules
A recently observed tremendous development of analytical techniques enables a comprehensive characterization of the biological, chemical and physical features of
microbial aerosol particles. This is particularly evident in
the case of deoxyribonucleic acid (DNA)-based and ribonucleic acid (RNA)-based methods including taxon-­
specific quantitative polymerase chain reaction (qPCR) or
droplet digital PCR (ddPCR). The use of these methods inboth Sanger sequencing-based and Next Generation Sequencing (NGS) analyses enables not only the identification of individual genera or species but also thecharacterization of diversity and metabolic potential of
airborne microbiota (Fig. 2). Independent of the method
used, the efficient extraction of DNA is a basic condition of
successful analysis. Polymerase chain reaction technologies can be applied for detection and quantification of either groups of microorganisms or specific strains regardlessof whether they are viable or culturable (Alvarez et al.,
1994; Blais-Lecours et al., 2012; Mukoda et al., 1994). In
aerobiological practice, the usefulness of this technique
was widely confirmed for analysis of airborne bacterial andfungal contaminants (Peccia and Hernandez, 2006; Prussin
et al., 2014). Regarding viruses, no comprehensive PCR
assay so far exists and profile screening is necessary eachtime when these agents are considered to be a major analytical target (Carducci et al., 2013; Masclaux et al., 2014;
Prussin et al., 2014). The most commonly applied laboratory protocols in microbial aerosol investigations include
16S rRNA gene (for total bacteria, total archaea, influenza,
and bacteriophages) as well as 18S and 28S rDNA or fragments located between them, called internal transcribedspacers (ITS) for fungi. Because of their structure, thesegenes have been termed molecular chronometers. They
are characterized by the presence of both conservative(i.e. slowly evolving) fragments as well as those that arecharacterized by interspecific variability (Blais-Lecours etal., 2012; Nehme et al., 2008; Oppliger et al., 2008; Perrott
et al., 2009; Verreault et al., 2011; Woese, 1987).
Various techniques utilizing 16S rRNA or ribosomal
RNA gene spacers that can be used to characterize thebiodiversity in aerosol samples and assess the presence of
etiological agents of bioaerosol-related diseases comprisecloning, fingerprinting, pyrosequencing, and NGS. Withcloning or sequencing, one can unequivocally confirm thepresence of specific microbial strain in the analysed sample. In turn, using fingerprinting methods including denaturing or temperature gradient gel electrophoresis (DGGE
or TGGE, respectively), terminal restriction fragment
length polymorphism (T-RFLP), and ribosomal intergenic
spacer analysis (RISA), both the biodiversity and temporal changes in microbial communities can be studied

Rafał L. Górny / KONA Powder and Particle Journal No. 37 (2020) 64–84

Fig. 2

Procedure in the assessment of exposure to harmful biological agents.

(Gandolfi et al., 2013; Madsen et al. 2015; Maron et al.,2005). When bioaerosol samples are studied, analysts almost always must have to deal with a cocktail of microorganisms. During their analysis, different microbial agentscan generate many species-specific signals, which must
be properly recognized and interpreted to accurately describe the collected microbiota. To do it in a holistic andunivocal way, the applied molecular methods should allow the performance of such an analysis, depriving thepossibility of confounding factors influencing its outcome. Today, among such methods are pyrosequencing
and NGS (Blais-Lecours et al., 2012; Delort and Amato,
2018; Nonnenmann et al., 2010).
Amid the most promising techniques for microbial
aerosol assessment is also droplet digital PCR (ddPCR).
This technique utilizes droplets formed in a water-oil
emulsion to arrange the partitions that separate the template DNA molecules. The droplets basically have thesame function as individual test tubes or wells in a microtiter plate in which the PCR reaction takes place, albeit ina much smaller format. The ddPCR system partitions nucleic acid samples into thousands of nanoliter-sized droplets, and PCR amplification is performed within each ofthem. Such a technique can be adapted for a variety of
applications including copy number variant analysis, rarevariant detection, gene expression analysis, and single-­
nucleotide polymorphism genotyping. Such an approachallows also smaller requirements for the sample thanother digital PCR systems, thus reducing costs and preserving template molecules (Hindson et al., 2011;
Mazaika and Homsy, 2014).
Other distinctive analytical protocols based on enzyme-­
linked immunosorbent assay (ELISA) and electrochemiluminescence (ECL) are employed to precisely localize andrecognize microbial aerosol molecules as well as to confirm the immunological reactivity of microbial propagules
using antibody-epitope binding as a common detection
mechanism. Antibody-based immunoassays, particularly
ELISA, are widely used, among other things for the measurement of aeroallergens. Methods for their measurement are not widely available, mainly due to the highlyvariable allergen production in different environments influenced by numerous factors, including substrate, temperature, biodiversity in microbial community, etc. Suchvariability makes it difficult to develop specific antibody-based immunoassays that detect the relevant fungal
allergens in a specific environment; however, such a situation opens the door for innovative solutions in this area
(IOM, 2004; Schmechel et al., 2003, 2004).

13. Role of threshold limit values for microbial
aerosols in exposure control
The threshold and/or reference limit values for somemicrobiological agents (e.g. bacteria, fungi or endotoxins),
if recognized and accepted by the international scientificcommunity, could be a useful tool in the interpretation of
the measurement results and, as a result, in protecting thehealth of the exposed individuals. The documented exposure to bacteria and fungi that ended in the proposal of
limit values for microbial contaminants dates back to the19th century. In 1872, Carnelly, Haldane, and Andersen
conducted an extensive study into bacteria and molds inthe air of schools and public housing. As they used a volumetric air sampler for the first time (i.e. Hesse’s beef-agarcoated glass tube) and subsequently formulated, based on
the airborne concentrations of microbial particles, the75Rafał L. Górny / KONA Powder and Particle Journal No. 37 (2020) 64–84

recommended level of 600 cfu m–3 as an indicator for excessive microbial pollution, this fact can be treated as apioneer bioaerosol exposure control. Although almost 150
years have passed since that moment, it has not brought
us much new data regarding the exposure standards for
microorganisms.
As was mentioned earlier, a precise relationship between the inhaled dose of microbial propagules and asubsequent adverse health response is not possible in thevast majority of cases. Numerous environmental as well
as microbial species and/or consortia-oriented biases prevent a comprehensive and holistic analytical assessmentof such exposure. Contrary to appearances, and despite
the time that has passed since the first volumetric measurement of bioaerosol, to this day there are not many
guidelines regulating the issues of microbiological material collection, its thorough analytical elaboration and, finally, quantitative and qualitative interpretation of theobtained results.
Nowadays, on the worldwide scale, there are no widely
accepted regulations standardizing microbial aerosol
sampling for exposure assessment in different environments. To create them, some tips can be taken from theregulations elaborated for the control of the working environment (up to now, they are summarized in four European
standards (EN) published by the European Committee forStandardization (CEN), i.e. EN 13098:2000—currently
its revised version is under CEN approval, EN
14031:2003, EN 14042:2003 and EN 14583:2004). Nevertheless, even with their consideration, it is necessary to
act according to a certain strategy, at the end of which an
unequivocal interpretation of the concentrations of microbiological aerosols measured in the environment will bepossible.

Fig. 376

14. Health-based versus environmentallybased approaches in the elaboration ofhygienic standards for microbial aerosols
The dynamic development of analytical methods allows
continuous improvement of the quantitative and qualitative description of the microbial pollution of the environment. Along with the progress in this area, there is also
an urgent need for the development of hygienic standards
for bioaerosols based on properly constructed strategiesof their creation. In the case of microbiological aerosols,
they are usually referred to medical (clinical) and environmental approaches. Such a strategy takes into accountthe research method as well as several environmental,
source, quantitative and qualitative criteria, which play a
key role in such a process. Fig. 3 illustrates their interdependencies.
Regarding adverse clinical outcomes provoked by the
exposure to microbial aerosols (that are probably the most
crucial ones), the ideal situation would be when:a) a hygienic standard would be created based on the relationship between exposure, type, and concentrationof microbiological agent and its health effects;b) a relationship would be epidemiologically proven;c) experimental (laboratory) evidence proving this relationship would be known;d) a relationship would be clinically confirmed.
Today, as was already underlined, such a situation does
not exist for any microbiological agent. Therefore, a wise
solution to this situation is urgently needed. As it would
seem, ‘a helping hand’ in this situation could be a so-called‘environmental philosophy’, being a reasonable alternative
for the above-described ‘clinical’ approach. According
to ‘environmental philosophy’ in the situation in which‘a solid link between the concentration of investigatedKey factors in the elaboration of threshold limit values for microbial aerosols.

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parameters and resulting adverse health effects cannot beeffectively established, then—based on the multiple biological agent concentration measurements—the reference
values should enable an evaluation of the quality of theenvironment, as well as determination of ‘what is typical
and/or acceptable’ and ‘what is atypical and/or unacceptable’ for a specific type of environment (or for its certainpart)’.
The threshold limit values hitherto proposed in the scientific literature are usually formed for the total numberof mesophilic bacteria, gram-negative bacteria, bacterial
endotoxins, mesophilic actinomyces, fungi, glucans, andsubtilisin for both occupational and non-occupational environments. A special emphasis is given to pathogenic
microorganisms for which their environmental tolerance
is at ‘zero’ level (i.e. no safety level exists and the threshold limit is usually 0 cfu m–3). For a more comprehensive
overview of worldwide exposure standards for microbial
aerosols, readers are referred to Brandys and Brandys(2012) and Górny et al. (2011).

15. Summary
According to World Health Organization guidelines,
today’s societies should live in a safer environment, with
exposure to contaminants hazardous to health at levels
not exceeding internationally agreed standards. They also
have the right to breathe healthy air, to receive adequate
information about potentially harmful exposures, and to
be provided with effective containment measures. Nevertheless, exposure to microbial aerosols is still common in
many different environments and is often the cause ofmany adverse health effects. Although the protection ofhuman health against the risks associated with this typeof exposure is not only a legal requirement but also a logical consequence of today’s state of knowledge, both thecontrol of exposure to microorganisms and the resultant
assurance of safe living and working conditions are nottreated with due seriousness. This situation should change
quickly, and the knowledge already available in this area
and the increasingly widespread use of tools for the precise quantification of exposure to airborne microorganisms should result, if not in elimination, at least in asignificant reduction of microbiological hazards.

Acknowledgments
This scientific work was supported by the Polish Ministry of Family, Labour and Social Policy from the Multiannual Program “Improvement of safety and working
conditions (2017–2019)” as Research Project No. II.N.15.

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Author’s Short Biography
Rafał L. Górny
Rafał L. Górny is a Full Professor of medical sciences, is currently Head of the Laboratory of Biohazards at the Central Institute for Labour Protection—National ResearchInstitute, Warsaw, Poland. In the last 25 years of professional work, he has been engaged
in numerous studies on the health-related aspects of exposure to particulate, biological,
and fibrous aerosols in occupational and non-occupational environments. His research
efforts have been presented in more than 70 peer-reviewed publications, more than 100
conference presentations, several monographs and book chapters. Since 2002, he has
been working as a World Health Organization and European Commission adviser within
the field of biological agents.

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Review Paper

Review of Encapsulated Salt Hydrate
Core-Shell Phase Change Materials †Hui Wang 1,2, Yunfa Chen 2, Jianqiang Li 2*, Lijiang Guo 2 and Minghao Fang 1
1

Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid Wastes, National Laboratory of Mineral Materials,
School of Materials Science and Technology, China University of Geosciences (Beijing), China
2
National Engineering Laboratory for Hydrometallurgical Cleaner Production Technology, Key Laboratory of Green Process and Engineering,
Institute of Process Engineering, Chinese Academy of Sciences, China

Abstract
The salt hydrate heat storage phase change material (PCM) has a promising prospect of application and has
become a research hotspot because of the advantages of high thermal storage density, high thermal conductivity,
moderate phase change temperature, and low price. However, some problems have restricted the application ofsalt hydrate heat storage materials, such as phase separation, supercooling, and corrosion of the metal container.
A microencapsulated PCM using the microencapsulated technology of solid PCM coated packaging with coreshell structure composite material is an effective method to solve the above problems. In this paper, the researchsituations involving microencapsulated salt hydrate are analysed. This review introduces the selection of core andshell materials, compares the different preparation methods of encapsulated salt hydrate PCMs and summarizes
the application fields.
Keywords: salt hydrate, core-shell microcapsules, phase change materials, encapsulating methods, application

1. Introduction
With the rapid development of global industry, a great
deal of energy is consumed. At the same time, the increase in energy demand has spurred people to find more
effective energy technologies to achieve rational utilization of energy structures in the global economy (Waqas A.
and Ud Din Z., 2013). The development of renewable energy must be accelerated, such as solar energy, wind energy, water energy, and so on (Milian Y.E. et al., 2017; Xu
B. et al., 2015; Mellouli S. et al., 2015). However, theseenergy sources are constrained by their own characteristics for large-scale development. For example, because ofchanges in time and season, solar energy and wind energy
are discontinuous and unstable (Tyagi V.V. et al., 2016).
Affected by environmental, ecological, and safety issues,
the development of hydropower and nuclear energy has
also been limited. Thermal energy storage has been developed in the past decades, as it can transfer heat to stor†
1
2*

Received 10 March 2019; Accepted 20 May 2019
J-STAGE Advance published online 13 July 2019No. 29 Xueyuan Road, Haidian District, Beijing 100083, China
1 North 2nd Street, Zhongguancun, Haidian District, Beijing
100190, China
Corresponding author: Jianqiang LI;
E-mail: jqli@ipe.ac.cn
TEL: +1-352-071-7191

age during the charging, and release it during thedischarging. Thermal energy storage has two methods
usually, including sensible heat or latent heat. Howeversensible heat storage material has the lower storage capacity compared to the latent heat storage materials, whichlead to the sensible heat storage systems need to occupy ahuge volume and large space. Therefore, latent heat storage called phase change materials has a high storage density with a small temperature during storing and releasingheat (Zhang H.L. et al., 2016). Phase-change energy storage technology can realize multi-energy comprehensive
application and allow safe, continuous, and stable output
through the application of large-scale energy storage
technology (Tyagi V.V. et al., 2012).
Phase change energy storage technology involves theenergy storage and release of latent heat generated byphase change materials (PCMs) during the process ofphase change, thereby alleviating the contradiction of themismatch between the supply of heat energy and the demand in time and space (Farid M.M. et al., 2004; Pasupathy
A. et al., 2008), which is the key technology to achieveenergy conservation and comprehensive gradient utilization. Energy storage is directly affected by the performance of PCMs. The primary selection criterias of PCMs
include high thermal storage capacity, high thermal conductivity, safety and low price. The PCMs are mainlyclassified by chemical composition, including organic

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Hui Wang et al. / KONA Powder and Particle Journal No. 37 (2020) 85–96

Fig. 1

Advantages and disadvantages of PCMs (Cabeza L.F. et al., 2011; Kuznik F. et al., 2011).

PCMs (paraffin, fatty acids, etc.) and inorganic PCMssuch as salt hydrates, and others (Zalba B. et al., 2003;
Zhou D. et al., 2012; Su W. et al., 2015). Their classification and corresponding characteristics are shown in
Fig. 1. Compared with organic PCMs, inorganic PCMs
have the advantages of high heat storage density, high latent heat during the phase change process, and high thermal conductivity. Salt hydrates are typical inorganic
PCMs and have outstanding advantages such as low
prices and the fact that they are easy to obtain. Therefore,
salt hydrate PCMs have the economic and technical feasibility and broad application prospects in many fields, suchas solar energy utilization (Xiao X. et al., 2013), building
energy conservation (Khudhair A.M. and Farid M.M.,
2004; Su J.F. and Wang S.B., 2012), power system peakshaving, waste heat recovery, and so on (Hyun D.C. et al.,2014; Lecompte T. et al., 2015).
However, salt hydrate PCMs have problems such asphase separation, supercooling, leakage, and instability
during phase change process (Zhang Y. et al., 2018),
which limits their large-scale application in many fields(Cao L. et al., 2014; Song S. et al., 2014).The microencapsulation technique is an effective method for salt hydrate,
as it can solve the leakage problem, increase the heattransfer area, reduce the reaction with the external environment and control the volume change during phasechange process. (Fang G.Y. et al., 2010; Jamekhorshid A.
et al., 2014; Su W. et al., 2015; Liu C.Z. et al., 2015).
Generally, microencapsulated PCMs refer to the coreshell PCMs. Occasionally, some researchers deemed thatthe shape-stabilized PCMs also belongs to the microencapsulated PCMs category (Zhao C.Y. and Zhang G.H.,

862011). The shape-stabilized PCMs are mostly integrated
PCMs with porous materials by capillarity (Milian Y.E. etal., 2017), which could solved the problems of salt hydrate
PCMs mentioned above. However, when the temperature
increases and reaches the phase change point, the liquid
PCMs will slowly leak out from the micropores, which
results the cycle performance of shape-stabilized PCMs
decrease at high temperature. In comparison, the coreshell microencapsulated PCMs are solid or liquid PCM
particles with a core-shell structure coated by film-­
forming material, thereby overcoming the shortcomingsof the shape-stabilized PCMs and improving the performance of PCMs (Milian Y.E. et al., 2017; Zhao C.Y. andZhang G.H., 2011). The structure of a core-shell microencapsulated PCM consists of core material and a shell material wrapped around the core. The core material can beeither a PCM or a plurality of PCMs or the mixture withstabilizers, diluents and excipients. Shell materials aremostly made of stable, soft, and odorless polymer materials. The polymer material must be able to form a film on
the surface of the core material, and has no reaction withthe core material, being chemically compatible (Liu H. etal., 2019).

2. Selection of core and shell materials
2.1 Core materials
The core material is the phase change material. The
principles of selection are large latent heat of phasechange, a suitable phase change temperature, good

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Table 1

Thermal physical properties of typical salt hydrates.

PCMs

Tm /°CΔHm /J·g–1

k/W·m –1·k–1

ρ/kg·m –3

Cp/J·kg–1·°C–1

LiClO3·3H2O

8

253

n.a.

1720 (s), 1530 (l)n.a.

ZnCl2·3H2O

10

n.a.

n.a.

n.a.

n.a.

CaCl2·6H20

29–30

170–192

1.008 (s), 0.561 (l)1802 (s), 1562 (l)n.a.

Na2SO4·10H2O

32

251–254.0

0.5441485 (s)2

Na2CO3·10H2O

32

267

0.514 (s), 0.224 (l)830

1.92 (s), 3.26 (l)Na2HPO4·12H2O

35–40

256–281

n.a.

1522

n.a.

MgSO4·7H2O

48.5

202

n.a.

n.a.

n.a.

Na2S2O3·5H2O

48

209

n.a.

1600

n.a.

CH3COONa·3H2O

58

270–290

n.a.

1450

n.a.

FeSO4·7H2O

64

200

n.a.

n.a.

n.a.

Ba(OH)2·8H20

78

265–2801.255 (s), 0.653 (l)2070 (s), 1937 (l)n.a.

Mg(NO3)2·6H2O

89.9

167

0.0611 (s), 0.490 (l)1550 (l), 1636 (s)n.a.

MgCl2·6H2O

117

167

0.704 (s), 0.570 (l)1450 (l), 1570 (s)–12.25 (s), 2.61 (l)Annotation: Tm: Phase change temperature (°C). ΔHm: Latent heat (J·g ). k: Thermal conductivity (W·m ·k ). ρ: Density (kg·m–3).
Cp: Specific heat capacity (J·kg–1·°C –1).

stability and durability, low likelihood of leaking, large
thermal conductivity, reversibility in a phase transition,and good chemical compatibility (Milian Y.E. et al.,2017). The phase change is reversible, and the chemicalcompatibility is good (Zhang J. et al., 2011). Salt hydrate
PCMs are increasingly favoured for their outstanding advantages such as high latent heat and low cost. Salt hydrates, as shown in Table 1, are typical of the moststudied PCMs. Although there are many salt hydrates, atpresent, the successfully coated salt hydrates as the corematerials are Na 2SO4·10H 2O, CaCl 2·6H 2O, Na 2HPO4·
12H2O, Mg(NO3)2·6H2O, Na2CO3·10H2O, and so on(Sharma S.D. et al., 2004; Sharma A. et al., 2009; Cabeza
L.F. et al., 2011; Su W. et al., 2015; Yang J.M. and Kim
J.S., 2017). The thermal properties of the microencapsulated PCMs are shown in Table 2.

2.2 Shell materials
From the viewpoint of structure stability, the shell material should meet the characteristics of high strength,
high toughness, good compactness and good chemical
stability to maintain its integrity and avoid leakage ofcore material under the action of external force. Considering the preparation and use of the material, the shell material should have good chemical compatibility with thecore material, no corrosion, no penetration, and it should
be cheap and easy to obtain. In addition, to maintain the
structure stability of core-shell microencapsulated PCMs,
the melting point of the shell material should be higher
than both the phase transition temperature of the core ma-–1–1terial and the highest temperature to be used.
Commonly shell materials are divided into organic andinorganic materials. From the literatures, most of the published papers are reported on the preparation of core-shell
microencapsulated PCMs with organic shell materials,
which means organic materials are easier to form coreshell microencapsulated PCMs (Liu H. et al., 2019). Generally used organic shell materials for coating salt hydrates
are urea-formaldehyde resin, polymethyl methacrylate, styrene, polyurethane, and ethyl 2-cyanoacrylate, as shown in
Table 2. Organic shell materials are costly and containmany harmful substances, such as benzene and aldehyde.
Therefore, inorganic shell materials are more preferable
due to the high thermal conductivity, safety and low
prices. Although most of the inorganic shell materials
have poor structure stability, considering the advantagesof the inorganic shell materials, the development of new
inorganic shell materials is important for improving theperformance of shell materials and promoting the application and development of salt hydrate encapsulated PCMs.

3. Methods for preparation of salt hydratecore-shell phase change materials
The encapsulation methods of phase change core-shell
PCMs are divided into chemical method and physicalmethod (Su W. et al., 2015; Kośny J., 2015; Liu H. et al.,2019), and their classification characteristics are shown in
Table 3. Among them, the suspension polymerization
method, the complex coacervation method and the spray

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drying method are not suitable for the encapsulation
preparation of inorganic PCMs due to their solubility andsystem stability problems. According to the literature research, the preparation methods of salt hydrate core-shell
microcapsules mainly include in-situ polymerization

method, solvent evaporation method and a few othermethods such as sol-gel method and interfacial polymerization method. The specific preparation process is also
shown in Table 4.

Table 2 Thermal properties of hydrate salt core-shell microcapsules.
PCMs

Tm /°CΔHm /J·g–1 Shell

Size

Mixtures(PEG1000/
Na2CO3·10H2O/
n-alkanes)

38.6

235.2

Urea Resin

Na2SO4·10H2O

27.9

254.0

Na2CO3·10H2O
Na2CO3·10H2O

38.6

Na2HPO4·12H2O

ΔHc-s/
J·g–1

Ref.

1–500 μm 17.7/15.8

44.6/42.5(Sarier N. andOnder E., 2007)

SiO2

100 nm—180.7(Zhang J. et al.,
2011)

235.2

TMPTA and MS

1.5 mm28

100(Platte D. et al.,
2013)

—

—

TMPTA and MS

—

24

200

(Platte D. et al.,2013)

Mg(NO3)2·6H2O

93/74

160.2

Ethyl-2-cyanoacrylate

100–
200 nm

91/83

83.2

(Graham M. et al.,2016)

MgSO4·7H2O

50.59

69.83

Urea Resin

35 um

48.36

25.46

(Liu C.Z. et al.,2017a)Na2S2O3·5H2O

49.9

218.93

SiO2

—

47.23

199.47(Max)(Liu C.Z. et al.,2017b)

Na2HPO4·12H2O

34.5

265.0

Cellulose acetate butyrate 3 μm
and diphenylmethylene
diisocyanate

26.69

140.4

(Salaün F. et al.,2010)

Na2HPO4·12H2O

34.72

—

Urea Resin

500 nm

41.5

121.2

(Wang T.Y. et al.,2013)

Na2HPO4·7H2O

34.7

177.8

Poly MMA with EA

6.8 μm51

145.5(Huang J. et al.,
2013)

Table 3

Tc-s/°C

Preparation methods and properties of nano/microencapsulated phase change materials.

Methods

Scale/μm

Advantages

Disadvantages

Chemical Processes contain in-situ, interfacial polymerization, emulsion and suspension polymerization
In-situ

0.05~1100

Easy to operate

Hard to control and easy to reunite.

Interfacial polymerization

0.5~1000

Good compactness for shell and highreaction speed

Limited options for a salt hydrate
system.

Emulsion

0.05~5

Good cooling, do not use volatilesolvents and low viscosity—

Suspension polymerization

2~4000High coating rate, small particle sizeand pollution.

—

Physical Processes contain sol-gel process, coacervation, solvent evaporation and spray-drying
Sol-gel process

0.2~20Mild reaction condition and homogeneous phase distribution—

Coacervation

2~1200Controllable diameter and large pH
range

No large-scale production

Solvent evaporation

0.5~1000

Low price and easy operation

No large-scale production and long
cycle

Spray-drying

5~5000Low cost and mass production

Easy to reunite at high temperature.

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3.1 In-situ polymerization method
When the core-shell PCMs are prepared through in situ
polymerization method, it involves a process whereby thereaction monomer and catalyst are added into the dispersion medium, and the core material is the dispersed phase.
The monomer undergoes prepolymerization at the beginning of the reaction, and then the prepolymer is polymerized. When the prepolymer polymerization size isgradually increased, it is deposited on the surface of thecore material. Because of the continuous progress ofcrosslinking and polymerization, the microencapsulatedshell of the core material is finally formed (Zhao C.Y.

Table 4and Zhang G.H., 2011). Fig. 2 shows the process of encap­
sulations of n-octadecane with resorcinol-modified
melamine-formaldehyde shell using the in situ polymerization method (Zhang H. and Wang X., 2009a).
Sarier N. and Onder E. (2007) used urea-formaldehyde
resin as the shell to encapsulate Na 2CO3·10H 2O andn-hexadecane. Polyethylene glycol 1000 was used as thedispersant. The prepared capsule has a smooth surface
and no leakage. It is suitable for textile products.
Zhang J. et al. (2011) used SiO2 as a shell to encapsulate
Na2SO4·10H2O as a core material in situ polymerization
method. The results indicate the microcapsules can improve the supercooling and phase segregation of the purePreparation of salt hydrate core-shell microcapsules.

Capsules scaleCore materials

Shell materials

Emulsifiers

Ref.

Nano/microencapsulated salt hydrates are prepared successfully by in situ polymerization
Micro

Mixtures (PEG1000/
Na2CO3·10H2O/n-alkanes)

Urea Resin

SDBS(Sarier N. and OnderE., 2007)

Nano (100 nm)

Na2SO4·10H2OTEOS and3-aminopropyltriethoxysilane

SDS and n-pentanol(Zhang J. et al., 2011)

Nano(100–200 nm)

Mg(NO3)2·6H2O

Ethyl-2-cyanoacrylate

Tween 80 and Span 20(Graham M., 2016)—

Mg(NO3)2·6H2O

Ethyl-2-cyanoacrylate

Tween 80 and Span 20(Graham M. et al.,
2017)

—

Na2SO4·10H2O

Ethyl-2-cyanoacrylate

Tween 80 and Span 20—

Mg(NO3)2·6H2O andNa2SO4·10H2O (1:1)

Ethyl-2-cyanoacrylate

Tween 80 and Span 20

Micro (35 μm)

MgSO4·7H2O

Urea Resin

SDBS(Liu C.Z. et al., 2017a)

Nano/microencapsulated salt hydrates are prepared successfully by solvent evaporation
Micro (3 μm)

Na2HPO4·12H2O

Cellulose acetate butyrate anddiphenylmethylene diisocyanate

Span 85(Salaün F. et al. 2010)

Micro (6.0 μm)

Na2HPO4·12H2O

PMMA

Span 85(Wang T.Y. et al., 2013)

Micro (6.8 μm)

Na2HPO4·7H2O

Modified Poly MMA with EA

Span 80(Huang J. et al., 2013)

Nano/microencapsulated salt hydrates are prepared successfully by interfacial polymerization(0.5~2.5 mm)

Na2HPO4

Polyamide membrane—(Hessbrugge B.J. andVaidya A.M., 1997)

Nano/microencapsulated salt hydrates are prepared successfully by sol-gel process
Na2S2O3·5H2O—

Fig. 2SiO2SDS(Liu C.Z. et al., 2017b)

Fabrication of microencapsulated PCM by in-situ polymerization. Reprinted with permission from Ref.
(Zhang H. and Wang X., 2009a). Copyright: (2009a) Elsevier B.V.

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Na2SO4·10H2O and have good cycling performance after
60 times, and good performance.
Platte D. et al. (2013) prepared salt hydrate microcapsules by in-situ polymerization of mercaptan michael addition using TMPTA and polyether as shells andNa2CO3·10H2O, Na2CO3·10H2O and Na2HPO4·12H2O ascore materials.
Wang T. et al. (2013) selected Na2HPO4·12H2O as thecore material and urea-formaldehyde resin as the shellmaterial. The microcapsules were successfully preparedby in-situ polymerization. The effects of the molar ratio of
urea and formaldehyde on the structure and morphologyof the obtained microcapsules were studied. The results
show that the prepared microcapsules have a core-shellstructure with a well-proportioned coating. Its average
particle size was about 500 nm, the latent heat of phasechange was 121.2 J·g–1, and the weight loss was less than
10 % in the temperature range of 30–84 °C.
Graham M. et al. (2016) used in-situ microemulsion
polymerization method to prepare microcapsules with
2-ethyl cyanoacrylate polymer as shell material andMg(NO3)2·6H2O as core material. The capsule size was
100–200 nm. The latent heat of the PCM was reduced by
3 % after 100 times of phase thermal cycles, and the degree of supercooling was greatly reduced. This was thefirst time to produce a longer life (100 times) for salt hydrate microcapsules. The latent heat of the microcapsulewas 83.2 J·g–1. After hundreds of thermal cycles, the latent heat value did not change much. The researchers also
confirmed by Fourier transform infrared spectroscopy
and observation that the chemical properties of the microcapsules were very stable after hundreds of thermal cycles. Graham M. et al. (2017) successfully preparedmicrocapsules containing Mg(NO 3) 2·6H 2 O, Na 2 HPO4·12H2O and their mixture as core materials by theabove methods.
Liu C.Z. et al. (2017a) successfully prepared microcapsule by in-situ emulsion polymerization with urea formaldehyde resin (UR) as the shell material and MgSO4·7H2O
as the core material. They analysed the microscopic mor-

Fig. 390phology, particle size distribution, phase change temperature, phase change latent heat of microcapsules. The
results reveal that when using sodium dodecyl benzene
sulfonate as the emulsifier, and emulsifier content was
0.5 g, the microcapsules had a smooth, uniform particle
size; the average diameter was 34.99 microns, the phasechange temperature of microcapsule was 48.36 °C and thephase change latent heat was 25.46 kJ·kg–1.

3.2 Solvent evaporation method
The solvent evaporation method means that the shellmaterial or the shell material formed by the reaction is
dissolved in the continuous phase first, and after the dispersion medium is volatilized, a shell is formed on thesurface of the droplet to obtain a microcapsule structure(Salaün F. et al., 2010). Fig. 3 shows a process by an interfacial polymerization.
Salaün F. et al. (2010) used a solvent evaporation
method, cellulose acetate butyrate and diphenylmethylene
diisocyanate as shell materials, and Na2HPO4·12H2O ascore material to prepare phase change microcapsules. The
author discussed the effects of different solvents such asacetone, toluene, carbon tetrachloride, and chloroform on
the morphology and coating rate of microcapsules, using
toluene and chloroform as organic solvents to generate
Na 2HPO 4·12H 2O@polyurethane microcapsules with acoating rate of 68.4 % and a uniform particle size distribution. Through SEM observation, the morphology of the
microcapsules was strongly influenced by the solvent.
The thermal properties of the microcapsules were studied
by TGA and DSC analysis, and the results show that thethermal properties of the microcapsule depended on thecontent of the core material and the synthesis conditions.
Wang T.Y. and Huang J. (2013) used polymethyl methacrylate (PMMA) as a shell material to encapsulate
Na2HPO4·12H2O using the same method. The polymerization was sufficiently carried out at a reaction temperature of 80 to 90 °C for 4 hours to form a composite phasechange microcapsule with a radius of 1–10 μm. The

Steps of microencapsulation by solvent evaporation. Reprinted with permission from Ref. (Li M. et al.,2008). Copyright: (2008) Elsevier B.V.

Hui Wang et al. / KONA Powder and Particle Journal No. 37 (2020) 85–96

literature indicates that it can reach a maximum phasechange enthalpy of 173.9 kJ/kg at a temperature of 51 °C.
To lessen the brittleness of polymethyl methacrylate
shell material and improve the processing property of salt
hydrate microcapsules, Huang J. et al. (2013) studied
Na2HPO4·12H 2O encapsulation by solvent evaporation
method with shell material made of methyl methacrylate
and ethyl acetate. Microencapsulated PCMs with a phasechange temperature of about 51 °C and a phase change
enthalpy of 150 J·g–1 were prepared. The reason for thechange in phase change temperature was analysed basedon the characterization data, which were due to the uneven distribution of components and the loss of the watercomponent during the preparation process. Thus, the corematerial coated with the microcapsules was actually
Na2HPO4·7H2O.
Wang T. et al. (2013) encapsulated DSP using PMMA
and UF at 51.51 and 41.15 °C with the corresponding latent heat of 142.9 and 121.20 kJ·kg–1. The results showthat they achieved encapsulation efficiencies were only
55.74 % and 63.97 % respectively. The organic solventcaused leakage after a few multiple heating-cooling cycles.

3.3 Interfacial polymerization method
The interfacial polymerization method refers to emulsifying or dispersing a core material in a continuous phasein which a shell material is dissolved, and then the monomer forms the microcapsule on the surface of the corematerial by polymerization. The interfacial polymerization can be mainly divided into interface addition polym-

Fig. 4erization and interface condensation polymerization
method, which is suitable for preparing microcapsules ofwater-soluble core material (Sarier N. and Onder E.,2012). Fig. 4 shows a process by Zhang H. and Wang X.
(2009b) in interfacial polymerization.
Hessbrugge B.J. and Vaidya A.M. (1997) prepared
Na2HPO4 as the core material and polyamide as the shellmaterial to prepare microcapsules by interfacial polycondensation. The results indicate that the microcapsules are
0.5 to 2.5 mm in size and can be used as a buffer.

3.4 Sol-gel method
The sol-gel process contains three steps: First, the precursor is mixed uniformly with the solvent. After the hydrolysis condensation chemical reaction, a stabledispersion of colloidal particles is generated. Last, a gelwith a three-dimensional network structure was formed
after aging of the sol ( Macwan D.P. et al., 2011). Fig. 5
shows the process of the sol-gel method.
Liu C.Z. et al. (2017b) successfully prepared Na2S2O3·
5H 2O@silica phase change microcapsules by sol-gel
method, using silica as the shell material and sodium
thiosulfate pentahydrate as the core material. They measured the microstructure, particle size distribution, phasechange temperature and latent heat of phase change microcapsules. They analysed the effects of different emulsifier content and the mass ratio of core material to shellmaterial. The results show that the phase change microcapsules had the regular spherical structure, smooth andcompact surface when the mass ratio of the core material
and the shell material and emulsifier is 1:0.4:0.04 and that

Microcapsule manufactured by interfacial polycondensation. Reprinted with permission from Ref.
(Zhang H. and Wang X., 2009b). Copyright: (2009b) Elsevier B.V.

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Fig. 5

Schematic formation of a sol-gel process. Reprinted with permission from Ref. (Zhang H. et al., 2010).
Copyright: (2010) Elsevier B.V.

the particle size distribution was uniform. The latent heatof the prepared phase change microcapsules was
199.47 kJ·kg–1, and the coating rate was 94.65 %. Afterthe silica coating, the supercooling degree and thermal
conductivity were improved, and the thermal stability was
obviously improved. At the same time, the leakage causedby the flow of the core material after melting was solved,
thus extending the cycle life of the inorganic salt hydrates
in practical application.
Yang J.M. and Kim J.S. (2018) successfully preparedmicrocapsules by using a combination of sol-gel and interfacial polymerization with siloxane and polyurea asshell materials and CaCl2·6H2O as core material. They
studied the characteristics of microcapsules with different
core-shell ratios and different pH values. The results indicate that the microcapsules can be prepared when the
core-shell mass ratio was 3.0, and when the pH was between 1.5 and 2.8. Especially when the pH was 2.35 and
2.55, the surface of the microcapsule was smooth with excellent thermal properties and a high coverage ratio.

3.5 Comparison of different microencapsulation
methods
The review has shown that salt hydrate PCMs can be
encapsulated by different methods such as in-situ polymerization, interfacial polymerization, solvent evaporation,
sol-gel methods, and so on. In brief, in-situ polymerization can be suitable for producing nanocapsules, but it isdifficult to achieve large-scale production because a highstirring rate is needed to generate droplets during the encapsulation process, which will consume a great deal ofenergy and produce high costs. Solvent evaporation canbe encapsulated using organic shells successfully. How-92

ever, the organic shells have poor thermal conductivity
and the preparation process is not controllable. Few studies have been conducted on interfacial polymerization andsol-gel methods for salt hydrate core-shell microencapsulation.

4. Application
4.1 Temperature-regulating fabricAs early as the 1980s, NASA carried out research on
the application of microencapsulated PCMs in thermal-­regulation protective clothing. Since then, much-­appliedresearch has been carried out in the field of clothing(Giraud S. et al., 2005; Giraud S. et al., 2002). This typeof functional clothing can adjust the temperature of theclothing and its surroundings, reduce the difference inskin temperature, and make the clothing more comfortable. In the main process, microcapsules are added to thefibre or coated on the surface of cotton cloth to develop fibre and cloth with self-regulating temperature performance. Sarier N. and Onder E. (2007) accomplished themicroencapsulation of PCMs by a manufacturing technique that can ultimately be used in different textile applications.

4.2 Buildings
PCMs have been used in buildings to meet comfort
thermal requirements for peoples (Hawes D.W. et al.,
1993; Neeper D.A., 2000; Kumirai T. et al., 2019). But,
there are some problems for PCMs in building applications, such as interaction between building structure andHui Wang et al. / KONA Powder and Particle Journal No. 37 (2020) 85–96

PCMs; leakage of PCMs to decrease the lifetime of thestructure and poor heat transfer for PCMs in the solidstate. To overcome the above problems, salt hydrate coreshell PCMs are applied in the field of energy-savingbuilding materials. Physical methods such as miscibility
and filling can be combined with traditional building materials to prepare energy-saving building materials suchas plates, coatings, and bricks with the function of phasechange energy storage. A comprehensive review of encapsulation techniques for inorganic phase change materials
and the influence on their thermophysical properties had
been carried out by Milian Y.E. et al. (2017). In this review, the researcher made a detailed summary of the application trend of microcapsules in the field of buildings.
The application of microcapsule phase change energy
storage materials in the buildings can reduce the fluctuation of indoor temperature and the power consumption ofrefrigeration or heating equipment to achieve the purposeof energy savings. But the researchers still admit greatchallenges to enlarge thermal and cycling stability and reduce corrosion with building materials (Ma Z. et al.,2016).
Farid M.M. et al. (2004) mixed calcium chloride microcapsules in hexahydrate into building cement and obtained a good temperature control effect.
In addition, salt hydrate microcapsule PCMs can also
be used for cooling electronic components (Wirtz R.A. etal., 2012; Kandasamy R. et al., 2008), waste heat recovery,
aerospace applications and so on.

Acknowledgements

5. Conclusions

Cabeza L.F., Castell A., Barreneche C., de Gracia A., Fernández
A.I., Materials used as PCM in thermal energy storage inbuildings: A review, Renewable and Sustainable Energy
Reviews, 15 (2011) 1675–1695. DOI: 10.1016/j.rser.
2010.11.018
Cao L., Tang F., Fang G., Preparation and characteristics of
microencapsulated palmitic acid with TiO2 shell as
shape-stabilized thermal energy storage materials, Solar
Energy Materials and Solar Cells, 123 (2014) 183–188.
DOI: 10.1016/j.solmat.2014.01.023
Fang G.Y., Chen Z., Li H., Synthesis and properties of microencapsulated paraffin composites with SiO2 shell as thermalenergy storage materials, Chemical Engineering Journal,
163 (2010) 154–159. DOI: 10.1016/j.cej.2010.07.054
Farid M.M., Khudhair A.M., Razack S.A.K., Al-Hallaj S., A
review on phase change energy storage: Materials andapplications, Energy Conversion and Management, 45(2004) 1597–1615. DOI: 10.1016/j.enconman.2003.09.015
Giraud S., Bourbigot S., Rochery M., Vroman I., Tighzert L.,
Delobel R., Poutch F., Flame retarded polyurea with microencapsulated ammonium phosphate for textile coating,
Polymer Degradation and Stability, 88 (2005) 106–113.
DOI: 10.1016/j.polymdegradstab.2004.01.028
Giraud S., Bourbigota S., Rocherya M., Vromana I., Tighzertb
L., Delobelc R., Microencapsulation of phosphate: Applica-

This review introduced the selection of core and shellmaterials, compared the different preparation methods ofencapsulated salt hydrate PCMs and summarized the application fields. Four types of preparation to successfully
prepare salt hydrate core-shell microencapsulation wereintroduced: the in-situ polymerization method, solvent
evaporation method, interfacial polymerization method
and sol-gel method. The research works on encapsulated
salt hydrate core-shell PCMs are relatively few comparedto those on organic core-shell microencapsulation. The
research has mainly focused on the study of the preparation methods, mostly using polymers as shell materials
because a polymer with a low coefficient of thermal conductivity will affect the heat transfer performance of microcapsule PCMs, a new type of inorganic shell materials
must be developed. Encapsulated salt hydrate core-shell
PCMs have not been applied at large scales yet, but these
PCMs have great potential application value. Therefore, itis necessary to strengthen the research on preparation
technology and actively expand its application fields.

This work was supported by the National Key Researchand Development Program of China (2016YFC0700905
and 2017YFC0703200) and Transformational Technologies for Clean Energy and Demonstration Strategic Priority Research Program of the Chinese Academy of
Sciences (Grant No. XDA21070302).

Nomenclature
DSP

Disodium hydrogen phosphate dodecahydrate

EA

Ethyl acrylate

MMA

Methylmethacrylate

PCMs

Phase change materials

PMMA

Polymethyl methacrylate

SDBS

Sodium dodecyl benzene sulfonate

SDS

Sodium dodecyl sulfonate

TEOS

Tetraethyl orthosilicate

TMPTA

Trimethylol propane triacrylateUF

Urea-formaldehyde resin

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Authors’ Short Biographies
Hui Wang
Hui Wang received her M.S. degree at Beijing University of Technology in 2012, andshe is currently a graduate student under the supervision of Prof. Minghao Fang in China
University of Geosciences (Beijing). Her research interests include inorganic phasechange materials.

Yunfa Chen
Yunfa Chen is Professor at the Institute of Process Engineering, Chinese Academy of
Sciences. He is President of the Chinese Society of Particuology, Vice-chairman of the
air pollution control industry technology innovation strategic alliance and Editorial
board member of the Particuology, Green Energy & Environment, etc. His research focuses on the preparation of nanostructured materials, porous functional materials, environmental purification materials, nanocomposites and their engineering applications.

Jianqiang Li
Jianqiang Li is Professor at the Institute of Process Engineering, Chinese Academy of
Sciences. He received his PhD from Tsinghua University in 2004. He worked as a JSPS
fellow at the Department of Materials, the University of Tokyo, from 2004 to 2006. His research mainly focuses on phase change materials, metastable inorganic functional materials, etc.

Lijiang Guo
Lijiang Guo is currently a Research Fellow at the Institute of Process Engineering,
Chinese Academy of Sciences. He received his PhD from Graduate University of Chinese
Academy of Sciences in 2012. Then, he worked at Qinghai Institute of Salt Lakes, Chinese
Academy of Sciences, until 2016. After that, he became a postdoctoral in Institute of Process Engineering, Chinese Academy of Sciences for two years. His research mainly focuses on phase change materials, solution chemistry, including phase diagram andthermodynamic model of aqueous solution.

Minghao Fang
Minghao Fang is Professor at School of Materials Science and Technology, China University of Geosciences (Beijing). He got his PhD from Tsinghua University in 2005. He
was a visiting scholar at college of engineering, University of Michigan, from 2011 to 2012.
His research mainly focuses on high-temperature protective materials, high-temperatureenergy-saving materials, advanced inorganic functional nano-material, etc.

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KONA Powder and Particle Journal No. 37 (2020) 97–113/Doi:10.14356/kona.2020013

Review Paper

Nanoparticle Technology for Respiratory Tract Mucosal
Vaccine Delivery †Leah M. Johnson 1, Jeffrey B. Mecham 1, Frederick Quinn 2 and Anthony J. Hickey 1,3*
1Center for Engineered Systems, RTI International, USA
Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, USA
3
Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, USA
2

Abstract
Immunization can be traced back to classical China. Modern immunization reduces the risk of infection byattenuating or killing the pathogen or using non-infectious antigens to elicit the immune response. The challengeof immunization is to raise a robust protective response without infecting the individual or overstimulating theimmune response, and this can be achieved by using nanoparticle delivery systems to specifically target the innate
immune system with known antigens and where necessary include an adjuvant to enhance the efficacy. Thesesystems can be targeted to mucosal sites that are located throughout the body with the nasal and pulmonary routesof administration allowing ease of access. Macrophages are the first line of defense of the innate immune system
and are the host cell for primary intracellular infection by several respiratory pathogens notably mycobacteria andstreptococci. The breadth of nanoparticle technology available to deliver vaccines has been explored andconsideration of its value in nasal and pulmonary delivery is addressed specifically.
Keywords: immunization, vaccine, nanoparticle, nasal, pulmonary, antigen

1. Introduction
Protection from disease by immunization was documented in classical China (Arouet F.M., (Voltaire), 1733).
Reports of the use of live organisms appeared in the eighteenth century most prominently by Jenner in preventing
smallpox using a cowpox-based vaccine from which theterm “vaccination” is derived (Smith K.A., 2011). Since
the discoveries of Koch in the late nineteenth century
vaccines have revolutionized disease prevention andhave significantly decreased infant and child mortality(Gradmann C., 2006). The observation that individuals
exposed to disease might develop immunity to future infection, and the initial steps at immunization were thefoundation for the field of immunology and the desire todevelop vaccines in the late nineteenth and early twentieth century. Advances in biotechnology combined withgreater understanding of infectious disease and host immunity have resulted in sophisticated approaches to vac†
1
2
3

*

Received 5 June 2019; Accepted 12 July 2019
J-STAGE Advance published online 24 August 20193040 Cornwallis Road, Research Triangle Park, NC 27709, USA
358 Vet Med, Biosciences Building, Athens, GA 30602, USA
Room1079, Genetic Medicine Building, Mason Farm Road, Chapel
Hill, NC 27599, USA
Corresponding author: Anthony J. Hickey;
E-mail: ahickey@rti.org
TEL: +1-919-541-6771

cine delivery and adjuvancy (Hoft D.F., 2008; Kaufmann
S.H.E., 2000).
The most prominent route of administration of vaccines
has been subcutaneous or intra-dermal injection. Vaccines also have been administered with adjuvant components intended to promote immunogenicity and elicit aprotective immune response. The most common adjuvants
were components of bacterial cell walls, such as Freund’s
adjuvant that contains materials originating from mycobacteria, or particulates such as alum (aluminum salts)(Dvorak A.M. and Dvorak H.F., 1974; Shah R.R. et al.,2017; Stils H.F., Jr., 2005).
As drug and vaccine delivery systems and knowledgeof immunity have improved new administration methods
and routes have been considered (Saallah S. et al, 2018).
Nanoparticle systems are known to offer unique biophysical opportunities to effectively deliver to antigen presenting cells at the site of administration. These particles may
be composed of a core inert non-degrading (waxes andplastics) substance to which antigen is adsorbed, or matrix degrading (natural and synthetic polymers) material
into which antigen is incorporated. It is now understoodthat there is a unique component of the immune systemthat is associated with mucosal sites (respiratory, gastro-­
intestinal and urogenital tracts). Consequently, as new
nanoparticulate vaccine delivery systems have been developed new routes of administration also have been

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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considered including the respiratory (nasal and pulmonary) and gastro-intestinal epithelia, sites of mucosal-­
associated lymphoid tissue. These alternative routes ofadministration offer the advantage of non-invasive ease ofadministration.
The history of nanoparticle manufacture overlaps withmicrosphere technology (Burgess D.J. and Hickey A.J.,
2007). The key components of natural and synthetic polymers had been clearly identified and all that was required
were processes to allow the manufacture of nanoparticles.
Since functionality of nanoparticles is often associatedwith smaller sizes a practical definition of 1–100 nm has
been adopted widely but clearly the scientific definition isderived from fundamental length dimension of particles
in sizes smaller than 1,000 nm (Commissioner O.o.t.,
2014; Nishijima N. et al., 2017).
Vaccines have been developed primarily to viral andbacterial pathogens. Natural immunity proceeds though
the innate and adaptive/acquired immune systems. Processing of the whole vector or organism allows specificcomponents to be isolated as identifying antigens that theimmune system employs as recognition factors to drive
clearance of infection and long-term immunity.
As the first line of defense the innate immune systemof phagocytic cells have been the target for engineered
solutions to vaccine delivery. Monocytes and macrophages are known to take up particles. From the later
1980s studies began to explore the interaction between
particles and phagocytic cells to evaluate the ability totarget these cells either through particle size alone or a
combination of size and targeting moieties.
This review will consider manufacture and characterization of nanoparticle-based vaccine delivery systems,
and the immunological consequences leading to protective immunity when delivered by different routes of administration.

2. Design and manufacturing of nanoparticlebased vaccines
The development of nanoparticle-based vaccine(nano-vaccine) delivery systems requires consideration ofseveral factors: route of administration, formulations,passive or active targeted delivery, efficacious dosing, andrequired frequency of vaccine exposure. The material
composition, the method of manufacture and processing
parameters all contribute to key physicochemical properties including the architecture with respect to antigen presentation for nanoparticle-based vaccines. This section
will briefly review the structures of nanoparticles andprovide a concise overview of the design and compositionof nanocarriers for delivery of vaccines, with an emphasison those delivered through the mucosal route of adminis-

98

tration. A description of the manufacturing and characterization of nanoparticle-based delivery systems will
follow.

2.1 Mechanisms of controlled presentation from acarrier
The mechanism for controlled presentation from a carrier vehicle is intimately linked to various parameters of
the system. Requirements for temporal and spatial controlof the biologically active ingredient (BAI) in vivo ultimately dictate design features, including formulations(e.g., drug, antigen, excipient, adjuvant), carrier material(e.g., polymer), and the architectural arrangements of individual constituents. As reviewed elsewhere (Uhrich
K.E. et al., 1999), temporally-regulated presentation of
BAI is achieved by prolonging exposure of BAI to thesurrounding environment. Two exemplary mechanisms
can delay BAI presentation from a carrier: using the polymer vehicle to control diffusion of the BAI into the surrounding environment or by via slow erosion of thevehicle itself to delay delivery of BAI. For the diffusion-­controlled mechanism, the release rates of BAI froma carrier vehicle is controlled by imposing physicalbarriers to transport (e.g., polymeric materials). In one
example, reservoir-style vehicles have designated compartments for the BAI and carrier material and use a permeable polymer membrane to control BAI release. A
wealth of examples exist for diffusion-controlled arrangements, including particle-based systems (Kamaly N.
et al., 2016) and implantable systems (Bourges J.L. et al.,2006; Croxatto H.B., 2002; Htay T. and Liu M.W., 2005;
Malcolm R.K. et al., 2012). The second temporally-­
regulated mechanism involves delaying the exposure of
BAI into the environment through controlled erosion of
the carrier polymer (e.g., polyester, polyanhydride). Degradation mechanisms typically involve hydrolysis to reduce the polymeric molecular weight and facilitate releaseof the BAI (Kamaly N. et al., 2016).

2.2 Design and composition of nanoparticles for
vaccine delivery
Given the breadth of nanoparticle-based delivery of
vaccines (Zhao L. et al., 2014), a comprehensive review of
each system is outside the aim of this review. This section
will instead highlight nanoparticle vehicles for delivery of
vaccines via the mucosal route of administration. We will
review two broad categories of nanocarriers: polymericnanoparticles and lipid-based nanoparticles.
Polymer Nanoparticles. Nanoparticles comprising
polymers are broadly categorized based on the source
material: natural or synthetic. Naturally sourced polymers
commonly include polysaccharides sourced from animals,Leah M. Johnson et al. / KONA Powder and Particle Journal No. 37 (2020) 97–113

plants, or microorganisms that are biocompatible and biodegradable (Tiwari P. et al., 2014). Natural polymers,
however, can carry disadvantages including possibility
for unpredictable rates of degradation, unintended immunogenicity, microbial contamination, differences between
batches, and poor mechanical strength (Bhatia S., 2016).
Despite the potential for undesirable attributes, naturally-­sourced polymers are successfully employed in various
applications for drug delivery, tissue engineering, andwound dressings.
Chitosan, which is sourced from crustaceans, exists asa cationic polysaccharide at low pH and can complex withnegative polyions to produce polyelectrolytes useful as
carriers for drug delivery (Hamman J.H., 2010; Nagpal K.
et al., 2010; Pandey R. and Khuller G.K., 2004). Chitosan
nanoparticles have been explored for various vaccines(Illum L. et al., 2001), including Mycobacterium tuberculosis (MTB) (Feng G. et al., 2013), diphtheria (van derLubben I.M. et al., 2003), pertussis (Jabbal-Gill I. et al.,1998) influenza (Amidi M. et al., 2007; Sawaengsak C. etal., 2014), and pneumococcal diseases (Xu J. et al., 2011).
Chitosan contains chemical groups, such as primaryamines, which permit conjugation of different moieties
onto the nanomaterial carrier for targeted applications(Chua B.Y. et al., 2012; Mohammed M.A. et al., 2017;
Zhang X. et al., 2008). Another polysaccharide, theseaweed-derived alginate, comprises repeating units of
α-L-guluronic acid and β-D-mannuronic acid and showswidespread utility as commercial wound dressings anddrug delivery vehicles (Thomas S., 2000; Tønnesen H.H.
and Karlsen J., 2002). Nanoparticles comprising alginate
have been explored for vaccine delivery (Sarei F. et al.,2013), and also show utility as a coating for chitosan
nanoparticles to improve stability of oral mucosally delivered vaccines (Borges O. et al., 2005; Liu Z. et al., 2013).
Guar gum, a polysaccharide comprising segments ofmannose and galactose, is resilient to human gut enzymes
while remaining susceptible to degradation by microflorain the human intestine, which makes this polymer beneficial for targeted delivery to the colon (Prasad Y.V. et al.,1998). Formulations of guar gum have been used to deliver active pharmaceutical ingredients (APIs) to the colon, such as flurbiprofen to treat inflammation (Vemula
S.K. and Bontha V.K., 2013) and methotrexate for coloncancer (Chaurasia M. et al., 2017) and for oral delivery of
Ag85A antigen for tuberculosis vaccination (Kaur M. etal., 2015). A plant-based polysaccharide, pectin, is composed of a linear backbone of α-1,4-linked D-galacturonic
acid (GalpA), in combination with diverse structural arrangements of branched regions (Liu L. et al., 2007). Pectin formulations can readily gel with mucin present within
the nasal cavity, making this polymer useful for nasal
drug administration (Morris G. et al., 2010; Watts P. andSmith A., 2009). Another natural polymer, gelatin, is pro-

duced through partial hydrolysis of collagen acquired
from animal sources (Tiwari P. et al., 2014). Gelatin
nanoparticles modified with polyethyleneimine (PEI), ovalbumin, and an immunostimulant were examined for anasal administered vaccine (Lin S.F. et al., 2018).
Synthetic polymers represent the second source of materials used to fabricate polymeric nanoparticles. Contrary to natural polymers, synthetic polymers benefit fromthe ability to strictly tailor design parameters and synthetic steps to ultimately meet targeted product profiles interms of mechanical properties, biodegradation timeframes, and purity. Synthetic polymers are either biodegradable or non-biodegradable with each category holding
unique advantages for the intended drug delivery system.
Biodegradable synthetic materials are briefly reviewed
here in the context of mucosal vaccine delivery.
The well-known family of biodegradable polyesters
that include poly (lactic acid) (PLA), poly (glycolic acid)(PGA), and the accompanying copolymer (DL-lactide-coglycolide) (PLGA) have been extensively studied and usedin various biomedical applications and FDA-approved
products, as reviewed elsewhere (Kapoor D.N. et al.,2015; Makadia H.K. and Siegel S.J., 2011). Delivery of
BAIs from a PLGA copolymer involves bulk erosion via
hydrolysis, which releases entrapped BAI. The hydrolytic
erosion and the ensuing release rates of BAIs are tuned
via polymer molecular weight, quantity of lactide andglycolide groups, crystallinity, and composition of endgroups. PLGA nanoparticles have been explored as carriers in a multitude of examples, including for oral andpulmonary vaccination against hepatitis B (Gupta P.N. etal., 2007; Mishra N. et al., 2011; Thomas C. et al., 2011),
ocular and nasal delivery of influenza antigens (Alkie T.N.
et al., 2018), and microparticles for pulmonary vaccination against tuberculosis (Shi S. and Hickey A.J., 2010).
Another biodegradable polyester, Poly-(ε-caprolactone)(PCL), is a hydrophobic semicrystalline polymer that undergoes bulk degradation in aqueous environments. As
compared to PLGA, the homopolymer of PCL typicallyexhibits longer timeframes for degradation and bioresorption (e.g., 2–4 years dependent on the molecular weight)(Woodruff M.A. and Hutmacher D.W., 2010). Nanoparticles comprising PCL have been explored for intranasal
and intramuscular delivery of diptheria toxoid (Singh J. etal., 2006) and nasal administration of the influenza A
H1N1 hemagglutinin protein (Gupta N.K. et al., 2011).
Polyanhydrides (PAs) are another class of synthetic
polymers used in delivery systems (Tamada J. and LangerR., 1992). Since anhydride groups are highly susceptible
to hydrolytic cleavage, polymer degradation occurs fasterat surfaces exposed to aqueous environments resulting in
BAI release from PA vehicles via surface erosion (Jain J.P.
et al., 2008). Degradation rates of PAs vary based on thecomposition of the polymer, which is readily tailored by99

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selection of monomers (e.g., aliphatic, aromatic) and useof copolymers (Jain J.P. et al., 2008). Numerous studies
have used PA nanoparticles for intranasal delivery of vaccines (Irache J.M. et al., 2010; McGill J.L. et al., 2018;
Zacharias Z.R. et al., 2018).
Lipid-Based Nanoparticles. In addition to polymericnanoparticles, lipid-based nanoparticles are widely used
for delivery of drugs and vaccines (Bulbake U. et al.,2017; Puri A. et al., 2009; Romero E.L. and Morilla M.J.,
2011). Liposomes are one type of lipid-based nanoparticle,
comprising spherical vesicles that self-assemble into alipid bilayer around a core of BAI. The physicochemical
properties of liposomes are readily customized thoughchoice of amphipathic lipids, which typically comprise
phospholipids (e.g., phosphatidylcholine) or cholesterol.
Although intramuscular injection is the common route ofadministration for liposomal vaccines, intranasal delivery
has also been explored (Bernasconi V. et al., 2016).
Solid lipid nanoparticles (SLNs) are another category of
lipid-based carriers useful for delivery of BAIs. The composition of SLNs include biocompatible materials (e.g.,
triglycerides, waxes), which are assembled into nanoparticles using scalable manufacturing processes, such as
high-pressure homogenization (see below). SLNs show
utility as mucosally-administered delivery systems, as
demonstrated with SLNs comprising carnauba wax for
intranasal vaccines against tuberculosis (Stylianou E. etal., 2014) and as intranasal carriers of the HIV-gp140 antigen (Arias M.A. et al., 2011).
The association of BAIs within these nanoparticle systems is schematically shown in Fig. 1. The hypotheticallocation of the antigen and any molecular adjuvant withina nanoparticle system can vary, depending on the material
composition and method of manufacture. Fig. 1(a) showsthe embedding of the antigen in a polymer matrix resultant of a solvent evaporation technique of the in situ polymerization approach. Fig. 1(b) illustrates surface
associated antigen that would occur as a result of passive
physical adsorption or using covalent binding at the sur-Fig. 1100

Schematic of general structure of nanoparticles with (a)matrix embedded antigen; (b) surface antigen; (c) matrix embedded adjuvant and antigen; (d) matrix adjuvant surface antigen; (e) matrix antigen surface
adjuvant; and (f) surface antigen and adjuvant.

face. Fig. 1(c–d) show the potential combinations of antigen and molecular adjuvant (often bacterial protein or cellwall component). Fig. 1(c) and (d) require considerationof the release rate of both antigen and adjuvant to ensurethat the kinetics of presentation to the immune system assure the required synergy. Fig. 1(e) is unlikely to offer thefull benefit of the presence of the antigen since it would
likely clear from the surface before significant antigen
presentation occurred. Fig. 1(f) would require mechanisms of long-term attachment to the particle surface thatwould allow time for antigen and adjuvant presentation.
The kinetics of desorption or erosion, for covalently
linked molecules should not be instantaneous for thisstructure to be useful. In general, the examples shown in
Fig. 1(a) to 1(d) are more practical than 1(e) and 1(f).

2.3 Methods of nanoparticle manufacture
Development of nanoscale materials is considered amodern technology, but their first uses can be traced backto the 4th century (NNI, 2019). In more recent history,
Michael Faraday described the optical properties ofnanometer-scale metals in 1857 (Faraday M., 1857), andover fifty years later, in the first years of the 20th century,
Beilby (Beilby G.T. and Neville F.H., 1904) and Turner(Turner T. and Poynting John H., 1908) separately demonstrated that visibly transparent highly conductive metallic
films could be fabricated using Faraday’s methods.
Nanoscale materials development gained momentum 42
years later, when La Mer and Dinegar published a process
to grow monodisperse colloids, in 1950 (Lamer V.K. andDinegar R.H., 1950), with nanoscience finally being internationally recognized later in the 20th century with the1985 Nobel Prize for the development of the “buckyball”
by Richard Smalley and his team at Rice University(Heath J.R. et al., 1985; Kroto H.W. et al., 1985; Zhang
Q.L. et al., 1986). One year earlier, Bell Labs’ Louis Brusdeveloped semiconductor nanocrystals (Brus L.E., 1984),
known as “quantum dots”, which was later awarded the2008 Kavli Prize in Nanotechnology. Completing the major developments in nanoscale materials in the 20th century, NEC’s Sumio Iijima developed the carbon nanotube
in 1991 and shared the 2008 Kavli Prize with Brus.
Since that time, synthetic nanoscale materials haveseen continuous development using two major strategies:
top-down/mechano-physical or bottom-up/chemo-­physicalmethods. Top-down methods are generally subtractive
techniques, where larger materials are ground down tosmaller materials through milling or grinding. Conversely, bottom-up techniques arrange smaller constituents into larger and more complex assemblies. This latterapproach enables the use of building blocks such as individual molecules that can self-assemble into larger organized arrays or monomers that can be polymerized into

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more targeted conformations and architectures such as
nanoparticles for drug delivery (Antonietti M. andLandfester K., 2002; Kumari A. et al., 2010; Limayem I.
et al., 2004; Reis C.P. et al., 2006). The nanoparticle formation process can be achieved through numerous techniques and processes that often include self-assembly and/or molecular-assembly polymerization techniques. Someof the more widely used methods involve microfluidics,
dispersion of pre-formed polymers and polymerization ofmonomeric polymer pre-cursors.
Microfluidics is a technique that utilizes miniaturized
systems to process extremely small volumes of fluids (aslittle as 10 –14 ml), by means of flow channels with dimensions from ten to several hundred microns. A paper published in Nature in 2006 discussed how this emerging
technique could be leveraged in molecular biology, pharmaceutical manufacturing, molecular analysis, biodefence, and microelectronics (Whitesides G.M., 2006).
Over 12 years later, microfluidics has been utilized as aprocessing technique in many different areas, including
the production of nanoparticles (Baroud C.N. et al., 2010;
Beebe D.J. et al., 2002; Di Carlo D., 2009; Lee J.N. et al.,
2003; Lin Y.W. et al., 2015; Stroock A.D. et al., 2002). The
microfluidic technique enables the rapid mixing of reagents and precise control of temperature and reagent dynamics, resulting in the production of a much narrower
size distribution than bulk synthesis methods (Lim J.M. etal., 2014). The fine control and high degree of homogeneity provided by the microfluidic synthesis are responsible
for the resulting smaller particle size and lower polydispersity (Valencia P.M. et al., 2012). Typically, microfluidic
synthesis is used to produce small volumes of nanoparticles, but some high throughput systems have been developed that are capable of scale-up (Lim J.M. et al., 2014).
Several nanoparticle manufacturing methods have beendeveloped that involve the controlled dispersion of preformed polymers. Solvent evaporation was one of the first
methods developed to form nanoparticles from a preformed polymer (Vanderhoff J.W. et al., 1979). Further development has been fostered by pharmaceutical chemists
in the production of drugs (Gurny R. et al., 1981). Thismethod uses solutions of polymers in volatile organic solvents into which the drug is loaded and dispersed. To thisorganic phase, water and surfactant are added and thecomplex mixture is agitated to from an emulsion(Allemann E. et al., 1993; Anton N. et al., 2008; Beilby
G.T. and Neville F.H., 1904). Upon evaporation of the organic solvent from the emulsion, via agitation or reducedpressure, a nanoparticle suspension is formed. Emulsion
methods can employ a typical single emulsion route involving an oil-in-water approach (o/w), as describedabove, or a double emulsion (water-in-oil) in-water (“W/O/W”) approach. In either case, the aqueous phase contains the stabilizer/surfactant and the organic solvent con-tains the pre-formed polymer phase. Both methods
require high shear agitation methods, such as ultrasonication or homogenization, to ensure that the emulsified reaction contains dispersed domains on the nanoscale, as
these become the nanoparticles upon removal of the organic phase by evaporation under reduced pressure or via
extended stirring. The resulting nanoparticles can then be
removed and collected from the aqueous phase using ultracentrifugation or lyophilization. Scale-up of this approach can be challenging due to the need for high shear
agitation and the requirement that the drug be oil-soluble.
A second method that utilizes pre-formed polymers has
been termed the nanoprecipitation or the solvent displacement method (Fessi H. et al., 1989). This method involves
the interfacial deposition of a polymer via the displacement of a semi-polar water-miscible solvent such as
ethanol or acetone which can be easily removed byevaporation with continued stirring (Mishra B. et al.,2010; Reis C.P. et al., 2006). The surfactant again resides
in the aqueous phase and a narrow size distribution canbe achieved by slow addition of the organic phase to thesurfactant-containing aqueous phase, or vice-versa, while
the size of the nanoparticles is a function of the type of
surfactant used (i.e., ionic, amphiphilic or non-ionic)(Fessi H. et al., 1989; Limayem I. et al., 2004). The natural pre-formed polymers chitosan and alginate require adifferent synthesis method involving ionotropic gelation.
To prepare chitosan nanoparticles, chitosan is acidified toa pH of 4–6 to render it water-soluble to which an alkaline
solution of sodium triphosphate (pH 7–9) is added. To
produce a high yield of stable solid nanometric structures,the chitosan to sodium triphosphate weight ratio should
target a range of 3:1 to 6:1. The synthetic conditions required to produce a high yield of nanoparticles with a targeted nanoscale size vary significantly as a function of
the purity, acid-salt form and overall molecular weight ofchitosan utilized, which requires that the formulation parameters be optimized for each chosen chitosan type
(Janes K.A. et al., 2001). Alginate particle formation istriggered by divalent metal containing salts, such as calcium chloride. Like chitosan, the reaction to form alginate
nanoparticles of targeted size involves precisely controlling the concentration/viscosity of the alginate solution, counter-ion concentration, and the speed of its
addition to the alginate, making it difficult to replicate theresulting particles with the degree of precision that othertechniques afford (Kaloti M. and Bohidar H.B., 2010).
One way to mitigate the synthetic challenges that chitosan
and alginate pose is to use them as surface modifiers in
pre-formed nanoparticles made from a different polymer.
Using this approach, researchers were able to decorate
the surface of PLGA-based nanoparticles with cationicchitosan and anionic alginate to facilitate the controlled
release of resveratrol (Sanna V. et al., 2012) using a101

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layer-by-layer nanoprecipitation method (Zhou J. et al.,2010). Images of particles produced via this approach are
shown in Fig. 2. PLGA-based nanoparticles, like related
PLA, Poly-L-Lactic Acid (PLLA), and PCL and polyanhydride nanoparticles, release their cargo via a hydrolysis
mechanism.
When exposed to water, the polymer chains are hydrolyzed, or cut, at the ester-bond (Ikada Y. and Tsuji H.,
2000) (PLGA, PLA PLLA, PCL), or anhydride-bond(Whitaker-Brothers K. and Uhrich K., 2006). This chain
scission event results in degradation of the mechanicalproperties of the polymer, with continued hydrolysis
events degrading molecular weight to the point that the
products can be removed from the body and excreted(Uhrich K.E. et al., 1999).
Most of the methods used to prepare polymericnanoparticles use organic solvents. In order to minimizerisks associated with their use, supercritical fluids can besubstituted (Aboubakar M. et al., 1999). Supercritical fluids possess a critical temperature, above which the fluid
remains a fluid, regardless of pressure. Supercritical carbon dioxide (SCO2) is used very frequently due to its relatively mild supercritical conditions of 31.1 °C and 72.9 bar(1057.3 psi). The low polarity of SCO2 facilitates high solubility of hydrophobic drugs which can then be sprayedthrough a capillary in a method called the Rapid Expansion of Supercritical Solution (RESS) process (Larson
K.A. and King M.L., 1986). The rapid expansion of thesolution into an ambient environment results in the generation of nanoparticles. This method was first developedfor inorganic particles before being used with pre-formed
polymeric materials (Al-Kassas R. et al., 2017; Anton N.
et al., 2008; Padrela L. et al., 2018; Williams H.D. et al.,Fig. 2

102

Scanning electron microscopy images of PLGA
(poly(d,l-lactide-co-glycolide)) (A), PLGA-CS1 (chitosan) (B), PLGA-CS2 (C), PLGA-CS3 (D), PLGA-Alg1 (alginate) (E), PLGA-Alg2 (F), and
PLGA-Alg3 (G) Resveratrol-loaded nanoparticles. All
scale bars represent 500 nm (Sanna V. et al., 2012). Reprinted with permission from the original publisher
Dove Medical Press LTD.

