ISSN 0288-4534

CODEN: KPPJAD

KONA

Powder andParticle Journal

No.38 (2021)

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

KONA Powder and Particle Journal No. 38 (2021)

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)
H. Choi(Changwon National Univ., Korea)
S. Das(Indian Institute of Technology, India)
J. Hidaka(Doshisha Univ., Japan)
E. Iritani(Nagoya Univ., Japan)
H. Kage(Kyushu Institute of Technology, Japan)
A. Kawasaki(Tohoku Univ., Japan)
D.J. Lee(National Taiwan Univ., Taiwan)
J.H. Li(Chinese Academy of Sciences, China)
H. Makino(CRIEPI, Japan)
S. Matsusaka(Kyoto Univ., Japan)
M. Naito(Osaka Univ., Japan)
Y. Otani(Kanazawa Univ., Japan)
F. Saito(Tohoku Univ., Japan)
Y. Sakka(NIMS, Japan)
H. Takeuchi(Gifu Pharmaceutical Univ., Japan)
W. Tanthapanichakoon (The Royal Society of Thailand, Thailand)
C.H. Wang(National Univ. of Singapore, Singapore)
S. Watano(Osaka Pref. Univ., Japan)
Secretariat
T. Yokoyama(Hosokawa Powder Tech. Foundation, Japan)
L. Cui(Hosokawa Micron Corp., Japan)

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 CoverIntermetallic compounds are homogeneously ordered, solidstate compounds of two or more metallic elements. They
have distinctive electronic structures which are completely
different from those of mixed metals. This characteristic
leads to unique electrical, thermal, magnetic, semiconducting, and chemical properties, which in the end, opens thedoor to a wide range of applications. Their highly ordered
atomic structure, even at the surface, is favorable for solidstate catalysis. Studies related to the catalytic application ofintermetallic compounds are usually focused on the binary
systems. Recently, ternary metallic element systems in Heusler Alloys demonstrate promising features for catalysis because of their novel fundamental catalytic properties. Reviewof this topic is discussed on pp. 110–121.

European / African Editorial Board
Chairman
G.M.H. Meesters(Delft Univ. of Technology, Netherlands)
F. Bourgeois
M.-O. Coppens
L. Gradon
A. Kwade
P. Milani
M.G. Rasteiro
J.M. Valverde
Secretariat
S. Sander
S. Wilk(Univ. of Toulouse, France)(Univ. College London, UK)(Warsaw Univ. of Technology, Poland)(TU Braunschweig, Germany)(Univ. of Milan, Italy)(Univ. of Coimbra, Portugal)(Univ. of Seville, Spain)(KONA Europe e.V., Germany)(KONA Europe e.V., Germany)

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

■ Publication Office

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

Headquarters of Hosokawa Micron Corporation■ Publication Date: 10 January 2021

KONA Powder and Particle Journal No. 38 (2021) Contents<Editorial>
1

Editor's Preface<Review Papers>
3

From Quasi-static to Intermediate Regimesin Shear Cell Devices: Theory andCharacterisation

Victor Francia, Lyes Ait Ali Yahia, Raffaella
Ocone and Ali Ozel
26

Static and Dynamic Stickiness Tests to
Measure Particle Stickiness

Erik J.G. Sewalt, Fuweng Zhang, Volkert van
Steijn, J. Ruud van Ommen and Gabrie M.H.
Meesters
42

Inertial Impaction Technique for theClassification of Particulate Matters andNanoparticles: A Review

Thi-Cuc Le and Chuen-Jinn Tsai
64

Drag Reduction in Turbulent Flows by
Polymer and Fiber Additives

Cristian Marchioli and Marina CampoloiKONA Powder and Particle Journal No. 38 (2021) 

82

Agglomeration and Dispersion Related toParticle Charging in Electric Fields

Mizuki Shoyama and Shuji Matsusaka
94

Recent Progress in Efficient Gas–Solid
Cyclone Separators with a High Solids
Loading for Large-scale Fluidized Beds

Chihiro Fushimi, Kentaro Yato, Mikio Sakai,
Takashi Kawano and Teruyuki Kita
110

Screening of Ternary Intermetallic Catalysts
Is Possible Using Metallurgical Synthesis:
Demonstration on Heusler Alloys

Takayuki Kojima, Satoshi Kameoka andAn-Pang Tsai
122 Particle Preparation and Morphology
Control with Mutual Diffusion AcrossLiquid-Liquid Interfaces

Kazunori Kadota and Yoshiyuki Shirakawa

iiContents

KONA Powder and Particle Journal No. 38 (2021) 

136

Contents

Consideration of Metal Organic Frameworks
for Respiratory Delivery

Ian E. Stewart, Ignacio Luz and Ninell P.
Mortensen
155

Mechanochemical Preparation of Mineral
Based Adsorbent and Its Effective
Purification Ability for Wastewater

Huimin Hu and Qiwu Zhang
168 Coal Particle Devolatilization and Soot
Formation in Pulverized Coal Combustion
FieldsNozomu Hashimoto and Jun Hayashi
189

Scaling-up the Calcium-Looping Process for
CO2 Capture and Energy Storage

Carlos Ortiz, José Manuel Valverde, Ricardo
Chacartegui, Luis A. Pérez-Maqueda and Pau
Gimenez-Gavarrelliii

KONA Powder and Particle Journal No. 38 (2021) <Original Research Papers>
209 Modulated Uniaxial Compression Analysis of
Respirable Pharmaceutical Powders

David Barona, Abouzar Shamsaddini,
Maximilian Aisenstat, Kyrre Thalberg, David
Lechuga-Ballesteros, Behzad Damadzadeh andReinhard Vehring
226

Effects of Powder Vibration and Time
Consolidation on Soft and Hard Wheat Flour
Properties

Yumeng Zhao, Poonam Phalswal, Abhishek
Shetty and R.P. Kingsly Ambrose
235

A Semi-Automated DEM Parameter
Calibration Technique of Powders Based on
Different Bulk Responses Extracted from
Auger Dosing Experiments

Bilal El Kassem, Nizar Salloum, Thomas Brinz,
Yousef Heider and Bernd Markert
251 The Properties of Kaolin from Different
Locations and Their Impact on Casting Rate

Mervat Said Hassan Badr, Shuaishuai Yuan,
Jiaqi Dong, Hassan El-Shall, Yamile A.
Bermudez, Diana C. Ortega, Jorge E.
Lopez-Rendon and Brij M. Moudgil

iv

Contents

KONA Powder and Particle Journal No. 38 (2021) Contents

260 Fabrication and Characterization of PrussianBlue-Derived Iron Carbide-Iron Oxide
Hybrid on Reduced Graphene Oxide
Nanosheets

Alowasheeir Azhar, Jacob Earnshaw, Mohamed
Barakat Zakaria, Ping Cheng, Yusuf Valentino
Kaneti, Md. Shahriar A. Hossain, Saad M.
Alshehri, Tansir Ahamad, Yusuke Yamauchi
and Jongbeom Na
269

Polymer-Particle Enhanced Visible Light
Range Photocatalytic Activity on Textile
Applications

Asena Cerhan Haink and G. Bahar Basim<Information Articles>
281 Book Review
285 3rd International Hosokawa Powder
Technology Symposium Held in China
287

The KONA Award 2019
(Awardee: Prof. Dr. Makio Naito)

288

General Information

Selected research achievements for the KONA Award 2019: One-pot processing methods developed by applying particle bonding principle. (p.287)v

KONA Powder and Particle Journal No. 38 (2021) /https://doi.org/10.14356/kona.2021019

Editorial

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

I would like to express my sincere gratitude to the reviewers for their hard work for the KONA Powder andParticle Journal. Thanks to the generous contributions of the volunteer reviewers as well as the interest of researchersin our journal, the number of submission to this journal is increasing after the registration on the major international
journal platforms and its level is further improving. Thanks to their strong support and effort, I am pleased to informthat 2019 Impact Factor (JCR) of the KONA Powder and Particle Journal is increased to 2.326, with the CiteScore
2019 of 4.2. Because of the limited space of this annual journal, the number of papers published here is regrettably
rather restricted. Therefore only the papers of good quality will be selected for the journal and further improved andrefined by the reviewing process.
The editorial team of the KONA Journal would like to take this opportunity to gratefully acknowledge thereviewers here and deeply appreciate their valuable time and professional contributions to the KONA Journal. We
apologize to any reviewers who may have been inadvertently omitted from this list. We are sincerely grateful to all
who have been of any assistance to the publication of this journal.

BOURGEOIS, Florent

MAKINO, Hisao

SAKKA, Yoshio

COPPENS, Marc-Olivier

MATSUYAMA, Tatsushi

TANAKA, Toshitsugu

GRADOŃ, Leon

MOUDGIL, BrijTOKORO, Chiharu

HICKEY, AnthonyOTANI, Yoshio

YAMAMOTO, Hiromitsu

KAGE, Hiroyuki

PURI, Virendra

YOKOYAMA, Toyokazu

KANO, Junya

RASTEIRO, Maria da Graça

KWADE, Arno

SAITO, Fumio

October 2020

vi

Copyright © 2021 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/).

KONA Powder and Particle Journal No. 38 (2021) 1–2/https://doi.org/10.14356/kona.2021020

Editorial

Editor’s Preface
Brij M. Moudgil
Chairman of American Editorial Board
University of Florida, USA

As Chair of the American Editorial Board, I am pleased to introduce the KONA Powder & Particle Journal No.
38. In continuation of the past tradition, this issue presents high quality review articles and original research papers.
The journal is reaching out to an ever-expanding cadre of researchers as illustrated by the diversity of disciplines
represented by the authors of the articles. KONA continues to serve academic and industry researchers from physical sciences to engineering and beyond. Furthermore, increased recognition of KONA as a high quality journal is atestimonial that recent changes in the review process, format and accessibility are moving in the right direction.
Powder technology continues to be recognized as an important business with tremendous global opportunity.
Technological advances in the field are demanding more complex particle design and powder properties. An example would be advanced sensor technologies that require multifunctional particle platforms with high precision tomeet lower and lower detection limits with high reliability. If designing such particles is a challenge, it is even abigger challenge to manufacture them on large scale. Most often large-scale production of precision particles remains an empirical exercise. Hopefully, advances in simulation and modelling, which is fast approaching practicalscale systems, would lead to new scale-up paradigms.
With diversification of the disciplinary base of particle and powder researchers, it is critical for KONA to reachout to young researchers with different professional backgrounds, and also to publish more state-of-the-art review
articles – a hallmark tradition of KONA over the several decades. In this regard, KONA may invite academic andindustry researchers, especially those who are at the forefront of scientific and technological advances, to publish
comprehensive review articles in the journal. These articles will further reinforce KONA’s position as a reliable
source for powder and particle related information. Additionally, KONA may also invite young researchers who arewithin a few years of receiving their advanced degrees to publish overview articles closely related to their particle
and powder related research endeavors.
While many institutions of higher learning were already offering select degree programs and courses online, thesudden emergence of the pandemic compelled delivery of almost all courses online, practically overnight. As challenging as it has been for instructors to suddenly shift to the online mode, it is equally if not more challenging forthe students to be thrust into this new learning environment. That said, it is not all doom and gloom! This uniquesituation certainly provides an opportunity to rejuvenate and redesign the course materials in a way that is meaningful to the students without losing the rigor of learning the subject matter. Simply repackaging the old material
into digital delivery mode will not do. We can expect that education’s new business model will drive the online delivery mode for most courses, with in-person learning confined to only a handful of courses.
However, serious challenges exist with online learning platforms, accessibility being a critical one. Many university students, even in developed countries, lack the internet bandwidth and other resources which their peers may

Copyright © 2021 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

have. Another serious challenge is almost assured disruptions due to future pandemics and climate change-related
disasters. Mitigating such risks requires the design of flexible curriculum for completing coursework and degree
programs on the academic front.
As there is a paradigm shift in knowledge creation and delivery from traditionally strong powder and particle research centers and institutes to individuals and smaller group efforts, acquisition of deep understanding of complex
systems may be at risk. However, this challenge may be overcome to an extent with the availability of more powerful and robust search engines and other IT mediated modalities. Such resources can hopefully enhance the existing
curriculum and enable development of new teaching modes to train the next generation of powder and particle technology professionals.
Overall, I believe that harnessing the application of AI/ML and advanced computational tools has the potential ofrevitalizing both the instruction and application of particle and powder technology.
I invite you to explore and enjoy this issue of KONA. Let us continue to work together and make KONA evermore relevant and reliable as a source of particle and powder technology knowledge and know-how.

Brij M. Moudgil
Chair, American Editorial Board
September 23, 2020

2

KONA Powder and Particle Journal No. 38 (2021) 3–25/https://doi.org/10.14356/kona.2021018

Review Paper

From Quasi-static to Intermediate Regimes in Shear Cell
Devices: Theory and Characterisation †Victor Francia *, Lyes Ait Ali Yahia, Raffaella Ocone and Ali Ozel
School of Engineering and Physical Sciences, Heriot-Watt University, UK

Abstract
The design of new technology for processing and manufacturing particulate products requires understanding
granular rheology over a broad range of conditions. Powders display a complex behaviour due to their ability
to rearrange under stress, and as a result, granular flow is generally classified into three flow regimes, namely aquasi-static regime dominated by frictional contacts, an inertial regime dominated by collisional and kinematicstresses and an intermediate regime where the three sources of stress are important to establish a stress-strain
rate relationship. Characterisation of the flowability is generally restricted to the flow initiation in quasi-static
regime, even if, transition into inertial conditions is very common in practical applications involving the control
of dense flows, such as powder handling, particle formation processes or additive manufacturing. This work
presents a critical review of available techniques to characterise the departure from the quasi-static regime into anintermediate flow. We revise the application of shear cells and present different strategies to modify classic devices
with external actuation, such as aeration, to operate at higher inertial numbers. We pay particular attention to
innovative designs using aerated Couette flow configurations, highlight the complexity in the standardisation andthe challenges in advancing towards a universal model.
Keywords: granular rheology, aeration, Couette flow, shear cell, flowability, characterisation

1. Introduction
A universal description of granular rheology is both afundamental and industrial challenge. Complex granular
flows are a feature of natural phenomena such as landlines,rock slumping and sand dunes as well as in industrial
processes such as granulation, milling and fluidisation.
Powders, particulates and gravels are often the scaffolds
where complex biological, physical or chemical processes
take place, and underpin disciplines spanning from geomechanics (Wheeler and Sivakumar, 1995) to volcanology(Petford, 2003), including the study of dense flows suchas soil (Pastor et al., 2009) and sediments (Baumgarten
and Kamrin, 2019). Powders constitute a large proportion of raw materials, intermediates, products and waste
in the primary and the process industry, and the energy,
environmental and manufacturing sectors. Pigments, ceramics, petrochemicals, plastics, bulk and fine chemicals
or fast-moving consumer goods are only some examples.
Although powders have been studied for a century, our†Received 6 July 2020; Accepted 21 August 2020
J-STAGE Advance published online 26 September 2020
* Corresponding author: Victor Francia;
Add: Edinburgh, EH14 4AS, UK
E-mail: v.francia@hw.ac.uk
TEL: +44 (0) 131 451 3293

understanding of granular flow is far from that of simple
fluids or solids. Individual particle interactions lead to acollective behaviour that makes powders restructure understress. If compressed, they respond as an elastic solid; butwhen diluted, they behave like a fluid (Jaeger et al., 1996).
Solid-like behaviour steams from the formation of a network of contacts, the so-called force chains, that transmit
the stress. In addition to these frictional contacts, particle
interactions are altered by a broad range of forces fromelectrostatics and van der Walls to liquid and solid bridges(Hartmann and Palzer, 2011). The dissipation and storageof energy in the force chains allow a bed of particles toremain static and fail only under the application of a given
stress. But as the flow becomes more rapid, force chainsreorganise and break. When the deformation (strain rate)is faster than the ability for the force chains to recombine,
they can no longer transmit and absorb stress, and thematerial restructures creating a fluid-like relation between
the applied stress and strain rate (Campbell, 2006). As apowder dilates, the free space between individual grains
increases and the transport of momentum becomes dominated by instantaneous collisions of nearby particles.
For sufficiently diluted cases, the flow displays a gas-likebehaviour where collisions are rare, and the motion of eachgrain is uncorrelated from its neighbours.
The changes in the stress-strain rate relation are related

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

3

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

to how grains reorganise and how the local force network
responds to structural properties such as particle concentration, size and shape. Understanding the transition between
different flow behaviours is crucial to develop new technologies because solid operations span a wide range of particle
concentration, consolidation stress and shear rate. The design of a powder processing plant involves flows spanningfrom dilute inertial systems, such as in pneumatic transport,
to slow frictional flows in storage, packaging, tabletting, or
agglomeration devices like roller compaction (Wu et al.,2010) or twin-screw granulation (Dhenge et al., 2013). Operations such agglomeration in high shear mixers (Knight
et al., 2001) or fluidised bed granulators are designed towork under dense conditions and display local transitions
between solid and liquid-like behaviour (Mort, 2009). In
many cases, this happens in an uncontrolled way throughthe agglomeration and deposition of cohesive powders in
multiphase reactors, heat exchangers (Diaz-Bejarano et al.,2017) or spray dryers (Francia et al., 2015).
No universal framework unifies the description of
granular rheology, and therefore, industry relies heavily
on empirical characterisation to classify the flowability of
powders. The earliest attempts used scores based on flow
tests such as the Carr (Carr, 1965), and Hausner (Hausner,1967) ratios, or more recently the Taylor composite index(Taylor et al., 2000). The use of properties such as unconfined yield strength or tensile strength is also common,but the flowability function, FF, defined as the ratio of the
major principal stress to the unconfined yield stress in the
powder, is perhaps the most utilised metric to characterise
powder flow (Hassanpour et al., 2019). The characterisation is typically limited to identify a flow threshold, that is,
the stress required to initiate flow, and it rarely extends into
studying the dynamic flow properties. The work of GDRMidi (Midi, 2004) describes in detail the characteristics ofgranular flows in six typical experimental configurations.
Those where the stress is imposed, such as heaps, drums,
annular flows and inclined planes display a hysteresis in theyield stress. A given stress is required to establish a dense
flow, but much smaller stresses are needed to maintain it.
The yield point itself depends not only the particle properties but also on the stress history of the sample. All typicalflow configurations (Fig. 1) show a complex flow patternwhere dense areas governed by enduring frictional contacts
interplay with other more dilute ones driven by instantaneous particle collisions. Ultimately, all develop complex
velocity distributions varying from a localised shear bandin the confined systems to linear and exponential decays infree surface flows. Given that the behaviour of a powder
varies drastically from one to another, it is required to carryour several static and dynamic tests to properly evaluate
the flowability as close as possible to the desired design
conditions (Krantz et al., 2009).
Most available tests focused on the flow initiation and

4Fig. 1 Typical configurations to study granular flow: (a) Couette (b)rotating drums and flows in (c) chutes e.g. parallel planes, inclined,
vertical (d) and heaps.

suffer from two limitations: transportability and universality. The discrepancies observed across different devices(Koynov et al., 2015) are a reflection of an overly simplified description of the system and inconsistencies in theexperimental procedures. The effect of the stress history ofa sample is well-known (Swize et al., 2019), but without
a common way to condition the powder, it is challenging
to draw any direct comparison between different tests andsamples. The measurements are also not universal. The
most established techniques are shear cells limited to aquasi-static flow (Schwedes, 2003). It is a consequenceof the practical difficulty in studying inertial systems andthe historical need to inform the design of silos. Although
it is key to understand a dense granular flow (Sundaresan,2001), the characterisation of dynamic properties is still far
from the same level of detail.
Recent works have summarised the scope of the techniques available today to study the flowability of powders(Ogata, 2019), and the challenges involved in developing
reliable dynamic tests for the study of caking and cohesivematerials (Ghadiri et al., 2020). They discuss in detailthe effects of properties such as size and shape, cohesionand how the interstitial fluid and the applied stress affectthe flowability. Here, we will focus on the latter andspecifically discuss the characterisation of the transition
between two extreme flow regimes, namely solid-like andfluid-like flow, in a shear device. We provide an overview
of the design and application of classic units and discuss
the strategies to develop similar tests in modified devices
that can cover a broader range of shear and consolidationstresses. The manuscript is organised as follows: Section 2
introduces the granular flow regimes and presents a brief
overview of the mathematical modelling of granular flows.
A brief review of the characterisation of the flow threshold,Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

including a summary of shear cells is given in Section 3.
The strategies to re-design the conventional shear devices
to experimentally capture the transition from solid-liketo fluid-like behaviour using an external actuation are
discussed in Section 4, followed by conclusions and suggestions for future work.

2. Rheology of granular flows
2.1 Flow regimes
The flow behaviour of granular material depends on
the applied stress, particle concentration and the effects of
the interstitial fluid. If the concentration is high or close
to the maximum packing, the material exhibits solid-likebehaviour where stresses are transferred with frictional
contacts between grains and slip layers move relative toeach other along the applied shear. In this regime, namely
frictional or “quasi-static” regime (Fig. 2a), the contacts
between grains have a long duration, and deformationof the grain layers occurs very slowly (Campbell, 2002).
Due to a highly dense concentration of particles, there isno much free space for the interstitial fluid, and its effects
are usually neglected. In the quasi-static regime, flow isoften studied by using soil mechanics principles or more
specifically, plasticity models detailed in the next section.
On the contrary, when the applied stress or the external energy transfer is sufficiently high, the particles have enoughinertia to leave their layers and flow more independently.
This flow regime is referred to as “rapid flow” or “inertial”
regime. Here the transport processes are considered governed by binary instantaneous particle-particle collisions
and random motions (Fig. 2a). With an analogy with the
kinetic theory of monatomic gases, the concepts of the socalled granular thermal energy or “granular temperature”
and the random fluctuating kinetic energy of particles are
introduced in the framework of continuum modelling. The
main formal differences between inertial granular flows
and molecular gases are the finite size of particles and thenon-equilibrium behaviour. The particle-particle collisions
are dissipative; therefore, the fluctuating kinetic energyof the particles is dissipated to thermodynamic heat. The
applied shear generates fluctuating kinetic energy throughcollisional and kinematic stresses (Fig. 2b). For a collisional stress, any collision between particles moving attheir mean velocity in a simple shear will enhance random
motion and lead to a velocity fluctuation quantified in the
granular temperature. However, for a kinematic stress, themotion of a particle parallel to a velocity gradient generates
a random velocity along its path (Fig. 2bii) and a source ofanisotropy in the fluctuating kinetic energy.
For inertial granular flows with low and moderate solid
concentrations, the interstices between the particles are

Fig. 2 Granular rheology. Sources of (a) stresses (kinematic, collisional and frictional) in a quasi-static, an intermediate and an inertial
flow regime for varying inertial number I, normal stress σ, shear rate and solid fraction εs (b) generation of fluctuating kinetic energy inkinematic and collisional mechanisms.
図キャプション：8pt(31)

far larger than in the quasi-static regime. These spaces arefilled with fluid, and the granular material is then described
as a multiphase flow, referred to as a gas-solid suspension,
where the fluid-particle interactions become significant on
the momentum transfer between phases. Many advanced
formalisms, however, focus on a collision-dominated regime and disregard the effect of interstitial fluid. Other effects typical of real-life scenarios like shape, polydispersity
or interparticle forces are often excluded from a continuum
formulation. In the extreme of a very dilute (kinematic)
gas-solid suspension, particle-particle collisions never
happen, and the solid phase momentum simply diffuses as5

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

the particles travel through the medium (Tsao and Koch,
1995). Their motion is mainly driven by the carrier fluid
and the interstitial fluid contributes to the particle stresses
with a covariance between particle and fluid fluctuations(Koch, 1990). Gas-solid suspensions are not within thescope of this review, and comprehensive discussions areavailable elsewhere (Fan and Zhu, 2005).
In between these two extreme regimes, there exists anintermediate regime with a characteristic particle contact
time larger than the instantaneous collision time but lower
than an enduring contact. It lies between the quasi-staticstate dominated by frictional forces and the inertial state
dominated by collisional stresses, and therefore, affectedby both. This work concerns with the experimental characterisation of such a system. From a phenomenologicalmodelling view, the transition between regimes can becharacterised by the inertial number, I, given by Jop et al.
(2006), as a scaled shear rate quantifying the interplay ofthe consolidation and the shear stress acting on a particle:
I

 d
/

t
I 

(1) t (1)
/  /d1 / 

(2)

I can be interpreted as the ratio between the time scaleassociated with the consolidation and the time scale of(2)
the strain as given in Eq. (2). As discussed in GDR Midi
(Midi, 2004), the shear or deformation time scale, tγ, canbe though to represent the time needed to create a deformation by moving the top layer applying a shear stress, τ.
The confinement scale, tσ, represents the time needed toreorganise this structure pushing the top layer to its lower
position and creating a packed system. Fig. 3 illustrates
the concept shearing a granular layer. If the confinement isvery quick compared to the deformation, the system willremain structured at a high concentration. On the contrary,
if σ is not high enough to preserve the confinement, thesystem dilates. In the limit of I→0 a powder remains in aquasi-static state and the system behaviour is independentof the shear rate and purely controlled by a constant ratio
between the shear and the normal stresses, τ⁄σ, denotedby different authors as apparent viscosity, μa or ηa, or thebulk, μb, or effective, μeff, friction coefficient or angle ofFig. 3 Depiction of the inertial number I as the ratio of the deformationand compression timescales, t γ and tσ.

6internal friction. In practical terms, even in a quasi-static
flow tσ cannot tend to zero, and in reality, the grains experience rearrangements and slow displacements that resultin intermittent dynamics. When the inertial number, I,
increases, the particle inertia starts to play a significant rolein the transport of momentum, and the system behaviour
becomes dependent on the shear rate.

2.2 Overview of mathematical modellingThis work does not intend to review the modellingof granular flows. Here we present a brief overview ofthe phenomenological, theoretical and computational approaches used to described granular flows in the context
of shear-cell devices. We refer the interested readers toCapriz et al. (2008) and Rao and Nott (2008) for a boarder
discussion and comprehensive reviews on kinetic theories,
plasticity, continuum and discrete modelling of granular
flow and the relevant references.
A continuum description is the preferred way to describe
granular flow in industrial processes handling billions ofparticles. For quasi-static flows, the theory of plasticity
is often used to develop continuum models. Specifically,
the plasticity theory determines the normal, σ, and shear
stresses, τ, as a function of the strain rates (changes in the
distance of adjacent particles with time in the neighbourhood of a point). In a slow regime, the frictional stresses are
independent of the strain rate, and under a normal stress,
granular material will shear only when the shear stress, τ,
exceeds a critical value. The failure behaviour is simply
described by a yielding law such as a Mohr-Coulomb
criterion but yielding laws do not provide information
on how particles flow or blocks of particles deform. To
overcome this limitation, plastic potential theories arecomplemented with the critical state theory using yield andpotential functions. Chen and Mizuno (1990) proposed apathway to relate the applied stress to the deformation and
Vun et al. (2010) listed the procedure to follow: (i) definea yield function, (ii) apply a plastic potential function torelate the rate of strain tensor to stress and (iii) set up a flow
rule that links the yield function to the plastic function.
The proposed quasi-static models feature different yieldfunctions. For example, Srivastava and Sundaresan (2003)
used the extended von Mises function, while Christakis
et al. (2006) developed a viscoplastic model based on
the Drucker-Prager plasticity function. The extended vonMises yielding law-based models was criticized (Dartevelle, 2004) for not accounting for energy dissipation andpredict infinite dilatancy, but these physical inconsistencies
are removed with a 3-D ‘‘compressible’’ formulation (Grayand Stiles, 1988). The limitations of these functions are
discussed by Andreotti et al. (2013).
Rapid granular flows have been investigated by experimental studies and statistical mechanical methods. The

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well-known experimental study of Bagnold (1954) where
spherical spheres were sheared in a coaxial cylinder rheometer, is the pioneering work on the constitutive behaviourof inertial granular flows. This heuristic study showed thatthe solid stresses, σ and τ, were a function of the square of
the applied shear rate, , at high rotating velocities. Fromthe view of the theoretical modelling, the Kinetic Theory
of Granular Flow (KTGF), an extension of the classical kinetic theory of gases to(11)dense and inelastic granular flows,
has been developed for forty years (Garzó and Dufty, 1999;
Lun et al., 1984; Yang et al., 2016). In the KTGF approach,
the granular material is modelled as a continuum medium,and the transport equations for solid concentration, momentum and granular temperature are derived. The square
relation between the solid stress and the shear rate has beentheoretically confirmed by KTGF models. Early comparisons of with annular-shear-cell test measurements werefirst reported by Lun et al. (1984) and later on several otherstudies (Hanes and Inman, 1985; Hsiau and Jang, 1998;
Orlando and Shen, 2012). However, these experimental
configurations provide information on the bulk behaviourof the granular material and not the motion of individual
grains. Further comparisons of KTGF predictions withlocal granular measurements include the work of Wildman
et al. (2008) where positron emission particle tracking(PEPT) was used to measure solid concentration and mean
velocity profiles inside a three-dimensional annular shear
cell.
Besides a continuum formulation, granular material canbe studied by computational approaches such as Discrete
Element Modelling (DEM) where individual particles aretracked via a Lagrangian approach solving Newton’s equations of motion and describing particle-particle collisions
with a soft sphere model (Guo and Curtis, 2015). Thesesimulations are classified as highly resolved because they
can provide flow properties at particle-scale such as velocities, contact number and forces. Due to the high demandfor computational resources, the method is applicable foracademic studies and small-scale laboratory experiments.
DEM simulations capture the persistence of a Bagnold
regime (da Cruz et al., 2005) in homogeneous shearingof particles in fully periodic domains with Lees-Edwards
boundary conditions, and are used to investigate boundary effects on confined geometries such as Couette flows(Vescovi et al., 2014).
The intermediate regime was first experimentally identified in inclined plane chutes (Pouliquen, 1999) and later ina Couette shear cell (Tardos et al., 1998), where the shear
stress τ was found to depend on the strain rate to a powerof between 0 and 2 that is a function of the solid concentration. While continuum models are available for quasi-staticand inertial granular flows, the closures for the intermediate
regime are still under debate. Johnson and Jackson (1987)
proposed a semi-empirical model that super-imposed

collisional and frictional stresses modelled with a criticalstate and an algebraic function of solid concentration.
A similar “additive” approach was applied by (Savage,1998) with using von Mises yield criterion. From a more
empirical point of view, Jop et al. (2006) unified these two
extreme regimes with a simple visco-plastic constitutive
law without any fitting parameter and validated their modelwith experiments of a granular pile flowing between roughsidewalls. The model is called the μ(I) model. It is basedon the Coulomb criterion and a bulk friction coefficient
function of the inertial number, I, Eq. 1. Similarly, da Cruzet al. (2005) performed DEM simulations of plane shearing
with frictional, inelastic disks and found that small valuesof I correspond to the quasi-static regime of soil mechanics,
while large values correspond to the collisional regime of
the KTGF.
There have been different ways to incorporate the frictional contribution of a dense flow into the KTFG (Wu etal., 2020). For example, Chialvo et al. (2012) carried out
homogeneous shear DEM simulations of frictional andfrictionless particles in the quasi-static and inertial regimes,
and proposed corrections to the model of Garzó and Dufty(1999) to bridge these regimes using the μ(I) rheology
model. Similarly, Vescovi et al. (2014) performed DEM
of wall-bounded plane shearing of particles and used theexpression for the correlation length developed by Berzi(2014) to modify the model of Garzó and Dufty (1999).
Jenkins (2006) proposed a phenomenological correction to
the rate of collisional dissipation in the KTGF model that
describes the decrease in dissipation of fluctuations during
enduring contacts. There are several studies that attempt
to expand the μ(I) models to a non-local rheology, forexample, using additional transport equations to describea weight function between fluid and solid-like parts ofthe stress tensor (Aranson and Tsimring, 2001; 2002), or
proposing new closures for μb dependent on coordination
number and the evolution of a fabric anisotropy tensor (Sunand Sundaresan, 2011). An application of non-local μ(I)rheology in quasi 2-D shear cell experiments has also been
given by Tang et al. (2018).

3. Quasi-static characterisation: shear cells
Shear cells are experimental devices designed to evaluate the flowability of a powder finding the relation between
applied normal stress, σ, and the shear stress, τ, required
for a static powder bed to fail. The operate performing
shear tests by applying two orthogonal stresses on a sample
and measuring its response. The first stress is denoted by
the normal or consolidation stress, σ (see Fig. 4a). σ isoften aligned with the gravity acceleration and includes
the weight of the powder. The second stress is orthogonal to the first one, and denoted by the shear stress, τ. It

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Fig. 4 (a) A granular layer under shear, τ, and consolidation, σ, stress.
(b) Yield locus line, τ = μ σ + C; μ: angle of internal friction; C: cohesivestrength; UYS, MPS: unconfined yield stress and major principle stress.

is increased gradually until the sample reaches its yield
point and starts flowing. Shear tests include two steps, aso-called pre-shearing test followed by the application offour to six different shear stresses. The objective of the
pre-shearing test is to create a reproducible structure in the
powder by applying a reference consolidation stress. The
sample is consolidated at high normal stress, σpr, and thenit is sheared until it fails and the recorded shear stress, τpr,reaches a constant value, denoted steady-state conditions.
The pre-shearing normal and shear stresses (σpr,τpr) set
a reference point for the study (blue point - Fig. 4b). At
this point, if the shear stress is removed, the displacementceases, but the sample reorganises into the same structureand so it exhibits the same response when it is sheared
further. After the preparation stage, several experiments are
conducted varying σ and τ, denoted “shear tests” or “shear
points” (red - Fig. 4b). The sample is sheared to the failure
point with a decrease in the consolidation stress (σ < σpr).
For each value of σ, the shear stress corresponding to thebed failure, τ, is recorded and reported in a (τ,σ) diagram tobuild the yield locus line: τ = μ σ + C where μ is the angle
of internal friction and C is the cohesive strength. The locus
line describes the yield stress in quasi-static granular flow,
it takes the form of a Coulomb behaviour where the yieldstress is independent of the shear rate. It should be notedthat the state of stress achieved in the sample after the
pre-shearing is particular to each device, which introduces
a degree of specificity to the method.
The angle of internal friction, μ, is reported as the slopeof the yield locus line connecting all (τ,σ) pairs. In otherwords, the ratio between the shear and normal stresses τ/σ8required for a sample consolidated at (σpr,τpr) to yield. Mohr
circles are used to derive other important parameters. The
principal stresses are defined as the base of the stress tensor
that creates no shear stress in the system and therefore,
minor and major, MPS, principal stresses can be obtained
as the intersection of a Mohr circle with the axis τ = 0. A
Mohr circle tangent to any point in the yield locus line isa representation of the conditions for critical failure at thatcombination of σ and τ. The principal stresses that describe
the structure of the powder sample are obtained from theMohr circle that contains the reference (σpr,τpr) and is tangent to the yield locus. The unconfined yield stress, UYS,
is defined as the normal stress required for the powder toyield under no shear. It is obtained from the Mohr circle
that contains the origin (a sample sustaining no stress) andthe yield locus line. There are other definitions of the locus
line stemming from shear tests. The bulk (or effective) μb
friction factor defined from a bulk yield locus line (τ = μbσ) that contains the origin and is tangent to the Mohr circleof the pre-sheared sample. The relation between the shear
and the normal stress in the pre-shearing point is given byτ = μss σ with μss the steady-state angle of internal friction.
The flowability function, FF, is reported as the ratio of MPS
to UYS.
Shear cells, or testers, can be classified into two categories: direct and indirect testers. In a direct tester thegeometry of the device imposes a sheared region on thesample, whereas in an indirect tester, the sheared zone in
the powder develops independently according to the stressapplied. Many indirect testers such as the uniaxial, bi-axial
and tri-axial testers were developed for specific applications and are generally not commercially available (Feiseand Schwedes, 1995; Jenike, 1970; Schwedes, 1996). This
work will focus on describing succinctly direct units, particularly examples of commercially available translationaland recent rotational devices. More comprehensive detailsof the design and the historical development of shear cells
can be found in the literature (Schwedes, 2003).

3.1 Jenike type translational testers
The working principle of translational shear testers iscreating shear by sliding one section of the sample. Jenike
provided one of the first translational devices used to study
flowability (Jenike, 1970) and design silos, leading to an
ASTM standard (Carson and Wilms, 2006). It consists in acontainer, or cup, with a stationary base and an upper ring
subject to shearing. The cup is filled with a powder sample,
and the lid is used to compact it by applying a constantvertical force (Fig. 5a). A horizontal force is applied tothe top ring until the bed fails and starts to slide. Fig. 5b
depicts the typical evolution of the shear stress, τ, inthe pre-shearing and shearing steps. In a Jenike test, thesteady-state flow condition is met when one observes a noVictor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

Fig. 5 Translational testers. (a) Cross-section of a sliding device (b)Qualitative illustration of the evolution of the shear stress during theexperimental procedure.

changes in τpr under the pre-shearing normal stress, σpr. In
a successive step, τ is set to zero removing the force and is
σ is reduced. The sample is sheared gain, and the value ofτ at the failure point is recorded as the first shearing point.
Additional tests using new samples are required to obtaineach point of the yield locus (Fig. 5b). The simplicity ofthe test made it widely accessible to industry as a way torank powders and study the effects of environmental conditions, composition, moisture, size and shape. However, thissimple configuration comes with a significant limitation.
The cell has a short shearing path, limited by the maximum
displacement, and for that reason, it does not allow for acontinuous test. A new sample is needed to measure eachshear point, which leads to a time-consuming process witha substantial intervention of the operator, and thus prone
to error.
Several works tried to overcome this limitation introducing a “constant volume methodology” (Duffy and Puri,
1999; Ladipo and Puri, 1997; Schulze, 2008; Tsunakawa
and Aoki, 1982) whereby the Jenike tester is modified
to operate continuously. After the steady-state flow isachieved at the prehearing test, σ is gradually reduced at asmall speed releasing the load on the lid. The corresponding evolution of the shear stress, τ, is recorded to construct
the yield locus line. The main advantage is the ability toperform a single continuous test measuring the evolutionof the sample from the point (σpr,τpr) to the point C using
one sample (green line - Fig. 4b). The early versions of theconstant volume translational testers were subject of criticism (Schwedes, 2003) because of their complex configuration. It has been suggested that this methodology tends tounderestimate the unconfined yield stress, nevertheless, tothe best of our knowledge, no detailed direct comparatives
confirm such a feature.
More recently, Shimada et al. (2018a; 2018b) developed
a new device to evaluate flowability using a constantvolume shear tester. The methodology aims at providing
continuous measurement of shear stress from a highconsolidation point under no shear (σcvt,0), through thesteady-state flow reference state (σpr,τpr) until the point atzero normal stress (C,0). The line from the point (σcvt,0)to the point (σpr,τpr) (purple line, Fig. 4b) is referred to as
the “consolidation yield locus”. The configuration of thetester is depicted in Fig. 6. The upper section of the cell
can be filled with a varying height of powder, allowing one
to conduct tests at a constant and controlled void fraction.
Once the powder is loaded in the cell, a vertical servo motor lowers the piston compressing the sample to the desired
stress (σcvt,0). When the value is reached, the vertical motion stops at a fixed position for 2 min to relieve the excess
stress. Afterwards, the horizontal servo motor applies ashearing force on the lower section until the shear stressreaches a constant value, τpr, registering the transition from(σcvt,0) to (σpr,τpr) directly (purple line - Fig. 4b). Next,
the consolidation stress, σ, is reduced to zero by gradually
lowering the vertical translation stage, reducing the shear
stress from τpr to C (green line - Fig. 4b). The set up allows
having a three-dimensional relationship between τ, σ andparticle concentration εs. It is comparable to historical testers and obtains the yield locus line in a single test of one
sample. However, it is still restricted to the length of theshearing path. While these testers are not widely available,
the reports involve the use of fine powders and the possibility to use small consolidation stresses.

Fig. 6 Constant volume tester. Reprinted from Shimada et al. (2018a)
under the terms of the CC-BY-NC-ND 4.0 license. Copyright: (2018)
The Authors, published by Elsevier B.V.

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3.2 Rotational shear testers
Rotational testers overcome the restriction of a shortshearing path employing a rotational force on two possible
geometries: a circular path (Fig. 7a) or an annular path
(Fig. 7b). In both, shearing is induced by rotation andthe normal force is applied on the top. To shear the bulk
powder, the lid and the base must rotate relative to eachother. In most devices, this is achieved applying a torque,T, on the base while the lid is fixed, such as in the Schulze
shear cell (Schulze, 1994). The reverse configuration, afixed base and a rotating lid are used in testers like theFT4 (Freeman, 2007) and the Brookfield PTF (Berry et al.,2014). The surfaces of the base and the lid are roughened or
equipped with blades to avoid sliding between the powder
and the wall. The experimental procedure of rotationaltesters follows the same sequence: a pre-shearing step thatconditions the sample, and a shearing test for every pair ofnormal and shear stresses to build the yield locus line. A
rotational unit can apply an unlimited shearing path, andin this way perform multiple measurements on a single
sample. It is easier to automate and therefore, reduces
human error.
Many types of rotational testers can be found in literature, e.g. (Berry and Bradley, 2007; Bishop et al.,
1971; Carr and Walker, 1968; Orband and Geldart, 1997;
Schwedes, 1996). All operate under the same principles,and vary in their geometry, size, the range and the levelof automation in the application of stress, and critically, inthe sample preparation and the pre-shearing stage. Here,we will focus on describing three commercially available
rotational testers: the Schulze shear cell, the Freeman
FT4 shear tester and the Brookfield PTF, as representative
examples of the design and the scope of the application ofring (Schulze and Brookfield) and torsional (FT4) units.
Fig. 8 describes qualitatively the experimental procedure. The Schulze shear cell (Schulze, 2008) is one of thefirst automated rotational shear devices. It features a rotating ring with a base that contains the sample, covered witha fixed annular lid where the normal force is applied. The
inner surface of the ring and the lower side of the lid areroughened. Shearing is induced by rotating the bottom ring

Fig. 7

Diagram of (a) torsional, (b) annular (ring) shear tester.

at angular velocity, ω, maintaining the lid stationary. To
apply a normal force and rotation independently, the design
includes additional elements, such as tie rods and a crossbeam used to stop the lid from moving. A normal force
is exerted on the top and transmitted to the sample as thenormal stress, σ. An upwards force counters the weight of
the lid allowing the cell to operate under a small σ. The procedure is similar to that in Fig. 5b, but without the need tochange the sample. It is faster and easier to automate. Afterthe measurement of the first shear point (σ1, τ1), the sample
is reconsolidated to σpr and sheared again to τpr (Fig. 8a).
The normal stress, σ, is reduced, and the sample is sheared
again to register the next point of the yield locus. Fig. 8billustrates the experimental procedure in a Freeman FT4
shear tester (Freeman, 2007; Freeman et al., 2009). An FT4
shear cell is a torsional shear cell in a reverse configuration,
whereby the base is stationary, and the shear is induced
by a circular rotating lid (Fig. 7). The stainless-steel lid isfitted with 18 baffles of 2 mm in height to ensure that theshearing occurs only between the grains. The base is a cylindrical glass vessel plugged with a rough plastic cover on
the base. The consolidation stress is applied lowering thelid onto the sample, and it is measured at the bottom. Oncethe desired value, σpr, is reached, the cell is rotated at very
low speed, and the torque is recorded continuously. The
procedure is the same, but the pre-shearing is different. The
consolidated sample at σpr is sheared to the failure point inconsecutive pre-shearing steps until the maximum shear
stress, τpr, registered in each step remains constant (< 1 %difference - Blue - Fig. 8b). At this reference point, the firstshearing test is performed reducing σ and registering the τrequired for the bed to fail. In this step, the axial positionof the lid is kept constant, and τ is computed as the peak ofFig. 8 Examples of rotational cells. Qualitative illustration of the evolution of the shear stress during the experimental procedure to construct theyield locus in (a) Schulze ring shear cell, (b) Freeman FT4 powder shear cell, (c) Brookfield PFT.

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the shear curve (Red - Fig. 8b). Shearing is repeated at avarying σ to complete the yield locus line using an intermediate pre-shearing state in between each measurement
to recondition the powder to (σpr,τpr). Fig. 8c describes
qualitatively the test in a Brookfield Powder Flow Tester
PFT. A Brookfield unit is like a Schulze tester, an annular(ring) device, but arranged in a reverse configuration witha stationary base and a rotating lid. It follows an experimental procedure similar to an FT4 with a slightly different
definition of τpr (Berry et al., 2014). The cell is made of astainless-steel annular base and a bladed lid. The consolidation stress is applied lowering the lid and measured at the
top of the device. The sample if consolidated at high stress,
σpr, and sheared several times until reaching a steady-state(Blue - Fig. 8c). One of its particularities is that the yield
locus line is constructed from low to high consolidation,
starting from a measurement at the lowest stress, 13  pr ,followed by 12  pr and σpr.
Shear cells are used as standard for the evaluation of theflowability of industrial powders and study their stability(12)during storage, a key attribute of formulated powders. In(13)many cases, materials are complex matrices of crystalline
and amorphous components that are prone to cake throughadhesion, sintering, deliquescence and formation liquidand solid bridges. Shear cells provide a way to study theeffect of particle properties and the environment in thisprocess. For example, Deshmukh et al. (2019) reports a
recent study using a Schulze cell as an in-vitro tool for oralprocessing of foods, but similar devices have been used for
decades. Teunou and Fitzpatrick (1999) proposed a ring
unit specifically designed to study foods and investigated
how environmental conditions affect the flow of flour, tea
and whey powders (Teunou et al., 1999). The cell was
installed in a chamber with controlled relative humidity rH
and T. As expected, an increase in either of the two leads
to a reduction in the flowability. The effect of consolidationand storage time was studied in a Jenike type cell (Teunou
and Fitzpatrick, 2000) providing the evolution of flow
functions. Fitzpatrick et al. (2007) used a similar device tostudy the effects of formulation and storage time in dairy
powders. Opaliński et al. (2012) designed another Jeniketype shear tester to study moist food powder and similarworks on the study of mixtures of coal and sawdust or
biomass mixtures were reported by Chen et al. (2012) andZulfiqar et al. (2006). Torsional units have also been shown
flexible tools. Guo et al. (2015) and Chen et al. (2018)used the FT4 shear cell to study the flow of biomass andcoal blends with and without a varying level of moisture.
Crawford et al. (2016) used it to study the effect of preprocessing of biomass and Léonard and Abatzoglou (2010)
to investigate lubricated and unlubricated pharmaceuticalpowders. The FT4 shear cell was also used by Leung etal. (2017) to investigate the flowability of pharmaceuticalpowders mainly driven by cohesion.

Although fundamental and comparative studies are lessfrequent, they can shed light into the local stress distributions and on how the particle level properties relate to thebulk behaviour. For instance, Zafar et al. (2015) used a
Schulze shear cell to investigate the flowability of cohesive
powders, and compared the results to characterisation
techniques such as the ball indentation (Hassanpour andGhadiri, 2007) that measures the hardness at a low consolidation, and the Sevilla Powder Tester (Castellanos et al.,2004). Louati (2016) and Louati et al. (2015; 2017), useda Schulze shear cell for a fundamental investigation of the
impact of moisture and particles size on the flow of glass
beads, and Hammerich et al. (2020) designed a modified
ring cell to study liquid saturated sediments. Wang et al.,(2016) proposed instead a new method to analyse datausing the FT4 under different initial consolidation. They
tested over 40 powders with four initial consolidationstress and proposed an empirical relation between the flow
function and a dimensionless cohesion C* (C* = C⁄σpr) that
separates the effects of initial consolidation stress and thetesting device.
There are other available shear devices like the Anton
Parr rheometer that uses impellers for shearing, the Peschlcell that modifies a standard ring shear cell, and othercommercially available units like the Hosokawa Micron
Powder Tester or GranuDrum. Many others well-known
testers have been developed for specific applications inresearch laboratories, for example, the use of fluidised
beds to measured tensile strength (Castellanos et al., 2004)or flowability (Girimonte et al., 2018), and the analysis
of caking with direct or indirect measurements of unconfined yield strength in uniaxial compression testers, e.g.
(Hassanpour and Ghadiri, 2007; Thakur et al., 2014).
From a more fundamental point of view, the use of visualisation techniques such as Magnetic Resonance Imaging(MRI) can reveal the transmission of stress in a quasi-static
flow at a particle level. Commercial shear cells made ofmetal are not suitable, but novel shear testers have been
designed for this specific purpose (Mueth et al., 2000).
The work of Cheng et al. (2006) and Sakaie et al. (2008)
reports a direct measurement of the evolution of the local
packing of a slow and smooth granular shear flow in a splitbottomed geometry. They sheared MRI sensitive seeds at
different rotational velocities and collected MR-images
after stopping the shearing process. Börzsönyi et al. (2011)
followed a similar approach to demonstrate that a shear
zone develops preferentially in regions with a lower friction. They studied a U-shaped horizontal shear cell consisting of two parallel L-shaped sliders and characterised theshearing band recording the displacement of MRI-sensitive
poppy seeds loaded in a sample of MRI-insensitive glass
beads.
Classic or new devices and commercial and custom
designs, all shear cells work under the same principle. And

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yet, different dimensions, sample volume and pre-shearing
procedures lead to disparities in the measurements fromdifferent testers. The impact the history of a powder has
in its response to stress is well documented (Swize etal., 2019), but the sample preparation procedures are still
specific to each device. The work of Berry et al. (2014) andSalehi et al. (2017a) compares the measurements of Brookfield, Schulze and Jenike testers, and Koynov et al. (2015)
reports on a comparative study of shear cells evaluating theflow of coarse (59 mm) and fine (4 mm) alumina powder.
Salehi et al. (2017a) found no important disparities between
testers, the largest differences being ascribed to highly
compressible powders, but the observations of Berry et al.
(2014) were consistent with the issues listed by Koynov
et al. (2015). In their comparative work, all shear cells
provided a good qualitative measurement of flowability,
but they were found to be more efficient with fine, cohesive
powders. In free-flowing powders, measurements could
not be used in a quantitative way to rank the materials but
only to identify them as free-flowing. Comparison acrossdifferent cells showed that not only the consolidation stressduring pre-shearing is important, but also the type of shear
cell. Barletta et al. (2015) provided a similar comparative
analysis in the context of biomass and identified importantdifferences only in the wall friction coefficients. It is in linewith the work of García-Triñanes et al. (2019), which finds
minor differences in the measurement of tensile strength ofcohesive powders in a Schulze and a Brookfield unit.
The full range of available devices to characterise thequasi-static flow of complex cohesive mixtures is describedby Ghadiri et al. (2020), Ogata (2019), and Schwedes(2003). Here we provided the reader with an overview ofthe design of classic shear testers, their limitations and theirscope for application. In the following sections, we describe how the modification of the classic designs with theuse of aeration and other external sources of actuation canlead to a new type of devices that are capable of performing
measurements in an intermediate regime and providing amore complete picture of the granular rheology.

4. Beyond the quasi-static regime
In the quasi-static regime, the yield locus line describes
the failure of a network of enduring contacts between particles in a bed of powder. Under an applied normal stress,
σ, the required shear stress τ = μ σ + C is purely a functionof the bulk material properties and the structure of thesample created by the consolidation at (σpr, τpr). However,at higher shear rate, or lower consolidation stresses, thepowder dilates, and as it transitions into an intermediate
regime, the shear stress, τ, establishes a dependency on theshear rate, . There are several ways to try to replicate andcharacterise this transition in a modified shear cell. In order

(11)
12

to depart from the quasi-static regime, one must operate ata higher inertial number, I, (see Eq. 1) by either operating
at a sufficiently high shear rate, , or at a sufficiently low(constant) consolidation stress, σ.
The operation at  simply by operating at a high rota(11)tional speed in indeed possible (Bagnold,
1954) but in practice this can lead to attrition of fragile particles. Ghadiri etal. (2000) discuss in(11)detail the importance of breakage andsegregation in a annular cells using catalyst powder, andHare et al. (2011) provide an example where measurementsof the attrition of pharmaceutical powders in a shear cell
are coupled with computational studies in an agitated bed.
Alternatively, the inertial number, I, can be reduced
operating at low consolidation stress, σ. Doing so requires
the application of an energy source to the bed that can overcome the action of the gravitational acceleration that would
otherwise consolidate the sample. The additional energy input can be introduced by the action of a particle-fluid force
using aeration or even complete fluidisation, or throughmechanical acceleration, such as agitation or vibration of
the sample. The following sections provide a summary of
current strategies describing a selection of shear devices
that use an external actuation to operate at low consolidation stresses. Modified classic shear cells are introduced in
Section 4.1, and Sections 4.2 and 4.3 describe the designof Couette-type rheometers and the use of mechanicallyagitated aerated or fluidised beds.

4.1 Modified shear testers
One of the first modified shear testers was introduced by
Klein et al. (2003). They developed an annular (ring) cell toshear a limestone powder (dp < 15 μm) at varying normal
stress and a shear velocity between 0.07 to 4,200 mm/min.
The design resembles a Schulze tester with the functionality of powder aeration. A motor is fixed to the base to rotate
the shear cell at the desired velocity. The base and the lid
are made of a permeable material, and feature 24 thin baffles to prevent the sample from sliding during the shearing
process. The vertical normal stress, σ, is applied by the lidon the top of the sample. Aeration is modulated via a mass
flow controller or through the measurement of air pressurein the exhaust. A f﻿luidisation index, FI, is defined as ratio
between the pressure drop of the gas flowing through a bedof powder ΔP, and the pressure drop required to counterthe weight of the bed and reach the minimum fluidisation,∆Pmf = W⁄A. Or in other words, the ratio between the gas
superficial velocity, uɡ, and the minimum fluidisation velocity, umf, FI = ∆P⁄∆Pmf~u⁄umf. When particles are aerated
by a gas velocity lower than umf, FI < 1, the bed of powder
remains static but it sustains much lower normal stress,
σ, due to the reduction of its effective weight under theaction of a drag and buoyancy forces. Klein et al. (2003)
studied the effect of aeration in the rheology of limestone.

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

They observed no differences in the shear stress, τ, required
for the bed to fail under a constant normal stress, σ, and a
fluidisation index FI < 0.7, in an indication that the powder
remains in a quasi-static regime. However, under a higher
FI but still operating with a fixed bed, 0.7 < FI < 1, theshear stress, τ, was found to decrease for an increasing air
velocity indicating the presence of an intermediate regime
between the quasi-static and the collisional regime characteristic of a fully fluidised system at FI ≫ 1.
Another example of a classic tester with an aeration
functionality was proposed by Johanson and Barletta(2004). They modified a Schulze device, to operate undera continuous counter air flow using a base of permeable
media and a modified perforated lid. Air pressure wasmeasured at the inlet and the flow was controlled with arotameter. They performed shear experiments on a fine silica powder (dp = 8 μm) and an FCC catalyst (dp = 50 μm)
and with a range of aeration up to FI = 1. As expected, theunconfined yield strength of the bulk material was foundto decrease with increasing aeration. The effective angle
of internal friction decreased approaching full fluidisation.
Other modified testers include the device developed byBarletta et al. (2007), which coupled a circular cell with therotating plate of a Peschl shear test bench to investigate theeffect of aeration in the flow of fine silica (dp = 7.6 μm) andmagnesium carbonate (dp = 3.5 μm). The design resembles
that of a short FT4 rheometer, featuring a circular fixedbase and a bladed rotational lid. The base is 61.8 mm in
inner diameter and 15 mm in height, and it consists ofa porous bottom plate that ensures a homogeneous air
Fig. 9 Depiction of a generic geometry of a (a) Coaxial-Cylinder rhedistribution. The experimental procedure mimics that ofometer applied to powders, and its use within a (b) flow and (c) aerated
device. Nomenclature: Ri and Re: inner and outer radii, L: bed heightFig. 8b. Experiments were performed at low shear rates, subject to shear; ω: rotational speed.
, and normal stress, σ, and below the minimum fluidisation(FI < 1). Their results confirm the observations of Klein et(11)al. (2003): for a fluidisation index FI < 0.7 no significant

a dimensionless characteristic shear rate,  C  w d / g ,differences appear in the angle of internal friction, in anwhere w is the shear rate at the wall. The use of  C is aindication that even when aerated, the samples remained inparticular case of the general inertial number I (see Eq. 1)
the quasi-static regime.
(14)
that considers a hydrostatic pressure as the source of the
(16)
(15)
consolidation stress. Experimental velocity profiles in Cou4.2 Couette-type shear testers
ette cells show the existence of localised shear bands on thewall of the rotating cylinder that depend on the conditions
Annular cells are a classic arrangement to study the rheof the boundaries. In order to avoid sliding, the walls of theology of Newtonian and non-Newtonian flows (Viswanath
cylinders must be roughened mechanically or by glueing
et al., 2007). Fig. 9a provides a generic description of theparticles or sandpaper. Due to the simplicity in design
geometry. In these devices, the fluid is sheared in between
and control, Couette cells are an excellent alternative totwo coaxial cylinders: an inner rotating one called bob andstudy the intermediate flow regime. The type of geometry
an external steady cylinder called cup. The viscosity anddescribed in Fig. 9a has been used for a long time to study
the shear stress are computed from the angular velocity,
powders and capture the stress–strain rate relationshipω, and the torque, T, applied to the inner cylinder. Cou(Craig et al., 1986; Hanes and Inman, 1985; Savage andette-type shear testers have been often used to study granSayed, 1984). Modern devices without any actuationular flows. Interested readers are referred to the overview
include the units proposed by Tardos et al. (1998) and a
by GDR Midi (Midi, 2004) for characteristic experimental
shorter, annular device described by Klausner et al. (2000).
velocity profiles. The evolution of the bulk or effective fricEvery cell imposes a fixed shear rate and relies on the action
tion coefficient μb in a Couette cell is given as a function of13

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

of gravitational acceleration to consolidate the sample. The
earlier studies establish a dependency of the shear stress on
the shear rate that simply by operating at high shear rate, , increasing the rotational speed of the inner cylinder, andthus w . The boundaries for the transition from the qua(11)si-static to the intermediate regime and inertial regimes arestill under debate. Experimental values have been proposed(15)
by Tardos et al. (1998; 2003) for the departure of the quasi-static regime, i.e.  C ~ 0.15 / 0.25 , and the collisional regime  C ~ 3, and later confirmed in computational studies(Vidyapati et al., 2012). In order to achieve a more general(17)
description and reacha higher range of inertial numbers, I,(18)
one canalso reduce the consolidation stress, σ, linked to thepowder weight. In the following sections, we describe thedesign of Couette cells that introduce aeration or flow in a
coaxial-cylinder configuration, Section 4.2.1, and virtual
cells that minimise sliding effects, Section 4.2.2.

4.2.1 Aerated coaxial-cylinder rheometers
Two alternatives have been proposed in literature inorder to actuate a coaxial cylinder rheometer (Fig. 9a) andoperate at higher inertial numbers. One can impose an axial
particle flow in the annular section inserting the unit in flow
device (Fig. 9b) or inject a counter-current stream of air toreduce the consolidation stress in an aerated or fluidisedchamber (Fig. 9c).
Tardos et al. (1998) first used a coaxial cylinder rheometer to investigate shear stress of non-aerated and aerated
powders. Its geometry and operation conditions are listed
in Table 1. The unit featured two concentrically placed
cylinders and the possibility to aerate the bed. The walls ofboth cylinders were covered with sandpaper to minimise
sliding. Two sets of experiments with and without aeration
were performed to study the effects of torque and the heightof the powder bed on the stress evolution. The experiments
under aeration (0 < FI < 1) investigated the distributionof stress under a varying shear rate. Fine free-flowing dry
powders were tested at three rotational speeds, ω, andthree bed heights, L. The authors proposed a model for the
Table 1variation of the torque, T, based on the assumption of alinear hydrostatic granular pressure, as:u ( R)2RL 
b gL2 Ri2sin( ) 1  g T
 u mf (3)Here, ρb is the bulk density of the powder and the lastterm accounts for the effect of the superficial velocity in(3)
reducing the effective weight of the sample. Eq (3) predicts
a linear dependency of the shear stress with the bed height,
τ~L, and a linear dependency between of the torque withthe gas velocity, T~ug, but a quadratic dependence of thetorque with the radius of the rotating cylinder, T ~ Ri2 , andthe height of the powder bed, T~L2. The authors assessedthe validity of Eq. (3) through experimental measurements(19) Unlikeof the stress distribution in a stationary material.
Eq (3), the well-known Janssen equation describes an
exponential distribution of the stress across the depth, but
it would predict a linear dependency, T~L, for a powder
in a quasi-static regime when the normal stress reaches anasymptotic value below a certain depth. The experimental
results obtained across different particle densities, diameters, shear rates and aeration levels confirmed the prediction of Eq. (3) based on hydrostatic loads and the effect of
aeration in reducing σ. These experiments were operated at
low shear rates, , and the results did not show any relation
between T and . In a further series of experiments, Tardos
et al. (1998) investigated the effect of higher shear rates (or(11) the rotational speed to 250 rpm bulk
higher  C) increasing(11)
samples of non-aerated
coarse glass beads. The effect of
the hydrostatic load was studied placing an 8 cm high layer(20)on top of the shearing column that blocked theof powder
bed from expanding. The results using different geometries
showed a weak dependency of the dimensionless torqueand shear rate ascribed to the variation of the annular gap
that was actually sheared. However, in the configuration
with an additional layer of powder, the entire annular gap
was sheared, and a linear correlation appeared between thedimensionless torque and shear rate with a slope of 0.25.
This is one of the first studies capturing the departure from

Summary of aerated or vibrated Couette-type cells for the characterisation of intermediate granular flow.