2013). Conversely, SCO2 can also be used as an anti-­
solvent, or precipitant, during the nanoparticle fabrication
process. This method is applicable to drugs that do notdissolve well in SCO2 in a method called the Supercritical
Anti-Solvent Process (SAS), where the SCO2 is passed
through the drug solution. Addition of SCO2 expands theorganic drug solution, causing the drug to precipitate,
thereby leaving the precipitated nanoparticles free fromany residual solvent (Reverchon E. et al., 2007).
In contrast to the methods described above that utilizepre-formed polymers, polymerization of monomeric materials provides a much greater degree of control over the
final properties of the produced nanoparticle. Emulsion
polymerization, a free-radical chain growth method, isthe most common route used in global production of polymers and is also a widely used nanoparticle production
route. In conventional emulsion polymerization, water isused as the dispersion medium, a surfactant is used todisperse the water-insoluble monomers in the water and awater-soluble free radical initiator is used to trigger thepolymerization chain reaction (Thickett S.C. and Gilbert
R.G., 2007). The conventional emulsion approach typically results in particles that are in the range of 50–
250 nm (Asua J.M., 2004; Garay-Jimenez J.C. et al., 2009;
Reis C.P. et al., 2006). The use of surfactants with this approach requires the removal of the surfactant materials
from the final product that can be costly at scale. To address this, surfactant-free emulsion techniques have beendeveloped where the initiator is water soluble and themonomers are typically vinylic or acrylic. While this approach is attractive as a polymerization method, nanoparticle size and polydispersity are more difficult to control,
due to the absence of surfactant (Zhang G.Z. et al., 2001).
In contrast, the mini-emulsion polymerization techniquealso utilizes water as the dispersion medium, as well aswater-soluble surfactants and water-insoluble monomers.
This approach differs in its use of a high shear device,
such as an ultra-sonicator, and low a molecular weightco-stabilizer, due to the high interfacial surface tension of
the system. For the polymerization of methacrylate(Mouran D. et al., 1996) and n-butylacrylate (Leiza J.R. etal., 1997), sodium laurylsulfate/dodecylmercaptan and sodium dodecylsulfate/hexadecane was used, respectively,
as the surfactant/co-stabilizer systems. Micro-emulsion
polymerization, while similar to the mini-emulsion approach, produces particles of smaller size and with fewer
polymer chains per particle. In some cases, particles as
small as 5–50 nm can be produced using this technique(Antonietti M. and Landfester K., 2002). Despite the potential of this nanoparticle synthesis method, micro-­emulsion has seen limited commercial use due to thedilute concentration of polymer and the use of surfactants
that typically exceed the monomer concentration in thispolymerization approach. Interfacial polymerization is a

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step growth polymerization approach that can be used togenerate nanoparticles (Aboubakar M. et al., 1999;
Vauthier C. et al., 2003). Interfacial polymerization involves the step-growth polymerization of two monomers
that are soluble in two phases, one dispersed and one continuous, where the reaction occurs at the interface of thetwo liquid solvents (Karode S.K. et al., 1998). Nanocapsules containing an oil-based core can be formed (Fallouh
N.A. et al., 1986), as can nanocapsules with an aqueous
core (Gasco M.R. and Trotta M., 1986; Watnasirichaikul
S. et al., 2000). Though the production of polymer-based
nanoparticles has been well demonstrated, precise control
of nanoparticle size and polydispersity remain as challenges with this polymerization technique.
From the brief review described above, it can be understood that neither the top-down nor the bottom-up
synthetic approach is preferable when scale-up to manufacturing volumes is considered. Rather, the applicable
synthetic technique is driven by considering the solvation
conditions required to properly drive the cargo into theencapsulation system. Therefore, solvent considerations,in tandem with nanoparticle dimensional requirements,
ultimately drives the choice of the synthetic scale-up approach.

2.4 Methods of nanoparticle characterization
The quality of the particulate system employed to deliver antigen and elicit an immune response must be assured and depends upon the particle size distribution, theinoculum (dose), and morphology (shape and surface
characteristics). Specialized techniques are required toassess each of these features. For nanoparticle systems theprimary method of particle size determination is dynamic
light scattering (DLS). This is typically the first techniqueused to characterize the nanoparticles and provides information about their size and size-distribution, with the latter typically referred to as the particle polydispersity.
Results from the DLS method can be qualitatively confirmed by transmission (TEM) and scanning electron microscopy (SEM), which also allows assessment of themorphology and shape of the nanoparticles. SEM generates an image of the particles by scanning it with a focused beam of electrons which, when scattered, gives
information on surface morphology and surface composition. TEM accelerates electrons to nearly the speed oflight and transmits them through the sample in a fashion
similar to an optical light microscope. This techniqueprovides information about the morphology of the sample,
as well as information about the internal composition of theparticle to identify crystallinity and magnetic domains.
Atomic force microscopy (AFM) provides information
about the particle surface via the use of a sub-micronprobe tip. Using the probe tip in contact mode, a topo-

graphical map of the particles can be generated. Using
non-contact mode requires the tip to hover over the sample area of interest and is very useful for analyzing fragile
biological and polymeric nanostructures (Mu L. and Feng
S.S., 2003).
A variety of surface analytical methods can be performed and the release of the antigen and adjuvant can be
conducted in dissolution media under appropriate conditions (pH, simulated gastric or pulmonary fluid) for theroute of administration with a relevant analytical method.
Methods include mass spectroscopy and electropho­
retic approaches, such as sodium dodecyl sulfate-­polyacrylamide gel electrophoresis (SDS-PAGE).

3. Delivery/Target-respiratory/Phagocytic cellsystem
3.1 Routes of administration
In order to be capable of engaging the key elements ofinnate and adaptive immunity, antigens must be processed and presented to immune cells. Antigen presentation is mediated by MHC class I molecules, and the class
II molecules found on the surface of antigen-presenting
cells and certain other cells. The Major Histocompatibility Complex-Class I (MHC-I) processing pathway islargely geared toward presentation of endogenous antigens encountered in the cytoplasm of most cell types.
Peptides derived by cytosolic proteolysis of such antigens
are translocated into the endoplasmic reticulum where
they encounter and may assemble with newly synthesized
MHC-I molecules. MHC class II molecules are expressedby antigen presenting cells, such as dendritic cells andmacrophages. MHC class II molecules bind to peptides
that are derived from proteins degraded in the endocytic
pathway (Mantegazza, A.R. et al., 2013).
The most common routes of administration for vaccines are parenteral, notably intra-muscular, intra-dermalor sub-cutaneous. However, there is increasing interest in
mucosal routes of administration (Youngren-Ortiz, S.R.
et al., 2017). Targeting of M-cells in the nasal mucosa,
macrophages and dendritic cells in the lungs, and Peyer’s
patches in the gastro-intestinal tract have been studied
extensively in the last 25 years (Calderon-Nieva D. et al.,2017; Jia Y. et al., 2015; Padilla-Carlin D.J. et al., 2008). It
is generally believed that nanoparticles are the most effective way to target the antigen presenting cells and thecells of the phagocytic mononuclear cell system (Fig. 3).
There are safety considerations related to the use of
nanoparticle therapeutics that are beyond the scope of thepresent review (Somasundaran P. et al., 2010; Sayes C.M.,
2014).

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3.2 Innate immunity
The innate immune system provides the first line of defense against foreign microbes, particularly on mucosal
surfaces, skin and at other interface areas. The mononuclear phagocytic system, or reticuloendothelial system, ischaracterized by monocytes and macrophages. The cell
types are often identified specifically by historical reference, e.g. Kupfer or Langerhans cells in liver and skin,respectively, or anatomical location, e.g. alveolar or
peritoneal macrophages. Phagocytic cells are responsible
for the initial uptake and clearance of pathogens and exogenous debris. They are considered housekeeping cells
as their role is to maintain the integrity of the physiological milieu. A variety of processes are mediated by phagocytic cells. These phagocytic cells are complemented byubiquitous antigen presenting, dendritic cells. Thus,
monocytes, macrophages, neutrophils and other granulocytes, Kupfer and Langerhans cells, and dendritic cells
are key players in the innate immune response. A variety
of processes are mediated by phagocytic cells. In the context of eliciting an immune response, these cells are active
against infectious materials through two major pathways:
Phagolysosomal trafficking and the production of cytokines and chemokines. Phagolysosomal trafficking initiates intracellular killing of internalized pathogens
through targeted production of reactive oxygen and nitrogen species, while cytokine and chemokine secretion suchas TNF-α and IFN-γ can kill pathogens by recruiting andinducing specific cytotoxic immune cells (Newton A.H.
et al., 2016; Ritchie A.I. et al., 2016).

Fig. 3104

Furthermore, the structure and composition of the adsorbed vaccine targets on the nanoparticle surfaces could
be important for optimal MHC I and MHC II antigen presentation. In this regard, nanoparticles may elicit responses after surface interactions or after becominginternalized by the various phagocytic cell types.
Nanoparticle characteristics such as size, shape, composition, degradation profile and overall consistency may influence uptake and subsequent immune responses. For
example, it has been shown that TiO2 nanotubes with adiameter of 30 nm produced less inflammation compared
to 80 nm (Lu W.L. et al., 2015). Alternatively, similar surfaces with a diameter of ~78 nm attenuated the inflammatory activity of macrophages (Ariganello M.B. et al.,2018). Therefore, outcomes cannot simply be predictedbased only on the size or surface features, but rather
nanostructured topography must undergo an evaluation to
obtain a reliable indication of inflammatory potential(Fig. 3).
In addition, complement activation and the inadvertentbinding of lipopolysaccharide to nanoparticles are important to consider as this may skew the outcome and interpretation of studies and have an impact on safety. Thus,a better understanding of the induction mechanisms forthe specific processes could pave the way for improved
vaccination strategies via nanoparticles.

3.3 Acquired immunity
Acquired or adaptive immunity is driven by T and
B-lymphocytes, the former generating natural killer andSchematic depiction of antigen presenting cell interaction with pathogen/vaccine particulate subsequentcell response. Grey shading indicates antigen processing pathways by the lysosome or following lysosomal escape promoting MHC-II and MHC-I antigen presentation.

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other T-cells, and the latter producing antigen specific antibodies. This component of the immune system results ina memory of previous exposures that generates protective
immunity to future infections. Additionally, citrate-­
buffered silver coated nanoparticles were shown to bephagocytosed by dendritic cells and macrophages, either
derived from the peripheral lymph nodes or as cell lines(Njoroge J.M. et al., 2018). Work with the J774 mouse
macrophage cell line demonstrated that the endocytosis of
57 nm PEG-treated silver-coated nanoparticles is dependent upon actin and clathrin-mediated endocytosis (Kuhn
D.A. et al., 2014). Also, 24-hour exposure to thesenanoparticles will induce elevated oxidative stress as
demonstrated by ROS formation in Jurkat T cells (Manke
A. et al., 2013). U937 human monocytic cells exposed topolyvinylpyrrolidone-treated silver nanoparticles demonstrated apoptotic cell death and ROS formation, however,the cellular effects were dependent upon the size of theparticle (Abdal Dayem A. et al., 2017). Other studies using primary human monocytes have similarly demonstrated a particle size-dependent effect. In these studies,
the smaller coated nanoparticles induced greater levels of
the pro-inflammatory cytokines (Elsabahy M. and Wooley
K.L., 2013). Active uptake of nanoparticles by alveolar
macrophages is enhanced by their presentation in micron-­sized aggregates whereas nanoparticles are preferentiallytaken up by DCs in the respiratory tract.
As described earlier T cell activation by coatednanoparticles is impacted by the size, other physical aspects, and the ability of the nanoparticles to stimulate innate immunity. However, many questions remain fortherapeutic vaccine development requiring acquired immunity. For example, it is critical to determine how topromote a T effector response, but not a T regulatory response, in an immunosuppressive microenvironment.
Fine-tuning the balance between the strong T cell responses and auto-immune side effects will also be a key
challenge.

3.4 Vaccines
The strongest immune response will be raised to wholeorganisms that present all antigens such that a robust
heterogeneous immunity can be achieved. Live virulent
organisms typically generate natural immunity in
immunocompetent individuals. The risk of infection issuch that living organisms are usually attenuated in termsof virulence to give the host immune system an advantage. An alternative that preserves the entire antigen library but mitigates risk entirely is the use of whole
inactivated organisms.
The use of nanotechnology in vaccinology has beenleading to the birth of “nanovaccinology” (Zhao L. et al.,2014). In both prophylactic and therapeutic approaches,

nanoparticles are used as either a delivery system to enhance antigen processing and/or as an immunostimulant
adjuvant to activate or enhance immunity. Therapeutic
nanoparticle vaccines currently are mostly being applied
to cancer treatment (Krishnamachari Y. et al., 2011), andless for treating infections. Alternatively, prophylactic
nanoparticle vaccines have been applied for the prevention of different diseases, particularly infectious diseases.

3.5 Nasal and pulmonary vaccine delivery
Nanovaccines can be delivered to the mucosal surfaces
in the respiratory tract as liquid suspension or micro-­aggregated particles (Irvine D.J. et al., 2015). There is along history of nasal delivery of vaccines (Arouet F.M.,(Voltaire), 1733). Deposition in the nose is efficient withparticles greater than 5µm being easily collected. A suspension of nanoparticles might be delivered from a nasal
spray with a droplet median diameter of approximately
20µm, FlumistTM (Medimmune) is an example of thisstrategy (Yusuf H. and Kett V., 2017). The concentrationand stability of the nanoparticle suspension will dictate
the nature of presentation to local immune cells (asnanoparticles or nanoparticle aggregates). However, anideal suspension product would be formulated to allow astable homogeneous dispersion of nanoparticles. Pulmonary vaccine delivery required particle and droplet sizes
below 5µm (Hickey A.J., 2004). Nebulized droplets containing nanoparticles or dry micro-aggregated particles
can be used to deliver vaccines to the pulmonary mucosa(Osman N. et al., 2018).
One area of current interest is the use of the lungs as aroute of administration for vaccines to prevent tuberculosis. MTB is the primary causative organism of this disease. The mycobacteria present antigens that elicit naturalimmunity and can therefore be used for immunization. A
variety of approaches have been attempted including attenuated whole organism (attenuated Mycobacterium
bovis, Bacille Calmette Guerin) (Garcia-Contreras L. etal., 2008), sub-unit proteins (Lu D. et al., 2007), fusion
proteins (Shi S. et al., 2010,) and viral vectored genes(Tameris M.D. et al., 2013). The whole organism has one
dimension in the nanoscale and viral vectors are nanosized. It may be possible to adopt a nanoparticle strategy
to deliver mycobacterial antigens to the lung mucosa andprotect against disease. In this context the M. tuberculosis
heparin-binding haemagglutinin antigen has been adsorbed to wax particles and shown to successfully immunize mice (Stylianou E. et al., 2014). Delivery of particlesof this nature to the lungs may be a means of inducing anenhanced innate immune response.

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4. Conclusions and future perspectives
Vaccines for preventing or treating serious infectious
diseases have been employed for millennia. The emergence of knowledge in microbiology and immunology atthe end of the nineteenth century drove eradication ofseveral otherwise deadly diseases. Research in the twentieth century improved vaccines and expanded their application to many otherwise untreatable viral diseases.
However, some diseases have resisted significant vaccine
development:—Prominent among these are mycobacterial
diseases, such as tuberculosis and viral diseases such as
influenza. The advent of nanoparticle technology and experience with the delivery of antigen and adjuvant in or
attached to an organic matrix material potentially advances vaccine development. Moreover, interest in targeting the cell mediated immune system located at accessible
nasal and bronchial mucosal sites of the respiratory tract
offers a strategy for disease prevention that has rarely
been considered and might be advanced using nanotechnology.

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Authors’ Short Biographies
Leah M. Johnson
Dr. Leah Johnson is a Senior Research Chemist in the Engineered Systems (ES) Division at RTI International. Dr. Johnson leads a research team to develop advanced polymeric materials for controlled delivery applications. She has experience with designing
polymeric systems for applications in biosensing, tissue engineering, and drug delivery,
with recent programs involving subcutaneous implants for prevention of infectious diseases, controlled-release dental materials, and polymeric implants for islet transplantation. In her role at RTI, she collaborates with various groups from private industry,
academic institutions, and government agencies to advance material systems to earlystage technical products. Dr. Johnson received her B.S. (Biochemistry) from the University of Michigan and her Ph.D. (Biochemistry) from the University of Colorado. She helda Postdoctoral Fellowship at Duke University (Biomedical Engineering), where she developed a bio-separation processes for acoustic-mediated rare cell isolation andtriggered-release systems for tissue engineering. She previously held positions at Pfizer
working in the nuclear magnetic resonance (NMR) laboratories and at Gilead Scienceswhere she researched biological pathways of new pipeline antiretroviral (ARV) drugs
and led small molecule screening campaigns for ARV discovery efforts.

Jeffrey B. Mecham
Dr. Mecham is a Research Chemist in RTI International’s Center for Engineered systems, in the Technology Advancement and Commercialization Division. In this capacity,
he is responsible for the design and synthesis of monomers, polymers and particles (atthe micro- and nanoscale) with targeted performance capabilities for a wide array of
applications. His team are contributors to the Center’s successful development ofparticle-based controlled release technologies for triggered release of therapeutics andchemistries for environmental remediation. The development of such materials over thelast several years at RTI has resulted in IP that has been licensed by interested parties forfurther development and subsequent commercialization of particles with controlled release properties.

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Authors’ Short Biographies
Frederick Quinn
Dr. Quinn earned a BS from Marquette University, a MS and PhD in Microbiology
and Biochemistry from Indiana University, Bloomington and completed a postdoctoral
fellowship in Microbial Pathogenesis at Stanford University. He oversaw several laboratory groups at the Centers for Disease Control and Prevention in Atlanta investigating
bacterial disease outbreaks including Brazilian Purpuric Fever, Cat Scratch Disease, meningococcal meningitis, Buruli ulcer, and ultimately tuberculosis (TB). In 1999, Dr.
Quinn completed a Fullbright Fellowship studying TB pathogenesis at the University ofBristol in Great Britain. In 2002, he became Professor and Head of the Department ofMedical Microbiology and Parasitology (now Infectious Diseases) in the College of Veterinary Medicine at the University of Georgia. His research focuses on understanding
the pathogenesis of Mycobacterium tuberculosis, with the ultimate goal of developing
improved vaccines and diagnostic tests for TB. Current collaborative activities include
novel TB vaccine development and animal efficacy testing, animal model development
for disease transmission, and understanding TB social networking and zoonotic transmission patterns in TB endemic areas including Africa.

Anthony J. Hickey
Dr. Hickey is Distinguished RTI Fellow, at the Research Triangle Institute and Directorof the UNC Catalyst for Rare Diseases of the Eshelman School of Pharmacy He obtained
Ph.D. and D.Sc. degrees in pharmaceutical sciences from Aston University, Birmingham,UK. He is a Fellow of the Royal Society of Biology, the American Association of Pharmaceutical Scientists, the American Association for the Advancement of Science and theRoyal Society of Biology. He received the Research Achievement Award of the Particulate
Presentations and Design Division of the Powder Technology Society of Japan, the Distinguished Scientist Award of the American Association of Indian Pharmaceutical Scientists;
the David W Grant Award in Physical Pharmacy of the American Association of Pharmaceutical Scientists; Thomas T Mercer Joint Prize for Excellence in Inhaled Medicines andPharmaceutical Aerosols of the American Association for Aerosol Research and the International Society for Aerosols in Medicine and the Ralph Shangraw Memorial Award for
Excipient and Excipient Technology of the International Pharmaceutical Excipient Consortium Foundation. He is founder (and formerly President and CEO) of Cirrus Pharmaceuticals, Inc., acquired by Kemwell Pharma; founder (formerly CSO, 2002–2007) of Oriel
Therapeutics, Inc, acquired by Sandoz and founder and CEO of Astartein, Inc.; member of
the Pharmaceutical Dosage Forms Expert Committee of the United States Pharmacopeia
and formerly Chair of the Aerosols Expert Committee of the USP. Dr. Hickey conducts a
multidisciplinary research program in the field of pulmonary drug and vaccine delivery fortreatment and prevention of a variety of diseases.

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Review Paper

Fluidised Bed Reactors for the Thermochemical Conversionof Biomass and Waste †Stefano Iannello, Shane Morrin and Massimiliano Materazzi *1

Department of Chemical Engineering, University College London, UK

Abstract
The growing population and economic development globally has led to increasing resource consumption andwaste generation. This has generated concern at local, national and international levels on environmental issues
including air quality, resource scarcity, waste management (including plastics) and global warming. The resulting
antipathy towards fossil fuels and waste landfilling has spurred the demand for alternative bioenergy and biofuels
production methods, making use of abundant biomass and waste feedstock. Although not new concepts, there has
been renewed impetus recently to develop advanced thermochemical processes such as pyrolysis and gasification
to treat biomass and municipal solid waste (including refuse-derived fuel therefrom). This is because theseprocesses have the potential to add value to cheap and abundant materials by converting them into advanced
biofuels and chemicals. The work presented in this paper is concerned principally with the technical analysis andreview of new-generation, state-of-the-art systems based on fluidised bed reactors operated with biomass andsolid waste. A comprehensive assessment of fluidised bed reactor types and operations is considered, withparticular attention given to those processes aimed at the production of clean syngas for the subsequent synthesisof high-value products, including bio-hydrogen, synthetic natural gas (SNG), and liquid fuels.
Keywords: fluidised beds, waste, thermochemical processes, waste-to-fuels

1. Introduction
Biomass and municipal solid waste (MSW) feedstocks
arise in vast quantities, presenting a largely untapped resource. Harnessing the energy content of these feedstocks—a significant portion of which will be renewable­—offers significant environmental, economic and, indeed,societal benefits. While mass burning, for heat and/or
power generation, has been the traditional route, thermochemical methods including gasification and pyrolysis
open up a range of options from chemicals to synthetic
natural gas and transport fuels (Barbuzza et al., 2019).
This is becoming increasingly relevant given the drive tofind alternatives to fossil fuels and reduce CO2 emissions(Masnadi et al., 2015).
Thermochemical processes have been known and used
for centuries. Examples include the pyrolysis and gasification of coal as early as the 19th century (Kamble et al.,2019; Nie et al., 2017). The pyrolysis of coal producedcoke and a coal gas, while the gasification of coal pro†
1*

Received 15 May 2019; Accepted 16 July 2019
J-STAGE Advance published online 1 October 2019
Torrington Place, London WC1E 7JE, United Kingdom.
Corresponding author: Massimiliano Materazzi;
E-mail: massimiliano.materazzi.09@ucl.ac.uk
TEL: +44(0)2076797868

114

duced a combustible gas referred to as synthetic gas (syngas), or producer gas. In spite of this long history, thedevelopment of thermochemical technologies for processing biomass and waste materials has been relatively recent, driven by the demand for resource conservation andmore efficient energy recovery. In terms of feedstock handled by gasification plants worldwide, for example, biomass and waste represent a very small portion, with mostsynthesis gas production derived from fossil sources.
Notwithstanding this, the thermochemical treatment ofresidual biomass, including solid waste, has significant
potential in its own right. In this respect, they add value
to low- or negative-value feedstock by converting them tomarketable fuels and products (Materazzi and Lettieri,2017). Furthermore, while waste materials can present
challenges, they have certain economic benefits over otherbiomass. For instance, most waste sources are subject to agate fee for their disposal; collection systems tend to beestablished, the cost of which is normally incurred by thewaste producer. Finally, unlike certain biomass materials,
waste does not compete with the production of food(Matsakas et al., 2017).
Fluidised beds have historically been used in thethermal processing of solid fuels due to their flexibility
and good conversion efficiency. Today, they still offer
good prospects for a rapid deployment of new-generation

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Stefano Iannello et al. / KONA Powder and Particle Journal No. 37 (2020) 114–131

thermochemical treatments for advanced biofuel production. This review focuses on the application of fluidised
beds for a range of different thermochemical routes forthe conversion of waste biomass and MSW-derived feedstock into energy, gases or liquid fuels. A thorough assessment of fluidised bed reactor types and operational
process conditions is provided. Technologies aimed at the
production of clean syngas are given special attention,
keeping in mind the high value products generated, including bio-hydrogen, biosynthetic natural gas (bioSNG),
and liquid fuels.

2. Basics of thermochemical conversions
Thermochemical conversion technologies are used totransform wastes and biomass into commercial fuels andenergy by employing processes at high temperatures.
They include combustion or incineration, pyrolysis, gasification, and may include additional chemical processes
for the final fuel synthesis. Apart from other technologicalfeatures, the temperature and excess air quantity differentiate these thermochemical routes. Consequently, they
may generate CO2 and water as final products (maximum
generation of heat) or intermediate valuable products(mostly hydrocarbons and syngas). Gasification and pyrolysis are not new concepts; however, only in recent
years they have been applied to the treatment of solid materials (Materazzi, 2017). These processes can also be
employed to produce syngas (namely H2 and CO) for use
in the production of modern synthetic fuels (e.g. biodiesel,
ethanol, bio-syngas or bio-hydrogen). These fuels canthen be converted into electricity or heat, or used fortransportation.
A number of exothermic and endothermic chemical reactions are involved in the thermochemical processing ofwaste residues. The most important ones are listed inTable 1

Table 1. The prevalence of one over the other defines theoverall process conditions and the final product composition.

2.1 Combustion
Combustion represents perhaps the oldest utilization ofsolid fuels in thermochemical processes. Chemically,
combustion is the complete oxidation of the hydrocarbon
species in biomass or wastes, and conversion into mainly
H2O and CO2. Combustion involves several processes
which occur simultaneously. Initially, the moisture content is driven off by the heat in the combustion chamber(or boiler), followed by the release of its volatiles content(referred to as devolatilisation). Actual combustion only
commences once the volatiles are ignited in the presence of
air. The heat released is used to produce a high-pressure
steam for electricity generation in steam turbines, andlow-pressure steam for internal use. Although bottom andfly ashes (derived from the inorganic content of the waste)
play a small role in the overall process, they have a significant effect on the energy balance, by way of the meanheat capacity (Materazzi et al., 2013). Incidentally, ferrous
and non-ferrous metals may also be recovered dependingon the bottom ash treatment options. Furthermore, theresidual ash can be improved, enabling its use as a construction material (Teixeira et al., 2019).

2.2 Pyrolysis
Pyrolysis takes place in the total absence of oxygen,
except in cases where partial combustion is needed toprovide the heat for the process itself. During the pyrolysis of solid waste fuel, decomposition occurs at relatively
low temperatures (approx. 300 °C–600 °C (Kwon et al.,2019)). The biomass or waste feedstock is converted into
gaseous (syngas), solid (char) and liquid (tar) products.

Main reactions during the thermochemical transformation of solid fuel.

Type/Label

Reactions

EnergyEquationkJ/molExothermic
Combustion{volatiles/char} + O2 → CO2 + H2O–300–400(1)

Partial oxidation{volatiles/char} + O2 → CO + H2

–100–200(2)

Methanation{volatiles/char} + H2 → CH4

–74.9

(3)

Water-gas shift

CO + H2O ↔ CO2 + H2

–40.9

(4)

CO methanation

CO + 3H2 → CH4 + H2O–206.3(5)

Pyrolysis

Biomass/waste → volatiles + char—

(6)

Water-gas/steam-carbon{volatiles/char} + H2O → CO + H2

159.9

(7)

Boudouard{volatiles/char} + CO2 → 2CO

172

(8)

Endothermic

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The net calorific value of the syngas is typically in therange of 10–20 MJ/Nm3. The condensable fraction is recovered by cooling the syngas for use as a liquid fuel. The
rate of heating and the pyrolysis temperature affect the
proportion of useful product generated from the process(namely H2, CO, CH4 and other hydrocarbons) (Safdari etal., 2019). The liquid product is referred to as bio-oil andcan be used as an alternative fuel oil in power and heatapplications or as feedstock in the production of various
commodity chemicals. The major drawback concern­ing
bio-oil is its high oxygen content (35–60 wt%) (Uzoejinwa
et al., 2018), which results in a low calorific value, instability and corrosiveness of the fuel (Sharifzadeh et al.,2019). The lower heating value (LHV) is usually between
18 MJ/kg and 20 MJ/kg, which is lower than the LHV ofconventional liquid fuels such as diesel (42 MJ/kg) andgasoline (44 MJ/kg) (Perkins et al., 2018). Recently, different studies to solve this issue have been conducted on
the co-pyrolysis of biomass and waste plastics. These
substances are particularly attractive for their high hydrogen contents of about 14 wt% (e.g. polyethylene, polypropylene, polystyrene), hence they could donate hydrogen
during the process with biomass and improve the bio-oil
quality (Zhou et al., 2006). According to Brebu et al.
(2010), the calorific value of the fuel oil produced via theco-pyrolysis of wood chips with polypropylene (at 1:1
mixing ratio) is 45 MJ/kg. This value is much higher thanthat obtained from wood chips alone (at 19.9 MJ/kg).

2.3 Gasification
Gasification is an intermediate between combustionand pyrolysis, involving partial oxidation of the fuel. In
particular, the oxygen is added but the amount is not sufficient to allow the fuel to be completely oxidised (i.e.
sub-stoichiometric), at temperatures typically above
800 °C (Almeida et al., 2019). The products of gasificationconsist of partially oxidised compounds—mainly H2, CO
and CO2. Partial combustion or an external heat supply
are necessary to sustain the gasification process. The
main product is a syngas which contains hydrogen, carbon monoxide and methane with a net calorific value of
4–10 MJ/Nm3 (Materazzi et al. 2016). This high calorificvalue means that the gases from gasification can be usedin gas turbines and/or internal combustion engines, orburned in conventional boilers connected to steam turbines. With regard to energy production, gasification has
many advantages over combustion. For instance, the syngas product may be more valuable as it can be combusted
at higher temperatures or used in fuel cells (Safarian etal., 2019; Whitty et al., 2008). It also produces a solid ash
product, low in carbon (i.e. char) and other inorganic contaminants (for example, chlorides, sulphides, heavy metals, etc.). The biggest potential of waste and biomass

116

gasification, however, is still not fully realised. Once thesyngas gas is cleaned and all impurities removed, it canbe used to generate chemicals or high-quality fuels via
catalytic stages (e.g. Fischer-Tropsch, methanation, etc.)(Karl and Pröll, 2018). This opens the door to a new andpotentially outstanding biorefinery industry which sees
gasification as one of the most promising thermochemical
technologies in the future for the production of sustainable fuels (Mazaheri et al., 2019).

3. Fluidised bed technologies applied tothermal treatments
Fluidised bed reactors (FBR) have a long record of success in the field of thermochemical conversion due to theirfavourable mixing features, near-constant temperatures
and the good operating flexibility (Salatino and Solimene,2017). These features make fluidised beds particularly
suitable for the application with heterogeneous feedstock,
including biomass and waste (Siedlecki et al., 2011).
In a fluidised bed, the fuel is suspended in a swirling
mass of hot particles (such as sand), fluidised by an updraft of hot gases. This system facilitates thorough mixing, and therefore good mass and heat transfer. These are
the main reasons why fluidised beds are best suited totransform heterogeneous materials via thermochemical
processes. The exit gases carry off some particulates ofash, fines and bed material. Heavier bed particles and ash
are decanted from the base of the gasifier, and replacedwith fresh bed material (normally inert sand) (Materazzi,2017). This mechanism is fuel-dependent, as fuels with ahigher ash content require more frequent extractions. In
modern applications, fluidised bed plants are better suitedto treating refuse-derived fuel (RDF) than raw MSW.
This requires pretreatment of the waste feedstock to remove recyclable materials, as well as dense, coarse objects, and to reduce particle size. Fluidised beds offer
flexibility in terms of feedstock calorific value, moisture,
particle size and density and sulphur content. Nonetheless, limitations may arise if the feed contains a significant portion of large, dense particles or low-melting-pointash. This flexibility centres on the ability to mix and holdthe fuel within the fluid bed, providing a sufficient residence time for reactions to reach completion. Alkalinematerials (for example, limestone) can also be charged tothe bed to help retain acidic impurities or to aid tar cracking and reforming reactions (Schmid et al., 2018). Worthyof note is that the heat input from the burning char (within
the bed) and the devolatilised gases (above bed) balances theoutgoing heat ‘consumed’ by endothermic reactions in thegas phase (e.g. water-gas/steam-carbon, steam reforming,etc.) (as illustrated in Fig. 1). This provides the basis forcontrolling the temperature of the bed during steady-stateStefano Iannello et al. / KONA Powder and Particle Journal No. 37 (2020) 114–131

Fig. 1

Fuel transformation scheme and influence of temperature and oxidation stage in an FBR.

Fig. 2 Fluidised bed reactor configurations: (a) bubbling; (b) circulating; (c) dual. Source: Adapted from Motta et al. (2018).

operation. In this respect, the equivalence ratio (ER)(namely the amount of air/oxygen inputted relative to that
required for stoichiometric combustion) is the parameterthat determines the difference between combustion, pyrolysis and gasification (Materazzi et al., 2013).
Fluidised bed technology is also well proven and mature in other applications such as the combustion of pulverised coal and biomass (Materazzi and Lettieri, 2017).
Different technologies can be classified in accordancewith their physical configuration and operating conditions(Fig. 2), as described in the following sections (Motta etal., 2018).

3.1 Bubbling fluidised bed reactor
Inside a bubbling fluidised bed reactor (BFB), the bed

media is fluidised from the bottom of the bed by way of a
distribution plate or gas nozzles with a velocity varying ina range of 1 and 3 m/s (Molino et al., 2016). Under these
conditions, the bed material (particle diameters ranging
between 0.5 and 1.0 mm, Group B of Geldart classification) is fully fluidised and behaves like a boiling liquid(Kunii and Levenspiel, 1991). The fluidisation state ismaintained by a gas-bubble emulsion which continuously
agitates the solid phase, enabling good mass and heattransfer between the solid and gas phase. Within the upper part of the reactor, namely the freeboard, only the gas
phase is present, as the bed material does not normally
get carried this high. Some of the gas-phase reactions takeplace here, even though the main stages of thermochemical conversion occur within or just above the fluidised bed(Molino et al., 2016). The cross-sectional area of the117Stefano Iannello et al. / KONA Powder and Particle Journal No. 37 (2020) 114–131

freeboard is usually wider in order to decrease the superficial velocity of the gas, maintain a fixed solid quantity inthe bed, and compel the particles to return to the bed. At
the gas outlet, appropriate equipment is required (e.g. cyclones) in order to capture particulate matter (e.g. fly ash)formed during the process (Motta et al., 2018). Concerning the feedstock, BFBs present good flexibility and areable to process a broad variety of fuels. Typical feedstocks
include biomass, RDF, low-rank coals, lignite, plastics
and solid-recovered fuels (SRFs), with particle sizes below 6 mm (Arena et al., 2011; Arena and Di Gregorio,
2016; Hu et al., 2012; Ud et al., 2016). Valin et al. (2019)
have compared the results obtained from the air gasification of woody biomass (namely beech sawdust and wastewood) and solid-recovered fuel using a bubbling fluidised
bed at 1.5 bar. The experiments were carried out whilevarying the addition of steam, ER ratio (between 0.00
(pyrolysis conditions) and 0.34) and the temperature (between 800 and 900 °C). They obtained a cold gas efficiency and carbon-gas conversion of 59 % and 80 %,respectively for SRF, and 75 % and 92 % for beechwood.
The authors concluded that the co-gasification of SRF andbiomass might be an effective way to improve the overall
efficiency and also limit the pollutant content in the final
product. In order to inhibit the phenomena of bed particle
agglomeration, which leads to defluidisation of the bed,
BFB reactors should operate at temperatures lower than
the fuel’s ash melting temperature (Samiran et al., 2016).
Zhu et al. (2019) studied the co-gasification of polyethylene and beech wood in a lab-scale fluidised bed reactor.
In particular, they investigated the effect of steam injection, feedstock composition and bed material on the hydrogen production. The results show that the Na-Y zeolite
provides the highest hydrogen content in the products
among all bed materials tested, including sand, ZSM-5
zeolite, and FCC catalysts. Moreover, the authors foundthat the smaller the wood-to-PE ratio, the higher is the hydrogen production.
The use of stand-alone BFBs is limited for some syngas
applications (i.e. catalytic transformation), due to both the
low gasification efficiency and solid conversion (Ramos etal., 2018). Such restrictions can nonetheless be prevented
by providing a longer solid residence time (for example,
through a solid circulating loop, as used in circulating fluidised beds) (Basu, 2006), or by adding an additional reforming step (e.g. plasma reformer) (Materazzi et al.,2015).

and bed particles become entrained in the gas stream as aresult, increasing the amount of solids in the freeboard. A
downstream unit is thus required to separate (e.g. using a
cyclone) and recirculate these particles (Ahmad et al.,2016; Alauddin et al., 2010). Recycling the solids has theadvantage of increasing the particle residence time, which
improves the carbon conversion efficiency and reaction
rates and leads to lower tar production (Gómez-Barea andLeckner, 2010; Puig-Arnavat et al., 2012; Samiran et al.,2016). The bed material is normally the same as for BFBs,
but with a smaller diameter (e.g. 0.2–0.5 mm). Similar to
BFB reactors, CFBs are able to operate with different
types of feedstock, as shown by Duanguppama et al.
(2016). The authors studied the pyrolysis of sawdust contaminated with mineral oils and solid wastes. In particular, they demonstrated that the bio-oil achieved its
maximum yield of 67 wt% at 500 °C, with an LHV ofabout 30 MJ/kg. Furthermore, they found that the presence of minerals increased the calorific value and thenon-condensable gas content by nearly 300 %.
There are some disadvantages to this configuration, including process control as well as higher investment costs(associated to solids separation equipment) (Zhou et al.,2009). Similar to BFBs, limitations are also present withrespect to bed agglomeration and ash melting (Hofbauer
and Materazzi, 2019), especially when operated on wastematerials.

3.3 Dual fluidised bed reactor
Dual or internal circulating fluidised beds (DFB or
ICFB, respectively) consist of two interconnected fluidised bed reactors with the bed material circulating between them, enabling efficient mass and heat transfer
between the two units (Fig. 3). The solid fuel is charged
to the ‘fuel reactor’ where it undergoes gasification or pyrolysis. The generated char and unreacted fuel are

3.2 Circulating fluidised bed reactor
Circulating fluidised bed (CFB) or external circulating
fluidised bed (ECFB) reactors can maintain the gas superficial velocities up to three to five times (5–10 m/s) longer
than the bubbling arrangement (Molino et al., 2016). Char118

Fig. 3

Concept of DFB fuel conversion.

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subsequently transported into the so-called ‘char reactor’for full gasification or combustion. In this way, the conversion processes are decoupled, ensuring complete independence of the gas phase in the two vessels. This results
in a purer and higher-quality gas product than that fromsingle reactors (Fuchs et al., 2019).
In gasification systems, the fuel reactor is a bubbling
fluidised bed gasifier operating between 800 °C and
850 °C with steam as the gasification medium (i.e. steam
gasification). Since the reactions during the steam gasification are mostly endothermic (e.g. Eqn. (7), Table 1),heat must be generated and provided to this stage (Shen etal., 2008). The heat required is generated in the second
reactor (fluidised with air), where combustion of the residual char from the gasification section takes place at 900–
950 °C (Fuchs et al., 2019). The flue gases generated exit
the char combustion reactor separately from the produced
syngas, which is therefore free of air/nitrogen. Concurrently, the heated bed material is recirculated into the gasification reactor, acting as an external heat source (LaVilletta et al., 2017).
DFBs present good scale-up potential and are suitablefor high specific capacities, although their construction israther complex (Puig-Arnavat et al., 2010). As for most
fluidised bed systems, these reactors can process a broad
variety of biomass including sewage sludge, grass (Vander Drift et al., 2005), wood chips and pellets (Hofbauer
and Rauch, 2008), dried coffee grounds (Xu et al., 2006),
cedar, oak sawdust (Suzuki and Namioka, 2005), almondshells and waste residues (RDF, SRF, mixed plastics, etc.)(Corella et al., 2007). Furthermore, dual fluidised bed systems generate syngas with a reasonable calorific value,rich in hydrogen. In this respect, Benedikt et al. (2018)carried out a set of experiments using different types ofbiogenic fuels (i.e. sugar cane bagasse, softwood, olive
pomace, bark and rice husk) and waste-derived fuels (i.e.
MSW fraction, shredder light fraction and MSW fraction
with 25 % blending of lignite) in a 100-kW pilot plant at
TU Wien, Austria. The resulting product gas has a LHVof around 11–12.5 MJ/Nm3 for the gasification of biogenic
feedstock, and 14–16 MJ/Nm3 for that of waste. Moreover, the H2/CO ratio of the syngas reached a value up to
3.9 for the waste-derived fuels (Benedikt et al., 2018). A
larger plant of 20 MWfuel based on the DFB concept is located in Göteborg, Sweden (Leckner, 2016) for the production of bioSNG from biomass.
A range of different design options can be consideredfor DFBs. This includes, for instance, two fast fluidised
beds, a bubbling and a fast fluidised bed, or a combinationof two bubbling fluidised beds (Fuchs et al., 2019; Kunii
and Levenspiel, 1991; Paisley and Overend, 2002). An example of a design based on the ICFB principle is the
MILENA gasification process (Fig. 4).
The gasification section includes a downcomer, riser

Fig. 4 Lab-scale MILENA gasifier. Source: Adapted from
Van der Meijden et al. (2010).

and settling chamber, whilst the combustion section encloses a sand transport zone and the BFB. The biomass is
fed into the riser where a small quantity of superheatedsteam is inputted from below (5 wt% of the biomass input) (Van der Meijden et al., 2010). In the riser, opposite
and below the biomass feeding point, an orifice allows theentrance of the hot bed material (typically olivine or sand)from the combustor. The hot bed material serves as aheating source for the biomass, which reaches a temperature of 850 °C. The heated fuel particles devolatilise andare converted into char, tar and gas, which rises throughthe reactor with a vertical velocity of nearly 6 m/s (Vander Meijden et al., 2010). This leads to a turbulent fluidisation regime within the riser as well as significant entrainment of char and bed material. Since the verticalvelocity decreases in the settling chamber, the gas separates from the solids, which fall down into the downcomer. The product gas exits from the top and is sent tothe cooling and cleaning section. The char is oxidisedwith air in the bubbling fluidised combustor in order toheat the bed material up to 925 °C. Subsequently, it leaves
the combustion section from the bottom and is sent to theriser again. The product syngas contains a certain number

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of contaminants such as sulphur, chloride, tar and dust
(Van der Meijden et al., 2010). These species must be
removed in order to prevent poisoning the catalyst in later
syngas applications (e.g. bioSNG synthesis). A pilot plantof MILENA gasification (500 kW) is employed by the
Energy Research Centre in the Netherlands (ECN), usingwood pellets as feedstock (Han et al., 2018). Operating in
the temperature range of 830–870 °C (gasification) and
940–1050 °C (combustion), the system can achieve a syngas with an H2 concentration on a dry basis of 23.8-vol%and a high heating value (HHV) of 15–17 MJ/Nm3.
Similarly to DFB gasification, pyrolysis can also be decoupled into two separate reactors, namely fuel pyrolysis
and char conversion. This is also known as pyrolysis-based cogeneration (Han et al., 2018). This kind of
configuration is still largely applied in the pyrolysis ofcoal, lignite and bituminous material (Han et al., 2018).
More research is needed on biomass and waste as feedstock. Aho et al. (2010) conducted an experimental study
on the pyrolysis of pine wood with subsequent improvement of pyrolysis vapours in a dual fluidised bed reactor.
The temperatures of the pyrolysis and upgrading steps
were 400 and 450 °C, respectively, with iron-modified zeolites used as catalysts. They found that the yield of biooil could reach 52.7 wt% and that a high selectivity
through de-oxygenated compounds could be achieved.
Similar configurations have been used recently to recoverwaste plastics in the UK and transform these into a reusable wax precursor for upgrading to fuels and new materials.

3.4 Chemical looping
Chemical looping gasification (CLG) and chemicallooping combustion (CLC) represent two established andattractive carbon removal technologies which permit N2free syngas or CO2 capture applications without requiring
the energy-insensitive gas-gas separation step (Mattisson
et al., 2018; Stollhof et al., 2018). As in DFB systems,
chemical looping consists of two different reaction zones(Fig. 5): a fuel reactor in which gasification or combustion take place, concurrently with the reduction of the oxygen carrier material (Eqns. (9) and (10)); and an air
reactor in which regeneration of the oxygen carrier occurs(Eqn. (11)). In this way, air and fuel are never mixed, resulting in a high-purity syngas or CO2 stream available
for carbon capture and storage (CCS) or utilization(CCSU).
CnH2m + (2n + m)MexOy→ (2n + m)MexOy-1 + nCO2 + mH2O

(CLC)  (9)CnH2m + nMexOy→ nMexOy-1 + nCO + mH2(CLG) (10)120

Fig. 5

Concept of chemical looping in fluidised beds.

MexOy-1 + 1/2O2 → MexOy(11)

The oxygen carrier is typically a metal oxide powder,
allowing the transport of O2 from the air reactor to thefuel reactor (Pans et al., 2013). Good candidates are copper, manganese, iron, cobalt and nickel. Moreover, someauthors have found that even iron in olivine (Lancee
et al., 2014) and silica sand used as bed material(Udomsirichakorn et al., 2014) are also capable of transferring oxygen between the two reactors. For the majorityof chemical looping concepts, the air and fuel reactors aredesigned as a high velocity riser and low velocity BFB,
respectively (Han et al., 2018). Using heat provided by theoxygen carrier, the solid fuel decomposes into volatiles
and char. The former species react directly with the oxygen content of the metal oxide, whilst the oxidation ofchar is a slow process that requires an intermediate steam
gasification step (Han et al., 2018). A CLC system withbiomass and an iron-based oxygen carrier was built inNanjing, China, in 2010 (Lyngfelt, 2014). Results showthat the smaller 1-kW plant generated an outlet gas fromthe fuel reactor with a carbon distribution of 95 % CO2,
4 % CO and 1 % CH4. Several CLC and CLG operations
have been studied in small pilot plants (Lyngfelt, 2014). In
this regard, it is important to recognise that the results
obtained on a small scale cannot accurately indicate theperformance on a large scale. This is due to the intrinsic
differences between large and small f luidised beds
(Lyngfelt and Linderholm, 2017). However, it has alreadybeen demonstrated that the CLC design is technicallypracticable for application on a large scale (Kolbitsch etal., 2009). Lyngfelt and Leckner (2015) presented an interesting techno-economic analysis for the effective
scale-up of this technology up to 1000 MWth for solid
fuels.

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4. Effect of operating conditions
The importance of operating conditions in thermochemical processes have been extensively studied, andmany excellent reviews can be found in the literature(Heidenreich and Foscolo, 2015; Hofbauer and Materazzi,
2019; Yates and Lettieri, 2016). This section will only
highlight some of the key aspects related to operation of
FBRs on waste feedstock. Among all factors, temperature
is perhaps the most important. As shown in Fig. 1, FBRs
usually operate at atmospheric pressure and relatively low
temperatures (< 900 °C) in order to avoid sintering of theashes and subsequent melting and agglomeration issues.
This is particularly relevant to operations with waste
feedstock, due to the high presence of ashes and inorganic
components in these fuels (Yates and Lettieri, 2016). On
the other hand, the amount of tar produced is known toincrease with decreasing temperature (Kinoshita et al.,1994). The typical approach to avoid this inconvenience is
to stage the oxidation phase at multiple levels, achieving
high temperatures only when needed, i.e. in those areas
where bed material is not present. These can include, forexample, the freeboard in fluidised beds, or the entire gas
space in dedicated ‘thermal cracking’ units. However,controlling the agglomeration phenomenon is also possible by means of frequent bed replacement and the addition of other components to the bed inventory. Lu et al.
(2015) conducted a study on catalytic coal gasification ina pressurised fluidised bed reactor. They demonstrated
that the sintering temperature of the coal ash increased
from 650 °C to 740 °C by adding a small amount (5 wt%)
of water-washed ash. The ash content in the fuel also affects the conversion process more directly. For instance,
ash can cause a reduction in the char activity by hindering
the reaction between oxygen and carbon within the pores.
Furthermore, solids discharge rates in FBRs have to beenhanced significantly in order to keep a constant bed
depth, thus increasing the fraction of heat losses and fluctuations within the system (Yates and Lettieri, 2016). Bed
depth and fluidising velocity, in turn, have an influence on
the residence time of reacting gases and particles within
the reactor, therefore affecting the thermal conversion efficiency and gas composition. For example, an increase in
bed height ensures a high residence time for the char particles within the bed and more stable conditions. On theother hand, the fluidisation velocity controls the mixing
and the expansion of the bed, as well as the gas residence
time and elutriation rates. Plenty of work has been conducted on different bed materials to be used in thermochemical processes, either for their catalytic properties intar reforming, or for different retention capacities of inorganic contaminants (Heidenreich and Foscolo, 2015;
Thunman et al., 2018). Koppatz et al. (2011) compared silica sand (as a reference inert material) and olivine in apilot-scale DFB system for wood pellet gasification. The
authors tested olivine with a particle size range of 400–
600 μm and particle density of 2850 kg/m3. The results
show a reduction of GC (Gas Chromatograph) tar andgravimetric tar content (both related to the fuel input) by
about 30 % and 57 %, respectively. Ly et al. (2018) investigated dolomite with a particle size of 180–250 μm as acatalyst for bio-oil upgrading from tulip tree pyrolysis.
They demonstrated that the HHV of the bio-oil reached avalue between 23.09 and 28.1 MJ/kg, which was higher
than that obtained from the pyrolysis with silica sand (i.e.
21.64–24.37 MJ/kg). In most cases, however, the extent towhich solid particles affect the tar content and productcomposition is determined by a series of concurring elements, including feedstock composition and atmospherein the reactor, rather than bed material alone.

5. State of the art of FBRs for thermochemical
conversion
5.1 Fluidised bed combustion
Combustion currently represents the most well-­established thermochemical conversion of waste into energy, with more than 1400 incineration plants in operationworldwide (Dong et al., 2018a,b; Leckner, 2015). There
has been a progressive increase in the number of combustion plants in different parts of the world: in Europe 455
plants were in operation in 2012 (Lausselet et al., 2016),
whereas the number in China has risen from 54 plants in2004 to 188 in 2014 (Dong et al., 2018a). Even though thelast generation of MSW combustors employs effective andadvanced flue gas cleaning, ash recycling and the use of
combined heat and power (CHP) cycle, there are stillsome limitations concerning electricity efficiency—which
is low at about 22–25 % (Dong et al., 2018b; Panepinto etal. 2014). This is due to a restriction on the maximum
steam temperature of the boiler, which is typically kept
below 450 °C to avoid corrosion by HCl (Belgiorno et al.,2003). Although fluidised bed reactors are a promisingtechnology, currently the main combustion technologies
for MSW treatment remain moving-grate and rotary kiln
combustors (Materazzi and Lettieri, 2017). Moving grates
are employed in most of these applications and have been
fully developed in order to meet the demands for largescale performance. This is due to their ability to handle
large volumes of waste, avoiding the need for prior removal of bulky material through shredding and sorting(Wissing et al., 2017). The percentage of MSW combustion plants utilising moving grates is 94 %, 88 %, 85 %and 76 % in Germany, EU, France and US, respectively,
with the remaining plants being either rotary kiln or fluidised bed combustors (Lu et al., 2017). However, the121Stefano Iannello et al. / KONA Powder and Particle Journal No. 37 (2020) 114–131

Table 2

Fluidised bed combustion systems. Source: Adapted from Koornneef et al. (2007)
Min

Max

BFB

17

142

7

CFB

2

520

51

Babcock and Wilcox

CFB

3

76

22

Babcock Borsig

BFB

0

35

5

CFB

9

120

10

Bharat Heavy Electricals

BFB

5

50

18

Outotec

BFB

10

45

9

Foster Wheeler

BFB

0

117

51

CFB

0

460

161

BFB

6

117

56

CFB

0

240

32

CFB

9

225

35

Technology

AlstomKvaerner Pulping
Lurgi

major downside of moving grates is their higher relative
maintenance and investment costs as compared to theother two technologies.
Fluidised bed combustors, on the other hand, can only
process waste after shredding and size reduction (such asRDF). Nevertheless, they can operate on a broad variety
of waste feedstock, in terms of properties and controllingemissions (Materazzi and Lettieri, 2017). Another important advantage is that the capital and operational investment for fluidised beds is only approx. 70 % of that formoving grates (Makarichi et al., 2018). Nowadays, eventhough China has the largest capacity of MSW plants operating fluidised beds, most of this technology is still imported from Europe (Li et al., 2015; Lu et al., 2017). The
largest suppliers of fluidised bed combustors are shown in
Table 2. The largest suppliers of CFB technology are
Alstom and Foster Wheeler, with Kvaerner being the market leader for BFBs. Outotec (formerly EPI) and Bharat
Heavy Electricals are prominent in their local markets ofNorth America and India, respectively. A number of
Outotec’s BFB RDF combustors, however, have been operating successfully in Italy (Materazzi and Lettieri,2017).
Recent combustor technologies comply with environmental requirements, but potential risks concerning sometoxic compounds released from the gas (i.e. dioxins andfurans) or from the ashes (heavy metals) are still present
at the core of public debate. In this regard, the development of alternative and more environmentally friendly
waste treatment is still essential.

122

Capacity (MWe)No. of Installations(2007)

Organisation

5.2 Fluidised bed pyrolysis
Pyrolysis has been studied as an effective alternative to
combustion for MSW disposal that allows more effective
resource and energy recovery. There is an abundance of
renewable feedstocks available worldwide that can beconverted into biofuels via pyrolysis. This includes forestry materials, agricultural crops, algal biomass and,more generally, lignocellulosic biomass (Dhyani and
Bhaskar, 2018). Furthermore, several studies have been
conducted on different industrial wastes (such as sewage
sludge, plastics and tyres), while only in the last few years
pyrolysis has been commercialised to treat MSW. Indeed,
the pyrolysis of MSW is receiving growing attention inboth small and larger cities due to an increasing struggle
to find new sites for landfills and incinerators, and consequently to avoid long-distance transportation (Chen et al.,2015). Although rotary kiln and fixed-bed reactors areused for MSW pyrolysis, fluidised bed reactors remain themain focus for research and future exploitation. In particular, they have been studied to investigate the behaviourof fast pyrolysis, as they offer higher heating rates(Hofbauer and Materazzi, 2019). Industries which havedeveloped fast pyrolysis technologies for generating biooil from biomass using fluidised beds include Ensyn(Canada and USA), DynaMotive (Canada) and the VTT/
Valmet/Fortum consortium (Finland) (Perkins et al.,2018). A summary of the commercial pyrolysis plants
worldwide is shown in Table 3.
DynaMotive’s fast pyrolysis process was developed at
the University of Waterloo in Canada from pyrolysis experiments on wood. The process produces bio-oil (50–75 wt%), non-condensable gases (10–20 wt%) and char

Stefano Iannello et al. / KONA Powder and Particle Journal No. 37 (2020) 114–131

Table 3 Pyrolysis units worldwide using f luidised bed reactors. Source: Adapted from Dhyani and Bhaskar (2018) andPerkins, Bhaskar, and Konarova (2018)
Organisation

Location

Technology

Feed rate (tpd)

Status

RTI International

USA

BFB

1

Operational

Ensyn

CanadaCFB

2

Operational

Red Arrow

USA

CFB

3

—

Union Fenosa

Spain

FB

5

Shutdown

University of Waterloo

CanadaBFB

6—

DynaMotive

CanadaBFB

11—

ValmetFinland

CFB

15

Operational

ENEL

Italy

CFB

16

—

Red Arrow

USA

CFB

24

—

Red Arrow

USA

CFB

30

—

Ensyn

Canada

CFB

150

Operational

FortumFinland

CFB

274

Operational

UDT

Chile

FB

0.36

Operational

University of Science & Technology of China, Hefei

China

FB

2.88

Operational

Metso

Finland

FB

7.2

Operational

Biomass Engineering Ltd.

UK

FB

10

UpgradeRecycling Technologies

UK

FB

25

Operational

Iowa State University

USA

FB

0.24

Operational

National Renewable Energy Laboratory

USA

FB

0.3

Operational

UOP

USA

CFB

1

Construction

Virginia Tech

USA

FB

6

Operational(15–20 wt%) which is combusted in order to provide heatto the fluidised bed, maintaining it at the desired operational temperature of 430 °C (Perkins et al., 2018). The
relative amount of each product depends on the feedstock
being processed. Ensyn’s rapid thermal processing (RTP)
technology was developed at the University of Western
Ontario, in Canada, stemming from research to produce
chemicals from biomass (Venderbosch, 2015). The core of
the process is a circulating fluidised bed reactor and theliquid yields vary between 65 wt% and 75 wt%. The firstsystem was commercialised in 1982 and a demonstration
plant of 15 tpd was sold to ENEL in Italy. At present,
there are four plants in operation in Ontario with a capacity of about 11 million l/y of pyrolysis oil produced. A
number of plants with a capacity of around 350 tpd areunder design and construction (Perkins et al., 2018). In
2009, Valmet built a bio-oil pilot plant (production capacity of 7 tpd) at their R&D centre in Tampere, Finland. A
large-scale plant (capacity 50,000 tpa of bio-oil) was subsequently built into Fortum’s combined heat and power
plant in Joensuu, Finland, in 2013. The liquid product has
an LHV of 13–18 MJ/kg and it is obtained from sawdust,

wood chips and forest residue. Both pilot and commercial
pyrolysis systems are presently operational and integrated
with a circulating fluidised bed reactor.
With regards to the pyrolysis of polymer feedstock, fluidised bed reactors can have advantages over other reactors due to favourable heat transfer during cracking (Chenet al., 2015). Hence, there are various processes which use
pyrolysis for the treatment of mixed plastic waste (MPW)such as the BP polymer cracking process (Al-Salem et al.,2010) and the Hamburg process (Kaminsky, 2006). The
Recycling Technologies plant in the UK is an example ofcommercial-scale pyrolysis which is able to handle
9000 tpa of residual plastic waste (Recycling Technologies, 2019) to convert it into a reusable wax product. The
DFB system consists of a fluidised bed pyrolyser containing bed material which is continuously circulated from/tothe regenerating section. Within this module, the bed material is heated up to 850– 900°C by combustion of thelightest fraction (e.g. methane, ethane) from the distillation stage, and then recirculated to the first reactor whereplastic pyrolysis occurs.

123

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5.3 Fluidised bed gasification
Gasification is currently considered a more attractive
process when compared to combustion and pyrolysis forboth biomass and waste treatment, due to the wide choiceof the various end products (Bhavanam and Sastry, 2011).
Moreover, it represents a cleaner alternative solution withrespect to increasing environmental restrictions (Arena,2012). However, the gasification of problematic materials,
such as waste, for biofuel production still needs to be
proven on a large scale for commercial take-off. The design of commercial gasifiers, currently used for combined
heat and power (CHP) production only, depends on feedstock availability, ranging from agricultural to industrial
and municipal waste streams. As with pyrolysis, fluidised
beds are the most employed for both waste and biomass
treatment as they provide a robust and flexible technology,
allowing a broad range of particle size feedstocks to beprocessed (Ramos et al., 2018).
A large-scale CHP gasification plant using a fluidised
bed reactor is located at Lathi, Finland. It was developed
by Foster Wheeler and has been operational since 2012
(Dong et al., 2018b). It has a capacity of 250,000 tpa ofwaste feedstock unsuitable for recycling, in the form of
SRF. The plant achieves a CHP efficiency and a net electricity efficiency of 61 % and 27 %, respectively. Waste
gasification takes place in a circulating fluidised bed reactor operated at 850–900 °C. As mentioned in Section 3.3,
DFB reactors are also being studied increasingly for gasification. This type of reactor has been operated successfully since 2001 in Güssing, Austria; with wood chips as
feedstock, olivine as bed material and operating at temperatures between 850 °C and 900 °C (Fuchs et al., 2019;
Karl and Pröll, 2018). The thermal power input of theplant is 8 MW, employed in an electric gas engine of
2 MW. An important success was achieved in 2007 whenan adsorption-enhanced reforming (AER) test was carriedout on the Güssing system, demonstrating its feasibility
even with a power plant engineered for conventional gasification (Fuchs et al., 2019). The effectiveness of an advanced gasifier concept, namely UNIQUE, has also been
proven with the same plant (Heidenreich et al., 2016).
UNIQUE consists of a compact solution based on the integration of fluidised bed gasification and gas cleaning
and conditioning directly into one vessel reactor. This isachieved by adding sorbents to the bed, to promote primary tar reforming and the removal of inorganic compounds, and by installing catalytic filters in the freeboard,for combined secondary tar reduction and particulate removal.
As of 2004, Ebara Corporation had 21 processes operating commercially in Germany and Japan. The technology is based on twin internally circulating fluidised bed
gasifiers. It was designed incorporating ash vitrification

124

technology for the detoxification of waste, energy recovery and material recycling within an integrated and economical process. A large-capacity plant located in
Aomori, Japan, has been in operation since 2000, and isbased on gasification and slagging combustion. The process is able to handle 450 tpd of automotive shredder residues (ASR) and sewage sludge, with a power output of
17.8 MWe (TwE, 2013). More recent information on Ebara
technology could not be found by the authors.
High-pressure operation in fluidised beds is also possible to favour the direct production of light hydrocarbons,
including methane, in the syngas. A well-proven exampleof this is the high-temperature Winkler process (alsoknown as HTW). The process is an evolution of the earlysteam/oxygen coal gasifier patented by Winkler in 1922,
further developed in 1997 for applications in power generation and the production of methanol (Leckner, 2016).
More recently (in 2011), Thyssen-Krupp-Uhde, Germany,
commercialised the technology. One of their projects involves the production of methanol from syngas, after biomass gasification. The HTW gasifier employed, located in
Sweden, has a capacity of 111 MW (Leckner, 2016). Another proven process which employs the HTW technology
co-fires pure biomass with waste-derived fuels underpressure (at 30 bar). This enables a methane-in-syngas
level of 8 % (dry basis) to be achieved (Adlhoch et al.,2000). A summary of other available gasification systems
across the world using fluidised bed technologies is presented in Table 4.