Reference

MaterialFIdp [μm]ω [rpm] [s –1]

Re / Ri / r* [mm]32.5/6–11

L [mm]

r1 : Anjaneyulu et al. (1995)

Glass

>1

400–900150

0.07/1.65

r2 : Tardos et al. (1998)

Multiple

0–1

70–53020/250

r3 : Marchal et al. (2009)

Glass

Vibrated

530—

10/12076.2/63.5
表セル：9pt,
以下同
20/10/11.5
10 –6 –102

195–285(41)
30

r4 : Colafigli et al. (2009)

Silica>1

26

2.4/16

0.12/0.76

69/50

300

r5 : Langroudi et al. (2010a)

Glass

Flow

500–1000

5/60

0.25/9152.4/101.6

101.6–406.4

r6 : Landi et al. (2012)

Glass

>1

48

3

0.13

69/50

300

r7 : Gutam et al. (2013)

Multiple0830–1300—

0.34–1.7

75/35–60

190

r8 : Lupo et al. (2019)

Multiple

0>1

80–2660.5—

25/10.528

r9 : Yahia et al. (2020)

Glass

0–1

50–5008/180

2.75/2270/10–18/12–20

70

14

20–40

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

a quasi-static flow and two distinct behaviours: quasi-static
at a low shear rate and intermediate at higher shear rate.
The same linear relationship between the stresses and theheight was confirmed across a broader set of experiments
by Tardos et al. (2003) varying the size of the internal
cylinder, and including measurements of normal stresses in
the radial and axial directions with the use of piezoelectric
sensors. In this work, a new constitutive equation was
proposed to unify quasi-static, intermediate and inertial regimes on the basis of a 2D analysis of the Couette flow using the additive approach of the stresses of Savage (1998).
Langroudi et al. (2010a; 2010b) were the first to propose
the creation of a flow system to increase the inertial number
in a coaxial-cylinder chamber. Fig. 9b depicts the general
concept. These units offer some flexibility. They can be
operated either in a batch or under a continuous axial flowof material in the annular space. The height of powder inthe shearing band can be controlled with the powder flow
rate, and an additional layer can be maintained above theshearing band, denoted overburden, to control the consolidation. In the study of Langroudi et al. (2010a; 2010b),
the behaviour of coarse glass beads was evaluated first
without the presence of the overburden. Four bed heights,
L, and four rotational speeds were tested. As described byothers in aerated (Tardos et al., 1998) and fluidised devices(Anjaneyulu and Khakhar, 1995), shearing caused thestratification of the flow with two distinct layers of mobile
and stagnant powder. Analysis of the torque was in agreement with Tardos et al. (1998) and confirmed the linear
correlation between τ and the bed height, L. The analysis
confirmed the presence of two regimes, a quasi-static flow
at low shear rates where τ is independent of , and anintermediate at higher values where τ increases with increasing . The authors assumed a power-law for the stress(11)
and shear rate relation,    n , and found that the
n-indexranges from 0.5 to 1 and increasing with higher shear rate.
(11)
This work
provided also important additional information(21)
by measuring the normal
stress, σ, acting on the shearing
surface of the material. Stress sensors were placed in boththe surface of the outer and inner cylinders, and a further
set of experiments was conducted with a fixed bed heightat 406.6 mm, an overburden of 101.6 mm and increasing
ω from 5 to 60 rpm. As expected, the normal stress σmeasured at the wall increased linearly with the depth in
the powder bed, and it was independent on the rotational
speed, ω. Measuring both the shear stress (indirectly) andthe normal stress (directly), they estimated the angle ofinternal friction, μ, and found that it was comparable tothe one evaluated with classic shear testers at low . The
authors proposed a constitutive model based on the datathat blends the Coulomb yield condition at zero shear withn
 /  tan    b (11) . Ina power law at a higher shear rate,
a later study, Langroudi et al. (2011) used the same device
equipped with capacitance probes to study the effect of(22)

polydispersity and shape in secondary flow patterns and thepowder dilation.
Langroudi et al. (2010a) also studied the effects of the
bed height, L, without overburden and confirmed a linear
dependency of the average τ on L with a slope proportionalto . However, as pointed out by Ghadiri et al. (2020),
there have been conflicting experimental observations.
Mehandia et al. (2012) and Gutam et al. (2013) report(11) of an exponential behaviour studying in detail theevidence
axial distribution of the stress in slow regime on a similararrangement (Table 1) including the direct measurement ofradial and axial normal stresses. In their device, aeration
was used only to homogenise the bed of powder, and thesamples were pre-sheared during 20–30 min to remove
any history effect. In contradiction with the observationof Tardos et al. (1998; 2003), all components of the stresstensor were seen to increase exponentially with the depth
in the bed. The behaviour was found to be consistent with
the Janssen equation across a range of conditions, which
was ascribed to the inherent anisotropy of the bed fabric.
In a later work, Krishnaraj and Nott (2016) associated theabnormal quadratic dependence of the stress with depth tothe formation of a secondary vortex in a Couette geometry.
The authors argue that the gravitational acceleration and its
interplay with the confinement are responsible of causing
a deviation from the expected liquid-like behaviour inisotropic plasticity models. These models disregard thetransmission of stress to a boundary as the majority ofcomputational DEM works do by imposing Lees Edwards
boundary conditions. The role of geometrical constraints,
particularly the size of the annular gap, therefore, requires
further investigation.
Lupo et al. (2019) conducted a similar study using an
Anton Paar cell featuring a pseudo-cylindrical impeller
with a grooved surface. They carried out torque measurements on aerated and non-aerated samples by immersing
the impeller at various bed depths. Experiments were performed below and above the minimum fluidisation using
different powders (see Table 1). As expected, T decreased
with the depth of the impeller for all the cases studied anddecreased with increasing gas velocity. However, the more
complex geometry of the cylinder/impeller requires further
analysis to be able to compute the stresses.
Couette flow configurations have also used to investigate
higher levels of aeration. For example, Anjaneyulu andKhakhar (1995) introduced an adapted Coaxial-cylinder
rheometer to study of the rheology of a fluidised beds
following an aerated arrangement, Fig. 9c. A viscometer(Brookfield, Synchro-Lectricas) was used to rotate an innercylinder. Two geometries with varying internal radius were
tested using glass beads with various sizes and reachingcomplete fluidisation FI > 1 (Table 1). For each airflow,
the inner rotating cylinder was immersed in the glass beads
sample at different elevations L. The experiments showed15

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

the formation of a dynamic layer around the rotating cylinder and a static layer at the vicinity of the wall. In line withthis observation, the authors proposed a pseudo-plastic
constitutive equation based to describe the granular material as a Bingham fluid. Fitting the experimental results
led to estimates of the bulk shear viscosity, μ, and the yieldstress, τy, where τy defined as the shear stress at a very low
rotational speed (ω→0). As expected, both μ and τy, decreased with increasing air velocity, but while τy decreased
monotonically and beyond the fluidisation conditions, μreached nearly constant value for FI > 1. This behaviour
was explained by the motion of the gas from the sheared
inner region to the outer packed region. The yield stress,
dominated by the outer packed bed, decrease as more gas
flows through for a higher FI but the viscosity, μ, remains
constant since it is governed by the shearing of the rotating
inner region, which does not dilate further. Both μ and τywere found to be independent of the particle size for thesame FI. At a low aeration level, the experimental results
were more scattered, and the inner cylinder radius and theimmersion depth had a significant effect on μ and τy.
Colafigli et al. (2009) developed an alternative design forhigh aeration levels, known as the Couette Fluidised-Bed
Rheometer (CFBR). A CFBR is designed to measure theapparent viscosity in a homogenous gas-fluidised bed. Itfeatures the same type of aerated geometry, Fig. 9c. The
external cylinder was made of Pyrex to allow direct observation of the fluidisation dynamics, and the inner cylinder
was made of stainless steel. Colafigli et al. (2009) used
nitrogen at ambient conditions as the fluidisation medium
and silica powder (dp = 26 μm). The height of the bed wasmaintained at a constant value to have the inner rotating
cylinder fully immersed, and enough space was left above
the bed to accommodate the expansion of the bed. The
apparent viscosity was evaluated from the steady-statevalue of the torque assuming a laminar flow in the annulargap. The values of viscosity were computed with the assumption of a Newtonian fluid and, therefore, they provide
only an estimate of an “apparent” viscosity. Nonetheless,the results indicated a clear and significant decrease in themean apparent viscosity with increasing ω. For a fixedrotational speed, the mean apparent viscosity decreased
with increasing airflow. Despite it remains unclear how toconvert the registered torque, T, to bulk physical properties
such as viscosity or yield stress, CFBRs offer an easy
way to evaluate and compare different powders and evenstudy the effects linked to changes in particle properties
or operation conditions, e.g. temperature or pressure. For
example, Landi et al. (2012) used a CFBR to investigate theflow properties of moisturised glass beads with relative humidity rH ranging from 15 % to 70 %. In this work, the rH
was controlled by using pre-humidified air stream used asa carrier in the bed. Surprisingly, the minimum fluidisation
velocity (0.09–0.12 m.s–1) followed no apparent trend with16

the rH, and at a fixed rotational speed (Table 1) the torque,T, was found to decrease monotonically with superficial
gas velocity, independently of the value of the rH.
A better understanding of the development of the flow
and the force chains in a Couette device can be obtainedwith visualisation techniques such as magnetic resonanceimaging (MRI). For example, Moucheront et al. (2010)
reported an MRI investigation of granular rheology in a
Couette device similar to that in Fig. 9a, where the material(Mustard seeds-MRI sensitive) was confined between twoplastic cylinders and sheared by the rotation of the innerone. Multi-layer MRI velocimetry was used to evaluate thevelocity profiles at different elevations. The authors wereable to determine the effect of the roughness of the innercylinder and the bottom base on the flow structure. The results demonstrate that the roughness of the bottom surface
has an effect localised only to a few granular layers, but theroughness of the inner cylinder wall affects significantly
the system determining the sliding velocity and the friction
coefficient.

4.2.2 Aerated virtual Couette configurations
The error associated with the roughness of the boundaries and the reliable estimation of shear stress τ aresome of the challenges encountered by coaxial-cylinder
rheometers. New modified cells address some of theseissues proposing new ways to harmonise the experimental
data and the wall boundary conditions. A coaxial-cylinder
rheometer can be easily modified by replacing the innercylinder by an impeller while maintaining a Couette flow.
The resulting alternative design is called virtual Couette
flow. It is depicted in Fig. 10. It has been used in the studyof granular material by several authors including Marchal
et al. (2009) and Yahia et al. (2020). Both studies used thesame strategy: the inner cylinder is replaced by an impeller

Fig. 10 Virtual Couette Flow: (a) Schematic, L: cell height; ω: rotational speed, Re, Ri and r*: external, inner and optimal radii; (b) Imageof the impeller denoted virtual cell. Adapted from Yahia et al. (2020) under the terms of the CC-BY 4.0 license. Copyright: (2020) The Authors,published by Wiley Periodicals, Inc.

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

with a longitudinal arrangement of equidistant straightbaffles aligned with the radial direction, see Fig. 10b. The
inner element rotates at a fixed position inside the material.
In doing so, the impeller creates a cylindrical geometry
filled with powder under solid body rotation at the velocityof the baffles. A shearing plane is created exclusively between granules at the outer surface of the moving virtual
cylinder, therefore eliminating any potential sliding effects.
Marchal et al. (2009) used a virtual Couette cell toinvestigate the effects of mechanical vibration on granularrheology. They first introduced the definition of an optimalradial position, r*, (see Fig. 10a) as a way to translate thetorque measurement into a transportable measurement ofshear rate, , and stress, τ. The optimal radial position,r*, is an exclusive geometrical property of each Couetteconfiguration. When reported at r*, both τ and  become
independent(11)of the dimensions of the outer and innercylinder. The formulation of r* was confirmed with fur(11)ther experimentation with Newtonian and non-Newtonian
fluids by Aït-Kadi et al. (2002) where several Couette-typeflow configurations were tested. This is a critical step inorder to fix a standard procedure to report data. Marchal
et al. (2009) employed an inner cylinder made of stainlesssteel. The baffle width was 5 mm and six were glued also
on the external cylinder surface to avoid particles sliding.
The external cylinder was mounted on a plate to apply
mechanical vibration during the shearing process. Experiments were performed with and without vibration using asample of coarse glass beads and a varying the shear rate, (Table 1). The results obtained in a non-vibrated bed foundno stress-strain rate relationship, but under mechanical vi(11)bration and low values of  the shear stress, τ, and the shear
rate, , were found to be linearly proportional describing a
Newtonian behaviour.
(11)including aeration, called an
A more advanced design(11)Bed Virtual Couette Rheometer (AB-VCR) was
Aeratedproposed by (Yahia et al., 2020). The AB-VCR adapts a
virtual Couette geometry similar to the one presented inFig. 10 to the FT4 Powder Rheometer. The aerated vesselof the FT4 is a glass cylinder. The inner cylindrical element(so-called virtual cell) has 3D printed six blades made ofplastic material (ABS-M30i, SYS systems 3D Printing).
Yahia et al. (2020) conducted experiments with and without aeration.
Under no aeration, the shear stress, τ, was found to be
independent of shear rate, , indicating that the powders
were in the quasi-static regime. At a fixed value of ,
the shear stress, τ, was dependent on particle size, which
was ascribed to different (11)bulk internal friction of each(11)
size class (μ500μm = 0.46 + 0.02, μ50–80μm = 0.36 + 0.01,
μ160–210μm = 0.32 + 0.01). The bulk friction coefficient measurements were compared with FT4 torsional shear cell
experiments, and they showed very good agreement.
During the aeration experiments, ambient air was injected

through the sample using a stainless-steel base grid to havea homogeneous flow distribution. The air velocity was increased from no aeration to a fluidisation index FI < 0.4, at
a varying shear rate  (Table 1). All powders display a quasi-static behaviour under this range of aeration. The shear
stress, however, was found to decrease with the increasing(11) with the observation of Tardos
air velocity in agreement
et al. (1998). It is worth noting that unlike them, this work
operated only in a batch mode and did not study the effectof an additional static layer of powder atop of the sample
to prevent the expansion of the bed. For a fixed fluidisationindex, a good agreement was found between the results
obtained with samples with the same angle of internal friction, μ, while the shear stress, τ, associated with a higher μwas systematically lower. Yahia et al. (2020) demonstrated
the potential of r* to standardise the measurements in
Couette shear testers. The authors compared the use of
three virtual cells of a varying radius and a fixed bed height(Table 1). As expected, in every powder, the torque, T, depended on the dimensions of the virtual cell, increasing for
an increasing radius. However, the shear stress τ computedat the optimal position, r*, using the recorded torque, T,
was the same for all the cells used.
These devices are still in development and quantitative
comparison is necessary, but the selection of presented
here shows the potential of Couette cells to investigate
the departure from a quasi-static flow. The versatility ofthe device permits to operate at a wide range of rotational
speeds, with or without an overload of static powder, withand without aeration, vibration or an imposed gravitational
flow, and they allow varying the geometry with a soundscaling parameter. However, the computation of τ from T
in each historical work is based on different assumptions,and the complete of information necessary to reconstruct
it is missing from most of the studied. Not all of them operate under the free expansion of the bed, a wide range ofparticle properties and geometries is present, and the natureof the axial distribution of stress remains to be clarified.
Nevertheless, the use of the optimal radial position, r*,opens the way to establish a standard in the computationof the shear stress and the shear rate. At this point, a comparative analysis of the studies in Couette configurations islimited to the qualitative features summarised in Table 2.
Overall, experiments find the expected behaviour at low 
where τ is independent of  with and without aeration. As
 increases at a high FI aerated cells capture the departure(11)
from a quasi-static regime, whereby τ starts to increase forincreasing . This relation (11)is modified with the operating (11)and the level of aeration. The torque and the bulk viscosity
decrease with the superficial gas velocity, and there are(11)
conflicting(11)reports regarding the axial distribution of thestress, where both a linear and an exponential dependencywith the bed height have been suggested.

17

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

4.3 Mechanically stirred (agitated) beds
Mechanically stirred beds are used to study the highest
range of shear rates under complete fluidisation. They measure the torque, T, required to rotate an impeller immersed
in a powder bed, Fig. 11a. T depends on the structure of
the powder and reflects its flowability. Depending on the
impeller shape and its position in the bed, T could be used
to compute a characteristic shear stress, τ. For example,
Bruni et al. (2005; 2007) developed a mechanically stirred
fluid-bed rheometer (msFBR) consisting of a flat impeller(36 mm diameter × 7 mm height × 0.7 mm thickness) thatrotates at a fixed position inside an aerated bed. The test
was conducted varying the impeller depth and the rate ofaeration below and above the minimum fluidisation. The
powder was preconditioned in every test by fully fluidising
it and decreasing the aeration level to the desired value toremove any history effects. Bruni et al. (2005) exploredthe effect of the aeration rate (0 < FI ≤ 1), the impeller
speed (0 to 8.79 rpm) and the depth ID on the torque,T, using alumina and soda glass beads. Under aeration,
FI < 1, the torque, T, was found to reach a constant value
at each speed only after a sufficiently long time, and as
expected, it increased with the depth until reaching aplateau at the bottom end. In a later work, Bruni et al.,(2007) proposed a model based on the Janssen equationand the Mohr–Coulomb yield criteria to predict the stressat the impeller depth, and evaluate the change in T at low
consolidation resulting from the combined action of thesample weight, the aeration and the impeller position. This
work studied alumina powders and glass beads varying theposition of the impeller with or without aeration (FI < 1),
and concluded that independently of the impeller depth,
the aeration does not influence T. Tomasetta et al. (2012)

Fig. 11 Examples of stirred aerated/fluidised beds: (a) Depiction of thegeneric geometry (b) Qualitative evolution of the BFE with increasing
gas superficial velocity, ug, during a FT4 downwards test.

estimated the flow properties from the data reported by
Bruni et al. (2007) developing a new procedure to computethe shear stress, τ, and the consolidation stress, σ, from thetorque. τ was found to increase linearly with σ in a similar
way to the yield locus characteristic a shear tester. The bulk
friction coefficient, μb, was then simply computed by τ/σ. It
was shown that the computed values of μb were in a good
agreement with the measurements obtained in a Schulze
ring shear test.
The FT4 rheometer can also be used as a mechanically
Table 2 Summary of the experimental behaviour described in the cells
stirred aerated bed. The unit is equipped with a twisted
listed in Table 1.
stainless-steel rotated blade that moves downwards andReference vs. main experimental observation
upwards through the powder. As in all the FT4 tests,
the powder is prepared in a conditioning cycle wherer1
Adopts Bingham model; μ and τ y decrease with ug
the twisted blade moves through the sample rotating in
r2
Measures T and deduces a hydrostatic stress profile
a clockwise direction, creating a uniform, reproducible(σ~L). Captures intermediate flow for  C  0.15
lightly packed sample (Freeman, 2007). Two tests can
r3
Proposes a vibrated virtual cell and r*. Finds Newtobe performed with a mechanically stirred configuration:nian behaviour  ~  under vibration and low  .
(42)
downwards and upwards. In both, the blade rotates in anr4
Adopts Newtonian model; μ decreases with ω
anticlockwise direction. In a downwards test, the rotation
r5
Measures normal stresses consistent with a hydrostatic(43)
表セル：9pt, 以下同
0.72
of a twisted blade(41)results in shearing while the axial move /  tan    b 
stress profile (σ~L); finds
ment applies a normal stress to the bed. The torque and ther6
Measures T decreases with ug independently of rH.
vertical force recorded in a downwards test can be used tor7
Measures normal stresses(44)in agreement with Jensen Eq
derive a so-called Basic Flowability Energy (BFE) which
and in contradiction with a hydrostatic stress profile.
represents the energy required for the blade to complete ar8
Measures how T decreases with L and ug
full translation. The BFE is, therefore, a parameter specificr9Demonstrates the use of r* in an aerated virtual cell;to the FT4. It lacks universal meaning, but it allows afinds that τ decreases with ug in quasi-static regime.
direct comparison of the flowability of different powders

18

Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

at various aeration conditions. Fig. 11b illustrates the
typical evolution of BFE with superficial gas velocity ug. A
non-dimensional aeration ratio (AR) defined as the ratio of
BFE at no aeration to BFE at a given air velocity has been
proposed as a way to classify flowability. If AR ~ 1 thepowder is not sensitive to aeration, which is typical of very
cohesive powders or a higher binder content. If AR >> 20,
the powder displays a low cohesive strength, it is very sensitive to aeration and likely to be fluidised. There are many
examples where the FT4 aeration test has been able to rank
the flowability of powders (Freeman, 2007). For example,
Gnagne et al. (2017) reported the properties of flours, Ono
and Yonemochi (2020) studied the effect of additives in the
flowability of ibuprofen and Ludwig et al. (2020) evaluatedits behaviour under fluidisation.
Although the method is clearly able to rank powders, itdoes not provide a transportable set of properties. The complex geometry of the blade makes it difficult to evaluate thecharacteristic strain rate and the shear stress, but the combination of experimental and computational studies can help
to address some of these limitations. The work of Hare etal. (2015; 2017) suggests that it is indeed possible to determine a characteristic τ for a powder in the FT4 aeration test.
Hare et al. (2015; 2017) combined experiments and DEM
simulations to determine the shear stress profile in the bed.
In order to estimate the strain rate and shear stress they
analysed the dynamic behaviour of a bed of large cohesive
glass beads (dp = 1.7–2.1 mm) during the FT4 aeration test
and found that τ was be constant across the blade lengthand increased as the impeller penetrated the bed. Hare etal. (2017) later provided a similar framework to analyse thestress and strain rates, and Nan et al. (2017a; 2017b) combined computational and experimental work to study how
aeration and shape affected the stress profiles in samples ofsoap roads, polyethylene and glass beads.
Oher commercially available stirred beds include theAnton Paar Powder Cell (APPC). This device works withthe same principle as the msFBR (Bruni et al., 2005; 2007)
recording the torque acting on an impeller immersed in an
aerated powder bed. The bed can be operated either below
or above the minimum fluidisation. The cell containing thepowder is made of a glass cylinder with a porous bottom
plate, and the unit is equipped with impellers of different
shapes and wall conditions. Salehi et al. (2017b) used an
APPC to study the effects of the impeller depth and theaeration rate on the torque acting on a flat blade impeller insamples of free-flowing powders, namely glass beads, alumina and sieved silica sand, up to the minimum fluidisation(0 < FI < 1). The dependency of T on the air velocity, thebed height and the impeller depth confirm the observationsof Bruni et al. (2005; 2007). They proposed to use a fitting
parameter as the “effectiveness” of the impeller to estimate
T at different depths. The model is based on the assumptionthat the shearing occurs only within the cylindrical region

captured by the impeller rotation. In a later work, Salehi
et al. (2018) measured T under different geometries in
non-aerated glass beads of different sizes. In a similar fashion to the works in an FT4, a combination of computationaland experimental data was used to evaluate internal flow
parameters such as the bulk friction coefficient between
particles and between particles and the blade.

5. Conclusions
Classic shear cell devices and a broad array of ad-hoc
experimental tests have served for decades as the standard to evaluate the flow threshold of cohesive industrial
powders. However, looking only at the initiation of theflow is a rather simplistic view of the rheology of granularmaterials. It fails to capture their dynamic behaviour andthe transition to intermediate and inertial regimes. These
are fundamental aspects of the flow behaviour observed innatural systems and industrial units. In order to efficiently
process powder, optimise unit operations and develop
new technologies involving dense particle flows such asprocess, energy and additive manufacturing, one requires
a precise understanding of all granular flow regimes.
Dynamic tests and many flow configurations have been
proposed as alternative ways to characterise the dynamic
behaviour of a powder. However, even the simplest devices
such as rotating drums, chutes or avalanches display a very
complex flow pattern, and the resulting bulk properties are
difficult to interpret.
It is important to move towards establishing a rigorous
and transportable analysis of the data across different devices. This review provides an overview of the strategies
developed in recent years to expand the usage of conventional shear cells from the quasi-static regime into the characterisation of intermediate and inertial flows by applying
external actuation. However, the practical difficulties inoperating at higher shear rates and the complex behaviourof granular matter make the development of flexible instruments very difficult. Commercially available units suchas the FT4 rheometer or the Anton Parr Powder Cell havetackled this challenge using a rotational cell under aerationto achieve very small consolidation stresses. Many othercustomised devices have followed similar principles using
modified testers, flow devices, fluidised bed rheometersand mechanically agitated beds. The main drawback ofthese units is linked to the assumptions employed to establish a relation between the registered torque and the characteristic stresses and shear rates. In this work, we have paid
particular attention to the development of aerated Couette
flow configurations to address some of these issues. Not
only it is a flexible geometry with a tight and independent
control normal and shear stress over a broad range of shear
rates, but these units offer a direct way to harmonise the19Victor Francia et al. / KONA Powder and Particle Journal No. 38 (2021) 3–25

interpretation of data. They provide geometry-independentshear rates and stresses, and the introduction of the new
virtual-cell concept removes most of the concerns associated to earlier units. However, their application is still limited, and further work is necessary to assess their viability
as an industrial characterisation technique.

Acknowledgements
RO acknowledges financial support from the EPSRC(EP/N034066/1).

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Authors’ Short Biographies
Victor Francia
Victor Francia is an Assistant Professor of Mechanical Engineering at Heriot-Watt
University, Edinburgh, UK, with industrial and consulting experience in the water, energy
and consumer good sectors. He moved to academia in 2012, working at Imperial College
London and later at University College London before starting in his research group in
2019 on multi-phase flow and responsive technology. He looks into complex particle flows,
how we can control dynamic structures using external actuation to design smart technology
and new devices able to self-regulate and improve efficiency in the process industry and theenvironmental and energy sectors.

Lyes Ait Ali Yahia
Dr. Lyes Ait Ali Yahia is a Research Associate in the Institute of Mechanical, Process
and Energy Engineering at Heriot-Watt University, Edinburgh. He was awarded a Ph.D. in
Science Engineering and Environment at the University of Paris EST Creteil, France. After
his doctoral studies on aerosol physics, he worked as a Teacher/Researcher Fellow in the
University of Paris EST Creteil. Since then, he has been working at Heriot-Watt University
on the rheology of granular materials where the focus of his work is to design experimental
procedures that will help understand the flow behaviour of granular materials.
Raffaella Ocone
Raffaella Ocone OBE FREng FRSE holds the Chair of Chemical Engineering in the
School of Engineering and Physical Sciences at Heriot-Watt University (UK) since 1999.
She has worked at the Università di Napoli (Italy); Claude Bérnard Université, Lyon
(France); Louisiana State University (USA); Princeton University (USA). In 2017 she became the first “Caroline Herschel Visiting Professor” in Engineering at RUHR Universität(Germany); in 2018 she was awarded a Visiting Research Fellowship from the Institute forAdvanced Studies at Università di Bologna (Italy). Raffaella’s main interests include themodelling of complex reactive systems and the hydrodynamics of granular media.

Ali Ozel
Dr Ali Ozel is an Assistant Professor in the Institute of Mechanical, Process and Energy
Engineering at Heriot-Watt University, Edinburgh. He was awarded a Ph.D. in Fluid
Mechanics at the National Polytechnic Institute of Toulouse, France. After his doctoral
studies, he worked as a post-doctoral fellow at the Fluid Mechanics Institute of Toulouse.
Before joining Heriot-Watt University, he was as an associate research scholar in the
Department of Chemical and Biological Engineering at Princeton University. He has beenworking on the development and deployment of state-of-the-art mathematical and computational modelling and simulation tools to study particle-laden flows and complex fluids.

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KONA Powder and Particle Journal No. 38 (2021) 26–41/https://doi.org/10.14356/kona.2021017

Review Paper

Static and Dynamic Stickiness Tests to Measure Particle
Stickiness †Erik J.G. Sewalt, Fuweng Zhang, Volkert van Steijn, J. Ruud van Ommen
and Gabrie M.H. Meesters*
Department of Chemical Engineering, Delft University of Technology, The Netherlands

Abstract
Sticking of particles has a tremendous impact on powder-processing industries, especially for hygroscopic
amorphous powders. A wide variety of experimental methods has been developed to measure at what combinationsof temperature and moisture content material becomes sticky. This review describes, for each method, how socalled stickiness curves are determined. As particle velocity also plays a key role, we classify the methods into
static and dynamic stickiness tests. Static stickiness tests have limited particle motion during the conditioning
step prior to the measurement. Thus, the obtained information is particularly useful in predicting the long-term
behavior of powder during storage or in packaging. Dynamic stickiness tests involve significant particle motion
during conditioning and measurement. Stickiness curves strongly depend on particle velocity, and the obtained
information is highly relevant to the design and operation of powder production and processing equipment.
Virtually all methods determine the onset of stickiness using powder as a starting point. Given the many industrial
processes like spray drying that start from a liquid that may become sticky upon drying, future effort should focus
on developing test methods that determine the onset of stickiness using a liquid droplet as a starting point.
Keywords: stickiness, powders, caking, glass transition temperature, sintering

1. Introduction
Sticking of particles has a tremendous impact on
numerous industries that process powders. Sticking cancause several issues, such as fouling and blockage ofequipment, or caking of stored powder. It can also be usedadvantageously to produce agglomerates with beneficial
properties. Why, how, and when particles stick together
are critically important questions. In this review, we focus
on the ‘when’ question by reviewing the experimental
methods commonly used to determine the conditions underwhich sticking occurs. We hereby focus on the stickinessof hygroscopic amorphous powders, which play a majorrole in the food industry (Boonyai et al., 2004). Crystalline
materials, which may also stick, but through a different
mechanism (Kamyabi et al., 2017), are beyond this review’s scope.
Whether two particles stick depends on their material
and a wide variety of parameters, including their temperature, and moisture content. A common way to characterize†

Received 5 June 2020; Accepted 11 August 2020
J-STAGE Advance published online 19 September 2020
* Corresponding author: Gabrie M.H. Meesters;
Add: van der Maasweg 9, 2629HZ Delft, The Netherlands
E-mail: G.M.H.Meesters@tudelft.nl
TEL: +31-15-278-5501

26

the stickiness of a material is to map the stickiness based on
the environmental temperature and the moisture content.
The moisture content can be described in terms of the particle’s water mass fraction (xw), or the equilibrium environmental relative humidity (RH). The part of the parameter
space for which the material is sticky is called the sticky
region, which is bounded by the so-called sticky-point
curve, T1(xw), and the so-called tack boundary, T2(xw), as
illustrated in Fig. 1. Besides the environmental parameters,
this map also illustrates the particle’s material properties
in the form of a boundary between the glassy state and therubbery state, known as the glass transition temperature,Tɡ(xw). The rubbery state has some overlap with the sticky
region, and with further hydration becomes the liquid state(Roos, 2002). While particles are non-sticky in the glassy
state, material properties, especially viscosity, drasticallychange upon transitioning to the rubbery state. Hence, thecurves represented by the differences T1(xw) – Tɡ(xw) andT2(xw) – Tɡ(xw) are two meaningful measurements of the
sticky-region that include the influence of temperature,moisture content, as well as the material. The distance between the sticky-point curve T1(xw) and the glass transition
curve Tɡ(xw) often slightly depends on xw (Palzer, 2005).
Therefore, the onset of stickiness is commonly reported
as a constant critical deviation from Tɡ(xw), denoted as(T – Tɡ)c.

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Erik J.G. Sewalt et al. / KONA Powder and Particle Journal No. 38 (2021) 26–41

Fig. 1 Map of temperature and moisture content showing the regionin which a material is considered sticky. This region is enveloped by
the sticky-point curve (T1(xw)), the tack boundary (T2(xw)), and thetemperature above which the material decomposes. The sticky-point
curve and tack boundary are often reported with respect to the glasstransition temperature of the material (dashed line), which separates its
glassy state from its liquid state. The difference T1(xw) – Tɡ(xw) is in literature more commonly referred to as (T – Tɡ)c. Figure is modified from
Lockemann (1999) and Kudra (2003).

Experimental stickiness tests generally aim to determine
the sticky-point curve or the tack boundary by measuring
stickiness for different temperatures and moisture contents.
While most methods approach the sticky region from theglassy state to find T1(xw) – Tɡ(xw), a limited number ofmethods approach the sticky region from the liquid state
to find T2(xw) – Tɡ(xw). Although the tack boundary is lesswell understood, it is known that the change in behavior isless sharp than near the sticky-point curve (Kudra, 2003).
While the measured parameter may differ between theexperimental methods, what all methods have in common
is that they follow two steps: (1) a conditioning step, where
the material is subjected to a specified temperature T andhumidity RH for a certain time window and (2) a measurement step where the stickiness of the powder is measured(Boonyai et al., 2004). Whereas these steps are separated
for some methods, they are intertwined for others. Hence,
not only the duration of conditioning influences the
sticky region’s boundaries but also the used measurement
method. While the influence of conditioning time is wellunderstood (Kamyabi et al., 2017), the influence of particle
motion in the conditioning and/or measurement step on theboundaries of the sticky region is still unclear. For skim
milk powder, one of the most abundantly tested materials,
a wide range for T1(xw) – Tɡ(xw) has been reported. For
particles that are static during the conditioning step, values
as low as 8 °C were reported for T1 – Tɡ (Verdurmen et al.,2006). By contrast, values as high as T1 – Tɡ = 63 °C werereported for particles moving at tens of meters per second(Walmsley et al., 2014).
Following Verdurmen et al. (2006), we therefore distinguish between two classes of methods in this review. The
first class is where the particles can be considered static

during conditioning (not set in continuous motion throughexternal means). The second class is where the particles are
moving during conditioning. We refer to the first class of
methods as static stickiness tests and to the second class as
dynamic stickiness tests.
This review aims to provide an overview of the available
methods to measure stickiness. As static stickiness tests, we
describe various visual observation tests, the shear test, thepenetration test, and the blow test. As dynamic stickinesstests, we describe the sticky-point test, the fluidized bed
test, the particle gun, the cyclone test, the optical test, andthe probe test. For each method, we describe how it can beused to determine either the sticky-point curve T1(xw) or thetack boundary T2(xw) of the sticky region. Additionally, we
describe what we view to be the method’s best application
in industry. The overview of methods shows that particle
velocity plays a significant role in the measured boundariesof the sticky region, illustrating the importance of choosing
the most appropriate method for the application in mind.