6. Fluidised bed reactors for biofuel synthesis
The role of fluidised bed reactors as applied to the thermal treatment of solid feedstock has been described in theprevious sections. However, these technologies also havesignificant potential with regard to other processes in thethermochemical industry. For instance, in recent years
many authors have been studying a range of techniques
for the production of biofuels using fluidised beds, including biosubstitute natural gas (bioSNG), biohydrogen andother chemicals.

6.1 Biohydrogen production
Producing hydrogen from biomass and waste can be aninteresting and environmentally friendly solution for use
in district heating and transport sectors (Heidenreich etal., 2016). Although there are many methods to producehydrogen, those most commonly used are based on fossil
fuel reforming. For instance, 95 % of H 2 production in
the US is by way of the steam reforming of methane(Muradov, 2017).
Obtaining a hydrogen-rich syngas from gasification is aStefano Iannello et al. / KONA Powder and Particle Journal No. 37 (2020) 114–131

Table 4

Gasification systems worldwide using fluidised bed reactors.

LocationFeedstock

Capacity

Technology

Name/Organisation

China

Agricultural and forestry residues

1 MW

FB

—/Tianyan Ltd.

China

Agricultural and forestry residues

0.2–1.2 MW

CFB—/GIEC

China

Rice husk, straw, wood sawdust,
peanut hulls

5.5 MW

CFB—/GIEC

Austrian Energy, TU Vienna

Biomass chips

8 MWth a

BFB/CFB

Güssing FICFB/—

CFB/BFB

Milena/—

CFB/BFB

Milena/—BFB/CFB

Chalmers/—

ECN Netherlands

Beechwood chips

0.03 MWthECN Netherlands

Wood pellets

0.8 MWth a

GoBiGas, Sweden
Mid Sweden University

Wood pellets
Wood pellets

2 MWthaaa

BFB/CFBMIUN/—a

CFB/CFBFERCO/—

0.15 MWthVermont, USA—

90 MWth

University of Canterbury, New Zealand

Wood chips/pellets

0.1 MWth a

BFB/CFBCAPE FICFB
Gasifier/—

Trisaia, Italy

Almond shells biomass

0.5 MWth a

BFB/CFBThe JOULE-MFCF
PlantENEA

Swindon, UK

RDF/wood chips

5 MWth

BFB/Plasma

GoGreenGas

Edmonton, Canada

MSW

38 MLPY(methanol,
ethanol)

BFB

Enerkem

Note: (a) Capacity as fuel input

fundamental step in ensuring a high-quality product. In
particular, it is important that the syngas is free of nitrogen due to the difficulty in separating different gas components (Materazzi et al., 2018). This can be achieved bymeans of the polygeneration concept based on a dual fluidised bed configuration in which the steam gasification of
biomass takes place (Kraussler et al., 2018). In this regard,
Kraussler et al. (2018) obtained a practically nitrogen-freesyngas with an H2 concentration of 40 vol% using woodchips as the feedstock. Other valuable products obtained
from the process were heat and electricity. Hydrogen canalso be produced within fluidised bed reactors using different pathways such as methanol steam reforming. A
study conducted by Shi et al. (2013) demonstrated that an
FBR filled with Cu/ZnO/Al2O3 catalysts was capable ofreaching a methanol conversion rate much higher thanthat of a fixed bed (over 20 %)—equating to approx.
91.95 % at 330 °C. This was due to the longer contact
time between the reactants, a larger surface volume ratio
and more uniform temperature. Alternatively, methanol
can be partially oxidised using N2O over an iron-­chromium catalyst, achieving a yield of H2 up to 95 % at
350 °C (Żukowski and Berkowicz, 2017). These routes are
particularly advantageous if methanol can be obtained via
biologic routes.

6.2 BioSNG production
Synthetic natural gas (SNG) produced from biogenic sources represents a renewable clean fuelsubstitute for fossil fuels in CHP, transportation and heating (Heidenreich et al., 2016). One of the most wellestablished processes for the production of SNG fromsyngas is the methanation technology; syngas is obtained
from the gasification of coal and is further transformed ina series of adiabatic fixed bed reactors (Heidenreich etal., 2016). The methanation pathway could be considered
an attractive process for obtaining bioSNG from wastederived syngas (Materazzi et al., 2018).
Even in this application, fluidised bed reactors havedemonstrated a higher performance compared to fixed
beds in terms of CO conversion and CH4 selectivity under
the same reaction conditions (Liu et al., 2013). This ismostly due to the close-to-isothermal conditions and good
catalyst mixing obtained in fluidised bed systems. It has
been demonstrated that by using an Ni-Mg/Al2O3 catalyst,
it is possible to achieve a CO conversion up to 95 % at atmospheric pressure, 480 °C and an H2/CO/N2 ratio in thesyngas of 3/1/1 (Liu et al., 2015). From simulation studies,
however, the optimum reactor configuration to carry out
this operation was found to be an isothermal fluidised bed
operating at 450–550 °C combining a tail-end fixed bed inwhich the CO conversion reached 99.8 % (Liu et al.,125

Stefano Iannello et al. / KONA Powder and Particle Journal No. 37 (2020) 114–131

2016). It also appears that the BFBs are more robust
against C2–C3 contamination in the syngas, with a significantly lower carbon formation when compared to fixed
beds (Kopyscinski et al., 2011).
The biological methanation of CO2 in fluidised beds isalso being investigated for the production of bioSNG frommultiple sources. For example, the catalytic direct methanation of carbon dioxide can be carried out in a BFB,
reaching an average yield and concentration of CH4
equivalent to 96 % and 88 %, respectively. The results
were obtained from experiments conducted in a biogas
pilot plant in Zurich (Witte et al., 2019).

6.3 Liquid biofuels production
Similarly to bioSNG, liquid fuels such as Fischer-­Tropsch diesel, biomethanol and bio-dimethyl ether(DME) are also gaining consideration as clean, drop-in
replacements for fossil fuels.
Methanol can be obtained via the catalytic conversion
of syngas from the fluidised bed gasification of both biomass (Liu et al., 2016) and waste (Iaquaniello et al., 2017).
The plant in Edmonton run by Enerkem, Canada, is acommercially available example of methanol production
from MSW (Arguin and Schubert, 2010). Methanol production is particularly relevant nowadays, not only because the methanol market is rapidly expanding, but also
because it represents an ideal chemical platform for thegeneration of other fuels including gasoline, olefins andkerosene (Ilias and Bhan, 2013). For example, fluidised
beds are widely applied in methanol-to-gasoline (MTG)
processes, operating by means of a ZSM-type zeolite catalyst, as demonstrated by Wang and Yuan (2014). They
have shown that the temperature range of 410–430 °C ensures a methanol conversion rate of 100 % and a gasoline
yield up to 25 % at 410 °C (Wang and Yuan, 2014).
Methanol-to-olefins (MTO) is another attractive process
as these substances, mainly ethylene and propylene,
are essential components in the chemical industry(Aghamohammadi and Haghighi, 2019). Producing lightolefins (C2–C4) and clean fuels such as gasoline and middle distillates from syngas is also possible via the
Fischer-Tropsch synthesis (FTS). Kang et al. (2011)
demonstrated that with iron-based catalysts in BFB reactors at 300 °C, it is possible to reach the highest productselectivity when compared to fixed bed reactors. The authors concluded that the best catalyst candidate was K/
FeOx to obtain the highest yield of light olefins (i.e. up to23 %) in the BFB reactor. In addition, recent studies
demonstrate that by doping metal or metal oxides onto the
ZSM-5 catalyst it is possible to produce aromatic species.
This process is also known as methanol-to-aromatics(MTA). Laboratory trials have been carried out in a multistage fluidised bed system, allowing a stable yield of aro-

126

matics (at 62–66 %) to be reached (Chen et al., 2019).

7. Conclusions
In recent years, fluidised beds have been of special interest due to their potential as the central component in
new thermochemical processes for utilising waste andbiomass as sources of bioenergy and biorefinery products,
notably in combustion, gasification and pyrolysis. This isbecause fluidised beds in all of their configurations offer anumber of advantages over most other methods of heterogeneous solid fuels processing. These include steady temperatures, high rates of heat transfer and good solids
mobility. Disadvantages include the attrition of solids,
particle losses by entrainment, limited reactor efficiency
because of the gas bypassing, and several issues inscale-up and design due to the complexity of the involved
processes. This is even more evident when problematic
fuels like municipal solid waste or waste biomass have tobe processed due to their heterogeneous nature and highash and moisture content.
This review is representative of the activity worldwide
in the field of thermochemical processes that see fluidised
beds as the core technology for the effective transformation of waste and biomass feedstocks. The application of
fluidised beds for the catalytic synthesis of chemicals andbiofuels is also briefly explored. Waste and biomass incineration is already widely applied commercially, while
technologies for the conversion into biofuels or hydrogenare being gradually exploited, as shown in this paper. Although advanced technologies on lab and pilot scales have
proven successful in many cases, they still struggle to be
employed commercially due to competitive market factorsthat are beyond the scope of this review. It is expectedthat environmental policies and regulations will help the
implementation of many sustainable technologies on alarge scale in the coming years. Thus, the thermochemical
processing of abundant and largely renewable sources like
waste feedstock will play an essential role in shiftingfrom fossil fuels to renewables quickly, economically andwith low technological risk.

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Authors’ Short Biographies
Stefano Iannello
Stefano is a new PhD student at the University College London (UCL), working on
fluidised beds applied to the thermochemical treatment of biomass and waste. He graduated from the University of L’Aquila (Italy) in 2018, with his final-year project undertaken at UCL with the Erasmus+ programme. For his final MSc project, Stefano has
developed advanced imaging techniques to better understand segregation phenomenaduring initial gasification and pyrolysis of waste feedstock in industrial reactors.

Shane Morrin
Shane is doing engineering doctorate (EngD) research at the University College London (UCL), in conjunction with industrial partners. Originally, Shane obtained a master’s degree in chemical engineering from Queen’s University, Belfast. After some years
working in industry and other fields, he took up an MSc in sustainable waste management at the University of Leeds. Subsequently, he worked in environmental consultancy,
specialising in waste composition projects. This led him to pursuing postgraduate research—namely the gasification of solid waste focusing on the release of sulphur and related constituents.

Massimiliano Materazzi
Massimiliano is a Research Fellow of the Royal Academy of Engineering (RAEng)and lecturer of fluid particle systems in the Department of Chemical Engineering at the
University College London (UCL). He has 10 years of combined industrial and academic
experience in thermal processes and particle technologies spanning applications acrossthe chemical, nuclear and renewable energy sectors. His research is oriented to several
aspects of chemical recycling technologies, with particular attention given to the thermal
treatment of problematic feedstock (e.g. household and industrial wastes), design of fluidised bed reactors for industrial applications, and catalytic processes for biofuel synthesis and chemical storage.

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KONA Powder and Particle Journal No. 37 (2020) 132–144/Doi:10.14356/kona.2020017

Review Paper

Recent Progress on Mesh-free Particle Methods for Simulationsof Multi-phase Flows: A Review †Mikio Sakai 1*, Yuki Mori 2, Xiaosong Sun 1 and Kazuya Takabatake 2
1
2

Resilience Engineering Research Center, School of Engineering, The University of Tokyo, Japan
Department of Nuclear Engineering and Management, School of Engineering, The University of Tokyo, Japan

Abstract
The discrete element method (DEM) and the moving particle semi-implicit (MPS) method are the most popularmesh-free particle methods in the discontinuum and continuum. This paper describes a state-of-the-art modelingon multi-phase flows using these mesh-free particle methods. Herein, a combinational model of the signed
distance function (SDF) and immersed boundary method (IBM) is introduced for an arbitrary-shaped wallboundary in the DEM simulation. Practically, this model uses a simple operation to create the wall boundary.
Although the SDF is a scalar field for the wall boundary of the DEM, it is useful for the wall boundary of the CFD
through combination with the IBM. Validation tests are carried out to demonstrate the adequacy of the SDF/IBM
wall boundary model. Regarding the mesh-free particle method for continuum, the phase change problem is oneof the challenging topics, as the solid state is usually modeled by extremely high viscous fluid in the phase change
simulation. The phase change simulation is shown to be efficiently performed through an implicit algorithm and aheat flux model in the MPS method. The adequacy of these models is verified by the numerical examples.
Keywords: mesh-free particle method, discrete element method, DEM-CFD method, signed distance functions,immersed boundary method, moving particle semi-implicit method

1. Introduction
The discrete element method (DEM) (Cundall andStrack, 1979), the smoothed particle hydrodynamics(SPH) (Monaghan, 1994) and the moving particle
semi-implicit (MPS) method (Koshizuka and Oka, 1996)
are well known as a mesh-free particle methods for simulations of multi-phase flows. Although they require different targets, these methods are capable of easily simulating
the violent motion of the media. The DEM, for instance,
has been employed for simulating discontinuum as in thecase of granular media and is known to inevitably andeasily introduce inter-particle force. Consequently, theDEM can introduce cohesive forces, such as van der
Waals force (Sakai et al., 2012) and liquid bridge force(Dhenge et al., 2013; Tsunazawa et al., 2016; Chan andWashino, 2018; Schmelzle and Nirschl, 2018; Sun andSakai, 2018; Sakai et al., 2019). Very recently, modelingof the particle shape has been extensively studied in the†

Received 24 June 2019; Accepted 18 August 2019
J-STAGE Advance published online 12 October 2019
1,2
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan* Corresponding author; Mikio Sakai;
E-mail: mikio_sakai@n.t.u-tokyo.ac.jp
TEL: +81-3-5842-6977 FAX: +81-3-5842-6977

132

DEM (Zhou et al., 2011; Govender et al., 2019; Kafashan
et al., 2019; Nie et al., 2019; Shrestha et al., 2019; Yang etal., 2019). In contrast, the continuum media have been
simulated using the SPH and the MPS methods, whichhave been consistently employed in the computation offree surface fluid flows, such as droplet impingement(Xiong et al., 2010, 2011), free surface fluid flow throughporous media (Sun et al., 2019), discharge of highly viscous fluid flow (Sun et al., 2012), and wave migration(Shibata et al., 2011). Hence, the mesh-free particle methods make it possible to simulate complex multi-phase flow
systems. From the background, this article highlights a
discussion on the recent progress of these mesh-free particle methods from the numerical simulation viewpoint ofmulti-phase flows.
Regarding the multi-phase flows involving solid particles, the DEM–CFD method (Tsuji et al., 1993) has been
widely employed, e.g., a fluidized bed (Sakai et al., 2010,2014; Yue et al., 2019), a pneumatic conveyor (Klinzing,2018), and a particle filtration technology (Kanaoka,2019). With this method, the local volume average technique (Anderson and Jackson, 1967) has been introduced
into the governing equations for the fluid phase. Moreover, staggered grids are usually employed in the fluid
flow calculation, where the grid size is sufficiently larger

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Mikio Sakai et al. / KONA Powder and Particle Journal No. 37 (2020) 132–144

than the particle size. Usage of the staggered grid makes
it feasible to simulate the fluid flow precisely and stably.
On the other hand, in the existing DEM–CFD method,modeling of an arbitrary-shaped wall and moving wall issubstantially impossible, because of the rectangular shapeof the staggered grid and the fixed grid points. A curved
wall boundary cannot be created by the staggered grid,and no useful model exists for the moving wall boundary.
Apart from the problem regarding the wall boundary, industrial-scale DEM–CFD simulation has not been performed on a single PC, though latest multi-core processors
such as central processing unit (CPU) and graphical processing unit (GPU) have been developed (Shigeto andSakai, 2011; Govender et al., 2018). This is because the
DEM–CFD simulations cannot be finished within practical calculation time when the number of the computational particles approaches to the actual one. From thisfact, the number of calculated particles is substantially restricted. Performing a calculation on a single PC is quite
important for industrial engineers, because they can perform the calculation by themselves without any expertise
regarding parallel computation and without introducing
supercomputers. In summary, the existing DEM–CFD
method has setbacks from the viewpoint of creating arbitrary shape wall boundary and due to a substantial limitof the number of calculated particles.
Phase change is one of the significantly important andchallenging problems in numerical modeling of particle
technology, e.g., additive manufacturing (Steuben et al.,2016; Russell et al., 2018) and thermo-mechanical behavior of powder (Krok et al., 2016). The MPS method cansimulate phase change at ease, and hence has been applied
to various phase change problems (Chen et al., 2014;
Duan et al., 2019). In the modeling, enthalpy has been introduced to simulate the phase change, and the solid stateis simulated by extremely highly viscous fluid. On thecontrary, heat flux has not been given on free surface in
the MPS method; instead, temperature supplied in theprevious studies. Eventually, heat balance has not beenassured during the heat transfer simulation using the MPS
method.
In this manuscript, state-of-the-art technologies for themesh-free particle methods, especially the DEM–CFD
and MPS methods, are introduced, where these have beendeveloped to address solutions to the above problems.

2. Arbitrary shape wall boundary model in
DEM–CFD method
A useful wall boundary model for the DEM-CFD
method is described herein, utilizing mainly a combination of the signed distance function (SDF) and the imme r se d bou nd a r y met hod ( I BM ). For a bet t e runderstanding of the combinational technique, the SDF is
first introduced briefly, and then the combined SDF–IBM
is described.

2.1 Wall boundary model for the DEM
The SDF has been originally used in the level-set
method (Osher and Fedkiw, 2002) in the CFD, and represents an implicit surface in space. Likewise, it has beenshown being utilized in the DEM (Yokoi, 2005). The SDF
consists of distance and sign; particularly, the distancefrom the nearest wall is calculated and saved for eachpoint in a grid enclosing the boundary shape. When thecomputational particle is inside the calculation domain,
the sign becomes positive, and vice versa.
Utilizing the SDF makes the computation of interaction
forces between solid particles and wall boundary an easytask, as it does not necessitate particle contact detection
for the surfaces, edges, and vertices comprising the wall,as compared to the conventional mesh-based wall boundary models. Once the distance from the particle center tothe wall is obtained, the overlap between them can beeasily estimated from the neighboring reference points.
Nevertheless, from a view point of energy conservation, the existing SDF model might lead to instability in
non-dissipative systems. The new SDF model (Shigeto
and Sakai, 2013) has been proposed to solve this problem.
In this model, the normal component of the contact force
is derived from the elastic potential energy; as such, thismodel enables the particle-wall interaction to retain theenergy conservation in a non-dissipative system.
The SDF, which is denoted by ϕ, is given by  x  s  x d  x ,(1)

where d and s are, respectively, the distance from thenearest wall boundary, and the sign that indicates the inside or outside of the calculation domain. The normal
vector in the particle-wall interaction npw and normalcompact of overlap δpwn are given by
npw 




(2)

  rp  npw ,

(3)

and

δpw n

where rp is the particle radius. Finally, in the new SDF,
the normal component of the contact force between theparticle and the wall is given byFCn  kδpw n   v rn  .

(4)

The tangential component of the contact force is obtained133

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in the same way as the traditional DEM as kδpw t  v rt
v rt
FC t   s FC n v
rtFC t    FC n
FC t    FC n,(5)

where vrt and μ are the tangential components of relative
velocity of the interacting particles and friction coefficient, respectively. Note that ϕ is not necessary in the tangential component of the elastic force.
A number of validation tests have proven the adequacyof the SDF model, specifically, for a ribbon mixer(Basinskas and Sakai, 2016b), a pot blender (Basinskas
and Sakai, 2016a), a twin-screw kneader (Sakai et al.,2015), and powder die-filling (Tsunazawa et al., 2015).

2.2 Wall boundary model for the CFD
Some CFD techniques have been proposed for modeling arbitrary-shaped wall boundaries, one of which adopts
an unstructured grid (Adam et al., 2016; R. Hu et al.,2019), where meshes are generated along the boundary.
Although this technique is well established, it poses a
problem on the mesh size, namely, the mesh size becomes
extremely small when highly complicated boundaries aremodeled. In addition, treatment of a moving wall is extremely difficult.
The IBM can be employed to overcome these problems.
With the IBM, the boundary profiles are projected to thenon-conforming computational grids. As such, Cartesian
grids can be used even with the existence of complicatedwalls. The IBM eliminates the necessity of mesh generation along the boundary. Thus, the IBM is more efficientthan boundary-fitted meshes. Fig. 1 shows schematicallythe boundary-fitted coordination system and the IBM.
Incidentally, the IBM falls under two categories (Lu etal., 2016). One is the so-called “continuous forcing”(Peskin, 2002) approach, in which control points are distributed over the boundary surface to modify the velocity
field. The other approach is called “direct forcing”(Kajishima et al., 2001; X. Sun and Sakai, 2016; Udono
and Sakai, 2017), in which the boundary profile is projected directly to the fluid grid. Moreover, transfer of wall
information to the computational grid plays a dominantrole, for which an efficient method of projection is required.
The numerical technique combining the IBM with the
SDF geometrical representation has been proposed(Xiaosong Sun and Sakai, 2016), with an objective of obtaining the local boundary profile easily. In the multiphase flows, the SDF provides a unified description ofwall boundary for both the solid and fluid phases, defining
superior computational efficiency. The numerical algorithm is shown briefly as follows.

134

Fig. 1

Overview of typical computational grid systems.

Governing equations for the fluid phase include thecontinuity and Navier–Stokes equations, where the local
volume average technique is introduced. These equations
are expressed as follows:    u 
0,
t

(6)

 u   uut p  f s     τ   ɡ ,

(7)

and

where ε, u, ρ, p, fs, τ, and ɡ are, respectively, the void
fraction, fluid velocity, fluid density, fluid pressure, solid–
fluid momentum exchange term, viscous stress, and gravitational acceleration. Combined Ergun (Ergun, 1952) and
Wen–Yu (Wen and Yu, 1966) equation is often used in theevaluation of the drag force acting on a computational
particle.
The IBM can simulate the solid–fluid interaction andeven utilizes structured grids, for which the object size
should be sufficiently larger than the mesh size. With theIBM, the volume-weighted average velocity is used to analyze the interaction between the fluid and the solid object. The volume-weighted average velocity U is
calculated byU
1   u  uobj.

(8)

In Eq.(8) α and uobj indicate the local volume fraction(LVF) of the object and the object velocity. Here α can be
determined efficiently by counting the saved points of theMikio Sakai et al. / KONA Powder and Particle Journal No. 37 (2020) 132–144

SDF in a CFD grid. Note that this volume-weighted velocity is used instead of fluid velocity, and the whole calculation domain is solved as a fluid, even inside the solid
object.
When fluid velocity u is replaced by the volume-­
weighted average velocity U, Eq. (7) can be updated as U    UU t p  f s     τ   ɡ  FIB ,(9)where FIB is the correction term in the IBM. The force
term FIB is given by

FIB  uobj  U 
Δt

.

(10)

Very recently, the authors have shown that fluid flow
might not be calculated suitably when the IBM is used as
the wall boundary. This problem can be solved by considering the density scaling coefficient (Sun and Sakai,2017), which is given by  0 scale  , otherwise

(11)

where γ is the density scaling factor. Actually, the density
is scaled in the pressure Poisson equation, where the grids
are filled by the object. Eventually, the pressure Poisson
equation is be given by  n 1 
 p n 1 
 scale
1   n 1   n    n 1U *  ,
Δt  Δt(12)with the density scaling factor being introduced. In Eq.
(12), superscript n + 1 and n are updated iteration number
and present iteration number.

filling. In the Advanced DEM-CFD method, combinationof the SDF and the IBM was introduced into the DEMCFD method. The schematic diagram of the die-fillingsystem is shown in Fig. 2; here, the shoe was moved by
0.10 m/s toward the left side. In this study, calculations
and experiments were performed under fair conditions.
The target powder was NONPAREIL-108® (FREUNDCORPORATION). The particle size and the particle density were, respectively, 200 μm and 1,379 kg/m3, and thenumber of the calculated particles was 150,000. A combination of the SDF and IBM was used for the wall boundary model for the DEM and the CFD. Fig. 3 displays theschematic diagram of the die-filling system. Fig. 3(a) is
the scalar field of the SDF, where the sign of the calculation domain and inside of the objects respectively became
positive and negative. The SDF was created independently
to each object. The interval of the SDF was usually
one-quarter of the particle size. Fig. 3(b) designates the
LVF for the IBM. When the object was fulfilled in a CFD
grid, the value of the LVF of the gas phase, namely, 1 – α,became zero. By calculating the values of the LVF, interactions between the object and fluid could be simulated
through the IBM. In order to show the influence of airflow
on the flow of the solid particles, two kinds of simulations
were performed: a DEM simulation for a single granular
flow and a DEM–CFD simulation for a gas–solid flow.
The calculation results are presented in Fig. 4. Die-filling
simulation by the DEM–CFD method, where air flow was
taken into consideration, demonstrated the appearance ofa clearance on top of the powder bed, as illustrated inFig. 4(a). On the contrary, the powder was fulfilled when
the DEM was simulated without air flow.
Actually, the powder bed shape obtained from the
DEM–CFD simulation exhibited an excellent agreementwith that of the experiment. Hence, consideration of the
air flow was shown as an indispensable factor for the simulation of the die-filling in pharmaceutical powders.

2.3 Powder flow involving airflow in die-filling
As a typical gas–solid flow system with a moving wallboundary, the powder die-filling is a preferable example.
To date, fundamental studies of die-filling (Zakhvatayeva
et al., 2018; Baserinia and Sinka, 2019) have been extensively focused in pharmaceutics. As far as the pharmaceutical particles are concerned, not only the particle size
is small but also their density. Hence, the drag force acting on these particles is exceptionally high. This fact implies that solid particle behavior can be precisely
simulated if solid–fluid interaction, gas flow, and moving
wall boundary are precisely modeled.
In the authors’ group, the Advanced DEM–CFD
method (Yao et al., 2018) was proposed for investigating
the effect of air flow on the particle filling state in die-­Fig. 2

Schematic diagram of a die-filling system (Yao et al.,2018) Copyright: (2018) Elsevier B.V.

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Fig. 4
Fig. 3

Wall boundary modeling by the SDF and IBM.

2.4 Industrial fluidized bed
A fluidized bed is extensively investigated by numerical simulation, where the DEM–CFD method is widely
employed. At present, application of the DEM–CFD
method to industrial fluidized beds (Sakai, 2016; C. Hu etal., 2019; Ge et al., 2019; Stroh et al., 2019) is among theimportant research topics. Not the shape of industrial fluidized beds is always simple, though rectangular systems
have been employed in the existing fluidized bed simulations. Nonetheless, the structure of actual fluidized beds
might be extremely complex, as tubes might have been
inserted, a slope might have been set at the bottom, orthey must have been equipped with cyclone. As a matterof course, number of the solid particles becomes huge in
the industrial systems. In this sense, besides modeling of
the calculation domain shape, the number of the computational particles becomes a critical problem as well. The
authors’ group attempted to solve the problem with thelimit of the calculated particles by developing a coarse
graining DEM (Sakai and Koshizuka, 2009; Sakai et al.,2010; Sakai et al., 2012b; Sun et al., 2014; Takabatake etal., 2018), in which largely modeled particles represent thegroup of the original particles where total energy between
them is assumed to agree. The adequacy of such approach

136

Effect of air flow on the powder filling.

has been shown through verification and validation tests,
in which the combined SDF–IBM was employed in the
numerical simulations for the fluidized bed. Very recently,
the compatibility of the coarse graining DEM and thewall boundary model of SDF/IBM has been proventhrough validation tests (Mori, Wu and Sakai, 2019),
whose results are addressed in this paper.
A schematic diagram of the fluidized bed system is illustrated in Fig. 5. In the fluidized bed, four tubes wereinserted. Gas was injected at 0.2 m/s from the bottom
side; glass beads were used for the powder and gas for air.
The coarse graining DEM was employed in this study;
hence, the number of computational particles could bedrastically reduced than the actual one. Namely, thecoarse grain ratio was 5.0 for 250,000 calculated particles.
Actually, the number of solid particles reached the orderof seven digits, and hence, calculation could not be performed without the coarse graining DEM on a single PC.
Hence, application of the coarse graining DEM makes it
possible to perform large-scale gas–solid systems with asmaller number of the calculated particles, as compared
to using the actual number. The SDF and the IBM were
employed as the wall boundary model, as depicted inFig. 6. In Fig. 6(a), the calculation domain was expressedas positive in the SDF. LVF of the gas phase (1 – α) was
zero inside of the object in the IBM, as illustrated inFig. 6(b).

Mikio Sakai et al. / KONA Powder and Particle Journal No. 37 (2020) 132–144

Fig. 5Three-dimensional fluidized bed system (Mori, Wu andSakai, 2019) Copyright: (2019) Elsevier B.V.

Fig. 7 designates snapshots obtained from the validation tests. Note the excellent agreement between the calculated and experimental results. Specifically, bubble
behavior and spatial location of the particles in the simulation and in the experiment were in good agreement. Besides, the pressure drop quantitatively agreed in thecomputation and the experiment. Thus, the coarse graining DEM was shown capable of simulating the macroscopic behavior of the original gas–solid flow system,
although the particle size was larger than the actual one.
This is because the total energy was modeled to agree
between the coarse grain particle and a group of the original particles. In fact, the calculation has been done prior
to the experimentation. Surprisingly, the agreement
could be obtained without any necessary adjustment in
the calculation.

Fig. 6

Wall boundary model in a gas-solid flow simulation.

highly viscous fluid flow and the heat flux on the fluid
surface, which are described herein.

3. Mesh-free particle method for a phasechange problem

3.1 The MPS method for phase change simulation

Modeling the phase change between the solid and liquid phases is one of the challenging problems in the CFD.
The mesh-free particle method is a promising approach tosimulate the phase change, and has been applied into various systems, such as additive manufacturing (Russell etal., 2018), welding (Wang et al., 2018), and nuclear severe
accidents (Duan et al., 2019). During a phase change, thesolid and liquid states are mixed, thus, such state is regarded as a solid–liquid flow in a broad sense. In the simulation of the phase change by the mesh-free methods, theefficient calculation for highly viscous fluid flow, as wellas supplying heat flux on the free surface, is essential.
The authors’ group has developed certain models for the

The original MPS method (Koshizuka and Oka, 1996)
has been developed for an incompressible fluid flow,where the pressure Poisson equation is calculated implicitly. Recently, weakly incompressible algorithm has been
introduced into the MPS method by calculating the pressure explicitly. Such method is referred to as E-MPS
method. Here, the kernel functions are the same as theoriginal ones. In general understanding, the accuracy of
the E-MPS method is quite similar to that of the original
MPS method, as both have been employed even in thesolid–liquid flow states in chemical engineering (Sakai etal., 2012; Yamada and Sakai, 2013; Sun et al., 2014). Modeling of the phase change between the solid state and137

Mikio Sakai et al. / KONA Powder and Particle Journal No. 37 (2020) 132–144

 2Φ

i

2D
 Φ j  Φi  w rj  ri  ,
Ωn 0 j  i(18)where D, n0, r and Ω are, respectively, dimension, initial
particle number density, position vector, and Lapracian
constant in the MPS method. In these models, weightfunctions are used to give smoothed interpolation for
quantities through the interaction between fluid particles.
In order to perform a phase change, the enthalpy is introduced as,hs  C pTm ,hhs  L,l
Fig. 7

Validation test result in a fluidized bed (Mori, Wu andSakai, 2019) Copyright: (2019) Elsevier B.V.

liquid state is described in the subsequent sections.
The governing equations for phase change simulationby the MPS method include a Lagrangian description of
the continuity equation, the Navier–Stokes equation, andenergy conservation equation,D   u 
0,
Dt

f 2
Du
1
1
  p  u  ɡ   n,
Dt




(13)

(14)

and
Dh

    T   Q,
Dt

(15)

where μf, σ, κ, δ and n, h, λ and Q are, respectively, fluid
viscosity, coefficient of surface tension, curvature, delta
function, normal vector, enthalpy, heat conductivity andheat source. In Eq. (15), the heat flux can be given as thevolumetric heat source,

Q   q,

(16)

with q as the heat flux.
Moreover, in the MPS method, the pressure and viscous terms in the governing equations are modeled by agradient model and a Lapracian model. Regarding fluid
particle i, these models are given by

Φ i

and

138

 Φ j  ΦiDr  ri  w rj  ri  ,


2  j
0
n j  i  rj  ri


(17)

(19)
(20)

where hs, Cp, Tm, hl, and L are, respectively, enthalpy ofthe solid phase, heat capacity, melting temperature, enthalpy of the solid phase, and latent heat. Incidentally,solid state is simulated as exceptionally highly fluid expressed by Arrhenius viscosity formula.
When the viscous term is calculated implicitly, updated
fluid velocity uk+1 can be obtained by the expressions,u*  u k1
 ɡ   p,
t


(21)


u k 1  u*
 f  2u k 1.

t

(22)

A detailed discussion on the MPS method is presented
in the original papers (Koshizuka and Oka, 1996).

3.2 Investigation on the calculation efficiency of ahighly viscous fluid
First, implicit calculation of the viscous term is shown
to be efficiently performed in the simulation of a discharged fluid flow in a glass melter.
In this system, kinematic viscosity, fluid density, andsurface tension coefficient were, respectively, 0.03 m 2/s,
2500 kg/m3, and 0.3 N/m. The highly viscous fluid was
flown by only the gravitational force. Fig. 8 illustrates thesnapshots obtained from a simulation of a discharged flowof the highly viscous fluid in a glass melter (elapsed time:
5.0 s, 10 s, 15 s and 20 s). Here, the volume flow rate in
the simulation agreed well with the experiment, in thesteady state. Subsequently, the acceleration due to the implicit model was investigated based on the maximum
value of the time step. Specifically, the time step ratio of
the Courant condition to diffusion number was roughly
10 –4, which implies that the computation could be accelerated up to 104 times faster than the original viscous calculation model in this system. Thus, the efficiency of theimplicit calculation algorithm was proven in the highly
viscous fluid flow system.

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Fig. 8Highly viscous fluid flow in a glass melter (Sun et al.,2012) Copyright: (2012) Elsevier B.V.

Fig. 9Verification test system for the heat flux model in the
MPS method (Takabatake et al., 2016) Copyright:(2016) Elsevier B.V.

3.3 Adequacy of the heat flux model in a meshfree particle method
Subsequently, the adequacy of the heat flux model ismentioned in the MPS simulation. In the MPS method,
instead of the heat flux, the temperature is usually given(the Dirichlet boundary condition) at the free surface due
to ease. On the contrary, heat balance cannot be kept if
the heat flux (the Neumann boundary condition) is not
given. As shown in Eq. (16), the heat flux can be introduced into the mesh-free particle method as heat source.
This attempt has been done very recently by the authors(Takabatake et al., 2016).
The adequacy of the heat flux model was examined via
heat transfer simulation in a simple system (Fig. 9).
As boundary conditions, heat flux was 25,000 W/m2 at
the top of the rectangle, while the temperature at the bottom was 300 K. Regarding the physical properties, thedensity, kinetic viscosity, specific heat, and thermal conductivity were, respectively, 1,000 kg/m3, 1.0 × 10 –3 m2/s,
10 J/(kg K), and 50 W/(m K). Temperature distribution in
the calculation and theoretical results were later compared.
The calculation result is shown in Fig. 10. Temperature
increased gradually from the initial value (300 K). The
temperature distribution achieved a steady state in 20 s
and was found to quantitatively agree with the theoreticalresults. This result implies that the heat flux can be given
even in the mesh-free particle method, where the free surface is violently moved.
This aside, a phase change simulation was performed
through the supplied heat flux. Two types of materials,
namely, Material-l and Material-2, were used in the calculations. The density, kinetic viscosity, specific heat, thermal conductivity, latent heat and melting temperature ofMaterial-1 were, respectively, 1,000 kg/m3, 1.0 × 10 –3 m2/s,

Fig. 10 Temperature distribution in the verification test
(Takabatake et al., 2016) Copyright: (2016) Elsevier
B.V.

100 J/kg K, 50 W/m K, 10,000 K, and 1.0 × 10 4 J/kg.
Material-2 had the same density, kinetic viscosity, and latent heat, while the specific heat, thermal conductivity,and melting temperature were, respectively, 10 J/kg K,
500 W/m K, and 320 K. As far as the boundary conditions
were concerned, the initial heat flux was 100,000 W/m2
on the upper side and the temperature was 300 K at thebottom side.
Snapshots obtained from the phase change calculation
are shown in Fig. 11. Due to the heat flux, the upper side
was molten at the beginning. Solidification occurred as
the molten fluid approached the floor, as the floor temperature was kept at 300 K. Hence, simulation of thephase change was demonstrated by the MPS method.

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Fig. 11 Snapshots obtained from a phase change simulation(Takabatake et al., 2016) Copyright: (2016) Elsevier
B.V.

4. Conclusions
This paper described a cutting-edge modeling on simulations for multi-phase flows using the DEM and the MPS
methods.
Relative to the DEM, a brand-new wall boundarymodel was introduced, namely, a combinational model ofthe SDF with the IBM, which was shown to be useful ingenerating an arbitrary shape wall boundary in the DEM–
CFD simulation. Such new model is advantageous in thesense that an arbitrary shape wall boundary could be created by a simple operation, and thus, it might be standardized in the future DEM–CFD simulations.
Regarding the mesh-free particle method for continuum
such as the MPS method, the phase change problem has
generally been a challenging topic. An implicit calculation method, along with the heat flux model, was developed for efficiently simulating the phase change. The
usefulness of such heat transfer modeling was demonstrated in this paper. Hereafter, it is expected to contributeto the numerical simulation of a thermo-mechanical problem.

Acknowledgments
Parts of this study were financially supported by JSPS
KAKENHI Grant Numbers 17H02825 and 17KK0110.

NomenclatureIBM

immersed boundary methodCPU

central process unitGPUgraphical processing unitD

dimension number (–)

FCnnormal component of contact force (N)FCttangential component of contact force (N)FIB

correction term in the IBM (N/m3)

fs

solid–fluid momentum exchange term (N/m3)

ɡgravitational acceleration (m/s2)

hsenthalpy of solid phase (J/m3)hlenthalpy of liquid phase (J/m3)kspring constant (N/m)

L

latent heat (J/kg)nnormal vector (–)

npw

normal vector in the particle-wall interaction (–)

n0initial particle number density (–)

p

fluid pressure (Pa)Q

heat source (W/m3)rdistance between two fluid particles (m)rpparticle radius (m)Δttime step (s)Uvolume-weighted average velocity (m/s)

uobj

object velocity (m/s)

vrrelative velocity of the interacting particles (m/s)α

local volume fraction of a object (–)δpw

displacement in particle-wall interaction (m)δdelta function (–)ε

void fraction (–)ϕ

signed distance function (m)γdensity scaling factor (kg/s)

η

damping coefficient (–)κ

curvature (m–1)λ

heat conductivity (W/m K)

μfviscosity (Pa s)

μs

friction coefficient of a solid particle (–)Ω

Lapracian constant in the MPS method (–)ρ

fluid density (kg/m3)

DEM

discrete element methodσcoefficient of surface tension (N/m)

CFD

computational fluid dynamics

τviscous stress (N/m 2)

MPS

moving particle semi-implicit

SDF

signed distance function

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Authors’ Short Biographies
Mikio Sakai
Dr. Mikio Sakai is currently Associate Professor in Resilience Engineering ResearchCenter in The University of Tokyo. He earned his Ph.D. degree from The University ofTokyo in 2006. Then, he became Assistant Professor in 2007 and Associate Professor in2008 in the same university. He has been Visiting Reader at Imperial College London
since 2016. He extensively studies modeling of granular flows, multi-phase flows and theheat transfer, besides the parallel computation techniques. He is a world-leading professor in computational granular dynamics, and hence, has delivered lots of invited lecturesin conferences. He holds important posts in powder technology community, such as Director of Society of Powder Technology of Japan and Head of Simulation & Modeling
Division in Association of Powder Process Industry and Engineering, JAPAN. At present, he is also Associate Editor of Chemical Engineering Science and Editor of Granular
Matter.

Yuki Mori
Mr. Yuki Mori is currently a freshman PhD student in Department of Nuclear Engineering and Management, School of Engineering, The University of Tokyo, and is JSPS
Research Fellow (DC1). He joined Prof Sakai’s group since 2016 and won Dean’s Award(Annual Best Student Award) upon completion of his masteral course in The Universityof Tokyo.

Xiaosong Sun
Dr. Xiaosong Sun earned his Ph.D. degree from The University of Tokyo in 2016. Then,he became Project Researcher in Resilience Engineering Research Center, School of Engineering, The University of Tokyo. He joined Prof Sakai’s group since 2011 and won Dean’sAward (Annual Best Student Award) upon completion of his masteral and doctorate
courses in The University of Tokyo.

Kazuya Takabatake
Mr. Kazuya Takabatake is currently a third-year PhD student in Department of Nuclear Engineering and Management, School of Engineering, The University of Tokyo,
and is JSPS Research Fellow (DC2) since 2018. He joined Prof Sakai’s group since 2015
and won Dean’s Award (Annual Best Student Award) upon completion of his masteralcourse in The University of Tokyo.

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KONA Powder and Particle Journal No. 37 (2020) 145–165/Doi:10.14356/kona.2020019

Review Paper

Rheology and Sedimentation of Aqueous Suspension of
Na-montmorillonite in the Very Dilute Domain †Yasuhisa Adachi 1*, Yoko Tsujimoto Kawashima 2 and Muhamad Ezral Bin Ghazali 3
1

Faculty of Life and Environmental Sciences, University of Tsukuba, Japan
Innovative Materials and Resources Research Center, Public Works Researches Institute, Japan
3
Graduate School of Life and Environmental Sciences, University of Tsukuba, Japan
2

Abstract
The scheme of DLVO theory and the concept of fractal structure of flocs applied to the suspension ofmontmorillonite have revealed out the unique nature of this clay dispersion. In this context, two major regimes arerecognized. The first is the electrostatically dispersed regime. And the second is the coagulated regime. In theformer, the formation of a diffusive electric double layer (EDL) characterized by reciprocal Debye length
measured from the surface of the particle is distinctively important. Intrinsic viscosity with electroviscous effects
and yield stress are interpreted by the steric presence of EDL. In the latter, the unit of transportation is a
coagulated floc with finite cohesive strength. Sedimentation process reflecting these factors is carefully observed
to recognize the turbulence generation by the formation of large flocs at the moment of gel collapse. Waiting timeprior to gel collapse was found to be determined reflecting the pH-dependent charging behavior. By taking into
account the effect pH-dependent charge, the DLVO based two regimes are further categorized into five. The
developed tools can be extensively used for the system involved with different ionic species, pH, volume fraction
and organic substances.
Keywords: Na-montmorillonite, Debye length, electroviscous effect, floc, cohesive strength, sedimentation
turbulence

1. Introduction
In a natural environment, nutrients and chemical pollutant are apt to adsorb on the colloidal particles which
are ubiquitously present in soil and water. Clays are major
components of environmental colloid. Understanding the
behavior of such colloid is critically important to predictthe diffusion and fate of chemical substances. In addition
to agricultural production, knowledge has been recognized very useful for the design and the development of
the technology of environmental remediation. Macroscopic transport properties in soils are determined reflecting microscopic interaction of colloidal phenomena insoils (Adachi Y. and Iwata S., 2003; Adachi Y., 2019).
Rheological properties of an aqueous dispersion of clay
have also received many attentions with respect to thetransportation of cohesive sediment in river and estuary†

Received 31 July 2019; Accepted 16 September 2019
J-STAGE Advance published online 31 October 2019
1,3
1-1-1 Tennoudai, Tsukuba, Ibaraki 305-8572, Japan2
1-6 Minamihara, Tsukuba, Ibaraki 305-8516, Japan* Corresponding author: Yasuhisa Adachi;
E-mail: adachi.yasuhisa.gu@u.tsukuba.ac.jp
TEL: +81-298-534862(Winterwerp J.C and Kestern W.G.M.V., 2004), land consolidation (Sudo S. and Yasutomi R., 1961), drilling mud
for construction work and petroleum production (Van
Olphen H., 1977) and usage in variety of application suchas cosmetic, paint, agricultural chemical, cement, ceramics, and so on (Lagaly G. and Ziemer S., 2003).
One of the typical clays with outstanding surface properties is the montmorillonite, which is a pure componentof bentonite; a usually used clay industry. Interesting nature of the aquatic system of montmorillonite has classically received scientific attention in the direction toswelling (Norrish K., 1954) and phase separation(Langmuir I., 1938; Michot L.J. et al., 2009). Another interest is also paid for the direct verification of DLVO theory (Callaghan I.C. and Ottewill R.H., 1974). In thepresent article, we limit our attention to the rheologicalproperties of Na-montmorillonite suspension and sedimentation process of the same clay. Although the choiceof Na-montmorillonite seems rather arbitral, this choice
will be turned out to be appropriate to remind typicalcommon features of soil colloid without losing their characteristic factors. The shape and distribution of electriccharges in the unit of clay particles will realize thesimplification of the complex nature of soil colloids in

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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terms of flocculation properties. They are the features ofadsorbing ions, the pH dependency of colloidal stability
in the framework of DLVO theory (Derjaguin B.V. andLandau L.D., 1941; Verwery E.J.W. and Overbeek J.Th.G.,
1947) and the concept of fractal nature of the structure of
aggregates (Cipelletti L. et al., 2000) and cohesive force
between the colloidal particles in the aggregate (Adachi Y.
et al., 2019).
A primitive and the most representative picture of theunit of montmorillonite is shown in Fig. 1. As illustrated
in this figure, the smallest unit is a very thin sheet with athickness of one nanometer and with a basal length scaleof a few hundred nanometers. The layer consists of two
different sheets. One is silica tetrahedral sheets which arelocated outside of unit clay sheet. The other is aluminaoctahedral sheet hold between two silica sheets. An isomorphous substitution such as from Al3+ to Mg2+ or Al3+
to Fe3+ taking places in the alumina sheet yields permanent negative charges at the face of the layer.
Due to the location of the substitution which taking
places at the alumina octahedral sheet sandwiched at thecenter of two silica layers, direct contact with water molecules or solving cations to the charged part of molecules
which will lead to irreversibly strong bond is avoided
when the sheet is immersed in water. Cations are considered to be adsorbed onto the surface of montmorillonite
sheets with hydrated layer of water molecules more orless reversible manner. Such a situation can be considered
to be suitable for the generation of exchangeable ions at
the surface of the sheet. In addition, it is known the resulted frequency of the substitution is approximately every 1 nm which induces significantly high value of cationexchange capacity to maintain a large amount of exchangeable mineral nutrient near the surface of montmorillonite sheet. This is very suitable to provide thecondition of abundant bio-available minerals for crop production. The accumulation of such clay will bring about
the fertility of soils.

Fig. 1146

A representative picture of the unit of montmorillonite.

On the other hand, the broken bonds located at the edgeof the layer have a capacity to adsorb H+ or OH– resulting
in the appearance of pH-dependent charge. Therefore,such charging property causes different types of associations between two sheets which are strongly pH-dependent(Tombacz E. and Szekeres M., 2004; Heath D. and TadrosF., 1983). In the acidic condition, the association between
Edge-Face is considered to be dominant and in alkalinecondition, Face-Face association will be dominant. A
pH-dependent charge at the edge of the sheet is also important when the interaction between natural organic
matter most of which has groups with pH-dependent
charge is analyzed (Ramos-Tejada M.M. et al., 2001).
Unique rheological characteristics and sedimentation behavior of montmorillonite suspension will be influenced
by such different associations.
In the present article, our attentions are limited to dilute suspension to clarify the relationship between the microscopic interaction at the level of colloidal surface andthe macroscopic behavior such as mechanical properties
and hydrological transportation. Our purpose here is tointroduce the variety of resulted behaviors which appears
reflecting just microscopically different conditions aroundthe clay particles. For this purpose, the framework of theclassical theory of electric double layer (EDL) (Gouy M.,
1910; Chapman, 1913) and DLVO (Derjaguin B.V. andLandau L.D., 1941; Verway E.J.W. and Overbeek J.Th.G.,1948) are confirmed to be very useful. In this respect, weregard the Debye reciprocal length which can be the index
of the thickness of EDL is one of the most important parameters. The value is expressed as, 1 

1e2

izi2nio(1) 0 r kT

By the analysis of dielectric spectroscopy and electrokinetic spectroscopy, we recognized κ–1 is also an important parameter (Tsujimoto Y. et al., 2013; Ishida T. etal., 1999).
However, this is not sufficient from two points. One isthat the colloidal stability is influenced by the above-­mentioned variety of pH-dependent associations. The
other is the lack of description of flocculated material.
That is, the geometrical structure (Adachi Y. and Ooi S.,
1990) and the strength of formed floc (Kobayashi M. etal., 1999; Kobayashi M., 2004) need to be considered(Adachi Y. et al., 2019). These two factors will be explained by the concept of fractal nature of flocculated
montmorillonite and the concept of cohesive strength offloc. These aspects can be understood by referring our recent result on the basis of hydrodynamic analysis. We will
also add our recent result of the sedimentation of flocculated montmorillonite which also demonstrates the significant
finding of the generation of turbulent flow when theYasuhisa Adachi et al. / KONA Powder and Particle Journal No. 37 (2020) 145–165

material is strongly cohesive. The waiting time for gel
collapse prior to the onset of sedimentation turbulence isaffected also by the pH-dependent charge (Wu M. andAdachi Y., 2017). That is, microscopic pH-dependent
charge also affects the macroscopic behavior.

2. Scheme of rheological data
2.1 Three regimes
The behavior of relative viscosity of dilute suspension
or the yield stress of slightly higher concentration of
Na-montmorillonite is summarized as a function of ionicstrength in the monograph of clay colloid chemistry (Van
Olphen H., 1977). The most typical pattern obtained forthe dilute suspension (0.23 %) using the rheometer takenfrom the text is shown in Fig. 2.
As shown in the figure, in the limit of low ionicstrength, relatively high value of viscosity is observed.
But the value of viscosity decreases dramatically with theincrease of ionic strength and after passing through theminimum value, it will increase again monotonously withan increase of ionic strength (Abend S. and Lagaly G.,
2000; Ali S. and Bandyopadhyay R., 2016). Similar behavior of the yield stress against ionic strength is also reported (Van Olphen H., 1977). The development ofdiffusive electric double layer formed around the montmorillonite sheet induces the electro viscous effect, thus
resulting in the high resistance against flowing motion.
On the other side, the increase of ionic strength will resultin the depression of diffusive part of electric double layer.
And in the extreme case, as predicted by the DLVO theory, flocculation is induced by the effect of van der Waals
attractive force. With these pictures, in the system ofslightly high concentration of montmorillonite: 1) Repul-

Fig. 2

Relative viscosity of a 0.23 percent (weight) Na-­
montmorillonite sol as a function of the amount of
NaCl added.

sive gel, 2) Intermediate dispersion and 3) Attractive gel,are recognized.

2.2 Capillary viscometer
It should be noted that in the flocculation region, theviscosity increases more gradually than that of the steep
slope observed for the limit of low ionic strength. By carrying out the additional experiment against pH change
and also with some observation of thixsotropy, Van
Olphen H. (1977) proposed various types of association
between clay sheets such as Edge-Edge, Edge-Face andFace-Face. As a result, microscopic card house structure
and layered stuck have been considered. However, it is noteasy to quantify these effects. Now the question arises,
how to quantify these pictures. This question was thestarting point of our long trip of study. Since it is known
that the measurement of intrinsic viscosity polymer solution using capillary viscometer (Fig. 3) will provide information of polymer conformation, we decided to apply
the same method to the analysis of montmorillonite suspension.
Usually, the viscosity of colloidal suspension is expressed as a function of the volume fraction of solid. The
most basic expression for the relative viscosity can be
written as a power series. That is,r  
1  K1  K 2 2 0(2)Where ηr denotes the relative viscosity. K1 is usuallyreferred as intrinsic viscosity which represents the increment of energy dissipation due to the interaction of aparticle and surrounding fluid and K2 is termed as the
Huggins’ coefficient representing the factor due to the interaction between two particles. Theoretical values of K1
and K2 for a suspension of rigid sphere were obtained 2.5(Einstein A., 1905) and 6.7 (Batchelor G., 1976), respectively. These values will increase reflecting the shape,
the degree of flocculation by means of the increase ofimmobile water. It should be noted that the square of K1 isFig. 3

Schematic illustration of capillary viscometer.

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close to K2.
In practice, we use the value of reduced viscosity defined as,  1    0 red
 K1  K 2 
  





(3)

If we plot ηred against ϕ, we can obtain K1 and K2, fromthe intercept and slope of the plot, respectively. Our dataof reduced viscosity of montmorillonite suspensions areplotted against volume fraction for various ionic strengthin Figs. 4 and 5. The former is the case of high ionicstrength. And the latter is the case of low ionic strength.
As for the data plotted in Fig. 4, we can immediately
draw the following conclusions: (1) K1 is significantly

Fig. 4/sϕ versus ϕ at various NaCl concentrations
1
0(pH = 10 ± 0.1). Reprinted with permission from Ref.
(Miyahara K. et al., 1998). Copyright: (1998) Elsevier
B.V.

larger than 2.5 reflecting the shape of montmorillonite.
The value is roughly a few hundred. (2) The considerable
value of the slope of all plot demonstrates significant effect of the interaction between clay sheets. (3) K2 increases monotonously with an increase of ionic strength.
It should be noted that this tendency will continue in theregion of rapid coagulation; the tendency is still much enhanced in the region where the concentration of NaCl ishigher than 1.0 M. The reason for their results will be described in section five.
In the meantime, from the data plotted in Fig. 5 for theregion of low ionic strength; much lower than CCC (critical coagulation concentration), we can conclude as follows. (1) K1 is smaller than the value demonstrated inFig. 4. It is due to the reflection of smaller size of flowing
unit under the condition of electrostatically dispersed
state. (2) Small increase of K1 and K2 by decreasing ionicstrength is confirmed. This result is an implication ofelectroviscous effects. That is, the decrease of ionicstrength means the increase of the thickness of electric
double layer. The increment of K1 denotes a primary electroviscous effect due to the interaction between the
charged sheet and ambient fluid containing ionic atmosphere. The increment of K2 denotes a secondary electroviscous effect which can be ascribed to the additional
interaction of the two EDLs surrounding the two charged
sheets.
As demonstrated so far, schema of the rheological data
proposed by Van Olphen H. (1977) was confirmed systematically to be reproduced by the simplest measurementof viscosity of dilute suspension. However, it is obviousthat the formed flocs are much bigger than the diameter ofcommercially available capillary viscometer, and theanalysis of zero shear limit behavior to correlate withyield stress desirable. This was the motivation to continue
further investigation on the flowing behavior of the suspension in extremely low shear rate, the yield stress andstrength of coagulated flocs.

2.3 Spiral viscometer

Fig. 5148

Reduced viscosity of the Na-montmorillonite suspension at various NaCl concentrations. Reprinted withpermission from Ref. (Adachi Y. et al., 1998b). Copyright: (1998) Academic Press.

Spiral type viscometer is a home-made capillary viscometer which we developed in order to analyze zero
shear and dilute limit (Kobayashi S. and Adachi Y., 2005;
Tsujimoto Y. and Adachi Y., 2011). As depicted in Fig. 6,
this viscometer is composed of two graduated cylinders
connected by a long capillary tube. This system enables
to measure viscosity at low-pressure gradient, which ismore than one thousand times smaller than the normal
capillary viscometer. The difference of the water levels in
the cylinders changes over time will eventually approachzero pressure gradients. The temporal variation of the difference of water level provides the information on therheological behavior of suspension in the zero shear

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Fig. 6

Fig. 7h(t)/h0 against t, where pH of NaCl ~ 10 (ϕ = 5.0 × 10 –4[–], ◆ : I = 1.0 M, ○: I = 1 × 10 –1 M, ×: I = 1 × 10 –2 M
and △ : I = 1 × 10 –3 M) Reprinted with permission
from Ref. (Kobayashi S. and Adachi Y., 2005). Copyright: (2005) The Japanese Society of Irrigation, Drainage and Rural Engineering.

Fig. 8h(t)/h0 against t, (ϕ = 1.0 × 10 –4 [–], ■: I = 5.0 × 10 –2 M,▲: I = 1 × 10 –2 M and ●: I = 5 × 10 –3 M). Reprinted
with permission from Ref. (Tsujimoto Y. and AdachiY., 2011). Copyright: (2010) Elsevier B.V.

Schematic illustration of spiral-type viscometer. Reprinted with permission from Ref. (Tsujimoto Y. et al.,2014). Copyright: (2012) Elsevier B.V.

limits.
Assuming the law of Poiseullie flow, the volumetricflow rate in the tube, Q is given as functions of scale ofthe viscometer by,Q  gh 4D128 L(4)

Where h indicates the difference of the levels. In our investigation, we used the viscometer with the length, L,
and the inner diameter, D, of the tube is one m and2.40 mm, respectively.
Based on the conservation of mass, the flow rate in the
tube is equal to the half of the temporal change of the difference level times cross section of cylinder, A. That is
Q 

1 dh
A
2 dt

(5)

From the substitution of the relation of Eqn. (4) into
Eqn. (5), the functional form of h(t) is simply obtained
from the integration with initial condition. That is
ln

h(t )
gD 4  th0
64 AL markably against ionic strength. It should be noted that
small flow rate is confirmed for the cases of extremely
low ionic strength and high ionic strength and that for
both cases, a considerable increase of viscosity was observed in the later period when pressure gradient is reduced.

(6)

The viscosity of suspensions is obtained from the slopeof the plot of ln((h(t))/(h0)) vs. t.

3. Electroviscous effects of montmorillonite
suspensions

2.3.1 Viscosity obtained by spiral viscometer

3.1 Introduction

The relation between ln((h(t))/(h0)) and t is easily measured manually for each chemical condition. The results
obtained for the case of coagulated suspension and electrostatically stable suspension are plotted in Figs. 7 and 8
respectively.
As demonstrated in both figures, viscosity changes re-

The development of EDL due to charging property ofclay particles is reflected in the viscosity of suspensions.
The formation of EDL around colloidal particles cancause the additional distortion energy of fluid, which iscalled electroviscous effects. There are two types of149

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electroviscous effects. The deformation of EDL due to
fluid distortion of shear causes the primary electroviscous
effect which increases the intrinsic viscosity that is also
affected by the shape of particles. Many scientists investigated in detail the change of viscosity of suspensions dueto this effect. The first systematic analysis was reported
by Booth F. (1950). In the case of montmorillonite, another interest for electroviscous effect is the relation withspillover of counter ion of basal charge to that of edge
charge (Chang F.R.C. and Sposito G., 1994, 1996; Chen
J.S. et al., 1990; Secor R.B. and Radke C.J., 1985).
On the other hand, when two charged particles flowed
to a close position by an external fluid motion, the EDL
around colloidal particles overlap which generate the additional energy dissipation. It causes an increment of viscosity and this type of electroviscous effect the secondary
electroviscous effect. It was treated theoretically by
Russel W.B. (1976, 1978) for a suspension of charged
spheres and has been regarded as one of the major factorsof non-Newtonian behavior. Krieger I.M. and Eguiluz M.
et al. (1976) pointed out that the secondary electroviscous
effects have an influence on the relative viscosity of colloidal suspension where a given shear rate can vary by
several orders of magnitude. Additionally, the effect wasproved to relate to shear thinning behavior. Buscall R.
(1991), Takamura K. and Van de Ven T.G.M. (2010) focused on the Doughetry-Krieger equation (D-K equation)
to analyze the electroviscous effects. Especially,
Takamura K et al. incorporated the particle interaction
parameter into the D-K equation. They indicated that thesecondary electroviscous effects became negligible athigh shear rate when the parameter was given to the D-K
equation as a function of Peclet number.
For montmorillonite suspensions, although experimental studies have been done, few studies focused on theelectroviscous effects. Egashira K. (1979) found that the
intrinsic viscosity of montmorillonite is 190, which ismuch larger than that of the theoretical value of sphericalparticles. However, he did not associate the high intrinsic
viscosity with the electroviscous effects. Adachi Y. et al.
(1998b) measured the viscosity of dilute montmorillonite
suspension at high pH with the Ostwald viscometer. They
found that the influence of the electroviscous effects was
remarkable in the region of NaCl concentration less than
1.0 × 10 –2 M. However, experimental data which show thedependence of the secondary electroviscous effect on theapplied shear stress are not enough. An application of spiral viscometer can be regarded as the best method to confirm and evaluate effects which is theoretically predicted
and confirmed for the suspension of charged particles.

3.2 Relationship between viscosity andelectroviscous effects
3.2.1 Experimental detection of electroviscous effect

The increment of K1 and K2 can be related to as the primary and the secondary electroviscous effects, respectively. In the case of the dilute colloidal suspension
composed of monodispersed sphere, the rheological behavior is characterized by the interaction between particles governed by electrostatic, viscous, and van der Waals
forces etc. The balance among these factors is qualitatively determined by a characteristic length. It is called
the effective collision radius (effective radius). Russel
W.B. (1976, 1978) focused on this effective radius, aeff totheoretically solve the secondary electroviscous effect.
Assuming the effective radius increase with developing
EDL, he derived the following expression of relative viscosity as
55
53  aeff  22
1     
r 

 
2
2
40  a (7)

α is a coefficient relating to the intrinsic viscosity. Also,
this coefficient is affected by the primary electroviscous
effect and can be calculated for sphere particles by Booth
F. theory. However, because of the shape of montmorillonite particles, the theoretical value of the intrinsic viscosity does not strictly agree with that for sphere (Adachi
Y. et al., 1998a).
Since the electroviscous effects are affected by the flow
field, it is considered as limitation due to the Peclet number is imposed. In fact, Eqn. (7) can be applied at only
lower Peclet number. Peclet number is the dimensionlessfunction described by the timescale for diffusive motion
relative to that for convection of flow and defined as follows
Pe 

6a 3
kT(8)

Where τ indicates the shear stress, and a indicates the hydrodynamic diameter (Adachi Y., 1995). Regardless ofPeclet number, it is useful that D-K equation, by which
Van de Ven T.G.M. and Mason S.G., (1977) and Buscall R.
(1991) to analyze the electroviscous effects, r  1  eff 


max 

2.5max(9)

Where,aeff    eff 
 a 

3

(10)

ϕmax indicates packing volume fraction. Eqn. (9) and Eqn.
(10) were used to estimate the experimental values of aeffby fitting that to our experimental data assuming

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ϕmax = 0.74 regardless of shear rate argued by Van de Ven
T.G.M. (1989).

3.2.2 Theoretical background of effective radius

The effective radius aeff is regarded as the distance inducing the distortion of the particle trajectory as shown in
Fig. 9. This value may be estimated from the balance between the electrostatic repulsive factor and factors inducing collision (Russel W.B., 1978).
The Brownian motion is dominant where Peclet number is small, the theoretical effective radius is determinedby the balance between electrical repulsive energy, Ve(r),and the diffusive energy, kT, as follows;

Ve (r)
1
kT
Where,

at r = aaff

(11)

Ve (r )  4 0 r a 2 2
 exp( r )exp(2 a)

r
kT
kT


(12)
exp( r )rr indicates the distance from a center of the particle. The
effective radius isFig. 9Illustration of the collision trajectory of colloidal particles in shear field. Reprinted with permission from Ref.
(Tsujimoto Y. et al., 2014). Copyright: (2012) Elsevier
B.V.




(13)
aeff   1 ln 
 ln(  / ln  ) On the contrary, when the Peclet number is larger thanone, the shear stress contributes to the interaction. The
mean effective radius can be estimated from the balance
between the hydrodynamic force and electrostatic repulsive force (Goodwin J.W. and Hughes R.W., 2000). The
hydrodynamic force is calculated from the Stokes drag asfollows;
Fsh  3a aeff

(14)

The electrostatic repulsive force is;1   aeff4 0 r a 2 2exp(2 a)exp( aeff )
Fe 
2
aeff

(15)

Balancing these two forces we get;1   aeff3
exp  aeff   2 2
3
aeff
4 0 r a  exp(2 a)(16)

Therefore, we can calculate the effective radius basedon the Eqn. (13) and Eqn. (16) according to Peclet number.

3.3 Relationship between effective radius andlong-distance interaction
The obtained data of the relative viscosity of montmorillonite suspensions are shown against volume fractionin Fig. 10. Although the viscosity measured by two different types of viscometers, the relative viscosity increases
with a decrease of ionic strength regardless of viscometers.
The tendency which the relative viscosity increased
rapidly rather than linear against volume fraction is remarkable especially for the data obtained by spiral viscometer.
Therefore, the secondary electroviscous effect clearly
influences the viscosity under low shear stress. The

Fig. 10 The relative viscosity (left: spiral viscometer, right: Cannon-Fensk, ( △ : I = 0 M, ▲: I = 10 –5 M, □:I = 5 × 10 –5 M, ■: I = 10 –4 M, ○: I = 5 × 10 –4 M, ●: I = 10 –3 M). Reprinted with permission from Ref.
(Tsujimoto Y. et al., 2014). Copyright: (2012) Elsevier B.V.

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Fig. 11 Relative viscosities against the applied shear stress on
ϕ = 1.0 × 10 –3 ( △ : I = 0 M, ▲: I = 10 –5 M, □:I = 5 × 10 –5 M, ■: I = 10 –4 M, ○: I = 5 × 10 –4 M, ●:I = 10 –3 M). Reprinted with permission from Ref.
(Tsujimoto Y. et al., 2014). Copyright: (2012) Elsevier
B.V.

Fig. 12 The effective radius against Peclet number ( △ :I = 0 M, ▲: I = 10 –5 M, □: I = 5 × 10 –5 M, ■:I = 10 –4 M, ○: I = 5 × 10 –4 M, ●: I = 10 –3 M). Reprinted with permission from Ref. (Tsujimoto Y. etal., 2014). Copyright: (2012) Elsevier B.V.

obtained relative viscosities are represented against theapplied shear stress in Fig. 11.
Below ionic strength of 10 –5 M, it is significant that theincrement of the relative viscosity with decreasing shear
stress. Such rheological behavior of so-called shear thinning phenomena was confirmed in the investigations forcolloidal suspensions (Krieger I.M. and Eguiluz M., 1976;
Buscall R., 1991; Takamura K. and Van de Ven T.G.M.,
2010). Based on the experimental data, we calculated andplotted the effective radius as a function of ionic strength
against Peclet number in Fig. 12.
Also, we draw lines that showed theoretical effective
radius. This value can vary depending on the zeta potential (Tsujimoto Y. et al., 2014). In addition, the values ofsalt-free suspension were calculated as ionic strength of
5 × 10 –6 M. At higher ionic strength, both experimental
and theoretical effective radius did not change muchagainst Peclet number.
As ionic strength become lower, it was remarkable that
effective radius change depending on the Peclet number.
This tendency qualitatively agreed with the theoreticalprediction. Also, these experimental values are larger
than the reciprocal Debye length. Further, the effective
radius of the salt-free suspensions reached to about1000 nm. This value corresponded to the interparticle
distance calculated for yield stress (Adachi Y., 1999;
Sakairi N. et al., 2005). Therefore, long-distance interaction that depended on the balance of various forces has
worked among montmorillonite particles.

4. Yield stress152

4.1 Simplified viewAs noted in the analysis of electroviscous effects, thebehavior of zero shear limit is critically important wheneffects of electrostatic repulsive force are dominant. Another clear relation between colloidal interaction andmacroscopic data can be referred in the analysis of yieldstress. By applying Hershe-Bulkley equation to the flow
curve measured using cone-plate viscometer for the suspension of Na-montmorillonite, Fujii K. et al. (1996) obtained the yield stress as a function of solid volume
fraction as follows.

 0  3.6  1013 7.24 0.008    0.026

(17)

Significant point of this result is that τ0 increases rapidly by the five orders of magnitude in the very narrow
range of ϕ. The power 7.24 is an important index to characterize this change. It should be noted that such rapid increase of τ 0 can be found in the literature of landconsolidation (Sudo S. and Yasutomi R., 1961; Yasutomi
R. and Sudo S., 1962) with much smaller proportional
constant.
In order to explain this relation, Adachi Y. (1999) andSakairi N. et al. (2005) assumed the parallel array ofmontmorillonite sheets which are electrostatically dispersed in the water as illustrated in Fig. 13. That is, microscopically, suspended montmorillonite sheets array inparallel due to volumetric restriction to minimize the freeYasuhisa Adachi et al. / KONA Powder and Particle Journal No. 37 (2020) 145–165

Fig. 13 Schematic illustration the parallel array of montmorillonite sheets which are electrostatically dispersedin the water. Reprinted with permission from Ref. (Adachi Y., 1999; Sakairi N. et al., 2005). Copyright:(1999) The Japanese Society of Irrigation, Drainage and Rural Engineering, (2004) Elsevier Inc.

energy of the dispersed system. The suspension is considered to be composed of certain domains in which parallel
arrays of layers are formed.
At the point of yielding, it is assumed that the stressdue to exerted force equals microscopic electric repulsion.
With the picture of a parallel array, the volume fraction ofmontmorillonite sheet can be expressed as,




d 

(18)

When the dominant force acting between clay layers isthe electrostatic repulsive force between two plates,
Gouy–Chapman theory to predict an osmotic pressure
can be used to estimate the repulsion between two plates(Hiemenz P.C., 1986). That is, the force per unit area isestimated as,zeΨ 0 Fr =64n0kT tanh 2  exp  d 
 4kT (19)

If we can assume that this force is equal to the yieldstress, and if we use the relation of Eqn. (19) based on theassumption of parallel array of montmorillonite sheets, τ0can be written as a function of ϕ as,zeΨ 0 

 1

 1
 0 = 64n0kT tanh 2  exp    4kT  e  (20)

αe is the correction factor tentatively introduced to countthe purity of material.
Calculated values of τ0 on the basis of Eqn. (20) assuming the NaCl concentration of 0.001 M are plotted inFig. 14 together with the previously reported data (Fujii
K. et al., 1996; Sudo S. and Yasutomi R., 1961; Yasutomi
R. and Sudo S., 1962). Supprizingly, relatively good
agreements are obtained if we apply αe = 0.5 for the dataof Fujii K. et al. (1996) and αe = 0.1 for the the data of
Sudo S. and Yasutomi R. (1962).

Fig. 14 The calculated values of Fr which is equivalent to τ0with respect to different volume fraction. Calculations
are based on 1:1 type ions for c = 0.001 M, δ = 1 nm,
T = 300 K, ψ = 100 mv (surface potential) which givesΥ02 = 0.56. Plotted data are ○ Fujii K. et al., △ Sudo S.
et al. and □ Yasutomi R. et al., respectively. Solid line
αe = 1: broken line αe = 0.5: dotted line αe = 0.1. Reprinted with permission from Ref. (Adachi Y., 1999).
Copyright: (1999) The Japanese Society of Irrigation,
Drainage and Rural Engineering.

4.2 Vane method
The proposed model explained in the previous section
was experimentally confirmed by the measurement as afunction of the volume fraction and ionic strength. Application of vane is one of the most simple and direct method
to determine the yield stress for a wider range of the volume fraction of clays without changing the geometry of
the sensor. The advantage is the prevention of slip flowwhich might be induced by other conventional methods,
such as concentric rotary viscometer. Our used vane consists of four blades welded perpendicular to each otherto the central shaft (Fig. 15). Approximately 300 ml

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Fig. 15 Schematic illustration of vane consists of four blades
welded perpendicular to each other to the central
shaft.

Fig. 16 Modified version of Sakairi N. et al. (2005) experimental results, where ( △ ), (×), (□), (+), and (◊) indicates results of ionic strength 10 –5, 10 –4, 10 –3,
5 × 10 –3, and 10 –2 M, respectively. Reprinted withpermission from Ref. (Sakairi N. et al., 2005). Copyright: (2004) Elsevier Inc.

suspension was used. The slip flow which might be induced beneath as well as along the cylindrical plane overlapping the rotational zone of the blade can beconsiderably prevented. Due to the small volume of exclusion during the insertion of the vane, the gel structure of
the suspension can be maintained. The shear stress was
obtained by the measurement of Torque, T, using the following equation,

 D 3  H 1 T   
 2  D 3 (21)Within the small displacement, the shear stress linearly
increases (Dzuy N.Q. and Boger D., 1983, 1985). However, the proportional relation will collapse at a certain
limit, indicating the maximum value of shear stress. Thismaximum value was taken as the yield stress of the sample. In order to prepare uniformly mixed suspensions, we
mixed suspension from time to time, waiting a long period, during which probable swelling may take place to let
whole samples be more or less uniform.
The samples were stirred strongly for 1 min with a reagent spoon in the beaker and placed under static conditions for another 1 min to avoid thixotropic effects. Thenthe vane was inserted gently into the suspension. The insertion took 30 s and the rotation was started, waiting foranother 30 s after the end of insertion. All measurements
were performed with the rotational speed set at 0.02 rpm.
The measurement of yield stress for a fixed ionic strength
was carried out by diluting the suspension with an electrolyte solution of ionic strength and pH equivalent tothose of the bulk solution. The control of pH was donewith solutions of NaOH and HCl.

4.3 Yield stress as a function of volume fraction
and ionic strength
In Fig. 16, the obtained values of yield stress are plotted as a function of volume fraction of montmorillonite

154

Fig. 17 Correction factor against volume fraction, where ( △ ),(×), (□), (+), and (◊) indicates results of ionic strength
10 –5, 10 –4, 10 –3, 10 –2 M, respectively. Reprinted withpermission from Ref. (Sakairi N. et al., 2005). Copyright: (2004) Elsevier Inc.

together with the theoretical calculations. As indicated in
the figure, experimentally obtained data qualitatively reproduced the theoretical tendency.
However, in quantitative sense, significantly large differences were turned out. That is, when the ionic strengthis over 10 –3 M, the calculated value on the basis ofEqn. (20) with αe = 1 overestimates the yield stress, while
under 10 –3 M the prediction underestimates the experimental values. We infer this discrepancy to the effective
thickness of sheet and introduced the correction factor, αt,
for the layer thickness. Then the equation to predict theyield stress can be written as,zeΨ 0 
 1 
 0 = 64n0kT tanh 2  exp   t    1
 4kT   

(22)

It should be noted that ϕ << 1.
In Fig. 17, the calculated value of αt, is plotted against ϕ.
The very interesting result is that the value of αt is almost
constant against ϕ. The mean value of αt for each ionicYasuhisa Adachi et al. / KONA Powder and Particle Journal No. 37 (2020) 145–165

Fig. 20 Decrease in the region of spillover of EDL.
Fig. 18 Correction factor against ionic strength where solidline indicates curve of approximated function. Reprinted with permission from Ref. (Sakairi N. et al.,2005). Copyright: (2004) Elsevier Inc.

5. Strength of flocs
5.1 Simple formalism

Fig. 19 Yield Stress vs pH where ϕ = 0.01128, n0 = 10 –2 (■:I = 1.0 × 10 –3 M and ◆ : I = 1.0 × 10 –2 M)

strength is plotted in Fig. 18. As demonstrated in this figure, the clear relationship between αt and n0 is obtainedas,
3.4 10 9 n00.256t(23)

It is very interesting to note that square of αt is proportional to κ–1. In Fig. 19, additional measurement of yieldstress for different pH value is plotted.
As demonstrated in this figure, significant dependencyof pH is confirmed for the system with the concentrationof NaCl larger than 10 × 10 –3 M. The increment of theyield stress appeared with the decrease of pH value isconsidered be ascribed to the effect of attraction between
negatively charged face of plane sheet and positively
charged edge as depicted in Fig. 20. It will be very interesting to examine same effect for the system lower ionicstrength where spillover effect of basal counter positive
Na ions shield the effect of positively charged edge. Moreexperiments are necessary in this domain.

In the previous two sections, we have focused on thesystem of electrostatically dispersed system. On the contrary, gel transition is also induced in the region of attractive gel which is referred as coagulation. In this regime,
the unit of motion is a floc. Therefore, the physical properties of a floc have been regarded as the most important
subject and numerous papers are reported on this subject
so far. Among them the structure and the strength of flocs
are the most fundamental and important (Adachi Y. andOoi S., 1990). That is, geometrical structure of the formed
flocs can be approximated as fractal objects and the sizeof flocs are determined by the balance of cohesive force
between composing particles and mechanically exerted
forces on flocs. Rate of sedimentation and rheologicalproperties are largely affected by these natures. Break up
of a droplet like aggregate were firstly visualized in shear
flow (Kao S.V. and Mason S.G., 1975). More systematicstudies on the strength of flocs were reported by Sonntag
and Russel for a floc made of polystyrene latex particles(Sonntag R.C and Russel W.B., 1987a, 1987b, 1988).
Later, on this subject, Kobayashi et al. (1999) proposed a
simple theory, that is,F
Nc  fc(24)

It should be noted that Nc reflects the information of restructuring of clusters in the floc and f represents thephysicochemical information such as interaction between
particles composing the floc. The size of floc is determined when the hydrodynamic shear force, Fh, scaled as

Fh  GD f2(25)

overcomes Fc. When f is constant irrespective of the size

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of the floc, the following scaling relation can be derived
assuming Nc is constant,Df  G 0.5

(26)

Such scaling relation has been numerically obtained byseveral researchers (Doi M. and Chen D., 1989; Higashitani
K. et al., 2001). Many experimental data are also reported(Bubakova P. et al., 2013; Ehrl L. et al., 2008; Frappier G.
et al., 2010; Jarvis P. et al., 2005; Kobayashi M., 2005; Léa
G. et al., 2019; Soos M. et al., 2008). However, no data
was available as for montmorillonite floc until recently.
This situation has motivated our recent research on montmorillonite floc (Adachi Y. et al., 2019).

5.2 Shear experiment with Couette chamber
Uniform laminar shear flow was generated in a concentric cylindrical vessel called the Couette chamber. The
configuration of the set-up is shown in Fig. 21. The rotation of outer cylinder generates stable laminar shear flow.
The gap distance was designed sufficiently large to adjust
the big size of montmorillonite floc. As indicated in the
figure, the chamber was installed so that the direction of
the ax of rotation will become horizontal.
This is important to avoid the effect of sedimentation
by gravity when flocs are developed during experiment.
The flowing flocs can be simply observed by an illumination of slit LED light source through a high-speed camera.
The snapshot is demonstrated in Fig. 22.
From such image of flowing flocs, we obtain the size
distribution of flowing flocs for each rate of shear andionic strength as demonstrated in Fig. 23. Generation ofsuch size distribution of fractal floc in the flow field is notcompletely solved (Maggi F. et al., 2007; Spicer P.T. andPratsinis S.E., 1996). Using such size distribution, we canobtain effective volume fraction of solid which can beused for the estimation of viscosity (Mori Y. and OtotakeN., 1956). Then the viscosity will be estimated as a function of shear rate.
By this method Kobayashi M. et al. (2000) successfully
expressed the shear thinning behavior of coagulated suspension. Such trial is worth to be done for different chemical condition which will yield different cohesive strengthof neighboring particles.
Since the formalism of Eqn. (26) is based on the maximum size, we tentatively plotted the D99 against shear rate
in Fig. 24. Absolute values of obtained slopes were foundto be slightly larger than 0.5. Our interpretation of this result is that the enforcement of internal floc is induced by
the increase of the number between clusters, Nc, in the
structure of a floc. Large flocs are considered to havemore chances to be rearranged into more closely packed
structure.
Assuming Nc is equal to three, Miyahara estimated thecohesive strength of coagulated montmorillonite (Miyahara
K. et al., 2002). The order of magnitude obtained from theFig. 22 Snapshots of flowing flocs at 2.0 M. Reprinted withpermission from Ref. (Adachi Y. et al., 2019). Copyright: (2019) Springer-Verlag GmbH.

Fig. 21 Experimental setup for shearing experiment. Reprinted with permission from Ref. (Adachi Y. et al.,2019). Copyright: (2019) Springer-Verlag GmbH.

156

Fig. 23

Cumulative frequency of Dmax at 3.0 M. Reprinted
with permission from Ref. (Adachi Y. et al., 2019).
Copyright: (2019) Springer-Verlag GmbH.

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value of viscosity of capillary viscometer corresponds tothe value obtained from break up of flocs. On the other
hand, it is noteworthy that there is monotonously upward
shift of the size of floc against ionic strength. This meansmonotonous increment of cohesive strength between
montmorillonite sheets with an increase of ionic strength.
Our interpretation of this result is demonstrated inFig. 25.
That is the approach of montmorillonite sheets by van
der Waals attractive force is disturbed by the presence ofshort-range repulsion due to the adsorbed ions with hydration water present at the gap between two surfaces.
The increase of ionic strength results in the decrease ofeffective size of adsorbed ions (Boström M. et al., 2001;
Higashi­tani K. et al., 2017; Pashley R.M., 1981).

Fig. 24 Floc diameter (D99) vs shear rate. Reprinted with permission from Ref. (Adachi Y. et al., 2019). Copyright:(2019) Springer-Verlag GmbH.

Fig. 25 Schematic illustration to explain the effect of the sizeof hydrated ions by the increase in the concentrationof NaCl. Two surfaces are allowed to approach to the
distance which corresponds to the size of ions. If thissize is decreased by the increase in ionic concentration, the two surfaces approach more closely. The
potential of the attractive force will increase
accordingly. Reprinted with permission from Ref.
(Adachi Y. et al., 2019). Copyright: (2019) Springer-­
Verlag GmbH.

6. Sedimentation
Flocculated montmorillonite and other clay minerals
are abundantly available in coastal sediment area. They
play a very significant role as a unit of transportation and
can influence a wide array of environmental phenomena.
Sedimentation behavior of a coastal sediment can be categorized into three distinctive regimes in accordance withsuspension concentration, which are dilute, semi-dilute,and concentrated (Imai G., 1980, 1981). In the dilute regime, the formed flocs settle independently with nodistinct interface between flocculated sediment and super­
natant. By contrast, in the semi-dilute regime, there is aclear interface boundary between sediment and supernatant. This means that in the semi-dilute regime, flocs inthe sediment appear to interact to form a network of sedimentation that has a clear interface boundary with thetransparent supernatant zone. In this regime, there appears idle time prior to settling phase due to the mutualinteractions among the flocs which hindered the settlingprocess. Lastly, in the concentrated regime, an initiallyformed network structure of flocculated sediment settles
very slowly under its own weight. Semi-dilute regime canbe further classified into three different stages: 1) Flocculation (Waiting time), 2) Sedimentation (Gel collapse)(Bartlett P. et al., 2012) and 3) Consolidation (Fig. 26).
At the onset of the flocculation stage, uniform dispersion is formed and gradually grow to form small colloidal
flocs (Fig. 26a-b). At this stage, we can identify theclear interface boundary between the flocculated Na-­
montmorillonite and the transparent supernatant. The
flocculation and sedimentation process are ongoing eventhough the rate of sedimentation is very small reflecting
the small size of flocs. The intersection point for tangentsof linear parts between the flocculation stage and sedimentation stage with maximum sedimentation rate is denoted as the flocculation time, tf. The waiting time prior
to gel collapse continues as the flocs grow bigger to forma space-filling structure of sediment (Fig. 26c). The stressis concentrated at some contacting points (marked as
black circles) in the network due to self-weight of the sediment (Fig. 26d). The apparent sedimentation rate is essentially low as the point will resist against thecompression by self-weight of the network. However,once the network could no longer stand for the stress, it
starts to break down and mark the onset of gel collapse.
Prediction of such gel collapse has attracted many attentions by many physicists (Manley S. et al., 2005; Poon
W.C.K. et al., 1999; Poon W.C.K., 2002; Cipelletti L. etal., 2000; Allain C. et al., 1995; Chang W.Z. and Leong
Y.K., 2014). Coarsening effect due to heterogeneity is presumably related to this scenario (Buscall R. et al., 2009).
Abrupt gel collapse initiates the set in of rapid sedimentation stage. Development of crack void while flocs fall157

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Fig. 26 Schematic representation explaining the progress of sedimentation of flocculated materials in thesemi-dilute regime (Ghazali M.E.B. et al., 2019).

down during gel collapse created the water channeling in
the network. Downward motion of flocculated sedimentwill induce the generation of upward plume of water
which flutters slightly (Fig. 26e). Lastly, during consolidation stage, the flocs settle down slowly due to its selfweight to fill the space underneath that was left to develop
early consolidation at the bottom of the cylinder(Winterwerp J.C. and Kestern W.G.M.V., 2004: Imai G.,
1981) (Fig. 26f).
Owi ng to the specif ic character istics of Na-­
montmorillonite to form enormously big flocs irrespectiveof pH value (Miyahara K. et al., 1998) under the conditionof high concentration of NaCl, we carefully observed thesedimentation behavior of strongly f locculated Na-­
montmorillonite in semi-dilute regime. In our recent
studies, we measured the changes of interface between
sediment and supernatant in varied initial height of suspension as a function of elapsed time for different levelsof salt concentration (Wu M. and Adachi Y., 2017; Ghazali
M.E.B. et al., 2019). Na-montmorillonite slurry coagulated under different ionic strengths, ranging from 0.25 M
to 1.5 M of NaCl, was placed in a settling cylinder andwas left to settle after manual mixing by end-over-end
method.
The result of the position of the boundary as functionof elapsed time is depicted in Fig. 27. However, the main

158

Fig. 27 Location of the boundary as a function of elapsed time(min) at pH 9.5 (b). Initial height of the suspensions
H0 = 15.8 cm, inner diameter of the cylinders
D 0 = 5.0 cm, volume fraction of Na-montmorillonite
ϕ = 1.097 × 10 –4. Reprinted with permission from Ref.
(Wu M. and Adachi Y., 2017). Copyright: (2017)
Springer-Verlag GmbH Germany.

experimental focus of the later study is to investigate thedependency of cylinder height on sedimentation behavior,
which was not reflected in the previous study.

6.1 Waiting time for gel collapse
We also developed an interest in the early stage of sedimentation to elucidate the relation between microscopicYasuhisa Adachi et al. / KONA Powder and Particle Journal No. 37 (2020) 145–165

heterogeneous interaction of clay particles and macroscopic behavior of Na-montmorillonite sedimentation.
Our previous study by Wu M. and Adachi Y. (2017) highlighted the duration of initial flocculation stage prior to
the gravitational collapse of Na-montmorillonite suspension as a function of ionic strength. We have confirmedthat ionic strength is inversely proportional to the duration
time of initial flocculation stage denoted as τ (Fig. 28).
That is, the duration time for the system undergoing
rapid coagulation under sufficiently high ionic strength isshorter (but not to be zero). The progress of small crack in
the weakly touched sediment network escalated after the
onset of gel collapsed as depicted in Fig. 29. This point
was considered to be a certain degree of flocculation
where the formed gel network of flocs collapsed due to its
self-weight, hence the result, τ, can be interpreted as thetime required to reach the point of flocculation (Wu M.
and Adachi Y. 2017).
It is basically determined by the inverse rate of flocculation. This interpretation was consistent with the colloidal stability analysis of Tombacz E. et al. (1988), whopointed out the dominancy of Edge-Face interaction detected as the difference in critical coagulation concentration which appeared in the lower pH under lower ionicstrength. Our result of the difference in τ also correlateswith this trend.

6.2 Sedimentation turbulence
Maximum settling velocity was plotted against cylinder
height as shown in Fig. 30. It appears that the maximum
settling velocity was varied depending on the height ofinitial slurry and the value was increased steadily with anincrease of initial slurry height (Ghazali M.E.B. et al.,2019).
The results also demonstrate that the maximum velocity increases with NaCl concentration. Increasing salt
concentration decreases the repulsive electrostatic effect,
breaking weak Edge-Face bonds and residual strong
Edge-Face bonds, and results in bigger flocs (Wu M. andAdachi Y., 2016). In this stage, the bigger flocs (i.e.
formed in high salt concentration) will settle down fasterthan the smaller one. By the velocity difference, collisionof settling flocs will take place which leads sto the development of the flocs. In the higher cylinder, the traveling
distance of falling flocs becomes longer. The development

Fig. 29 Generation of small cracks in the weakly connected
sediment structure during gel collapse.

Fig. 28 Flocculation time as a function of ionic strength forthe different pH values (pH = 4.0 and pH = 9.5). Dueto the un-coagulated suspension under the conditionof pH 9.5 and ionic strength 0.05 M NaCl, the relative
movement of boundary between supernatant and coagulated suspension could not be recorded in Fig. 2.
Therefore, the duration time at the condition (pH 9.5
and NaCl 0.05 M) cannot be calculated. Reprinted
with permission from Ref. (Wu M. and Adachi Y.,
2017). Copyright: (2017) Springer-Verlag GmbH Germany.

Fig. 30 Maximum velocity as function of cylinder height at
different levels of ionic strength (Ghazali M.E.B. etal., 2019).

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of flocs along the long traveling distance is coupled withthe turbulence. This sequence creates a feed-forwardmechanism which will further enhance the sedimentation
process.
In the case of taller cylinder, the traveling distance offalling flocs becomes longer, the falling flocs will thenhave more chances to collide with the other small flocs
and becomes still bigger in size and mass to accelerate thesettling speed. As the result, the rapid sedimentationcommenced at a different period of time (Imai G., 1981;
Dobias B. et al., 1993). Each floc settled differently interm of velocity, due to different size and density. The
void formed simultaneously is connected to create channeling of counter flow. The observed pattern of fluctuation
was similar to a turbulent flow (Pope S.B, 2000). We term
this phenomenon as the “sedimentation turbulence”(Ghazali M.E.B. et al., 2019). This phenomenon is notwell described in the previous study (Michaels A.S. and
Bolger J.C., 1962; Wu M. and Adachi Y., 2017; Miyahara
K. et al., 2001, 2004) in which direct application of the result of fluidized led for non-flocculated materials wasdone (Richardson J.F. and Zaki W.N., 1954).
The floc motion induces a turbulent flow, which will
induce further development of flocs. That is, floc formation is due to turbulent flow passing through, which increases the settling velocity. Consequently, the flocs will
collide with the neighboring flocs to grow into bigger
flocs.

7. Conclusion and remarks for the future
In the present article, we focus on the behavior of aqueous dispersion of Na-montmorillonite in the dilute condition to elucidate the relation between the level of colloidal
and interface chemistry such as microscopic interactionof colloidal particles and the level of macroscopic properties which will control the hydrological transport phenomena and the massive motion of the materials. The
review was started to examine the simple viscosity as afunction of ionic strength which is in accordance with the
DLVO scheme.
In the limit of low ionic strength, viscosity increases
dramatically demonstrating the electro-viscous effect especially due to the interaction of EDLs formed around thesuspended particles. The data obtained using our homemade spiral viscometer confirms the long-range interaction between the flowing montmorillonite sheets which
will contribute to enhance the viscosity significantly inthe limit of zero shear rate. The value of yield stress obtained by vane was found to be clearly reduced to that ofelectrostatic repulsion due to the interaction of EDLs. Unfortunately, we are not able to convert the repulsion to attraction which stands for the deformation. However, the160

estimated distance obtained from the analysis of actualforce between two sheets was estimated to be longer thanthe Debye reciprocal length implying the significance oflong-range interaction. More systematic data against pH
will elucidate the role of spillover effects of EDL of basal
part and Edge-Face interaction.
On the contrary, the data obtained for the region ofhigher ionic strength, viscosity increases monotonouslywith an increase of ionic strength. This tendency wasconfirmed by the measurement on the size of flowing
flocs. Our interpretation was the presence of additional
repulsion due to the adsorption of hydrated sodium ionswhose diameter decreases with an increase of ionic concentration in the region of ionic concentration higher than
CCC. The observation of sediment volume also confirms
the tendency. One important finding for the sedimentation
behavior is to find out the clear evidence for the feed-­
forward enhancement of the rate of sediment. That is, thesedimentation induces flocculation and flocculation will
enhance the rate of sedimentation and so on. We term thisbehavior as sedimentation turbulence. Another importantresult was obtained for the difference of waiting prior togel collapse against pH and ionic strength. That is, pH dependency exists for the concentration below 0.5 M but
will disappear for the concentration higher than 1.0 M.
Although, our applied methods in the previous studies
are done with very primitive instruments; viscosity measurement with Ostowald capillary viscometer, Spiral capillary viscometer, observation of floc in a simple shear
flow, sedimentation behavior in the mess cylinder, we canconclude that there are five different regimes. They are,
EDL dominative repulsive phase, pH-dependent repulsive
phase, dispersed phase, pH-dependent attractive, pH-­
independent attractive phase. Continuous study for precise pH dependency will clarify this picture. In addition,
further investigation for different chemical conditions(Penner D. and Lagaly G., 2001; Montoro M.A. andFrancisca F.M., 2019), such as effect of divalent ions
(Kobayashi S. and Adachi Y., 2008) and effect of organic
substances (Wilkinson N. et al., 2017; Tombacz E. et al.,1998) will provide us very useful result for the consideration of natural colloid.

Acknowledgements
This research was partly supported by JSPS Kakenhi
16H06382. Our former students, Dr. Katsumi Miyahara,
Dr. Nobuyuki Sakairi, Mr. Maro Tamaki, Prof. Katsumi
Fujii, Mr. Syunya Kobayashi, Mr. Di Chuan and
Mr. Yanuar Argo are acknowledged for their experimental support. Dr. Motoyoshi Kobayashi, Dr. Setsuo Ooi andProf. Katsuya Nakaishi are thanked for their guidance
throughout this study.

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NomenclatureαCorrective Factor

β

Representative of long formulae

ε
ε0

2

Dielectric constant (C /J m)
2

Dielectric constant of vacuum (C /J m)2

h’cDistance (mm)h0Distance (mm)hc

Distance (mm)K1

Intrinsic viscosity (ml/g)

K2

Huggins’ coeficiente [-]kBoltzmann constant (J/K)

εr

Relative dielectric constant of water (C /J m)

kT

Diffusive energy (J)κ

Debye reciprocal length

L

Length of capillary tube (m)ηViscosity (mPa-s)n0

Number concentration of the ions (M)η0Viscosity of solvent (mPa-s)ni

Ionic concentration (M)ηrRelative Viscosity (mPa-s)

Pe

Peclet number [-]ηsViscosity of suspension (mPa-s)

Q

Flow rate in the tubeδ

Layer thickness (nm)rDistance from a center of the particle (nm)ρDensity of fluid (kg/m³)rpm

revolution per minuteτTime of initial flocculation stage (min)T

Absolute temperature (K)τShear stress (Pa)T

Torque (Nm)

τ0

Yield stressTe

End of torque (Nm)τeShear stress at end of torque (Pa)Ts

Side of torque (Nm)τsShear stress at side of torque (Pa)tTime (sec, min)τy

Yield stress (Pa)Ve(r)

Electrical repulsive energy (J)ϕVolume fraction [-]z

Valence of electrolyte solution [-]ϕmax

Packing volume fraction [-]ϕeff

Effective volume fraction [-]Ψ0

Surface potential (mV)ξ

Zeta potential (mV)

aeff

Effective radius (nm)

CCC

Critical Coagulation Concentration

D

Diameter of the vane (mm), Inner diameter of capillary tube (mm)D99

Floc diameter (mm)

Df

Diameter of floc

Dmax

Maximum floc size (mm)dMean distance of clay layers (nm)EDLElectric Double LayereElementary charge (C)FeElectrostatic repulsive force

Fr

Force per unit area (Pa)FshHydrodynamic force

G

Shear Rate (s –1)

gGravitational acceleration (m/s2)

H

Height of the blade (mm)hDifference of the levels (mm)References
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Authors’ Short Biographies
Yasuhisa Adachi
Yasuhisa Adachi is Professor of Life and Environmental Science in Tsukuba University. He has diploma and PhD from the University of Tokyo (Agricultural Eng,). His research has focused on flocculation for more than 30 years. Currently he is the leader of
research unit, Bio-resources Colloid Engineering in University of Tsukuba. Main subjects are kinetics of coagulation and flocculation, structure of resulted floc, sedimentation and rheology of flocculated material. He was awarded an academic award fromJapanese Society of Irrigation, Drainage and Rural Engineering in 2015.

Yoko (Tsujimoto) Kawashima
Yoko (Tsujimoto) Kawashima received her PhD from University of Tsukuba back in
2014. Her doctoral thesis is entittled “Electrokinetics and rheological behavior of clay
suspensions in electrostatically dispersed state”. Currently, she works in the material
section in Public Works Research Institute for the proper evaluation of asphalt.

Muhamad Ezral Bin Ghazali
Muhamad Ezral Bin Ghazali is a young researcher currently pursuing his doctoral
degree at University of Tsukuba, Japan. He graduated with Master of Philosophy from
Malaysia-Japan International Institute of Technology, University of Technology, Malaysia(UTM), and was awarded with Japanese Government (Monbakugakusho) Scholarship tofurther his studies in Japan. His area of studies include natural coagulant and flocculation in water treatment. Currently, his research focused on sedimentation behaviour ofmontmorillonite.

165

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Original Research Paper

Shape Controllable Synthesis of Silver Particles
by Selecting the Crystallization Routes †Jianmei Liu 1,2, Qiang Lin 1, Yu Zhou 1, Jinhui Dai 2* and Yongsheng Han1 *12State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, China
Institute of Materials Science and Engineering, Ocean University of China, China

Abstract
Classic crystallization describes a burst nucleation followed by a layer-by-layer atom deposition. The non-classic
crystallization refers to particle mediated crystallization process. Different crystallization routes lead to theformation of diverse structured materials. Here we report a rational synthesis of silver particles by selecting the
crystallization routes. Silver particles were synthesized by a solution reduction approach. The crystallizationroutes were regulated by adding amino acids to stabilize silver ions which leads to the decrease of the reduction
rate. Without amino acids, silver dendrites were largely formed. With the addition of amino acids, flower-like (lowconcentration of amino acids) and spherical silver (high concentration of amino acid) particles were synthesized.
Three kinds of amino acids were tested and the similar results were obtained. The time-dependent
characterization on the evolution of silver particles showed that silver dendrites were formed by the classic atom
deposition while the other two morphologies were formed by the combination of classic and non-classic
crystallization. The silver particles synthesized were evaluated for ethylene epoxidation and the dendritic particles
demonstrated a high selectivity.
Keywords: crystallization, silver particles, shape control, reaction kinetics, catalytic selectivity

1. Introduction
Crystallization starts from nucleation followed by thegrowth of nuclei. It is a key process in materials formationand industrial production (Zeng J. et al., 2012). For many
years, the crystallization has been described through burst
nucleation followed by layer by layer growth or Ostwald
ripening (Li Y. et al., 2018; Zeng J. et al., 2012). However,this traditional description faces challenges recently because more and more hierarchical structures synthesizedin laboratories or found in nature, which could not be explained by the classic crystallization. For example,
well-faceted porous calcium carbonate particles have beensynthesized by the diffusion of CO2 into the calcium chloride solution (Wang T.X. et al., 2005). These porous particles were built up by the perfectly 3D-aligned calcite
nanocrystals superstructures. Based on these findings, thenon-classic crystallization process is proposed, in which
†
1
2

*

Received 20 July 2018; Accepted 20 September 2018
J-STAGE Advance published online 17 November 2018
1 North 2nd Street, Zhongguancun, Haidian District, Beijing
100190, PR China
238 Songling Road, Qingdao, 266100, China
Corresponding author: Yongsheng Han;
E-mail: yshan@ipe.ac.cn, daijh@ouc.edu.cn
TEL: +86-10-82544873

166

particles coalescence plays a major role on the growth of
products (Colfen H. and Antonietti M., 2008; Runkana V.
et al., 2005). Except this different conception on crystallization, Watzky and Finke (Watzky M.A. and Finke R.G.,
1997) formulated a constant slow nucleation followed by
autocatalytic growth, in which the nucleation lasts for along time and competes with the growth of particles. The
well-accepted Ostwald ripening also faces challenge by
the Digestive ripening (Kalidindi S.B. and Jagirdar B.R.,
2009). The former describes that big particles prefer togrow in solution on the cost of small particles while thelater refers that small particles grow at the expense oflarge ones. Therefore, there are many debates in the fieldof crystallization, which leave the uncertainty but also thetreasure to be discovered.
Although the traditional theory of crystallization faces
challenges, scientists never stop their effort to synthesize
crystals with controllable size and morphology. Different
approaches have been developed to control the shape of
crystals, which includes templating methods (Fuji M. etal., 2013), kinetic controlling methods (Xia Y.N. et al.,2015) and so on. Chemists have developed a fine
shape-controlled method by adding surfactants or macromolecules to interfere the growth of crystals (Ruditskiy A.
and Xia Y.N., 2016). By this method, they have successfully synthesized various morphological metal particles,

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Jianmei Liu et al. / KONA Powder and Particle Journal No. 37 (2020) 166–175

including spheres (Han K.N. and Kim N.S., 2009), cubes(Zeng J. et al., 2010), tetrahedrons (Wiley B. et al., 2004),
nanobars (Zhang Q. et al., 2012) and nanowires (Xiong
W.W. et al., 2016). They ascribed the role of surfactants totheir selective adsorption on the facets of crystals to block
the growth of these facets. But different opinions alsocome up. David Wei and co-authors (Zhai Y.M. et al.,2016) proposed that the surfactant polyvinylpyrrolidone
preferentially adsorbs along the perimeter and serves as aphotochemical relay to direct the anisotropic growth.
Shape control of materials is a long-term interest of ourgroup. We have developed a bubble templating method forone-step synthesis of hollow particles (Han Y.S. et al.,2007, 2009). Recently, we are focusing on the role ofchemical diffusion and reaction kinetics in shaping particles. By regulating the diffusion and reaction rates ofchemicals, we have synthesized diverse morphologies ofmetal particles and oxide particles (Wang H. et al., 2013;
Yang T. and Han Y.S., 2016; Yang T. et al., 2015; Yang Y.
et al., 2014). It was found that the diffusion of chemicals
could switch the crystallization from classic to non-­classic
modes, which led to the formation of diverse morphologyof platinum particles (Yang Y. et al., 2014). In this paper,
we attempted to investigate how the reaction rate influences the crystallization process. Silver particles were synthesized by a solution-based reduction approach, in whichhydroxylamine was used to reduce silver ions producing
silver particles. The reduction rate was regulated by adding amino acid as complexation agents. With the additionof amino acid, the reduction rate was slowed down due tothe complexation. In different reduction rates, the formation process of silver products was monitored. Both theclassic crystallization and non-classic crystallization wereobserved when the reduction rates changed, which led to
the formation of diverse morphologies of silver particles.

2. Experimental sections
2.1 Materials
All chemicals used in this study are of analytical grade
and used without further purification. They were purchasedfrom Sigma-Aldrich. Deionized water with a resistivity
higher than 18.2 MΩ used throughout the experiments
was generated by a Mili-Q system (Millipore, USA).

2.2 Synthesis of silver particles with various
morphologies
In a typical experiment, 2 ml silver nitrate (100 mM)
and a defined amount of amino acid were dissolved in
40 ml deionized water, respectively, stirring for 10 minutes to form a stable complex. Then 2 ml hydroxylamine

solution (200 mM) was added into the above mixture to
initiate the reduction. To monitor the evolution of silver
particles, the solution was taken out at different reaction
time. The solution was immediately transferred to liquid
nitrogen to terminate the reduction, and then the frozen
samples were dried by freeze drier (Christ ALPHA 1-2
LD plus, Germany). The reactions were carried out in athermos-stated water bath at 25 °C, and the concentrationof amino acids varied from 0 to 40 mM.

2.3 Characterizations
The morphologies of silver products were characterized
by a JSM-7001F Thermal Field Scanning Electron Microscope (JEOL, Japan) and a JEM-2100 (UHR) Transmission
Electron Microscope (JEOL, Japan) at an accelerating
voltage of 200 kV. Samples for SEM and TEM analysis
were prepared by dipping solution on aluminum foils andcarbon-coated copper grids, respectively.

2.4 Quantization of the reduction rates
When the silver ions are reduced by hydroxylamine,
the hydrogen ions are the byproduct. The generation rateof Ag atoms is equal to the production rate of hydrogenion, so the reduction rate can be quantified by measuring
the increment of hydrogen ion, which corresponds to adrop of pH. The pH electrode (Mettler-Toledo S470 Seven
Excellence pH/Conductivity meter) was placed in thesolution to record the pH change during reaction.

2.5 Catalyst preparation and selectivity
evaluation
The Ag/α-Al2O3 catalysts were prepared by an excessive impregnation method. Firstly, the silver slurry was
prepared by dissolving cesium hydroxide (the mass fraction of Cs ion = 1000 ppm) and Ag2C2O4 into an ethylenediamine (EDA) solution to form a diamine silver solution(the mole ratio of Ag2C2O4:EDA = 5:12). When the silver
particles were added into the ethylenediamine solution,
the amount of Ag2C2O4 was decreased to keep the same
mole ratio of silver and EDA. Then the porous alumina
supports were immersed in the slurry to load silver salt.
The supports were heated by hot air at 300 °C for fiveminutes, generating the Ag/α-Al2O3 catalysts. The ethylene epoxidation was conducted in a stainless steel reactor with 4 mm inner diameter. The catalysts were broken
and sieved to 0.9–1.4 mm, then 1 ml sample was loaded
into the reactor. Quantitative analysis of inlet and outlet
gas composition was performed on an online Prima dB
mass spectrum produced by Thermo Scientific. The gas
was ionized by the bombardment of electron current inion
source. Stand Faraday detector was used to analyze the167Jianmei Liu et al. / KONA Powder and Particle Journal No. 37 (2020) 166–175

Fig. 1

An illustration of a switch of crystallization routes from the classic to the non-classic mode via reaction
kinetics.

gas concentration, and the concentration between 10 ppb
to 10 ppm was detected by secondary electron multiplier.
Gas feed composition was C2H4 25–30 %, O2 7–8 %, CO2
3 %, ethylene dichloride (EDC) 0.1–0.5 ppm, balance N2
at 1.7 MPa total pressure, and the gas hourly space velocity (GHSV) of 7000 h–1. The EO selectivity was expressedas the following equation.
S EO % 

ΔEO
ΔEO  0.5  ΔCO 2

3. Results and discussion
The main difference between the classic crystallizationand the non-classic crystallization is the growth unit ofcrystals. In the classic crystallization, the growth units
are atoms or ions or molecules which deposit on the surface of nuclei by a layer by layer mode. In the non-classic
crystallization, the growth units are usually clusters or
particle which aggregate to form products. We supposethat the reaction kinetics could change the crystallizationroutes. At a high reaction rate, quick reaction leads to a
burst nucleation followed by a classic crystallization. At alow reaction rate, the nucleation lasts for a long time andthe newly-burn nuclei tend to aggregate to form particles,
which leads to the non-classic crystallization, as shown in
Fig. 1. In the following, the evaluation on this hypothesis
will be conducted.
We synthesized silver particles by a solution-based reduction approach, in which hydroxylamine was used toreduce silver ions producing silver particles, as shown in
the following:

2Ag   2NH 2OH  2Ag  2H 2O  N 2  2H  (1)The reduction rate was regulated by adding glycine
into the silver solution. With the addition of glycine, the168

Fig. 2

The reduction rates of silver ions with the addition ofglycine due to the stabilization of silver ions by complexation.

reduction rate was slowed down due to the stabilization ofsilver ions by glycine. To quantify the reaction rates, thepH value of the solution was recorded during the reaction,
which was used to calculate the reaction rates due to hydrogen ions are byproduct of the reduction, as shown in equation 1. Without glycine, the reaction rate is 1.166 × 10 –6 mol
L –1 s–1, as shown in Fig. 2. With the addition of glycine,the reaction rates decrease to 0.335 × 10 –6 mol L –1 s–1 at
10 mM glycine and 0.147 × 10 –6 mol L –1 s–1 at 40 mM
glycine, respectively, which confirms the complexation ofsilver ions by glycine. In the following, we attempt tosynthesize silver particles at different reaction rates toevaluate the role of reaction kinetics in crystallization.
Silver dendrites were largely generated when the silver
salts were mixed with hydroxylamine solution, as shown in
Fig. 3. Fig. 3A shows the low-magnification image of silver
products, indicating uniform and large scale of dendritic
particles. Fig. 3B–3E show time-dependent evolution ofsilver dendrite, which was carried out by taking samples atdifferent reaction times and immediately putting samples

Jianmei Liu et al. / KONA Powder and Particle Journal No. 37 (2020) 166–175

Fig. 3

SEM images of the silver dendrites synthesized in water at different reaction time. A showing the
low-magnification SEM image of silver dendrites synthesized after 30 min, indicating high yield anduniform of product; B–E showing silver dendrites synthesized in 1 s, 5 s, 10 s, 30 min, respectively. The
scale bars represent 1 μm.

into the liquid nitrogen to stop the reaction. After the reaction of 1 second, the silver products already show dendritic characters with clear main trunk and side branches,
as shown in Fig. 3B. When the reaction time is increased
to 5 seconds, the dendrite prototype grows to three-­dimensional complex structure. Small particles areformed on the surface of the trunk and the side branches
become longer with the formation of next-level branches
on their surface, as shown in Fig. 3C. Prolonging the reaction to 10 seconds, the dendrites become dense and compacted, as shown in Fig. 3D. Further prolonging thereaction time, small particles disappear and the dendritic
structures become clear and complete, as shown in Fig. 3E.
The time dependent characterization indicates that the formation of dendritic structures is pretty fast and the classic
crystallization may dominate the growth of particles.
The silver dendrites were characterized by transmission electron microscopy (TEM), as shown in Fig. 4.
Fig. 4A shows an overall dendritic structure of silver particles. The selected area electron diffraction (SAED) pattern of the growth front of silver dendrites marked by red
circle is shown in Fig. 4B, which indicate that the silver
dendrite is single-crystalline with the main growth direction of <110>, as shown in Fig. 4C. The single crystalline
and boundary free characters of silver dendrites indicatesthat silver dendrites are formed by a classic crystallization
process. Fig. 4D is the growth model of silver dendrites.
In most cases of metal solidification and nano-synthesis,
the formation of symmetric dendrites follows the classic
crystallization in which atoms are the main building
blocks for the growth of dendrites (Xing H. et al., 2016).
If the silver dendrites are formed by a classic crystallization, a change on the reduction rate is expected to switch
the classic crystallization to the non-classic mode, on thebasis of the assumption in Fig. 1, which is the issues wewant to evaluate in the following.

To regulate the reduction rate of silver ions, glycine
was added into silver salt solution before the reduction.
The glycine stabilizes silver ions by complexation, whichleads to the decrease of reduction rate (Liu J.M. et al.,2015). Silver particles were synthesized at different
amount of glycine. When the glycine concentration is
10 mM in the solution, flower like silver particles areformed, as shown in Fig. 5. These particles are composedof fan-shaped sheets which assemble together forming
flower structures with the diameter of several micrometers. To track the formation process of silver flowers, wetook samples at designed time and stop the reaction by
putting the samples into liquid nitrogen. In the early stageof reaction, nanosized silver particles are formed, as
shown in Fig. 5B. Prolonging the reaction to 10 seconds,
nanosized particles grow and assembled together, forming
the prototype of flowers, as shown in Fig. 5C. Further
prolonging the reaction to 30 seconds, each particle in theflower grows to fan-shaped particle, as shown in Fig. 5D.
On the surface of these particles, protuberances are observed, which is probably the result of later adsorption ofsmall particles. When the reaction is increased to 30 minutes, the morphology of silver flowers does not change
remarkably except the size, as shown in Fig. 5E. The
time-dependent characterization indicates that silver
flowers are formed by the aggregation of individual nanosized particles followed by the growth of each particle.
The silver flower has been characterized by TEM, as
shown in Fig. 6. The dark center in TEM image indicatesthat the flower has a dense core while the grey epilayer
confirms the thin layer of each petal. The selected area
electron diffraction pattern from the petal, as shown in
the inset of Fig. 6, indicates that each petal is crystalline.
Flower structured particles have been synthesized inmany materials. Different formation mechanisms havebeen proposed for these amazing structures. Among

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Fig. 4

TEM image (A) of the silver dendrites synthesized. Selected area electron diffraction patterns (B, C)
from the specific sites labeled in (A). D is the growth model of silver dendrites.

Fig. 5SEM images of the silver products synthesized by the solution-based reduction approach in 10 mM glycine solution. A showing the low-magnification SEM image of silver flowers synthesized after 30 min,indicating uniform and high-yield of products. B showing nanosized silver particles synthesized after 5 s
reaction; C showing the silver aggregates composed of flakes synthesized after 10 s reaction; D and E
showing silver flower synthesized in 30 s and 30 min, respectively. The scale bars represent 1 μm.

them, self-assembly of individual particles is the mostplausible (Sung H. and Choi M., 2013), in which the building block particles are formed firstly and then aggregate
together following certain orientation. But this mechanism does not work well in our system because the initial
particles are much smaller than the final petal and theirmorphology is also different, as shown in Fig. 5. Therefore, each individual particle should undergo a later
growth process after the aggregation. Since the fan-170

shaped particle is formed in a short reaction time (30 seconds) with single crystalline feature, we suppose thatatom deposition plays a key role in the later growth ofindividual particle. Therefore, it seems that the flower
particles start from the aggregation of nuclei followed by
the classic growth of nuclei. The formation of flower-likestructures is a combination of the classic and non-classic
crystallization. The involvement of non-classic crystallization is probably caused by the decrease of reduction

Jianmei Liu et al. / KONA Powder and Particle Journal No. 37 (2020) 166–175

rate of silver ions. At a slow reaction, the silver nuclei or
small particles can not grow up quickly. They prefer toaggregate to reduce their surface energy under stirringand grow up later by atom feeding.
To further evaluate the role of reaction kinetics in crystallization process, we synthesized silver particles at
40 mM glycine solution. Spherical silver particles arelargely synthesized in this condition, as shown in Fig. 7A.
The time-dependent morphological evolutions of silver
spheres are shown in Fig. 7B–7E. At the initial reaction
time of 5 seconds, irregular particles are formed with thesize of several hundred nanometers, as shown in Fig. 7B.
Prolonging the reaction to 30 seconds, the flower aggregates are observed, as shown in Fig. 7C. When the reaction is increased to 5 minutes, spheres with roughFig. 6

A TEM image of the silver flower and the selected area
electron diffraction pattern (inset) from the flower. The
scale bar represents 200 nm.

Fig. 7

surfaces are synthesized, as shown in Fig. 7D. Further
prolonging the reaction time to 30 minutes, the size andmorphology of silver spheres change, as shown in
Fig. 7E. The time-dependent characterization indicatesthat the formation process of spheres is similar to that of
the flower particles. They are the products of particles aggregation followed by classic crystallization. Owe to thedecrease of reduction rate, the nucleation process is prolonged, which competes with the growth process to consume silver atoms. The newly formed nuclei adsorb on thesurface of growing particles and become new sites for thegrowth, forming dense flower particles.
To exclude the role of chemical effect on the morphology of silver particles, we synthesized silver particles at
two more amino acid solutions, namely arginine and phenylalanine solutions, as shown in Fig. 8. No matter whichamino acid is added, the morphology of silver particles
switches from dendrites to flower like particles then tospheres with the increase of amino acid concentration,
which indicates that the change of silver morphologies is
independent on the types of amino acid. Since the addition of amino acid slows down the reduction rate of silver
salt, the reaction kinetics should play a key role on thechange of silver morphology. It is normally accepted thatthe kinetics factors influence the growth rate of crystal
facets, which leads to the formation of diverse shapes ofcrystals (Xia Y.N. et al., 2015). This interpretation works
well for the anisotropic growth of single crystals. But it
can not explain the formation of hierarchical polycrystalline crystals, such as the flower-shaped particles in which
the petal originates from different nucleus. Therefore, wehave to consider the aggregation of nuclei in the formationof hierarchical crystals.
Silver is an industrial catalyst of ethylene epoxidation to
generate ethylene oxide (EO) which is the largest volume
chemicals produced by chemical industry. The oxidation

SEM images of the silver products synthesized in 40 mM glycine solution. A showing the low-­magnification SEM image of silver spheres synthesized at 30 minutes, indicating high yield of sphericalparticles. B showing the silver nanoparticles synthesized at 5 seconds; C showing the silver aggregates
synthesized at 30 seconds; D and E showing silver sphere-like particles synthesized at 5 and 30 minutes,
respectively. The scale bars represent 1 μm.

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Fig. 8SEM images of the silver products synthesized in arginine (A) and phenylalanine (B) solution at various
concentrations, and the reaction time was fixed at 30 minutes. AB showing the silver dendrites synthesized without any amino acids; A1 and A2 showing the silver particles synthesized in the arginine solution of 5 mM, 20 mM, respectively; B1 and B2 showing silver particles synthesized in phenylalanine
solution of 0.5 mM, 5 mM, respectively. The scale bars represent 1 μm.

of ethylene in the presence of supported silver catalysts
not only leads to the formation of ethylene oxide, but also
induces the side reaction to form carbon dioxide. Therefore, the selectivity is the important issue of silver catalysts. Considerable effort has been devoted to understandthe mechanism of silver-catalyzed ethylene epoxidation.
There are two types of oxygen species playing the active
centers for ethylene epoxidation on silver (Ren D.M. etal., 2017). One is the active oxygen in a nucleophilic attack of the C-H bond while the other is active in an electrophilic addition to the double C = C bond. The former
facilitates the formation of carbon dioxide while the latteris in favor of the formation of ethylene oxide. It was reported that the electrophilic oxygen is dominant in the Ag(111) at the addition of cesium (Bukhtiyarov V.I. et al.,2003). Since the silver particles synthesized in this study
have a major exposure of Ag (111), we added the synthesized silver particles to the silver slurry containing
1000 ppm Cs ions and loaded the slurry into the alumina
supporter, to evaluate the effect of particles morphologies
on the selectivity of catalysts. The total loading capacityof silver is 17 wt% which includes 20 % silver particles.
It is found that the addition of silver particles leads tothe increase of the selectivity of ethylene epoxidation andthe silver dendrites have the highest selectivity, as shownin Fig. 9. The dendritic silver particles grow along the<110> with the largely exposed facet of (111), as shown in
Fig. 4, which leads to the highest selectivity of silver dendrites. The flower-like silver particles also demonstrate ananisotropic growth with the major surface of (111) while
the silver spheres are polycrystalline having a reduced
surface of (111). All these particles are well crystallized insolution, which benefits the desorption of oxygen to generate ethylene oxide. This study indicates that the facet

172

Fig. 9Reaction selectivity of ethylene epoxidation catalyzed
by silver. In the preparation of supported catalyst, silver particles with different morphologies are added
into the silver slurry and loaded on the alumina supporter, which results in the different selectivity at thesame loading capacity of silver.

control is an effective solution to develop high selectivity
and efficient catalysts.

4. Conclusions
A rational synthesis of hierarchical silver structures
was reported in this paper. Silver dendrites, silver flowers and silver spheres were largely synthesized by controlling the reduction rates which was regulated by adding
ammonia acids to stabilize silver ions and slow down the
reduction. With the decrease of reduction rate, silver dendrites changed to silver flower and then to silver spheres,
which were observed in three kinds of ammonia acids.

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Time-­dependent characterizations on the evolution ofparticles showed that silver dendrites were formed byclassic crystallization via atom deposition while the othertwo morphologies were formed by the combination ofparticles aggregation and atom deposition. At a high reaction rate, quick nucleation was followed by atomic layer
growth on the surface of nuclei, forming silver dendrites.
At a low reaction rate, the nucleation was prolonged. The
later formed nuclei adsorbed on the growing particles andbecame new sites for the classic growth, which led to theformation of hierarchical polycrystals, such as silver flowers. This study confirmed the role of reaction kinetics inswitching the crystallization routes, which is expected to
improve our understanding on the growth of hierarchicalstructures and to enhance our ability for rational synthesisof material structures.

Acknowledgements
This study was supported by National Natural Science
Foundation of China (91534123). The financial supports
from the Hundreds Talent Program from the Chinese
Academy of Sciences and the project from the State Key
Laboratory of Multiphase Complex Systems are warmly
appreciated. We thank Alexander von Humboldt foundation for a postdoctoral research scholarship in 2007 and arenewed research stay in 2015.

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Authors’ Short Biographies
Jianmei Liu
Jianmei Liu got her bachelor degree from Ocean University of China in 2013. As ahighly distinctive graduate, she started her master at the same university, and as a joint
student, she studied in Yongsheng Han’s group (Institute of Process Engineering, Chinese
Academy of Sciences) for about three years until she got her master degree in 2016. Thenin 2017, she started her PhD study in research school of chemistry, Australian National
University, and works on functional materials, specially dielectric materials.

Qiang LinMr. Qiang Lin got his bachelor degree in 2002 and master degree in 2005 from Tsinghua
University. After his graduation, he joined Beijing Research Institute of Chemical Industry, Yanshan Branch, SINOPEC and worked there on the research and development of
catalysts for ethylene epoxidation. In 2012, he began to pursue his PhD at the Institute ofProcess Engineering, Chinese Academy of Sciences and passed the doctoral dissertation
defense in July, 2018. Now, He focuses on the preparation and improvement of silver
catalysts.

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Authors’ Short Biographies
Yu Zhou
Yu Zhou graduated from China University of Petroleum (Beijing) in 2018 with the
major of chemical engineering. He was an exchange student in Institute of Process Engineering, Chinese Academy of Science for 2 years starting from 2017. His research focus
on the controllable synthesis of silver nanoparticles.

Jinhui Dai
Dr. Jinhui Dai holds a position of Professor in Ocean University of China. He wasconferred doctor degree by Tsinghua University in 2003. His research mainly focuses on
the preparation and application of solid buoyancy materials and inorganic nanostructures.

Yongsheng Han
Dr. Yongsheng Han is a Professor in the Institute of Process Engineering, Chinese
Academy of Science, Beijing, China. He was conferred doctor degree from Tsinghua
University in 2004. Immediately after his graduation, he went to Japan, Nagoya Instituteof Technology as a postdoctoral researcher. In 2007, he was awarded Alexander von
Humboldt fellowship and went to Germany, Max Planck Institute of Colloids and Interfaces. In 2011, he succeeded in the application of Hundred-Talent Program and joined in
Institute of Process Engineering. His current research interest is to discover the mechanism dominating the structure development of materials for the rational synthesis of catalysts and energy storage materials.

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Original Research Paper

Real-time in-situ Rheological Assessment of Sticky Point
Temperature and Humidity of Powdered Products †Johan C. Groen 1*, Wim Kooijman 1, Djamilla van Belzen 1, Gabrie M.H. Meesters 2,
Denis Schütz 3, Timothy Aschl 3 and Patrick Verolme 1
1

Delft Solids Solutions B.V., The Netherlands
Department of Chemical Engineering, Delft University of Technology, The Netherlands
3
Anton Paar, Austria
2

Abstract
Unwanted changes in powder flow behavior can unexpectedly occur when a product is exposed to certain
conditions of temperature and humidity. This can happen during production, but also during transport or storage.
The work reported here demonstrates the novel approach of using an amended powder rheology set-up formeasuring and predicting such changes in powder flow behavior. The developed methodology makes it possible tovary in-situ the temperature and the relative humidity of the air to which the product is exposed, thereby
mimicking realistic conditions of production or related unit operations. An air flow capable of fluidizing thepowder particles is controlled at a specific constant temperature and its relative humidity can be altered whilemeasuring the torque in the fluidized powder bed in real time. The fluidization is necessary for generating ahomogeneous introduction of temperature and relative humidity. Results obtained using citric acid andcommercial coffee whitener products have proven this methodology to provide both similar and in certain
instances dissimilar results compared to the more established methodology such as measuring the vapour
adsorption isotherms. These observations are explained. In this way, it can be predicted under which
combinations of temperature and humidity a product does or does not become sticky. The main advantages of ourapproach are that the flow properties are directly assessed, the interpretation of the obtained data is morestraightforward and that the measurement times are shortened substantially.
Keywords: powders, stickiness, powder flow, caking, humidity

1. Introduction
A wide array of products is in powder or granular form.
Quite often these products are available as free-flowing
materials for easy transporting, packaging, dosing andhandling by the customer. In this respect, the prediction
and investigation of powder flow is an important measure(Schulze D., 2008). Different techniques are available forinvestigating powder flow, and measurement conditions
can be varied from non-consolidated to highly consolidated systems. Leturia M. et al. (2014) have convincingly
shown that one or more appropriate measurement techniques should often be applied in order to get an understanding of the product’s flow properties under realistic
†
1
2
3

*

Received 12 May 2018; Accepted 21 February 2019
J-STAGE Advance published online 6 April 2019
Molenweer 2 B, 2291 NR Wateringen, The Netherlands
van der Maasweg 9, 2629 HZ Delft, The Netherlands
Anton Paar Strasse 20, 8054 Graz, Austria
Corresponding author: Johan C. Groen;
E-mail: groen@solids-solutions.com
TEL: +31-174-271-460 FAX: +31-174-271-461

176

conditions. Surprisingly, Salehi H. et al. (2017) have recently shown that even similar methodologies working
with the conventional Jenike shear and ring shear principle
can provide inconsistent results. This all makes a reliable
assessment of the powder flow properties a complicatedtask. To make it even more challenging, besides the intrinsic characteristics of the product expressed as particle
size, particle shape, porosity and surface area and density,
also extrinsic conditions can be of vital importance.
The exposure of stable and non-stable granular products to certain conditions of temperature and relative
humidity can transform free-flowing and thus easy-tohandle products into more cohesive and sometimes evensticky materials, eventually leading to caking and clogging of machinery and packaging. Examples of materials
that are sensitive towards stickiness are numerous and canbe found throughout all industries, e.g. in the food industry (Juarez-Enriquez E. et al., 2017) but also in the pharmaceuticals (Lumay G. et al., 2016; Sandler N. et al.,2010) and chemicals industries (Stanford M.K. et al., 2002
and Sun C., 2009). This is considered a major issue in the
powder handling industry and although these phenomena

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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are highly undesirable, they often come unexpectedly.
The effect of temperature on the flow properties of materials has already been investigated using a high-temperature annular shear cell (Tomasetta I. et al., 2013). Here thechanging flow properties of consolidated powders werecompared while varying the temperature, yet the humidity was not regulated.
The prediction of stickiness due to interaction withwater at a certain temperature is a complicated task andnot easily feasible for newly developed or modified products. Moreover, the fact that some quite recent publications deal with the subject of powder flow in relation to
extrinsic conditions such as moisture and temperature
confirms the relevance of the topic (Lumay G. et al., 2016;
Emery E. et al., 2009). In these studies, however, typicallythe water content of the material was studied as the main
descriptor rather than the impact of the relative humidity
in the air, although current literature by Juarez-Enriquez
E. et al. (2017) strongly recommends that the latter option
is much more appropriate.
The interaction of the material of interest with moisturefrom the environment can be studied by recording water
vapor sorption isotherms (Mathlouthi M. et al., 2003).
The uptake of water is then measured as a function of therelative humidity at a certain temperature and the isotherm evidences when a certain interaction of water withthe material is present. Often kinetic models, such as thetwo-parameter BET or the three-parameter GAB model(Goula A.M. et al., 2008), are applied to determine themonolayer coverage of the material, the latter model being often used for food products. The models can be used
to identify the possible presence of sticky behavior, yetthey are not applicable for every material. Since it is notalways clear what actually is causing the water uptake,these measurements are often complemented by techniques capable of determining the glass transition temperature (Emery E. et al., 2009). Below the glasstransition temperature, an amorphous material behaves as
being in a glassy state with a very high viscosity due tothe limited molecular movement at low temperatures(Downton G.E. et al., 1982). However, above the glasstransition temperature, a glassy material starts to transform into a ‘rubbery state’ and the viscosity of the material decreases considerably. A relationship between theglass transition temperature and stickiness was alreadyestablished for a wide range of food powders. Interestingly, however, the glass transition temperature is highly
dependent on the presence of water (vapor) in the system,
and Bhandari B.R. and Howes T. (1999) as well as Goula
A.M. et al. (2008) have convincingly shown that water
vapor typically has a strongly depressing influence on theglass transition temperature. This means that techniques
capable of measuring phase transitions while working
with often a constant (inert) carrier gas flow are restricted

to adequately take into account the implication of water.
Furthermore, a phase transition of an amorphous material from a glassy state into a rubbery state does not necessarily have to occur in order to make a powder material
sticky. Hygroscopic materials that interact with water canalso display sticky-like properties, turning a free-flowing
powder into a cake-like compound without being accompanied by a phase transition. Even for materials that are
not hygroscopic, an enhancement of inter-particle forcesby liquid bridges due to an increased relative humidity
has been proven, e.g. by measuring the onset of avalanches of glass beads (Soria-Hoyo et al., 2009). Even forglass beads up to 4 mm, this enhancement of inter-particle forces could be seen. Furthermore, the particular liquid bridging behavior is highly dependent upon surface
and solvent polarity as shown in recent work (Jarray et al.,2019). The complex admixture of different polarities inindustrially relevant samples (such as the complex admixture of carbohydrates, fatty acids and proteins present incoffee creamer) increases the difficulties. From the adsorption isotherm only, it is often difficult to derive sticky
point conditions, even despite the presence of different kinetic models. An additional complicating factor is thatstickiness also depends on particle morphology such as
the size and the shape of the particles (Shi H. et al., 2018).
This impressive set of variables means that assessment of
the stickiness of a certain product preferably requires astudy of the particular product under realistic conditionsof temperature and (relative) humidity.
An attractive tool would thus allow a direct assessmentof powder flow under varying conditions of moisture andtemperature. First studies by Lazar M.E. et al. (1956) that
already appeared in the 1950’s report on stickiness inwhich an impeller stirred by hand was used to identify
changes in resistance in the powder material upon increasing the temperature. Though being an effective
methodology, the sensitivity of the method was clearly too
low to detect the early onset of stickiness.
More recently, Özkan N. et al. (2002) reported on theuse of a powder rheometer to accurately measure thesticky point. In this study different variables—temperature, time, and pressure of compaction—were investigated, however, only the moisture content in the productwas altered and no study was done on the impact of therelative humidity of the surrounding atmosphere thatwould be realistic, e.g. during storage and transport.
Other works reported so far have mostly used external
cabinets to accommodate and equilibrate powder samples
externally under certain conditions of temperature and/or
relative humidity.
In the work reported here, we discuss the in-situ variation and control of temperature and relative humidity
during which changes in the flow of the powder materials
are recorded in real time by a novel powder rheometer

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set-up in order to determine the range of conditions at
which the material can become sticky.

2. Experimental
2.1 Materials
Commercially available coffee creamer with the product name Completa (Friesland Campina, The Netherlands)
was purchased from the local grocery store and usedwithout further modification.
All materials were kept in their original containers andstored in a glovebox under nitrogen in order to avoid interaction with moisture.
Citric acid monohydrate with a purity of > 99 % was
acquired from Boom Chemicals (The Netherlands) andwas used with minor modification. The only modification
applied was reducing the particle size using a mortar.
This was done to obtain a powder with a particle size
< 300 μm that could be fluidized in the rheometer set-up.
The citric acid monohydrate sample thus obtained appears
to contain 8.2 wt.% water, whereas a true monohydrateshould have 8.6 wt.% of water. The implication of theslightly lower water content is discussed in the results anddiscussion section.

2.2 Methods
Water vapor sorption isotherms were recorded in an
IGASorp HT from Hiden Isochema, which employs the
dynamic vapor sorption principle. A microbalance with
sub-microgram resolution is used to record weightchanges due to the adsorption or desorption of water vapor molecules. Isotherms were recorded in a temperature
range of 15–75 °C and a relative humidity range of
5–90 %. In a typical experiment, approx. 10–20 milligrams of sample were used.
Powder rheometry investigations were executed in a
modified Anton Paar MCR 302 rheometer equipped withthe optional powder cell. The cell is cylindrical with a diameter of 50 mm and has a porous material (borosilicate
glass Frit; Por. 4 (Schott Duran)). The stirrer used was a
two-blade stirrer of rectangular shape measuring
36 mm × 10 mm, and continuously held at a 10 mm gap.
Modifications to the stock cell consist mostly of an exchange of the bottom plate of the cell holder from stainlesssteel to a custom-made PEEK model to avoid extensive
heat loss through conductive transfer. Fluidization of thepowder sample was used in the actual analysis in order toachieve a homogeneous introduction of the water vapor
during exposure to different relative humidity values. A
fluidization velocity from 2.5–12.7 cm/s was set for theexperiments. Although fluidization of the sample induces

178

substantially lower torque values compared to a packed
bed, the sensitive torque sensor and the low residual friction of the air bearing in the rheometer makes accurate
and repeatable measurements possible under these conditions. The two-bladed spindle that was used for a continuous recording of the torque in the sample was rotatedconstantly at fairly high rpm values (50 rpm) to further
improve the homogeneous interaction of the water vapor
within the sample. The air used for fluidization, controlled
by a mass flow controller, was heated by means of anevaporation mechanism powered by an external heater
kept constantly above 105 °C and heat tracing of the connection lines. The relative humidity was regulated bymeans of a Harvard PHD-2000 infusion syringe pumpdevice integrated into the heated gas line for instant evaporation and subsequent dosing of the required amount ofwater, thereby attaining the desired relative humidity
value.