2. Glass transition temperature
The glass transition temperature Tɡ marks the temperature where an amorphous material transitions from a glassy
state to a rubbery state upon increasing temperature. Whileboth states are fundamentally a liquid, the behavior of theglassy state is solid-like, being hard and brittle, and the rubbery state behaves like a highly-viscous liquid. The natureof the glass transition is the molecular freedom of movement, which is restricted in the glassy state (Roos, 2002).
The most common method to experimentally determine Tɡ is using differential scanning calorimetry (DSC),
although several other methods are available (Li et al.,2019). In DSC, the Tɡ is found by subjecting the material
in the glassy state to a temperature ramp and measuring
the specific heat capacity. The specific heat capacity showsa characteristic change during the glass transition (Hogan
et al., 2010; Roos, 2010). By repeating the experimentat different xw, the curve for Tɡ(xw) shown in Fig. 1 canbe experimentally constructed. Similarly, dynamic vapor
sorption (DVS) can be used to measure the vapor sorption
characteristics by applying a ramp in relative humidity at a
fixed T while measuring the sample’s mass. In the glassy
state, water sorption only occurs at the surface, while therubbery state also allows for bulk sorption, such that acharacteristic change in the water sorption rate is observedat Tɡ (Burnett et al., 2004).
The glass transition temperature can also be estimatedtheoretically, for example using the Gordon-Taylor or
Couchman-Karasz equation. The Gordon-Taylor equation
can be used to determine the influence of water on the glasstransition temperature Tɡ(xw) of a dry powder, based on theglass transition temperature of the anhydrous powder (Tɡ,s)27

Erik J.G. Sewalt et al. / KONA Powder and Particle Journal No. 38 (2021) 26–41

and pure water (Tɡ,w), and the weight fraction of moisture,
xw, asTg ( x w ) (1  x w )Tg,s  kx wTg,w(1  x w )  kx w

(1)with Tɡ,w = –135 °C (Roos, 2002). The constant k is often
calculated from the densities ρ, Tɡ,s, and Tɡ,w as k = (ρsTɡ,s)/(ρwTw,s) (Katkov and Levine, 2004; Simha and Boyer,1962).
The Couchman-Karasz
equation, while similar tog: DejaVu
Serif + サイズ小さく
Eq. (1), is based on thermodynamic additivity of specificheat capacity. Although different versions are reported,the(1)so-called ‘modified’ version is found when usingk = ∆Cp,w/∆Cp,s in Eq. (1). The changes in heat capacity∆Cp at Tɡ can be found using DSC (Sochava, 1997). For∆Cp,w, 1.94 J K–1 g–1 is often used (Katkov and Levine,
2004; Roos, 2002). Katkov and Levine 2004 showed thatthe modified version of the Couchman-Karasz equation
overestimated the Tɡ of mixtures and underestimated theplasticizing effect of water while they obtained a better fit
using the so-called ‘original’ Couchman-Karasz equationln (Tg ) (1  x w )ln (Tg,s )  kx w ln (Tg,w )(1  x w )  kxw(2)

While the Gordon-Taylor and Couchman-Karasz equations
are suitable for most simple systems and can be used to(2)construct
the curve for Tɡ(xw) in Fig. 1, they should be usedwith caution when considering complex mixtures (Katkov
and Levine, 2004).
The glass transition temperature servers as a naturalreference in the stickiness map and allows one to compare
the stickiness of different type of materials. Similarly, theTɡ serves as a reference in an attempt to come to a universal
predictive equation of the dynamic viscosity in the rubbery
state. The Williams-Landel-Ferry (WLF) equation relates
the viscosity of a material to the distance from the Tɡ-curve(T – Tɡ) as
log10

C1(T  Tg )g C 2  (T  Tg )(3)with C1 and C2 two constants and ηɡ the viscosity at the glasstransition temperature. While the WLF equation is often(3)
considered
to be valid for temperatures up to Tɡ + 100 °C(Lomellini, 1992; Williams et al., 1955), it is only valid if
correct values for the constants and ηɡ are chosen. Valuesof ηɡ are typically in a range between 1011 Pa s to 1014 Pa s
(Downton et al., 1982; Katkov and Levine, 2004; Murti etal., 2010; Palzer, 2005; Paterson et al., 2015; Wallack andKing, 1988). Recently, the glass viscosity of freeze dried
amorphous lactose was measured to be 1.1 × 1014 Pa s,
although the authors suggest that further confirmation isrequired (Paterson et al., 2015). The wide variety of reported constants suggests that there is no universal set valid
for different types of materials and different temperatures.
Nevertheless, (C1, C2) = (–17.44, 51.6 K) as originally

28

reported by Williams et al. (1955), are often considered
to be universal (Aguilera et al., 1993; Murti et al., 2010;
Palzer, 2005; Schulnies and Kleinschmidt, 2018; Wallack
and King, 1988). Peleg (1992) found that these constants
give large deviations when T – Tɡ > 20 °C, and suggested(C1, C2) = (–10.5, 85.6 K), which better matched the experimental trend for the ηɡ of amorphous lactose measured
by Paterson et al. (2015). However, (C1, C2) = (–8.86,
101.6 K) also provided a good fit to other experimental
data (Dagdug and Garcı́a-Colı́n, 1998; Ferry, 1980). Others
use material-specific constants, such as (C1, C2) = (–14.5,
36.4 K), which were fitted for skim milk powder (Walmsley
et al., 2014). Since the WLF equation is exponential, careshould be taken in the choice of the constants when using
the WLF equation to predict the dynamic viscosity. To
illustrate the importance of this choice for a prototypicalcase (T – Tɡ = 20 °C and ηɡ = 1012 Pa s), the constants by
Williams et al. (1955) give η = 1.3 × 107 Pa s, while theconstants by Peleg (1992) gives η = 1.0 × 1010 Pa s, which
is a difference of three orders of magnitude. As there are
currently no clear rules of thumb on the selection of constants, we suggest that best practice would be to fit C1 and
C2 to experimentally measured viscosity data.
The direct relation between viscosity and T – Tɡ throughthe WLF equation leads to the natural question whether
viscosity can be used as a predictor for stickiness. The
success of viscosity as a predictor is expected to dependon the dominant mechanism of adhesion. For hygroscopic
amorphous powders close to Tɡ, sticking is expected tooccur primarily through immobile liquid bridging or viscoelastic deformation (Palzer, 2005). In case immobile liquid
bridging primarily causes sticking, we generally expect
viscosity to be more meaningful than when viscoelastic
deformation primarily causes sticking. More specifically,using sintering theory by Frenkel (1945) and classic viscoelastic contact models, Palzer (2005) could predict thecritical T – Tɡ needed for sticking. However, this model did
not successfully predict sticking of high velocity particle
gun experiments (Murti et al., 2010). A contact model
for adhesive elastic particles showed better results when
predicting the critical T – Tɡ for high velocity collisions(Walmsley et al., 2014). The mentioned works strongly
suggest that viscoelasticity should be accounted for when
predicting (T – Tɡ)c for collisions of particles in motion,and that the observed (T – Tɡ)c is a result of the colliding
material’s rheological behavior and the collision’s kinetics.

3. Static stickiness tests
Testing stickiness of powders using static stickinesstests follows a general protocol. First, a powder bed iscompressed under a stress σ to cause a certain amount ofconsolidation (Fig. 2a). Second, the powder is conditioned

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by exposing it to an environment of controlled temperatureand relative humidity (Fig. 2b). The duration of this conditioning step can be adjusted. When sufficiently long, thepowder’s moisture content is in thermodynamic equilibrium with the moisture in the environment such that xw and
RH are related through a vapor sorption isotherm. Third,a measurement is performed on the conditioned powder(Fig. 2c). Prior to the measurement, the powder can beconsidered static with little movement of the particles.
Therefore, we refer to this class of tests as static stickinesstests, which are deliberately different from the dynamic
stickiness tests in which the particles are actively set incontinuous motion during the conditioning and measurement step. Next, we describe the different static stickinesstests.

3.1 Visual observation
The most straightforward form of analysis is throughvisual observation. Typically, a sample with a specified
dry matter content is placed in a closed container. After
conditioning it at a given temperature, the container isturned upside down to see whether any particles are stuck
to the bottom. This procedure is repeated at different
temperatures until particles noticeably stick to the bottom,
which is identified as the sticky-point temperature (Palzer,
2005). By repeating this procedure for different moisture
contents, the sticky-point curve T1(xw) in Fig. 1 can beconstructed. An alternative visual observation test is one
in which the powder’s temperature is increased stepwise
while observing changes in the appearance of the powder
bed (Tsourouflis et al., 1976; Verdurmen et al., 2006).

3.2 Shear test
Shear tests are used to characterize powder stickinessby measuring the powder’s response to shear stress. Two
common approaches are uniaxial compression and shearing in shear cells. The uniaxial compression approachconsolidates the bed with normal stress σ and then compresses along one axis until failure. The failure stress σf fordifferent values of σ gives a yield locus that can be used tofind the unconfined yield strength σc by drawing a Mohr
circle starting at σ = 0 Pa (Schulze, 2008). The unconfinedyield strength σc is used as the parameter for bed strengthand can be determined for different environmental T and
RH (Fitzpatrick et al., 2007b; Hartmann and Palzer, 2011).
In order to find a sticky-point curve T1(xw), a critical bed
strength, which is characteristic for a sticky powder, must
be determined first. It can be empirically determined before
testing using the same or comparable materials (Palzer andZürcher, 2004).
Similarly to uniaxial compression, shear cells can beused to determine σc and acquire T1(xw) by defining a
critical σc for the bed strength of a sticky powder (Hartmann and Palzer, 2011; Schulnies and Kleinschmidt,

Fig. 2 An overview of the static stickiness tests. a) In the consolidation step, the powder is compressed under a stress σ. b) In the conditioning step, thepowder is subjected to temperature T and relative humidity RH for a specified duration. c) The measurement of stickiness proceeds differently per test.

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2018). However, shear cells improve on result consistency by preshearing before measuring the failure stress.
Preshearing to steady-state at normal stress σ1 eliminates
any stress history, for example, due to filling (Schulnies
and Kleinschmidt, 2018). After preshearing, the shear
stress is reversed to reduce the shear stress to zero. Subsequently, the sample is sheared to failure while measuring
shear stress στ under normal stress σ2 so that σ1 < σ2
(overconsolidation), which ensures a peak is observed forthe failure stress (Schulze, 2008). By shearing to failure atdifferent σ2 while preshearing at identical σ1 a yield locus
can be found. From this point on, the acquisition of σc andT1(xw) is similar to uniaxial compression.
Besides acquiring the sticky-point curve, shear tests haveother commonly used applications related to stickiness andpowder cohesion. Shear tests are commonly used to quantify the powder flowability. The flowability is described interms of the flow function, which is the inverse slope in aplot of unconfined yield strength σc versus normal stressσ (Fitzpatrick et al., 2007b; Jenike, 1964; Papadakis andBahu, 1992; Schulze, 2008). Shear cells can also be used tomeasure wall friction. This is done by replacing the bottom
ring of a shear cell with the wall material. When choosing
the wall material similar to industrial surfaces or packaging
materials, the adhesion of powder to these substrates canbe measured (Papadakis and Bahu, 1992; Schulze, 2008).
Commonly used examples of shear cells are the manual
Jenike shear cell (Jenike, 1964), the automated Schulze
ring shear test (Schulnies and Kleinschmidt, 2018), or the
more recent Freeman FT4 Powder Rheometer (Freeman,2007) and Anton Paar MCR rheometers (Anton Paar
GmbH, 2020; Groen et al., 2020). Conveniently, both theFreeman and Anton Paar powder rheometers can quickly
change environmental T and RH independently throughpowder bed aeration with conditioned airflow (Freeman,
2007; Groen et al., 2020; Mitra et al., 2017). Besides uniaxial compression and shear cells, other types of shear tests
for measuring flowability have been reported (e.g., Warren
Spring cohesion tester, Peschl shear cell). These were notdescribed as their application to find T1(xw) was not foundin literature (Pasley et al., 1995).

3.3 Penetration test
Penetration tests are similar to the uniaxial compression
tests, but use a puncher with a diameter of 1 mm to 2 mm
to penetrate the powder bed to a preset depth (Knight andJohnson, 1988). Measurement of the required penetration
force Fp, which is a measure for bed strength (Özkan et al.,
2002; 2003), is done after conditioning at a fixed T and RH
for a given time. Through repetition, while varying these
conditions, the sticky-point curve T1(xw) is found for the
combinations of T and RH, where the measured Fp equals
a predetermined critical value for which the powder is30

considered sticky (Özkan et al., 2003).

3.4 Blow test
The blow test uses a small thin tube to blow air at a
powder bed surface. The tube is placed millimeters above
the surface at an angle of 45°. The airflow through the tube
is increased until particles dislodge from the surface of theconditioned powder bed, which is the endpoint of the blow
test. The flow rate of air at which particles start dislodging
is a measure for bed strength (Paterson et al., 2001). The
sticky-point curve T1(xw) is found at the T and RH where
the airflow to dislodge particles reaches a predetermined
critical value for which the powder is considered sticky(Foster et al., 2005; Paterson et al., 2005).
A benefit of the blow test is the ability to test multiple
times without needing to repeat the consolidation and conditioning step. The powder bed sits on a distributor plate,which sections the powder into multiple parts with an equalamount of powder. Each section of powder is conditioned
with the same T and RH and can be measured separately
by rotating the thin tube. Therefore, the blow test is convenient when interested in temporal measurements, suchas determining the rate of bed strength increase (Paterson
et al., 2005).

3.5 Comparison of tests
While simplicity is a strength of the visual observation
tests, it is also their greatest weakness. The accurate detection of the sticky-point temperature relies on the observer’s
experience. Based on caking theory, we expect that visible
changes in powder properties occur after a high degreeof agglomeration has taken place (Kamyabi et al., 2017).
Hence, human observers can miss the onset of stickiness,
which would cause an over-prediction of the sticky-pointtemperature. The onset of stickiness can be more precisely
quantified with the other tests. Based on the literature, wefind that shear tests are more accurate than penetration
tests, with less scatter of data and time consolidation effects that are easier to detect (Knight and Johnson, 1988;
Schwedes, 2003). Based on these findings, we recommend
using uniaxial compression or shear cells instead of penetration tests, in line with Knight and Johnson (1988), whorecommended to only use penetrometry in support of shear
cell experiments. While shear tests are applied to the bulkof the powder, the blow test is applied to the powder’s surface, suggesting that the blow test mostly tests the surface
conditions. Blow tests nevertheless create channels in the
powder bed (Billings et al., 2006; Paterson et al., 2005),
indicating that the bulk is strongly affected by blow test.
Hence, we expect that blow tests can be used to determine(bulk) stickiness, similarly to the shear tests. An advantageof the shear tests over the blow test is that the compression

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during consolidation can be maintained during conditioning, while an advantage of the blow test over the shear tests
is that multiple measurements can be performed without
having to repeat the consolidation and conditioning steps.
The shear, penetration, and blow tests can be used toquantify bed strength for different T and RH based on themeasured parameter (yield strength, penetration force,flow rate). To, in turn, relate bed strength to stickiness, apredetermined value of the critical bed strength is required
at which the powder of interest is considered sticky. A way
to overcome having to predetermine a critical bed strength
is by considering the temporal behavior. Experiments withthe blow test, for example, show an initial linear increaseof bed strength with time (Foster et al., 2006; Paterson etal., 2005). Similar experiments with shear cells are timeconsuming since each test requires repetition of consolida­tion and conditioning, but suggest a similar linear increaseof bed strength with time (Fitzpatrick et al., 2007a; 2007b;2008). By measuring the rate (i.e., slope) of increase for arange of T – Tɡ, one can infer the sticky-point curve T1(xw)by plotting the rate versus T – Tɡ and extrapolating to arateof zero. In case the critical bed strength is not available apriori, studying the temporal behavior to determine the rate
of bed strength increase as a function of T – Tɡ provides ameans to construct the sticky-point curve T1(xw).

3.6 Application areas of static stickiness tests
Generally, the static stickiness methods are useful in predicting the long-term behavior of powder during storage,transport, or in packaging. In these situations, particles may
stick together under the influence of humidity in a process
known as caking. This process comprises multiple steps.
Firstly, environmental conditions cause particle surfaces
to become viscous. Contacting liquid particle surfaces
become connected through liquid bridges. Secondly, theliquid bridges that formed grow in size, increasing powder

cohesion. Thirdly, the pores that existed between particles
disappear as the liquid fills up the pores (Kamyabi et al.,2017). During the caking process, the bed strength initially
increases with time until a maximum value is achieved. As
the process continues, the bed strength starts to decrease,attributed to partial crystallization of material to non-sticky
crystals (Fitzpatrick et al., 2007b), as well as a decreased
liquid bridge viscosity due to increased liquid adsorption(Hartmann and Palzer, 2011). Static stickiness tests are
particularly suitable for assessing the progress of caking bymonitoring bed strength as a function of time. Shear tests
are particularly useful because they can emulate storage
environment conditions in a warehouse or transport vehicle by maintaining a certain level of compression duringconditioning and measurement. Using shear cells where
the powder can be sheared against a wall material is also
applicable to measure powder stickiness in food packaging.

4. Dynamic stickiness tests
The class of dynamic stickiness tests covers the tests
where particles are not static during conditioning, but set incontinuous motion through external means. This introduces
particle velocity or contact time between particles as anadditional relevant parameter. An overview of dynamic
stickiness tests is listed in Table 1, showing the measured
parameter and the most suitable application. Most dynamic
stickiness tests approach the sticky region from the glassy
state, while just a few approach it from the liquid state.

4.1 Sticky-point test
The sticky-point test is the earliest reported method tomeasure stickiness, hence the name (Lazar et al., 1956).
This test has also been referred to as a propeller-driven
test (Boonyai et al., 2004). As shown in Fig. 3, the device

Table 1 List of methods to measure dynamic stickiness

MethodMeasured parameter

Application

Sticky-point test

TorquePowder mixing

Fluidized bed

Bed collapse/Pressure drop

Fluidized beds:
Preventing bed collapse
Granulation

Particle gun

Deposited mass

Cyclone test

Visual change

Pneumatic transport
Cyclones
Pneumatic transport
Cyclones
Fluidized beds

Optical test

Scatter intensity

Versatile application, opaque powder

Probe test

Tensile force

Droplet evaporation

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uses a container in which a powder with known moisture
content xw is placed. The sample container is submerged
in a heating medium to control the powder’s temperature.
The sample is continuously stirred at fixed angular velocity
with a stirring device, and the required torque τ is measured. Typically, a temperature ramp is imposed where thetemperature is slowly increased until the powder transitions
from the glassy to the rubbery state. Above Tɡ, the cohesive
forces increase. Further increase of the temperature leads
to particles sticking together, leading to a sharp increase in
the required τ. The temperature where this sharp increase isobserved is identified as the sticky-point temperature. By
repeating the test with different xw, the sticky-point curveT1(xw) can be found.
Detection of the sticky-point in the earliest versions
relied on manual stirring. When the stirring had become
noticeably more demanding, the sticky-point was reached(Downton et al., 1982; Lazar et al., 1956). More accurate
detection methods use automatic stirrers or shear cells
equipped with stirrers, which record the τ required forstirring (Özkan et al., 2002; Wallack and King, 1988). Recently, the method has been further improved by utilizing
aeration in an Anton Paar rheometer equipped with a propeller (Groen et al., 2020). The option to aerate the powder
is used to fluidize the powder, which occurs at a sufficiently
high airflow velocity. The powder conditions are controlled
by changing the T and RH of the airflow, instead of using
a heating medium surrounding the container. The propeller
stirs the fluidized powder and measures the required τ. The
required τ is substantially smaller than without fluidization,although the rheometers are sufficiently sensitive (Groenet al., 2020). The benefit of aeration or fluidizing is thatenvironmental conditioning occurs rapidly by changing
the air’s temperature and humidity. In our view, this makes
the sticky-point test combined with fluidizing the powder apromising method for measuring dynamic stickiness, bothin terms of accuracy and a shorter experimental time.
Besides applying the sticky-point test to free-flowing
powder, it has also been used to measure the stickiness ofFig. 3 A sticky-point test. A powder with known moisture content
is placed in a temperature-programmable water bath. The powder isstirred at a fixed angular velocity, and the required torque τ is measured.

32

drying liquids. Hence, instead of determining the stickypoint curve T1(xw), the tack boundary T2(xw) is determined.
Kudra (2003) used a laboratory batch dryer equipped witha stirrer to measure the stickiness of drying sludge. They
found that the temperature where the torque substantially
increased was different from the T1(xw) that is found whenapproaching from the glassy state. The conclusion wasthat most materials have a sticky-region in which they are
sticky (Kudra, 2003).

4.2 Fluidized bed
As discussed for the sticky-point test, the fluidization of
powder reduces the required conditioning time. However,
because powder fluidization is highly sensitive to powder
cohesiveness, the fluidized bed in isolation is also suitable
to measure stickiness. In a fluidized bed, which is shownin Fig. 4, a powder bed sits in a column while airflow isapplied at the bottom. Fluidization causes expansion of thepowder bed so that the powder displays fluid-like behavior
with a high degree of mixing. The sticky-point curve’s acquisition goes as follows: The T or RH of the fluidizing air
is increased stepwise. Most commonly, a RH ramp is used
at a fixed T by increasing the airflow’s humidity. As thecohesiveness increases, there is a point where the fluidized
bed collapses (defluidization). The conditions where thecollapse of the powder bed is observed, visually, or usingpressure drop measurements, is the sticky-point T1 (Palzer,
2005; Verdurmen et al., 2006). By repeating the RH ramp
at different temperatures, the sticky-point curve T1(xw) canbe drawn.
In many cases, fluidized bed collapse is detrimental
when it occurs. Hence, much research has been done on
the detection and prevention of bed collapse (Bartels et al.,2008). Methods such as the attractor comparison method
can be used to detect early changes in the bed that indicate
an upcoming collapse (Van Ommen, 2001) and havebeen used to determine the sticky-point curve T1(xw) (vanFig. 4 A fluidized bed test. The humidity or temperature of the conditioned airflow is increased stepwise until the powder bed collapses.

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der Knaap, 2006; Verschueren et al., 2007). When suchdetection methods are implemented, the sensitivity of thefluidized bed as a stickiness test is expected to be high.

4.3 Particle gun
The particle gun has been designed to measure thesticking of high-velocity particles to a wall and is shown in
Fig. 5. It is a duct through which conditioned air is flowing
at high velocity with a target plate at the far end of theduct. For each experiment, a sample of approximately 25 g
powder is introduced into the duct. The particles become
entrained in the conditioned air-jet shortly until eventually
impacting the target plate. Due to the short exposure ofparticles to the air, the particle gun relies heavily on the
rapid acclimation of the powder surface to environmental
conditions. The short acclimation time has consequences
for liquid bridge formation as the thin surface region thathas adsorbed vapor limits their potential width (Murti etal., 2010). The measured parameter is the percentage of
injected powder deposited on the target plate. Plotting thisparameter versus T – Tɡ shows negligible 0 % deposition
until a critical value of T – Tɡ is reached. Above this temperature, deposition is observed and increases linearly withT – Tɡ. The temperature where deposition starts increasing
is taken as T1(xw) (Zuo et al., 2007).

4.5 Optical test
Lockemann (1999) proposed an optical test, shown in
Fig. 7, which uses changes in reflectivity to determine thesticky-point curve. The proposed optical test consists of arotating test tube containing the free-flowing powder withknown (xw). The tube is inserted into an oil bath with aprogrammable temperature. A near-infrared source emits
light to the sample while a fiber-optical sensor records
the back-scattered signal. The sensor is also immersed in
the oil-bath to prevent any refraction of the signal. Whenparticles in the tube stick together, the powder flowability changes, which is observed as a sudden change inreflectivity. This marks the sticky-point temperature T1(Lockemann, 1999). The experiment has to be repeated for
different xw to determine T1(xw).

4.6 Probe test
The probe test is the only method that is solely applicable to measure stickiness when starting from the liquidstate. Hence, instead of the sticky-point curve T1(xw),
the tack boundary T2(xw) is found. The probe test can beapplied to liquid films or droplets (Chen J. et al., 2008;
Werner et al., 2007a). The approach for either is similar.

4.4 Cyclone test
The cyclone test, shown in Fig. 6, uses a cyclone inwhich conditioned air is circling (Boonyai et al., 2002).
When the air is at a steady-state, approximately 1 g of
powder is injected at the top of the cyclone. When conditions are such that the powder becomes sticky, particle
lumps and powder deposition on the cyclone are observed
within minutes. Longer experimental times lead to fullimmobilization of the powder. The experiment starts at a
low RH of the air and is increased stepwise until lumping
and deposition are observed visually, which marks a pointon the sticky-point curve T1(xw).

Fig. 5 The particle gun. Conditioned air flows with high velocity
through an air duct. The powder is introduced through a funnel, andthe entrained particles hit the target plate. Particles either bounce off ordeposit on the plate.

Fig. 6 A cyclone stickiness test. Conditioned airflow is used to circulate
a powder sample through the cyclone. Non-sticky particles remain
entrained in the cyclone, while sticky particles can agglomerate or stickto the cyclone wall.

Fig. 7 The optical test. A rotating sample tube is placed in a heatedwater bath. A fiber-optical sensor illuminates the sample and receives
scattered light. Redrawn from Lockemann (1999).

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The droplet probe test is shown in Fig. 8 and goes as follows. Droplet evaporation is monitored gravimetrically byplacing the droplet on a scale (Werner et al., 2007a, 2007b).
At some point during evaporation, a probe is loweredwith a fixed speed to touch the droplet’s surface and thenretracted, also with a fixed speed, while the required force
for retraction is measured. Hence, this approach is similar
to a force measurement with Atomic Force Microscopy(Fabre et al., 2016). The peak tensile force FTU is thendetermined, which is a measure of the tack, or stickiness,of the sample (Hammond, 1965; Kambe and Kamagata,1969). By plotting FTU versus drying time, a point is foundwhere FTU increases substantially, marking the tack boundary T2(xw) with xw determined gravimetrically based on theinitial solids concentration and the measured weight loss.
It should be noted that the measured FTU is influenced by
the probe speed and material (Adhikari et al., 2007; Green,1942). Besides xw, the sample’s temperature T also changes
during evaporation, which should be accounted for when
determining T2(xw) (Schutyser et al., 2019).

4.7 Comparison of tests
The particle gun, fluidized bed, cyclone test, and optical test use a powder as a starting point, approaching the
sticky region from the glassy state to find the sticky-point
curve T1(xw). The probe test starts from the liquid state andhence can be used to determine the tack boundary T2(xw).
The sticky-point test can be used starting from the glassy
or liquid state and is hence suited for determining bothboundaries. The influence of inter-particle contact time wasalready observed for the static stickiness tests investigating
caking. The longer the powder bed is subjected to environmental conditions where the powder will cake, the stronger
the powder bed becomes. Control over particle motion
and contact time in the dynamic stickiness tests provides
a means to investigate the influence of motion within asample on the boundaries of the sticky region.
Particle motion depends on the angular velocity of thestirrer or the container in the sticky-point and optical tests,

Fig. 8 The probe test. A probe is lowered until it touches the evaporating
droplet. The probe retracts, and the required tensile force FTU is measured. The droplet evaporation is monitored gravimetrically. Redrawn
from Boonyai et al. 2004.

34

on the air velocity in the fluidized bed, cyclone test, andparticle gun, and the probe speed in the probe test. A key
challenge, in comparing these tests or studying the influence of particle motion on the boundaries of the sticky region, is that particle motion largely differs in all these tests.
Even for a single test at a single condition, particle motion
may be heterogeneous. In a sticky-point test, for example,
stirring can cause the powder to distribute inhomogeneously in the stirring vessel, e.g., due to the stirrer digging
channels in the powder. Similarly, in a fluidized bed, theparticle velocities are inhomogeneous, mostly due to thecommon occurrence of bubbling (Seville et al., 2000).
Hence, quantification of the relative velocity between
the particles, and the resulting inter-particle contact time,presents a challenge, apart from the particle gun where theparticle impact velocity may be controlled and quantified(Murti et al., 2010; Walmsley et al., 2015; Zhao, 2009).
The clearest influence of particle motion has been
observed with the particle gun, as shown in Fig. 9. The
data by Murti et al. (2010) shows a minimal increase for(T – Tɡ)c with increasing vi. The data by Walmsley et al.
(2015) shows a sharp increase of (T – Tɡ)c with increasingvi, although, at vi > 20 m s–1, the effect appears to level
off. A similar trend was observed by Zhao (2009) where
vi ranged from 10 m s–1 to 45 m s–1. These particle gun
experiments show that a larger vi shifts T1(xw) to higher
temperatures so that (T – Tɡ)c is increased.
The influence of particle motion also becomes apparent
when different methods are compared with each other.
A static method where the visual change of an SMP bed
was used to find (T – Tɡ)c was compared with a dynamic
fluidized bed method where the pressure change wasused to find (T – Tɡ)c (Verdurmen et al., 2006). Over an

Fig. 9 Velocity-dependence of (T – Tɡ)c using skim milk powder and theparticle gun. Triangles ▲ are data by Walmsley et al. (2015); circles ●are data by Zhao (2009), and squares □ are data by Murti et al. (2010).
Note that the data cannot be directly compared between authors as
different experimental settings were used. Error bars indicate the experimental range for (T – Tɡ)c that was reported by the respective authors.
The dashed trendlines are to guide the eye.

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experimental range of RH = 12 % to 30 %, the average offset of the sticky-point curve to the Tɡ was determined. The
static test resulted in an average offset of T – Tɡ = 13 °C
and the dynamic stickiness test resulted in an average
offset of T – Tɡ = 18 °C. Another example is a comparison
between the dynamic fluidized bed and particle gun tests.
The (T – Tɡ)c was obtained for both methods using various
types of skim and whole milk powder. While the results
varied, for 6 out of 8 samples, the (T – Tɡ)c was lower for
the fluidized bed by ≈ 10 °C to 15 °C. For the other two
samples, the two methods provided similar results (Murti etal., 2010; Zuo, 2004). Based on these results, we strongly
recommend matching the velocity of the particles in the dynamic stickiness test to the application in mind to achieve
the most accurate T1(xw).
In an attempt to further clarify the influence of particle
motion on (T – Tɡ)c, data from dynamic stickiness tests wasgathered in Table 2. No data was found for the optical test
and data for the probe test could not be used to find (T – Tɡ)c.
For each experiment, the impact velocity vi of particle collisions was estimated. For the particle gun, the vi was chosen as the air jet velocity. For the sticky-point test, vi wasestimated as the maximum angular velocity of the stirrer.
For the fluidized bed, an average particle velocity v̂p was
estimated using Eq. (4), with U the superficial velocity andUmf the minimum fluidization velocity (Ennis et al., 1991).
The constant α was estimated from Seville et al. (2000)[11] tobe α = 0.53.
vˆp (U  U mf )(4)

For the data where vi could be estimated, no clear trend
with(4)(T – Tɡ)c could be found. Nonetheless, a wide range of(T – Tɡ)c = –5 °C to 90 °C has been reported. Further analysis indicated that, besides vi, material and experimental
differences can also play a substantial role in determining(T – Tɡ)c, some of which is highlighted below.
Some outliers can be explained by material differences,e.g. the (T – Tɡ)c = 90 °C is for a skim milk powder (SMP)
with 80 % protein, which is known to decrease stickiness(Hogan and O’Callaghan, 2010). Another example is thelow value of –5 °C for a fluidized bed experiment using
amorphous lactose. Using a range of RH = 7 % to 32 %,the results were (T – Tɡ)c = –5 °C to 3.8 °C with a single
outlier of (T – Tɡ)c = 21 °C for RH = 53 %, the highest
humidity tested. Amorphous lactose is known for its early
onset of stickiness (Zuo et al., 2007) and crystallization(Schulnies and Kleinschmidt, 2018). We expect the latter
could have played a role in the outlier as crystallization
reportedly reduces liquid bridge strength (Fitzpatrick et al.,2007b).
However, even for similar materials, the deviation canbe quite large. Using SMP in a particle gun with a velocityof 15 m s–1 the (T – Tɡ)c was found to be 34 °C to 36 °C

by Murti et al. (2010) and 57 °C to 61 °C by Walmsley etal. (2014). Two experimental differences explained thisdeviation. In the experiment of Walmsley et al. (2014), thedeposition was only measured for the air jet’s impingement
location, not for the entire target plate. Particles that strayfrom the jet direction move through the air with undefined
T and RH. Hence, the surface conditions of stray particles
cannot be accurately determined. Additionally, the target
plate was heated to match the temperature of the air jet.
The plate temperature Tp can play an important role andis often a relevant industrial parameter, e.g., in dryers,
pneumatic ducts, fluidized beds, and cyclones (Walmsley
et al., 2014). A higher Tp is known to reduce the amount ofwall deposition (Chen X.D. et al., 1993). Walmsley et al.
(2014) found reduced deposition for higher Tp, which wasconsistent regardless of the used vi. Such wall temperatureeffects are also found outside of food processing, such as
cold spray deposition (Khalkhali and Rothstein, 2020). The
improvements of the particle gun made by Walmsley et al.
(2014) show that the experimental conditions influence theresulting T1(xw). Hence, the experimental conditions need
to be accurately chosen when stickiness tests are used forpredicting powder processing parameters.