3. Results and discussion
The first experiments performed were using the coffee
creamer. Both the water vapor sorption isotherms and thetorque curves are recorded at a certain fixed temperature
as a function of a stepwise change in relative humidity
over time. The original data obtained were therefore plotted as a function of time and can be replotted as a function of relative humidity. For the conventional DVS
method, the original data are displayed in Fig. 1, andshow the uptake of water vapor due to the increase of therelative humidity over time. Initially, the uptake is relatively low and equilibrium is reached fairly quickly.
At a certain RH value, the uptake becomes more significant, and reaching equilibrium requires more time.
Therefore the measurement time is different for eachFig. 1

Typical dynamic vapor sorption curve of the coffee
creamer sample at 25 °C, with increase and decrease of
the relative humidity at this temperature and the weightchange of the material due to this relative humidity
change.

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point, as it is only when equilibrium is obtained that therelative humidity is increased in order to record a newdata point. Upon reaching the maximum RH value of
90 %, the relative humidity is decreased, to identify
whether the desorption of water vapor is reversible to theadsorption of water vapor. Usually, for materials that undergo a phase change or materials that are able to strongly
adsorb water vapor, the desorption isotherm is not reversible to the adsorption isotherm, which is a direct indicationthat the material has changed during the measurement.
Visual inspection of the material under investigation after
the measurement can confirm whether or not this change
has occurred. Using the weight change of the material ateach equilibrium point, the isotherm can be constructed.
The torque curve obtained with the Anton Paar Rheometer set-up is displayed in Fig. 2 and shows the torquechanges due to the increase of relative humidity over time
at a certain constant temperature. The humidity change isa manual operation and the stepwise increase is executedwith a fixed time interval. At the end of each relative
humidity point, the torque is measured and the friction
isotherm can be plotted. The main advantage of the technique is that the actual flow behavior of the material ismeasured, and thus that the increase of the torque at a
certain relative humidity value actually describes that theflow ability of the material changes. With the DVS technique, the uptake of water vapor is not necessarily an indication that the flow properties of the material havechanged and that the material has become sticky. It istherefore also not necessary to record a decrease in humidity with the rheometer set-up, as the change in flow
behavior is directly monitored. This also translates to amuch faster determination of the sticky points of materials,
as with the Anton Paar Rheometer a measurement can be
performed within 6 h, while with the DVS technique, ameasurement could last several days.

Fig. 2Torque curve of the coffee creamer sample at 23 °C
obtained with the Anton Paar Rheometer, with an increase of the relative humidity at the set temperatureand the torque change of the material due to this relative humidity change.

3.1 Powder Rheometry of Coffee Creamer
The isotherms obtained from the torque profiles of thecoffee creamer sample at different temperatures are plotted in Fig. 3. The isothermal plots show a stable torquevalue at lower relative humidity values and an increased
torque value when the relative humidity exceeds a certain
value. The increase in torque is a direct indication that theflow properties of the material are decreasing and thusthat the material becomes sticky. Two distinct regions canbe discerned and a linear fit has been plotted in these regions. The cross-section of both fits determines the point
where excess water is present and the material becomessticky. The resulting sticky point values for the coffee
creamer at different temperatures are quantitatively summarized in Table 1.
Since this approach is solely based on the flow properties of the material, the sticky point does not have to be
derived from a water vapor sorption isotherm using a certain method or model, as is the case for DVS. The sticky
point can be directly determined and is a direct indicationof when the flow properties change and thus when thematerial becomes sticky.
3.2 Water Vapor Sorption of Coffee Creamer
The water vapor sorption isotherms are given in Fig. 4,
where the sample weight is plotted as a function of relative humidity at different temperatures. The dynamic vapor adsorption measurements with water vapor over thecoffee creamer sample reveal that for each temperature, atlower relative humidity values, an almost stable weight isobtained. For the measurements performed at all four
temperatures, three distinct regions can be discerned,
namely a region where the material shows hardly any uptake, a quite linear second region where the sample weightof the material steadily increases and, at higher humidity
values, a third region can be seen where after the steadyincrease of the sample weight, a sort of exponential increase occurs. The uptake seen can be caused by adsorption in pores of the material, adsorption on the externalsurface area or by the transition of a certain component(from amorphous to crystalline). Each of these regions
describes a different state the material is in, and in orderto know when the materials become sticky, to derive thesticky point, is not an easy task. Since the sticky point has
to be derived from the obtained isotherms, it can be debated what is the best method to do so.
The GAB (Guggenheim-Anderson-de Boer) model iswidely used on food materials and could provide the best
fit. The model has been applied on the acquired data sets,
and the monolayer uptake is obtained, from which subsequently the sticky point can be determined. The obtained
sticky points are listed in Table 1.
A similar procedure as used when obtaining the Anton
Paar values was applied that determines the intersection

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Fig. 3 Torque isotherms of the coffee creamer sample at 4 different temperatures, 23 °C, 31 °C, 42 °C and 54 °C,
with the fitted regions in the isotherms obtained with the Anton Paar Rheometer technique.
Table 1

Sticky point values for coffee creamer recorded via the powder rheometer methodology and derived from the water
vapor sorption isotherms using the various methods, in the temperature range from 23–54 °C.

T rheometer T DVS°C°CSticky point
rheometer% RH

Sticky point DVS,GAB model% RH

Sticky point
DVS, linear fit(1 and 2)% RH

Sticky point
DVS, linear fit(1 and 3)% RH

Sticky point
uptake point
DVS
% RH

23

25

59.4

62.2

51.9

70.5

50

31

30

54.7

39.8

46.0

68.2

45

42

40

44.1

43.3

40.5

70.4

40

54

54

15.9

27.8

32.4

71.7

35

of two linear fits through the first two regions in the isotherms. The suitability of this procedure has been verified
for materials and isotherms where the GAB model wasapplied and this has proven to produce consistent—insignificantly different—results. However, the isotherms display three different regions and it is unclear in which
region the material starts to become sticky. Linear region
1 (the region of low relative humidity values of the isotherm) is fitted and regions 2 and 3 have been fitted andthe results of both fittings are listed in Table 1.
Another method that can be used to derive the sticky
point of a material from the water vapor adsorption isotherms is by taking the point where the material starts totake up water, the uptake point method, and these points
have also been added to Table 1.

180

Table 1 clearly illustrates for the data obtained with theAnton Paar rheometer that with an increasing temperature
the sample becomes sticky at a lower relative humidity
value. The data display a linear trend, with the exceptionof the sticky point determined at 54 °C, which deviatesfrom this fit. During this measurement, it could be observed that water vapor insertion into the gas stream occurred unequally. This led to spikes where the RH values
were increased, which caused the material to become
sticky at an earlier stage than expected, not corresponding
to the set RH values. Therefore, this point is omitted infurther calculations and comparisons.
The sticky points obtained with the GAB model show
some similarities but also some large deviations whencompared with the sticky points of the rheometer.

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Fig. 4

Adsorption isotherms of the coffee creamer sample at 4 different temperatures, 25 °C, 30 °C, 40 °C and
54 °C, with the three fitted regions in the isotherms obtained with the Dynamic Vapor Sorption technique.

Furthermore, a linear trend between the 4 sticky points
obtained with the GAB model cannot be obtained. During
fitting of the isotherms with the GAB model it could already be seen that the data could not be fitted adequately.
Lewicki P.P. (1997) and Maroulis Z.B. (1988) have shownthat the regression method used to fit the model can resultin inaccurate results, but also that not all isotherms can be
accurately fitted using the model. In our case, the coffee
creamer material is not completely dry when adsorptioncommences and this results in a minor mass decrease,which in turn does not allow an accurate fit of the GABmodel. This procedure is used in order not to alter thematerial prior to the measurement which could occur, andis described vide infra for the citric acid material. The
model has been applied on the isotherm obtained overdried coffee creamer material and this resulted in an adequate fit and good correlation with the rheometer values.
It is thus very important how the vapor sorption data is
obtained whether or not the GAB model can be applied.
Fitting of the linear regions of the isotherms results insticky points that have a rather good correlation with thedata obtained with the rheometer, and a nice linear trend
is found when regions 1 and 2 are used, as using the highrelative humidity region (region 3) results in sticky points
that do not correlate with the rheometer results and also
do not provide a nice linear trend. The latter statement

can be made regarding the results obtained when the
sticky point is determined using the uptake point method,at the onset of excess water adsorption.
In a Mollier diagram the temperature is plotted versus
the absolute quantity of water, which is expressed as kg
water per kg air. The obtained sticky points at a certain
temperature are converted from RH values to absolute
water quantities and can be plotted in such a diagram. Using the best fit, a curve can be constructed through theobtained data points and two regions are obtained, asticky region and a non-sticky region. The Mollier curves
derived from the sticky points obtained with the Anton
Paar Rheometer and the DVS system are shown in Fig. 5.
The Mollier diagrams of only the GAB model and the linear fit of the regions 1 and 2 have been calculated, since
only these methods provide linear results.
The relative humidity values of the sticky points obtained with the rheometer method and the linear fitting
methods are rather similar when compared with eachother, and the Mollier diagrams derived from these humidity values are also very similar, indicating that consistent
results can be obtained with both methods. Both diagrams
show that the top of the curve is at 80 °C, with 0.043 kg
water/kg air obtained with the rheometer and 0.044 kg
water/kg air with the DVS system using the linear fit
methodology. Both diagrams also have a maximum

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temperature of approx. 100 °C, which matches nicely withthe maximum degradation temperature obtained with a
TGA experiment performed on the material. The relative
humidity values of the sticky point obtained with the
GAB model were already quite different compared tothose of the rheometer, and distinct differences can beseen when the Mollier diagram is constructed from theseresults. The top of the curve is at 65 °C with 0.026 kg
water/kg air, and the maximum temperature has shiftedfrom 100 °C to 80 °C.

Fig. 5

Mollier diagram of the coffee creamer material derived
from the sticky points obtained via the Anton Paar
Rheometer and the DVS system (GAB model and linear fit).

Fig. 6182

If one would simply apply the GAB model and use thedata to construct the Mollier diagram, an underestimation
would be made, which will negatively impact on the flexibility in handling the material during production andstorage.
3.3 Powder Rheometry of Citric Acid Monohydrate
The isotherms obtained from the torque profiles of thecitric acid monohydrate sample at different temperatures
are plotted in Fig. 6. The isothermal plots show a stable
torque value at lower relative humidity values and an increase when the relative humidity exceeds a certain value.
Two distinct regions can be discerned and a linear fit has
been plotted in these regions. The cross-section of bothfits determines the point where excess water is present
and the material becomes sticky. The resulting sticky
point values for the citric acid monohydrate at different
temperatures are quantitatively summarized in Table 2.
3.4 Water Vapor Sorption of Citric Acid Monohydrate
The dynamic vapor adsorption isotherms over the citricacid monohydrate material are plotted in Fig. 7 and revealthat initially, at lower relative humidity values, the material
displays a loss in mass rather than an uptake. This initialloss in mass can be ascribed to the (partial) transition of
citric acid monohydrate to citric acid anhydrate. Then aTorque isotherms of the citric acid monohydrate sample at 4 different temperatures, 25 °C, 44 °C, 60 °C
and 72 °C, with the fitted regions in the isotherms obtained with the Anton Paar Rheometer technique.

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nice plateau is obtained and at a certain relative humidity
value, a substantial linear uptake can be discerned. This
linear uptake could be caused by several phenomena,
namely due to the transition of the anhydrate to the monohydrate form or by uptake of water in the pores and/or external surface area of the material or by multilayer
adsorption. A third phenomenon was also observed,
namely that at these higher relative humidity values coupled to the temperatures, the material started to liquify.
So besides the fact that it is not always evident where toderive the sticky point from a water vapor isotherm, thefact that all these phenomena occur simultaneously makes
it almost impossible to make a good distinction and propTable 2 
Sticky point values for citric acid monohydrate
recorded via the DVS using the curve fitting method
and powder rheometer methodology in the temperature range of 25–72 °C.
T rheometer T DVS°C°CSticky point
rheometer% RH

Sticky point
DVS
% RH

25

25

66.4

69.0

44

40

52.7

66.7

60

65.7

41.2

61.7

72

71.3

37.5

57.3

Fig. 7erly determine the sticky point of the material, eventhough it was visually observed that the material became
sticky during the measurements.
The GAB model could not be applied for this material,
and again the procedure using linear fitting over the tworegions has proven to be the most adequate.
Drying the material prior to the measurement eliminates the weight loss observed at low relative humidity
values. However, the water vapor uptake occurs at thesame relative humidity values as the undried material.
For the data obtained with the Anton Paar rheometer,
Table 2 also clearly illustrates that with an increasing
temperature the sample becomes sticky at a lower relative
humidity value. A linear trend can be fitted through all
four data points.
Fitting of the linear regions of the water vapor isotherms results in sticky points that can be fitted with alinear trend, yet clearly deviate from the results obtainedwith the rheometer, as the relative humidity values of theobtained sticky points via the linear trend method aremuch higher. This is due to the fact that during the uptakeof the citric acid monohydrate at higher relative humidity
values, different phenomena occur (change from anhydrous
to monohydrate, water uptake at the external surface areaand liquefaction), and the DVS system is not able to distinguish between these several phenomena. This therefore

Water vapor isotherms of the citric acid monohydrate sample at 4 different temperatures, 25 °C, 40 °C,
65.7 °C and 71.3 °C, with the fitted regions in the isotherms obtained with the Dynamic Vapor Sorption
technique.

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method, and this could easily result in inaccurate results,
while with the rheometer, such problems can be avoided.
Another advantage of the rheometer set-up is that themeasurement times are drastically reduced.

Acknowledgements“This scientific work could not have been completed
without the practical efforts of Swasti Soekhradj.”

Fig. 8 Mollier diagram of the citric acid monohydrate material
derived from the sticky points obtained via the Anton
Paar Rheometer and the DVS system (linear fit).

leads to an incorrect determination of the sticky point.
When the Mollier diagrams are constructed, the large
differences between the two techniques become evenmore apparent. The Mollier diagram constructed with therheometer data shows a nice top around 100 °C with
0.12 kg water/kg air and a maximum temperature around
130 °C. This maximum temperature nicely approaches
the melting point of citric acid, which is at 153 °C.
The Mollier diagram constructed with the DVS system
has a top at a very high temperature of 290 °C with 7.5 kg
water/kg air. The maximum temperature is around
360 °C. These values suggest that for almost all temperatures and moisture contents present, the material will not
become sticky, while it was clearly observed that the materials do become sticky, and the maximum temperature
exceeds the melting point of citric acid where the material
will surely become sticky. This thus indicates that for
more complex materials, the DVS technique is not reallycapable of accurately determining the sticky points andconstructing the Mollier diagram.

4. Conclusions
From this study it can be concluded that with the rheometer set-up and linear fit approach, results can be obtained that correlate very nicely with results obtained
from the DVS method. In some cases, e.g. the citric acidmaterial, the rheometer set-up is capable of producing
more reliable results.
This is due to the fact that the rheometer set-up directly
measures the flow properties of a material and is thus capable of directly assessing the sticky point. The DVS
technique measures water vapor uptake and is not capableof making a distinction between the several phenomenathat may occur during the measurement.
Furthermore, the sticky point has to be derived fromthe water vapor sorption isotherms using a model or184

Nomenclature
BET

Brunauer–Emmett–Teller

DVS

Dynamic Vapor Sorption

GAB

Guggenheim–Anderson–de BoerPEEK

Polyether ether ketone

RH

Relative Humidity (%)

TGA

Thermogravimetric Analysis

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Authors’ Short Biographies
Johan Groen
Johan Groen studied chemistry in Delft and obtained his PhD. in chemical technology
from the Delft University of Technology on the theme of zeolite catalysis. During his
stay at the university, Johan published over 40 scientific papers and contributions inbooks, and he is the inventor of one patent. In 2008, Johan co-founded Delft Solids Solutions, a contract research institute in the Netherlands devoted to particle and powder engineering, of which he is co-owner and science & technology director. His interests lie
in the coupling between fundamental properties of particles and powder behaviour typically encountered in the powder handling industry.
Wim Kooijman
Wim Kooijman studied Chemistry in Rotterdam and obtained his BsC. in chemistryfrom the Hogeschool Rotterdam in September 2017. Wim wrote his graduation thesis
about powder stickiness as an intern at Delft Solids Solutions in Wateringen. After hegraduated Wim joined Chevron Oronite Technology Netherlands as a Laboratory Technician. In March 2019, Wim switched jobs, becoming a Project Technician for the development of Automotive Engine Oils at Chevron. He is interested in analytical and organic
research in Chemistry, which results into the development of new, more environmentallyfriendly products.

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Authors’ Short Biographies
Djamilla van Belzen
Djamilla van Belzen studied Chemistry at the University of Applied Sciences inLeiden. Djamilla got her B.Sc. in 2018 after her internship at Delft Solids Solutions. After her internship Djamilla started to work for CarbonX, located in Delft, as a QA/QC
technician. Her interests lie in the physical part of chemistry and technology.

Gabrie Meesters
Dr Gabrie Meesters has 27 years of industrial formulations experience at Gist-­
brocades, Genencor International and DSM. He has 23 years of experience as a part-timeProfessor at TU Delft in particle technology and product design. From January 2019, hebecame a full-time Assistant Professor at the TU Delft, Faculty of Applied Sciences,
Product and Process Engineering. He is a contributor to several books on formulations.
He is the editor of three books on product design and solids processing. He publishedover 70 refereed papers, has more than 20 patents and supervised more than 100 BSc, MSc
and PhDs. He is a regular speaker at conferences and workshops. He was the organizerof the 2010 Partec and the 2010 World Congress on Particle Technology in Nuremberg,
Germany.
Timothy Aschl
Timothy Aschl holds a PhD in chemistry from the École Polytechnique, France, and a
Master’s degree in applied physics from the Technical University of Graz, Austria. His
research was focused on biosensors and biofuels. Timothy joined Anton Paar as a global
product manager for powder rheology, and in this role he is a frequent speaker at seminars and training courses for companies and universities for a wide range of branches
and industries around the world.

Denis Schütz
Denis Schütz earned his Master’s degree in chemistry at the University of Graz in2009 and afterwards joined the PhD programme for materials chemistry and chemicalengineering at TU-Graz, finishing in 2013. He did postdoc research at Graz Universityof Technology and postdoc research at Jozef Stefan Institute. At present he is principal
scientist for powder rheology and applied scientist for materials at Anton Paar GmbH.
His current interests are in granular media and powder flow research as well as
high-temperature processing and device building.
Patrick Verolme
Patrick Verolme studied chemistry in Rotterdam and received his Bachelor of Science
degree from the Rotterdam Hogeschool, after performing his graduation study at Delft
Solids Solutions on the topic of water vapor sorption studies. Since 2012, Patrick has
been working at Delft Solids Solutions in the field of solid particle/powder research, withhis main area of expertise being specific surface area, porosity and vapor sorption studies. His role has expanded to the research of bulk powder characteristics, on which he isa frequent speaker at seminars and courses.

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KONA Powder and Particle Journal No. 37 (2020) 187–194/Doi:10.14356/kona.2020007

Original Research Paper

Development and Validation of a Simplified Laboratory Test
to Design Vertical Stirred Mills †Maurício G. Bergerman * and Homero Delboni Junior
1

Mining and Petroleum Engineering Department, University of Sao Paulo, Brazil

Abstract
The use of vertical stirred mills in the mining industry has increased remarkably over the past few decades as aresult of the growing demand for finer ore grinding. This equipment is recognized to deliver higher energy
efficiency in fine grinding operations when compared to conventional tubular mills. Methods of designing verticalstirred mills involve operational experience, pilot plant tests and bench tests. An important issue is that thelaboratory-scale test, conducted in the standard 8"×10" jar, requires at least 10–20 kg of material, depending onore density, which is not available in many cases, particularly in the early stages of greenfield projects. For
regrinding of flotation concentrates, several bench scale flotation tests are required to generate such a sample. The
paper describes the development and validation with six different ore samples of a simplified laboratory jar mill
test using a 6"×8" jar, which is smaller than the 8"×10" size, the latter commonly used which requires about onetenth of the mass required in the standard test. The proposed test indicated similar results as compared to thestandard procedure.
Keywords: grinding, regrinding, jar test, vertical stirred mill, scale-up

1. Introduction
A significant demand for finer grinding has been noticed in several mining projects over the past few decades
to achieve adequate liberation, as required for the concentration of valuable minerals. However, the finer the product size, the greater the grinding energy consumption,
resulting in an overall increase in operating costs, which
may reach or even exceed 50 % of the mineral processing
costs (Daniel and Lewis-Gray, 2001; Vieira and Peres,2013). Comminution technology can have a major impact
on subsequent ore concentration stages (Daniel and Lewis-­
Gray 2001; Marsden, 2009; Napier-Munn, 2012; Pease etal., 2010), which further underlines the importance ofproper technology and equipment selection. Appropriate
grinding circuit selection and design is thus a key aspectassociated with successful mining projects.
Based on these trends, vertical stirred mills with low
impeller speed, such as the VertimillTM, has been adopted
throughout the mining industry since 1970s (Bergerman,
2013; Goto 2010; Mazzinghy et al., 2017; Toroman and†Received 20 December 2018; Accepted 11 March 2019
J-STAGE Advance published online 20 April 20191
Av. Prof. Mello Moraes, 2373, Butantan - CEP 05508-030, Sao
Paulo, Brazil* Corresponding author: Maurício G. Bergerman;
E-mail : mbergerman@usp.br
TEL: +55-11-2648-6076 FAX: +55-11-2648-6076

Katircioglu, 2011). These mills consist of a vertical cylindrical chamber in which the charge is stirred by a lowspeed impeller. In this paper, it is referred to as verticalstirred mill. Several authors have shown that grinding
technology based on impeller stirred mills will be of fundamental importance in minimizing energy consumption
in regrind circuits (Bergerman and Delboni Jr., 2014;
Hogg and Cho, 2000; Kawade and Schwedes, 1997;
Marsden, 2009; Mazzinghy et al., 2017; Napier-Munn,
2012; Norgate and Jahanshahi, 2011; Rule and Neville,
2012; Valery Jr. and Jankovic, 2002).
The design of vertical stirred mill for specific applications are generally based on laboratory tests. Accordingly,
Metso, which is one of the main manufacturers of verticalstirred mills, adopts a standard batch grinding test using a8" (203 mm) in diameter by 10" (254 mm) in length(8"×10") jar (Jankovic and Valery Jr., 2004). The test is
carried out according to different grinding times until thetarget particle size is reached. Such a test provides a relationship between specific energy consumed as a functionof particle size, the latter referred as d80. The required energy consumption is thus calculated using such a relationship, based on the target particle size. The specific energy
obtained is then multiplied by a factor of 0.65. Such a factor, referred to as the VertimillTM (VTM) factor, assumes
a higher efficiency associated with VTMs (Wills andFinch, 2016). The above described procedure provides agood correlation with industrial mills and is used as an

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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industry standard for the design of this kind of equipment(Bergerman, 2013; Wills and Finch, 2016; Donda, 2003;
Mazzinghy et al., 2014). The sample required to perform
each grinding time is based on the calculated volume required to entirely fill the voids within the steel ballcharge, which for the standard tests is 1.381 L. For instance, for a material with a bulk density of 3.04 g/cm3,
such as the iron ore concentrate used in this study, eachgrinding time will require 4,203 g of sample, which results in a total of 21,105 g for all five grinding times.
A remarkable aspect of designing vertical stirred mills
for industrial regrind circuits is the lack of sufficient massfor carrying out batch grinding tests that follow the standard adopted by Metso. This is a serious hurdle for projects in the early stages, as 100–1,000 kg of ore would benecessary to obtain the required amount of regrinding
feed. Indeed, in a typical copper sulphide flotation project, a significant amount of rougher concentrate is required for regrind testing. Such a situation becomes evenmore critical for low-grade ores, where rougher concentrate mass recovery is low as well. One practical consequence is that a number of industrial regrind circuits aredesigned without any proper laboratory or pilot testing
validation. Laboratory batch tests based on significant
smaller sample mass would thus be particularly useful for
designing vertical stirred mills.
This paper describes the development and validation ofa laboratory jar mill test using a 6"×8" jar, requiring muchless sample than a standard test, which is carried out witha 8"×10" jar, as described in Mazzinghy et al. (2014) andWills and Finch (2016). The required specific energy isTable 1188

based on the global specific energy method (Austin et al.,1984). The samples used in our tests represented the respective industrial regrind circuit in all cases.

2. Materials and methods
Tests were carried out with six different ore samples,
including copper, phosphate, and iron ores obtained in industrial grinding circuits from Brazil. The surveyed
plants were as follows: Anglo American Minas Rio Project (iron ore), Vale Salobo (copper ore), Vale Sossego(copper ore), Mosaic Tapira (phosphate ore), and Vale Vitoria Pelletizing plant (iron ore). Plant flow sheets and operating data may be found elsewhere (Bergerman et al.,2012; Guimarães, 2004; Mazzinghy et al., 2015; Meyer etal., 2015). Each sample was tested to determine the respective density of solids (using a pycnometer), the bulk
density by using a graduated measuring cylinder, and theparticle size distribution and specific surface area by laser
scattering using a Malvern 2000 Mastersizer. Deionizedwater was used as a dispersion medium in the analysis
carried out using Malvern. The refraction indexes of particles were 1.45, 1.729, and 1.627, respectively for copper,
iron, and phosphate ores, while it was 1.33 for the dispersion medium. The Malvern analyser stirrer speed was
2,500 rpm and ultrasound was applied for one minute.
After the initial ore characterization tests, each sample
was quartered for grinding in both 6"×8" and 8"×10" jars
according to test conditions listed in Table 1. Both mills
were fitted with smooth stainless-steel liners.

Test conditions for each jar test.

Conditions and Characteristics

6"×8" jar

8"×10" jar3

Jar volume (m )0.00370.0082

Ball filling, J (%)

42

42

Charge voids (%)

40

40

Grinding ball size (mm)

12.7

12.7

Solids (%)

70

70

Charge interstice filling, U (%)

100

100

Sample mass foreach grinding
cycle (g)Anglo American Minas Rio

1,883

4,203

Vale Salobo

1,306

2,914

Vale Sossego—sample 1

1,386

3,094

Vale Sossego—sample 2

916

2,044

Mosaic Tapira

1,145

2,555

Vale Vitoria

1,838

4,102

Mill speed (rpm)

82.5

71.4

Mill rotation speed (% critical speed)

76.0

76.0

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Fig. 1 illustrates the laboratory mill used in all tests.
Five grinding times were carried out for each sample according to standard periods of 5, 10, 20, 40, and 80 minutes. A fresh sample was used in each grinding time.
Additional tests were carried out with the sample ofSalobo ore, for which a larger mass was available. In thiscase, the same initial sample was ground according to the
stipulated five grinding periods. Although it is atime-consuming test, as size analysis is required in between consecutive grinding times, such a procedure reduces the required sample to one-fifth of the standard test.
The jar mill power consumption was measured by atorque meter (Fig. 1), and results were compared to estimates using the equation proposed by Rowland Jr. (1986)(Eqn. 1), which applies to jars with a diameter smaller
than 2.44 m.

2.44  D 
kWb 6.3D 0.3sin 51  22  
 2.44 
0.1

3.2  3Vp  Cs 1  910Cs  (1)2where:
kWb = mill power per metric tonne of balls (kW/t)
D = mill diameter inside liners (m)Vp = fraction of mill volume loaded with balls (%)
Cs = fraction of critical speed (%)
The product particle size distribution, density, and millFig. 18"×10" jar mill equipped with a torque sensor.

Fig. 2

power error was determined through five repeated measurements of the same sample/test and the respective
standard deviation was determined. Details of all error
calculations are described in Bergerman (2013). The assessment procedure adopted indicated that the error associated with the mill power calculation was very low(below 1 %, thus not represented in the error bars of thegraphics presented in the paper), whereas the particle size(d80 and specific surface area) error was approximately
5 %, which is the value used at the error bars in
Figs. 3–10.

3. Results and discussion
The results obtained in the characterization tests aredescribed in Table 2 and Fig. 2.
The d80 of the samples varied from 69 to 166 μm, while
their bulk density varied from 1.48 to 3.04 g/cm3. The
values varied within a relatively wide range for both d80
and bulk density, which was here considered instrumental
for validating the proposed regrinding test.
Figs. 3 to 8 illustrate the d80 and specific surface area
parameters, as well as specific energy consumption, calculated with Eqn. (1), for the different grinding times andTable 2

True and bulk densities of tested sample.

SampleDensity of solids(g/cm3)

Bulk density(g/cm3)

Anglo American
Minas Rio

5.03 ± 0.08

3.04 ± 0.03

Vale Salobo

3.63 ± 0.02

2.11 ± 0.04

Vale Sossego—sample 1

3.68 ± 0.01

2.24 ± 0.01

Vale Sossego—sample 22.98 ± 0.05

1.48 ± 0.02

Mosaic Tapira

3.15 ± 0.04

1.85 ± 0.01

Vale Vitoria

4.79 ± 0.15

2.97 ± 0.01

Particle size distribution of grinding test feed samples.

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Fig. 3 Specific power consumption as a function of d80 and specific surface area—Anglo American
Minas Rio sample.

190

Fig. 4

Specific power consumption as a function of d80 and specific surface area—Vale Salobo.

Fig. 5Specific power consumption as a function of d80 and specific surface area—Vale Sossego
sample 1.

Fig. 6

Specific power consumption as a function of d80 and specific surface area—Vale Sossego
sample 2.

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Fig. 7 Specific power consumption as a function of d80 and specific surface area—Mosaic Tapira
sample.

Fig. 8 Specific power consumption as a function of d80 and specific surface area—Vale Vitória
sample.
Table 3

Jar test results in both mills for different selected specific energies (10 and 20 kWh/t).

SampleJar

10 kWh/t

20 kWh/t

d80(μm)

Difference
(%)

d80
(μm)

Difference(%)

Anglo American Minas Rio

6"×8"
8"×10"

50.8
53.0

4.2

37.5
38.5

2.5

Vale Salobo

6"×8"
8"×10"

38.4
39.5

2.8

30.2
30.5

1.2

Vale Sossego—sample 16"×8"8"×10"

32.8
32.2

2.0

23.4
21.5

9.1

Vale Sossego—sample 26"×8"8"×10"

29.3
31.4

6.6

23.0
25.0

7.9

Mosaic Tapira

6"×8"
8"×10"

62.7
62.5

0.3

36.3
34.2

6.2

Vale Vitoria

6"×8"
8"×10"

67.5
68.3

1.3

47.8
49.0

2.6

jar dimensions.
Regression carried out in each graph indicated generally
good fitting for both d80 and specific surface area as a function of specific energy consumption. Such observation
was valid for both jars used in tests i.e., the standard
8"×10" and the proposed 6"×8". The results obtained forthe different jars are very similar, with small differences
within the errors related to the measurements. Larger dif-ferences between the jars appeared only for Vale Sossego
sample 2. One possible explanation is that, for this sample, the feed was already very fine and the extent of size
reduction obtained was very limited for the grindingtimes studied.
In order to compare the results for both tests in two different specific energy consumptions, Table 3 compares
the results of the jar tests in both mills for 10 and 20 kWh/t.

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The results focus on product d80, which is the reference
parameter for vertical stirred mill design and selection.
The data shown in Table 3 illustrate that the results arevery similar, with less than 10 % difference between thed80 obtained for the different jar sizes. In fact, differencesin absolute terms were within the ± 2 μm, which is considered very small. This can be explained as the two tests
conditions, for both 6"×8" and 8"×10" jars, have similarparameters, which includes same ball size, critical speed,
length to diameter ratio (1,33 for the 6"×8" jar and 1,25 forthe 8"×10" jar) and power per volume unit (5,0 kW/m3 forthe 6"×8" jar and 5, 6 kW/m3 for the 8"×10" jar).
Figs. 9 and 10 and Table 4 illustrate the variation of d80

and specific surface area parameters as a function of
specific power consumption for different grinding times,
using only one sample (o.s.) for all grinding periods. In thiscase, the material from the first grinding time was placedback in the mill for the second grinding time and so forth.
The results indicate no significant differences between
the standard test procedure and the proposed one, i.e., regrinding the initial sample in the different grinding periods. It also shows the same magnitude of errors, in spiteof the additional sample manipulation involved with thesize analysis required between grinding times.
Based on such results, one can consider any one of thetests, standard or simplified, as a basis to design verticalFig. 9 Specific power consumption as a function of d80 and specific surface area—one sample per
grinding time vs. one sample for all grinding times - 6"×8" jar—Vale Salobo sample.

Fig. 10 Specific power consumption as a function of d80 and specific surface area—one sample per
grinding time vs. one sample for all grinding times - 8"×10" jar—Vale Salobo sample.
Table 4

Jar test results in both mills for different selected specific energies (10 and 20 kWh/t).

Sample192

Jar

10 kWh/t

20 kWh/t

d80(μm)

Difference
(%)

d80
(μm)

Difference(%)

Vale Salobo one sample

6"×8"
6"×8" o.s.

38.4
40.2

4.6

30.2
31.2

3.4

Vale Salobo one sample

8"×10"
8"×10" o.s.

39.5
39.4

0.2

30.5
29.2

4.4

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stirred mills. The required sample mass is, however, thegreat difference between the tests. In the case of Anglo
American Minas Rio ore, the sample required for the
standard test was 21,015 g, as opposed to 9,165 g for thesimplified test. Such requirement would be reduced to1,883 g if one considers the regrind of the same sample ineach grinding period. Moreover, considering the average
mass recovery of approximately 47 % at this mineral processing plant, the mass of material to be floated in a laboratory study could be reduced from 45 to 4 kg. Whenconsidering sulphide ore, such as Vale Salobo, where themass recovery of the rougher stage is around 10 %, themass of material to be floated in a laboratory test campaign would be reduced from 146 to 13 kg, in order to obtain the 1,306 g required for the simplified jar test.

4. Conclusions
The study demonstrated the possibility of using significantly less sample mass in the test currently used for designing vertical stirred mills. The results of the proposed
6"×8" jar test showed a difference of only ± 2 μm in the
product d80, as compared to corresponding results obtained from tests carried out according to standard Metso8"×10" jar test. This can be explained as the two tests
conditions, for both 6"×8" and 8"×10" jars, have similarparameters, which includes same ball size, critical speed,
length to diameter ratio and power per volume unit. The
sample requirement of the proposed test is less than halfthat of the standard test. The sample requirement may be
reduced to one tenth of that required in the standard test if
the regrind of the same sample in the each grinding period procedure is adopted. The difference is quite significant especially in early development stages of a project.
In such situations the mass of available ore is small. Other
sample limitations include projects involving low-content
metallic ores, which require flotation tests to be carriedout at low mass recovery rates to generate enough regrinding mass feed. In both cases, the proposed test
method is an adequate alternative to assess the energy required by the regrinding process.

Acknowledgements
The authors wish to thank mineral processing teams of
Anglo American, Vale and Mosaic for their support, as
well as Professor Cícero Moraes from Polytechnic Schoolof Engineering—University of Sao Paulo, for his help in
the torque mill construction and implementation. They
also like to thanks the Technological Characterization
Laboratory of USP for the support in the Malvern analysis. This research was supported by FAPESP [grant no.

2015/11739-2] and CNPq [grant no. 308767/2016-0].

Nomenclature
kWb

Mill power per metric tonne of balls (kW/t)

Cs

Fraction of critical speed (%)

DMill diameter inside liners (m)d80

Diameter of 80 % passing sieve size (μm)

Vp

Fraction of mill volume loaded with balls (%)

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Authors’ Short Biographies
Mauricio Guimarães Bergerman
Dr. Mauricio Guimarães Bergerman graduated in Mining and Mineral Processing Engineering from The University of São Paulo (2003), obtaining his masters (2009) anddoctoral (2013) degrees at the same university. He has worked for seven years at Vale, at
the Sossego copper plant industrial operation, Pico iron ore processing plant, as well as
developing new copper ore projects in Brazil and Africa. He has worked four year as Assistant Professor at Alfenas Federal University and currently is Assistant Professor in the
Mining and Mineral Processing Engineering Department of The University of Sao
Paulo. His research is mainly focused on grinding, physical concentration, and mineralprocessing project development and optimization.

Homero Delboni
Dr. Homero Delboni, Junior graduated in Mining and Minerals Processing Engineering from the University of São Paulo. In 1989, he obtained a M.Eng. degree in Minerals
Engineering at the same university. He joined the Julius Kruttschnitt Mineral ResearchCentre of the University of Queensland, Australia, where he obtained his PhD degree in
1999. He is currently a Lecturer in the Department on Mining and Petroleum Engineering at the University of São Paulo, where he is involved in both teaching and research inmineral processing, particularly in comminution.

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Original Research Paper

Integrating Particle Microstructure, Surface and Mechanical
Characterization with Bulk Powder Processing †Rodolfo Pinal 1* and M. Teresa Carvajal 2
1
2

Department of Industrial and Physical Pharmacy, Purdue University, USA
Department of Agricultural and Biological Engineering, Purdue University, USA

Abstract
Multiple industrial applications, including pharmaceuticals, rely on the processing of powders. The current
powder characterization framework is fragmented into two general areas. One deals with understanding powders
from the standpoint of its constituting agents—particles. The other deals with understanding based on the bulk—
the collective behavior of particles. While complementary, the two aspects provide distinct pieces of information.
Whenever possible, experimental techniques should be used to predict powder behavior. However, it is equallyimportant to recognize that because of the natural complexity of powders, existing predictive approaches willcontinue to be of limited success for predicting the collective behavior of particles. This article discusses theunderstanding of powder properties from two perspectives. One is the effect of surface energy at the bulk level(large collections of particles), which controls interactions between powders. This aspect is most useful if studied
at the bulk-powder level, not at the single-particle level. Another perspective deals with the physico-mechanicalproperties of individual particles, responsible for the observed behavior of powders when subjected to mechanicalstress from unit operations such as milling. This aspect, which controls the failure mechanism of powders
subjected to milling, is most useful if assessed at the single-particle, not at the bulk level. Therefore, in order tofully understand, and eventually predict, or at least effectively model powder behavior, a good-judgement-based
combination of microscopic and bulk-level analytical methods is necessary.
Keywords: powder, particle, surface energetics, surface composition, nanoindentation, flowability

1. Introduction
Imagine trying to obtain a wide-angle panoramic image of a particular view, using a regular photographic
camera. The task requires multiple frames, where eachframe provides detailed information about a small segment of the whole picture. The panoramic image can thenbe obtained by “stitching” together the multiple frames
captured by the camera. One important consideration isthat in order to successfully stich the multiple frames into
a faithful representation of the panoramic view, it is also
necessary that each individual frame also exhibits somedegree of overlap with the neighboring images. The panoramic image example just described, is analogous to thatof the physical characterization of powders. Each analyticaltechnique utilized provides a “snapshot” of a particularattribute of the powder, and a fundamental understanding†

Received 18 June 2018; Accepted 1 August 2018
J-STAGE Advance published online 8 June 2019
1,2
West Lafayette, Indiana 47907, USA* Corresponding author: Rodolfo Pinal;
E-mail: rpinal@purdue.edu
TEL: +1-765-496-6247 FAX: +1-494-6545

about the properties and behavior of the material, or panoramic view, comes from integrating the information obtained from the multiple analytical techniques. The
wide-angle photograph notion provides a useful generalstarting point. However, for every analogy, there is always
a point at which it ceases to be applicable, and this is no
exception. One critical difference between the panoramic
image situation and the characterization of a powder material, is that constructing the panoramic view is a mono-­
dimensional task, whereas the physical characterizationof a powder material is a multi-dimensional one. In otherwords, in making the panoramic image, every single shot
carries the same type of (exclusively visual) information,
whereas in powder characterization, each single shotcounterpart (analytical technique) provides different type
(dimension) of information.
Handling and processing powders is an integral aspectin various industries, including pharmaceuticals, food andnutraceuticals, cement and ceramics, among others. This
report focuses on pharmaceutical and food applications.
However, the principles covered in the discussion presented here are not necessarily limited to these industry
segments, but should be valid for powders in general.

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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We often refer to the handling and processing of bulk
powders. At first, the term “bulk powder” is self-­
explanatory. However, it will become clear through thepresentation of this article, that a refinement of the term
“bulk” is necessary, in order to give proper context towhat is meant by powder characterization. Specifically, interms of the properties of interest and the instrumental
techniques utilized to make the corresponding measurements.
As stated in a recent publication (Hickey A., 2018), thecomplexity of pharmaceutical powders resides on theirvariety of physicochemical characteristics that impact
bulk requirements such as powder flow, agglomerationand dispersion. The similarity in complexity has the same
type of effect on food-relevant powders (Burgain J. et al.,2017; Kim E. et al., 2005; Thakur S. et al., 2013).
Powders consist of large collections of solid particles.
In subjecting a powder to the various analytical tests utilized for physical characterization, it is important to keep
track what aspect of the particles is being interrogated by
the analytical method used (Crowder T. and Hickey A.,
2000; Feeley J. et al., 1998; Hickey A. et al., 2003; Shi J.
et al., 2015).
Consider for example powder X-ray diffraction (PXRD)
and BET gas adsorption isotherm testing. These two
methods can be typically conducted on the same “bulk”
powder. However, each of these analytical methods
probes into (allowing us to look into) distinctly different
parts of the same powder sample. PXRD provides information regarding the arrangement of molecules making
Table 1the inner core of the powder particles, but it provides noinformation regarding the surface properties of the same
particles. The BET analysis on the other hand, provides
information about the surface ability to interact with thegas adsorbate, but reveals nothing about the inner core of
the particles. Needless to say, full physical characterization of powders requires understanding both surface- andcore-particle properties (Feeley J. et al., 1998; Ho R. et al.,2009; Otte A. and Carvajal T., 2011; Shi J. et al., 2015;
Willart J. et al., 2006). Accordingly, both sets of properties are equally important. However, the relative relevanceof surface- vs. (inner) core-particle properties depends on
the specific process under study or on the focus of thespecific investigation being carried out on powders. In thediscussion presented in this article, we make the distinction between “bulk-core” and “bulk-surface” properties.
Bulk-core properties are exemplified, without limitation,
by PXRD, while bulk-surface properties are exemplified(without limitation again) by BET gas adsorption analysis. The purpose of such differentiation is to be able todiscuss the properties of “bulk powders” without the encumbrance of ambiguity. Table 1 shows a partial list ofanalytical techniques commonly used in the physicalcharacterization of powders. The list includes the type ofsample interrogation (core vs. surface) provided by eachtechnique.
Despite a large body of published work on the subject(Begat P. et al., 2005; Khoo J. et al., 2011; Heng J. et al.,2006; Ho R. et al., 2011; Ho R. et al., 2009; Leturia M. etal., 2014; Roberts R and Rowe R., 1987; Shi J. et al.,Analytical methods frequently used for the physical characterization of powders.

Analytical Technique

Core-bulk
information

X-ray Powder Diffraction (PXRD)✓✓

BET Adsorption
Differential Scanning Calorimetry (DSC)✓

Infrared Spectroscopy (IR)✓✓Inverse Gas Chromatography (IGC)✓

Laser Diffraction
Water Uptake/Hygroscopicity

(1)

✓

✓

X-ray Photoelectron Spectroscopy (XPS)(3)

Near Infrared Spectroscopy (NIR)
(1)

✓
✓

SEM(2)
AFM/Nanoindentation

Surface-bulk
information

✓

✓

✓

 epending the mechanism of water uptake, adsorption or absorption, surface- orDcore- information is obtained.
(2)
Qualitative information about surface topography.
(3)Surface topography (physical and interactive). Nanoidentation provides mechanicalinformation pertaining to the core of the particle.

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2015), it is unfortunate that among industrial scientists involved in powder processing applications, the role andhence the importance of the surface properties of powders
does not occupy the prominent position it actually warrants. To put the situation in perspective, let us take thecase of nanoparticle systems for example. Even introductory-level knowledge on this subject makes it clear that at
the nanoscale level, surface properties become dominant
over core-particle properties. In fact, one of the tenets of
the nanoparticle filed, is that when the majority of themolecules in a solid sample are located at the surface instead of in the core of the particles, material properties
begin to operate in a different domain, i.e., in the nanoscaledomain. It is generally considered, that outside thenanoparticle domain, i.e., in the micro-scale or even macro-particle range, since the proportion of molecules occupying the surface is negligibly small compared to the
proportion occupying the core of the particles, the effectof surface molecules is not of major consequence. This
general notion is as incorrect as it is widespread. Actually,
independently of what percent of the total number of molecules of a powder sample is located at the surface, interaction among the particles in a powder are predominantly
controlled by surface properties. That is, when two particles encounter each other (Stewart P., 1986), their interaction is blind, so to speak, to the nature of their cores, but
entirely determined by the nature of their surfaces. Consider for example two sets of glass beads of equal diameter,with the difference that one set of beads is all solid glass,while the other consists of hollow beads filled with a different material, water for example. Even if water is themain component of the hollow beads, it will play no roleon the interaction (beyond that of density) among beadsof the same or different type. The interaction between
solid and water-filled beads will be entirely a manifestation of glass-with-glass surface encounters. If the surfacesof the two types of beads are equal, so will be their respective surface properties, and the result will be what isreferred to as ideal mixing, as further discussed below.

2. Surface characterization—Surface
energetics
The effects of milling on material properties has beenaddressed in terms of disruption of the crystalline structure, assessed by PXRD, and by studying thermal properties (Feng T. et al., 2008; Wildfong P. et al., 2006; Willart
J. and Descamps M., 2008; Willart J. et al., 2006). However, it is recognized that further research is needed on
this area. Consider the hypothetical situation where themilling of a crystalline powder results in particle size reduction but without any disruption of the crystal lattice.
Each crystalline structure is characterized by a series ofdiffraction planes. Depending on the strength of the intermolecular interactions between parallel layers of a specific plane, some planes are mechanically favored toward
providing openings for cleavage, leading in turn to crystal
fracture. Milling crystalline materials results in particle
size reduction by means of particle fracture. The fracture
pattern tends to follow the favorable cleavage openings
that are characteristic of the particular crystal structure.
For this reason, milling crystals results in more than justa general increase in exposed surface area. The mere increase in surface area produced by milling, bears an inherent change in the specific surface energy of the milled
powder. The fracture of crystal particles at cleavage
planes results in an increase in the abundance of exposedcleavage-plane surfaces, and the surface energy of such
surfaces is a function of cross-sectional exposure of functional groups located on the particular cleavage plane.
Studies on the surface energy of the crystal faces exposed
upon milling have been reported, giving a wealth of useful information (Chamarthy S. and Pinal R., 2008a,b;
Feeley J. et al., 1998; Ho R. et al., 2012; Otte A. et al.,2012; Planinsek O. et al., 2010). However, under the conditions of industrial applications of milling, particle size
reduction is almost invariably accompanied by disruptionof the crystal structure of the particles. Such crystal disruption is an unintended but inevitable “side effect” ofmilling. Moreover, in industrial applications of milling,
particle fracture patterns rarely, if ever, “abide” by exclusively breaking at the most favorable cleavage openings.
Independently of the particle fracture pattern during milling, particle size reduction is invariably accompanied byan increase in surface area.
One important consideration is that the milling-induced
surface area increase is inherently heterogeneous in termsof its energetic content. Thus, the following section discusses the usefulness of conducting surface properties
analysis using inverse gas chromatography (IGC) for
powder systems. This approach is more relevant to industrial applications, since it is not possible in practice tocontrol the fracture patterns of the particles, nor to prevent the disruption of the crystal structure during the process. Detailed reviews on the principles of IGC covering
pharmaceutical systems are available in the literature(Heng J. et al., 2006; Ho R. and Heng J., 2013).
As stated, particle-particle interactions in powders are
mediated by the surfaces involved. The surface energy ofthe particles in powders is a major factor on the attributesof powder blends. Consider the blending of two powdermaterials, 1 and 2. Let us assume that particles of the two
powders have different physicochemical properties but
similar particle size distribution. In this report, we follow
the common convention of using the term cohesion to refer
to attractive interaction among particles of the same material and the term adhesion to refer to attraction between

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particles of different materials. The work (energy) of cohesion, for each of the two components of the powder
mixture is given by the geometric mean rule:d = 2 γd  γd
W1,1
1
1

(1)

d = 2 γd  γd
W2,2
2
2

(2)

where Wd is the work of cohesion, γ d is the dispersive
component of the surface energy, and the subscripts denote powder component 1 and 2, respectively. Analogously, the work of adhesion is given by:
d = 2 γd  γd
W1,2
1
2

(3)

where the subscripts 1 and 2 denote the interaction between the two different powders, 1 and 2.
It is noteworthy that among dispersive, dipole and hydrogen bonding interactions, dispersive interactions are
the weakest, yet they often dominate over the other typesof (stronger) intermolecular interactions when it comes topowder mixing. The reason is that dispersive interactions
are non-directional; the only parameter at play for theiroperation is distance. The non-directionality of dispersiveinteractions is in fact the basis for the applicability of thegeometric mean rule. Dipolar interactions, and to a considerably greater extent hydrogen bonding interactions,
are highly directional, i.e., they require a precise molecular orientation in order to take effect. In liquid mixtures,
molecules are free to rotate and orient themselves, thus
readily satisfying the geometric requirements imposed byinter-dipole as well as donor-acceptor hydrogen bonding
interactions. For this reason, hydrogen bonding and dipolar interactions are dominant in liquid mixtures, rendering dispersive interactions comparatively inconsequential.
The situation is quite different in the solid state, where theinability of the molecules to freely orient themselves renders the orientation-dependent, specific interactions practically inconsequential, or at least non-dominant. The
result is that the non-specific (non-directional) dispersivetype of intermolecular interactions control inter-particle
interactions, and with that, they control powder mixing toa large extent.
The type of mixing and resulting blend between powders 1 and 2 depends on the overall energetic balance between cohesive and adhesive interactions. Ideal powder
mixing is observed whend  Wd  Wd
W1,2
1,1
2,2

(4)

That is, when the dispersive surface free energy of eachpowder, 1 and 2 alone (cohesion), as well as the particle-­particle interaction work resulting from the blend (adhesion), are all of similar magnitude. From a conceptual

198

Fig. 1

Ideal powder mixing. Near IR monitoring of the composition of a 50:50 lactose-tolmetin mixture as a function of blending time. Reprinted with permission from
Ref. (Ely D. et al., 2006). Copyright: (2006) Elsevier
B.V.

point of view, an ideal powder blend can be said to besymmetric, in the sense that swapping the positions of
any two particles of equal (or similar) surface area andsize in the blend can be done at (nearly) zero energy cost.
From a practical point of view, the symmetry of an ideal
blend manifests itself as a highly homogeneous mixture.
Fig. 1 shows an example of a nearly-ideal powder blend,
consisting of 50:50 (w/w) lactose and tolmetin, an anti-­
arthritis drug (Ely D. et al., 2006). Blend uniformity wasmonitored during blending using near infrared (NIR)
spectroscopy. Fig. 1 shows that the 50 % composition isreached very shortly after the start of mixing. Furthermore, the magnitude of the standard deviation also falls
very sharply right at the onset of mixing. The result is ahighly uniform powder blend, generated very quickly
and, most significant, stable to prolonged mixing. In relation to Equation 4, the Wd values determined using IGC
for lactose, tolmetin and the lactose-tolmetin mix are
100.1, 102.7 and 101.4 mJ·m–2, respectively (Ely D. et al.,2006). The closeness among these values indicates that
lactose-lactose, tolmetin-tolmetin and lactose-tolmetininteractions are all energetically nearly equivalent. Consequently, none of them is favored over another, leading
to symmetric mixing. The result is a random, highly uniform mixture.
Fig. 2 shows an example where the mismatch in surface energy between the components of a powder blend
leads to non-uniform mixing. That is, in a segregating
powder mixture. The experiment of Fig. 2 involves a
50:50 (w/w) mixture of two pharmaceutical excipients,
dextrose and Di-Tab (dicalcium phosphate). The experiment was carried out in the same way as that of Fig. 1(Ely D. et al., 2006). However, the results are quite different in each case. Fig. 2 shows that the dextrose-Di-Tab
mixture is highly segregated. Throughout the blendingtime, the Di-Tab concentration recorded is lower than its
actual content in the mixture. This result indicates that the
distribution of the components is highly non-uniform, withdextrose physically masking Di-Tab, hence interferingRodolfo Pinal et al. / KONA Powder and Particle Journal No. 37 (2020) 195–213

Fig. 2

Non-ideal (segregating) powder mixture. Near IR monitoring of the composition of a 50:50 dextrose-Di-Tab
mixture as a function of blending time. Reprinted withpermission from Ref. (Ely D. et al., 2006). Copyright:(2006) Elsevier B.V.

with its NIR signal. It should be pointed out that by itself, having one component of the powder mixture block
the NIR signal of the other is not necessarily a problem(non-random mixing). In fact, in some applications suchas the pulmonary delivery of pharmaceutical powders,
non-random powder mixtures are actively sought. Put invery simple terms, the goal in such type of mixtures is forthe particles of one of the powders (typically the active
pharmaceutical ingredient) to coat the surface of the particles of the other powder, which effectively functions as acarrier. This type of unsymmetrical powder mixtures are
sometimes referred to as ordered mixes (Staniforth J. et al.,1981a; Staniforth J. et al., 1981b). It is conceivable that in anordered mix of two powders, the coating particles would
partially mask the NIR signal of the carrier (coated component). However, an important characteristic of the so-calledordered mixes is that while being non-homogeneous at
the single-­particle level, the non-uniformity of the blend
as a whole exhibits a definite pattern. In other words, atrue ordered mix could show lower­-than-actual level of
one of the components (the coated one), similar to what isseen in Fig. 2. However, the profile of the (partially obstructed) signal would exhibit the flatness and smoothness
of Fig. 1. Most importantly, the standard deviation plot
should resemble that of Fig. 1 for an ordered mix to exist.
The fact that both the Di-Tab NIR signal in Fig. 2 does
not flatten with mixing time combined with the large andconstantly changing standard deviation indicate that dextrose and Di-Tab simple do not mix well, such that theblend is an unstable, segregating mixture without any
well-defined attribute for quality purposes. The significance of an unstable standard deviation of the blend isfurther discussed later in this report. The IGC-determined
Wd values for dextrose, Di-Tab and the dextrose-Di-Tab
mix are 63, 83.6 and 72.6 mJ·m–2, respectively. In practical terms, the mismatch in surface energies involved in
the mixture of Fig. 2 is indicative of a poor quality blend,
which would result in inconsistent performance if theblend were to be used, as obtained, in product development.

The concept of pharmaceutical quality, along with thedriving principles for safety and efficacy, are inextricably
connected to the ability to reproduce, i.e., to always produce a consistent product in all its properties and attributes.
Regulatory authorities recognize that raw materials usedin pharmaceutical manufacturing, many of which are supplied as powders, bear some degree of inherent variability(Yu L. et al., 2014). Such that in order to obtain a consistent product, it is necessary to adjust the manufacturing
process as needed, that is, to account for, and accommodate the observed variability among different lots orbatches of what is nominally considered the same raw
material. In this regard, the concept of sameness among
different lots a raw material used in pharmaceutical manufacturing plays a central role.
Sameness has two different connotations, one at the
raw material level, and one at the product level, althougheach leads to the same overall result. Sameness refers to
the actual match in properties and attributes among different lots of the same raw material, such that every lot
will function in precisely the same way when used inpharmaceutical processing.
Conversely, when different lots of the same raw material do not quite match each other, sameness is achievedby adjusting the process parameters accordingly, such thesame end-product is obtained with different lots of the
raw material. It is important to point out that in either
case, it is necessary to have a thorough understanding of
those specific functional attributes of the raw material
that are critical to the process outcome. A pernicious
problem often faced in pharmaceutical development, isthat despite being deemed as meeting the criteria forsameness (on the basis of physical characterization testing), different lots of the same raw material are found not
to function in the same way during processing.
An illustration of the importance of properly differentiating between core-bulk and surface-bulk properties in
the context of assessing lot-to-lot sameness (or variability)
is provided in a study involving soluble starch, a material
used as compressing aid (Chamarthy S. et al., 2009). A
starting sample of soluble starch was divided into two
portions. One portion was subjected only to sieving, in
preparation to using it to make compressed compacts. The
other portion was subjected to a washing process, drying
and subsequent sieving in order to de-agglomerate andmatch the particle size distribution of the unwashed portion. The two samples were subjected to a series of analytical tests involving the instrumental methods routinely
used for the physical characterization of powders. Resultsfrom different tests, each probing the core-bulk properties(PXRD under different humidity conditions, FTIR, true
density and hygroscopicity) gave the same results for thetwo powder samples. Even the BET-determined surface
areas where the same within 2 % for nitrogen gas and199

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within 10 % for water vapor for the two samples. Basedon the analytical results, the two portions (or “lots”) ofsoluble starch would typically be deemed as equivalent,i.e., as meeting the sameness criteria, thus making themsuitable substitutes for each other when used in pharmaceutical manufacturing. However, when actually used tomake compacts, the two samples did not produce equivalent compacts, under any of the processing conditions investigated. The washed portion of the starch produced
mechanically stronger compacts under all conditions ofapplied compression force, as well as under all equilibrium relative humidity conditions tested. It should bepointed out that the difference in mechanical strength between the two samples held even under the limiting conditions of zero porosity, based on Ryshkewitch analysis(Newton J. et al., 1993; Ryshkewitch E., 1953). Thismeans that the difference in mechanical properties was infact the result of different energy of interaction between
conjoined particles forming the compact and not the resultof differences in spatial distribution of the particles within
the compacted solid. Surface energy analysis revealed
that the washed portion of the starch powder was moreenergetic than the unwashed portion, in terms of both thepolar and dispersive components. However, the greatest
difference was observed in the dispersive surface energy
component, which as discussed above, is the dominantpart when it comes to solid inter-particle interactions. The
soluble starch study is a clear example of a situation commonly faced in pharmaceutical processing. Namely, one
where from an analytical point of view, two “lots” of a
raw material are the same, but they are never the same
when it comes to the functional/processing point of view.
The fact that the core-bulk testing methods gave essentially the same results for the two samples of soluble
starch is not surprising. After all, the chemical and physical composition of the material is minimally affected, if atall, by a simple washing process. Furthermore, the factthat the BET surface area, a classic surface-bulk analysis
technique, gave very similar results for the two samples,
offers a lesson worth bearing in mind: differences in surface energy of powders may be missed if based on the interaction with a single gas (or vapor) probe molecule, as itis the case with BET analysis. Dispersive surface energy
measured using IGC relies on a series of vapor probe molecules, not just one. In other words, surface energy analysis base on IGC carries a greater information content.
Milling powders is one of the most commonly used
unit operations in pharmaceutical processing. Even
though the single objective of milling is the reduction ofparticle size, the input of mechanical energy into the system invariably leads to unintended, hence uncontrolled
physical changes of the sample. Fig. 3 depicts the physicalchanges undergone by crystalline particles when the powder is subjected to milling. A portion of the mechanical200

Fig. 3 Mechanical activation of crystalline powders. A portionof the mechanical energy supplied during milling isstored in the material in the form of crystal defects
and/or amorphous content.

energy supplied during milling results in the fracture of
the particles, thus leading to the sought after particle size
reduction. Naturally, a significant portion of the energy
supplied is dissipated as heat. However, some of the energy
supply in milling is neither consumed toward particle
fracture nor dissipated as heat. There is a portion of themechanical energy that results in dislocations made to theorderly arrangement of the molecules in the crystal. Suchdislocations constitute crystal defects, depicted in the bottom left corner of Fig. 3. Continued supply of mechanicalenergy results in an increase in the concentration of dislocations within the crystal lattice. As the concentration of
crystal defects increases, it is possible to reach a threshold
defect-concentration value, such that the orderly molecular arrangement of the crystal becomes completely obliterated. This situation, often referred to as amorphization,
gives place to place to the amorphous form of the material, as depicted on the bottom right corner of Fig. 3. The
disruption of the crystalline structure of powders inducedby milling is termed powder activation. The particles in
activated powders are more energetic than the particles in
the original (unmilled) material. Powder activation is thus
a mechanism by which milled powders, through a change
in the arrangement of the molecules, are capable of storing a portion of the mechanical energy supplied during
the milling process. The mechanical activation of powders is both a core-bulk and a surface-bulk property, observable both in terms of surface interactions and innerparticle properties. It is important to point out that the depiction of mechanical activation in Fig. 3 is a rather simplistic one, but it correctly captures the general processes
at work.
There is a widespread misconception that prolonged
milling of powders will eventually lead, in general, to theamorphous form. That is not so. Whether or not continued

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milling (mechanical energy supplied) leads to the formation of the amorphous form depends on the properties of
the crystalline material itself. For example, the milling of
ketoconazole (an antifungal drug) first results in crystal
defects, while prolonged milling eventually leads tocomplete amorphization. Conversely, the milling of griseofulvin (another antifungal drug) invariably results inmechanical activation in the form of crystal defects, andno matter how long the milling time is extended, complete amorphization of griseofulvin is not achieved. On
the contrary, synchrotron source PXRD studies revealthat milling amorphous griseofulvin results in the formation of defect-­bearing crystals (Chamarthy S. and Pinal
R., 2008a; Feng T. et al., 2008; Otte A. et al., 2012).
As stated above, mechanical activation of powders directly affects both core-bulk and surface-bulk properties.
The importance of differentiation between core- andsurface-aspects is clearly illustrated by comparing theproperties of milled crystals with their corresponding
amorphous form. Fig. 4 shows the dispersive surface energy of griseofulvin and felodipine (a blood pressure lowering drug). Each graph shows the surface energy values
for the native (original, unmilled) crystal used as reference, as well as those of the milled crystals and of theamorphous form. From the core-bulk point of view, theenergy rank order for both drugs is necessarily amorphous > milled crystal > reference, and there cannot be
any dispute about that, since this is precisely the rank order of energy requirements to achieve full and partial disruption of the crystal structure, with the unmilled crystal
as baseline reference, in each case. However, it is noteworthy that from the point of view of the surface alone,
the energetic rank order is milled crystal > reference > amorphous. This may seem an anomalous result.
However, it would be anomalous if only core-bulk properties counted and surface properties were irrelevant, which
is never the case. Here we have a situation where the material with the highest core-bulk energy content is also theone with the lowest surface-bulk energy. The reason for

Fig. 4the most energetic core-bulk form, i.e., the amorphous,
exhibiting the lowest surface energy is attributable to thehigher degree of molecular mobility that is characteristicof the amorphous form, relative to its crystalline (either
native or milled) counterpart. Molecules at interfaces bear
an excess in free energy, relative to the molecules inside
the core. Any system will have a tendency to spontaneously minimize its surface energy. The question iswhether the driving potential is strong enough to overcome the kinetic threshold of the process. Molecules in
the amorphous state bear an excess amount of energy
equivalent to the heat of melting (save a heat capacity correction for liquefaction taking place below the melting
temperature), relative to the native crystal. In contrast,
dislocated molecules in a milled crystal bear only a fraction of the equivalent of the heat of melting. One important consideration is that molecules in the amorphous statealso have a high degree of mobility. Specifically, a degreeof mobility lacking in molecules confined in a crystalline
arrangement, including dislocated molecules, relative totheir reference position/orientation in the orderly crystal.
Consequently, molecules at the surface of the amorphous
form are more readily capable or rearranging themselvesin order to spontaneously minimize the overall surface
energy of the particle. Conversely, molecules occupying
surface dislocations in the crystal, remain wedged inplace without nearly the same ability to reorient themselves in order to reduce (minimize) energy of the particle
surface.
Putting aside the reasons for the higher surface energy
observed in milled crystals, it is important to consider the
potential impact in terms the practical aspects of powder
properties and performance. For example, the data in
Fig. 4 suggest that the powder of milled crystals may be,initially, more easily wetted than the amorphous powder.
Once wetted however, the amorphous powder will necessarily dissolve considerably faster. Further studies areneeded in order to compare the cohesive properties ofthe milled crystals with those of the amorphous powder.

Dispersive surface energy of three powders from a common source: Original crystal, milled crystal andamorphous powders of griseofulvin and felodipine.

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Especially considering that the high molecular mobility inthe amorphous form, responsible for its lowest relative
surface energy, will also tend to promote inter-particle
fusion. After all, inter-particle fusion provides a simple
mechanism for surface energy minimization, which is theultimate driving force. Conversely, in the absence of any
annealing (which typically requires elevated temperatures
or long inter-particle contact times), cohesion of particles
in the milled powder will be mostly controlled by dispersive surface interactions, with a comparatively minimal
effect from molecular mobility.
It is pertinent to consider the impact of the interrogation
scale of the analysis performed, on the type of information
obtainable regarding powder properties. The advancementof nanotechnology along with its associated analytical
tools, on multiple application fronts, has resulted in theability to study particle (including surface) properties atever higher levels of resolution. In parallel to these advances, the notion that the higher the level of resolution
on the analysis of particle surfaces provides the path toward complete understanding of the surface properties
and behavior of powders, has been gaining popularity.
Consider the hypothetical situation where the physicaland energetic properties of every constituent particle of apowder sample are perfectly uniform. Under such a scenario, the obtainable information would be essentially thesame, whether the analysis method used probed one
square meter or one square micron of surface. Accordingly, under this idealized situation, differences in bulk
powder properties between different lots of the same material will be primarily the result of differences in their
particle size distributions. In real systems however, surface heterogeneity is an inherent characteristic of powders, and the lack of surface homogeneity is precisely oneof the most important factors responsible for the observed
behavior of bulk powders.
Let us now consider two surface analysis methods on
opposite ends of the resolution spectrum. Before proceeding with this comparison, it is important to clearly differentiate between sensitivity and resolution. Atomic force
microscopy (AFM) and IGC are both highly sensitive
methods, in the sense that each gives distinctly different
readings based on differences among samples that may beundetected by other methods. However, AFM and IGC
have very different levels of resolution. AFM interrogatesvery small, localized sections of the surface, whereas IGC
interrogates very large, unconfined sections of the same
surface. As received, typical pharmaceutical powders oforganic materials have specific surface area in the orderof 1–3 m2·g–1. Accordingly, a typical IGC surface energy
analysis test provides information on powder surface areain the order of 1 m2. That is, IGC reports on a sample ofactual “bulk powder,” not simply on a collection of particles (the significance of this point is further discussed

202

below). AFM analysis generates images typically of theorder of 5 × 5 to 20 × 20 μm 2. Consider a hypotheticalpowder sample with a specific surface area of 2 m2·g–1
subjected to analysis using both IGC and AFM. Since
IGC is a non-destructive method, the analysis by bothmethods could conceivably be performed using the exact
same set of particles. AFM provides highly detailed information, including unambiguous quantification of themagnitude and distribution of energetic heterogeneity
present in the test specimen. This type of information has
a level of resolution that is inaccessible by other analyticalmethods. Precisely because the high resolution however,full assessment of the powder surface using AFM would
require collecting substantially more than 109 images. Alternatively, in order to reduce the number of collected
AFM images to a practicable number that is nonethelessstatistically representative, it would be necessary to know,a priori, the energy distribution of the surface from two
points of view: the range of the magnitude of the surface
energy, as well as the energy distribution across the powder surface, in order to select the appropriate physicallocations that give a representative sample. But these twopieces of information are, precisely, what the surface
analysis is meant to provide in the first place. The limitations of using IGC for surface analysis go in the opposite
direction. IGC provides surface energy values based on
probing the entirety of the sample, i.e., in the example
discussed here, the entirety of 2 m2 of surface in 1 g of
powder. The contrast between the capabilities of AFM
and IGC embodies their complementarity. AFM provides
exquisitely detailed information, capable of clearly differentiating between very small regions of surface in thesame powder, but it would make it a formidable task tounambiguously differentiate between different lots of thesame powder material. Conversely, IGC is exquisitely
suited to differentiate between lots of the same powdermaterial, but such a capability comes at the expense of not
being able to provide any information about the energetic
properties of specific regions in the sample. IGC provides
a characteristic surface energy value but it provides no information about surface energy in any particular region of
the sample.