4.8 Application areas of dynamic stickiness tests
The moving nature of the particles in dynamic stickinesstests makes these tests useful for predicting the behaviorof powder in most of powder production and processing
equipment. However, it makes them unsuitable for measuring powder caking. The application of the dynamic
tests will depend on the impact velocity vi of collisions
and whether particle-particle or particle-wall collisions aretested.
The particle gun can measure the highest impact velocityof all the reviewed methods and involves particle-wallcollisions. Initially, an impact velocity of 20 m s–1 waschosen for its similarity to industrial cyclones (Zuo et al.,2007). The high impact velocity makes it a useful method
to predict stickiness for high-velocity pneumatic handling,
dried material colliding with spray dryer walls, or industrial cyclones. Additionally, by changing the target plate’smaterial or dimensions, the influence of wall material or
impact angle can also be investigated (Murti et al., 2010;
Walmsley et al., 2015).
The sticky-point test and fluidized bed have continuously moving powder, making these tests useful forvarious industrial applications involving moving powders
such as powder mixing, blending, and milling. Sincemany industrial processes incorporate a fluidized bed, astickiness test using fluidized powder will be most applicable to the fluidized bed itself. Limitations of the stirrer’s
angular velocity and the velocity of fluidization airflow
make the sticky-point test and fluidized bed ill-suited for35

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Table 2 A selection of the reviewed literature for dynamic stickiness tests.
Material

Method(T – Tɡ)c (°C)

vi (m s –1)

Ref.

Sucrose & fructose

Sticky-point test

9 to 26a—

Downton et al., 1982

Amorphous lactose

Fluidized bed–5 to 210.055 ± 0.055b

Zuo et al., 2007

Amorphous lactose

Particle gun

19 to 37

20

Zuo et al., 2007

Particle gun

36 to 40a

20

Paterson et al., 2007aCoffee creamer (maltose)

Fluidized bed

10 to 20a0.05 ± 0.025b

Groen et al., 2020

High fat cream powder

Particle gun

38

20

Paterson et al., 2007b

Low fat cream powder

Particle gun

26

20

Paterson et al., 2007b

SMP15

Fluidized bed

10—

Hogan and O’Callaghan, 2010

SMP25

Fluidized bed

22—

Hogan and O’Callaghan, 2010

Maltodextrin DE21

Fluidized bed

47 to 62—

Palzer, 2005

SMP55

Fluidized bed

45—

Hogan and O’Callaghan, 2010

SMP80

Fluidized bed

90—

Hogan and O’Callaghan, 2010

Orange juice powder

Sticky-point test

17 to 25a—Brennan et al., 1971

SMP

Fluidized bed

14 to 23—

Verdurmen et al., 2006

SMP

Fluidized bed

29—

Hogan and O’Callaghan, 2010

SMP

Fluidized bed

25 to 34

0.01

Murti et al., 2010

SMP

Sticky-point test

23

0.3

Hennigs et al., 2001

SMP

Cyclone test

11.4

—

Intipunya et al., 2009

SMP d < 45 μm

Particle gun

8.2

10.3

Zhao, 2009

SMP d < 45 μm

Particle gun

14.8

19.4

Zhao, 2009

SMP d = 45 μm to 65 μm

Particle gun

11.6

10.3

Zhao, 2009

SMP d = 45 μm to 65 μm

Particle gun

23.5

19.4

Zhao, 2009

SMP

Particle gun

18.6

10.3

Zhao, 2009

SMP

Particle gun

30.1

14.8

Zhao, 2009

SMP

Particle gun

39

19.4

Zhao, 2009

SMP

Particle gun

53.4

45.6

Zhao, 2009

SMP

Particle gun

34

4.5

Walmsley et al., 2015

SMP

Particle gun

48

5.4

Walmsley et al., 2014

SMP

Particle gun

43

6.5

Walmsley et al., 2015

SMP

Particle gun

30 to 31

10

Murti et al., 2010

SMP

Particle gun

34 to 36

15

Murti et al., 2010

SMP

Particle gun

57 to 61

15

Walmsley et al., 2014

SMP

Particle gun

32 to 35

20

Murti et al., 2010

SMP

Particle gun

60 to 63

25

Walmsley et al., 2014

SMP

Particle gun

33 to 43

30

Murti et al., 2010

Tomato powder

Sticky-point test

36 to 41a—

Lazar et al., 1956

White cheese powder

Particle gun

28

20

Paterson et al., 2007b

Whole milk powder

Fluidized bed

23 to 38

0.09

Zuo et al., 2007

Whole milk powder

Particle gun

38 to 6120

Zuo et al., 2007

Whole milk powder

Sticky-point test

36 to 41a1.0Özkan et al., 2002

Amorphous lactose

a The (T – T ) was not directly obtainable from the paper, instead, it was calculated using Eq. (1) and Eq. (2).
ɡ cb A range for fluidization velocity was reported, authors did not test the influence of velocity.

SMP15: Skim milk powder with 15 % protein, similar for SMP25, SMP55, and SMP80. Ranges for (T – Tɡ)c are mostly due to experimental scatter.

36

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high-velocity processes such as spray drying or pneumatic
handling. Further work on the influence of the intensity ofcontinuous mixing on the sticky-point is required to choose
experimental conditions for specific applications whenusing the sticky-point test and the fluidized bed. Using the
sticky-point test with a fluidized powder solves some of theissues of the individual methods. However, sensitive equipment is necessary to measure the smaller increase of torqueat the sticky-point, compared to without fluidization, whichis possible with advanced rheometers (Groen et al., 2020).
The cyclone test was proposed as an alternative for the
fluidized bed test, while we expect it to achieve sufficientparticle motion to be an alternative for the particle gun as
well. Boonyai et al. (2004) suggested that the cyclone test’s
primary advantage over the fluidized bed is that the cyclone
test measures both adhesion and cohesion while the fluidized bed measures only cohesion. Therefore, the cyclone
test would be more suitable to predict stickiness in spraydrying, fluidized beds, and pneumatic handling of powders(Boonyai et al., 2004). However, it is difficult to judge thisstatement since, besides the original paper by Boonyai etal. (2002), we only found one application of the cyclone
test in literature (Intipunya et al., 2009).
The optical test can be used if the tested material scattersnear-infrared light (Boonyai et al., 2004). Since it was
proposed, no further experiments using this method havebeen reported to our knowledge. Hence, no judgment of its
applicability can be made momentarily. Still, commonly
tested powders such as amorphous lactose and various milk
powders are all opaque, indicating that this method could
be applied to these powders.
The most prominent application for the probe test is
the droplet evaporation phase of spray drying. However,the use of a bulk moisture content severely limits thisapplication. Werner et al. (2007a) measured the stickinessof an evaporating droplet with the probe test. The onsetof stickiness occurred much earlier than expected basedon the droplet’s bulk moisture content, which indicatedsolute had accumulated at the droplet surface. Hence, thegravimetrically determined droplet water content is an unhelpful parameter for determining T2(xw), which makes theprobe test not applicable to industrial processes involving
rapid evaporation. Crucially, this includes spray drying,
for which there is no adequate method to predict droplet
stickiness in the initial evaporation phase. Future methods
should focus on the drying droplet’s surface conditions forfinding the tack point T2(xw), either through direct measurement or by modeling the gradient formation under the
influence of evaporation (Adhikari et al., 2005).

5. Conclusion

measure the stickiness of amorphous powders relevant in
the food industry. The reviewed methods included visualobservation tests, shear tests, the penetration test, the blow
test, the sticky-point test, the fluidized bed, the particle
gun, the cyclone test, the optical test, and the probe test.
For each method, we described how either the sticky-pointtemperature T1(xw) or the tack boundary T2(xw) can be
determined. We have classified the methods based on theparticle mobility during the conditioning and measurement
steps into static stickiness tests and dynamic stickinesstests.
Static stickiness tests have limited particle motion
during the conditioning step, which can be as long as
desired. Therefore, these tests are particularly suitable tomeasure the caking rate of powder beds. Hence, industrial
applicability is predominantly in predicting the long-term
behavior of powder during storage or in packaging. Static
stickiness tests have shown that the caking rate can be related to T – Tɡ when T – Tɡ > (T – Tɡ)c, although the natureof the relation is dependent on the used method. Nonetheless, this approach gives much insight into the stability ofstored powders.
Dynamic stickiness tests involve particles with significant particle motion during the conditioning and measurement step. The particle gun is a good method to measurestickiness during particle-wall impacts, while the combination of the sticky-point test and fluidized bed measurestickiness for particle-particle collisions and continuously
mixed systems. A wide range of testing conditions can beachieved by varying the impact velocity or contact time
between particles. Hence, information from dynamic stickiness tests is highly relevant to the design and operation of
powder production and processing equipment. Dynamic
stickiness tests have shown that velocity plays an importantrole in the location of the sticky region, with larger velocity
shifting the sticky-point curve T1(xw) to higher temperatures so that a larger (T – Tɡ)c is obtained.
An essential type of stickiness test that is lacking is a dynamic test that measures particle stickiness when movingfrom the liquid state to the sticky-region, hence, finding
the tack boundary T2(xw). Much unclarity exists for whenevaporating solute containing droplets are sticky, while
this is hugely relevant for spray drying, which is one of themost used processes in the food processing industry. The
probe method does approach the sticky-region from theliquid state, but the reliance on the droplet’s bulk properties
makes it unable to determine values for T2(xw). Further
work in predicting the surface stickiness, either throughdirect measurement or by modeling the gradient formation
under the influence of evaporation, is required to predict
droplet stickiness.

In this review, we provided an overview of methods that37

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Acknowledgments
This scientific work is supported by the Netherlands
Organization for Scientific Research (NWO) (grant number 15459).

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Zuo J.Y., Paterson A.H., Bronlund J.E., Chatterjee R., Using aparticle-gun to measure initiation of stickiness of dairy powders, International Dairy Journal, 17 (2007) 268–273. DOI:
10.1016/j.idairyj.2006.02.010

Authors’ Short Biographies
Erik J.G. Sewalt
Erik Sewalt MSc obtained his MSc in Food Technology at Wageningen University &Research. His specialization was Sustainable Food Process Engineering. His MSc thesis
was about modeling the diffusion of pepsin in protein gels to understand food breakdown.
He did an internship on in-vitro digestion of protein-rich food at University of California,
Davis, USA. From October 2017, he became a PhD candidate at TU Delft, Faculty of Applied Sciences, Product and Process Engineering. His research activities as PhD candidate
revolve around understanding the agglomeration of evaporating droplets in spray drying.

40

Erik J.G. Sewalt et al. / KONA Powder and Particle Journal No. 38 (2021) 26–41

Authors’ Short Biographies
Fuweng Zhang
Dr. Fuweng Zhang is a postdoc working at Dept. Chemical Engineering, Delft University of Technology (the Netherlands). He received his Ph.D. from the University of
Sciences and Technology Beijing in 2014. After that, he was appointed as a post-doctoral
researcher working at University College Cork, Ireland. He has 6 years of experience inthe research area of multi-phase flow, pneumatic transportation, and fluidization of powdermaterials. He currently focuses his research on developing novel technologies to enhance
the fluidization of the cohesive pharmaceutical powders.
Volkert van Steijn
Assistant Professor at the Department of Chemical Engineering at Delft University ofTechnology (the Netherlands). He obtained his PhD degree on droplet microfluidics in2010, with honours. He worked as a postdoc at Harvard University in the lab of Prof. David
Weitz on the development of droplet-based laboratories-on-a-chip for applications in thearea of life sciences. With a strong background in soft matter, droplet flows, and transportphenomena, his group develops microfluidic tools that contribute to solving problems in
the area of health and life sciences.

J. Ruud van Ommen
Professor of Chemical Enginering at Delft University of Technology (the Netherlands).
He obtained his PhD degree at Delft in 2001. He has been visiting professor at Chalmers
University of Technology (Gothenburg, Sweden) and the University of Colorado (Boulder, USA). In recent years, he expanded his research from chemical reactor engineeringto the scalable production of advanced, nanostructured materials. In 2011, he started an
ambitious program (funded by an ERC Starting Grant) to investigate the interplay between
agglomeration and coating of nanoparticles in the gas phase. He has published about 200
journal papers, of which a considerable part on powder technology.
Gabrie M.H. Meesters
Dr Gabrie Meesters has 27 years of industrial formulations experience at Gistbrocades,
Genencor International and DSM. He has 23 years of experience as a part-time professor at
TU Delft in particle technology and product design. From January 2019, he became a fulltime assistant professor at the TU Delft, Faculty of Applied Sciences, Product and Process
Engineering. He is a contributor to several books on formulation. He is the editor of threebooks on product design and solids processing. He published over 70 refereed papers, hasmore than 20 patents and supervised more than 100 BSc, MSc and PhDs. He is a regularspeaker at conferences and workshops. He was the organizer of the 2010 Partec and the2010 World Congress on Particle Technology in Nuremberg, Germany.

41

KONA Powder and Particle Journal No. 38 (2021) 42–63/https://doi.org/10.14356/kona.2021004

Review Paper

Inertial Impaction Technique for the Classification ofParticulate Matters and Nanoparticles: A Review †Thi-Cuc Le and Chuen-Jinn Tsai *Institute of Environmental Engineering, National Chiao Tung University, Taiwan

Abstract
Inertial impactors are applied widely to classify particulate matters (PMs) and nanoparticles (NPs) with desired
aerodynamic diameters for further analyses due to their sharp cutoff characteristics, simple design, easy
operation, and high collection ability. A few hundred papers have been published since the 1860s that addressed
the characteristics and applications of the inertial impactors. In the last 30 years, our group has also carried out
lots of studies to contribute to the design and the improvement of inertial impactors. With our understanding ofinertial impactors, this article reviews previous studies of some typical types of the inertial impactors including
conventional impactors, cascade impactors, and virtual impactors and the parameters for design consideration ofthese devices. The article also reviews some applications of the inertial impactors, which are mass concentration
measurement, mass and number distribution measurement, personal exposure measurement, particulate matter
control, and powder classification. The synthesized knowledge of the inertial impactor in this study can help
researchers to design an inertial impactor with an accurate cutoff diameter, a sharp collection efficiency curve, andno particle bounce and particle overloading effects for long-term use for PM classification and control purposes.
Keywords: inertial impactor, cascade impactor, virtual impactor, nanoparticles, sampling

1. Introduction
There was a great demand to develop devices for collecting airborne particles of different sizes to study the effect of particulate matters (PMs) on human health(Anderson J.O. et al., 2012). In the period from 1860 to
1880, researchers discovered that inertial impactors canbe used to collect airborne particles for further analysis(Marple V.A., 2004). The inertial impactors including theconventional impactor, cascade impactor, and virtual impactor can classify particles into different size ranges
based on particle’s inertia. In the inertial impactors, when
the airflow is forced to change the direction, the particles
with sufficient inertia escape the turning flow while theparticles with less inertia remain in the flow resulting in
the particle size-based classification. A burst of development of the inertial impactors has exploded since 1945
when the first cascade impactor (a series of conventional
impactors) was developed to collect size-fractionated airborne particle samples with a high collection efficiency toobtain the particle mass distribution (May K.R., 1945).
†

Received 4 December 2019; Accepted 6 February 2020
J-STAGE Advance published online 31 March 2020
* Corresponding author: Chuen-Jinn Tsai;
Add: University Road, Hsinchu 30010, Taiwan
E-mail: cjtsai@nctu.edu.tw
TEL: +886-3-5731880 FAX: +886-3-5727835

42

Since the 1970s, researchers computed the flow field andparticle trajectories within the impactor by using the finite
difference methods and showed that the impactor has a
sharp cutoff characteristic (McFarland A.R. et al., 1978).
Thereafter, the impactor was considered as a standard device for PM classification based on particle aerodynamic
diameter.
The virtual impactor was developed later since 1966
(Conner W.D., 1966) with a feature not found in the conventional impactor, in which particles are collected in aprobe instead of on the collection plate to avoid particle
bounce. The virtual impactor also attracted lots of interest
from researchers for PM classification since two particle
size fractions can be collected for further analysis as thedesign theory was studied and better understood (Marple
V.A. and Chien C.M., 1980; Zahir M.Z. et al., 2018). Since
1970 until now, inertial impactors have been used extensively for various purposes such as (i) size-based classification for mass concentration measurement (Le T.C. andTsai C.J., 2017; Le T.C. et al., 2019), (ii) particle mass distribution measurement (Marple V.A. et al., 1991;
Demokritou P. et al., 2004a), (iii) chemical composition
measurement (Marple V.A. et al., 1991), (iv) personal exposure measurement (Tsai C.J. et al., 2012b), and (v)nanoparticle (NP) measurement (Chow J.C. and Watson
J.G., 2007).
The main reasons behind the diverse application of the

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Thi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63

inertial impactors are their sharp separation, high collection abilities, relatively simple design, and easy operation.
But several limitations are inherent to the impactors suchas particle bounce and re-entrainment (Turner J.R. andHering S.V., 1987; Fujitani Y. et al., 2006), particle overloading (Tsai C.J. and Cheng Y.H., 1995; Demokritou P.
et al., 2004b), and particle loss (Fang C. et al., 1991;
Durand T. et al., 2014), which can degrade their performance. Moreover, some typical characteristics of the inertial impactors such as the cutoff diameter, the sharpnessof collection efficiency curve, and the properties of the
impaction substrate should be understood well since PMs
have different sizes, shapes, types, compositions andcharacteristics (Loo B.W., 1975; Hinds W.C., 1999). There
have been many studies conducted to resolve these issues
from 1970 onward, which are reviewed in detail in Section 2.
In the last 30 years, our group has also carried out lotsof studies to contribute to the design and the improvementof inertial impactors. In 1995, an impactor with an inverted conical cavity as the collection plate was developed
to eliminate the particle bounce and re-entrainment andenhance the loading capacity (Tsai C.J. and Cheng Y.H.,
1995). This design was studied further by other researchers (Chang M. et al., 1999; Kim D.S. et al., 2006; Kim Y.J.
and Yook S.J., 2011; Kim W.G. et al., 2013) and used forthe development of the EPA (Environmental Protection
Agency) PM2.5 well impactor ninety-six (WINS) (Peters
T.M. et al., 2001). Some different personal samplers weredeveloped to measure respirable particles and NPs for the
exposure assessment at workplaces such as personal inertial impactor (Huang C.H. et al., 2006) and novel active
personal nanoparticle sampler (PENS) (Tsai C.J. et al.,2012b). The PENS was used for further studies by otherresearch groups (Hsiao T.C. et al., 2010; Hsiao T.C. et al.,2011; Sung G. et al., 2018) or for field measurements(Young L.H. et al., 2013; Zhou Y. et al., 2014; Zhu C.S. etal., 2016; Asbach C. et al., 2017; Zhu C.S. et al., 2017).
Some commercial sampling devices were studied to improve their sampling performance at our laboratory. We
found the inter-stage loss of NP clogging in the last fourstages of the micro-orifice uniform deposit impactor(MOUDI) due to its step-wised nozzle structure withabrupt contraction (Liu C.N. et al., 2013b) and developed
the NCTU micro-orifice cascade impactor (NMCI) withsmooth nozzle shape to eliminate these problems (Chien
C.L. et al., 2015). The sampling performance of the standard EPA louvered PM10 inlet and PM2.5 WINS inlet wasstudied and the particle bounce, re-entrainment, and particle overloading effects of these devices were found (LeT.C. and Tsai C.J., 2017; Le T.C. et al., 2019). The
non-bouncing modified louvered PM10 (M-PM10) inlet andthe modified WINS (M-WINS) were developed for the
long-term sampling purpose without the need for frequent

maintenance. A multi-filter PM10 and PM 2.5 sampler(MFPPS) which consists of PM10 and PM2.5 impactors
was developed for collecting multiple samples of PM10
and PM2.5 simultaneously for different analyses or comparison tests of different devices (Liu C.N. et al., 2011).
Besides, numerous theoretical and experimental studies
have been carried out by our group, which explored fundamental issues of the inertial devices including the effectof gravity on particle collection efficiency (Huang C.H.
and Tsai C.J., 2001), the influence of impaction plate diameter and particle density on the collection efficiency ofinertial impactors (Huang C.H. and Tsai C.J., 2002a), theeffect of porous metal (Huang C.H. et al., 2001; Huang
C.H. and Tsai C.J., 2002b; Huang C.H. and Tsai C.J.,
2003) and porous foam (Huang C.H. et al., 2005) as theimpaction substrate on the cut-size and collection efficiency, and the influence of the relative humidity (RH) on
NP concentration and particle mass distribution measurements by the MOUDI (Chen S.C. et al., 2011).
With our understanding of inertial impactors, this article aims to synthesize the existing knowledge of impactor
design and discuss future perspectives in the applicationsof inertial techniques to classify PMs, NPs, and powder.
The design principle, cutoff characteristics, and the advantages and disadvantages of each type of inertial impactors are reviewed. Some typical applications of inertial
impactors including mass concentration measurement,
mass and number distribution measurement, personal exposure measurement, PM control, and powder classification are discussed. Two types of inertial impactors
including the conventional impactor and the virtual impactor are covered.

2. Principle and design consideration
The types and principles of the inertial impactors arepresented in textbooks (Hinds W.C., 1999; Marple V.A.
and Olson B.A., 2011) and are described briefly here to
support the design and application considerations. The
description and pros and cons of each type of inertial impactors are summarized in Table 1. The lists of theircommercial devices can be found in Watson J.G. andChow J.C. (2011).

2.1 Conventional impactor and cascade impactor
A conventional single-stage impactor consists of asingle or multiple nozzles which are either round- or
rectangular-shaped and an impaction plate below the nozzle as shown in Fig. 1a. When the particle-laden air
passes through the nozzle(s) and makes a turn above theimpaction plate, particles with sufficient inertia are notable to follow streamlines and impact on the collection
plate while particles with less inertia will flow out of the43Thi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63
Table 1 Types of inertial impactors.

Brief description

Pros and cons

Typical devices

References

The impactor consistsof a single nozzle andan impaction plate,used to collect particles smaller than acertain size.

Pros: Simple configuration, easy
operation, and low cost.
Cons: Low flow rate, large
cut-size, and possible particle
bounce, particle overloading, andparticle loss.

EPA PM2.5 WINS;EPA louvered PM10
inlet; EPA flat-topped
PM10 inlet

McFarland A.R. et al.,
1984;
Peters T.M. et al.,2001;
Tolocka M.P. et al.,
2001

Single-stage,
The impactor consists
multi-nozzle impactor of a nozzle plate withmultiple nozzles andan impaction plate,used to collect particles smaller than acertain size.

Pros: Simple configuration, easy
operation, a wide range of flow
rates, and a smaller cut-size.
Cons: Particle bounce, particle
overloading, particle loss, andmultiple jet interactions.

EPA Hivol PM10
impactor (1133 L/min); Harvard sharpcut impactor (10 and
20 L/min)

McFarland A.R. et al.,
1984;
Turner W.A. et al.,2000

Cascade impactor

The impactor is aseries of multi-nozzle
impactors, used tomeasure particle mass
distribution.

Pros: It can measure particle
mass distribution ranging from10 nm to 10 μm.
Cons: Possible overloading,particle re-entrainment, andinterstage loss.

MOUDI; MOUDI-II;
Andersen cascade
impactor; NMCI

Andersen A.A., 1966;
Marple V.A. et al.,1991;
Chien C.L. et al., 2015

Low pressure impactor (LPI)

The cascade impactor
operates at low
pressure condition.

Berner-type low-pres- Berner A., 1972
Pros: It can measure particle
mass distribution of NPs down to sure impactor
10 nm.
Cons: High pressure drop.

Electrical low pressure impactor (ELPI)The device consists ofa charger and acascade impactor coupled with electrometers, used to measureparticle number
concentrations electrically

Pros: Automatic and nearlyreal-time measurement with a
response time of less than 5 s.
Cons: Possible particle bounce
unless the oil-coated sintered-metal substrate is used;
Resolution is not good for NPs.

Dekati@ ELPI

Keskinen J. et al.,
1992;
Järvinen A. et al.,2014

Virtual impactor

The impactor consistsof a single nozzle anda single collection
probe, used to collecttwo particle size
fractions.

Pros: No particle bounce andparticle loading effect; Simultaneous measurement of two
particle size ranges.
Cons: Contamination of coarse
particles by particles smaller
than the cut-size; Particle loss;
Use of two flow meters.

Dichotomous sampler

McFarland A.R. et al.,
1978

Single-stage, singlenozzle impactor

impactor and are either collected by a filter for further
analyses or measured directly by an aerosol instrument(Marple V.A. and Olson B.A., 2011). In order to classify
particles into many size ranges, a series of single-stage
impactors are used, which is called cascade impactor(Marple V.A. and Olson B.A., 2011). The successive
stages are designed to provide progressively higher jet
speeds and/or reduced pressures so that the average aerodynamic size of particles collected at each stage is progressively smaller. Many nozzles (multi-nozzle) are44

mainly used to increase the airflow rate. These nozzles
are drilled on a nozzle plate which is placed on the top of
the impaction plate with a given jet-to-plate distance.

2.1.1 Design theory
The design theory of the conventional impactor isbased on the numerical modeling of the flow field and theequations of particle motion by Marple and co-workers(Marple V.A. and Rubow K.L., 1986). The performanceof the inertial impactor is characterized by the collection

Thi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63

Fig. 1 Inertial impactor problems (a) normal case (b) particle bounce, (c) particle overloading, and (d) particle loss.

efficiency curve, which is an “S” shape curve due to the
non-ideal and non-uniform flow field in the impactor. The
collection efficiency curve is represented by the cutoff
aerodynamic diameter (Dpa50), which is the aerodynamic
diameter for 50 % collection efficiency, and the sharpness
or geometric standard deviation (GSD ≥ 1.0) of the particle collection efficiency curve. The GSD is calculated as(Marple V.A. and Olson B.A., 2011)

GSD 

Dpa84

(1)

Dpa16

where Dpa84 and Dpa16 are the aerodynamic diameters for
84 % and 16 % collection efficiencies, respectively. The
most important parameter that governs the collection efficiency is the Stokes number (Stk) which is used to predictwhether a particle will impact on the impaction plate orfollow the air streamlines to exit the impactor. Stk is theratio of the particle’s stopping distance to the characteristic dimension of the nozzle and is calculated as follows(Marple V.A. and Olson B.A., 2011)Stk

p Dp2Cc Dp  U 0

9 W

2 C ( D )Up0 Dpa
c
pa
0

9 W

(2)

where ρp is the particle density (kg/m3), ρp0 is the unit
density (1000 kg/m3), Cc is the slip correction factor, U0 is

the air jet velocity (m/s), Dp is the particle diameter (m), μ
is the dynamic air viscosity (kg·s/m2), and W is the diameter or the width of nozzle (m). Stk50 is the Stokes number
for 50 % collection efficiency. For an impactor, Stk50 is
usually fixed under optimized conditions, and Dpa50 can
be calculated as the following equation (Marple V.A. and
Olson B.A., 2011):

Dpa50 9 W
p0Cc (Dpa50 )U 0

Stk 50(3)

Jet Reynolds number (Re) is another parameter governing the flow field and the particle collection efficiency. Re
influences the sharpness of the collection efficiency curve
more than the cutoff diameter. Re of the round-nozzle impactor is expressed as (Marple V.A. and Olson B.A., 2011)Re 

ρaWU 0μ(4)where ρa is the air density (kg/m3). The inertial impactors
will have sharp and nearly the same collection efficiency
curves with a fixed Stk50 of 0.24 (round nozzle) or 0.59
(rectangular nozzle) if Re ranges from 500 to 3000.
The S/W ratio, which is the jet-to-plate distance (S) divided by W, also influences the collection efficiency. An

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Thi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63

impactor will have a sharp efficiency curve if S/W isgreater than 1.0 for a round-nozzle impactor and greaterthan 1.5 for a rectangular-nozzle impactor (Marple V.A.
and Rubow K.L., 1986). S/W usually ranges from 1 to 5 toeliminate the effect on Stk50 for single nozzle impactors(Marple V.A. and Liu B.Y., 1974). Furthermore, in orderto provide a sufficient time for the particles to accelerate
to the fluid velocity, the throat length (T) divided to W (T/W) should be larger than 1.0 and the entrance of the nozzle should be tapered or conical (Marple V.A. and WillekeK., 1976). In addition, the effect of particle gravity on theincreasing particle collection efficiency was found when
Re is below 1500 (Huang C.H. and Tsai C.J., 2001). Other
parameters influencing the collection efficiency curves
are the impaction plate diameter, the particle density(Huang C.H. and Tsai C.J., 2002a) and the design of impaction surfaces (Tsai C.J. and Cheng Y.H., 1995; Tsai
C.J. and Lin T.Y., 2000). A small impaction plate willcause an increase in the cutoff diameter (Huang C.H. andTsai C.J., 2002a) while a small impaction well will decrease the cutoff diameter due to the secondary impaction
on the wall of the well (Hu S. et al., 2007).
It is noted that the above design considerations are not
only suitable for singe-nozzle, single-stage impactor but
also applicable for the multi-nozzle, multi-stage impactor
with nozzles far enough from each other. If the nozzles
are too close, nozzle crossflow interaction occurs, which
affects the collection efficiency of the multi-nozzle impactor (Fang C. et al., 1991; Kwon S.B. et al., 2002). The
cross-flow parameter, which is a function of the numberof nozzles, nozzle diameter, and nozzle cluster diameter,should be less than 1.2 to eliminate the effect of the crossflow interaction (Fang C. et al., 1991). Other previous
studies showed that the cutoff characteristics of themulti-nozzle impactor are also effected by S/W and Re
even if they fall in the recommended range for the singlenozzle impactor (Gudmundsson A. et al., 1995; Kwon S.B.
et al., 2002; Yao M. and Mainelis G., 2006). The cutoff
characteristics of successive stages of the cascade impactor with the Dpa50 < 100 nm was found to be very sensitive
to S/W (Arffman A. et al., 2011; Tsai C.J. et al., 2012b; Liu
C.N. et al., 2013b). In the multi-nozzle impactor, the secondary deposit of particles due to the jet interaction leads
to the differences between the theoretical and experimented collection efficiencies and the less sharp collection
efficiency and lower Stk (Rocklage J.M. et al., 2013;
García-Ruiz E. et al., 2019).
To achieve smaller cut-sizes in the lower stages of thecascade impactor, multiple micro-orifice impactors(MOIs) or low pressure impactors (LPIs) are used. In the
LPIs, particles with a very small cutoff diameter (e.g.
0.05 μm) are collected due to the increase of the slip correction factor with the decrease in the pressure. A large
vacuum pump to draw the air through the nozzles at a

46high flow velocity is needed which creates a large pressure drop for the impaction to take place at low pressure(e.g. 3 kPa). The nano-size cutoff diameter (e.g. 2 or 5 nm)
can also be achieved by expanding the aerosol into an
evacuated region creating hypersonic impaction conditions (Fernandez de la Mora J. and Schmidt-Ott A., 1993).
These low pressure impactors may have the evaporation
loss of semi-volatile particle materials (SVM) (Biswas P.
et al., 1987). In comparison, in the MOIs, the smaller cutoff diameter is obtained by using numerous small microorifices, which provide the desirable flow rate at a relatively low pressure drop. The evaporation loss of SVMs
was shown to be eliminated in the MOIs if the pressure
drop is less than 40 kPa (Fang C. et al., 1991). The cascade impactor can be developed with the above design
considerations and calibrated with the standard method
presented by Marple V.A. and Olson B.A. (2009). The
consideration of designing an inertial impactor with asmaller cut-size, a sharper collection efficiency curve, anda higher flow rate is summarized in Table 2.
There major drawbacks of the conventional impactor
are particle bounce, particle overloading and particle loss
as shown in Fig. 1b–d. Since these effects can cause theshift of the cutoff diameter and the collection efficiency
curve leading to incorrect PM measurement, numerous
researches have studied these problems to find out thesolutions (Liu C.N. et al., 2013b; Le T.C. and Tsai C.J.,
2017; Le T.C. et al., 2019).

2.1.2 Particle bounce effectParticle bounce occurs when the impactor plate is unable to absorb the kinetic energy of the incident particles
completely (Fig. 1b). The particles are not retained by thesurface, resulting in the lower particle collection efficiency for particles larger than the cutoff diameter (John
W. et al., 1991; Bateman A.P. et al., 2013). The reboundparticles can be collected on the after filter or a subsequent stage resulting in the positive bias of PM measurement or the shift of the mass distribution toward smaller
aerodynamic sizes (Marple V.A. and Olson B.A., 2011;
Jain S. and Petrucci G.A., 2015). The particle bounce depends on the adhesion energy between particles and theimpaction surface, the energy loss mechanisms in particles (dissipation energy) and the initial velocity (or kinetic
energy) of particles (Bateman A.P. et al., 2013; Jain S. andPetrucci G.A., 2015). After impaction, the incident kinetic
energy is balanced by several energy relaxation terms including dissipation energy, adhesion energy, and reboundenergy. Rebound energy that is greater than the sum of
dissipation and adhesion energies will result in particle
bounce. Physical properties of particles such as hygroscopicity, size, density, phase, elasticity, and hardness canalso play an important role in particle bounce behavior(Matthew B.M. et al., 2008; Bateman A.P. et al., 2013;

Thi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63
Table 2 Design considerations of inertial impactors.