2.1 Powder complexity
Particle engineering applications deal with controllingthe conditions of particle generation such that the attributes of the particles obtained can be made to meet specific (desirable) parameters. We should take into accountthat the end-product of the majority of particle engineering methods is a powder. One important question has to
do with the connection between particle properties andbulk powder properties, as discussed below.
There is wide agreement that powders exhibit complex

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behavior, so it is necessary to discuss the complexity of
powders, specifically, in connection to powder characterization by analytical methods. We must point out that theterm complexity has multiple connotations, spanningfrom lay usage to its informal and formal scientific use. In
this report, the term complexity (or Complexity) is usedin the context of emergent properties (or Emergent Properties) from the point of view of classical systems theory.
Physically speaking, we can say without ambiguity that
powders are solid materials. However, their dynamic
properties, especially those involved in energy dissipation, do not conform to the behavior of classical solids,
liquids or gases. Even when viewed as collections of multiple particles, powders stand apart from other multi-particle systems such as suspensions or dense gases (Jaeger
H. et al., 2000). The same is true when trying to treat the
dynamic properties of solids in the same way as those ofcontinuous systems. Compare for example the case of
mixing two liquids, with that of mixing two powders. In
the liquid, molecular thermal motions suffice to spontaneously reduce to zero, hence eliminating, all concentration gradients thus giving a homogeneous mixture. In a
powder mixture on the other hand, thermal motions are
essentially irrelevant, since external forces such as gravity dominate the behavior of the material. Furthermore,
for particles at or below a critical, material-dependentsize, electrostatic (coulombic) forces begin to compete
with, and at sufficiently small size, eventually dominate
over gravity. Consequently, the reduction of composition
gradients necessary to obtain a homogeneous powder
blend, requires the application of external energy, such asthat provided by tumbling or by the action of a propeller.
However, even when the energy supply requirement forgradient elimination is fully satisfied in each (liquid andsolid) mixture case, powder mixtures exhibit distinctly
different behavior. For example, thermal motions suffice
to prevent segregation of components in liquid mixtures.
In other words, thermal motions overcome any tendency
toward segregation resulting from differences in molecular dimensions or from differences in density (more appropr iately, par tial molar volu me) bet ween thecomponents in a liquid mixture. Conversely, in the case of
powder mixtures, density differences not only can havean effect, but depending on the magnitude of the difference, the same effect can actually operate in opposite directions (Oshitani J. et al., 2016). For this reason, thewidely used V-blender type, so frequently used to blend
pharmaceutical powders, often actually functions an effective particle separator (Jaeger H. et al., 2000).
Let us consider the powder mixtures presented in
Figs. 1 and 2 above. We can say that a tumble mixer isanalogous to a kaleidoscope toy. Namely, each rotation of
the tumbler gives place to one among an infinite numberof possible different physical combinatorial arrangementsof the particles. As stated above, the mixture represented
in Fig. 1 can be considered (energetically) symmetric. As
a result, once the blend reaches the pre-established 50 %content for each component, each subsequent tumblingrotation will give place to a different physical arrangement of the particles. However, because of its symmetricnature, all different physical arrangements created will beenergetically equivalent to each other, i.e., a different configuration of the same uniform blend.
The situation is different for the powder mixture represented in Fig. 2. The lower-than-nominal (50 %) composition detected indicates a non-uniform mixture throughout
the mixing process. Even more telling is the unstable
standard deviation value accompanying the fluctuating
composition. These unstable values are rather superficial
signs of the blend’s inability to reach equilibrium, either
as a homogeneous or as a non-homogeneous but orderedmix, despite the continuous influx of mechanical energy.
Therefore, the underlying issue here is one of energy dissipation. Energy dissipation is in fact the conduit responsible for bringing systems toward, or away from,equilibrium (Jaeger H. et al., 2000). These considerations
point to a fundamental difference between the behavior of
powder and liquid mixtures. In liquid mixtures, mechanical energy leads either to a uniform single-phase mixture(miscible components), or to two-phase system (partially
miscible components). In either case, the end result is adissipative system, i.e., at some point, any additional energy influx does not alter the composition of the mixture.
In contrast, some powder mixtures, like the one illustrated in Fig. 2, do not reach equilibrium or even a steadystate, despite continued energy influx.
Based on the above considerations, it is worth looking
into the cause and effect of uniform vs. non-uniform mixtures. We can say that the mixture of Fig. 1 is uniform
because it is energetically stable, while the opposite istrue for the mixture of Fig. 2. In a uniform powder mixture, continued influx of mechanical energy leads only tomultiple configurations of the same zero gradient blend.
The rest of the mechanical energy is very effectively dissipated as heat. In a unstable, hence non-uniform mixture,such as that of Fig. 2, the continued influx of mechanicalenergy does not have the same clean-cut partitioning. Energy dissipation is particularly different. In each reconfiguration of the collection of particles, a portion of theenergy supplied is chaotically absorbed and released, inthe form of segregation and desegregation of the powder
components, such that the mixture is never able to achieve
full desegregation (uniform mix), nor full segregation into
“two phases” (clean separation of the two powders). The
unstable mixing of Fig. 2 should not be confused with theterm “overmixing” often used in connection with lubrication using magnesium stearate (MgSt), for example. Optimal lubrication of powders with MgSt usually relies on203Rodolfo Pinal et al. / KONA Powder and Particle Journal No. 37 (2020) 195–213

stopping the mixing process at a point where only partial
coverage of the other powder has been achieved.
Generally speaking, powders are complex systems interms of their properties and behavior. However, the typeof complexity, or lack thereof, resides on the specificproperty in question and on the type of behavior it elicits
on the powder. According to classical systems theory, systems can be Simple, Complicated or Complex (Cotsaftis
M., 2009)—the uppercase notation on this first instance ismeant to reflect that, as used here, these terms carry specific meanings. Accordingly, a simple system is one where
each agent (particle in the case of powders) is weakly
coupled with other agents. That is, each particle operates
as an almost independent one-component subsystem. For
example, consider a powder for which the microscopic
characterization has been fully achieved down to thesingle-­particle level. Taking the mass of the powder as aproperty of interest, it is simply the summation of themass of every constituting particle. That is, the effect of
one particle is completely unperturbed by the action ofother particles.
A complicated system is one where the action of theconstituting agents (particles) are somewhat, although
weakly, coupled to the actions of other agents, but thesystem can still be decoupled for the most part. For example, for the hypothetical powder system described above,
for which every single particle has been catalogued, itwould be possible to predict the tapped density, with areasonable level of confidence. That is, the action of one
particle is somewhat perturbed by the action of other particles, but not to the extent of obliterating its effect on theproperty of interest.
A complex system is one where the action of one agent(particle) is strongly coupled to other agents. That is, thedynamics of the system are determined by the inter-agent
interactions, effectively placing a shield to the tracking ofother constituting agents. Consider once more the case ofa fully characterized powder at the microscopic level. No
extent of single-particle characterization, no matter how
exhaustive, would be able to lead to a prediction of theavalanching behavior of the powder. The avalanching behavior of a powder is neither the total nor partial combination of the avalanching properties of its constituting
particles. The avalanching phenomenon is a cooperative(powder) property, not a particle property. We can therefore say that avalanching is an example of an Emerging
Property in powders (Corning P., 2002). Emergent properties (or emergent phenomena) is one of the manifestationsof systems complexity. Emergence refers to properties or
behavior observable in arrangements of multi-agent systems but not present in the individual agents making up
the system (Corning P., 2002; Sitte R., 2009). The complex behavior of bulk powders is also observable in otherproperties. For example, the angle of repose (AOR) para­

204

meter, which has been widely used for decades, is an example of a deceptively simple, complex property. It is avery simple matter to experimentally measure the AOR.
However, the usefulness of the AOR is severely limited asa design, control or operating tool, because its value depends on a multitude of parameters (Wouters I. and Geldart
D., 1996). The AOR is another manifestation of complexity in powders; it is also an emergent property, and assuch, it is the result of many variables operating all at
once (Sitte R., 2009), some of which are not even traceable to the individual particles.
It is not surprising that efforts to predict powder properties have not been very successful for the most part. In
predicting fluidized bed behavior for example, it is often
assumed that particles behave independently from eachother in the bed. More specifically, the equations and correlations carry the assumption that interactions among
particles are exclusively collisional, and discrete elements
models (DEM) rarely capture particle clustering for example. The reason is that no mechanistic model exists yet(McMillan J. et al., 2013). Paradoxically, it seems that thevery strength of simulation models like DEM for example, i.e., their foundation on first-principles, is also at theroot of their limitations in predicting the complex behavior of powders.
Simulation models inherently (perhaps unavoidably)
bear the reductionist notion that a fundamental understanding of the properties and behavior of the different
parts of the system inevitably leads toward a thoroughunderstanding of the whole. This view is not necessarily
naive, but perhaps somewhat anachronistic. That is, alegacy from the reductionist hubris from the early 20th
Century and subsequent decades. Specifically, from theperiod when physics could arguably be considered as the
king of science. In the early 21st Century, it is biology thescience that arguably occupies the pinnacle placement. It
is impossible to describe the attributes of living entities
without deliberately counting on Complexity and Emergent Properties, since it involves a wealth of properties ofthe system that cannot be induced (predicted) from an understanding, even if thorough, of the constituting parts(Corning P., 2002). Accordingly, the last few decades haveproduced a resurgence in the study of complex systems
and emergent properties, extending beyond living systems, including physics (Cornacchio J., 1977; Corning P.,
2002).
Computer simulations of powder properties are firmly
based on first-principles. However, to the extent that theexisting set of first-principles remains incapable of predicting emergent properties, simulation-based descriptionof powder behavior will continue to be limited. For instance, an elegant example of a first-principles based sequential simulation of powder materials, starting withquantum mechanical modeling, followed by molecularRodolfo Pinal et al. / KONA Powder and Particle Journal No. 37 (2020) 195–213

mechanics simulation and subsequently DEM modeling,
was very successful in predicting density, but not nearlyas successful in predicting surface energy (Loh J. et al.,2013). We should point out that, like mass, density is theproperty of a simple or a complicated system (see definitions above). On the other hand, the surface energy of apowder is the property of a complex system. It is worth
noting that the complexity of a system is not a single
all-encompassing quality; a complex system is likely tohave different types of complexity, depending on theproperty under consideration (e.g., density vs. surface energy) (Sitte R., 2009). Moreover, it is unlikely that all
emergent effects play a role in every case (i.e., property
under consideration), or that one emergent force has thecontrolling effect in all cases (McMillan J. et al., 2013). It
appears that the notion of being able to predict bulk powder properties through computer simulations firmly basedon first-principles is by no means incorrect, it is rather incomplete.
Predicting emergent properties is, by definition, beyond
the reach of the current modeling paradigm. In addition to
the first-principles already in place, the successful simulation and prediction of emergent properties and behaviorof powders will require a set of second-principles. Moreappropriately put, there is a need for a second set offirst-principles for emergent properties, which as of today,
are not yet established. One can venture to say that no
amount of computing power or degree of refinement on
existing first-­principle-based equations, will suffice tofully describe the complex properties of bulk powders.
Today, the first-principles conundrum posed by Complexity is amply recognized across different segments of thescientific community, and significant advances towardelucidating those novel first-­principles that govern emergent properties are being made (Chen C. et al., 2009;
Galla T. and Guhne O., 2012).

2.2 Powder processing and surface properties
modification
Full prediction of powder properties is still in the future at this time, but correlations involving bulk powder
properties relevant to processing such as flowability,
blending and compactability have been reported usingbulk-surface energy measurements based on IGC. Thisapproach has been useful in explaining certain phenomena and behavior that typical analysis methods cannot
elucidate. The graphical insets in Table 2 show examples
where IGC-based surface energy analysis of various systems help understand performance and associated responses during processing. However, in order to ascertain
the presence of process-induced structural alterations,microscopic-level information, such as that provided by
AFM or SPM (scanning probe microscopy) are indeed

invaluable. The results show that a systematic characterization of milled molecular crystals provides fundamental
insight essential to potentially predict and control bulk
powder behavior.
A study on the surface of mannitol (Ho R. et al., 2010)
found agreement between surface energy values obtained
from contact angle measurements and those obtained
from IGC analysis. Furthermore, the study found that theheterogeneity of surface energy resides mainly on the polar groups populating the surface, such that surfaces
become more homogeneous when the polar groups arecapped with non-polar functional groups using silanization. It is important for the significance of this finding to
be clear. The heterogeneity of surface energy resides
mainly on the polar groups populating the surface. However, the effect of such heterogeneity is mainly manifested
through the dispersive (non-polar) component of the surface energy.
Table 3 lists powder materials that have been recently
studied in our laboratory. The list includes two basic materials, waxy corn starch and a food powder (not identified
for confidentiality reasons). Subjecting the basic materials
to different processes results in different powders, eachidentified on the first column of Table 3. The different
powder samples identified in the table have been subjected
to surface-property evaluation using different techniques,
including IGC, scanning electron microscopy (SEM), and
X-ray photoelectron spectroscopy (XPS). Subjecting thebasic materials to different processes gives place to different surface-modified powders in each case. The result of
surface modification is a change in powder properties, as
discussed below.
Fig. 5 shows the effect of exposing starch to enzymatic
reactions on the surface energy of the powder. One of theeffects of the enzymatic treatment of starch is the development of fine pores on the surface of the particles. Thereis also an increase in the surface energy of the treatedpowders, relative to the native (untreated) material. The
dispersive component surface energy values span from36.71 (native) to 43.34 mJ·m–2, with AMG < CGT < AML.
It is noteworthy that this magnitude of variation of thedispersive surface energy among the different starch powders, is of similar magnitude as the range found to result
in completely different compaction properties for soluble
starch (Chamarthy S. et al., 2009).
It is expected for powders in general, that the chemicalcomposition of the surface has a direct effect on surface
energy. It is further expected that the surface energy ofthe powder will have a strong effect on bulk properties
such as powder flow. The food powder material in Table 3
provides a clear example this type of chained relationship.
The chemical bond composition of the surface of thefive food powders produced by different processes wasdetermined using XPS. The XPS results are listed in

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Table 2

Examples of behavior tendencies of various powder systems in relation to their surface energy.
Surface energy of milled griseofulvin associated with defects(dislocations) showing dislocations have the highest surface
energy Chamarthy S. and Pinal R., 2008a.

Surface energy of milled dl-propranolol increases withdecreasing particle size. (Adapted from York P. et al., 1998).

Decrease in surface energy of woodpolyethylene composite
results in lower tensile strength (Adapted with permission from
Dominkovics Z. et al., 2007. Copyright: (2007) Elsevier B.V.).

Milling-induced amorphization of indomethacin monitored by
IGC (Reprinted with permission from Ref. Planinsek O. et al.,2010. Copyright (2010) Elsevier B.V.).

Table 4. It is noteworthy that even though the starting
material for making all five food powders is the same, thesurface abundance of different chemical bonds, including
the carbon/oxygen ratio, vary substantially among them.
These results indicate that besides being an inherent characteristic of bulk powders, surface variability in terms ofchemical composition can be substantial, depending on
the processing conditions chosen. Therefore, it is important not to confuse surface heterogeneity assessed from asingle particle (as done with microscopically-based methods), with surface heterogeneity assessed with bulk
powder-­based methods. The former provides a highly de-206

tailed, but a very small frame, of a truly large, multiframe “panoramic” picture.
The results of surface energy analysis using IGC for
the five food powders are listed in Table 5. The choice ofprocess employed to produce different powders from thesame starting material, results surface energy values thatspan from 31.2 to 43.3 mJ·m–2. Notice once again that themagnitude of this difference in surface energy is of theorder of that resulting in non-uniform mixing (see Fig. 2),
as well as that conducive to distinctly different compaction properties (Chamarthy S. et al., 2009). Based on the
spread of surface energy values among the different foodRodolfo Pinal et al. / KONA Powder and Particle Journal No. 37 (2020) 195–213

Table 3

Examples of surface modified powders.

Table 4

XPS surface bond composition.

Corn Starch–Enzymatically Modified
ID

Process

NTV

NativeAMG

Amyloglucosidase

AML

α-Amylase

CGT

Cycoldextrin glycosyltransferase

Food Powder–Different Processes

Chemical Bond Signal (%)
Sample
ID

C-C,
C-H

C-O

C=O,
O-C-O

COOH

C/O

SD1

39.8

42.6

13.7

3.8

2.08

SD2

58.4

31.2

6.0

4.3

3.49

SD3

41.1

42.2

12.7

3.9

2.16

FD

36.5

44.1

15.9

3.4

1.83

MRC

72.2

18.9

4.5

4.3

6.90

ID

ProcessSD1

Spray-dried

SD2

Spray-dried

Table 5 Surface energy of food powder samples at surface
coverage of 0.02 n/nm

SD3

Spray-dried

SampleFD1

Freeze-dried

Dispersive Surface Energy (mJ·m –2)
Mean ± s.d. n = 4

MRC

MilledSD1

31.4 ± 0.27

SD2

36.8 ± 0.57

SD3

31.2 ± 0.97

FD37.8 ± 1.58

MRC

43.3 ± 0.34

Fig. 5

Surface energy analysis at infinite dilution of starch
modified with different enzymes and corresponding
SEM microphotographs.

powder lots, as initial estimate, it would be reasonable toexpect different bulk powder properties among the differently processed food powders.
The practical applications of the type of information provided in Tables 4 and 5 is reflected in the bulk properties,
such as powder flow. The cohesiveness of the differently
processed food powder lots was investigated by its effecton the flow properties of the bulk powder. The avalanching energy was measured using a Revolution Powder Analyzer, RPA (Mercury Scientific Inc.) apparatus. Briefly,
RPA uses a low stress and dynamic avalanching tech-

Fig. 6

Effect of surface composition on powder flowability.

nique to determine the flow of the powder. The parameters determined on the RPA include the avalanche angle,
the avalanche time, and the avalanche energy. The avalanche energy is a measure of the energy generated byeach avalanche. The more cohesive, less flowing the powder, the greater the avalanche energy.
The results are graphically shown in Fig. 6. The figure
shows that there is a correlation between the C-C signal
from the surface of the powder obtained by XPS and thedispersive component of the surface energy. The figure
also shows a correlation between the dispersive free energy of the powder, which is attributable in part to the207Rodolfo Pinal et al. / KONA Powder and Particle Journal No. 37 (2020) 195–213

abundance of non-polar C-C bonds at the surface, and thetendency toward cohesiveness, or difficulty to flow of thepowder.
The example in Fig. 6 is of great practical significance.
It shows that subjecting the same starting material to thesame unit operation (e.g., spray-drying), makes it is possible to obtain a powder exhibiting easy flow, or one exhibiting difficult flow, or even one with borderline flow
behavior, all depending on the choice of process parameters.
The examples of Figs. 5 and 6, as well as the data fordispersive and composition on Tables 4 and 5, show theimportance of the surface chemistry of excipients andfood powders. Several reports on the effect of surface
composition on the flowability and the nature of cohesiveness of powders upon handling can be found in theliterature (Begat P. et al., 2005; Burgain J. et al., 2017;
Chamarthy S. et al., 2007; Heng J. et al., 2006; Kim E. etal., 2005; Leturia M. et al., 2014; Thakur S. et al., 2013).

3. Complementarity of bulk- and microscopic(mechanical)-based analysis methods
Microscopic-level techniques such as AFM or SPM andbulk-level techniques such as IGC are all high sensitivity
methods, although with very different scales of analysis(resolution). The two types of techniques are complementary toward the ability to fully understand powder properties and behavior. Each of the two types of analysis
methods provides different pieces of information, which
together make a fuller picture. AFM and SPM inform
about the individual agents (particles), while IGC informs
about the cooperative (emerging) properties from suchagents. It is important to point out that even though microscopic, single-­particle analysis methods make it apractically impossible task to ascertain surface heterogeneity at the bulk (m2) scale, it does not mean that suchmethods are unsuitable for assessing bulk properties ofpowders in general. On the contrary, based on single-­
particle analysis, microscopic techniques are uniquely
suited for informing about bulk behavior in processes
such as milling.
Powder materials are prevalent in various industrial
segments, and milling is equally almost ever-present as
the unit operation of choice for particle size reduction. An
important disadvantage is that as a rule, the milling process is difficult to control, making it almost impossible totell much in advance about the response of the powder as
its constituting particles undergo size reduction.
This section discusses a viable approach for probing
the mechanical response, such as plastic-elastic properties
and fracture phenomena of APIs (active pharmaceuticalingredients) molecular crystals, obtainable in advance to208

subjecting powders to unit operations that involve mechanical stress. The approach consists in using SPMbased nano- and micro-scale measurements, in order toestablish the likely macroscopic-scale behavior. This typeof single-particle approach provides the possibility of predicting particle size outcome with minimal crystal disruption, giving a level of confidence about the physicalchanges induced by milling without the need to conduct
run-and-stop milling tests in order to ascertain the desired
milling endpoint. The underlying concept is based on taking advantage of the ability to microscopically measure theinherent mechanical properties of the crystal. This information is then used to predict particle fracture behavior
during milling. The parameters obtained from this type of
testing provide a new perspective toward the fundamental
understanding of the complex bulk process of milling.
As mentioned earlier in this report, of the mechanicalenergy supplied during milling, a portion is consumed inparticle fracture, a portion is dissipated as heat, and another portion gets incorporated into the activated powder.
Activation, in turn, occurs both at the core-particle level,
as disruptions to the crystal lattice, and at the surface
level, as changes in the surface energy of the powder. The
preceding sections of this article focused primarily on thesurface activation effect. In this section, we focus on theenergy portion first named above. Specifically, on the way
microscopic analysis methods can provide specific information about particle fracture, and how this information
can help in predicting some bulk properties of the resulting powder.
The plastic-elastic properties of materials play a determining role on their behavior during milling. Plasticity incrystals results from activating multiple slip systems toaccommodate strains in multiple directions. In pharmaceutically relevant crystals, the chance of activating arather limited number of slip planes simultaneously, issignificantly greater than in the case of cubic unit cellsystems, common in easily deformed metals, for example.
Studies on succinic acid (Jing Y. et al., 2011) using
nanoindentation show the presence of a limited numbersof slip planes. A similar situation has been observed withother organic crystals, such as acetaminophen (Ho R. andHeng J., 2013). The abundance, or lack thereof, of slip
planes in the crystal is critical in determining whether
materials will deform plastically via slip, or if fracture
will occur. Creation of dislocations or defect-induced
amorphization (Ho R. and Heng J., 2013; Jing Y. et al.,2011) are possible with plastic deformation. Lower tendency toward amorphization is usually conducive to particle fracture. Particle fracture, in turn, may be either adesirable (micronizing) or undesirable (tableting) responseof a solid.
The mechanical properties profile curves for pharmaceuticals is similar to that obtained with ceramic andRodolfo Pinal et al. / KONA Powder and Particle Journal No. 37 (2020) 195–213

Fig. 7Force-displacement curves for caffeine crystals (FormI). Reprinted with permission from Ref. Ghosh et al.
2009. Copyright: (2009) American Chemical Society.

energetic materials (explosives), measured using nanoindentation (Taw M. et al., 2017). Plastic deformation inthese systems can be imparted during processing (millingand compaction), and the defect density subsequently influences properties such as hardness and elastic modulus,
as well as performance attributes (Nibur K. and Bahr D.,2003). A study on the deformation of a brittle molecular
crystal such as sucrose using nanoindentation, allowed
the identification of the onset of dislocation motion prior
to fracture (Ramos K. and Bahr D. 2007). This type ofexperiments showed promising results on the applicabilityof nanoindentation to quantify plasticity of pharmaceutical and food materials.
The crystal lattice of a solid is one of the dominant factors for controlling the response of the material to an applied stress. Nanoindentation allows mechanical testing ofsubmillimeter crystals, in order to determine the stressstrain-fracture behavior of solids. This allows to quantify
elastic, plastic, and fracture behavior tendencies. Nanoindentation is a technique that has been used to experimentally identify slip planes in inorganic materials like metals
and semiconductors (Bradby J. et al., 2001; Nibur K. andBahr D., 2003; Ramos K. et al., 2009; Stelmashenko N. etal., 1993).
Fig. 7 shows an example of force-displacement curves involving caffeine (Ghosh S. et al., 2013). The shift behavior
can be related directly to both slip and fracture events, andprovides insight into the way the competition between
these two phenomena, determine how brittle a molecular
crystal is.
The crack initiation threshold, subject to elastic/plastic
indentation has been reported from indentation studies inceramic materials (Lankford J. and Davidson D., 1979).
The strength of particles was calculated based on the interaction between crystal flaws, where flaws play a dominant role in particle fracture, and the local stresses are
significantly greater than the loading stress (Inglis C.,1913). During particle fractionation in a mill, particles are
first stressed, then cracks may propagate from preexistingflaws, leading to maximum the tensile stress (Wong R. etal., 2001). Following these reports, and recognizing thatin the pharmaceutical industry crystalline APIs are rarely
used without milling, de Vegt O. et al. (2009) studied theinfluence of flaws and crystal properties on particle fracture in a jet mill, using sodium chloride as model compound. It was concluded that impurities and pre-existingflaws in the crystals influence the fracture behavior ofparticles in a jet mill. Prediction of fracture behavior ofmolecular crystals has been proposed using the hardness
to stress ratio as criterion (Burch A. et al., 2017a). Organic
molecular crystals are more challenging; they exhibit
much less symmetry, are anisotropic and with very complex structures compared to those of many metallic or ceramic inorganic materials.
A study on the characterization of the mechanical properties of five pharmaceutical materials was conducted using a similar fracture mechanics approach to that applied
to ceramics and semi-brittle materials. The study was
performed using large size crystals, providing differentiating information between brittle and semi-brittle materials (Taylor L. et al., 2004). This type of information canbe used for cataloguing solids to be subjected to milling.
The study of mechanical deformation of molecular
crystals is often challenging because of their brittle or
ductile nature. Conventional methods of testing, including
microindentation of compacts or microindentation of single crystals, leads more often than not to fracture (Bradby
et al., 2001; Maughan et al., 2015). A further complicationis that growing large size (millimiter) crystals of many
pharmaceutical materials is difficult if not impossible.
More recently, a nanoindenter was used to test verysmall, submillimiter crystals, in the range of 50 to200 μm. With this approach, a wide variety of crystalline
solids can be examined, including those that are difficult
to grow into larger single crystals. Studies on the mechanical properties of griseofulvin (Maughan M. et al.,2015), idoxuridine and pentafluorobenzamimide (Burch
A. et al., 2017b) demonstrated that brittleness of pharmaceutical crystals can be determined by nanoindentation.
The technique allows testing with a variety of tip geometries and very high local stresses at ultra-low loads, making it possible to identify the nucleation of dislocations
and orientation dependent strength prior to fracture(Burch A. et al., 2017b; Maughan M. et al., 2015). Thus,
the nanoindentation technique has excellent potential as ameans for predicting the degree of size reduction upon
milling.
Force-displacement curves provide information on theplastic-elastic deformation of materials. Assessing fracture behavior, elastic and plastic properties of molecular
crystalline structures including pharmaceuticals, food209

Rodolfo Pinal et al. / KONA Powder and Particle Journal No. 37 (2020) 195–213

and some explosives are of interest due to the need ofunderstanding and controlling the range of behavior ofmaterials under mechanical stress. Clearly, the materials
from these industries have very different specific uses andpractical applications. However, all these crystalline materials share similarities in their molecular arrangements
and in their physical and mechanical responses. Actually,studies on energetic materials (explosives), often rely on
APIs used as “mocks” due to safety, handling and costconsiderations.
Table 6 and Fig. 8a show the force displacement similarities, and lack thereof, between two APIs and one explosive using a Berkovich indenter (Burch A. et al., 2017b).
The crystalline explosive cyclotetramethyl-enetetranitramine (HMX), and two crystalline APIs serving as inert“mock” materials, idoxuridine (IDX), and 2,3,4,5,6-penta-­
fluorobenzamide (PFBA), were used for comparison. It
was found that IDX served as a suitable inert “mock” material to study and simulate the properties of the explosive
HMX, whereas PFBA was not a suitable “mock” material.
Fig. 8b shows the unloading traces of IDX. At maximum load, the traces are superimposable, an indication thatthe sample did not crack (Burch A. et al., 2017b). Noticethat if cracking occurred, the degree of cracking, as wellas the distribution of cracks would need to be identicalbetween the two samples for their profiles to overlap

Table 6 Mechanical properties for HMX (explosive) and two“mock” APIs (n~20 indentations × 10 crystals per material).
*Material*H (GPa)*Er (GPa)

HMX

1.00 ± 0.11

25.2 ± 2.1

IDX1.00 ± 0.15

23.3 ± 2.2

PFBA0.25 ± 0.04

4.69 ± 1.43

* Reprinted with permission from Ref. Burch A. et al., 2017a(Morris, 2007).
An important aspect is that in the field of propellants,
explosive and pyrotechnic materials, pharmaceutical organic compounds are used as surrogates to understandtheir properties. Thus, the pharmaceutical field will clearly
benefit from the analysis methods developed in the highenergy materials field. It is now possible with these methods to study plastic-elastic deformation and to apply thisknowledge during formulation and process development.
Nanoindentation studies are promising for determining
the mechanical properties of materials that can in turn predict particle size output after milling or compaction behavior. Recent studies establish nanoindentation as a usefultechnique to measure mechanical properties (elastic-­
plastic properties and fracture behavior) of submillimeter
samples where traditional mechanical testing techniques
fail to meet the size or geometric requirements (Burch A.
et al., 2017a). The physical parameters at the single-­
particle level, or more precisely, at the single-plane of theparticle surface level, obtained using nanoindentation are
informative about the bulk powder level response of crystalline materials subjected to milling. An example of abulk property of powders that is better assessed using microscopic (non-bulk) analysis methods is the pulverization
factor, P, obtained from nanoindentation measurements(Zbib M., 2015). This parameter provides information on
the primary failure mechanism of the particles, i.e., comminution vs. cracking.

4. Conclusions
Structural differences in the arrangement of powders
and the state of agglomeration within a formulated powder
do not depend directly on the properties of the constituting particles. The behavior of large collections of particles
involve emergent properties, i.e., attributes that cannot be

Fig. 8a Force-displacement curves and Fig. 8b. Unloading profiles Reprinted with permission from Ref. Burch
A. et al., 2017a. Copyright 2017.

210

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directly traced back to the particles themselves, but originate as cooperative properties. Therefore, many criticalbulk properties of powders depend, to a very significant
degree, on the combined surface properties of collectionsof particles, which operate as a whole and for the mostpart, cannot be traced down to partial contributions fromindividual particles. In addition, environmental factors
and processing history, including manufacturing processes and storage conditions become encoded primarily,
although not exclusively, on the surface of the materials,
thus playing a dominant part on powder properties andperformance.
Processing conditions involved in milling, spray drying
and freeze drying invariably alter the surface of powdermaterials. The changes in surface involve variations on thetype of functional groups exposed at the surface. The direct
result of such variations is variations on surface energy
and consequently variations on cooperative interactions
that manifest themselves in bulk properties such as powder flow, compaction, wetting and blending properties.
Some but not all bulk properties of powders depend on
material characteristics and the size of the primary particles. Particle size reduction effects can be reliably related
to the properties of the constituting particles, especiallyusing nanoindentation techniques.
We have shown that the characterization of powders
needs to go beyond traditional physicochemical assessment. A combined assessment of bulk-surface and nano-­mechanical properties will be necessary in order to achievea through characterization mapping of the particle properties along with a robust understanding of their collective
behavior.

Acknowledgments
The authors acknowledge the work of Dr. Juan ManuelMartinez and Mr. Hector Lozano for the surface and bulk
characterization, and to Ms. Alexandra C. Burch for themechanical assessment. We also thank the Dane O.
Kildsig Center for Pharmaceutical Processing Research(CPPR) for technical support.

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Authors’ Short Biographies
Rodolfo Pinal
Dr. Pinal is Associate Professor of Industrial and Physical Pharmacy and Director of
the Dane O. Kildsig Center for Pharmaceutical Processing Research (CPPR) at Purdue
University. He obtained his PhD in Physical Pharmacy from the University of Arizona.
Before joining Purdue, Rodolfo worked for thirteen years in the pharmaceutical industry.
He was Research Leader at Hoffmann-La Roche, heading the Solid State Pharmaceutics/
characterization group. His research focuses on solubility and solubilization of drugs
from both the solid-state properties and solution chemistry perspectives. His research includes studies on excipient functionality and he is currently working on formulation
technologies for patient-centered medicine.
M. Teresa Carvajal
Dr. Carvajal is a Faculty Member at the Agricultural and Biological Engineering department at Purdue University. Prior to joining Purdue University, Dr. Carvajal worked
in the pharmaceutical industry for 13 years, Hoffmann-LaRoche (NJ) and Bayer (CT).
She obtained her Ph.D. in Powder Technology from the University of Bath, UK, M.S. in
Physical Pharmacy, a minor in Physical chemistry from the University of Arizona, USA
and B.S. in Chemical Pharmaceutical Biologist from the UNAM, México. Carvajal’s research approach is on surface-mechanical-processing relationships for understanding
bulk properties and impact on formulation development, processing and performance ofFood and Pharmaceutical powders.

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Original Research Paper

Preparation and Properties of Spherical Natural Rubber/Silica
Composite Powders via Spray Drying †Siah Ying Tang 1,2, Prachaya Sopanon 1, Wiwut Tanthapanichakoon 1,3
and Apinan Soottitantawat 1*
1

Center of Excellence in Particle and Materials Processing Technology, Department of Chemical Engineering,
Faculty of Engineering, Chulalongkorn University, Thailand
2
Advanced Engineering Platform, School of Engineering, Monash University Malaysia, Malaysia
3
Academy of Science, Royal Society of Thailand, Thailand

Abstract
In this work, composite powders of natural rubber/silica (NR-SiO2) were prepared via sol-gel and spray drying
method. The morphology and physical properties of resultant rubber composite powders were characterized byscanning electron microscopy with energy dispersive X-ray spectrometry, laser light scattering particle sizer andthermogravimetric analyzer. The results showed that spray-dried NR-SiO2 particles were spherical in shape withdiameter of less than 10 μm, with silica on the outer layer. The particle size was found to increase gradually with
the increase in NR/Si mass ratio. Marginal growth in particle size was observed with increasing feed flow rate.
Increasing inlet air temperature improved the latex particle encapsulation by silica layer while maintaining thefinal particle size. The mechanical properties of NR-SiO2 powders-filled polylactic acid (PLA) composite increase
gradually with the addition of dried particles of higher rubber content. However, the composite exhibited
relatively lower or reduced tensile strength and elongation at break compared to the host PLA polymer. This could
be attributed to poor filler dispersion associated with weak filler/matrix interaction effect occurring during meltcompounding process.
Keywords: natural rubber, silica, composite powder, spray drying, sol-gel

1. Introduction
Natural rubber (NR) is an important natural plant polymer that is widely applied in various industrial sectors
such as automobile, tires, aerospace, sports and consumer
products. In recent years, there is growing research interest towards the preparation of ultrafine NR powders(NRP) with better physical and mechanical properties.
NRP represents an attractive alternative to conventionalrubber sheets in some applications, especially as additives
or impact modifier. The use of fine NRP offers greater
convenience in use and transportation compared to rubber
sheets that require additional processing.
Numerous efforts have been made on the synthesis of

†
1
2
3

*

Received 2 April 2019; Accepted 3 June 2019
J-STAGE Advance published online 29 June 2019
Phayathai Road, Pathumwan, Bangkok 10330, Thailand
Jalan Lagoon Selatan, Bandar Sunway, 47500 Subang Jaya,
Selangor, Malaysia
Sanam Suapa, Dusit, Bangkok 10300, Thailand
Corresponding author: Apinan Soottitantawat;
E-mail: apinan.s@chula.ac.th
TEL: +66-8-8689-6226

214

dried rubber-based particles ranging from micrometer tonanometer scale. For instance, Thill A. et al. demonstrated that it is possible to prepare nanoporous composite
powder based on polybromostyrene and silica nanoparticles using ultrasonic spray system (Thill A. et al., 2005).
Sae-Oui et al. reported the preparation of rubber powders
via spray drying of pre-vulcanized NR followed by subsequent use as plastic additive in high-density polyethylene(HDPE) (Sae-Oui P. et al., 2010). Several powdered rubbers were successfully synthesized through gamma radiation crosslinking and spray drying of rubber lattices (Li D.
et al., 2007; Peng J. et al., 2002; Wang Q. et al., 2011). It
has been reported that the formation of nano-powderedrubbers is closely linked to the use of rubber latex withsuitable crosslinking degree (Li D. et al., 2007).
Instead of irradiation technology, Paiva et al. describeda methodology to produce composite spherical rubber
powder by the modification of styrene-butadiene latex
with methyl methacrylate and colloidal silica followed byspray drying (Paiva L.B.d. et al., 2014). Dried particulate
rubber with particle sizes of 1 μm to 10 μm were obtained. On the other hand, the preparation of spray driedstyrene-butadiene latex powder containing carbon

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Siah Ying Tang et al. / KONA Powder and Particle Journal No. 37 (2020) 214–223

nanotubes as reinforcing filler was demonstrated by Zhou
et al. and his co-workers (Zhou X. et al., 2006). The above
examples support the idea that spray drying is an attractive, yet efficient tool of producing dried rubber powders
with controllable size and morphology. Spray drying is infact a well-established technique used in pharmaceuticalsectors (Lee D.-J. et al., 2013; Okamoto H. et al., 2002;
Tong H.H.Y. et al., 2006). Although the rubber powders
can be obtained by irradiation or latex modification in aprior step to spray drying, the drawback associated withthese technologies are cost and safety problems.
Hence, we explored the possibility of producing composite rubber powder without the use of irradiation or
modifying agents. We reported a methodology of natural
rubber/silica (NR-SiO2) composite powder preparation by
spray drying a dispersion mixture containing silica soland rubber latex. Silica is chosen because it is a kind of
ceramic materials widely used in rubber reinforcement.
In this study, the dried silica-coated rubber particles wereformed via sol-gel reaction of siloxane on NR particles
during spray drying. The effect of NR to silica mass ratio,
spray-dryer feed rate and inlet air temperature on theproperties of NR-SiO2 powders was investigated. As partof study, the spray dried composite powders were melt-­
extruded and incorporated as filler into thermoplastic
polylactic acid (PLA) in order to evaluate their thermal
and mechanical properties. The findings of present study
offer a simple method to fabricate NR-based powders with
tailorable mechanical properties that may have useful application as impact modifier in chemical and plastic industries.

2. Materials and methods
2.1 Materials
Pre-vulcanized natural rubber latex with a total solid
content of 60 wt% was obtained from Thai Rubber Latex
Co. Ltd. Sodium silicate was procured from Fluka Chemicals, Germany. The host polymer in this study was polylactic acid (PLA) 2002D supplied by Nature Works, USA.
All other chemicals were of analytical grade.

2.2 Preparation of NR-SiO2 composite powders
The preparation of rubber composite powder was performed in 3 steps: (1) preparation of silica sol; (2) mixing
of NR latex with silica sol; (3) spray drying process. First,
silica sols were prepared by dispersing sodium silicate ina diluted aqueous solution of hydrochloric acid (HCI) at
50 °C for 5 min. The sodium silicate solution underwent
hydrolysis and polycondensation reactions to form silica
sols. Next, the as-prepared silica sols of 20 wt% silica

content were added to a diluted NR latex suspension andfollowed by sonication to constitute colloidal mixtureswith varying NR/Si mass ratios ranging from 0.25:1 to
10:1. Finally, dry NR-SiO2 powders were obtained by subjecting the mixture of silica sols and diluted NR to spraydrying (mini-spray dryer, Buchi 190 model, Switzerland)
at inlet air temperature of 160 °C and feed flow rate of
9 mL/min. The effect of feed rate and air inlet temperature on the final properties of resultant composite particles was also investigated.

2.3 Preparation of NR-SiO2 particles filled PLA
thermoplastic
The NR-SiO2 filled PLA specimens were prepared according to the following procedure. A fixed 5.0 wt% ofspray dried NR-SiO2 powder was first blended andmelt-compounded with PLA thermoplastic powder to obtain powdery mixture using a co-rotating twin screw extruder (LabTech LTE 20–40, LabTech Engineering Co.,
Ltd., Thailand) with temperature profile of 145–195 °C.
The extrudates were then compression-molded at pressureof 50 bar and temperature of 165 °C for mechanical properties investigation.

2.4 Characterizations
The as-synthesized rubber composite powders werecharacterized in terms of particle size distribution, morphology, thermal stability and elemental composition.
Particle size distribution was measured with laser diffraction analyzer (Mastersizer 2000, Malvern, UK). Prior to
the size measurement, the NR-SiO2 powder was dispersed
in distilled water under sonication to obtain a homogeneous suspension without particle agglomeration. The
morphological observation and elemental analysis ofspray dried NR-SiO2 particles were performed using
scanning electron microscopy with energy dispersive
X-ray spectrometer (SEM-EDX, JSM-6400, JEOL Ltd.,Tokyo, Japan). The weight loss measurement of silica(control) and spray dried NR-SiO2 particles was carriedout in nitrogen gas with a thermogravimetric analyzer(TGA/DSC1, Mettler Toledo, Thailand).
The mechanical properties of the NR-SiO2 particles
filled PLA specimens were investigated using an electromechanical tensile tester (INSTRON 4206 universal testing machine, USA) in accordance with ASTM D256 and
ASTM D638 Type 1.

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3 Results and discussions
3.1 Characterization of NR-SiO2 composite
powders
3.1.1 Particle size distribution of NR-SiO2 powders

causing latex-latex interparticle coalescence and agglomeration during drying process. It is worth mentioning thatfurther increasing NR/Si mass ratio to 10:1 contributed toa more severe particle agglomeration, resulting in larger
mean particle diameter as shown in Fig. 1(b).

Fig. 1 shows the particle size distributions and mean
particle diameters of rubber composite powders preparedat different NR/Si mass ratios. As shown in Fig. 1(a),there was no obvious change in the size distribution observed at the 3 lowest NR/Si ratios. The composite particles obtained at mass ratios of 0.25:1, 0.5:1, and 1:1 hadvery similar narrow size distributions with mean diameters centered at ~0.6 μm (Fig. 1(b)). The size distribution
curves became significantly broader and shifted to thebigger particle size region with further increase of NR/Si
mass ratio from 2:1 (Fig. 1(a)). This observation could be
attributed to the formation of a layer of silica around the
NR latex particles. When the NR/Si mass ratio is smalleror equal to unity, the silica interacts well with rubber particles through cohesive forces to form a network in thesuspensions, leading to crust formation after spray drying. However, when the value of this ratio reach 2:1 or silica amount is insufficiently lower than NR content, theparticles tend to form this network in an aggregated form,

3.1.2 Morphology of NR-SiO2 powders

Fig. 1

Fig. 2

216(a) Particle size distribution and (b) mean particle diameter of NR-SiO2 powders prepared at different NR/
Si mass ratios. Reproduced by permission from
Prachaya S. (2011).

It is well known that particle shape has a strong influence on the flow characteristics of powders (Ogata K.,
2019; Talako T. et al., 2009). The morphology of spraydried rubber composite particles was characterized by
SEM and the micrographs of the samples are presented inFig. 2. As shown in Fig. 2(a–f), all spray dried NR-SiO2
particles were almost spherical in shape. However, large
agglomerates were observed at higher NR/Si mass ratios.
This observation substantiated our earlier findings onparticle size measurement. The higher the NR/Si mass ratio, the more frequent the particles were aggregated insome regions. When a sufficiently high amount of silica
was present, most of the rubber composite materials appeared as individual spherical particles (Fig. 2(a–b)).
When silica content was significantly reduced, the drying
process results in the formation of agglomerated clusters,
as evidenced in Fig. 2(f). It is clear that the composite
particles aggregate greatly when there is insufficient silica
to coat or encapsulate the rubber particle surface.

SEM micrographs of NR-SiO2 powders prepared at different NR/Si mass ratios: (a) 0.25:1, (b) 0.5:1, (c) 1:1, (d)2:1, (e) 6:1, and (f) 10:1, respectively. Magnification 5
kx. Reproduced by permission from Prachaya S. (2011).

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3.1.3 Elemental composition of NR-SiO2 powders

The results of elemental sample analysis by EDX arepresented in Table 1. The relative amount of silicon was
decreased as the NR/Si mass ratio was increased. The results indicated that the amount of silica in the form of
SiO2 available for rubber particle encapsulation became
insufficient at higher mass ratios. For NR/Si mass ratio of
0.25:1 and 0.5:1, the elemental ratio of C/Si was lower
than 1 and most of the NR particles are sufficiently encapsulated within the silica shell. As expected, the elemental
ratio of C/Si increased as the mass ratio rose from 0.25:1
to 6:1. In this case, the amount of silica required for coating rubber particles decreases significantly, leading tomore particle aggregation as a result of insufficient surface coverage. It was considered that a plateau of silica
encapsulation extent was reached at NR/Si mass ratio of
8:1, as evidenced by the essentially constant elemental ratio of C/Si.

3.1.4 Thermal stability of NR-SiO2 powders

The TGA curves of spray dried NR-SiO2 powders areshown in Fig. 3. All spray dried samples prepared at
different NR/Si mass ratios showed a similar thermal deg-

Fig. 3

TGA curves of NR-SiO2 powders prepared at different
NR/Si mass ratios. Reproduced by permission from
Prachaya S. (2011).

Table 1Elemental composition of NR-SiO2 powders preparedat different NR/Si mass ratios.

NR/Si mass
ratio

% Element
C

Si

O

Na

0.25:1

13.14

28.11

44.77

13.98

0.47

0.5:1

17.29

24.00

45.38

13.33

0.72

1:1

29.47

18.07

42.39

10.07

1.63

2:1

56.10

9.28

29.03

5.59

6.04

4:1

65.27

5.38

25.49

3.40

12.13

6:1

71.33

5.14

20.39

2.78

13.88

8:1

75.58

3.53

18.64

1.99

10:1

76.36

3.59

17.45

2.29

radation trend. There was an apparent thermal decomposition step for NR macromolecular chains. The onset
temperature of decomposition with pronounced weightloss was observed in the range of 220 °C to 240 °C. When
more silica was incorporated into the rubber composite
matrix, the main decomposition profile gradually shiftedto a higher temperature. This indicated that the spraydried composite powder gradually possessed a more complex thermo-oxidative decomposition associated with noticeable improvement of thermal ageing resistance.
Similar observations were reported in the literature (Paiva
L. B. d. et al., 2014; Peng Z. et al., 2007; Sen D. et al.,2006). The thermal stability of as-prepared composite
powders was greatly governed by the effective silica coating of rubber particles.

3.1.5 Effect of feed rate

The effect of feed flow rate to the spray dryer on the
NR-SiO2 powder properties was determined. Fig. 4 andTable 2 show the effect on the particle size distribution
and mean particle diameter of NR-SiO2 powders preparedat fixed NR/Si mass ratio of 2:1 and constant inlet air temperature of 160 °C. The results showed that increasing thefeed flow rate produced a mild gradual increase in powder
particle size. By increasing the feed rate, more latex composite dispersion was introduced and atomized during
spraying, thus resulting in larger liquid droplets and inducing more collisions and subsequent fusion of small
particles into larger ones, as shown in Fig. 5. The thin uneven silica coating and uncoated NR surface can, respectively, be distinguished by looking at the distribution of Si

C/Si ratio
Fig. 4

Particle size distribution of NR-SiO2 powders preparedat a different feed rates. Reproduced by permission
from Prachaya S. (2011).

Table 2

Mean particle diameter (μm) of NR-SiO2 powders at adifferent feed rates.
Feed rate (mL/min)

21.41

NR/Si mass
ratio

7

9

11

13

21.27

2:1

6.93

7.65

8.15

8.28

Reproduced by permission from Prachaya S. (2011).

Reproduced by permission from Prachaya S. (2011).

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Siah Ying Tang et al. / KONA Powder and Particle Journal No. 37 (2020) 214–223(see the tiny bright spots in Fig. 6(b), (e), (h) and (k)) andC elements (see the tiny bright spots in Fig. 6(c), (f), (i)and (l)). The composite particles prepared at a lower feed
rate showed higher coverage of latex particles with silica,

Fig. 5

SEM micrographs of NR-SiO2 powders prepared at adifferent feed rates: (a) 7 mL/min, (b) 9 mL/min, (c)11 mL/min, and (d) 13 mL/min, respectively. Magnification 5 kx. Reproduced by permission from Prachaya
S. (2011).

Fig. 6218

possibly due to the increasing rate of heat transfer(Reineccius G.A., 2001).

3.1.6 Effect of inlet air temperature

Fig. 7 and Table 3 show the effect of different inlet air
temperature on particle size distribution and mean particle diameter of composite particles prepared at fixed NR/
Si mass ratio of 2:1 and constant feed rate of 9 mL/min. It
can be seen that increasing the inlet air temperature resulted in negligible changes in the particle size. As shownin Fig. 8, though the powder showed fractured particle
surface with cracks or fissures, an increase in inlet air
temperature produced more nearly smooth and hard particles. This is mainly due to fact that the increase in drying
air temperature provided greater driving force for moisture evaporation, causing rapid drying and formationof rigid outer layer over rubber particles (Fig. 9(g))(Alamilla-Beltrán L. et al., 2005; Finney J. et al., 2002). A
relatively high drying temperature can accelerate both thehydrolysis and condensation processes of silanol groups,
leading to higher conversion of silica sols into gelled particles (Wang S. et al., 2015). As a consequence, higher air
inlet temperature favored the formation of more smooth
and uniform layer of silica particles, as evidenced by thepresence of high density of Si elements shown in Fig. 9(h)SEM micrographs and EDS elemental X-ray maps showing silicon and carbon distribution within
NR-SiO2 powders prepared at different feed rates: (a–c) 7 mL/min, (d–f) 9 mL/min, (g–i) 11 mL/min,and (j–l) 13 mL/min respectively. Reproduced by permission from Prachaya S. (2011).

Siah Ying Tang et al. / KONA Powder and Particle Journal No. 37 (2020) 214–223

and (k). On the basis of obtained data, the optimum spray
conditions for preparation of spherical rubber powders

Fig. 7

Particle size distribution of NR-SiO2 powders preparedat different inlet air temperatures. Reproduced by permission from Prachaya S. (2011).

Table 3

Mean particle diameter (μm) of NR-SiO2 powders at
different inlet air temperatures.

NR/Si massratio

Inlet air temperature (°C)
120

140

160

180

2:1

7.53

7.66

7.65

7.68

Fig. 9containing fixed NR/Si mass ratio of 2:1 were determined
as inlet air temperature of 160 °C and feed flow rate of
9 mL/min and therefore used in the subsequent study reported above.

Fig. 8

SEM micrographs of NR-SiO2 powders prepared at different inlet air temperatures: (a) 120 °C, (b) 140 °C, (c)160 °C, and (d) 180 °C, respectively. Magnification 6
kx. Reproduced by permission from Prachaya S. (2011).

SEM micrographs and EDS elemental X-ray maps showing silicon and carbon distribution within NR-SiO2 powders prepared at different inlet air temperatures: (a–c) 120 °C, (d–f) 140 °C, (g–i) 160 °C and (j–l) 180 °C respectively. Reproduced by permission from Prachaya S. (2011).

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Siah Ying Tang et al. / KONA Powder and Particle Journal No. 37 (2020) 214–223

3.2 Characterization of NR-SiO2/PLA composite
3.2.1 Morphology of NR-SiO2/PLA composite

SEM images of NR-SiO2/PLA composite containing
5.0 wt% spray dried rubber powders as filler and prepared
via melt compounding process are illustrated in Fig. 10.
Based on Fig. 10(b–d), the NR-SiO2-loaded PLA composite showed a wrinkled and crumpled layer structure,possibly due to the strong filler-filler or particle-particle
interactions resulting from fairly high mass ratio of NR tosilica. When the amount of latex was more than that ofsilica layer, the rubber particles were not sufficiently covered by silica layer and thus agglomerated rapidly, leading
to poor adhesion to and poor dispersion in polymer matrix. Individual NR-SiO2 particles could be observed in
the composite containing rubber powder of higher NR/Si
mass ratio, as evidenced in Fig. 10(d). In comparison,neat PLA exhibited little or no wrinkled appearance witha relatively homogeneous smooth surface. This morphological observation suggested that a better dispersion ofrubber fillers in the polymer matrix was essential to yieldan uniform NR-SiO2/PLA composites.

3.2.2 Thermal and mechanical properties of NRSiO2/PLA composite

The DSC curves of NR-SiO2/PLA composite and PLA
polymer are presented in Fig. 11. The results showed that
there is no significant variation of glass transition temperature (Tg ~ 62 °C) and melting temperature (Tm ~160 °C) of all investigated composite specimens and neat
PLA. The small variation (< 1 °C) could be primarily due
to the restriction in the polymer chain mobility caused by
the interaction between the powder filler and PLA matrix(De Falco A. et al., 2007; Paiva L.B.d. et al., 2014).
Table 4 summarizes the tensile strength, elongation atbreak and impact strength as a function of NR/Si mass
ratio and spray drying conditions. Based on Table 4, one
can observe that all the investigated mechanical properties exhibited a similar trend in which the addition ofdried NR-SiO2 powders led to an increase in the tensile
strength and elongation at break as well as the impact
strength values. However, all NR-SiO2 powder-filled PLA
specimens showed lower or reduced tensile strength andelongation at break than neat PLA, which reflected thepoor dispersion and high agglomeration of filler particles
within PLA matrix. This could be mainly ascribed to thepresence of wrinkled surface as evidenced in Fig. 10 andthus uneven residual stress distribution in the composite
material. The wrinkled or crumpled morphology resulting
from structural defects was caused by poor filler dispersion accompanied by weak filler/matrix interaction effectoccurring during melt-compounding process. Similar observations on the effect of wrinkles on tensile properties
and fracture stress were reported by Min et al. and Papageorgio et al. (Min K. et al., 2011; Papageorgiou D.G. etal., 2017). Furthermore, it was reported that good dispersion control and the interaction between polymer-particle
filler play a vital role in transferring properties from filler

Fig. 10 SEM micrographs of NR-SiO2/PLA composite containing 5.0 wt% spray dried rubber powder preparedat different NR/Si mass ratios: (a) PLA (control), (b) 0.5:1, (c) 1:1, and (d) 2:1. Magnification 1 kx. Reproduced by permission from Prachaya S. (2011).

220

Siah Ying Tang et al. / KONA Powder and Particle Journal No. 37 (2020) 214–223

associated with poor filler-matrix interaction decreased
the composite’s mechanical strength; therefore, themelt-compounding process needs to be improved.

Acknowledgements
This scientific work was financially supported by theCentennial Fund of Chulalongkorn University.

References
Fig. 11 DSC curves of NR-SiO2/PLA composite containing
5.0 wt% spray dried rubber powders prepared at different NR/Si mass ratios. Reproduced by permission
from Prachaya S. (2011).
Table 4

Mechanical properties of NR-SiO2/PLA composite
containing 5.0 wt% spray dried rubber powders prepared at different NR/Si mass ratios.

NR/Si massratio

Tensilestrength(MPa)Elongation atbreak (%)

Impactstrength (J/m)

0.5:1

13.3 ± 3.8

0.98 ± 0.1

47.5 ± 3.5

1:1

18.5 ± 4.2

1.18 ± 0.3

51.7 ± 7.4

2:1

24.2 ± 2.7

1.49 ± 0.2

55.3 ± 5.6

PLA45.1 ± 3.0

2.75 ± 0.1

48.9 ± 0.0

Reproduced by permission from Prachaya S. (2011).

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4. Conclusions
In this study, we demonstrated a simple preparation of
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showed that the rubber particle size increased graduallywith the increment of NR/Si mass ratio. Increasing feedflow rate induced the fusion of small particles with marginal increase in particle size. It was found that a low feed
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Authors’ Short Biographies
Patrick Tang Siah Ying
Dr. Patrick Tang Siah Ying is a Senior Lecturer at School of Engineering, Monash
University Malaysia. He received his BEng degree in Chemical Engineering from University of Malaya, Malaysia in 2008. He obtained his PhD degree in Chemical Engineering from The University of Nottingham in 2012. Between 2012–2014, he was as an
Assistant Professor at University of Tunku Abdul Rahman (UTAR). In 2019, he did collaboration research in Center of Excellence in Particle and Materials Processing Technology supported by Centennial Fund of Chulalongkorn University. His current research
focuses on micro/nano-encapsulation, cellulosic nanocomposite and cavitation technology.

Prachaya Sopanon
Prachaya Sopanon graduated from Center of Excellence in Particle and Materials Processing Technology under supervision of Assistant Prof. Apinan Soottitantawat. He received his BEng and MEng degree in Chemical Engineering from Chulalongkorn
University in 2010 and 2012, respectively. He is now working as process engineer in
Chevron Thailand Exploration and Production, Ltd.

Wiwut Tanthapanichakoon
Professor Wiwut Tanthapanichakoon is a Technology Adviser at SCG Chemicals Co.
Ltd. in Thailand, Fellow of Academy of Science, Royal Society of Thailand, andEmeritus Professor of Tokyo Institute of Technology in Japan and also Chulalongkorn
University in Thailand. He was the founding Executive Director of the National Nanotechnology Center at the National Science and Technology Development Agency inThailand. He holds a BEng degree in Chemical Engineering from Kyoto University inJapan, and a PhD degree in Chemical Engineering from The University of Texas atAustin. His current research focuses on particle technology, process analysis and simulation, and reaction engineering.

Apinan Soottitantawat
Assistant Prof. Apinan Soottitantawat is Head of Center of Excellent in Particle andMaterials Processing Technology, Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University. He received his BEng degree in Chemical Engineering from Chulalongkorn University, Thailand in 1998. He obtained his DEng degreein Molecular and Biochemical Engineering from Tottori University, Japan in 2005. He
was researcher at National Institute of Advanced Industrial Science and Technology(AIST), Japan and National Science and Technology Development Agency (NSTDA),
Thailand. His current research focuses on particle technology, encapsulation technology
and chemical process scale-up.

223

KONA Powder and Particle Journal No. 37 (2020) 224–232/Doi:10.14356/kona.2020011

Original Research Paper

Synthesis of Precision Gold Nanoparticles Using
Turkevich Method †Jiaqi Dong 1, Paul L. Carpinone 1, Georgios Pyrgiotakis 2,
Philip Demokritou 2 and Brij M. Moudgil 1*
1
2

Center for Particulate and Surfactant Systems, Department of Materials Science and Engineering, University of Florida, USA
HSPH-NIEHS Nanosafety Center, School of Public Health, Harvard University, USA

Abstract
Gold nanoparticles (AuNPs) exhibit unique size-dependent physiochemical properties that make them attractive
for a wide range of applications. However, the large-scale availability of precision AuNPs has been minimal. Not
only must the required nanoparticles be of precise size and morphology, but they must also be of exceedingly
narrow size distribution to yield accurate and reliable performance. The present study aims to synthesize
precision AuNPs and to assess the advantages and limitations of the Turkevich method—one of the common
chemical synthesis technique. Colloidal AuNPs from 15 nm to 50 nm in diameter were synthesized using theTurkevich method. The effect of the molar ratio of the reagent mixture (trisodium citrate to gold chloride), thescaled-up batch size, the initial gold chloride concentration, and the reaction temperature was studied. The
morphology, optical property, surface chemistry, and chemical composition of AuNPs were thoroughly
characterized. It was determined that the as-synthesized AuNPs between 15 nm and 30 nm exhibit well-definedsize and shape, and narrow size distribution (PDI < 0.20). However, the AuNPs became more polydispersed andless spherical in shape as the particle size increased.
Keywords: gold nanoparticles, nanomaterials, Turkevich Method, synthesis, characterization

1. Introduction
Gold nanoparticle (AuNP) is one of the most extensively studied engineered nanomaterials (ENMs). The
original work of AuNP synthesis can be traced back to1940 when the formation of colloidal gold upon reacting
gold chloride (HAuCl4) and trisodium citrate (Na3C6H5O7
or NaCt) was first reported (Hauser E.A. and Lynn J.E.,
1940). The detailed work of Turkevich and his coworkers(Turkevich J. et al., 1951) has become one of the milestones of AuNPs synthesis. Since then, the synthesis
method has been modified and improved (Frens G., 1973)
for a diverse area of interests including the developmentof chemical sensors for water quality analysis using surface enhanced Raman spectroscopy (SERS) (Tian F. et al.,2014), surface-induced catalytic activities (Lopez N. et al.,
2004; Xie W. et al., 2012), drug delivery in biological systems (Ghosh P. et al., 2008; Saallah S. and Lenggoro I.W.,
†
1
2

*

Received 25 April 2019; Accepted 6 June 2019
J-STAGE Advance published online 24 August 2019Gainesville, FL 32611, United States
Boston, MA, 02115, United States
Corresponding author: Brij M. Moudgil;
E-mail: bmoudgil@perc.ufl.edu;
TEL: +1-352-846-1197

2242018) and nano-toxicology studies (Beltran-Huarac J. etal., 2018; Somasundaran P. et al., 2010; Grobmyer S.R.
and Moudgil B.M., 2010; Pyrgiotakis G. et al., 2018). The
reason that AuNPs are attractive to a wide variety of applications is because of the surface plasmon resonance(SPR), a size- and shape-dependent property (Haiss W. etal., 2007) and their biocompatibility (Sondi I. andSalopek-Sondi B., 2004; Zhang X., 2015).
Despite all the unique properties of AuNPs, the precision control of the particle size and size distribution presents a major challenge in this field often due to the fact ofbatch-to-batch variation in a local temperature gradient,
the efficiency of reagent mixing and the resulting local
concentration gradient (Kimling J. et al., 2006). For thisreason, the availability of high precision AuNPs is rather
limited and the price could easily go above $10,000 pergram. So far, only a few studies have discussed themethod and effect of scaled-up AuNP synthesis. This
study discusses the detailed procedure to synthesize precision AuNPs with the mean particle size between 15 nm
and 30 nm, polydispersity index (PDI) less than 0.20, andscale up the batch reactor size to 1.5 L.

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 37 (2020) 224–232

2. Materials and methods
2.1 Materials
Gold (III) chloride hydrate (99.995 % trace metals basis) and trisodium citrate dehydrate (ACS reagent,≥ 99.0 %) were purchased from Sigma-Aldrich and usedwithout further purification. Hydrochloric acid (certified
ACS Plus) and nitric acid (certified ACS Plus) were purchased from Fisher Scientific. Deionized water (18.2 MΩ)
was used for all procedures.

2.2 Synthesis of AuNPs
All flasks used as reaction vessels were cleaned using
freshly prepared aqua regia. Aqua regia was prepared using concentrated hydrochloride acid and concentrated nitric acid with the volume ratio of 4:1 respectively.
In a typical AuNP synthesis, 50 ml of 0.25 mM gold
chloride (HAuCl4) solution was prepared in a flask. Independently, 34.0 mM (1.0 wt.%) trisodium citrate (NaCt)
solution was prepared. The flask containing HAuCl4 solution was heated using a hotplate with constant and vigorous stirring. In order to avoid contamination andevaporation of the solvent during the synthesis, a disposable Petri dish was used to cover the flask. After the
HAuCl4 solution reached the boiling point under ambientpressure, a specific volume of NaCt solution was rapidly
injected into the HAuCl4 solution. The molar ratio (MR)of NaCt to HAuCl4 was the primary factor controlled toachieve the desired particle size (Frens G., 1973). The
synthesis was complete when the color of the suspension
no longer changed. Typically, the reaction took 2–5 min
depending on the MR. The sample was cooled naturally toroom temperature.
In a scaled-up AuNP synthesis, the volume of the
HAuCl4 and NaCt solution were proportionally increased.
The HAuCl4 solution was heated and vigorously stirred.
The injection of a larger volume of NaCt solution was
done using multiple disposable syringes to ensure fast andefficient mixing.

temperature (25 °C).
Transmission electron microscopy (TEM). Micrographsof AuNPs were acquired using FEI TECNAI F20 S/TEM.
The particle size and size distribution of each sample
were obtained by image analysis using Image J.
A more in-depth analysis of a representative sample of
AuNPs was carried out at HSPH-NIEHS Nanosafety Center. In addition to particle morphology, the surface composition and chemical composition were analyzed indetail.
X-ray photoelectron spectroscopy (XPS). The surface
composition of AuNPs was analyzed using Thermo Scientific K-Alpha XPS system. The sample was prepared byrepetitive spraying and drying AuNP suspension on Si
wafer until 1 mg of AuNPs in total was deposited. AvantageTM Software (Thermo Scientific, Waltham, MA) wasused to calculate the elemental composition.
Fourier transform infrared spectroscopy (FT-IR). The
Perkin Spectrum One ATR was used to obtain the infrared spectrum of a representative sample of AuNPs. The
spectrum was analyzed manually with all peaks identified
based on the NIST FT-IR database.
Inductively coupled plasma mass spectrometry(ICP-MS). The elemental composition of a representative
sample of AuNPs was analyzed using Thermo-Finnigan
Element 2. The protocol (Herner J.D. et al., 2006) of sample preparation and composition evaluation was followed.