Requirements

Solutions

Limitations

References

To decrease thecut-size by

increasing the flow rate

Re numbers should be in the range of
500–3000 to achieve a sharp collection
efficiency curve

Marple V.A. and Rubow K.L.,
1986

decreasing the diameter orwidth of nozzles

It may cause an increased pressure drop
and it is hard to fabricate the micro-size
nozzlesBerner A., 1972;
Marple V.A. et al., 1991

decreasing the jet-to-plate
distance

It may cause an increased pressure drop
if S/W is ≤ 1.0 for round-nozzle impactors and ≤ 1.5 for rectangular-nozzle
impactors

Chien C.L. et al., 2015

increasing nozzle throat length T/W ≥ 1.0

To increase the
sharpness of thecollection efficiency
curve byTo increase the flowrate byMarple V.A. and Liu B.Y.,
1974

increasing the impaction plate
diameter

It is applicable as Re < 1500

Huang C.H. and Tsai C.J.,
2002ausing the elliptical concave
impaction plate

It is applicable for round-nozzle impactor

Kim Y.J. and Yook S.J., 2011

gravitation force assistance

It is applicable as Re < 1500

Huang C.H. and Tsai C.J.,
2001

reducing the pressure by using
high jet velocities

Evaporation of semi-volatile compounds Chen S.C. et al., 2007;
Arffman A. et al., 2011

reducing the nozzle throat
lengthT/W ≤ 1.0. It is just applicable for low
pressure impactors

Arffman A. et al., 2011using an additional punched
impaction plate

It is a complicated configuration

Cheon T.W. et al., 2017using horizontal inlet withrectangular-slit-nozzle

It is a complicated configuration

Kim M.K. et al., 2014

increasing the number ofnozzles

W should be ≥ 0.04 cm to lower fabrication cost

Chien C.L. et al., 2015

using rectangular nozzles

The less sharp collection efficiency
curve was foundKim M.K. et al., 2014

Kang M. et al., 2015; Chen M. et al., 2016). It was reported that liquid and liquid-coated particles were collected with an efficiency of nearly 100 %, while thecollection efficiency of solid particles could be as low as
20 % (Matthew B.M. et al., 2008).
To increase the adhesion energy and minimize the solid
particle bounce, the impaction plate is usually coated withvacuum grease, vacuum oil or silicone oil (Turner J.R.
and Hering S.V., 1987), covered by a glass-fiber filter(GFF) saturated in water (Dunbar C. et al., 2005), or
soaked in vacuum oil (Vanderpool R.W. et al., 2007). Useof rough impaction plates (Marjamäki M. and KeskinenJ., 2004), porous substrate (Huang C.H. et al., 2001;
Huang C.H. and Tsai C.J., 2003; Huang C.H. et al., 2005),
or specially designed impaction plate (Kim Y.J. and Yook
S.J., 2011; Kim W.G. et al., 2013) can also reduce particle
bounce. For the coated substrate, the type and the thickness of the coating material also affect the particle

bounce. If the coating materials interfere with chemical
analysis (Wang L. et al., 2005; Fujitani Y. et al., 2006), an
uncoated impaction surface is preferred (Kang M. et al.,2015). In addition, the relative humidity of incoming
aerosols conditioned to a higher value (> 70 %) can minimize particle bounce, due to the increase in the adhesionenergy by capillary force between adsorbed water on theparticle and the impaction plate (Chen S.C. et al., 2011;
Bateman A.P. et al., 2013).

2.1.3 Particle loading effectAlthough the coating materials help to reduce the particle bounce effectively, the particle loading effect occurs
when too many particles are collected on the impaction
substrate after a long sampling period (Fig. 1c). When thegrease-coated impaction plate is loaded heavily with particles, the incident particles strike on previously depositedsolid particles rather than the coated plate, resulting in

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possible particle bounce (Tsai C.J. and Cheng Y.H., 1995).
Moreover, the particle blow-off problem may take placewhen heavily loaded particles are swept away from thesubstrate by high-velocity jet flow.
Therefore, the net effects of substrate overloading are
similar to particle bounce: lower collection efficiencies forparticle larger than the cut-size and the shift of the measured size distribution toward the smaller particle sizes(Tsai C.J. et al., 2012b). The problem of particle overloading can be overcome by reducing the sampling time since
it affects the amount of particles collected. Many methods
have been proposed to increase the particle loading
capacity on the impaction substrate to extend the sampling period, including the special designs of impaction
plates (Tsai C.J. and Cheng Y.H., 1995), oil-soaked filters(Peters T.M. et al., 2001), oil-coated impaction substrate(Tsai C.J. et al., 2012b), multi-hole impactor with Trypticase Soy Agar (TSA) substrate (Lai C.Y. et al., 2010) or
rotating substrates (Marple V.A. et al., 1991; Tsai C.J. etal., 2012b).
However, when the oil-coated filter substrate is used toeliminate particle bounce, the particle loading effect canstill occur since the oil, which has a lower viscosity than
the grease, wicks up through the previously depositedparticle layer by the capillary action, and eventually leads
to the pile-up of the deposited particles on the substrate.
This causes the shift of the cutoff diameter and collection
efficiency curve to the smaller sizes leading to incorrect
PM measurements (Kenny L.C. et al., 2000; Vanderpool
R.W. et al., 2001). Even with the rotating stage design in
the MOUDI (Marple V.A. et al., 1991), it is expected thatseveral tens of layers of deposited particles will appear on
the grease-coated stage for particle bounce and loading
effect to occur when the typical stage inlet aerosol massconcentration is 10–20 μg/m3 during 24-h sampling (Tsai
C.J. and Cheng Y.H., 1995). The special designs of impaction cavities and wells have better performance comparedto that of flat impaction surfaces since rebound particles
can be retained (Tsai C.J. and Cheng Y.H., 1995; Peters
T.M. et al., 2001).
An M-PM10 impactor with oil-soaked GFF substrate
supported by a porous metal disc as shown in Fig. 2 wasdesigned to avoid the particle bounce and overloading effects (Le T.C. et al., 2019). In the M-PM10 impactor, there
is a 1-mm layer of oil remaining on the top of the substrate and the pores of the porous metal disc are filledwith vacuum oil to enhance the loading capacity. With
these improvements, the modified PM10 impactor showed
a good sampling performance with a bias of less than
± 10 % during 30 sampling days. Based on the concept ofwater-saturated GFF substrate of Dunbar C. et al. (2005)
and impaction well (Peters T.M. et al., 2001), a PM2.5 impactor with the water-wetted GFF substrate modified
from the WINS was developed by our group as shown in48

Fig. 2 Schematic diagram of the M-PM10 impactor (Le T.C. et al.,2019).

Fig. 3 Schematic diagram of the M-WINS (Le T.C. and Tsai C.J.,
2017).

Fig. 3. This impactor design not only can eliminate theparticle bounce by using the water-wetted GFF impaction
substrate but also avoid the particle overloading effect byinjecting a small amount of water upward to wash the deposited particles off the impaction surface continuously(Le T.C. and Tsai C.J., 2017). Instead of using water, the
M-WINS can inject vacuum oil periodically to wash offparticles to save oil consumption. Washing impaction
substrate to eliminate particle bounce and particle overloading effects can be applied to different types of impactors as well.

2.1.4 Particle loss effectParticle loss is another limitation of inertial impactors(Fig. 1d). Instead of being collected on the impaction
substrate, particles can also deposit on the inner walls of
the impactor, including the nozzle and the casing, leading
to the underestimation of the collection efficiency and the
distortion of the measured mass distribution. Large particles can be lost by impaction while nanoparticles can beThi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63

lost by convention-diffusion. The losses may vary withparticle properties. If particles are liquid or sticky, they
will adhere to any surface upon contact with it. Some ofdry particles, however, may rebound when they hit thesurface and remain airborne. Experimental and theoretical studies have been conducted for determining the particle losses by impaction and diffusion (Chen S.C. et al.,2007). The inertial loss of large particles normally occurs
on the contractions which connect the big inlet tube to thesmall nozzle or on the surface of nozzle plate (Durand T.
et al., 2014; Kumar A. and Gupta T., 2015a, 2015b).
Another particle loss in the cascade impactor is theinter-stage particle loss, which occurs in the inter-stage
space above the intended stage to collect particles. Theinter-stage loss is due to turbulent particle deposition
when they pass through sharp corners or obstructions between two adjacent stages (Marple V.A. et al., 1991). Typically, significant particle loss occurs in the lower stagesof the cascade impactors due to diffusion-convention(Demokritou P. et al., 2002b; Watson J.G. and Chow J.C.,
2011). The NMCI with smooth nozzles could minimize
the convection-diffusion particle deposition in the nozzle(Liu C.N. et al., 2013b). In another study, 80 % of particle
loss was found to concentrate around the nozzles and
20 % on the impaction plate in a stage of the DLPI
(Dekati® Low-Pressure Impactor) (Durand T. et al., 2014).
Some conventional impactors were designed by changing the geometry of the impactor to enhance the collection efficiency to obtain a lower cut-size, including using
the horizontal inlet to concentrate particles in the central
axis of nozzle (Kim M.K. et al., 2014; Kim W.G. et al.,2014; Heo J.E. et al., 2018), using an additional punched
impaction plate installed between the nozzle outlet andimpaction plate (Cheon T.W. et al., 2017), and the combination of the impactor and the initial filter to achieve a
sharp collection efficiency curve (Zhang T. et al., 2017;
Zhang X. et al., 2018). Table 3 lists the design solutions toresolve the problems of conventional impactors.

2.2 Virtual impactors
The virtual impactor is another type of inertial impactors, which consists of the nozzle(s), and the collection
probe(s) (Marple V.A. and Olson B.A., 2011). In the virtual impactor, the collection probe diameter (D), which isslightly larger than W, is used to replace the collection
plate of the conventional impactor to eliminate particle
bounce and particle overloading effects (Loo B.W., 1975).
Particles with sufficient inertia are retained in a relatively
stagnant air passing through the collection probe while
particles with less inertia follow the airflow to exit the
impactor. The minor flow (Q1) is about 5–20 % of the total air flow (Q) or the major flow (Qo) is about 80–95 % of
the total air flow (Hinds W.C., 1999).

Many studies have been conducted to examine the cutoff characteristics and the influencing parameters of thevirtual impactor of the basic design (McFarland A.R.
et al., 1978; Marple V.A. and Chien C.M., 1980; Lim K.S.
and Lee K.W., 2006). They concluded that the theoreticalcutoff characteristics of the virtual impactors are similar
to those of conventional impactors, which are mainly governed by Stk and Re (Marple V.A. and Chien C.M., 1980).
The other parameters such as collection probe/nozzle diameter ratio, nozzle length, entrance cone angle, and nozzle to collection probe distance do not have an important
effect on the collection efficiency. Although the value of
D/W does not affect the cutoff characteristic, it should beless than 1.49 to eliminate the flow field effect. The cutoff
diameter increases as the minor and major flow ratio (Q1/
Qo) decreases (McFarland A.R. et al., 1978; Marple V.A.
and Chien C.M., 1980). The virtual impactor avoids theparticle bounce effect without using the impaction plate,but an intrinsic disadvantage of the virtual impactor is thecontaminations of coarse particles in the major flow byfine particles. That is, a portion of particles less than the
cutoff diameter will remain in the minor flow or the socalled minor flow contamination. A virtual impactor with
reduced fine particle contamination was designed by confining the aerosol flow within a central core enveloped bya sheath of clean air (Chein H. and Lundgren D.A., 1993).
The opposing jets design and the introduction of a clean
air core as the envelope around the particle-laden stream
were also used to eliminate fine particle contamination.
Another major disadvantage of the virtual impactor isthe particle internal losses which affect the cutoff diameter significantly (Xu Z., 1991). Particles are normally lostat the upper edge of the collection probe or on the backside of the probe plate. The particle loss is affected by D/
W, Re, Q1/Q, the nozzle protruding through the nozzle
plate, the shape of the collection probe inlet, and thealignment of the axes of the nozzle and the collection
probe. High particle losses occur for particles having a diameter close to the cutoff point (Marple V.A. and Chien
C.M., 1980). The particle loss can be reduced by proper
contouring of the probe entrance, decreasing Re, and increasing Q1/Qo and S/W ratio (Marple V.A. and Chien
C.M., 1980). The particle loss can be reduced by increasing D/W but it may reduce the sharpness of the particle
collection efficiency curve. Certain values of the throat
length of the probe opening, the radius of the roundedshoulder of the probe opening, and the diameter of thelower surface of the nozzle required to reduce the particle
loss were suggested (Marple V.A. and Chien C.M., 1980).
It is summarized that D should be about 30–50 % larger
than W, the radius on the inside of the collection probe inlet is about 30 % of W, the nozzle should protrude two to
three times W through the nozzle plate, S should be about
1–1.8 times W, and the axes of the nozzle should be49

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Table 3 Solutions of inertial device problems.

Problems

Solutions

Pros and cons

References

Particle bounce

Using glass fiber filter
or Teflon filter as an
impaction substrate

Pros: Simple and no chemical interference
Cons: Expensive

Marple V.A. et al., 1991

Greased substrate

Pros: Easy implementer
Cons: Can’t be suitable for chemical analysis;
Particle overloading effect

Turner J.R. and Hering S.V.,
1987;
John W. et al., 1991

Oiled substrate

Pros: Cheap, high loaded mass, low viscosity, anduniform coating
Cons: Particle loading effect and oil evaporation

Turner J.R. and Hering S.V.,
1987;
Peters T.M. et al., 2001;
Le T.C. et al., 2019

Porous metal substrate

Pros: No chemical interference
Cons: The shift of the collection efficiency curveand cutoff diameter; Less sharp curve

Huang C.H. et al., 2001;
Huang C.H. and Tsai C.J.,
2002b; 2003

Foam substrate

Pros: No chemical interference
Cons: The shift of the collection efficiency curveand cutoff diameter; Less sharp curve

Huang C.H. et al., 2005

Water substrate andwater washing

Pros: No chemical interference; Can be used tocollect samples for chemical analysis; Long-term
use
Cons: Pumps are needed to inject and drain water

Dunbar C. et al., 2005;
Le T.C. and Tsai C.J., 2017

Cavity-type impaction
substrate

Pros: No energy, solutions or materials are needed
Cons: The curve is not very sharp

Tsai C.J. and Cheng Y.H., 1995

Elliptical concave
impaction plate

Pros: No chemical interference
Cons: The determination of dimensions is needed;
It just helps trap some re-bound particles

Kim W.G. et al., 2013

Cup impactor

Pros: No chemical interference
Cons: Special design; The cut-size can’t be predicted

Kim D.S. et al., 2006

Using virtual impactor

Pros: Two size fractions
Cons: Fine particle contamination; High particle
loss near the cut-size.

McFarland A.R. et al., 1978;
Marple V.A. and Chien C.M.,
1980

Oiled substrate

Pros: Cheap and high loaded mass
Cons: Short-term use and oil evaporation

Turner J.R. and Hering S.V.,
1987

Porous metal substrate

Pros: High loaded mass
Cons: The shift of the collection efficiency curveand cutoff diameter; Less sharp curve

Huang C.H. et al., 2001

Continuous water
washing

Pros: Long-term use without frequent maintenance Le T.C. and Tsai C.J., 2017
Cons: Pumps are needed to inject and drain water

Rotated impaction plate

Pros: Long-term use
Cons: A motor is needed; Coated substrate;
Complicated configuration

Marple V.A. et al., 1991;
Tsai C.J. et al., 2012b

Horizontal inlet invirtual impactor

Pros: High collection efficiency
Cons: Complicated configuration

Heo J.E. et al., 2018

Smooth nozzles

Pros: No particle clogging
Cons: Need special technique to fabricate microsize nozzles

Fang C. et al., 1991;
Liu C.N. et al., 2013b;
Chien C.L. et al., 2015

The symmetricalarrangement of nozzles

Pros: Uniform deposition
Cons: Not enough study

Kwon H.B. et al., 2018

Particle overloading

Particle loss

Multiple-jet
interaction50Thi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63

aligned closely to that of the collection probe (Hinds
W.C., 1999).
Some special designs of the virtual impactor to eliminate particle loss and improve the collection efficiency
were developed. This includes the slit virtual impactor assembled with an orifice installed upstream of the acceleration nozzle to concentrate the minor flow at the center ofthe collection probe (Lim K.S. and Lee K.W., 2006; Lee
H. et al., 2014) or the impactor with three-partitioned horizontal inlet (Zahir M.Z. et al., 2018). The virtual impactor with an ultrafine cutoff diameter at a moderatepressure drop was developed by using a very small roundnozzle and at a low flow rate (Sioutas C. et al., 1994b) or
slit nozzles to operate at a high flow rate (Sioutas C. et al.,1994a).
Since it is hard to control both minor and major flows,
the virtual impactor is usually designed as a single-stage
virtual impactor. The multi-stage virtual impactor to collect particles in different size ranges simultaneously wasstudied (Marple V.A. et al., 2013, 2014a; Wada M. et al.,2017). To increase the flow rate to 1000 L/min, the use ofmulti-nozzle virtual impactors was also designed to reduce the pressure drop (Szymanski W.W. and Liu B.Y.,
1989). It is noticed that the multi-nozzle virtual impactor
may have multiple jet interaction problem leading to thedegradation of the impactor’s performance (Fang C. et al.,1991). The virtual impactor with the rectangular nozzle
can increase the flow rate without changing the cut-size ascompared to the single round-nozzle virtual impactor(Masuda H. and Nakasita S., 1988). A slit-shaped nozzle
virtual impactor in which the width of the slit is the samewith the diameter of the round nozzle was developed toovercome the crossflow interaction problems of the multiple jets at a high flow rate (Ding Y. and Koutrakis P.,
2000).

3. Application of inertial impactors

and ultrafine particles (Chen S.C. et al., 2010a; Chen S.C.
et al., 2010b), long-term measurement for PM2.5 and ultrafine particles mass concentrations (Lin G.Y. et al., 2015),
and the measurement of PM10, PM2.5 and PM0.1 for source
characterization and apportionment (Gugamsetty B. et al.,2012).

3.1 PM mass measurement
In order to measure the ambient PM mass concentration to determine the compliance with NAAQS for PM10
and PM2.5, respectively, the PM FRM (Federal Reference
Method) samplers and FEM (Federal Equivalent Method)monitors are used (U.S.EPA, 2017a; Le T.C. et al., 2020).
The FRM samplers and FEM monitors use size-selective
inlets to classify the desired particle sizes for collecting
on the filter for further analysis. Due to the sharp cutoff
characteristics of the inertial impactors, they are widely
deployed for the size-selective inlets. The PM10 and PM2.5
size-selective inlets are designed based on the U.S. EPA
requirements for the cutoff diameter, the sharpness of thecollection efficiency curve, the flow rate, and the accuracy
for long-term sampling. A list of PM10 and PM2.5 sizeselective inlets including the conventional impactor andvirtual impactor is shown in Table 26.1 in Watson J.G.
and Chow J.C. (2011) and is not repeated here. U.S. EPA
designated that the PM10 size-selective inlets should havethe cut-size of 10 ± 0.5 μm and the sharpness of the sampling efficiency curve of 1.5 ± 0.1 (U.S.EPA, 2017a) and
the PM2.5 size-selective inlets should have the cut-size of
2.5 ± 0.2 μm but the curve sharpness is not specified. The
sharpness curve of the PM2.5 inlet needs to agree withthat of the WINS (GSD = 1.18) (Peters T.M. et al., 2001)
and very sharp-cut cyclone (VSCC, GSD = 1.16) (Kenny
L.C. et al., 2004), which are the standard inlets specified
in U.S.EPA (2017a). Other countries specified the curve
sharpness of 1.2 ± 0.1 (MEPC, 2013; ECS, 2014).

3.1.1 The inlet for a single size fraction
The development of the inertial impactor is in line with
the need to develop PM measurement devices. PM measurement serves various purpose such as (i) the determination of PM10 or PM2.5 concentrations to determine thecompliance with the national ambient air quality standard(NAAQS), (ii) the determination of particle mass distribution, (iii) the determination of physical and chemical
properties of particles, and (iv) the exposure assessmentof PMs. Many studies were carried out by our group for
ambient mass measurement of PM2.5 and ultrafine particles using commercial inertial impactors for PM2.5 massconcentration measurement and the evaluation of the performance of PM2.5 monitors (Liu C.N. et al., 2013a), themeasurement of mass concentration and chemical composition of PM2.5 (Liu C.N. et al., 2014; Liu C.N. et al., 2015)

The conventional impactors are used extensively as an
inlet to classify a single size fraction since they have
sharper cutoff characteristics than that of the cyclone,which include AMI (Airmetrics) MiniVol™ impactors(AMI, 2020), Harvard sharp-cut impactors (Turner W.A.
et al., 2000), Hi-vol PM10 samplers (McFarland A.R. et al.,1984), Med-vol (Medium volume) PM10 samplers (Olin
J.G. and Bohn R.R., 1983), Flat Top Dichot PM10 inlet(McFarland A.R. et al., 1978), BGI FRM Louvered PM10
samplers (Tolocka M.P. et al., 2001), and EPA WINS
PM2.5 inlet (Peters T.M. et al., 2001). These inlets are different in the sampling flow rate, cutoff diameter, and sampling curve sharpness. The Hi-vol PM10 sampler is widelyused for sample PM10 with a high flow rate of 1133 L/min(Fujitani Y. et al., 2017). The impaction plate of the Hi-vol51

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PM10 sampler was suggested to be grease-coated to eliminate the particle bounce and re-entrainment to avoid PM10
overestimation as compared to other samplers (Lee S.J.
et al., 2005). A slight difference in the cutoff characteristicof the PM10 inlet can cause a sensible difference in PM10
measurements between different PM10 inlets since themode of many ambient mass-size distributions is nearly
10 μm (Ranade M.B. et al., 1990). The Med-vol PM10
sampler is the one used for sampling PM10 at the medium
flow rate of 113 L/min (Gertler A.W. et al., 1993) but is not
deployed widely. Some other impactors have been designed to operate at high flow rates that exceed hundredsof liters per minute (Misra C. et al., 2002) and even thousands of liters per minute (Fulghum M.R. et al., 2012;
Staymates M. et al., 2013) to collect more mass of PM10,
PM2.5, PM1 or PM0.1.
Nowadays, many FRM samplers and FEM monitors
use low-volume flat-topped (McFarland A.R. et al., 1984)
and louvered PM10 inlets (Tolocka M.P. et al., 2001) toclassify particles smaller than 10 μm at the low flow rateof 16.7 L/min (U.S.EPA, 2017b). However, several studies
found that the low-volume PM10 inlet has uncertainty inthe measured sampling efficiency. These studies foundthat the sampling performance of PM10 inlet is very sensitive to variation of particle sources (Wang L. et al., 2005),
particle size distribution (Buser M.D. et al., 2008), and
TSP/PM10 ratio (Total suspended particulates) (Watson
J.G. et al., 2011). The low-volume PM10 sampler overestimated PM10 when it was used to measure fly ash particles
as compared to the Andersen cascade impactor (Park J.M.
et al., 2009). When the particle source is dominant by
particles larger than the cut-size, a small fraction of particles larger than the cut-size may cause the overestimation(Faulkner W.B. et al., 2014). In the previous study, we
found that the distortion of the sampling performance ofthe low-volume PM10 sampler could be due to particle
bounce and re-entrainment from the uncoated surface of
the PM10 inlet, and particle overloading of the PM10 impactor after a long sampling period, resulting inover-measurement and under-measurement, respectively.
Thus, the PM10 inlet was required to be cleaned every day
to eliminate these effects. Similarly, most of FRM samplers and FEM monitors (16.7 L/min) using PM2.5 WINS
as the PM2.5 inlet (U.S.EPA, 2017b), whose impaction
well have to be replaced after 3–5 days sampling to eliminate the particle overloading problems (Le T.C. and Tsai
C.J., 2017). The M-PM10 inlet and PM2.5 M-WINS inlet
developed by our group were tested for one month without frequent cleaning and maintenance. They can be used
to replace the traditional PM10 inlets and PM2.5 WINS inlet for PM sampling.
The MiniVol impactor with the flow rate of 5 L/min isalso used to determine the mass and chemical composition of fine particles (Du W. et al., 2017; Fan Z.L. et al.,52

2017; Thuy N.T.T. et al., 2018) or used as the reference forcalibration (Begum B.A. and Hopke P.K., 2019). However,the previous studies showed that the MiniVol data did notagree well with the other collocated samplers and monitors (Kingham S. et al., 2006). This could be due to theparticle bounce and particle loading effect. The impaction
plate of the MiniVol impactor needs to be cleaned and recoated grease after 5 sampling days or more often if overloading is observed to recovery the good performance(AMI, 2020). The mini-volume (4 L/min) or low-volume(10–20 L/min) Harvard sharp-cut impactors with different
cut-sizes of 10, 2.5 and 1.0 μm, which use the oil-coatedimpaction substrate to eliminate the particle bounce effect, were mainly used for indoor measurement and outdoor field tests (Rovelli S. et al., 2017).

3.1.2 The inlet for two size fractions
To determine the compliance with NAAQS, it is often
desirable to fractionate particles into two size fractions
simultaneously, one corresponding to the coarse particle
mode (> 2.5 μm) and one corresponding to the fine particle mode (≤ 2.5 μm). The virtual impactor is very suitable
for this application (Lin G.Y. et al., 2015; Landis M.S. etal., 2017). The Andersen Dichotomous Virtual impactor(McFarland A.R. et al., 1978) is the most widely used forcollecting coarse and fine particles at a low flow rate of
16.7 L/min (Gugamsetty B. et al., 2012). Other types ofvirtual impactors were developed and deployed for specific measurement purposes. For instance, the PM1.0/2.5/10
trichotomous sampler (cascade virtual impactor) with thehigh sampling flow rate of 1133 L/min was developed tomeasure the mass and the ion concentrations of PM at
Phoenix, Arizona, USA (Marple V.A. et al., 2013, 2014a).

3.2 Particle mass distribution measurement
The determination of the mass concentration of theparticles less than a certain size is valuable but it is desirable to determine the mass distribution of entire aerosol
particles. In this case, the cascade impactor can be deployed to cover a very wide particle size range from a few
nanometers to tens of micrometers (Marple V.A. et al.,
1991; Fernandez de la Mora J. and Schmidt-Ott A., 1993;
Arffman A. et al., 2015). It is desirable to have a cascade
impactor for particle mass distribution measurement witha wide range of flow rates, a large range of particle sizes,
a good size resolution (or number of channels), low pressure drop, uniform particle collection, less inter-stage
loss, no particle bounce, high loaded mass, and easy assembly and disassembly of the stages (Marple V.A.,
2004). The list of the commercially available cascade impactors is shown in Table 8-1 in Marple V.A. and Olson
B.A. (2011). Some commonly used cascade impactors areAndersen cascade impactor (Andersen A.A., 1966), Mer-

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cer cascade impactor (Mercer T.T. et al., 1970), Quartz
Crystal Microbalance (QCM) cascade impactor (Hering
S.V., 1987), Pilat cascade impactor (Pilat M.J. et al., 1970),
Berner low-pressure cascade impactor (Berner A., 1972),
Low-Pressure Impactor (Berner A., 1972), Dekati®
Low-Pressure Impactor (DLPI) (Durand T. et al., 2014),
MOUDI (Marple V.A. et al., 1991; Marple V.A. et al.,2014b) and NMCI (Liu C.N. et al., 2013b; Chien C.L.
et al., 2015).
The most widely used cascade impactor for determining particle mass distribution is MOUDI, which measuresmass concentrations in ten size fractions down to
nano-size particles with a moderate pressure drop(Dpa50 = 10, 5.6, 3.2, 1.8, 1.0, 0.56, 0.32, 0.18, 0.10, and0.056 μm) at the medium flow rate of 30 L/min (Marple
V.A. et al., 2014b). In the MOUDI, particles with different
size ranges are collected on the well-prepared substrates
such as oil-coated aluminum foil or Teflon filter to determine the mass concentration distribution. An advantageof the MOUDI is that it can collect particles uniformly on
the substrate by using multiple nozzles and rotating impaction plates and/or nozzle plates. The impaction substrates can either be Teflon filters for mass determinationand chemical composition or grease-coated aluminum foil
for mass concentration only without significant particle
bounce effect. The MOUDI coupled with nano-MOUDI
or 10 L/min MOUDI-II was further developed to havehigher resolution for nanoparticles with three additional
stages (Dpa50 = 0.010, 0.018 and 0.032 μm) after the 10thstage (Dpa50 = 0.56 μm) (Marple V.A. and Olson B.A.,
1999). The MOUDI-II is used for size-fractionated measurement of mass concentration, chemical composition,and morphology of ambient ultrafine particles. The
MOUDI-II needs a long sampling time to collect enoughNP mass to measure their mass concentrations and chemical compositions accurately. Our group studied the performance of the MOUDI and found that the nozzles of
7th–10th stages of the MOUDI are clogged easily due tothe stepwise structure with abrupt contractions. The nozzle plates are not suitable for ultrasonic cleaning to remove particle deposits due to their thin and fragile
structure (Liu C.N. et al., 2013b). Therefore, the NMCI
with a smooth nozzle shape was developed to eliminate
the clogging problems (Liu C.N. et al., 2013b).
Due to the need for the automatic measurement of particle mass distribution, several cascade impactors havebeen developed and commercialized. The requirement of
the real-time measurement is the sensitivity for low particle concentration detection and short response time. The
ten-stage QCM cascade impactor, in which piezo-electric
quartz crystals sensors are flush-mounted on the impaction plates, was developed earlier (Chuan R.L., 1970). In
the QCM cascade impactor, the mass concentrations arecalculated based on the difference in the frequencies of

the QCMs before and after particle impaction on thepiezoelectric crystal (Chen M. et al., 2016). The previous
studies showed that the QCM cascade impactor has theparticle bounce effect (Hering S.V., 1987), high particle
loss of up to 50 %, low off-center sensitivity, and low sensitivity of nanoparticle concentrations (Keskinen J. et al.,1992). A novel QCM cascade impactor was developed toovercome these problems, in which the RH controller wasused to control the RH of incoming aerosol to between
40 % and 65 % to eliminate the particle bounce effect andensure particle coupling with the QCM, and the impedance measurement was used to achieve nanogram mass
resolution (Chen M. et al., 2016).
The Electrical Low-Pressure Impactor (ELPI) developed by Keskinen J. et al. (1992) can be used to detect the
number concentration distribution in real-time. The ELPI
consists of a unipolar charger followed by a cascade impactor coupled with multichannel electrometers. Particles
are first charged unipolarly when they pass through the
charger and then collected on the electrically isolated impaction plates in the cascade impactor. The current ofeach stage is read by a corresponding electrometer channel and converted to particle number concentration. Numerous studies have been conducted to calibrate andimprove the performance of the ELPI. The latest ELPI(Dekati® ELPI®+) was developed to measure particle
number distribution with very high size resolution (13channels), wide particle size range (from 6 nm to 10 μm),
and fast response (seconds) (Järvinen A. et al., 2014). It
should be noticed that the performance of the ELPI can beaffected by the charging efficiency which depends on particle size and concentration and is influenced by the agingof the charger (Järvinen A. et al., 2014). The electrical
low-pressure cascade impactor was developed further forachieving higher resolution with 100 or 500 size fractions(i.e. HR-ELPI+) (Saari S. et al., 2018) or measuring
nanoparticle mass concentration using a wire-to-rode corona charger to eliminate the new particle formation
which may occur in the pin-to-plate corona charger (HanJ. et al., 2018).