3. Characterization
3.1 UV-visible spectrum
The blue shift of the SPR peak center and the reductionof peak width (Fig. 1) were indicative of the decrease inparticle size and the polydispersity, respectively, as the

2.3 Characterization of AuNPs
The optical property and morphology of AuNPs werecharacterized using the following techniques for the purpose of general screening.
UV-visible spectroscopy. UV-visible spectra were acquired using an Ocean Optics USB2000 + XR1-ES UV/Visible spectrometer with DH-mini light source.
Dynamic light scattering (DLS). The particle size, size
distribution, and polydispersity index (PDI ) wereobtained using a Malvern Zetasizer Ultra (Malvern
Panalytical Ltd). All measurements were made at room

Fig. 1The SPR peak position of AuNPs shifted to shorter
wavelength and the peak width decreased as the molar
ratio increased from 1.00 to 3.20.

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molar ratio increases. A shoulder on the spectrum wasobserved for the samples with the molar ratio below 2.00,
which indicated the AuNPs could be anisotropic in shape(Kimling J. et al., 2006) or a certain degree of agglomeration. Literature suggested that the reason was probably
due to insufficient control of the nucleation and growth
events and/or insufficient particle stabilizing when less
NaCt was used in the reaction (Wuithschick M. et al.,2015). In contrast, the AuNP synthesized using the molar
ratio between 2.00 and 3.20 exhibited narrower peakwidth.

Table 1 TEM image analysis of the representative AuNP samples.

3.2 Dynamic light scattering

3.3 Transmission electron microscopy

DLS measurements (Fig. 2) showed that relatively uniform (PDI < 0.20) AuNPs between 15 and 30 nm weresynthesized using the Turkevich method. The PDI increases as the particle size becomes larger. As the MR decreased below 2.4, bimodal particle size distribution wasobserved with sub-10 nm particles present in addition to
the major peak. The presence of the sub-10 nm was confirmed by TEM images in Fig. 3b & 11.

TEM image analysis confirmed the DLS measurementof particle size, as shown in Fig. 3 with image analysis of
the AuNP samples in Table 1. Also, slightly elongatedparticles were observed for the 50 nm sample.

Sample15 nm AuNP

50 nm AuNPCount (#)

124

103

Mean Diameter ± SD (nm)16.99 ± 1.41

51.6 ± 5.16

Media Diameter (nm)

17.00

51.83

Aspect Ratio ± SD

1.10 ± 0.07

1.22 ± 0.14

Roundness ± SD

0.91 ± 0.05

0.83 ± 0.09

3.4 XPS, FI-IR, and ICP-MS
The XPS (Fig. 4) and FT-IR (Fig. 5) data, in Table 2
and Table 3, respectively, showed the presence of carbon,
oxygen, sodium and chlorine elements on the surface of
AuNPs, which was typical for AuNPs prepared using theTurkevich method.
Finally, the chemical composition of the colloidal AuNPs
sample was verified by ICP-MS. The results summarized
Table 2

Fig. 2The particle size of AuNPs increased as the molar ratio
decreased. A bimodal distribution was observed for
AuNP samples with MR ≤ 2.40. (System: 50 ml batch
size, 0.25 ml HAuCl4, 1 wt% NaCt, 100 °C reaction
temperature)

Fig. 3

TEM images of as-synthesized AuNPs a) MR = 2.80,
mean size = 15 nm, batch size = 1.5 L; b) MR = 1.50,
mean size = 50 nm, batch size = 1.5 L.

226

XPS data of the 15 nm AuNP sample.

Element

Peak

Atomic Percentage

Gold

Au4f

0.51

OxygenO1s

38.72

CarbonC1s

45.39

Chloride

Cl2p

3.19

Sodium

Na1s

12.20

Fig. 4

XPS data of the 15 nm AuNPs sample.

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 37 (2020) 224–232

Fig. 6

Fig. 5
Table 3

FT-IR data of the 15 nm AuNPs sample.
FT-IR data of the 15 nm AuNPs sample.

Peak (cm–1)

Correspondence

3352 cm–1

Water

1639 cm–1

Water, Citrate

Table 4

Summary of chemical composition analysis of the
15 nm AuNPs.

Inductively
CoupledPlasma Mass
Spectrometry

Purity of AuNP

99.99 ± 0.31 %Concentration of AuNP 51.296 ± 1.657 μg/ml

Control of particle size by changing the molar ratio of
NaCt to HAuCl4 with the Turkevich method.

particle size would be approximately the same regardlessof the molar excess (Wuithschick M. et al., 2015). As the
MR decreases (MR < 3) there would be less citrate available to stabilize the seed particles. Consequently, aggregation of the seed particles would occur, which results in
fewer particles, larger final particle sizes, and less spherical particle shape. A recent study provides evidence of
coalescence of 2 nm citrate-capped AuNPs in solution(Zhu C. et al., 2018), which supports the mechanism proposed by Polte et al. The aggregation of seeds would stop
after the particle concentration was significantly reduced.
The presence of aggregates could induce a self-catalytic
effect which promotes the reduction of Au3+ on the aggregate surface itself. Eventually, the growth stopped when
all precursor is consumed in the reaction.

4.2 Effect of batch sizein Table 4 indicated that the sample was highly pure(> 99.9 %).

4. Results and discussion
4.1 Effect of molar ratio
One of the advantages of the Turkevich method is theability to control the AuNP size by changing the molar
ratio of NaCt to HAuCl4. Typically, AuNPs between
10 nm and 150 nm can be synthesized by decreasing themolar ratio (MR) from 4 to 0.5 as shown in Fig. 6 (Chow
M.K. and Zukoski C.F., 1994; Frens G., 1973; Turkevich J.
et al., 1951). Further decrease in the MR would result in
an incomplete reduction of HAuCl4 to AuNPs.
According to the proposed mechanism (Polte J., 2015;
Polte J. et al., 2010), large numbers of seed particles(~2 nm in radius) were formed as the supersaturation of
the gold atoms increased rapidly. If there was sufficient citrate in the solution (MR > 3) the seed particles would bestabilized, and the AuNPs growth process and their final

The scaled-up AuNP synthesis was done by increasing
the size of the reaction vessel as well as by proportionally
increasing the reagent volumes. The effect of the batch
size on the AuNPs was studied using UV-visible spectrum and the DLS measurement. In the experiment,
AuNP synthesized in 50 mL batch vs. 1.5 L batch werecompared. The results showed that there was minimal

Fig. 7

Batch size had minimum effect on the UV-visible spectrum of AuNPs synthesized (System: 0.25 ml HAuCl4,
1 wt% NaCt, MR = 2.80, 100 °C reaction temperature).

227

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 37 (2020) 224–232

reduced electrostatic repulsion between AuNPs, thus reduced colloidal stability.

4.4 Effect of reaction temperature

Fig. 8Batch size had a minimum effect on the particle sizeand size distribution of AuNPs synthesized under the
given conditions. (System: 0.25 ml HAuCl4, 1 wt%
NaCt, MR = 2.80, 100 °C reaction temperature).

difference in the optical properties (Fig. 7) as well as theparticle size, size distribution (Fig. 8) within the tested
batch sizes.

4.3 Effect of initial HAuCl4 concentration
The effects of initial HAuCl4 concentration on AuNP
size and distribution was investigated. In the experiment,
the molar ratio of NaCt to HAuCl4 was held constant at
2.5. AuNP was synthesized under initial HAuCl4 concentrations between 0.2 mM and 1 mM. The SPR peak positions of the spectra in Fig. 9 stayed relatively constant as
the concentration increased, which suggested that the
AuNPs particle sizes were not significantly impacted by
the initial concentration under the test conditions. However, the peak breadth increased slightly as the initialconcentration increased, which indicated that AuNPs became more polydispersed. The results agreed with the literature (Zabetakis K. et al., 2012) that the polydispersity
was reduced when the initial HAuCl4 concentration waslow (< 0.8 mM). However, the AuNP size and size distribution would be impacted if the reagent concentration
was sufficiently high due to increased ionic strength andFig. 9228

UV-visible spectra of AuNPs samples synthesized withspecific initial gold chloride concentration. (System:
50 ml batch size, MR = 2.5, 100 °C reaction temperature)

Turkevich showed that a decrease in temperature would
result in a decrease in particle size (Turkevich J. et al.,1951). At relatively lower temperatures (< 90 °C), theoverall reduction rate and thus the nucleation rate waslower, so that fewer seed particles would be initially produced as compared to a higher temperature. Because theconcentration of HAuCl4 was initially the same, the final
particle size will be larger if there were fewer seed particles assuming equivalent conversion rate at all temperatures tested.
In the present study, the effects of temperature wastested at two different molar ratios of citrate to gold asshown in Fig. 10. At the molar ratio of 2.5 to 1, the particle size decreased with increasing reaction temperature.
These results can be explained by the change in kinetics
described above. However, at a higher molar ratio, e.g.
7.6:1, no measurable change in the particle size was observed.

4.5 Other factors in the Turkevich method
In recent years, the Turkevich method has been further
investigated in order to achieve more precise control overthe particle size and size distribution by adjusting the reaction conditions. Literature reports suggest that there are
additional critical parameters in Turkevich method, suchas pH (Li C. et al., 2011; Schulz F. et al., 2014), the orderof reagent addition (Ojea-Jiménez I. et al., 2011; Schulz F.
et al., 2014; Sivaraman S.K. et al., 2011) and the latent
heat of the reaction (Ding W. et al., 2015).
The solution pH could play a critical role in the AuNPs
formation. The precursor HAuCl4 exists as different complexes [AuCl4–x(OH x)] – depending on the solution pH(Wuithschick M. et al., 2015). As the pH of the solution

Fig. 10 The change in AuNP diameter as a function of the reaction temperature in Turkevich synthesis. The diameter was calculated using the method described by
Haiss et al. (Haiss W. et al., 2007)

Jiaqi Dong et al. / KONA Powder and Particle Journal No. 37 (2020) 224–232

increases, the Cl– anions would be exchanged with OH–.
The HAuCl4 complex becomes less reactive as more Cl–anions are exchanged. The percentage of each complex
would affect the overall reduction rate. In the Turkevich
synthesis, the solution pH was determined by the initialconcentration of HAuCl4. In addition, the reductant NaCt
also served as a pH buffer. When NaCt was initially added
to the HAuCl4 solution, the pH quickly increased, thereby
transforming the reactive HAuCl4 complex into a less reactive complex. During this process, the nucleation was
induced rapidly by the reactive HAuCl4 complex. The nucleation process subsequently would slow down and stop
due to the transformation of the reactive gold complex
into hydroxylated gold complexes that were less reactive(Wuithschick M. et al., 2015).
Another critical factor reported in the Turkevich
method was the order of reagent addition. In the standard
synthesis protocol, NaCt was injected into a boiling
HAuCl4 solution. In the literature, it was reported that by
injecting HAuCl4 into boiling NaCt a smaller final particle size can be produced with a narrower size distribution(Ojea-Jiménez I. et al., 2011; Sivaraman S.K. et al., 2011).
In the conventional synthesis, citrate was rapidly injected,
thereby not allowing it to convert into other species,
whereas if the order of addition was reversed, the citratesolution was brought to boiling point first, allowing it totransform into different species in the heated solution before reacting with HAuCl4. Previous researchers believedthat dicarboxyacetone, a product of citrate thermal oxidation, could play a significant role in Turkevich synthesis(Turkevich J. et al., 1951; Wuithschick M. et al., 2015).
The decrease in particle size could be attributed to the increase in dicarboxyacetone concentration due to thermaloxidation of NaCt during the heating process. Further
studies are needed to determine the exact mechanism of
citrate oxidation and the role of dicarboxyacetone in the
AuNPs formation.
Last but not the least, the effect of latent heat of theboiling HAuCl4 solution was also believed to be a factor
that affects the formation of AuNPs in Turkevich synthesis (Ding W. et al., 2015). It was reported that an increaseof the latent heat could lead to a reduction of approximately 3 nm in final particle size. Ding and co-workers
believed that the decrease in the final particle size wasdue to increased nucleation and growth rate as more heat
was provided during the reaction.

4.6 Limitations of the Turkevich method
The Turkevich method is a relatively simple and reproducible technique for the synthesis of spherical particles
between 10 nm to 30 nm. However, the particles becomeless spherical, the size distribution becomes broader, andthe results were less reproducible for the synthesis ofFig. 11 Sub-10 nm AuNPs (5–8 nm) was observed in theas-synthesized 50 nm AuNP sample with the MR =1.5.

AuNP above 30 nm size. Bimodal particle size distributions were observed for AuNP samples synthesized with
MR ≤ 2.4 as shown in Fig. 2. The presence of sub-10 nm
particles can be observed in the AuNPs sample (MR = 1.5)
by TEM as shown in Fig. 11. It was hypothesized that thepresence of sub-10 nm AuNPs could be attributed to incomplete Oswald’s ripening which happened when NaCt
concentration was relatively low in the reaction to stabilize all AuNPs. However, it was not entirely understoodand warrants further study.

5. Conclusions
Gold nanopar ticle (AuNP) synthesis using theTurkevich method was revisited. The effects of molar ratio, batch size, reagent concentration, and the temperature
were investigated in this study. The particle size, size distribution, morphology of the AuNPs were characterized
in detail, and the results agreed with the values reported
in the literature. The AuNPs size was tuned from 15 nm
to 50 nm by decreasing the molar ratio of NaCt to HAuCl4
from 2.8 to 1.5. However, the AuNPs became morepolydispersed and less spherical as the molar ratio decreased. The batch synthesis was scaled up to 1.5 L andthe as-synthesized AuNPs exhibited identical opticalproperty and morphology as the AuNPs synthesized in
50 ml batches. At a constant molar ratio, the initial concentration of HAuCl4 had minimal effect on the final particle size and size distribution within the range tested.
The particle size increased with decreasing reaction temperature at the molar ratio of 2.5. However, there was no
significant effect of temperature on the particle size at themolar ratio of 7.6.
Other potentially important factors reported in the229Jiaqi Dong et al. / KONA Powder and Particle Journal No. 37 (2020) 224–232

literature include the solution pH, the order of reagent addition, and the latent heat. These factors were not examined in the present study, and need further investigation.
Overall, the Turkevich method was found to be reliablefor producing precision gold nanoparticles (PDI < 0.20)
between 15 nm and 30 nm.

Acknowledgment
This material was based upon the work supported by
NSF (Award No. 1602032), OndaVia, Inc., Research reported in this publication was also supported by National
Institute of Environmental Health Sciences under Award
Number (NIH grant # U24ES026946). The engineered
nanomaterial used in the research presented in this publication have been synthesized, characterized, and pro­vided by the Engineered Nanomaterials Resource andCoordination Core established at Harvard T. H. Chan
School of Public Health (NIH grant # U24ES026946) aspart of the Nanotechnology Health Implications Research(NHIR) Consortium.
Any opinions, findings and conclusions or recommendations expressed in this material were those of the author(s) and do not necessarily reflect the views of the
National Science Foundation and the National Institutesof Health.

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Authors’ Short Biographies
Jiaqi Dong
Jiaqi Dong received his B.S. in Materials Science and Engineering from Illinois Institute of Technology 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 the supervision of Dr. Brij Moudgil and Dr. Bahar Basim at
the Center for Particulate and Surfactant Systems (CPaSS). His current research focus ismetallic nanoparticle synthesis and functionalization using fluidics.

Paul Carpinone
Paul Carpinone received his BS in Chemical Engineering and Ph.D. in Materials Science and Engineering from the University of Florida. He joined the Particle Engineering
Research Center (PERC) in 2006, and subsequently, the Center for Particulate and Surfactant Systems (CPaSS), where he conducted his doctoral and subsequent academic research work. He has authored over sixteen publications, patents, and book chapters. His
research interests include surface and interfacial chemistry, particle synthesis and characterization, nanotoxicology, analytical characterization, and X-ray diffraction.

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Jiaqi Dong et al. / KONA Powder and Particle Journal No. 37 (2020) 224–232

Authors’ Short Biographies
Georgios Pyrgiotakis
Dr. Georgios Pyrgiotakis is a Research Scientist at the Harvard T. H. Chan School of
Public Health and the Research Coordinator for the HSPH-NIEHS Nanosafety Center.
He holds a Ph.D. degree and an MS degree in Materials Science and Engineering fromthe University of Florida. His research is focused on the health and environmental implications of nanotechnology and how it correlates to the material properties. He also developed a novel, nanotechnology-based, chemical-free method for air and surface
disinfection that utilizes only water to kill dangerous pathogens. He authored more than
60 publications and book chapters. At the time of this publication, he is a Research Investigator II at Bristol-Myers Squibb.

Philip Demokritou
Philip Demokritou is an Associate Professor at T. H. Chan School of Public Health,Harvard University and Director of the Center for Nanotechnology and Nanotoxicology(www.hsph.harvard.edu/nano). His current research focuses on understanding, manipulating, and applying engineered nanomaterials and phenomena at the nanoscale withspecial emphasis on assessing the fundamental nano-bio interactions in biological systems, nanosafety and potential applications of nanomaterials in environmental and life
sciences. He is currently the Director of the NIH/NIEHS funded Nanosafety Center(www.hsph.harvard.edu/nanosafety) which is part of the NIH/NIEHS Nanotechnology
Health Implications Research (NHIR) consortium. He is also a founding Co-Editor in
Chief of NanoIMPACT.

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, and his 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 offunctionalized nanoparticles, antiscaling and surfactant mediated corrosion inhibitors,
photocatalytic degradation of hazardous microbes, and nanotoxicity. He has publishedmore than 400 technical papers and has been awarded over 25 patents. He is a member of
the U.S National Academy of Engineering.

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KONA Powder and Particle Journal No. 37 (2020) 233–243/Doi:10.14356/kona.2020012

Original Research Paper

NMR as a Tool to Characterize the Aggregation Structure of
Silica Nanoparticles in a Liquid †Chika Takai-Yamashita 1, Emiko Sato 2 and Masayoshi Fuji 2*
1
2

Faculty of Engineering, Gifu University, Japan
Advanced Ceramics Research Center, Nagoya Institute of Technology, Japan

Abstract
The NMR-based solvent relaxation technique, a non-invasive tool to characterize the surface of particles, which
are dispersed in a liquid, was applied to characterize the nanoparticles’ aggregation structure. The liquid
molecules in a dispersion undergo a rapid exchange between the bound states at the interface and highly mobile
free states in a bulk liquid. The relaxation time of the liquid molecules bound on the particle surface is shorter
than that of the free states liquid. By detecting how much liquid is bound on the particle surface, the wetted
specific surface area (S NMR) can be determined. In this study, it was clarified that the water adsorbed at more thana 1.138 layer from the silica surface can be detected by the NMR and the maximum limitation ranged from 2.160
and 3.336 layers. The model aggregates with an artificial solid neck among the particles were mixed with thesilica nanoparticle dispersion. Although the determined S NMR was underestimated compared to SBET from gas
adsorption, even a low ratio (5 mass%) of the model aggregates in the dispersion can be detected.
Keywords: aggregation structure, wetted specific surface area, solvent relaxation NMR, adsorbed water, silica

1. Introduction
It is well known that nano-sized particles easily aggregate due to many active sites on their surface compared tomicron-sized particles. It is also common knowledge thatthe excellent properties of the nanoparticles, such as mechanical, thermal, magnetic, electrical, etc., are strongly
affected by the structure of their aggregation in addition
to their dispersion.
The three-dimensional silica nanoparticles network inrubber, linked by their secondary aggregates, encourages
the wet grip performance of car tires on ice. These important particle network structures were characterized bysmall-angle X-ray scattering (SAXS) in combination withtransmission electron microscopy (TEM) (Baeza et al.,2013; Stauch et al., 2019). Song et al. (2019) proved that
aggregation in a heat-transfer fluid called a nanofluid,which was obtained by suspending metallic nanoparticles
in a conventional liquid, can increase the thermal conductivity due to the formation of an “efficient heat channel,”using the Monte Carlo simulation considering phonon
†
1
2

*

Received 28 May 2019; Accepted 12 July 2019
J-STAGE Advance published online 10 August 2019
1-1 Yanagido, Gifu 501-1193, Japan
3-101-1 Honmachi, Tajimi 507-0033, Japan
Corresponding author: Masayoshi Fuji;
E-mail: fuji@nitech.ac.jp
TEL: +81-572-24-8110 FAX: +81-572-24-8109

transport. Yang et al. (2019) developed a self-healing system of a thermoplastic polymer in which the superparamagnetic nanoparticle aggregations were embedded.
Under the application of an oscillating magnetic field, themigrated nanoparticles generate a high local temperature
which heals the electrical tree channels in the polymer.
Ajmal et al. (2019) produced that a highly-conductive
silver/polyvinyl alcohol nanocomposite fibers by adding
silver ions to prevent aggregation of the originally dispersed silver nanoparticles. The gaseous byproduct fromthe precursors dramatically increased the flexibility of thenanocomposite’s tensile strength.
Thus, understanding the aggregation structures, which
are directly connected to the nanoparticles’ performance,is highly recommended. There have been several techniques to characterize them via microscopic observations,scattering of electromagnetic waves, sedimentation tests,
rheological behaviors (Wang et al., 2012), differential
scanning calorimetry (DSC) (Korobov et al., 2010), nitrogen gas adsorption (Yoshida et al., 2016), etc. Some of thedata were analyzed in combination with theoretical models including fractal dimensions.
The interparticle bond energies can range from weakvan der Waals forces (agglomerates) to stronger solid statenecks (aggregates). Teleki et al. (2008) distinguished thoseof “as-prepared” flame-made TiO2 nanoparticles by the
TEM observations before/after a high-pressure-dispersion,in combination with the particle size distributions

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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measured by dynamic light scattering (DLS) and the specific surface area calculated from the N2 adsorption isotherm by applying the Brunauer–Emmett–Teller equation.
When considering deformation of the aggregation structure under vacuum during observation, some techniques
to fix the aggregation structures of particles such as carbon coating on the freeze-dried-thinned-samples called
cryo-replica TEM (Tiarks F. et al., 2008) and direct
visualization technique through polymerization of medium-­soluble-monomers (Takahashi M. et al., 2004), were developed. These visualization techniques are indeed
effective for understanding, however, at the same time,they are time-consuming when manually obtained 100–
1000 particles need to be counted for reliable determination of the particle size distribution (Tsantilis S. et al.,2002).
The ultrasmall-angle X-ray scattering (USAXS) andthe small-angle neutron scattering (SANS), as the scattering techniques, detect a structure of 1000 nanometers at
most which reflects the nanoparticles’ aggregation. The
scattering profile as a function of the scattering vector q(q = 4π sin(θ)/λ, where 2θ and λ are the angle between theincident beam and the detector, and wavelength of the radiation) can be fitted with intensities calculated from different model shapes when the size distribution is known(Kammler et al., 2004; Hurd et al., 1987). Gilbert B. et al.
(2009) reported that low-aggregation (i.e., higher porosity)of iron oxyhydroxide nanoparticles improved the metal
uptake performance due to physical loss of the accessible
surface area, by a synchrotron SAXS analysis considering
the fractal dimensions. Bharti et al. (2011) determined thelysozyme as a protein induced compact and a loose flocculated silica nanoparticles network at low and high pHs,
respectively, by the laboratory SAXS and proved by cryoTEM and a sedimentation test which will be describedlater.
Korobov et al. (2010) estimated the aggregation structure from the DSC traces by observing the melting behaviors of water in the particles’ gap by means of thenanophase of water’s non-freezing property. Yoshida et al.
(2016) combined N2 gas adsorption with a He gas pycnometer and DLS to characterize the primary and secondary aggregation of carbon black, as an alternative toconventional ways such as the incorporation of chemicals(e.g., cetyl trimethyl ammonium bromide, di-butyl phthalate) into the particles’ gap. They warned that the pressureduring the Hg intrusion into the particles’ gap probably
deformed the aggregation structure.
The particle size distribution from the sedimentation
test was determined by Stokes law. The sedimentation
time is inversely proportional to the particle size to thesecond power. For the nanoparticles, of course, centrifugal force is required to reduce the time (Allain et al.,1995). Lerche et al. (2007, 2014 and 2019) proposed an234

analytical centrifuge (AC) system for determination of thecharacteristic material properties related to the sedimentation and consolidation behavior of the dispersions. The
STEPTM-Technology (Space and Time resolved Extinction
Profiles) allows one to simultaneously measure the intensity of the transmitted light as a function of time and position over the entire sample length. The data aredisplayed as a function of the radial position as the distance from the center of rotation. The progression of thetransmission profiles contains information on the kineticsof the separation process and allows particle characterization. They also showed that this technique was very ef­
fective for dispersions of hard and soft micro- andnanoparticles (e.g., titania or lysozyme coated silica), sterical, electrosterical, and rheological stabilization (polyelectrolyte coated nanoparticles), mixtures of different
particle types (silica and iron oxide nanoparticles), at any
pH value and ionic strength. Walter et al. (2015) developed a new data evaluation technique by applying analytical ultracentrifugation (AUC) which can detect particles
less than one nanometer in size with Ångström resolution.
They showed a very good correlation with an error of
10.65 % between atomic force microscopy AFM and AUC
for the mean lateral diameter of the fully delaminatedgraphene oxide (GO) sheet, which was achieved using one
single AUC measurement and hydrodynamic modelingbased on an assumed sheet height and density.
Meanwhile, Nelson A. et al. (2002) monitored the individual adsorption of two different polyelectrolytes (PEOand PVP) on silica particles as well as the polymeric displacement of one polymer (PEO) by another (PVP) using
nuclear magnetic resonance (NMR) at 200 MHz. This relies on the fact that mobile (liquid-like) and immobile(solid-like) protons have very different relaxation times.
They also investigated the effect of electrolytes on adsorbed polymer layers on PEO adsorbed silica (Flood andCosgrove, 2006), determined how many polymers per
particles (Flood and Cosgrove, 2008) using NMR at 300
and 400 MHz.
According to Fairhurst et al. (2016), a portable benchtop NMR spectrometer operating at 13 MHz could possibility determine the particle size, wetted surface area, andporosity of the nanoparticles (nanocarbon) due to the factthat solvent molecules in a dispersion undergo a rapid exchange between the bound states at the interface andhighly mobile free states in the bulk solvent. The relaxation time of the solvent molecules bound on the particle
surface is shorter than that of the free states solvent. The
observed single relaxation time, Tav, is determined fromthe reciprocal of the spin relaxation rate, Rav. As Eqn. 1
indicates, the relaxation rate is an average of the relaxation rates of the molecules on the particle surface, Rs,
and free solvent, Rb, weighted by their relative populations as Ps and P b.

Chika Takai-Yamashita et al. / KONA Powder and Particle Journal No. 37 (2020) 233–243

Rav = Ps Rs + Pb Rb(1)

The wetted specific surface area, Sw, of the particles
can be expressed as follows. Considering the particle volume concentration, φ p, thickness of the bound liquid
layer, L, the particle density, ρp, the Eqn. 1 was transformed into 2.

Rav = ϕp S w L ρp (Rs − Rb ) + Rb

(2)

Using standard reference materials, the constant (called
the specific surface relaxivity) kA (= Lρp[Rs – Rb]) was defined. It clearly depends on both the particle type and dispersing solvent. Using this parameter, Eqn. 2 reduces tothe following Eqn. 3.

Rav = k A S w ϕp + Rb

(3)Here, Rsp = [Rav/Rb] – 1, which indicates the affinity ofthe particle surface to the solvent, is defined. Rsp increases
with an increase in their affinity with the same specificsurface area. Using Eqn. 4, the wetted specific surface
area (S NMR) can be determined.
Rsp RbS NMR =

(4)

k A ϕpThe NMR based solvent relaxation technique has advantage of being non-destructive with minimal tem­
perature control requirements and minimal sample
pretreatment in addition to a rapid analysis for highly-­
concentrated and opaque samples which are sensitive toaggregation. Various particles have already been characterized using the solvent relaxation NMR to investigate
the exfoliation behavior of Laponite clay (Karpovich etal., 2016), the hydrophilicity and hydrophobicity of superparamagnetic Fe3O4 nanoparticles (Ali et al., 2018), thereactivity of CuO, ZnO, and SiO2 (Paruthi and Misra,
2017), the wetted specific surface areas of ZnO and Ag/
ZnO as photocatalysts (Saoud K. et al., 2015), etc. Fairhurst et al. (2016) provided information regarding the selection of the solvent in which porous particles (e.g.,porous graphene) were dispersed. In the case of using ethanol, which has a strong interaction with the graphene, amuch more mobile bound layer provided shorter decay
times than the water samples. Depending on which of therelaxation times was used for the calculation, the wetted
specific surface area significantly changed. Elliott and coworkers (2018) investigated the effect of a high electrolyte
concentration on the particle surfaces by solvent relaxation NMR. TiO2 nanoparticles were unaffected by thesolvent conditions, while the Rsp values of the SiO2 andCaCO3 nanoparticles were substantially enhanced in thepresence of the KCl electrolyte. They concluded that thedifference in RSP between TiO2 and CaCO3 is attributed toa counterion effect. Hossain et al. (2018) characterizedaqueous dispersions of hollow amorphous nanoparticles
with a 50-nm outer size that have two liquid accessible
surfaces (i.e., inner and outer surfaces) using solvent relaxation NMR. A higher wetted surface area was observed in the hollow nanoparticles than in the dense
nanoparticles. The solvent relaxation NMR has been utilized to investigate various kinds (metal oxides, metals,
and ionic crystals) and shapes (spheres and clays) of particles which are dispersed in both aqueous and nonaqueous
solvents. This has a great potential for particle characterization, however, there is still some challenging concerns
regarding the understanding of the obtained relaxationtime.
In this study, we focused on applying the NMR based
solvent relaxation technique to understand the aggregation structure of nanoparticles. There is solvent (water, in
this study) which penetrates into the particle’s gap during
the aggregation. By counting the adsorbed amount of thesolvent, the density and porosity of the aggregation can be
estimated. However, the problem is how many adsorbed
layers can be detected and how many are unclear. According to Hossain et al. (2018), the water captured in approximately 30-nm-hollow interior (Lee et al., 2014) had
probably been detected by the solvent relaxation NMR.
The ability of the solvent relaxation NMR to characterize
the nanoparticle aggregation structure was investigated in
combination with water vapor adsorption. Based on the
results, characterization of model aggregates in the silica
nanoparticle dispersions was attempted. The model aggregates were prepared with different loads by uniaxialpressing.

2. Experimental section
2.1 Sample preparations
Silica nanoparticles (Aerosil 200 (12 nm), Aerosil 130(16 nm), and Aerosil OX50 (40 nm), all kindly provided
by Nipppon Aerosil Co., Ltd.) or silica sub-micron particles (SO-C1 (0.2–0.4 μm), kindly provided by Admatechs
Company Limited) were dispersed in distilled water or an
organic solvent (hexane, purchased from Fujifilm Wako
Pure Chemical Corporation) by a 1-h stirring. Unless otherwise noted, the particle concentration of the dispersions
was kept at 10 mass%.
For the experiment to compare the dispersion states, anultrasonication (HSR-301, Honda Electronics Co., Ltd.)
was additionally conducted at 1 MHz, 40 W for 180 seconds.
For the experiment to investigate the effect of the adsorption amount of water, particles were exposed to water

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vapor for 24 h whose humidity was controlled by saturated salt solutions of 60, 70, 80, 86, and 92 % by
NaBr·2aq, Ca(NO3)2·4aq, KBr, KI, and KNO3, respectively (Kawamura et al., 2014). The adsorbed weight ofwater was determined by weighing before and after the
24-h exposure.
The model aggregates were prepared using silica nanopaticles (Aerosil 130) as follows. The pellets with 10-mm
diameter were prepared by uniaxial pressing (TB-50H-D,
NPa System Co., Ltd.) with the average load of 1, 5, and
10 kN (13, 64, and 127 MPa). The porosity of the pellets
were 78.4, 69. 5, and 62.1 %, respectively, measured bytheir volume and weight. The as-prepared pellets wereheat treated at 400 °C for 2 h to intentionally create solid-­state necks among the nanoparticles. The heated pellets
were then milled and sieved using 100-μm stainless steel
mesh. The fragments of the pellets over 100 μm wereused as the model aggregates. The model aggregates, after vacuum deairing for more than 1 h, were dispersed in
distilled water by a magnetic stirrer for 24 h as a
10 mass% dispersion.
To investigate the effect of the ratio between the model
aggregates and the as-received silica nanoparticles(Aerosil 130, after vacuum deairing), the 5 kN load model
aggregates were mixed with the silica nanoparticles usinga magnetic stirrer for 24 h to form a 10 mass% dispersion.
The concentrations of the model aggregates were 0, 5, 10,40, and 100 %.

2.2 Characterizations
The dispersion state was also characterized by a laser
diffraction instr ument for par ticle size analysis(MT3200II, MicrotracBEL Corp.). The water vapor adsorption isotherm and nitrogen gas adsorption isotherm
were created using a high precision gas/vapor ad­
sorption measurement instrument (BELSORP-max II,
MicrotracBEL Corp.).
Regarding the NMR based relaxation technique, 1.0 mlof the dispersion was placed in a sample tube and inserted
it into the Acorn area (Xigo Nanotools, Inc.). The sample
resides within a coil located between two permanent
magnets. A static, uniform magnetic field causes the protons within the solvent to align with the magnetic field.
This process typically takes a few seconds. At the start ofthe measurement, a short radio frequency (RF) pulse excites the coil at a frequency of approximately 13 MHz.
This pulse produces a large magnetic field inducing atemporary shift in the magnetic orientation of the sample
protons. When this induced field stops, the protons of thesample dispersion then realign with the static field. This
realignment induces a decaying voltage in the coil (XiGoNanotools, 2015). By using specific RF pulse sequences,
the sample’s T1 (longitudinal, spin-lattice relaxation) and

236

Fig. 1

Typical graph obtained from the NMR based solvent
relaxation technique.

T2 (transverse, spin-spin relaxation) relaxation times aremeasured. T1 and T2 depend on the rotational and translational motion of the molecules. The magnitude of the shift
in relaxation (from bulk to surface) is different for T1 andT2. Typically, the shift in T2 is greater than for T1. The T2
measurement uses the Carr-Purcell-Meiboom-Gill(CPMG) pulse sequence method. Fig. 1 shows the typicalT2 data of the silica nanoparticle dispersion and distilledwater as the dispersing medium.
The 37 % reduced points from the initial magnetization
is defined as T2. The T2 value of the dispersion was morethan twice as high as that of water. It can be said that
there is a large amount of water molecules trapped on thesilica nanoparticle surface. The kA, that appeared in Eqn.
3, was determined using the specific surface area of thesilica particles calculated from the nitrogen gas adsorption isotherm applying the BET equation.

3. Results and discussion
3.1 Effects of particle sizes, concentrations, andadsorbed water layer on the relaxation time
As shown in Fig. 2, the effects of the particle sizes andconcentrations on the relaxation time were investigatedusing Aerosil 200, Aerosil OX50, and SO-C1, whose
nominal primary particle sizes were 12 nm, 40 nm, and
0.2–0.4 μm, respectively. The T2 values are listed inTable 1. Regarding the particle concentrations (1, 3, 5,
and 10 mass%), there was a decreasing tendency in the relaxation time independent of the particle size. This isconsistent with Fig. 1 that the amount of the water molecules trapped on the particles increased with the increasing particle concentration. It is well known that theChika Takai-Yamashita et al. / KONA Powder and Particle Journal No. 37 (2020) 233–243

Fig. 2

Table 1

Effects of primary particle sizes and particle concentrations on the relaxation time; (a) Aerosil 200, (b)Aerosil OX50, and (c) SO-C1.

The T2 values of silica particle dispersions with different solid contents.

T2 [ms]Solid content
Aerosil 200[mass%](12 nma)Aerosil OX50
(40 nma)

SO-C1(0.2–0.4 μma)

11035.71766.91945.4

3607.1

1174.61340.9

5

344.7

930.7

965.3

10

188.6

599.8

643.9

a

Nominal primary particle size.

specific surface area increases with a decrease in the particle size. When comparing the particle sizes, the relaxation time decreased with the decreasing particle size.
This can also be explained by the increasing amount of
the water molecules trapped on the particle surface.
Fig. 3 shows (a) the particle size distributions and (b)the magnetization vs relaxation time of the SO-C1 dispersions before and after ultrasonication. In Fig. 3(a), before
the ultrasonic treatment (i.e., after magnetically stirringfor 24 hours), the main peak of the suspension was over
10 μm and it was reduced to less than 0.2 μm after thetreatment. Due to the ultrasonication, the sub-micron particles were so dispersed as to have a particle diameter
close to that of primary particles. The relaxation time decreased after the treatment although the change was small(before treatment T2 was 643.9 ms and after, 584.6 ms.) as
shown in Fig. 3(b). It seems that the sub-micron particles
formed weak agglomerates which easily disperse by theultrasonication (Higashitani et al., 1993).
The NMR relaxation defines two liquid phases, i.e., thesurface liquid at the particle surface and bulk liquid far
from particle. Then how many adsorbed water layers on
the particle surface are the surface liquid?
The silica surface exhibits hydrophilic property due toFig. 3

Changes in (a) the particle size distributions and (b) relaxation times of the silica particle dispersions before
and after ultrasonic (US) treatment.

lots of silanol (SiOH) groups which are categorized into
three types in accordance with the number of OH groupbonds to the Si atom, i.e., isolated OH, geminal OH, andtriple OH. According to Fuji and Chikazawa et al. (2000),
the number of total silanol groups on the fumed silica
nanoparticles was 2.8 per nm 2 and decreased with the237Chika Takai-Yamashita et al. / KONA Powder and Particle Journal No. 37 (2020) 233–243

heat treatment; 2.3/nm 2 at 200 °C, 1.9/nm 2 at 300 °C, 1.4/
nm2 at 400 °C, and 1.3/nm2 at 500 °C, determined by the
Grignard method.
With a decrease in the silanols, siloxane (Si-O-Si)
bonds are created and the hydrophilicity decreases. Withan increase in the relative humidity where the particles
have been stored, the adsorbed amount of water on theparticles increases and the degree of particle aggregationis changed (Kawamura et al., 2014).
Fig. 4 shows typical water vapor adsorption isothermof the silica nanoparticles (Aerosil 200). The adsorption
isotherm is IUPAC classification type III. In general, because the interaction between the silica surface and watermolecules is strong, the water adsorption isotherm is described as type II. When the interaction between the adsorbate and a solid surface is weak, the adsorption
isotherm is listed as type III. In this case, it is thought thatthe number of silanols on the Aerosil 200 surface is low
in comparison to the silica gel. The reason why is re-Fig. 4

Table 2

Water vapor adsorption isotherm of Aerosil 200 withadsorbed amount of water measured by weight difference before/after humidity control.

garded as follows. Aerosil 200 is synthesized at a hightemperature by a dry process. The surface silanols are
eliminated in that process. During the initial stage of water adsorption as shown in Fig. 4, the localized adsorptionof water molecules occurs on the silanols. This localized
adsorption then grew into an island-state adsorption bycooperative adsorption. Furthermore, the adsorbed
amount increased at a high relative humidity due to theoccurrence of a multilayer adsorption on the continuous
two-dimensional water layer which is constructed by contact among the water islands (Fuji et al., 2000).
The plots as black circle in Fig. 4 represent amount ofwater adsorbed on the humidity-controlled-silica nanoparticles measured by the weight difference before and after
water vapor exposure. The adsorbed water amount also
increased with the relative humidity although there are
errors which are probably due to measurement principle
differences.
Table 2 lists (a), (b) the amount of adsorbed water, (c)the number of adsorbed water molecules, (d) adsorbed
water molecules per one silanol groups, and (e) estimatedadsorbed water layer when the humidity is controlledfrom 60 to 92 %. The number of adsorbed water layers
rapidly increased especially at the higher relative humidity.
Fig. 5 shows the relaxation time constant (1/T2) as afunction of the number of adsorbed water layers which
was estimated from the water vapor adsorption isotherm
as shown in Table 2. These solvent relaxation data were
measured as silica nanoparticle, n-hexane dispersions toprevent adsorbed water layer diffusion into the solvent
and to only detect the bound water. The 1/T2 increased
with an increase in the adsorbed water layer. It is notedthat gradual increases were observed near the first layer.
The first inflection point after the first layer indicated thatthe adsorbed water at more than a 1.138 layer from thesilica surface can be detected by the NMR. The second
inflection point indicated that the layer between 2.160 andEstimation of adsorbed water layer on silica nanoparticles calculated from the water vapor adsorption isotherm.
Amount of adsorbed water [mg/g](c) Number of(b) amount of water adsorbed water
vapor adsorptionc
molecules (× 109)a(d) Number ofadsorbed watermolecules per one
silanol groupa(e) Estimatedadsorbed waterlayer per one
particleb

18.0

25.3

8.47

1.51

0.847

70

30.0

34.0

11.38

2.03

1.138

80

57.5

53.1

17.76

3.17

1.776

86

71.3

78.0

26.10

4.66

2.610

92

77.7

99.8

33.36

5.96

3.336

Relative humidity[%](a) weight difference before/after
humidity control

60

a,b
b

Calculated from c.
Calculated using the specific surface area of AEROSIL 200.

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Fig. 5

Relaxation time constant as a function of number of adsorbed water layers calculated from water vapor adsorption isotherm.

Fig. 7

Fig. 6

Relationship between Rsp and total surface area ofAerosil130.

Particle size distributions (left) and optical microscopic observations (right) of the model aggregates
prepared with (a) 1 kN, (b) 5 kN, and (c) 10 kN.

3.336 seems to be the maximum limitation which can bedetected as bound water on the silica surface. At least therange between the 1.138 and 2.610 layers can be detected
as the bound water.

3.2 Characterization of nanoparticle aggregation
by NMR
We now focus on applying the NMR solvent relaxation
to investigate the silica nanoparticle (Aerosil 130) aggregation. The nanoparticle aggregates have small poresamong the nanoparticle gaps where solvent (water in thiscase) is included in. How can the NMR detect the boundwater in the small pores? To investigate this, the relaxation time of the artificially-prepared model aggregateswith different sized pores was determined. The preparation of the aggregates was described in the experimental
section. The pore sizes were adjusted by load (i.e., 1, 5,

and 10 kN, which correspond to 13, 64, and 127 MPa, respectively) when preparing the pellets of Aerosil 130. The
pellets were used as the model aggregates after being
fractured and sieved.
Before starting, the relationship between Rsp (= [Rav/Rb] – 1) and the total surface area of Aerosil 130 was evaluated as shown in Fig. 6. The Rav, that appeared in the
Eqn. 1, is expressed by the sum of the relaxation time
constants (1/T2) of the bound water on the particle (Rs) andfree water (Rb) which is being multiplied by each concentration. The particle concentrations were changed between 0.15 and 10 mass%. The total surface areas at eachsolid concentration were calculated using the specific surface area (calculated using BET theory from the gas adsorption isotherm data). The Rsp value and the total
surface area showed an approximate proportional relationship. Therefore, it can be said that the relative evaluation of the wetted surface area of Aerosil 130 is possible

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Fig. 8(a) Nitrogen gas adsorption (ADS) and desorption (DES) isotherm and (b) BJH pore size distributions ((c)
enlarged) of model aggregates.

using the Rsp value. The model aggregates were thencharacterized by their size distribution, microscopic observations, and pore size distribution. Fig. 7 show the size
distributions by the laser diffraction technique and optical
microscopic observations of the model aggregates prepared with 1, 5, and 10 kN after being milled and sieved(> 100 μm). Their median diameters (D50) were 360.0(1 kN), 343.9 (5 kN), and 388.9 μm (10 kN), respectively.
It can be said that they have similar size distributions. The
optical microscopic observations showed us that similar
fractured shapes were obtained and small-sized aggregates with less than 100 μm were eliminated. Fig. 8
shows the nitrogen gas adsorption desorption isotherms
and pore size distributions calculated using the BJH
method from the isotherms of the model aggregates. The
specific surface area (SBET from BET theory) from theisotherms, average pore size, and pore volume (BJH theory) are listed in Table 3. With an increase in the load,
they decreased. Fig. 9 shows SEM images of the fractured surface of the model aggregates. The rough surface
can be clearly observed in the 1 kN model aggregates.
The large pores of more than 100 nm were also observedin the SEM images, which are more than 46.13 nm calculated from the BJH. A pore size more than 50 nm is
out-of-detection when using the gas adsorption isotherm.
In combination with a mercury porosimetry, the micron-­ordered large pores of the pellets disappeared over
60 MPa (5 kN, here) (Our unpublished results). With anincrease in the load, the roughness clearly decreased.
Fig. 10(a) shows typical relaxation time curves of themodel aggregates at 1, 5, and 10 kN load. Each standard
deviation of ten measurements was in the range between
0.5 and 0.7. Fig. 10(b) shows the relationship between thewet specific surface area (S NMR) and SBET. The decreasing
tendency of the S NMR with an increase in the load was
similar to that of the SBET. Since the sizes of the model
aggregates are similar as shown in Fig. 7, these changes
can be affected by the aggregation structure. The reason
why S NMR is smaller than SBET is probably due to unde-240

Table 3Fundamental data of the model aggregates preparedat 1, 5, and 10 kN.

Load
[kN]

D50
[μm]a

SBET
[m 2/g]b

Averagepore size
[nm]c

Pore
volume[cm3/g]c

1

360.0

137.6

46.13

1.81

5

343.9

133.7

29.50

1.09

10

388.9

124.2

22.07

0.84

a

Average size from DLS.
BET specific surface area.
c
BJH therory.
b

Fig. 9SEM micrographs of the model aggregates preparedwith (a) 1 kN, (b) 5 kN, and (c) 10 kN.

tectable bound water on the very top surface of the particle. Can the NMR detect the model aggregates which are
mixed in the slurry? Fig. 11 shows the S NMR of the
10 mass% slurry with different ratios of the model aggregate (5 kN). The S NMR, represented as blackened triangles, decreased with an increase in the model aggregate
ratio and approached the value of the 5 kN model aggregate. The broken line appeared as the theoretical S NMR
calculated using S NMR considering ratio of the as-received
AEROSIL 130 and 5 kN model aggregates. The measured

Chika Takai-Yamashita et al. / KONA Powder and Particle Journal No. 37 (2020) 233–243

S NMR became smaller than the theoretical value, especially for the higher ratio of the model aggregate (i.e., 0.4
in this case). This is probably due to the as-received
AEROSIL 130 gathering together with the model aggregates. Note that even a low ratio (i.e., 0.05) of the model
aggregate can be detected by the solvent relaxation NMR.

4. Conclusion
The effectiveness of the solvent relaxation NMR as atool to characterize the nanoparticle aggregation structure
was verified. The most important finding in this study isthat the adsorbed water layer on the silica nanoparticles
ranging between 1.138 and 2.610 can be detected as boundwater to determine the wet specific surface area (S NMR).
The S NMR of the artificially prepared model aggregates
was underestimated compared to SBET due to undetectablewater which was strongly bound on the particle surface.
The S NMR could even show low ratio of the model aggregates in the silica nanoparticle dispersion. The required
amount for the NMR experiment is only 1 mL and themeasuring time is just few minutes regardless of the particle concentration. In addition, not only the aqueous dispersion, but also a nonaqueous dispersion can bemeasured. Indeed, there are still difficulties in understanding the results, however, the proposed techniquecould be a simple and versatile tool to characterize thenanoparticle aggregation structure.
Fig. 10 Typical results of model aggregates and wet specificsurface area (S NMR) calculated using Eqn. 4. The
break line in (b) means S NMR = SBET.

Acknowledgements
A part of this study was supported by JSPS KAKENHI
18K04699, Leading Initiative for Excellent Young
Researchers (LEADER) of MEXT, and Hosokawa Powder
Technology Foundation. The authors received helpfuladvice from Dr. S. Takeda, Takeda Colloid Techno-­
Consulting Co., Ltd. The authors thank to Admatechs
Co., Ltd., and Nippon Aerosil Co., Ltd., for providing thesilica particles.

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Fig. 11 S NMR of the 10 mass% slurry with different ratios ofmodel aggregate (5 kN). The bold and broken lines
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Authors’ Short Biographies
Chika Takai-Yamashita
She received her Dr. Eng. in 2007 from the Nagoya Institute of Technology and joined
Kurimoto Co., Ltd., until 2011. She was a postdoctor at the Nagoya Institute of Technology from 2011 to 2014 and took a maternity leave for one year. During her JSPS research
fellowship (2017–2018), she was an Academic Guest in Empa, Switzerland, for half ayear by support of Young Researchers’ Exchange Program between Japan and Switzerland from JSPS. From November 2018, she was a Research Associate at the Faculty ofEngineering in Gifu University by support of the Leading Initiative for Excellent Young
Researcher of Ministry of Education, Culture, Sports, Science and Technology.

Emiko Sato
She received her Bachelor’s degree in 2013 and she investigated effect of frequency on
dispersion behavior of silica nanoparticles under ultrasonication. She then joined Master
degree in 2015 and focused on characterization of nanoparticle aggregation structure using NMR solvent relaxation technique. She joined Ibiden Co., Ltd., in 2015.

Masayoshi Fuji
He received his Dr. Eng. in 1999 and joined the Tokyo Metropolitan University, as a Research Associate in 1991. He was a Visiting Researcher at the University of Florida, USA,
from 2000 to 2001. He joined the Nagoya Institute of Technology as an Associate Professor
in 2002 and became a Professor in 2007. He is Editor-in-Chief of Advanced Power Technology since 2019. His representative awards include the award from the minister of education, culture, sports, science and technology Japan in 2013, CerSJ award for academic
achievements in ceramic science and technology in 2014 and the science award of the Society of Inorganic Materials, Japan in 2017.

243

KONA Powder and Particle Journal No. 37 (2020) 244–257/Doi:10.14356/kona.2020014

Original Research Paper

Production of Hematite Micro- and Nanoparticles in a Fluidized
Bed Process—Mechanism Study †Nadine Le Bolay *, Rihab Lakhal and Mehrdji Hemati
1

University of Toulouse, France

Abstract
A continuous, compact and simple process was developed to synthesize micro- and nanoparticles of iron oxide.
The process combines the spraying (pulverization) of an aqueous solution of iron nitrate in a fluidized bed reactor
containing coarse and hot glass beads (T = 200 °C) for the production of solids and a transported bed reactor for
calcination (T = 490 °C). The intermediate product formed in the fluidized bed reactor is 2-line ferrihydrite, while
the calcination reactor allows the production of hematite micro- and nanoparticles. These particles arecharacterized by a narrow size distribution, a mean size of 0.5 μm, a specific surface area of 24 m 2 g–1 and adensity of 4499 kg m–3. Particles are made up of small clusters of crystallites having an average size of 47 nm anda low internal porosity (0.12). The reaction mechanism was studied using a muffle furnace and a lab convective
dryer. It was found that several steps are involved leading first to the production of iron nitrate dihydrate after theremoval of the solution water, as well as two and then five molecules of water of hydration. After that, theelimination of nitrate leads to the production of ferrihydrite. Finally, ferrihydrite is transformed into hematite dueto the removal of residual nitrate and water of hydroxylation.
Keywords: hematite nanoparticles, ferrihydrite, fluidized bed, properties, mechanisms

1. Introduction
The production of nanometric particles is of great interest for various industrial sectors since they have attractive
properties. In particular, magnetite, hematite and mag­hemite nanoparticles present interesting magnetic, electrical and optical properties. They are used for wastewater
treatment, biomedical and catalytic applications, or as
pigments for painting. Moreover, they are intensively investigated for applications in gas sensors, lithium batte­ries and cosmetic products.
Conventional processes for the synthesis of hematite
nanoparticles, such as chemical precipitation (Lunin A.V.
et al., 2019), hydrothermal synthesis (Zhu M. et al., 2012),
forced hydrolysis (Wang W. et al., 2008), sol-gel (Pawar
M.J. and Khajone A.D., 2012) and microemulsion(Housaindokht M.R. and Pour A.N., 2011), comprise numerous steps: precipitation and crystallization, filtration,
washing, drying and dry grinding. All these operations
need numerous devices which may lead to a high cost of†

Received 4 May 2019; Accepted 26 July 2019
J-STAGE Advance published online 7 September 2019
1
INP-ENSIACET-LGC, 4 Allée Emile Monso, CP 44362, 31030
Toulouse Cedex 4, France* Corresponding author: Nadine Le bolay;
E-mail: nadine.lebolay@ensiacet.fr
TEL: +33-5-34-32-36-82

244

production and may affect the reproducibility of the pro­
duct properties. Other methods such as thermal decomposition (Glasgow W. et al., 2016) or spray pyrolysis (Ozcelik
B.K. and Ergun C., 2015) were proposed as a continuous
process. However, the production capability of some ofthem is limited.
In previous studies carried out in our laboratory (Pont
V. et al., 2001; Hémati M. et al., 2003), fine particles were
produced using a hot fluidized bed reactor containingcoarse and hydrophobic beads with a diameter of over
500 μm. Aqueous solutions containing organic or inorganic salts were pulverized within the reactor. The solution was then dried at the contact of the hot beads, leading
to the formation of nano- and microparticles which werethen removed from the beads’ surface due to a strong
mixing of the fluidized medium under the effect of thefluidizing gas. This operation led to the production ofparticles having a nature identical to that of the products
in solution.
In the study presented here, we propose to add a stepwhich allows transformation of the particles leaving thefluidized bed. For this purpose, we implemented calcination after the particles’ production in the fluidized bed, inorder to produce hematite particles using a precursor
solution of iron nitrate nonahydrate dissolved in water.
The objectives are to characterize the products formedin the process, and to understand and analyze the various

Copyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Nadine Le Bolay et al. / KONA Powder and Particle Journal No. 37 (2020) 244–257

phenomena occurring in the generation and calcination
reactors. The manner in which the particles are formed in
the process is also explained. Finally, a mechanism is proposed, defining the different reaction steps appearing
during the transformation of the iron nitrate solution.

2. Experimental
2.1 Equipment and procedures
2.1.1 Fluidized bed process

The process used in this study is presented in Fig. 1.
The fluidized bed reactor is a vertical stainless steel co­lumn with an inner diameter of 0.1 m and a height of
0.5 m, filled up to half its capacity with 1.5 kg of glass
beads (diameter = 1.4–1.6 mm) and topped by a conicalfreeboard section. This conical section is closed by a lid
equipped with a guide tube for the introduction of aspraying system and an exit for evacuating gas and particles. The column is provided at its base with a vine box
permitting air homogenization. The fluidization gas distribution is ensured by a distributor made up of a perforated stainless steel plate with a porosity of 2 %, underwhich a metallic grid of low opening is fixed, whose role
is to prevent the fine particles from passing through the
distributor. Before entering the bed, the fluidizing air flowrate is measured by means of rotameters and the air ispreheated by an electrical heater (4 kW). The precursor
solution (aqueous solution of iron nitrate nonahydrate) isstored in a reservoir placed on a balance in order to control the flow rate of the solution. It is drawn up by a volumetric pump from the reservoir to an internal mixing
two-fluid spray nozzle (Spray System Co.). The atomizinggas (air) flow rate is controlled by a middle valve andmeasured by a rotameter. The atomizer is a downward

Fig. 1

facing nozzle and is located in the bed. The bed temperature is controlled by means of a PID regulator. Monitoringof temperature and pressure drop is achieved during ope­
ration.
A cyclone (0.09 m in diameter and 0.15 m in height),
with a cut diameter of around 10 μm for the operating
conditions used in this study, is placed at the fluidized bed
reactor outlet. It allows recovering particles larger than its
cut diameter (large solid particles or broken beads), while
fine particles are entrained in the gas current towards theend of the process.
Then, the gas-particle suspension supplies a second
reac­tor (calcinator). This reactor, made up of a heat resistant stainless steel tube (0.1 m in diameter and 1.7 m inlength), is heated externally by an electrical furnace(8 kW). Prior to filtration, the suspension at the outlet ofthe calcinator is cooled at 150 °C by a cold air current toavoid any degradation of the filter. The filtration is carriedout by a vibrated metallic sleeve filter containing four
compartments, each of them including one cartridge. Iron
oxide particles are recovered at the filter bottom. This filter was preferred to a cyclone because of its greater efficiency to arrest fine particles (dp > 0.3 μm).
The experimental protocol is as follows. The fluidized
bed reactor is charged with the glass beads and thenclosed. The bed is fluidized with preheated air, to reachthe set point temperature. The second reactor is also
heated and in parallel the cooling air is fed to its outlet
side. In order to reduce the thermal disturbance caused by
the liquid atomization, pure solvent (distilled water) is
initially sprayed into the fluidized bed reactor at the same
flow rate as the precursor solution. When the bed temperature returns to the set value, the distilled water is switchedwith the iron nitrate solution, and 1.5 kg of solution issprayed into the reactor. Particles are recovered at thebottom of the cyclone and the filter and are maintained in

Schematic of the process.

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a desiccator at ambient temperature before being analyzed.
The experiment was repeated 5 times with the same
operating conditions in order to verify the synthesis reproducibility.

2.1.2 Muffle furnace

In parallel, solution samples (2 g with the same concentration as the solution used in the fluidized bed process)were placed in glass cups and heated for one hour in a
muffle furnace kept at different temperatures (30, 50, 80,
100, 120, 130, 140, 150, 200, 250, 300, 400 and 500 °C).
After the treatment, the samples were removed fromthe furnace and weighed. Photos were taken and the pro­ducts were immediately analyzed.

2.1.3 Lab convective dryer

For a better understanding of phenomena occurring at
low temperatures, a lab convective dryer was used to dry
solution samples at several fixed air temperatures up to
80 °C, which is the maximum temperature in this device.
Hot air flowed parallel to the surface of a sample holder
having a disc shape covered by cotton, on which 7 g ofsolution with the same concentration as indicated above
were deposited. The sample holder was placed on a sample port pipe. It was connected to a scale (Metler Toledo
France, AT261, precision +/– 0.1 mg) in order to continuously register the sample mass, while an infrared pyrometer (Kheller, Cellatemp PQ13AF1, Germany) placed above
the sample allowed the temperature of the sample surface
to be measured in parallel.
A preliminary study showed that the air flow velocity
has a significant effect on the drying kinetics for values
lower than 0.5 m/s while the effect can be neglected forhigher values. Thus, this parameter was fixed at 0.8 m/s.

2.2 Material characterization
The particles’ composition was characterized using
Fourier transform infrared spectroscopy (FTIR TENSOR
27, Bruker Optic) and Raman spectroscopy (RAMAN
labram HR 800, Horiba Yvon Jobin). The crystalline
structure was identified by X-ray powder diffractometry(D8 ADVANCE, Bruker). The average crystallite size ofthe samples, dX-ray, was calculated from X-ray diagrams
according to the Debye-Scherrer equation:d X-ray k .
  cos(1)

where λ is the X-ray wavelength (λ = 1.5418 Å in thisstudy), θ, the diffraction angle for the (104) peak, β, thepeak width at mid-height and k, the Scherrer constant,equal to 0.9.

246

The size distribution of the particles was measured bymeans of a dry laser granulometer MALVERN Mastersizer 2000 equipped with a Scirocco. Data were treatedwith the Mie theory in order to minimize artefacts at verysmall sizes. The particles were also observed using ascanning electron microscope (SEM-FEG JSM 7100F
TTLS, JEOL). The particles’ real (skeleton) density wasdetermined using a helium pycnometer (Micromeritics
Accupyc 1330TC). Finally, the Brunauer-Emmet-Teller(BET) surface area, pore size distribution, pore volume
and average pore diameter were measured using a multigas porosimeter ASAP 2010 M Micromeritics.
Analyses were repeated 3 times to control the reproducibility of the properties.

2.3 Precursor solution
The precursor used in this study was iron nitrate nonahydrate, Fe(NO3)3·9H2O, purchased from Sigma Aldrich
France (purity ≥ 98 %, impurities: chloride, sulfate). The
properties of this precursor are the following: mean dia­meter = 150 μm, molecular weight = 404 g mol–1, solubility at 20 °C = 300 g/100 g water, melting point = 47.2 °C,
boiling point = 125 °C and real density = 1684 kg m–3.
The precursor was dissolved in water to form a solution
having a concentration equal to 66.7 wt.%, i.e. 2 kg ofiron nitrate nonahydrate per kg of distilled water, which is
89 % of the saturation concentration at 20 °C. The poro­sity and the density of this solution at 20 °C are 7.6 × 10 –3
Pa s and 1360 kg m–3, respectively.

3. Characterization of the materials producedin the process
3.1 Operating conditions
The operating conditions of the process were fixed asfollows.
Concerning the fluidized bed and the calcinator temperatures, we analyzed the variation of the mass loss ofthe solution samples in the muffle furnace (Fig. 2).
Taking into account the slope changes, four steps canbe defined:— between ambient temperature and 80 °C, with amass loss of 54.4 wt.%,— between 80 °C and 130 °C, with a mass loss of
10.1 wt.%,— between 130 °C and 150 °C, with a mass loss of
19.3 wt.%,— between 150 °C and 500 °C, with a mass loss of
3.2 wt.%.
These zones correspond to different reactions that will
be described later.

Nadine Le Bolay et al. / KONA Powder and Particle Journal No. 37 (2020) 244–257

In order to ensure that the reactions of the three firststeps occurred in the fluidized bed reactor, while the last
step took place in the calcinator since it needs a high temperature, the fluidized bed and the calcinator temperatures were set at 200 °C and 490 °C respectively. After
different attempts, the temperature of the generation reactor was fixed at 200 °C, i.e. a little above 150 °C, to be
sure that the third reaction step was achieved before theparticles left this reactor, since the residence time in thefluidized bed is shorter than in the muffle furnace. Thus,
the first apparatus is the particle generation reactor where
an intermediate material is produced, while the second
one is the transformation reactor that the final material
leaves.
The fluidization air flow rate was equal to 40 m3 h–1 at
200 °C, the corresponding velocity being equal to 1.6
times the minimum fluidization velocity of the beads
which was determined at 0.84 m s –1. The spraying air
flow rate, fixed at 1.6 m3 h–1 at ambient temperature, washigh enough in order to obtain a good dispersion of solution droplets within the fluidized bed. Finally, the mass
flow rate of the solution was equal to 0.3 kg h–1.

Concerning the precursor, one can observe different
absorption bands characteristic of nitrate at 825, 1384 and1764 cm–1, of OH stretching vibration at 3400 cm–1, of
H-O-H bending stretching vibration at 1635 cm–1 and of
atmospheric CO2 at 2360 cm–1.
As for the product recovered at the cyclone bottom,
similar bands are observed. However, the characteristic

3.2 Intermediate material
The intermediate material is produced in the solid-­
generation reactor. Given the configuration of this reactor,
particles cannot be directly sampled in the fluidized bed
during experiment. Consequently we analyzed the pro­
duct recovered at the cyclone bottom. Furthermore, to be
sure that the product recovered at the cyclone bottom isrepresentative of the product in the reactor, at the end of
the experiment glass beads were removed from the reactor after the process was stopped, and the powder adhered
to the beads was collected.

3.2.1 Composition of the productThe intermediate powder, recovered at the cyclone bottom, was characterized by infrared spectroscopy, as wellas the precursor (Fig. 3a).

Fig. 3Fig. 2Mass variation of the solution heated at different temperatures in the muffle furnace.

Analyses of the products.
a) FTIR spectrab) Raman spectrac) X-ray diagrams247

Nadine Le Bolay et al. / KONA Powder and Particle Journal No. 37 (2020) 244–257

nitrate band at 1384 cm–1 is narrower than that on the
spectrum of iron nitrate nonahydrate. In addition, threebands appear between 800 and 400 cm–1, respectively at
700, 570 and 460 cm–1, which are not present on the ironnitrate nonahydrate spectrum. These bands suggest thatthe product is ferrihydrite (Mazzetti L. and Thistlethwaite
P.J., 2002). The product was also analyzed by Raman
spectroscopy (Fig. 3b) and the spectrum confirms the nature of the intermediate product. Two forms of this pro­
duct are mainly proposed in the literature: 2-line and6-line ferrihydrites. They have similar FTIR and Raman
spectra (Mazzetti L. and Thistlethwaite P.J., 2002) but
different X-ray diffraction patterns (Majzlan J. et al.,2004). The first one shows two broad XRD peaks and thesecond one six XRD peaks. The intermediate product wasalso analyzed by X-ray diffraction (Fig. 3c). Two broad
peaks are clearly observed at 34.7° and 62.4°, indicatingthat it is 2-line ferrihydrite that is produced in the generation reactor.
Finally, some powder fixed on the surface of the glass
beads directly sampled in the generation reactor at theend of the experiment was analyzed by infrared spectroscopy and X-ray diffraction. The results confirm that 2-line
ferrihydrite was also synthesized within the dry fluidized
bed reactor and consequently did not undergo any transformation in the cyclone.

Fig. 4

Particle size distribution of the cyclone product.

Fig. 5

SEM photo of particles at the cyclone bottom.

3.2.2 Structure and morphology

The powder collected at the cyclone bottom was analyzed with a laser granulometer and a scanning electron
microscope. The particle size distribution of the powder isbetween 0.2 and 550 μm with a mean diameter (d50) of
31.4 μm (Fig. 4). SEM micrograph of Fig. 5 shows thatthe powder is made up of:— Large fragments with a size of several micrometers,on which small particles are agglomerated. Thesefragments constitute the population with sizes
higher than the cut diameter of the cyclone (10 μm).
— Smaller particles with a size lower than the cut dia­meter of the cyclone. This population contains
small microfragments and nanoparticles, andshould not be stopped by the cyclone. Their pre­sence in the sample taken at the cyclone bottom isdue to a partial desagglomeration of small particles
stuck on large fragments under the effect of the particles’ movements within the cyclone. Theseephemeral agglomerates were formed according to
Van der Waals or electrostatic forces.
These different particles populations are formed at thesurface of glass beads during solid generation. SEM micrographs of a bead surface are presented in Fig. 6. One
can observe particles with a size lower than 1 μm stuck
on a compact deposit which is cracked.
To explain the presence of both small particles and248

solid film on these photos, Fig. 7 shows different schemes
explaining the progressive behavior of the precursor solution pulverized on the beads.
During the generation step, the precursor solution ispulverized in the bed of coarse glass beads fluidized by
hot air. When the beads pass under the spraying jet, a li­
quid film is formed around them (a). This thin film is thendried and decomposed, which leads to the formation of
nanoparticles of intermediate product on the beads (b).
Some of the particles are removed from the bead surface
under a friction effect, either in an individual form or in
the form of small agglomerates, and they leave the reactor
with the air current (c). However, some particles remain
adhered to the beads’ surface. Prolonged spraying of the
precursor solution leads to a liquid deposition on thesmall particles remaining on the beads’ surface or bet­
ween them (d). The transformation of the solution thus
deposited leads on the one hand to a progressive filling of
the interstitial spaces between the particles by othernanoparticles, and on the other hand to an increase of
their size. These repeated phenomena allow the production of a solid film with a low porosity around the glass

Nadine Le Bolay et al. / KONA Powder and Particle Journal No. 37 (2020) 244–257

beads, and nanoparticles are deposited on this solid film,
as it can be seen in Fig. 6. If all these steps are repeatedthroughout the experiment, the thickness of the solid film
is increased (g). Under precursor transformations (drying
and decomposition), the film is subjected to cracking, andcollisions between beads weaken the solid phase which
can be broken and form fragments.