3.3 Personal exposure measurement
Personal exposure measurement of PM is to assess the
PM exposure of individual workers in workplaces or microenvironments where they spend most of their time
daily (Marple V.A. and Olson B.A., 2011). The personal
exposure measurement depends on the pollutant concentration and exposure time. Comparison to the inertial impactors used for PM sampling, the inertial impactors
which are used for personal exposure measurement havespecific requirements. The devices have to be light, small,portable, self-contained and battery-powered to moveeasily from one location to another and are placed near53

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the personal breathing zone, which is about 30 cm hemisphere around mouth and nose (Asbach C. et al., 2017).
These devices need to collect an adequate amount of particle mass with a uniform deposit on the substrate for subsequent PM mass concentration, chemical composition,
morphological, and crystallographic analyses manually.
The personal exposure devices are listed in Volkwein J.C.
et al. (2011) for workplaces and in Rodes C.E. (2011) for
non-occupational microenvironments. Personal exposure
impactors measure PM10, PM 2.5, and PM1.0, inhalable(Dpa50 = 100 μm, thoracic (Dpa50 = 10 μm), and respirable(Dpa50 = 4 μm) particles regulated by the National Institutefor Occupational Safety and Health (NIOSH), International Organization for Standardization (ISO), and Comite’ European de Normalisation (CEN) (Volkwein J.C. etal., 2011).
To meet the respirable aerosol sampling criteria, the inertial impactors are designed to have a less sharp efficiency curve (Volkwein J.C. et al., 2011). Personal
single-stage impactor (Tsai C.J. et al., 2012b), two-stage
impactor (Demokritou P. et al., 2001), three-stage personal impactor (Tsai C.J. et al., 2008), and cascade impactor (Chen M. et al., 2018) and multipollutant samplers
were developed for personal exposure measurement since
1970s and some which were widely used. These include
Marple personal impactor, personal environmental monitor (PEM), mini-MOUDI, parallel particle impactor, personal modular impactor, Sioutas cascade impactor,
personal PUF pesticide sampler, and personal impactor
filter pack (Marple V.A. and Olson B.A., 2011). The
Marple personal impactor with 8 stages at the flow rate of
2 L/min and Sioutas cascade impactor at the flow rate of
9 L/min are the most frequently used samplers for mass
distribution measurement (Tsai C.J. et al., 1997b; Sharma
R. and Balasubramanian R., 2018).
The personal exposure measurement for nanoparticles
has drawn serious concern due to the adverse health effectof nanoparticles released from nanopowders and nanomaterial manufacturing processes. Nanopowders such as
TiO2, SiO2, and ZnO are released to the workplaces depending on their dustiness or the property of a given material to generate dust (Tsai C.J. et al., 2009; Tsai C.J. etal., 2011). Some studies were carried out by our group(Tsai C.J. et al., 2011; Tsai C.J. et al., 2012a) to determine
the generation and dispersion characteristics of nanoparticles.
Some commercialized personal cascade impactors canbe used for the nanoparticle exposure measurement suchas mini-MOUDI (13 stages with particle sizes ranging
from 10 nm to 10 μm) operating at the flow rate of 2 L/
min and Sioutas cascade impactor (4 stages with particle
sizes ranging from 0.25 to 2.5 μm) operating at the flowrate of 9 L/min (Asbach C. et al., 2017). Due to the highpressure drop that is needed to classify nanoparticles,

54

only a few of personal exposure samplers were developed
to collect nanoparticles. Besides, the nanoparticle samplers need to operate for a long sampling period to collectenough mass for further gravimetric analysis since
nanoparticle mass is very small. The personal cascade
impactors using inertial filters for nanoparticle collection
were developed with a moderate pressu re d rop(< 5–10 kPa) (Kumsanlas N. et al., 2019) which is basedon the design of inertial filter (Zhang T. et al., 2017).
Our group developed the PENS, which can be used tocollect respirable particles and nanoparticles simultaneously by using a cyclone as a pre-separator to remove particles larger than 4 μm and a micro-orifice impactor with
the Dpa50 of 101.4 nm followed by the filter cassette (Tsai
C.J. et al., 2012b). The PENS eliminated the particle
bounce and overloading effects by using a rotating, silicone oil-coated Teflon filter as the substrate. The PENS
operates at a low flow rate of 2 L/min and slightly highpressure drop (< 14–15 kPa), which is still acceptable fora personal sampling pump of 21 kPa (AirChek XR5000,
USA). The PENS are used for NP mass concertation measurement in workplaces (Young L.H. et al., 2013; Asbach
C. et al., 2017) and ambient air as well (Zhu C.S. et al.,2016; Zhu C.S. et al., 2017). The field comparison test of
the PENS with the collocated SKC respirable dust aluminum cyclone (SKC Inc., PA, USA) and sequential mobility
particle sizer (SMPS; GRIMM Aerosol Technik, Gmbh,
Germany, Model 5.500) in metal working places showedthat the PENS correlated well with the cyclone for PM4
and SMPS for PN0.1 (Young L.H. et al., 2013). The aspiration efficiency of the PENS was good and agreed wellwith that of NIOSH two-stage personal bioaerosol samplers (Zhou Y. et al., 2014).
The PENS is currently being studied further to enhance
its performance at a higher flow rate of 3–5 L/min and alower pressure drop of < 15 kPa. To achieve the same cutsize of lower than 100 nm at the higher flow rate andlower pressure drop, the PENS can be re-designed withmore nozzles with larger diameter and smaller S/W. The
wetted GFF substrate can be used in the PENS to wash
off deposited particles continuously to achieve a longsampling period without particle bounce and overloading
effects (Le T.C. and Tsai C.J., 2017).

3.4 PM control
Control of PM emission is critical to reduce airborne
PM concentration and health risks. Major particle control
devices include wet scrubber, electrostatic precipitators(ESPs), cyclones, and baghouses, each of which has theadvantages and disadvantages in the application. The wet
scrubbers remove particles by using water spray or water
film, which causes a very high operating pressure drop,
metal corrosion, and water pollution (Huang C.H. et al.,Thi-Cuc Le et al. / KONA Powder and Particle Journal No. 38 (2021) 42–63

2007; Pui D.Y.H. et al., 2014). The ESPs which use electrostatic force to remove particles have the minimum removal efficiency for particles ranging from 0.1 to 1.0 μm
due to the minimum electrical mobility in this submicrometer range (Hinds W.C., 1999; Pui D.Y.H. et al.,2014). The cyclones are used extensively for PM control
due to its simple structure, low pressure drop, and low
cost but the collection efficiency for fine particles is low(Pui D.Y.H. et al., 2014). The baghouses use fabric filters
to remove particles based on dust cake filtration with ahigh pressure drop (Hinds W.C., 1999; Pui D.Y.H. et al.,2014). Thus, the baghouses are required to be cleaned andregenerated frequently. Special materials such as electretfilters can be used to enhance the efficiency of the depth
filtration with a low pressure drop (Tien C.Y. et al., 2020).
Our group developed successfully some control devices
overcoming some drawbacks to achieve high removal efficiency for fine and ultrafine particles including a wireon-plate ESP (Li Z. et al., 2015), an efficient single-stage
wet ESP (Lin G.Y. et al., 2010), an efficient venturi scrubber system (Tsai C.J. et al., 2005; Huang C.H. et al.,2007), and a wet electrocyclone (Lin G.Y. et al., 2013).
The efficient venturi scrubber system uses a condensation
device to grow sub-micron particles to super-micron sizes
before they are removed by a traditional venturi scrubber
operating at a moderate pressure drop of 4.3 kPa (Huang
C.H. et al., 2007). The wet electrocyclone combining thecyclone with an electrostatic precipitator with wall cleaning by water film was developed to enhance the collection
efficiency for ultrafine particles for a long service period(Lin G.Y. et al., 2013). This combination technique wasreferred by other researchers (Titov A., 2015; Zhang X. etal., 2018).
The well-designed control devices can be used for PM
and NP control in industries but they are not suitable forsome circumstances such as the semiconductor industry
with the coexisting residual gases and ultrafine particles(Tsai C.J. et al., 1997a). For instance, the ESPs may cause
fire hazard or explosion. The inertial impactor is a potential device to replace the conventional control devices forremoving NPs with a smaller footprint than the wet
scrubber, a higher efficiency than the cyclone, less costly
than the ESP, and a longer service time than the baghousesince it can be designed to have ultrafine cut-sizes and canuse water/oil-wetted impaction substrate to eliminate
overloading effect without frequent maintenance. However, the impactor requires a high operating pressure drop
for NP control. This can be resolved by growing particles
by condensation method. Recently, by coupling with particle condensation growth method, the inertial impactors
were deployed to control ultrafine particles as a filterless
control method to save the cost (Pyo J. et al., 2017). Thiscondensation technique was used in the past to enlarge
ultrafine particles to submicron particles to increase thecollection efficiency of the impactor (Demokritou P. et al.,2002a). The combination of the inertial impactor with theparticle growth device has the potential for ultrafine particle removal with a high removal efficiency, small footprint, moderate pressure drop and long-term use without
frequent maintenance need.

3.5 Powder classification by inertial devices
Powder classification is different from PM samplingsince powder sources generate high mass concentration
and wide size range (0.01 to 1000 μm) (Lai W.H. et al.,2005). Powder classification is to separate powder smaller
than a certain size from the source powder to obtain desired narrow powder distributions with high precision touse in bio-medicine, electronic information, fine ceramics, food industry, and coating industry (Guo L. et al.,2007; Wang D. et al., 2014). Powder classifiers can also be
designed to classify coarse, fine, and nano-sized particles
simultaneously with precise cutoff sizes and sharp cutoff
characteristics to achieve high production rates (Liang S.,
2010). Classification by inertial/centrifugal force such as
cyclone is one of the popular methods since the cyclone
has a simple structure and cheaper to make (Yoshida H. etal., 1991; Yoshida H. et al., 2008). It is found that large
particles are repulsed or re-entrained if the inner wall of
the cyclone is not oil-coated (Yoshida H. et al., 1991), andparticles smaller than cut-size will be collected due to theturbulent eddies in hydrocyclone resulting in the so-calledfishhook effect of the powder classification efficiency
curve (i.e., the raise of curve in small particle size range)(Roldanvillasana E. et al., 1993; Lai W.H. et al., 2005). It
is to be noted that the sharpness mentioned here refers to
the ratio of Dpa75/Dpa25 (Morimoto H. and Shakouchi T.,
2003; Lai W.H. et al., 2005).
Nowadays, powder classifiers are developed to separate
nanopowder with a sharp classification efficiency (i.e.,
without contamination of coarse powders and fishhook effect) to have a uniform powder to use in ultra-conductor,
optical, thermal, electromagnetic, and biomedical fields(Morimoto H. and Shakouchi T., 2003; Wang D. et al.,2014). In comparison to the cyclones, the inertial impactors, which have sharp cutoff characteristics and accurate
cut-size, have a good potential to be used for powder classification with a narrow size range. The water/oil wetted
inertial impactor in which the impaction substrate iswashed clean by using water or oil can be used for powderclassification at a high particle loading rate without particle loading effect. Further investigation to use the impactors for power classification is worthwhile.

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4. Conclusions and future perspective

Nomenclature

The study of the inertial devices has been an interesting topic since the 1860s when the first impactor was developed to observe the relationship between the particles
and health effects due to its simple principle and structure,easy operation, and low cost. The design theory was also
developed numerically based on the critical experimental
and field tests by Marple and his co-workers. As a result,many inertial impactors were commercialized to serve as
the size-fractionators and samplers for mass concentration
measurement, mass and number distribution measurement, particle collection for chemical analysis, and healthexposu re measu rement. Nu merous st udies wereconducted to resolve the particle bounce, particle loading,and particle loss effects to improve the performance of theinertial impactors. Therefore, the inertial impactors are
deployed widely to measure a wide size range of particles
with a wide range of concentration and different particle
types.
Inertial impaction technique still attracts researchers towork on it since the application of inertial devices is diverse. The impactors can be studied further to extend thecut-size to a very small size such as nano-size, provide
real-time mass and number concentrations with very highsensitivity, fast response, and high resolution, and apply
for specific applications in medical and pharmaceuticalareas (Marple V.A., 2004). Besides sampling and measurement, the inertial impactors can potentially be used
for PM control with a lower cut-size than the cyclone, alower pressure drop than the baghouse and less costly
than the electrostatic precipitator if they are coupled withcondensation particle growth devices. The biggest challenge of the inertial impactors for the control and powderclassifications is how to scale up and extend the lifetime.
To meet these challenges, this article has reviewed andprovided the design considerations and applications of theinertial impactors for the benefit of aerosol and powdercommunities.

Cc

Slip correction factor

D

Collection probe diameter (m)DpParticle diameter (m)Dpa50

Cutoff aerodynamic diameter (m)GSD

Geometric standard deviationμDynamic air viscosity (kg·s/m 2)

ρa

Air density (kg/m3)

ρpParticle density (kg/m3)

ρp0

Unit density (1000 kg/m3)

Q

Total flow rate (L/min)

Qo

Major flow rate (L/min)

Q1

Minor flow rate (L/min)Re

Reynolds numberS

Jet-to-plate distance (m)Stk

Stokes number

Stk50

Stk for 50 % collection efficiency

T

Throat length (m)U0Air jet velocity (m/s)

W

Nozzle diameter/width (m)Acknowledgments
The authors gratefully acknowledge financial support
from the Taiwan Ministry of Science and Technology via
the contracts MOST 108-2622-8-009-012-TE5, 107-3011F-009-002- and 107-2221-E-009-004-MY3 and theHigher Education Sprout Project of the National Chiao
Tung University and Ministry of Education (MOE),
Taiwan.

56

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Authors’ Short Biographies
Thi-Cuc Le
Thi-Cuc Le received Ph.D degree in 2018 and is currently a postdoctoral fellow at theInstitute of Environmental Engineering, National Chiao Tung university (NCTU),
Taiwan. She is also a lecturer at Department of Environment, Hoa Sen University,
Vietnam. Her current research interests are air quality sampling and instrumentation, air
pollution control, and air quality management.

Chuen-Jinn Tsai
Chuen-Jinn Tsai is Chair Professor of the Institute of Environmental Engineering, National Chiao Tung University (NCTU), Taiwan. He received Ph.D. in the Particle Technology Laboratory (PTL), Mechanical Engineering Department, University of
Minnesota. His research interest is to apply aerosol technology in aerosol and air pollution sampling, monitoring and control. He received the 2006 International Aerosol Fellow (IAF) award from the IARA and 2015 Asian Aerosol Fellow from AARA torecognize his outstanding research, technical development, education and service contributions to aerosol science and technology.

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KONA Powder and Particle Journal No. 38 (2021) 64–81/https://doi.org/10.14356/kona.2021009

Reiew Paper

Drag Reduction in Turbulent Flows by Polymer
and Fiber Additives †Cristian Marchioli 1,2* and Marina Campolo 1
1
2

Department of Engineering and Architecture, University of Udine, Italy
International Center of Mechanical Sciences, Italy

Abstract
This article provides a review of the recent progress in understanding and predicting additives-induced dragreduction (DR) in turbulent wall-bounded shear flows. We focus on the reduction in friction losses by the diluteaddition of high-molecular weight polymers and/or fibers to flowing liquids. Although it has long been reasoned
that the dynamical interactions between polymers/fibers and turbulence are responsible for DR, it was not until
recently that progress was made in elucidating these interactions in detail. Advancements come largely fromnumerical simulations of viscoelastic turbulence and detailed measurements in turbulent flows of polymer/fiber
solutions. Their impact on current understanding of the mechanics and prediction of DR is discussed, andperspectives for further advancement of knowledge are provided.
Keywords: turbulence, drag reduction, polymers, fibers

1. Introduction
Over the last decades, there has been a steady increasein the number of scientific events and publications dedicated to the phenomenon of Drag Reduction (DR) in turbulent wall-bounded flows. The reduction in turbulent
friction losses by the dilute addition of high-molecularweight polymers, fibers or other types of additives (e.g.
surfactants) to flowing liquids has been extensively studied since the phenomenon was first observed over 70
years ago. One of the reasons is the huge practical importance of turbulent DR in a wide range of process engineering applications that are commonly found in the food,
pharmaceutical, and biomedical industries (Han et al.,2017; Bhambri et al., 2016; Jovanović et al., 2006). Indeed,almost all these applications, such as transport of crude
oil in pipelines (Hart, 2014) or heat transfer and exchange(Tiong et al., 2015; Fsadni et al., 2016), involve the use ofdrag-reducing additives in gas-liquid/liquid-liquid flows.
It has long been argued that DR is determined by the
dynamical interactions between additives and turbulence(see Lumley, 1969; Berman, 1978 for further details), yet
it was not until recently that progress had been made in
†

1
2

*

64

Received 9 June 2019; Accepted 2 December 2019
J-STAGE Advance published online 29 April 2020
Via delle Scienze 208, 33100 Udine, Italy
Piazza Garibaldi 18, 33100 Udine, Italy
Corresponding author: Cristian Marchioli;
E-mail: marchioli@uniud.it
TEL: +39-0432-558006 FAX: +39-0432-558027

understanding these interactions and predicting DR in
turbulent shear flows. Advancements have been grantedby the possibility to perform high-fidelity simulations ofviscoelastic turbulent flows and detailed measurements of
turbulence in dilute/semi-dilute additive solutions, mostly
via non-invasive optical techniques. Facing the applications quest for more quantitative information on DR
mechanisms, numerical and experimental techniquescharacterized by unprecedented accuracy and access into
the flow have been developed to disclose new featuresthat are peculiar of additive-induced DR phenomena. In
this review, we address precisely these phenomena, focusing on the case of polymer- and fiber-induced DR in turbulent wall-bounded shear flows. DR phenomena are
discussed in connection with current physical understanding of how polymers and/or fibers interact with the various scales of turbulence: from the small scales resolving
the flow in Lagrangian models to the large-scales ofEuler-Euler models. Since the targeted field of research isextremely vast, we will cover only the issues relevant tothe use of high-molecular weight polymers and fibers as
Drag-Reducing Agents (DRA) in processes of industrial
interest, leaving other types of additives (surfactants,
micro-bubbles and compliant coatings) and applications
out of the discussion.

2. Background: Phenomenology of DR
In this section, we will try to highlight current understanding of the microscopic interactions that occur

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Cristian Marchioli et al. / KONA Powder and Particle Journal No. 38 (2021) 64–81

between the coherent structures of the flow and the additive, which govern the macroscopic features of DR phenomena. The essential dynamical interactions were poorly
understood and remained largely unknown until faithful
direct numerical simulations (DNS) of polymer/fiberinduced DR in channel flows became feasible (Kim et al.,2008). We will discuss such interactions considering thereview by White and Mungal (2008) as the starting point
to provide an update on the advancements that have beenachieved over the last decade through numerical and experimental evidence. In their review, White and Mungal(2008) already established that DR produced by polymer
and/or fiber additives can be described phenomenologically as the outcome of dynamic interactions that takeplace between the additive and the turbulent flow. This
interaction leads to a significant modification of the nearwall turbulence structure, as demonstrated, for instance,by the LDA measurements of viscoelastic polymer solutions of Escudier et al. (2009), thus altering the nature andstrength of the coherent structures that populate this region of the flow and play a crucial role in the selfsustaining mechanism of wall turbulence. The reader isreferred to Marchioli and Soldati (2002) and Picciotto etal. (2005), and references therein for further details onthese mechanisms. A nice pictorial view of this process,as induced by rigid neutrally-buoyant fibers, was given by
Paschkewitz et al. (2004, 2005), and is shown in Fig. 1.

Fig. 1 Instantaneous visualization of near-wall vortices and wallnormal velocity contours for (a) single-phase Newtonian and (b) fiberladen channel flow. Fiber parameters: Peclet number Pe = 1000,
aspect ratio λ = 100, concentration nL3 = 18. Velocity contours areequally spaced in the range ±0.013Uc with Uc the centerline velocity.
Panel (c): Mechanism for fiber-induced DR. I. Fibers align in intervortex regions. II. Fibers generate large stresses and body forces that
oppose vortex motion. III. Vortex structures are dissipated and fibers
realign in flow direction. IV. Vortices re-emerge and cycle repeats.
Reproduced with permission from Paschkewitz et al. (2004).

Panels (a) and (b) of this figure show the effect of the fibres on the near-wall vortices, which are usually referred
to as Quasi-Streamwise Vortices (QSV) and are visualized here using iso-surfaces of the second invariant of thevelocity gradient tensor (Blackburn et al., 1996). In the fiber flow, QSVs are both larger and weaker, and the contours of the wall-normal velocity show an increase inspacing. The vortices are also spread out over a larger region in the wall-normal direction relative to the Newtonian flow. In the case of fibers, this happens because
fibers that move through the high stress regions of theflow (phase I in Fig. 1), most pronounced in regions of intense vortex activity, generate large stresses and bodyforces that oppose to vortex motion (phase II). This interaction weakens the vortices and enhances fiber alignment
in the flow direction (phase III). Upon fiber reorientation,
the reduction in local fiber stress allows the vortices to reemerge and the turbulence is sustained in a weakened
state (phase IV).
A similar phenomenology is observed in the case ofpolymer-induced DR, and is summarized in Fig. 2, takenfrom Graham (2014). This figure refers to situations inwhich the ratio of the elastic forces to the viscous forces
within the flow, parameterized by the Weissenberg number Wi (defined more precisely in the next section), are
low to moderate. In the case of Newtonian turbulence, theflow is characterized by active intervals, dominated bystrong three-dimensional, coherent vortical motions(Marchioli and Soldati, 2002), for the majority of the timeand only occasionally enters hibernation intervals. Once
Wi exceeds an onset value, indicated as Wio in the figure,these flow structures start to stretch the polymer chains.
Such stretching weakens the near-wall coherent structures, thus leading to reduction of the friction drag (regarded as the primary mechanism operating at low levelsof DR). Specifically, the polymers are stretched within the
low-speed streaks and relax as they get rolled into theFig. 2 Schematic of the stochastic cycle displayed by viscoelastic turbulent minimal channel flow at low Reynolds number (Re ∼ 3000) andmoderate Weissenberg number (Wi ∼ 25). Reproduced with permission
from Graham (2014).

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streamwise vortices. The resulting polymer force works
to loosen the vortices. As Wi further increases, polymer
stretching by turbulence becomes persistent and stresses
accumulated over time reach: The polymer chain is deformed more rapidly than it can relax, so a threshold value
beyond which the active turbulence can no longer sustain
itself is reached: Flow hibernation sets in and allows thepolymer molecules to relax again. Once the turbulence
becomes active again, the cycle repeats. Note that this
scenario implies that DR is primarily a near-wall phenomenon. Under these circumstances, a limiting state may bereached, in which turbulence must be entirely suppressednear the wall (Graham, 2014; Wang et al., 2014). The scenario just described is in accordance with several studies(see Paschkewitz et al. (2004), Dubief et al. (2004, 2005)
and Gillissen et al. (2008) among others) which revealed
that the body forces due to polymeric stresses oppose thevortical motions of the QSV that populate the buffer layerthat mediates momentum exchange between the near-wallregion and core fluid in channels and pipes.
The similarity between the phenomenological interpretations of Paschkewitz et al. (2004, 2005) and of Graham(2014) highlights the fact that polymer and fiber stresstensors show the same characteristics, at least in the low
drag reduction regime as noted by Boelens andMuthukumar (2016). In particular, because fibers cannot
store turbulent kinetic energy in their backbone, thismechanism has to be explained by viscosity effects. The
macroscopic manifestation of the mechanism just discussed is a reduced wall friction, namely a modified mean
velocity profile, a redistribution of the shear stress inside
the boundary layer and a reduction in the energy dissipation rate at length scales close to the lower end of the energy cascade yet still within the inertial range (deChaumont Quitry and Ouellette, 2016; Xi et al., 2013;
Ouellette et al., 2009).
Further evidence of the above-mentioned mechanisms
has been provided by the analysis of the effect of elasticity
on the coherent flow structures, which suggests that the
self-sustaining process of wall turbulence becomes
weaker because the additive is able to counteract both thebiaxial and uniaxial extensional flow regions around
QSVs (Roy and Larson, 2006). Above the buffer layer,
however, hairpin vortices are more prevalent than QSV.
In Newtonian flows, hairpins can regenerate to form hairpin packets that produce large amounts of streamwise kinetic energy, as well as multiple ejections resulting in
turbulent bursts and formation of new QSVs (Adrian etal., 2000). Further, hairpin vortex packets significantly
contribute to the mean Reynolds shear stress (Jodai andElsinga, 2016; Ganapathisubramani et al., 2003), which
has two parts: the coherent stress caused by non-linear interactions among individual vortices within the packet
and incoherent stress originated from velocity fluctuations

66

induced by each vortex (Lee and Sung, 2011; Adrian etal., 2000). In drag-reduced flows, the hairpins in the log
layer are weakened by the counter torques produced by
the additive (Kim et al., 2007), similarly to what happens
to QSV in the buffer layer. Kim et al. (2008) have examined the time evolution of hairpin packets interacting witha polymer conformation field, showing that the non-linear
threshold of initial vortex strength required to trigger
auto-generation of new hairpins increases as the flow viscoelasticity increases, especially in the buffer layer. In
other words, the generation of new vortices is suppressedby the polymer stresses, thereby decreasing the turbulent
drag. Similar findings were obtained by Guan et al. (2013)
and Fu et al. (2014). Guan et al. (2013) used time-resolved
particle image velocimetry to investigate the effect of
DRA on the spatial topological character of coherent vortices in wall-bounded turbulence. Although the (polymer)
additive solution was not found to affect the spatial topological shape of these vortices, a drastic decrease of theassociated fluctuating velocity and velocity derivatives inthe solution was observed. The resulting reduction of thewall friction was ascribed to the suppression of vortex occurrence and intensity. Fu et al. (2014) used particle image
velocimetry in combination with planar laser induced fluorescence to investigate DR in turbulent channel flow
upon inhomogeneous injection of polymer solution fromone channel wall. The focus of the study was polymer diffusion, which controls the local polymer concentration
and was found to be suppressed due to turbulence inhibition compared to the diffusion of a passive scalar in unladen turbulence.
Very recently, Elsnab et al. (2019) have provided newexperimental evidence of the effect of DR on the structureof turbulence in channel flow. These authors have shown
that, for the DR between 6.5 % and 26 %, several fluid
velocity statistics (e.g. the mean profile slope in the inertial sublayer or the peak value and peak position of thestreamwise r.m.s.) tend to increase with DR in a continuous and essentially linear manner, whereas the relationship between the injected polymer concentration and thelevel of DR is nonlinear. According to Elsnab et al. (2019),
a primary effect of polymer is that it limits near-wall vorticity stretching and reorientation, and thus attenuates/
delays the three-dimensionalization of the vorticity field.
This scenario is corroborated by the observed onset of theinertial layer at large-enough wall distance, as well as anincrease in the scale of the organized vortical motions,and, finally, a reduction in the overall scale separation in
the inertial range.

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3. Onset of DR, maximum DR and available
theoretical frameworks
Two features of DR due to additives have been consideredextensively in archival literature: the onset of DR and theso-called Maximum Drag Reduction (MDR) asymptote.
In this section, we will recall these features showing how
the physical mechanisms of DR and the underlying dynamical interactions between additives and turbulence
have been incorporated in suitable criteria to predict DR.
Scaling arguments and experimental data have led todevise a time criterion for polymer-induced DR in wallbounded flows (Hershey and Zakin, 1967; Lumley andKubo, 1985), which requires that for DR to occur, thepolymer relaxation time must be longer than a representastive time scale of the near-wall turbulence, i.e., Tz >  u 2 ,s τ
where Tz is the average time taken by a stretched polymer
to return to a coiled configuration, μs and ρs are the viscosity and the density of the solution, and u τ =  w / sis the wall friction velocity, with τw the wall shear stress.
For a flexible linear polymer in solution, the relaxation
time can be expressed as Tz ∼() , where N is thes N 3/5ak BT

3number of repeating monomers in the polymer molecule,a is length of a single monomer (the repeat unit fromwhich a polymer is built), kB is the Boltzmann constant,and T is the solution temperature (Flory, 1953). According
to the classical formulation of the time criterion, onset of
DR occurs when the ratio of the polymer timescale to thetimescale of the near-wall turbulence, defined as the wallshear Weissenberg number Wiτ =Tz su τ2, is of order unity.
s

Whenever this condition is met, the polymer molecule
undergoes the so-called coil-stretch transition (Somani etal., 2010): Molecules become abruptly stretched and theelongational viscosity increases, up to several orders ofmagnitude. Elongational viscosity increases preferentiallynear the wall, where the extensional strain rates are thehighest, and acts to suppress turbulent fluctuations, increase the buffer layer thickness and eventually reducewall friction (Sher and Hetsroni, 2008). The flow-induced
coil-stretch transition of high molecular weight polymers
has generally been considered to be of first order (Ghosaland Cherayil, 2018). However, there is evidence of significant slowing down in the rate at which the polymers relax
to equilibrium in the vicinity of the transition: This suggests that the transition may be more complex, since theslowing down effect is typical of a second-order transition, and characterized by a broad spectrum of conformational states (Ghosal and Cherayil, 2018).
A recent development of the time criterion for DR has
been put forth by Boelens and Muthukumar (2016), whoinvestigated numerically the drag-reducing mechanism inthe onset regime for both flexible polymers and rigid fi-

bers. Based on the similarity of the polymer and fiber
stress tensors in turbulent flow, these authors infer that acommon drag-reducing mechanism exists, and suggestthat it must be associated with a viscous effect. In particular, they find that all terms in the stress tensor are negligible, except the off-diagonal terms associated with rotation:
Therefore, DR arises from rotational motion of fibers andpartially stretched flexible chains. Based on these observations, the rotational orientation time is proposed as theunifying time scale to characterize DR by both types ofadditive. This time scale can be defined as τr = KVrμs/kBT,
where K is a proportionality constant including terms related to the shape and the volume of the rotating molecule,and Vr is the free space per molecule. The rotational orientation time of rod-like macromolecules can be obtained
either directly by dielectric measurements or by relaxationof dichroism, or indirectly by viscoelastic measurements(Boelens and Muthukumar, 2016).
The time criterion for DR is generally confirmed bynumerical and experimental data, yet the omission ofpolymer concentration represents a serious limit to theapplication of the criterion for predictive purposes. Indeed, several works in which mono-disperse polymers
characterized by a single value of TZ (instead of a distribution of TZ as found for poly-disperse polymers) havedemonstrated that the onset of DR depends systematicallyon polymer type and concentration (Campolo et al., 2015;
Yang and Ding, 2013). The contribution of concentrationin determining the onset of DR has been accounted for in
the context of the so-called elastic theory developed by
De Gennes and co-workers (Tabor and De Gennes, 1986;de Gennes, 1990) based on the elastic behaviour of
stretched polymers. According to this theory, DR by coilstretch transition occurs when the elastic energy stored by
the partially-stretched polymers, which increases with decreasing length scale of turbulence (i.e. increased stretching characteristic of turbulence dynamics), becomescomparable to the energy of the turbulent flow, which decreases with the scale size. When this situation occurs,
the elastic energy interferes with the turbulent cascademechanism preventing it to proceed all the way to the
Kolmogorov scale (Xi et al., 2013). This can lead to buffer
layer thickening and reduced drag. Experimental measurements by Ouellette et al. (Ouellette et al., 2009; deChaumont Quitry and Ouellette, 2016), who studied theeffect of long-chain polymers on the Eulerian structure
functions in a turbulent von Kàrman swirling flow, support this framework as they indicate that the introductionof polymers into the flow modifies the energy cascade by
extracting turbulent kinetic energy from the flow and partially dissipating it directly (Valente et al., 2014). As a result, the rates of energy injection, transfer and dissipation
for the turbulence are no longer all equal, as they must be
in Newtonian turbulence where viscosity provides the67

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Cristian Marchioli et al. / KONA Powder and Particle Journal No. 38 (2021) 64–81

Fig. 3 Schematic representation of the elastic theory for the onset of
DR. Panel (a) shows the time scales in homogeneous turbulence, including the onset length scale r*. The 2/3 power law is valid for scales
larger than the Kolmogorov scale η, L being the largest flow scale.
Panel (b) sketches the condition for which the scale r** can be determined, namely when the turbulent energy per unit volume, whichscales as r 2/3, is equal to the elastic energy per unit volume, which begins to grow at r* and scales as [λ(r)]5/2, with λ(r) = (r*/r) n the powerlaw of polymer stretching for r < r*. Reproduced with permission from
Sreenivasan and White (2000).