Fig. 6

SEM photos of a glass bead covered with powder at
4000× (a) and 25000× (b).

Fig. 7

Besides these explanations, one can also think that theresidual moisture and the sticky nature of the interme­
diate solid phase deposited on the beads’ surface generate,during collisions, an instantaneous bonding between thebeads at their contact points (solid bridge formation). The
resistance of the bridges between the beads depends onthe deformability of the solid film. Under the effect of the
bed agitation created by fluidization, these contacts arebroken, extracting a part of the solid bridges and thus
forming large fragments. However, if bonding strengths
exceed those of breakage imposed by the fluidized medium, the beads will stick to each other, the bed will forma block and fluidization will stop.
In this study, the production of nano- or microparticles
in the fluidized bed reactor may be due to:— Attrition caused by friction between the beads. Thismechanism leads to the formation of nanometricparticles that are removed from the film surface.
These particles cannot be retained by the cyclone
because of their small size and feed the calcination
reactor;— Partial removal of the solid deposit formed bybonding forces between glass beads. The solid
bridges between the beads may be broken under theeffect of the intense movement of the fluidized bed,causing a detachment of large fragments whose size
is sufficient for them to be stopped by the cyclone;— Cracking and fragmentation of the solid film depo­
sited around the beads, due to collisions between
them. Under a drying effect, the film can crack,
which is observed in Fig. 6a, and fragments larger
and more angular than fine particles can be released. Nanoparticles can stick on these fragments,
most of them ranging in size from a few micrometers to several tens of micrometers. These fragments,
an example of which is shown in Fig. 5, are stopped
by the cyclone.

Formation of a solid film and particles on the beads’ surface.

249

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In the generation zone of the process, four types of particles are formed: elementary spheroidal grains, small agglomerates of these grains, large and angular fragments,
as well as these large fragments on which elementarygrains are stuck. These two last populations of particles
are mainly stopped by the cyclone, while the two first are
essentially carried by the air flow towards the calcination
reactor. Note that the size of the fragments can be modified by fragmentation or agglomeration caused by theirinteractions with the fluidized medium that can act as aball mill.

(Cornell R.M. and Schwertmann U., 2003; Waychunas
G.A. et al., 2005; Qi P. and Pichler T., 2014). The value forour product is in the lowest range. The pore size distribution of the particles is presented in Fig. 8b. Pore diameters vary between 3.3 and 20 nm with a mean diameter
equal to 6 nm. Moreover, the pore volume is equal to0.03 cm3 g–1. This latter value corresponds to a low internal porosity of 0.1. These results suggest that particles ofthe synthesized ferrihydrite are mesoporous.

3.2.3 Surface properties

3.3.1 Composition of the product

The real density of the synthesized ferrihydrite was determined using helium pycnometry. It is equal to 3730 kg m–3
and is close to the value reported by Cornell R.M. and
Schwertmann U. (2003) which is 3960 kg m–3.
Fig. 8a shows adsorption-desorption isotherms of thesynthesized ferrihydrite. This product exhibits an isotherm of type II with a hysteresis, characteristic of a micro and mesoporous product. From this data, the surface
area was determined at 83 m 2 g–1. According to otherworks, the specific surface area of ferrihydrite depends on
the synthesis method and ranges from 50 to 400 m2 g–1

3.3 Final material
Fig. 3a shows not only the FTIR spectra of the precursor and the intermediate product, but also the spectrum of
the final product, while its Raman spectrum is presented
in Fig. 3b. These two spectra are those of hematite(α-Fe2O3). In addition, the final product was analyzed by
X-ray diffraction (Fig. 3c). All peaks are indexed to arhombohedral crystalline phase of hematite (JCPSD card
33-0664). The average crystal size of the hematite
nanoparticles was calculated from the dominant peak(104) at 2θ equal to 33.2°, using the Debye-Scherrer equation, and is equal to 47 nm. Zhu M. et al. (2012) synthesized hematite nanoparticles having a crystallite mean
size of 51.4 nm by a hydrothermal method. As for
Gurmen S. and Ebin B. (2010), they applied ultrasonicspray pyrolysis for the production of hematite particles.
The crystallite size of their nanoparticles was between 18
and 33 nm, depending on the operating conditions.

3.3.2 Structure and morphology

The particles recovered at the process outlet were analyzed with a laser granulometer. Fig. 9 shows a narrow
particle size distribution, between 200 nm and 2.1 μm,
with a mean diameter (d50) of 0.5 μm. Chin S.M. et al.
(2014) produced hematite particles through an auto-­
combustion synthesis. The size distribution of theirFig. 8250

Adsorption-desorption curves (a) and pore size distribution (b) of the synthesized ferrihydrite.

Fig. 9Size distribution of the synthesized particles.

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particles was multimodal, ranging between 0.6 and450 μm. The particles were made up of large agglomerates of nanoparticles with a size from 60 to 140 nm. Theseauthors indicate that drying and dry grinding do not allow
individualizing nanoparticles. Ozcelik B.K. and Ergun C.
(2015) produced spherical α-Fe2O3 particles via spray pyrolysis. Agglomerates of elementary particles were observed with an average diameter between 315 nm and1.16 μm, depending on operating conditions. The average
diameter of their elementary particles was between 70
and 320 nm. Tan W.-F. et al. (2014) obtained monodispersed hematite nanoparticles through chemical precipitation. It was possible to control the morphology of the
α-Fe2O3 samples by the synthesis conditions, whichyielded spherical particles (diameter 50–80 nm) or elliptic
particles (diameter of 50–80 nm and length of 250–
300 nm).
A SEM micrograph of particles recovered at the filter
bottom is presented in Fig. 10a. They are made up of
spherical nanoparticles mostly individual or weakly agglomerated, since the agglomeration tendency is low, under the effect of interparticle forces. The smaller

Fig. 10 SEM micrograph of synthesized particles (50000×) (a)and size distribution of the elementary particles (b).

elementary spherical particles are rather compact andtheir surface is smooth, while the larger ones are nanostructured. Concerning the small particles, one may suggest that they are the result of fine droplets of spraydrying in the air before reaching the beads’ surface. As
for the nanostructured particles, the plastic character ofthe precursor during its transformation is at the origin of
their formation.
The size distribution of the elementary particles wasdetermined using SEM images treatment, by analyzing
about 1000 particles (Fig. 10b). Half of the elements havea size lower than 100 nm, which can be related to the ave­rage crystal size (47 nm) calculated from X-ray diffraction
data in Section 3.3.1. As for the elements having a size
higher than 100 nm, one can consider that they corres­
pond to the large nanostructured elements.

3.3.3 Surface properties

Helium pycnometry analysis was used to determine thereal density of the synthesized powder which is equal to4499 kg m–3.
BET results (Fig. 11) show that:— The adsorption-desorption isotherms curves are of

Fig. 11 Surface properties of the synthesized hematite:adsorption-desorption curves (a) and pore size distribution (b).

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type III, which is characteristic of a crystalline
product with a low specific surface area. This one
was determined from these data and is equal to
24 m2 g–1.
— The total pore volume is equal to 0.03 cm3 g–1.
— The pore size diameters are between 1.8 and 10 nmwith a mean pore diameter of 6.5 nm.
From these results, an internal porosity, χ, of the formulated product equal to 0.12 was calculated using the equation:


Vpore
1
 Vpore(2)where ρ is the real density of Fe2O3 nanoparticles andVpore the specific total pore volume.
Taking into account this porosity and assuming that theagglomerates consist of spherical nanoparticles, the mean
diameter of the nanoparticles was calculated by:
dp 

6 (1   )S BET (3)This mean diameter is estimated at 47 nm and is similar to the crystal size determined in section 3.3.1.
These results suggest that the particles are agglome­
rates of crystallites. The low value of the internal porosity
indicates that a particle can be considered as a consolidated granular medium whose pore network is the space
between the crystallites. Indeed, the change in the physical state and the mechanical and thermal stresses exerted
by the fluidized bed on the precursor during its transformation may be at the origin of the formation of sphericalsolid particles.
Housaindokht M.R. and Pour A.N. (2011), applying a
microemulsion method, obtained a mean pore diameter inthe range of 7.1–29.1 nm and a total pore volume of bet­
ween 0.16 and 0.21 cm3 g–1, depending on the operating
parameters used in their study. Ahmmad B. et al. (2013),
using a biosynthesis method, found a lower pore size distribution, comprised between 3 and 15 nm with a total
pore volume of 0.03 cm3 g–1.
In the dry fluidized bed process used in this study, significant forces are imposed, which lead to the synthesis ofspherical solid particles. These particles are constituted of
agglomerates of crystallites held together by bonding
forces. These agglomerates are rigid and ordered underthe effect of external forces.
Regarding the production efficiency, it is equal to theratio between the mass of the powder recovered at the filter bottom and the mass expected from conversion of the
precursor injected into the process. For the operating conditions fixed in this study, it is about 75 %. Indeed, a252

small amount remains in the fluidized bed (on the beads’
surface) while the main lost powder is stopped by the cyclone. This efficiency depends, on the one hand, on thesurface properties of the glass beads, and, on the other
hand, on the fluidized bed movement which is strongly
impacted by the operating conditions. In particular, ahigher fluidization velocity enhances the mixing of thebeads in the fluidized bed, leading to a decrease of thesolid film thickness around the beads and of the size ofthe fragments removed from the beads’ surface. This will
be analyzed in detail in a further study.

4. Reaction mechanisms
To our knowledge, no study is presented in the literature on the reaction mechanism of the thermal decomposition of an iron nitrate solution. Few works based onthermogravimetric and differential thermal analyses weredone on the mechanism of thermal decomposition of ironnitrate nonahydrate powder into hematite. However, theauthors do not agree on the nature and the number of mo­lecules removed during the first reactions, or on the intermediate material formed:— Removal of 9 molecules of water to form anhydrous
iron nitrate (Keely W.M. and Maynor H.W., 1963;
Mu J. and Perlmutter D.D., 1982; Pereira Da Silva
C. et al., 2018); 7 molecules of water (Gadalla A.M.
and Yu H.F., 1990; Elmasry M.A.A. et al., 1998;
Melnikov P. et al., 2014); 6 molecules of water and
1 molecule of nitric acid (Erri P. et al., 2004;
Wieczorek-Ciurowa K. and Kozak A.J., 1999; Tong
G. et al., 2010);— Intermediate material: Fe2O3·3H2O (Gadalla A.M.
and Yu H.F., 1990), Fe(OH)3 (Elmasry M.A.A.
et al., 1998) or FeOOH (Erri P. et al., 2004;
Wieczorek-Ciurowa K. and Kozak A.J., 1999; Tong
G. et al., 2010).
Other authors suggested ferrihydrite as the intermedia­te material but they did not propose any reaction
mechanism (Bødker F. et al., 2000; Oliveira A.C. et al.,
2003; Rzepa G. et al., 2016). The reason may be that the
ferrihydrite formula is not well defined.
The thermal decomposition of the solution of iron nitrate nonahydrate involves various reactions in four steps,
as seen in Fig. 2. The study on the reaction mechanism ispresented below.
The process configuration does not allow taking samples over time and at different temperatures within thesolid generation reactor. In addition, setting the temperature of the fluidized bed at a value lower than 100 °C leads
to a risk of caking of the bed due to a too slow drying of
the solution and creation of solid bridges between thebeads. Consequently, it was decided to carry out the study

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using the muffle furnace. This work was completed byexperiments carried out in the lab convective dryer des­cribed in Section 2, in order to define more precisely thephenomena occurring at temperatures lower than 100 °C.

4.1 Results obtained with the muffle furnace
The 13 samples heated in the muffle furnace at different
temperatures were all analyzed by FTIR spectroscopy.
Some spectra are presented in Fig. 12. The product obtained after the third step and the final product were also
analyzed by X-ray diffraction (no diagram presented) tocontrol that they are ferrihydrite and hematite, respectively. Moreover, some photos of the samples are shownin Fig. 13.
Studying the first step of the mechanism between ambient temperature and 80 °C, one can say from the two
first photos and the two first FTIR spectra that the solution dries progressively as the temperature increases andits color changes. A solid film is formed at the sample
surface. Since the two FTIR spectra are similar, no reaction occurs. Thus the mass loss of 54.4 wt.% of the initialsolution sample is only due to the removal of water. This
mass loss corresponds to the elimination of the water
added to the precursor powder to make the solution, andof seven molecules of water of hydration of iron nitratenonahydrate (dehydration). Consequently, after this step,
the sample is made up of iron nitrate dihydrate.
Concerning the second step of the mechanism between
80 and 130 °C, the samples become pasty and brown. On
the FTIR spectra, the width of the nitrate peak at
1384 cm–1 is reduced, while three bands with a low intensity appear between 800 and 400 cm–1. The calculated

Fig. 12 FTIR spectra of samples heated in the furnace.

mass loss of 10.1 wt.% of the initial solution sample corresponds to the elimination of one molecule of nitrate.
As for the third step between 130 and 150 °C, with amass loss of 19.3 wt.% of the initial solution sample, thenitrate peak on the FTIR spectrum becomes narrower, indicating that nitrate is still eliminated, and the bands bet­
ween 800 and 400 cm–1 continue to evolve, to come close
to those of ferrihydrite. The samples are dark brown andunder a powder form.
Finally, the fourth step ranges between 150 and 500 °C,
with a mass loss of 3.2 wt.% of the initial solution sample.
The powder color changes from dark brown to red. The
nitrate peak has totally disappeared and the bands bet­
ween 800 and 400 cm–1 have significantly changed tomatch those of hematite. Thus the residual nitrate is removed, as well as the two last molecules of water, calledhydroxylation water. During this step, ferrihydrite istransformed into hematite.

4.2 Results obtained with the convective dryer
During the first step in the muffle furnace, more thanhalf of the solution mass is lost. In order to understandhow the molecules of water are removed, the lab convective dryer described in Section 2 was used to dry thesolution between 40 and 80 °C.

4.2.1 Water drying

A first series of experiments was performed with distilled water in order to have a reference. Fig. 14 shows thevariation with time of the water mass, the temperature of
the water surface and the drying rate for an air temperature fixed at 80 °C.

Fig. 13 Photos of samples heated in the furnace.

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Three zones are observed on the figure:— Prior to 380 seconds, the water sample is heated by
hot air, and its temperature increases rapidly. This
leads to an increase in equilibrium vapor pressure(i.e. saturating vapor pressure). This first zone iscalled initiation period.
— Between 380 and 3000 seconds, the water temperature is constant and equal to 48.8 °C, the mass decreases linearly and the drying rate is constant.
Water is evaporated, and the water molecules havea low binding energy. The evaporation enthalpy ofwater is due to the energy supplied by hot air. The
partial pressure of water vapor at the surface of thewet cotton (equilibrium pressure) is that of the saturating vapor of water at the sample temperature.
This second zone is called drying period at constantrate.
— Above 3000 seconds, when almost all the weakly
bound water is eliminated, the cotton temperature
increases rapidly to reach the set point value fixed
at 80 °C. An increase in binding forces between thelast water molecules and cotton, as well as a combination of convective transport and resistance of water transfer from the cotton inside to the surface
lead to a decrease of the water partial pressure at
the surface (equilibrium pressure), and consequently to a slowdown of the evaporation rate. The
supplied heat is higher than that necessary for eva­
poration, and thus the temperature of the cotton

Fig. 14 Water drying in the convective dryer at 80 °C. Variation of (a) the mass and the temperature of the cotton
surface, and (b) the drying rate.

254

surface increases to reach a new equilibrium stateat which the cotton temperature becomes equal tothat of the hot air. This third zone is called drying
period at decreasing rate.
For other experiments on water drying, the air temperature was fixed at 40 and 53 °C. Similar curves wereobtained, with a temperature of the cotton surface in thesecond zone at 27.8 and 34.8 °C respectively, i.e. the sample temperature increases with air temperature. Furthermore, when increasing this parameter, the drying rate isincreased and the evaporation time is reduced.

4.2.2 Solution drying

The precursor solution was then dried at different air
temperatures in the convective dryer. Fig. 15 shows theinfluence of this parameter on the mass and the temperature of the sample surface during drying.
Different points are added on the curves, defining themass loss corresponding to the removal of the solution
water, of the solution water + 2 molecules of water of hydration in iron nitrate nonahydrate, of solution water + 4
molecules of water of hydration, and of solution water + 7
molecules of water of hydration. This last point is present
only for the two highest temperatures since it was notpossible to reach this level at 40 and 53 °C.
Based on these results and on the evolution of the drying rates (curves not presented), it was possible to delimit
5 zones (Fig. 15b) whose time ranges decrease when the
air temperature increases.

Fig. 15 Effect of the air temperature on the solution drying.
Variation of (a) the mass and (b) the temperature of thesample surface during the treatment.

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Zone 1 is characterized by a rapid increase of the sample temperature up to a value depending on the air temperature, as well as a rapid increase of the evaporation
rate. The mass loss is around 3 wt.% of the initial solution
mass, whatever the air temperature. As for water drying,
this zone is an initiation period.
Zone 2 is still characterized by an increase of the sample temperature, but this increase is more moderate thanin zone 1. Moreover, the evaporation rate is constant. In
this zone, called drying period at constant rate, the water
removal leads to an increase of iron nitrate concentrationin the sample, and consequently to an increase of the surface temperature. The mass loss during this period isaround 25 wt.% of the initial solution mass for all the airtemperatures. After the two first periods, the concentration of iron nitrate in the solution had increased from 0.67
to 1.27 g per g of water. This concentration corresponds
to the elimination of 85 wt.% of the added water of thesolution. At 40 °C, it is equal to 73 % of the saturation
concentration of iron nitrate.
In zone 3, the increase in the surface temperature isslightly higher than in zone 2, while the evaporation rate
decreases. During this period of drying at decreasing rate,
the mass loss is about 11 wt.% of the initial solution mass
for all the air temperatures. At the end, all the water used
to form the solution is evaporated, as well as 2 moleculesof water of hydration, and the concentration of iron nitratein the solution still increases. For example, it reaches 1.1
times the saturation concentration at 40 °C. The chemical
formula of the product obtained at this stage isFe(NO3)3·7H2O. The decrease in the evaporation rate may
be explained by the fact that the high iron nitrate concentration may modify the medium consistency and thus theresistance of water transfer from the medium inside to its
surface. The product becomes viscous, and one can evensuggest that at low temperatures, a crystallization/precipitation phenomenon begins since the iron nitrate concentration is higher than the saturation concentration.
In zone 4, the sample temperature rises very slowly toreach the set point. The mass loss in this zone is about
15 wt.% and corresponds to the elimination of the 5 othermolecules of water of hydration, leading to iron nitrate
dihydrate, Fe(NO3)3·2H2O. The evaporation rate decreases
compared to the previous steps, due to a higher viscosityof the medium and the probable presence of solid particles
that slow down water migration in the medium. This corroborates the observation of the solid film observed on thesample surface treated at 80 °C in the muffle furnace. The
elimination of these 5 molecules of water is thus a slow
phenomenon.
Finally, the temperature in zone 5 is constant while themass still decreases due to the onset of the elimination of
HNO3 already discussed when analyzing the results of the
muffle furnace.

It can be observed in Fig. 15 that the different pheno­mena described above are accelerated by an increase intemperature. Indeed, the heat supplied to the sample increases, and so does the saturating vapor pressure of water. Thus, the drying kinetics is enhanced, and the time
ranges of the various zones are reduced.
The total mass lost during the 4 periods of water elimination in the convective dryer is 54 wt.% of the initialsolution mass. It is similar to the mass lost during the firststep of the mechanism in the muffle furnace (54.4 wt.%).

5. Conclusions
Hematite nanoparticles were synthesized in a compact
and simple process where a solution of iron nitrate nonahydrate was pulverized, dried and transformed in a flui­dized bed reactor containing glass beads to produce
particles that were then submitted to calcination in an entrained bed reactor. Different analytical techniques havemade it possible to characterize the produced materials,
to determine their properties and to propose a reaction
mechanism.
An intermediate product called ferrihydrite is producedin the fluidized bed reactor. The product leaves the reactor
in different forms: on the one hand a solid film whichcoats the beads is cracked during drying and is fragmented under the effect of high stresses caused by the
movement of the fluidized bed, to generate micron-sizedparticles that are retained by the cyclone, and on the other
hand nanoparticles that are removed from the glass beads’
surface to be entrained in the calcination reactor where
they are transformed into hematite (α-Fe2O3). These particles are individual or hardly agglomerated. Their size distribution is narrow and monomodal (between 0.2 and2.1 μm). The particles produced are small agglomerates ofcrystallites whose size is about 47 nm. They can be considered as a consolidated porous granular medium because of the low internal porosity (0.12).
The heat treatment of the solution of iron nitrate nonahydrate in a muffle furnace and in a lab convective dryer
has allowed the proposal of a reaction mechanism definedin different steps. First, the water added to make the solution is lost as well as two molecules of water initially contained in the precursor. This elimination is rapid andleads to Fe(NO3)3·7H2O. Then, five other molecules ofprecursor water are removed slowly to form iron nitrate
dihydrate. These two steps occur below 80 °C. Between
100 and 200 °C, iron nitrate dihydrate is decomposed into
ferrihydrite with the elimination of nitric acid and nitrate.
These different steps take place in the fluidized bed reactor from which ferrihydrite particles are entrained by thefluidizing air. Finally, above 200 °C, ferrihydrite is transformed into hematite in the calcination reactor, with a255

Nadine Le Bolay et al. / KONA Powder and Particle Journal No. 37 (2020) 244–257

removal of the residual nitrate and of hydroxylation water.

Nomenclaturedp
dX-ray
k
SBET
Vpore
β
θ
λ
ρ
χ

Particle mean diameter (m)Average crystallite size (m)Scherrer constant (–)
Specific surface area (m 2 g–1)
Total specific pore volume (m3 kg–1)
Peak width at mid-height (m)Diffraction angle (°)
X-ray wavelength (Å)
Real density (kg m –3)
Internal porosity (–)

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Authors’ Short Biographies
Nadine Le Bolay
Nadine Le Bolay is Professor in chemical engineering in ENSIACET-INP at Toulouse.
Her research focuses on particle technology and characterization of minerals and polymers, and was applied in different fields such as fluidized bed processes, electrochemical
reactors, polymerization reactors, grinding and co-grinding processes, composite materials.

Rihab Lakhal
Rihab Lakhal obtained a PhD in process engineering at the University of Toulouse in
2016. During her thesis, she worked on a new process for the synthesis of iron oxide
nanoparticles based on a particle generation step in a fluidized bed reactor followed by acalcination step in an entrained reactor. She focused on the reaction mechanism and kinetics and the powder characterization.

Mehrdji Hemati
Mehrdji HEMATI is Professor in chemical engineering in ENSIACET-INP at Toulouse.
His research activities focused into three items:
Hydrodynamic and transfers in dense and circulating fluidized bed. Two approaches
were developed: the experimental approach and the theoretical approach.
Application of fluidized bed in the field of chemical reaction gathering catalytic reactions, gas-solid reactions (biomass and sewage sludge pyrolysis, gasification and combustion).
Processes for elaboration of materials gathering: drying, mixing, size enlargement by
spray coating and granulation, dry impregnation in F.B.
He is author and co-author of more than 100 publications in international scientific journals.

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KONA Powder and Particle Journal No. 37 (2020) 258–264/Doi:10.14356/kona.2020015

Original Research Paper

Electrodynamic Sorting of Industrial Scrap Metal †James R. Nagel, Dave Cohrs, Jacob Salgado and Raj K. Rajamani *1

Department of Metallurgical Engineering, University of Utah, USA

Abstract
Electrodynamic sorting (EDX) is a new technology developed to sort industrial scrap metals. Under the present
embodiment, an electromagnet is placed directly underneath a conveyor belt and then excited by an alternating
electrical current to produce a time-varying magnetic field. As scrap particles pass through the field overhead,electrical eddy currents are induced throughout their volumes and then repelled away. If the frequency of
excitation is very high (e.g., 12 kHz), then the lightweight aluminum particles tend to jump far more dramaticallythan heavier materials like copper, brass, and zinc. To demonstrate the principle, a small-scale prototype wasassembled and tested. Using an 8-inch (20 cm) lane width, the system could process industrial scrap Zorba at a
throughput of over 550 lbs/hour (225 kg/h) with an aluminum grade of 97.6 % and a recovery of 93 %.
Keywords: eddy currents, recycling, scrap metal waste

1. Introduction
One of the greatest challenges in the metal recycling
industry is the problem of sorting. Scrap metals rarely
present in a clean, high-purity state, but instead tend to
manifest as dirty mixtures of several distinct metals bundled together. Such contamination can dramatically reduce the economic value of an otherwise pure material,
which means recyclers will often go to great lengths toseparate metals down to their base constituents.
Depending on the specific material properties, someseparation processes might be relatively straightforward
to implement. Most notably, ferrous metals like iron andsteel will strongly react to an applied magnetic field andcan thus pull away from any other nonmagnetic materials
nearby. Known simply as magnetic separation, the technology is typically embodied as a special array of permanent magnets, and it is a popular method for extracting
ferromagnetic metals from shredded automobile waste(Oberteuffer, 1974; Svoboda and Fujita, 2003).
Another widespread technology is called eddy current
separation (ECS), which utilizes a time-varying magnetic
field to extract nonferrous metals from nonmetallic fluff.
Typically, ECS is embodied as a mechanically rotating
drum of permanent magnets, though other configurations
are possible as well. A comprehensive historical review of†1*

Received 28 May 2019; Accepted 8 July 2019
J-STAGE Advance published online 18 September 20191135 S 1460 E, ROOM 412, Salt Lake City, UT 84112-0102, USA
Corresponding author: Raj K. Rajamani;
E-mail: raj.rajamani@utah.edu
TEL: +01-801-581-3107

258

ECS can be found in Smith et al. (2019) while Nagel(2018a) provides a detailed mathematical description of its
underlying physics. In brief, the process works by inducing electrical eddy currents to flow throughout the interiorof conductive particles as they pass through the timevarying magnetic field of the ECS. The relative motion
between the electrical currents and the applied magnetic
field then results in a net force of deflection that causes
conductive particles to jump up and away from the applied field. In contrast, low conductivity materials (mostnotably, nonmetals) do not allow any significant eddy currents to flow throughout their interiors and thus experience no significant force of deflection.
Due to the widespread use of ECS among auto-shredding
facilities, there is a tendency to produce relatively similar
mixtures throughout the industry. In particular, one of
the more common products is called Zorba, which isloosely defined as any combination of nonferrous scrap
metals that is predominantly aluminum (ISRI, 2016). At
present, Zorba is an especially difficult material to sort,and there does not yet appear to be any clear technological solution to the problem. For example, dense media
separation attempts to exploit the disparity in mass density between so-called “light” metal fractions (e.g., aluminum and magnesium) and the “heavies” (e.g., copper,
brass, and zinc) (Lee et al., 1994). Unfortunately, the process is prohibitively expensive to implement, and so very
few recycling facilities are willing to invest in such an
operation. Alternatively, hand sorting can be a viable
method of separating Zorba, but only when the cost of human labor is very low (Taylor, 2017). It is also particularly
difficult to sort the so-called “fine” materials with thisCopyright © 2020 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

James R. Nagel et al. / KONA Powder and Particle Journal No. 37 (2020) 258–264

method (e.g., less than 3 cm), since each individual particle must be inspected and separated.
One emerging technology that addresses such limitations is called electrodynamic sorting (EDX). The principle is similar to a traditional eddy current separator inthat a time-varying magnetic field is used to induce eddy
currents in scrap metal particles. However, rather than rotate a mechanical array of permanent magnets, the EDX
system excites a fixed electromagnet with an alternating
electrical current. This allows the frequency of excitation
to reach far beyond the limits of a mechanical system, and
it is capable of separating materials by both electricalconductivity and mass density.
In one EDX embodiment, Dholu et al. (2017) used awire-wound, gapped toroid to generate a magnetic field at
6.5 kHz. The gap was then fed with 12.5 mm spheres ofcopper, aluminum, and brass, which were all sorted withperfect grade and recovery. The system was then operated
at a frequency 1.9 kHz to sort aluminum spheres by alloy
composition. The results were likewise very impressive,with grade and recovery values reaching well-above
90 %. In another embodiment, Smith et al. (2017) used asimilar gapped toroid at 21.4 kHz to separate aluminum
particles from silicon and CdTe as a simulation of shredded photovoltaic waste. Although the particles were muchsmaller (1–3 mm) and nonuniform, the grade and recovery values still reached above 95 %.
Despite the many advantages of EDX, the embodimentof a gapped toroid suffers from at least three limitations.
The first limitation stems from the gap itself, which introduces a small bottleneck through which material must be
fed. This bottleneck heavily restricts throughput, thereby
preventing EDX from processing materials on the scalerequired by modern industrial recyclers (typically many
tons per hour). A second limitation arises from the geometry of scrap material itself, which often manifests as
thin, flaky particles. When fed into a gapped magnetic toroid, flat particles tend to orient themselves along theminimum cross-sectional area with respect to the appliedmagnetic field. This reduces the deflection forces experienced by such particles, thereby lowering the effectiveness of EDX as a sorting process. A third limitation arises
when magnetic particles (e.g., iron and steel) accidentallyenter the magnetic gap. While conductive, nonmagnetic
particles repel away from the applied magnetic field, magnetic particles are instead pulled directly in. The result isthus a clogged gap that greatly impedes the performanceof the sort.
To alleviate the limitations of a gapped toroid, this paper proposes the new EDX embodiment depicted inFig. 1. Rather than drop material through a gap, the electromagnet core is instead oriented upright and then embedded directly underneath a conveyor belt. Doing so
dramatically improves the throughput of the system, sincematerial can now flow freely over the top of the magnet
rather than funnel through a narrow bottleneck. It canalso operate on thin, sheet-like particles, since gravity
now forces them to orient along the direction of maximum cross-sectional exposure to the magnetic field. The
embodiment is further robust against any accidental exposure to ferrous material because the presence of theconveyor belt naturally prevents particles from getting
pulled into the gap.

2. High throughput EDX
As a demonstration of the new embodiment, the authors constructed the small-scale prototype depicted inFig. 2. The system begins with a vibratory feeder thatsteadily pours scrap material onto a conveyor belt, after
which it is rapidly accelerated up to a constant horizontal
velocity of 2.0 m/s. Embedded directly within the conveyor
assembly is an electromagnet core that is excited by analternating electrical current. The tips of the electromagnet
are placed in direct contact with the underside of theconveyor belt so that scrap particles pass directly throughthe magnetic field overhead. Depending on such factors
as electrical conductivity, mass density, and physicalgeometry, some of the particles will repel up and away

Fig. 1

Schematic diagram of the EDX embodiment with electromagnet cores placed directly underneath the conveyor belt.

Fig. 2

Prototype assembly with major components indicated.

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James R. Nagel et al. / KONA Powder and Particle Journal No. 37 (2020) 258–264

from the magnet and are thus referred to as “throws.”
Likewise, any particles that pass through the field without
any significant deflection are simply referred to as “drops.”
A mechanical splitter is then used to separate the throws
from drops, which collect in their corresponding bins
underneath. Finally, due to the excessive heat that builds
up in the electromagnets, an axial flow fan is used to circulate air through the cores and maintain stable temperature.
Fig. 3 shows a close-up photograph of the electromagnet core that was embedded within the conveyor belt assembly. Since the cross-sectional shape is somewhat
reminiscent of the letter U, the authors chose to refer to it
as a “U-core” geometry. At the top of the U are the tips,
which were specially designed to funnel magnetic flux
into a small volume of space overhead. The legs of the U
are then wrapped with insulated copper wire that is excited by an alternating electrical current of 7 Apk per coil.
At the bottom of the U is a base section to connect thelegs together and stabilize the structure. The core length
is then divided into three sub-sections, with each coil section electrically connected in parallel. Total core dimensions are roughly 20-cm length, 8.6-cm thickness, and12-cm height.
The basic geometry of the U-core appears to have been
conceived as far back as 1972 (Trondle, 1972), but seems
to have only been used to remove nonferrous metals fromnonmetallic minerals. Most likely, the earlier embodiments could not be excited at very high frequency or elsethe internal generation of eddy currents would rapidly
heat the core beyond safe limits. For this reason, it is vitalto choose a magnetic core material with both low conductivity and low hysteresis loss, and such materials may nothave been commercially available so long ago. Fortunately, MnZn ferrites are now widely accessible, and theyreadily satisfy many of the desirable properties for an
EDX core. Even so, the excessive drive current and magnetic field intensity still tends to generate a significant
amount of heat throughout the core, and so it was necessary to circulate air with an axial flow fan in order tomaintain stable temperatures.
In order to drive a sufficient electrical current throughthe EDX coils, it was necessary to utilize the circuit dia-Fig. 3260

Electromagnet core and windings.

gram in Fig. 4. A signal generator begins by exciting thecircuit with a sinusoidal voltage, which is then boosted bya high-power amplifier (20 V/V gain) to provide the necessary high-level drive current. The rest of the circuit thenconsisted of a series connection between some lumped
capacitance C, a parallel connection of six inductors, anda small 0.1-Ω resistor for current sensing.
The most noteworthy feature of the electrical circuit is
the parallel connection between coils. Electrically speaking, each coil around the core may be treated as a large,
lumped inductance with some equivalent series resistance(not shown). In principle, the coils could simply connect
in series, but doing so would result in a total inductanceof about 50 mH or more. If we then imagine exciting themagnet at 7.0 Apk and a frequency of f0 = 12 kHz, the resulting voltage drop across the coils would exceed 26 kV.
Since this is well beyond safe or practical, it was necessary to connect the coils in parallel, thereby reducing theimpedance of the circuit. Specifically, if the current is divided among N coils, then the total inductance of the circuit falls by a factor of N 2. Thus, when the circuit wasconnected into 6 parallel coils, the net inductance fell to amere 1.3 mH. The trade-off to this approach is that total
current must increase by a factor of 6 in order to maintaina consistent current density across the windings. Even so,when the coils were excited to a peak current of 42 Apk,
the coil voltage dropped to a manageable value of only
4.4 kV.
The final component of the circuit is capacitance, whichmust be chosen carefully to specify the desired resonant
frequency. In particular, the resonant frequency of a series RLC circuit is given as
f0 =

1
2π LC

(1)

Thus, to excite a 1.3 mH inductance at a frequency of
12 kHz, the necessary capacitance evaluates to roughly
135 nF. In practice, however, there does not exist a single
commercial device with such capacitance that can also
withstand a full 42 Apk of current. The capacitance wastherefore divided among multiple 10 nF units that were

Fig. 4Circuit diagram of the EDX drive electronics.

James R. Nagel et al. / KONA Powder and Particle Journal No. 37 (2020) 258–264

likewise connected in parallel (depicted as the single,
lumped capacitance C in Fig. 4). Once assembled, thesystem was found to resonate at a frequency of 12.7 kHz.

3. Separation theory
The simplest mathematical model for a scrap metal
particle is that of a sphere with radius a and a uniform
conductivity σ. The sphere is then excited by a time-­varying magnetic field in sinusoidal steady state with angular frequency ω and a peak field intensity B0 at thecenter. The magnetic field is also assumed to have a weak,
linear gradient dB/dx along the x-direction, resulting in anet, time-averaged force Favg that points along the direction of negative slope. Building on the work of Rony
(1965) and Lohöfer (1989), we may calculate Favg using
3B0 R 3  1 1 sinh (q)  sin (q)  dB,
Favg 
0  3 q cosh (q)  cos (q)  dx(2)where q = √2μ0 σωa2. Although Eqn. (2) is technically anapproximate expression, Ray et al. (2018) measured theforces on metal spheres under magnetic excitation andshowed it to be remarkably accurate.
Fig. 5 shows the calculated forces acting on 10 mm
spheres with differing values of conductivity. In all cases,
the applied magnetic field was set to B0 = 50 mT with afield gradient of dB/dx = 1.0 T/m. The top graph shows
σ = 60 MS/m, which is typical for such metals as copperand silver. At the bottom end is σ = 10–20 MS/m, which istypical for such metals as cast aluminum, brass, and zinc.
The key insight from this analysis is that, in the limit asf→∞, all forces tend towards the same, asymptotic valuethat is independent of conductivity. Acceleration, however, still depends on the overall mass of the particle,

Fig. 5

Net force acting on a 10 mm conductive sphere as afunction of excitation frequency. The peak magnetic
field intensity is B0 = 50 mT with a field gradient of
1.0 T/m.

which is a function of mass density and physical geometry. For example, aluminum has a density of roughly
2.7 g/cm3 while copper has a density of about 9.0 g/cm3.
The implication is that, with all other parameters held
equally, a particle of aluminum will experience threetimes the acceleration of an equivalent copper particle. A
high-frequency EDX assembly can thus be treated as a
sophisticated density sorter.
Although the spherical model is very straightforward,
there are many scrap particles that do not fit well intosuch a category. In particular, thin metal sheets are acommon manifestation in any stream of fine Zorba, and itis necessary to apply complex numerical methods whencalculating force and torque. Most notably, the work of
Nagel (2018b) provides a simple finite-difference schemethat rapidly calculates of the eddy current density in thinrectangular sheets.
The most significant distinction between thin sheets
and bulky spheres is that thin sheets throw far more dramatically after passing through the field of an EDX core.
The reason is primarily due to the way in which metal
sheets lie flat on the conveyor assembly, thereby exposing
them to a much greater magnetic field intensity. The result
is a much greater excitation of eddy currents and thus amuch greater throw length. A practical consequence of
this effect is that the new EDX embodiment can also sortparticles by physical geometry as well as electrical conductivity and mass density.

4. Test procedure
To demonstrate the new EDX configuration, the authorsacquired a 6000-lbs (2700 kg) sample of fine Zorba froma local scrap recycling firm. Depicted in Fig. 6, the material was primarily distributed between 5–25 mm in size,
thus earning it the nickname of “one inch minus.” Thesimplest separation that can be performed by EDX is a removal of the light aluminum fraction from the heavies,
which is very similar to what a dense-media plant would
attempt to perform. To divide the labor into manageable
chunks, the material was hand-shoveled into 5-gallon
buckets and then processed one bucket at a time. Eachbucket of material was weighed, sorted, and then weighedagain after collecting into the throw/drop bins. Finally,
after every tenth bucket, we extracted a small sample ofmaterial (≈ 1 kg) from the initial mixture, the throw pile,and the drop pile. All samples were then analyzed formetal composition using a portable XRF analyzer, whichwere then averaged to give the final composition. The entire procedure took about 3 days to complete.
It is important to note that the use of XRF analysis isdifferent from a direct chemical analysis. The reason is
because most common metals are actually complex alloys

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of many different elements put together. Thus, a complete
chemical breakdown would not provide any insight into
the probability of throwing or dropping a given particle.
To that end, it is necessary to treat each scrap particle as
an individual unit unto itself, rather than an amalgamationof chemical elements. The authors therefore divided thefeedstock into four distinct categories to reflect their primary alloy composition. This information was then used
to calculate the resulting probabilities of throw and drop
for the various metal compositions. The categories arethus summarized as:• Al (Wrought/Cast): The most common componentof Zorba is aluminum, which can take the form of either cast alloys or wrought alloys. Cast alloys typically contain about 8–10 % Si, 2–5 % Cu, and 1–2 %Zn, while wrought alloys are typically comprised ofabout 96–98 % aluminum with a small percentage ofother trace elements.
• Cu (Free): This category indicates any piece of relatively pure copper, such as copper pipe or copper
wire, that is 96 % copper content or more.

• Brass/Bronze: The most common alloys of copper
are brass and bronze, which typically vary between
60–90 % copper content plus significant amounts ofZn and Sn.
• Zinc/Other: Free zinc is the most common remaining
metal in the heavy fraction. There also tends to be asmall amount of other trace metals, such as Cr, Sn,and stainless steel, but these are usually too insignificant to bother accounting for.

5. Results and discussion
Fig. 6 provides photographs of the initial mixture, followed by typical throw and drop samples after sorting.
Note that all images have been color-enhanced to help
bring out the distinctly red and yellow hues of the copperand brass. Table 1 provides a summary of the XRF analysis for each category.
Over the course of the sort, it was found that throughput could vary quite significantly as a result of the vibratory feed rate and material composition. Although it could
potentially reach as high as 800 lbs/h, the materials
tended to collide with each other around the divider andreduce grade/recovery. It was eventually decided that afeed rate of about 550 lbs/h (250 kg/h) was a practicalthroughput for the 20-cm lane width.
The next metric of interest is power consumption,
which was measured by probing the output voltage anddrive current with an oscilloscope. Under normal operating conditions, the power amplifier would deliver a peakvoltage of 33 V and a peak current of 36 A. The net,time-averaged power consumption of the entire magnetic
assembly was therefore about 600 W. It is important tonote, however, that a significant fraction of this power
consumption appeared to be a result of coupling between
the magnetic core and the metal frame around it. Although it is difficult to be sure how much power waswasted as a result, it was most likely in the range of about
100–200 W. The implication is that, in principle, the magnetic core itself may only need to dissipate about 400 W
during operation. After further accounting for the power
consumption of the vibratory feeder (≈ 400 W), theTable 1 Percent composition of Zorba before and after sorting.

Fig. 6262(Top) Scrap metal feedstock consisting of fine Zorba
donated by a local recycling firm. (Middle) Light aluminum fraction thrown by the EDX sorter. (Bottom)
Heavy fraction in the drop bin.

Category

Pre-Sort

ThrowsDrops

Al (Wrought/Cast)

71.4

97.6

15.0

Copper (Free)

4.4

0.5

12.7

Brass/Bronze

11.3

0.6

34.3

Zn/Other

12.9

1.3

38.0

Weight Percentage

100

68.3

31.7

James R. Nagel et al. / KONA Powder and Particle Journal No. 37 (2020) 258–264

conveyor drive motors (≈ 200 W), and a 50 % efficiency
within the power amplifier, the total power consumption
for the entire EDX assembly reaches 1800 W. Thus, given
a feed rate of 250 kg/h, we arrive at 7.2 kWh to sort one
metric ton of material.
The final metrics of interest are aluminum grade in thethrow bin and total aluminum recovery. Using the formal
definitions of Dholu et al. (2017), the aluminum grade wasfound to reach an impressive 97.6 %. Of the small amountof contamination that also reached the throw bin, the majority appeared to result from thin sheet geometries. For
example, US coins are a common product in shredded automobiles, and pennies in particular seemed to be themost prevalent. This resulted in a significant zinc contamination to the throws, since pennies are essentially thindisks of zinc with a thin copper coating.
To calculate the aluminum recovery, it is simply a matter of measuring the total aluminum mass in the throw
bin and then dividing it by the original aluminum mass.
The result was about 93 % aluminum recovery from theoriginal mixture, with the other 7 % landing in the drop
bin with the heavies. After examining the material, it wassurmised that the majority of errors were due to small
particle sizes (e.g., 5 mm or less), which could not throw
effectively in the 12.7 kHz field being applied. If the magnetic field were instead excited to much higher frequency,
however (e.g., 20 kHz or more), then is likely that recovery would have increased significantly as well.
On the other end of the size scale, many large particles
of aluminum were simply too big to experience a proper
throw by the magnet, but this can only be alleviated byredesigning the magnetic gap for a greater protrusion offield into the space above. Many other observed sourcesof error were also found to be purely kinematic in nature.
For example, collisions between particles and the divider
were common, and there is also a finite settling time formaterial as it drops onto the fast-moving conveyor belt.
Fortunately, such errors can be corrected through revisions in the basic mechanical structure, which means future iterations are likely to yield even more reliable
outcomes.

Acknowledgments
This work was funded by the United States Advanced
Research Project Agency-Energy (ARPA-E) METALSProgram under cooperative agreement grant DE-­
AR0000411.

Nomenclature
ECS

Eddy Current Separator/Separation

EDX

Electrodynamic SortingaSphere Radius (m)B0Magnetic Field Intensity (T)C

Capacitance (F)f0Resonant Frequency (Hz)F

Force (N)I

Electric Current (A)L

Inductance (H)μ0

Vacuum Permeability (H/m)σ

Electrical Conductivity (S/m)ω

Angular Frequency (rad/s)

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Authors’ Short Biographies
James Nagel
James Nagel completed his PhD in 2011 from the University of Utah in Salt Lake City,
Utah, where he was awarded the Stockham Medal of Excellence for conspicuously effective teaching. His background is in electrical engineering with a specialty in applied
electromagnetics and numerical methods. He now works as a research associate for the
University of Utah and is a co-founder for EDX Magnetics, LLC.

Dave Cohrs
Dave Cohrs completed his Bachelor of Science in 2007 at the University of Maryland
in Baltimore, Maryland, where he studied Environmental Science with an emphasis on
Analytical Chemistry. He managed water quality laboratories at public aquariums for 16
years and has consulted for aquariums, zoos, and academia on water chemistry and life
support topics. He now works for the University of Utah as a research associate and is aco-founder for EDX Magnetics, LLC.

Jacob Salgado
Jacob Salgado completed his Bachelor of Science in Metallurgical Engineering from the
University of Utah in 2018. He is a decorated military veteran who served in the UnitedStates Army from 2010–2013 and deployed overseas in support of Operation Enduring
Freedom. He has been working as a research associate at the University of Utah since 2015,and he has also worked as a product engineer for EDX Magnetics, LLC, since 2018.

Raj Rajamani
Raj Rajamani has been on the faculty of the Metallurgical Engineering Department of
the University of Utah, Salt Lake City, Utah, USA since 1980. Currently he holds the position of Professor. His research interests include population balance modeling of tumblingmills, computational fluid dynamics of hydrocyclones, discrete element modeling ofsemi-autogenous grinding mills, eddy current sorting of metallic particles and modeling ofhigh pressure grinding rolls. He received the Antoine M. Gaudin Award, presented by theSociety of Mining, Metallurgy and Exploration Engineers Inc. in the year 2009.

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KONA Powder and Particle Journal No. 37 (2020) 265–267/Doi:10.14356/kona.2020021

Information Article

Book Review
Introduction of a new book entitled “Spherical
Crystallization as a New Platform for Particle Design
Engineering” by Y. Kawashima

Springer Singapore,
ISBN: 978-981-13-6786-1,
1st ed. 2019, XVII, 118 p.

Traditional powder (KONA) technology has described successfully powder processing, i.e. powdered material
handling, as a mass-unit operation system such as comminution, classification, agglomeration and others. A paradigm shift has been occurred in modern powder technology by looking at carefully individual particle’s property itself such as surface topography and even internal structure at molecular level. As a result, a new concept of particle
design engineering has been arisen to modify or change the property or function of the raw particulate material toproduce more valuable product. In general, there are two ways for particle designing, classified as break-down andbuilt-up methods. We proposed a new built-up particle-design method, called the “spherical crystallization process,” which can open the door to unique crystallization engineering that could replace traditional micro- and nanotechnology approaches. In this process, nano to micro crystals produced by crystallization are spherically
agglomerated at the same time. Spherically agglomerated crystals can improve the micromeritic properties oforiginal particles, which can be reliably formulated in pharmaceutical dosage forms. The paradigm shift ofnano-to-microparticle design by spherical crystallization is overviewed by looking at the principle of sphericalagglomeration in liquid and new particle design platform developed by the spherical crystallization system shownin the contents (Table 1).
In Chap. 2, it was described that the ultrafine crystals formed by antisolvent crystallization of an API (salicylicacid) are simultaneously self-agglomerated—spherically—by a small amount of bridging liquid produced from thecrystallization solvent by phase separation. The agglomeration kinetics were described by a first order, followed tozero-order process with mass base after crystallization finished. In Chap. 3, the paradigm shifted pharmaceuticalprocess provided by spherical crystallization is explained by direct-tableting API. The way how spherically agglomerated API crystals can be directly tableted without using a binder is explained owing to the paradigm shiftedcompaction behavior of spherically crystallized products appearing under static and dynamic compactions. In
Chap. 4, it was explained how the spherical crystallization technique was developed as a novel particulate-design
platform to create various functional particulate preparations. Spherical crystallization was originally carried out
using a tri-solvent system, that is, a good solvent, a poor solvent, and a bridging liquid, in which the crystallized
particles spherically agglomerated with the bridging liquid induced from the system simultaneously. It was recently
found that if a good solvent solution is partially miscible in a poor solvent, the residual undissolved good solvent
acts as a bridging liquid for the crystals, which can make the original spherical crystallization technique widely applicable to any other API. Ascorbic acid crystals, as poorly compressible model crystals, are spherically agglomerated using a binary-solvent system, enabling direct tableting without requiring a binder. To improve thephysicochemical properties of APIs, such as their solubility or therapeutic performance, a multi-component system
was developed by combining a surfactant or hydrophilic polymer with a dispersing (poor) solvent. The solubility of
the formulated drug can be enhanced by adding a specifically interacting API to the formulation. The solubility of
the anti-inflammatory drug indomethacin is enhanced by combining it with epirizole to form a new spherically265crystallized complex. Spherical crystallization using a double-component system such as theophylline and ethylene
diamine can produce polymorphic aminophylline depending on the water content in the system. Polymeric spherical crystallization has been developed for preparing drug carriers (microspheres and microballoons) for novel
DDSs. Interestingly, the spherical crystallization process can be widely applied as a platform technique for semisolid materials such as vitamin E, which is transformed into a solid powder and can be filled in a capsule or tabletedusing colloidal silica. In Chap. 5, it was described how an ethanol solution of an acrylic polymer, such as Eudragit(RS, S or L), and an API dispersed in water or polyvinyl alcohol (PVA) forms quasi-emulsion droplets in which the
API and the polymer are co-precipitated to form a spherical micro-matrix. A controlled drug-releasing system wasdeveloped by using this process, termed “emulsion solvent diffusion (ESD)” method. Hollow microspheres (microballoons), which are used for multiple floating-controlled drug-delivery systems, are developed by the polymeric
spherical crystallization process. To quantitatively describe the floating behavior of the microballoons in the stomach, a novel radio-scintigraphical method using Technetium-99m has been developed. In Chap. 6, the developmentof biocompatible and biodegradable polymeric micro/nanospheres using poly (D,L-lactide-co-glycolide) (PLGA),
loaded with a bioactive substance by the ESD method, is described. It is difficult to directly formulate nanospheresin their final pharmaceutical form due to their strong aggregation tendency. To overcome those problems, the PLGA
nanospheres are transformed into solid dispersed nanosphere composites containing a water-soluble excipient, suchas a sugar alcohol, which can reproduce the original fresh nanospheres (NSs) dispersed at the applied site. Preparing nanocomposite particles can allow to handle them in the same way for preparing solid-dosage forms, such astablets, capsules, dry-powder inhalations (DPIs), and so on. PLGA nanospheres with chitosan-modified surfaces
can improve the drug absorption at the target site due to a sustained stay and prolonged release of the drug. Transdermal DDSs containing PLGA-nanosphere composites have been developed for nanocosmetics, as discussed in
Chap. 7. A whitening and anti-aging cosmetic containing ascorbyl tetraisopalmitate (VC-IP) loaded PLGA NSs,
named “NanoCrysphere®,” was launched in 2004 by Hosokawa Co. Ltd. In Chap. 8, future perspectives of the platforms for designing new DDSs and manufacturing them at industrial scale with a new continuous pharmaceuticalprocess are described.
[Author: Kawashima, Yoshiaki]

Table 1
1

Contents

Introduction........................................................................................................................................................................................ 1
References............................................................................................................................................................................................. 92

Concept of Spherical Crystallization............................................................................................................................................. 11
2.1

Spherical Self-Organized Agglomeration of Fine Particles in a Liquid.................................................................................. 11

2.2

Spherical Crystallization of Salicylic Acid with Simultaneous Agglomeration and Crystallization..................................... 12

2.3

Spherical Crystallization Kinetics and Agglomeration Mechanism........................................................................................ 15

References........................................................................................................................................................................................... 18
3

Paradigm Shifted Pharmaceutical Process Introduced by Spherical Crystallization............................................................. 19
3.1

Paradigm Shifted Primary Particle Properties of Spherical Crystallized Products................................................................ 19

3.2

Critical Operating Parameters Determining the Secondary Particle Properties of Spherically Crystallized Products			for Direct Tableting................................................................................................................................................................... 21

3.3

Paradigm Shifted Mechanical Properties of Spherically Agglomerated Crystals for Direct Tableting................................. 23

3.4

Paradigm Shifted Static Compaction Properties of Spherically Agglomerated Crystals for Direct Tableting...................... 26

3.5

Paradigm Shifted Dynamic-Compression Behavior of Spherically Agglomerated Crystals for Direct Tableting................ 29

References........................................................................................................................................................................................... 334266

Particulate-Design Platform Developed by the Advanced Spherical Crystallization System................................................ 35
4.1

Spherical Crystallization of a Poorly Soluble Drug (Enoxacin) with an Ammonia Diffusion System................................... 35

4.2

Spherical Crystallization of a Poorly Compressible Powder for Direct Tableting Using Binary-Solvent Systems................ 39

4.3

Spherical Crystallization of a Multi-component System to Improve the Physicochemical Properties.................................. 42

4.4

Polymeric Spherical Crystallization for the Preparation of Drug Carriers (Microspheres and Microballoons).................... 49

4.5

Transforming Waxy Semisolid Drugs into Solid-Dosage Forms, Such as Capsules or Tablets............................................. 53

References........................................................................................................................................................................................... 58
5

Development of Novel Microsphere and Microballoon DDSs by Polymeric Spherical Crystallization................................. 59
5.1

			

Preparation of Microspheres (Microsponges) for Controlled-Drug-Release Systems by Polymeric Spherical
Crystallization........................................................................................................................................................................... 59

5.2

Controlled-Drug-Release Behavior from Microspheres Prepared by Polymeric Spherical Crystallization.......................... 64

5.3

Preparation of Hollow Microspheres (Microballoons) for Multiple Floating-Controlled Drug-Delivery Systems by PSC.. 68

References........................................................................................................................................................................................... 76
6

Development of a PLGA-Nanosphere DDS Prepared by Spherical Crystallization with a Polymer..................................... 77
6.1

			

Development of a Preparation Method (ESD and PS) for PLGA Nanospheres and Their Properties(Size Distribution and Drug-Release Properties)..................................................................................................................... 77

6.2

Design and Engineering of a Nanocomposite Particulate System for DDS............................................................................ 83

6.3

Oral Nanocomposite DDSs with Peptides or Hormones Such as Insulin and Calcitonin....................................................... 85

6.4

Oral Nanocomposite DDS Containing a Nucleic Acid (NF-κB Decoy Oligonucleotides) for Colon Delivery...................... 86

6.5

Pulmonary Nanocomposite DDS Containing a Hormone or an Antiathmatic Drug.............................................................. 89

6.6

Transdermal Nanocomposite DDS........................................................................................................................................... 92

References........................................................................................................................................................................................... 95
7

Application of PLGA NSs to Cosmetics......................................................................................................................................... 99
7.1

Development of Whitening and Anti-aging Cosmetics............................................................................................................ 99

7.2

Medical Skincare PLGA NSs for Sensitive or Atopic Dermatitis Skin................................................................................. 100

7.3

Moisturizing and Breakage-Free-Type Make up Products.................................................................................................... 101

7.4

Effective Anti-Acne-Agent Delivery to Pores Using PLGA NSs........................................................................................... 103

7.5

DDS-Functionalized Hair-Growth Tonic Using PLGA NSs.................................................................................................. 105

References......................................................................................................................................................................................... 106
8

Future Perspectives of PLGA Nanospheres for Advanced DDSs and Continuous Preparation Systems for Spherical
Crystallizers.................................................................................................................................................................................... 107
References..........................................................................................................................................................................................117

Author’s Short Biography
Yoshiaki Kawashima
Yoshiaki Kawashima is an Emeritus Professor of Gifu Pharmaceutical University anda Contract Professor of Aichi Gakuin University. He received his doctoral degree in1970 in pharmaceutical engineering at Kyoto University. Professor Yoshiaki Kawashima
is the pioneer and a world-leading pharmaceutical scientist to develop a new platform forparticulate design engineering. The most unique particle engineering process developedby him is “spherical crystallization technique.” This built up design system was evaluated as the receipts of many honors and awards, including the Pharm. Sci. World
Congress Award, Colorcon Intnl. (FIP) Award and KONA Award. He has coauthoredmore than 400 scientific papers, 120 review papers, 50 books/chapters, and 70 patents.
He is an International Fellow of AAPS, SGPhW and JAPST.

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Infomation Article

The 53rd Symposium on Powder Technology
The 53rd Symposium on Powder Technology organized by Hosokawa Powder Technology Foundation took placeat Hotel Nikko Osaka, in Japan on Monday, October 7, 2019. It was held by the planning of Council of Powder
Technology, Japan and with the sponsorship of Hosokawa Micron Corporation. Nearly 180 people from the industries and universities attended this symposium. The theme of the symposium this year was “Forefront of Fundamentals and Applications of Advanced Powder Processing”. There were six lectures including a special one givenby the KONA Awardee with questions and answers after each lecture followed by a get-acquainted party for further
free discussions.
At the beginning of the symposium, Mr. Yoshio Hosokawa, the president of the Foundation, gave the opening address mentioning that this symposium was started in 1968, more than 50 years ago and has been continued almost
annually since then. Prior to the lectures, the KONA Award presentation ceremony was held and the plaque of
KONA Award was handed from the president to Prof. Mojtaba Ghadiri, who received this Award in the last fiscal
year 2018. The KONA Award has been given to the researcher with excellent performance and contributions to thepowder and particle science and technology since 1990. It was first started by Hosokawa Micron Corporation but
taken over by Hosokawa Foundation after its establishment in 1991. Though it had been presented to Japanese researchers by the Foundation till three years ago, it was opened to worldwide and given to the overseas researcher by
the Foundation two years ago for the first time.
In the special lecture given by Prof. Ghadiri, a critique of the current state of the art in rheometry of cohesive
powder flow was presented, reviewing features of a number of instruments widely used for the evaluation of thecohesive powder flow, which is reviewed in this issue of the journal.
The contents of the symposium are shown below. In the second lecture was presented the way of thinking to use
the technique of reducing spring constant to reduce the calculation time or cost for the Discrete Element Method(DEM), which is one of the most popular simulation methods widely used to study the phenomena concerning
granular materials or powders or to develop and optimize granular facilities and processes.
The following lecture 3 was concerning the methodology for designing nanoparticles which was summarizedbased on two mixing concepts of rapid mixing and precise diffusion control. The synthesis of TiO2 nanoparticles by
double-tube microreactor developed and the K-M mixer as a typical micro mixer for strict control of nucleation process was introduced together with its performance on the processing of nanoparticles.
In the lecture 4, the results of the study of mechanism of the biomineralogical processing which improved thegold recovery from 25 % to finally 92 % using the differential thermogravimetric analysis and quantitative evaluation of minerals with scanning electron microscopy wereintroduced.
It the lecture 5, the mechanism for high viscosity of thesealant and adhesives in which the calcium carbonate particles are dispersed was explained on the measurement of
the viscosity of confined liquid plasticizer between thesurfaces imitating the particle surface of calcium carbonate using shear resonance measurement system.
In the final lecture, along with the history of the machines for spheronization of natural graphite particles
used as the negative electrode of the LIB secondary battery to improve its energy density and their working
mechanisms, a new phenomenon model was introduced
and elucidated.

268

KONA Award presentation ceremony

The 53rd Symposium on Powder Technology
Theme: “Forefront of Fundamentals and Applications of Advanced Powder Processing”
Date: Monday, October 7, 2019

Place: Hotel Nikko Osaka (Tel 81-6-6244-1111)

Opening address Mr. Yoshio Hosokawa (President of Hosokawa Powder Technology Foundation,
President of Hosokawa Micron Corporation)• 2018 KONA Award presentation ceremony
Session 1

Chaired by Prof. Makio Naito (Osaka University)• Lecture 1 (Special lecture by the KONA Awardee)“Rheometry of Cohesive Powder Flow”
Prof. Mojtaba Ghadiri (University of Leeds, UK)• Lecture 2“Recent Topics in the DEM Simulation of Granular Flow”
Prof. Toshitsugu Tanaka (Osaka University)
Session 2 Chaired by Emeritus Prof. Ko Higashitani (Kyoto University)• Lecture 3“Production of Fine Particle Materials with High Performance by Microreactor”
Prof. Kazuhiro Mae (Kyoto University)• Lecture 4“Biomineral Processing of Graphitic Refractory Gold Ores Using Enzymatic Reactions”
Prof. Keiko Sasaki (Kyushu University)
Session 3 Chaired by Prof. Satoru Watano (Osaka Prefecture University)• Lecture 5“Controlling Surface Modification of Calcium Carbonate Filler and Characteristic of Its Composite Material”
Dr. Yoshisada Kayano (General Manager, Shiraishi Kogyo Kaisha, Ltd.; Director, Shiraishi Central
Laboratories Co., Ltd., Japan)• Lecture 6“Challenging History to Spheronize Natural Graphite for Secondary Battery”
Dr. Kohei Hosokawa (Executive Vice President, Business Management, Hosokawa Micron Corporation,
Japan)
Closing remarks

Emeritus Prof. Fumio Saito (Tohoku University, President of Council of Powder Technology,
Japan)

Symposium on Powder Technology

Get-acquainted Party

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Information Article

The KONA Award 2018
The KONA Award 2018 was presented to Dr Mojtaba Ghadiri, Professor of Chemical Engineering at the University of Leeds, UK, Fellow of the Royal Academy of Engineering, Chartered Engineer and Fellow of the Institutionof Chemical Engineers. For the period 2001 to 2011, he was the founding Director of the Institute of Particle Science and Engineering at Leeds. He graduated in Chemical Engineering from the University of Tehran, Iran, andhas an MSc from Imperial College London (with Distinction) and PhD from the University of Cambridge, for which
he was Awarded P.V. Danckwerts Prize. He worked for Unilever Research for two years before taking up an academic post at the University of Surrey, where he worked for 18 years before joining Leeds in 2001. He has served
the editorial boards of five learned journals, and until recently was the Chairman of the Europe & Africa Board of
KONA Powder and Particle Journal, and the Subject Editor of Chem. Eng. Res. & Design (ChERD). He has acted
as an expert assessor for the Australian, Belgian, Canadian, Italian, Norwegian and Swedish Research Councils aswell as the Engineering and Physical Sciences Research Council (EPSRC), which is the UK’s main agency forfunding research in engineering and the physical sciences, and as an expert witness for a number of legal cases. He
has contributed to the organization of a large number of national and international conferences, most notably World
Congresses on Particle Technology, the European Symposia on Comminution and Classification, International
Symposia on Agglomeration and national meetings via the Particle Technology Special Interest Group of IChemE.
He is the chair of judging panel of Geldart Medal of IChemE, and until 2019 he was a Consultant of the Inter­national Fine Particle Research Institute (IFPRI). In April 2010, he was awarded the Iinoya Award of the Society of
Powder Technology, Japan, for his contributions to the promotion of international cooperation in powder technology.
His research has been focused on the development of relationships between microscopic and macroscopic properties and phenomena; i.e. the way in which the microstructure of particulate solids and the micromechanics oftheir interactions in process equipment influence the performance of the process and product characteristics. His
work on the following topics has had notable academic and industrial impacts:
Attrition and milling: Novel methods of grindability and attrition testing.
Powder mechanics: Analysis of cohesive powder rheology, accelerated powder caking testing, powder dispersion, flowability testing by Ball Indentation Method.
Particle characterization: New method for measuring single particle adhesion, sol-gel production of nano-particle
systems for solid oxide fuel cells.
Tribo-electrification & electro-coalescence: Development of three test methods for tribo-electric charge transfer measurement. Analysis of dynamics of coalescing droplets under electric fields and development of new art forcompact electro-coalescer design.
Granulation and agglomeration: 3D printed agglomerates for granule breakage tests, characterizationof strength and structure of granules, scale-up of highshear granulators.
Modelling by CFD-DEM: Analysis of powder rheometry; effect of particle shape, inter-particle coating
variability in rotary batch coaters, a new linear contact
model for elasto-plastic and adhesive contacts, spraydrying aerodynamic dispersion of cohesive clusters,
modelling of dense and complex granular flow in highshear mixer granulators. Further information on his research activities and collaborations can be viewed at:
http://ghadiri-group.leeds.ac.uk/.
Mr. Y. Hosokawa (Left), the president of Hosokawa Foundation
and Prof. Ghadiri, the KONA Awardee

270

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Infomation Article

General Information
History of the Journal
In the history of KONA Powder and Particle Journal, twoorganizations have been playing an important role. The one is theCouncil of Powder Technology, Japan (CPT) and the other is the
Hosokawa Powder Technology Foundation (Hosokawa Foundation).
The CPT was established in 1969 by Hosokawa Micron Corporation
as a nonprofit organization to enhance the activities of research anddevelopment on powder science and technology. The Hosokawa
Foundation was established in 1991 as a public-service corporation
approved by the Ministry of Education, Culture, Sport, Science andTechnology of Japan. The issues from No.1 (1983) to No.12 (1994)
of KONA were published by CPT and the issues from No.13 (1995)
by the Hosokawa Foundation.
The aim of KONA in the early days was to introduce excellent
Japanese papers to the world and thus KONA consisted of papers
recommended by some Japanese academic societies and translated
from Japanese to English. From the issue of No.8, the CPT changed
its editorial policy to internationalize the KONA and to incorporate
papers by authors throughout the world in addition to translated
papers. In response to this change, three editorial blocks have beenorganized in the world; Asian-Oceanian, American, and European.
The policy and system have not changed even after the Hosokawa
Foundation has taken over from the CPT. From the issue of No.27(2009), publication of translated papers has been terminated andonly original papers have been published. The CPT is still active
today and is collaborating with the Hosokawa Foundation.
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
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research papers of high quality submitted to the KONA
Editorial Committees, and refereed by the reviewers and editors.
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It is now possible to submit your paper online via Editorial
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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.
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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) 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.
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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.
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•	The maximum pages printed in KONA are supposed to be:
15 for an original paper and 25 for a review paper.
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their definition and dimensions in SI units.
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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) have recently shown ....”(3) Copyright and permission•	The original paper to be submitted to KONA has not been
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