ergy at scale r**, which can be expressed via the energy
transfer rate per unit mass through the inertial range, ϵT.
Note that, in non-Newtonian turbulence, ϵT differs fromthe energy injection rate through the cascade and fromthe energy dissipation rate due to viscosity, since polymers can provide a non-viscous mechanism for draining
energy from the cascade (de Chaumont Quitry andOuellette, 2016). When concentration is very small, thescale r** will be smaller than the Kolmogorov scale η andthe turbulence will be unaffected by the polymer. A minimum concentration exists for which r** = η, and onset of
DR occurs. Following the onset, for a fixed value of theflow Reynolds number Re, DR initially increases withpolymer concentration but saturates beyond a certain
value. This threshold value for concentration corresponds
to the so-called Maximum Drag Reduction (MDR), whichis generally attributed to the dynamics being reduced to amarginal yet persistent state of subdued turbulent motion(Virk, 1975; Li et al., 2015; Choueiri et al., 2018). In theliterature, the MDR asymptote is found to be identical fordifferent types of polymer-solvent combinations (Calzetta,
2010). For a fixed value of polymer concentration, DR initially increases with increasing Re, following a uniqueconcentration-dependent trajectory up to a certain Re after which an abrupt change of trajectory is observed. Suchchange indicates the location at which the DR curve
merges with the MDR asymptote.
One scenario is that MDR occurs when the concentration of the polymer is high enough to allow for unstretched coils to overlap. This implies (see also
Sreenivasan and White (2000) for experimental validaGm su τ2 ⋅ Wi −1 where Gm is the elastic energytion) that =when concentration is equal to the value cm at which DR
data cross over the MDR asymptote. Since this expression
for Gm neglects the dependence on the scale r**, the following additional expression for the energy can be derived (Sreenivasan and White, 2000):

only mechanism of energy dissipation.
When the elastic theory is applied to homogeneous isotropic turbulence, one might expect that, for a given combination of the polymer and the flow and using the same
notation as in Sreenivasan and White (2000), a turbulent
length scale r* exists, whose corresponding time scale τr*matches TZ , as sketched in Fig. 3(a). This length scale canbe expressed as r* = ur*TZ , with ur* the velocity scale
1/3
 Gm 

5/6
characteristic of the scale r*. Following Kolmogorov 41(1)  u 2  Wi  Re ,
1/3


*
s

theory, such velocity scale can be expressed as u r* = (r  )1/3
u r* = (r *  ) . Polymer molecules are expected to undergo
where Reτ = uτR/ν is the shear Reynolds number of thestretching by all scales smaller than r* and to affect theflow (R being the characteristic size of the flow domain,
flow only at scales smaller than r**. The scale r** ise.g. the pipe radius in pipe flow) and β is a constant that
smaller than r* and can be determined assuming that thecan be determined upon comparison with experiments.
elastic energy per unit volume stored by the polymer
For pipe flow, the best agreement with available data isequals the turbulent energy per unit volume that can beobtained for β ≃ 1, which implies that r** near the MDR
associated to that scale, as sketched in Fig. 3(b). Anotherasymptote scales with R. The interpretation of this scaling
crucial result of the elastic theory is the relation that conis that, at the MDR asymptote, a small amount of stretchnects the elastic energy with the power law scaling ofing (characteristic of length scales of order R) will be
**
5/
2
2
)]
=
s (Tenoughr **) 2/3 to make the elastic energy of the polymer compapolymer stretching, which reads as G[ (r =su r **
2**
2/3
rable to the turbulent kinetic energy of the fluid. When=s (T r )(Sreenivasan and White, 2000), wheresu r **
G = ckT/N is the elastic energy (c being the polymer conthis condition is met, polymers cause the growth of thecentration in units of monomers per unit volume) and thebuffer layer thickness across the entire boundary layer.
quantity on the right-end side is the turbulent kinetic enIn spite of the apparently sound theoretical ground on

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which the theory is based, and despite the agreement withseveral experimental datasets, the phenomenological explanation just discussed is not able to provide a uniquebounding mechanism of MDR. First off, the theory is not
self-consistent since it assumes that, whenever stretched,polymers can drain energy from the flow but also thatthey can affect the flow only at scales r < r** < r*. This
inconsistency was addressed by Xi et al. (2013), who proposed to modify the original elastic theory framework bybalancing the rate of energy transfer rather than the energy itself. By doing so, these authors were able to identify the scale at which the additive is expected to affectthe energy cascade and use this scale to collapse their experimental DR data on a single master curve. The samemodel, referred to as energy flux-balance model, has beenassessed by de Chaumont Quirty and Ouellette (2016),
who focused on the characterization of concentration effects on the Eulerian and Lagrangian structure functions.
One example of their results is provided in Fig. 4, whichshows the compensated velocity transverse structure

Fig. 4 Panel (a): Compensated transverse velocity structure function
as a function of r/ηw, with ηw the Kolmogorov scale in flow of pure water. Panel (b): same data as in panel (a) with length rescaled by a factor
ϕ2/5, derived from the energy flux-balance model. Reproduced with permission from de Chaumont Quitry and Ouellette (2016).

function, D NN, expressed as: 3 DNN (r )  4 C r 2/3 


2

3/2

 T ,(2)

where C2 is a known scaling constant. The figure compares the compensated structure function for pure waterwith that obtained for polymer solution at varying concentration ϕ, expressed in ppm, at high Re but moderate
Wi. As ϕ increases, the structure function reaches a plateau at larger length scales and the value of this plateau isdifferent from that measured in pure water. The important
points, however, are that (1) data for different polymer
concentrations are found to collapse when curves are rescaled by the factor ϕ2/5 (see Xi et al. (2013) for further details), and (2) data collapse on two distinct curves: One
for concentrations below 5 ppm and one for concentrations above 10 ppm. Such different ϕ-dependent behaviour
was ascribed to the possible onset of interactions between
individual polymer chains, which are favoured at higher
concentrations and are more likely at small Wi (e.g. below
the range for which a sharp coil-stretch transition is observed). Based on these findings, which were observed tohold also for structure functions in the time domain, deChaumont Quitry and Ouellette (2016) concluded that theenergy flux-balance model seems to be able to capture theessential effect of polymer concentration on turbulence,even if its application should be limited to dilute solutions.
In addition, there is evidence of situations in which
MDR occurs when the Reynolds stresses are due primarily to the fluctuating stresses of the additive (see Whiteand Mungal, 2008 for further details) and situations inwhich the polymer concentration field is inhomogeneous,e.g. in injection experiments: The theory does not takesuch inhomogeneities into account. Most importantly,
however, the difficulty in predicting MDR comes fromthe fact that the flow, at the onset of MDR, does not reacha purely laminar state: Rather, turbulence is reduced (either via elastic or viscous effects or both) to a marginalstate at the edge between laminar and turbulent motion.
This may suggest the existence of a peculiar self-sustaining
transitional flow regime in which the stresses produced by
the additive play a key role and promote DR mechanismsthat are inherently different from those known for
Newtonian f luids. Indeed, very recent results from
Choueiri et al. (2018) provide evidence of a dynamical
disconnection of the asymptotic state from ordinary turbulence: These authors show that, for an appropriate
choice of parameters, additives can reduce the drag beyond the MDR limit, eliminating turbulence and giving
way to laminar flow. At higher polymer concentrations,however, the laminar state becomes unstable, resulting ina fluctuating flow with the characteristic drag of the MDR

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asymptote. At sufficiently high Reynolds numbers, suchflows are observed to be structurally different from
Newtonian turbulence albeit being characterized bystreak patterns that are similar to those resulting fromelastoinertial turbulence at Reynolds numbers well below
the threshold for Newtonian turbulence. This type of behaviour has brought to a new interpretation of MDR,
which is based on the idea that the dynamics of the flow
upon onset of MDR are driven by the elastoinertial instability for high-enough polymer concentrations (Choueiri
et al., 2018; Samanta et al. 2013). In other words, the MDR
limit and the characteristic approach towards it may beseen as the result of two states of turbulence: Newtonian
turbulence and elastoinertial turbulence. When these two
turbulent states coexist, a transition from one to the otheris observed. Based on such observations, Choueiri et al.
(2018) have proposed a state map for Reynolds number
versus polymer concentration, in which the different manifestations of turbulent flow observed for a specific typeof additive (polyacrylamide) are summarised. This map isreported in Fig. 5 and shows a number of interesting features. First, the onset of turbulence (the left lower branch
in Fig. 5) is delayed by the action of polymers. Second, as
Re is increased, turbulence sets in as localized turbulent
puffs and, subsequently, to growing turbulent slugs provided that polymer concentration remains below a certain
threshold of concentration (C < 20 ppm in Fig. 5). The
onset of puffs and slugs is delayed compared to
Newtonian fluids, and leads to mixed state which theneventually approaches MDR instead of allowing for complete relaminarization of the flow. Third, above thethreshold for concentration, fluctuations set in more uniformly in space and lack the spatial intermittent characterof the Newtonian transition scenario. For a further increase in concentration (C > 90 ppm in Fig. 5), this insta-

Fig. 5 State map for Reynolds number versus polymer concentration.
While Newtonian turbulence is controlled by the Reynolds number,elastoinertial turbulence and its instabilities are controlled by the relation between shear rate γ and concentration. Iso- γ lines are shown in
the portion of the map where elastoinertial instabilities are observed.
Reproduced with permission from Choueiri et al. (2018).

70

bility occurs at Re significantly smaller than the lowest
value for which Newtonian turbulence would be observed.
The important finding here is that, at intermediate concentrations, elastoinertial instability sets in before MDR
is reached.
The discussion made so far highlights that drag reduction may be characterized by relatively few dimensionlessgroups, notably the f low Reynolds number and theWeissenberg number. Such parameter space has been
nicely summarized by Graham (2014), and the schematic
proposed by this author is shown in Fig. 6. In this figure,Ex is the extensibility number, representing the maximum
value of the ratio between the extensional stress due to thepolymer and the extensional stress due to the solvent,β = μs/(μs + μp) with μs the solvent viscosity and μp the additive viscosity, while El = Wi/Re is the elasticity number(El = 0 for Newtonian flow). For a given set of experiments, Ex and β have constant value the schematic provides the DR map as a function of Re and Wi only. Eachoblique line in the figure is characterized by constant El
and represents a series of experiments at increasing flow
rate. As Re increases, transition from laminar to turbulent
flow occurs. The lowest oblique line, labeled “A”, corresponds to small El. As flow rate increases, transition toturbulence occurs first, then at some higher flow rate, Wi
becomes sufficiently large for the polymers to stretch and
DR to set in. This onset Weissenberg number, denoted as
Wio in the figure, is around 10–20. The MDR regime iseventually reached at Re much higher than those considered in the plot. The line labeled “B” corresponds tolarger El, and refers to a situation in which transition occurs at a sufficiently high Wi to prevent Newtonian turbulence: Polymer relaxation is slow enough to leave theturbulence unaffected by viscoelasticity, yet the flow rate
must still increase beyond transition to reach MDR. Theline labeled “C” corresponds to values of El large enoughto let the flow enter the MDR regime directly upon transi-

Fig. 6 Parameter space of turbulence and DR in dilute polymer solutions. Boundaries are in general fuzzy and oblique. The linear stability
limit Re = 5772 is also shown but is not relevant for the present discussion. Reproduced with permission from Graham (2014).

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tion to turbulence. Finally, the line labeled “D” corresponds to the case of elastoinertial turbulence (referred toas early turbulence): In this case, transition can occur at
significantly lower Re than in Newtonian flow. As mentioned by Graham (2014), the detailed correspondence between this regime and the MDR regime is still poorly
understood. Experiments suggest the existence of a continuous transition from the laminar flow curve to the
MDR curve, driven by the occurrence of some kind of
linear instability of the laminar state at sufficiently highRe and El: To the best of our knowledge, however, no simulation data obtained from available viscoelastic constitutive models has provided evidence of such linear
instability yet.

4. Recent analyses of DR onset and MDR inwall-bounded turbulence
In this section, we provide a survey of both numericaland experimental analyses of DR onset and MDR in wallbounded flows, with a twist towards viscoelastic effects,
to highlight current trends and research pathlines in the
study of turbulence-additives interaction. Shahmardi etal. (2019) investigated the turbulent flow of a polymer
solution in non-axisymmetric square ducts, using the
FENE-P model to simulate the presence of polymers. The
main macroscopic effect associated to the presence of thepolymers is to modify the secondary flow by increasing
the circulation of the streamwise main vortices and moving the location of the maximum vorticity towards thecentre of the duct. In addition, the low- and high-speed
streaks that characterize the fluid velocity distribution
near the wall are found to grow in size and coherence. As
far as the viscoelastic behaviour of the flow is concerned,
the Weissenberg number is found to influence strongly
the flow (as also shown in Zhou and Schroeder, 2016):
The cross-stream vortical structures grow in size and thein-plane velocity fluctuations are reduced as flow elasticity increases. Overall, the viscoelastic flow is less uniform
than its Newtonian counterpart, even if the direct contribution of the polymer stress term in the energy budget isfound to be small in amplitude. The same type of numerical approach, namely direct numerical simulation of an
incompressible FENE-P fluid, was employed by Li et al.
(2015) and Teng et al. (2018) to study DR in both turbulent
Poiseuille and Couette flow in a plane channel. Focus of
the analysis was the additive-induced modification of thenear-wall flow structures. In Poiseuille flow, the ratio ofpolymer relaxation time to the time scale of vorticity fluctuations in the mean flow direction is found to remainclose to unity in the near-wall region, from the onset of
DR to MDR. Moreover, the average axial energetic vortex
convection time is observed to increase with increasing

DR while its rotation speed decreases. Since the rate ofdecrease in the rotation speed is found to exceed the increase of the vortex convective time, MDR is achieved
when these two time scales become nearly equal. A similar DR mechanism is observed in Couette flow only in thenear-wall region. In the core region of the flow, differences are found, the most intriguing being the significant
polymer stretching that arises from a more intense mutual
exchange between the elastic potential energy and theturbulent kinetic energy of the flow (Teng et al., 2018).
Also, the spanwise and wall-normal components of theconformation tensor are found to reach their peak value:
Such finding is in contrast with that observed in Poiseuilleflow, where polymer stretching and elastic/kinetic energy
exchanges in the core region are negligible and peak values of the conformation tensor components occur near thewall (Teng et al., 2018).
White et al. (2018) also investigated polymer dragreduced flow in a wall-bounded domain, focusing on theredistribution of mean momentum and the mechanisms
underlying the redistribution processes in channel flow.
From a mechanistic perspective, the experimental observations of White et al. (2018) indicate that polymers reduce the intensity of near-wall vorticity stretching, thus
leading to an outward migration of the peak in the Reynolds shear stress and its gradient. In turn, such migration
leads to a reduced mean velocity gradient at the wall, a
more gradual decay of the mean vorticity, and causes thewall-normal position where inertially dominated mean
dynamics occurs to move outward from the wall. At highenough DR, the inertial sublayer runs out of physicalspace and ceases to exist: This implies that the state of
MDR is attained only upon annihilation of the inertial
sublayer.
Owolabi et al. (2017) investigated experimentally the
turbulent DR mechanism in flow through ducts of circular, rectangular and square cross-sections using two
grades of polyacrylamide (a flexible linear polymer) inaqueous solution having different molecular weights andvarious semi-dilute concentrations. The authors exploredthe relationship between DR and fluid elasticity, exploiting the polymer mechanical degradation1 to vary the rheological properties of the solution. Under controlled
degradation conditions, streamwise velocity profiles atvarious levels of DR indicated a thickening of the buffer
layer, up to the entire cross-section at MDR, in agreementwith previous studies (Gillissen and Hoving, 2012;
Paschkewitz et al., 2004). Based on their measurements,
Owolabi et a. (2017) were able to derive a quantitative
prediction of DR from the knowledge of polymer relaxation time, flow rate and geometric length scale (using eiMechanical degradation and its effects on DR will be discussed in
Sections 5 and 6.
1

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Cristian Marchioli et al. / KONA Powder and Particle Journal No. 38 (2021) 64–811 Wic DR % 2C  ther the Newtonian pressure drop combined with rheology(3)
1  exp(Wic  Wi)
data, or the average shear rate as an initial guess todetermine Wi, combined with an iterative procedure).
with C ∞ the approximate limiting value of DR % asThis prediction reads as:
Wi→∞ and Wic the critical Weissenberg number for the
onset of drag reduction (set to be Wic = 0.5, in agreement

Fig. 7 Fanning friction factors at different flow rates and pumping times for (a) pipe, (b) rectangular channel and (c) square duct. Dotted lines represent the appropriate laminar flow equations for Fanning friction factor; dot-dashed lines represent the correlations of Blasius for pipe and square ductand of Dean for rectangular channel; solid lines represent the correlations of Virk (1975) for pipe and rectangular channel and of Hartnett et al. (1986)
for square duct at MDR; the shaded regions represent f = ±10 % of MDR. Reproduced with permission from Owolabi et al. (2017).

Fig. 8 (a) Combined f-Re data for cylindrical pipe, rectangular channel and square duct (symbols and colours as in Fig. 7). (b) Variation of DR %with Weissenberg number. The solid black line represents Eq. 3. Reproduced with permission from Owolabi et al. (2017).

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with the theory of Lumley, 1973). In observing a working
functional dependence of DR % on Wi alone, the dependence on the ratio β of solvent to total viscosity, on inertia(i.e. on the flow Reynolds number) and on other viscometric functions, e.g. first or second normal-stress differences, is neglected. In spite of these approximations, theprediction fits reasonably well with the data, as shown in
Figs. 7 and 8. It must be noted that, in the MDR limit,
some weak Reynolds number dependence remains, as
DR % scales roughly as Re0.1 in this limit, and there is aspread in the literature for data nominally at MDR(Graham, 2014), highlighted by the grey region in
Fig. 8(b). Given the quality of the data collapse illustrated
in Fig. 8(b), however, the authors concluded that both β
and Re should be regarded as second-order effects, at least
for the concentrations and range of Re investigated.
Another correlation to predict the upper limit of DR using polymers as DRA has been proposed recently by
Zhang et al. (2018), for the case of turbulent pipe flow.
The main equation of the model computes the average
drag reduction as:
1 
DR % 
(1  ) 1  12Wi 2 (4)where β is the ratio of the solvent viscosity to the liquid
viscosity after the polymer is added at the zero shear rate,
and = =

1− c − c / l 23
1− c / l 2(), with c the trace of the conformation

tensor and l the dimensionless maximum length of thepolymer in the solution. Since c and l cannot be measured, the above equation must be used assuming c = 0 to
make it useful for practical engineering applications. The
model assumes that all vortex structures disappear in the
turbulent flow, i.e. complete laminarization is achieved. A
slightly older work on DR in dilute polymer solutions was
carried out by Xi and Bai (2016). These authors investigated the laminar-turbulent transition of the solution
showing its connection with MDR. The idea of the study
comes from the speculation (prompted by the universalityof MDR) that the MDR asymptote might be associatedwith a class of weak or marginal turbulent states that already exist in Newtonian flows but only become unmasked at high levels of polymer elasticity. As fluid
elasticity increases, the transition to hibernating states
becomes much more frequent, resulting in them taking up
a larger proportion of the overall statistics or a flow more
dominated by features of MDR. This idea clearly hints tothe already-mentioned DNS results (Graham, 2014; Xi
and Graham, 2012) on the intermittent transitions between strong active turbulence and weak hibernating turbulence. Xi and Bai (2016) identified the marginal state
associated to the weakest form of turbulence that can besustained as a dynamical edge state consisting of traveling waves and relative periodic orbits. The dynamics ofsuch state are characterized by low-frequency fluctuations
and exhibit regular bursts of turbulent activities separated
by extended quiescent periods. The flow field is dominated by elongated vortices and streaks, with weak extensional and rotational motions. Flow structures and ES
kinematics match hibernating turbulence and, according
to Xi and Bai (2016), offer explanations for the existence
and universality of MDR. Yet, the quantitative magnitudeof MDR still remains unsolved.
Fujimura et al. (2017) studied numerically the influenceof the polymer aggregation length on turbulent DR inchannel flow. Polymer aggregation was modeled using abead-spring chain model. The authors find that the local
polymer relaxation time increases as the natural length ofthe polymer increases and the spring constant decreases,
and observe that DR increases logarithmically with therelaxation time. Based on this logarithmic dependency,
the authors speculate that the drag-reducing effect of thepolymer occurs when it is longer than the diameter of turbulent vortical structures: Longer polymers are found to
induce higher energy dissipation upon interacting withthe flow structures and tend to suppress turbulent fluctuations. The role of polymer length was also examined by
Yang and Dou (2010) in connection with wall roughness
effects. These authors proposed and validated a theoretical formula to describe the flow resistance in laminar,transitional and turbulent flows from the hydraulicallysmooth regime to the fully rough one. This formula wasdeveloped based on the findings that, while polymers insmooth pipe flow increase the viscous sublayer thickness(thus leading to DR), polymers in rough pipes also increase the near-wall velocity when compared to Newtonian flow conditions, implying that roughness has anegative effect on DR. Indeed, larger roughness tends tonarrow the gap between the resistance in viscoelastic
flows and that in unladen flows.
As far as analysis of fiber-induced DR is concerned,
Moosaie and Manhart (2011, 2013) used a sophisticatedrheological model based on direct Monte-Carlo solver tocompute fiber orientation dynamics and study the effect ofBrownian diffusivity and fiber aspect ratio on the
non-Newtonian stress generated by the fibers. The model
enables stochastic simulation of the Fokker-Planck equation, in contrast to the moment approximation simulation
approach used by Paschkewitz et al. (2004), which requires a closure model. Application of the model to turbulent channel flow shows a shift of the logarithmic law
region of the mean velocity profile, indicating a thickening of the viscous sublayer. The streamwise velocity
fluctuations are enhanced, while the spanwise and wallnormal ones are attenuated. However, there are discrepancies with the results of the moment approximation
approach. The closure model required by the moment
approximation approach provides wrong estimates of the73Cristian Marchioli et al. / KONA Powder and Particle Journal No. 38 (2021) 64–81

mean non-Newtonian shear stress at the wall: This has adirect effect on the wall stress deficit and hence on theamount of DR (Moosaie and Manhart, 2013).
Fiber-induced DR has been investigated also by
Gillissen and Hoving (2012). These authors performed
pipe flow experiments showing that turbulent DR in plugflow of concentrated suspensions of macroscopic fibers is
a self-similar function of the wall shear stress over the fiber network yield stress. This behaviour was modelled interms of a central fiber network plug, whose radius is determined by the yield stress. The pipe cross section canthen be divided into a solid plug for r < rc, with rc the radial coordinate at which the surface of the plug is located(corresponding to the point in the pipe where the shear
stress of the fluid equals the fiber network yield stress),
and a Newtonian annulus for r > rc. The plug constrains
the size of the turbulent eddies in the surrounding annulus, thus reducing the friction factor as compared to
Newtonian flow. Note that, if the notion that a large aspectratio is key for DR, then one should expect polymers andfibers to reduce the drag by similar mechanisms. The experiments by Gillissen and Hoving (2012), however,showed marked differences, e.g. in the profiles of themean flow. Polymers act in the near-wall, buffer layer, effectively thickening the viscous sublayer, while leaving
the momentum transfer in the turbulent core unaffected.
Macroscopic fibers, on the other hand, act in the turbulent
core, and have little effect in the near-wall region. Thisdifference stems from the different lengths of polymers
and fibers. Polymers are usually of sub-Kolmogorov
length scale and, on the scale of the near-wall vortices,can be regarded as a continuum that induces an additional
viscosity and acts to reduce the momentum transfer of thenear-wall vortices (Voth and Soldati, 2017). Fibers, on theother hand, are rarely below the Kolmogorov scale.
Rather, they are usually orders of magnitude larger than
the near-wall vortices and, instead of inducing internal
friction, tend to impose external constraints on the nearwall vortices, which are thus forced to restructure themselves.

5. Predictive correlations for DR in wallbounded flows
In the previous sections, we focused on the phenomenology of polymer/fiber-induced turbulent DR and on thetheoretical frameworks that have been developed to explain the underlying physics. In this section, we focus on
one aspect of practical relevance for the design of industrial systems exploiting DRA, namely the predictive correlations that are available to determine amount of DR
expected for a given DRA concentration in a specific solvent. The amount of DR can be predicted using two types

74

of correlations: those that simply fit the experimental data(typically collected in small-scale pipes), whose predictability for industrial scale applications is however rather
limited (Campolo et al., 2015), or those developed basedon physics of the DR phenomena which appear more
promising in the industrial practice (Dubief et al., 2005).
Given the wealth of correlations for drag-reducing flowsthat are available in the literature, we will purposely focus
only on those providing the friction factor. Specifically,
we will discuss results from unpublished experimental
tests made with polymers (polyethylene oxide, PEO) inpipes of different diameter, equipped with centrifugal
pumps to assess the predictive capability of some widely-used correlations, discussing the efficacy of the tested
additives as DRA. Tests were performed under controlled
conditions: A pre-mixed homogeneous mixture of additive and solvent was introduced in the test rig and pumped
along the loop using a low-shear pumping system in order
to avoid peaks of shear stress, which could prematurely
degrade the additive (Elbing et al., 2009; Choi et al.,2000). Details on the experimental facility are provided inCampolo et al. (2015).
The theoretical variation of friction factor expected in
the polymeric regime when polymer degradation is negligible reads as (Shetty and Solomon, 2009; Virk, 1975):

(

(

)

1
=(4 + )log10 Re f − 0.4 − log10 Re ff(

where δ is the slope increment and Re f
Reynolds number, defined as:
=
f)
(Re
*

2 w /  ⋅ D∝  w0.5 ∝  w0.5
s

)

*

(5)

) is the onset*(6)

where D is the pipe diameter, νs is the kinematic viscosityof the solvent, τw is the wall shear stress and γw is the wall
shear rate. Fig. 9 shows the results of tests performed in
the pipes using PEO (Polyox WSR-301 by Dow
Chemicals), and hydrolized Polyacrylammide (HPAM,
Magnafloc 1011 by Basf) as water-soluble polymer. Eachpanel in the figure shows the variation of friction factor,
1 / f , for a given polymer concentration (symbol) as afunction of wall Reynolds number, Re f = Reτ 2 , inPrandtl Karman coordinates. The black line represents
the Prandtl-Karman friction factor (P-K) for pure waterand smooth pipe; the gray line in the top left corner represents Virk’s MDR asymptote. Dashed lines shown together with the experimental points represent thetheoretical variation of friction factor given by Eq. (5).
The experimental data follow the polymeric regime up to*a threshold value of Re f
above which they departfrom theory due to mechanical degradation. The lattercan be ascribed to two different phenomena: the mechanical degradation due to turbulence and the mechanicaldegradation due to the injection system. Mechanical deg-()

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Fig. 9 Prandtl-Karman plot of friction factor variation produced by polymer injection: different symbols refer to different polymer concentrations;each row shows the effect of polymer type: WSR-301 (top row) and Magnafloc 1011 (bottom row); each column shows the effect of pipe diameter(D = 30 mm, left column; D = 100 mm, right column); colours represent concentration (0.25 ppm, red; 0.50 ppm, blue, 1.00 ppm violet; 2.50 ppm,
green; 5.00 ppm, brown; 10.00 ppm, purple). Results from the Authors.

radation due to turbulence is associated to breakage of themonomers of the polymer chain produced when the shear
rate exceeds the threshold value  *w which is a function ofpolymer molecular weight, Mw:  *w= A ⋅ M wB , with A andB coefficients that depend on polymer type (Elbing et al.,2009). For PEO: A = 3.4·1018 and B = –2.20; for HPAM:
A = 1.16·1023 and B = –2.73. We remark here that, following Tabor and De Gennes (1986), the onset condition
identifies a value of the fluid time scale, usually equal to1/γw, matching the relaxation time scale of the polymer,
which depends on the polymer molecular weight. This
yields  w ∝ M w−1 . The use of such relation assumes thatthe onset of drag reduction is independent of polymer
concentration. This assumption has been widely usedsince Virk (1975) showed a negligible influence over awide range of polymer concentrations. However, otherstudies (see Elbing et al. (2009) and references therein)
have shown that weak concentration dependence may beobserved under certain conditions. Winkel et al. (2009)
and Vanapalli et al. (2006) found that  w= a ⋅ M w−1 witha = 3.35·109 for PEO, as derived from the experimental
data reported by Campolo et al. (2015). Elbing et al.
(2009) report τw = 1.68 ± 0.60Pa for HPAM having
Mw = 5.5·106 from which one can calculate a = 9.25·109.

The slope increment δ depends on molecular weight andconcentration, whereas it should not depend on pipe diameter (Campolo et al., 2015) and a specific slope increment δ/C 0.5 can be defined to characterize the dragreducing ability of a polymer-solvent pair and an intrinsic
slope increment Π = δ/(C/Mw)0.5 can be defined which depends only on the species skeletal structure. Based onthese assumptions, one can use experimental data to identify the value of onset Reynolds number and slope increments.
The second mechanism for polymer chain degradationis due to the injection system, characterized by locallylarge values of strain rate, D = uss / d , with uss and d thevelocity of polymer master solution and the injection pipe
diameter, respectively. Recent experimental evidence (Elbing et al., 2011) has demonstrated that individual polymer chains are stretched and fractured on a relatively
short time scale (order of milliseconds in the cited experiments), whereas changes in the mean molecular weightoccur on a significantly longer time scale (order of tenthsof seconds). This large time scale separation is ascribed to
the fact that, at any instant in time, a relatively low percentage of polymer chains are significantly stretched.
According to Vanapalli et al. (2006), polymer chain deg-75

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Fig. 10 Reference curves for DR prediction in industrial loop. TC (red line) is the theoretical line corresponding to the polymeric regime; OP (greenline) is the curve corresponding to one-pass scission; SS (blue line) and INJ (purple line, visible only in the largest pipe) correspond to steady state
scission and degradation due to the injection system, respectively. Symbols correspond to WSR-301 solution at the reference concentration of 1 ppm.
Results from the Authors.

radation under elongational flow is triggered by strain
rates exceeding a threshold given by: D= D ⋅ M wE , where
D and E are also coefficients, e.g. E = 4.2651·1010 and
D = –1.23 for PEO; D = 1.64737·1011 and E = –1.27 for
HPAM (Vanapalli et al., 2006). These data on polymer
mechanical degradation can be used to identify and plotin P-K coordinates the limiting value of shear stress andelongational stress the polymer can be exposed to before
being degraded by the flow. Fig. 10 shows these curves
together with the experimental data collected for PEO(WSR-301) at 1 ppm concentration in the three different
pipes. TC (red line) is the theoretical line corresponding
to the polymeric regime (Eq. 5); OP (green line) is thecurve corresponding to one-pass scission; SS (blue line)
corresponds to steady state scission and INJ (purple line,
visible only in the largest pipe) corresponds to degradation produced by the injection system. The agreement between experimental data (red symbols) and reference
curves for degradation is quite good and indicates thatdrag reduction in real systems can be predicted with some*confidence also for situations in which Re f ≥ Re f .
Mechanical degradation leads to the alteration of the molecular weight (Yang and Ding, 2013). To determine thelocal molecular weight of the injected polymer, Elbing etal. (2011) proposed the following scaling:(M w  M ws
 exp 8.6 10 5 (t f   w )
M wo

)

(7)

where Mw is the local molecular weight, Mws is the steadystate molecular weight (defined as the minimum Mw thatcan be obtained at a given γw), Mwo is the non-degradedvalue of Mw at the point of injection, and tf = (X – Xinj)/U∞
is the polymer residence time in the flow, (X – Xinj) being
the distance travelled by the polymer, and U∞ the convection velocity. Fig. 11 shows the accuracy of this scalingfor different characteristics of polymer degradation within

76

Fig. 11 Normalized difference between measured and steady-state molecular weights scaled with the product of residence time and wall shear
rate. Results refer to rough (solid symbols) and smooth (open symbols)
surfaces. The solid curve is the fit to the data and is provided by Eq. 7,
namely Eq. (3.12) in Elbing et al. (2011). The error bars were determined from standard error propagation analysis. Reproduced with permission from Elbing et al. (2011).

a turbulent boundary layer. Changes in mean molecularweight occur on a time scale proportional to the polymer
residence time. In addition, Mw tends to a finite level withincreased residence time and shear rate, and the key parameters that control the degradation process appear to be
the shear rate, polymer residence time in the TBL flow,
Mwo and Mws (Elbing et al., 2011).

6. Additive DR from a physico-chemical
perspective
As mentioned in the previous section, mechanical degradation represents an important aspect of DR phenomena
because of its practical implications for the design of ac-

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curate experiments (Wyatt et al., 2011). Mechanical degradation pertains the physico-chemical aspects of DR,
which are in strong connection with the rheological andfluid mechanics aspects already covered. We believe that
discussing physico-chemical aspects is thus important toprovide a coherent picture of the intrinsic complexity of
DR phenomena.
Regarding mechanical degradation, a crucial issue isthe polymer resistance to chain scission, which poses anupper bound to the level of DR that can be achieved by
the additive as well as the time/distance over which theadditive is effective as drag reducer (see Choi et al., 2000;
Elbing et al., 2009; Soares et al., 2015). When polymers
are added to the flow as a homogeneous mixture in awall-bounded flow, protocols (e.g. batch mixing by low
shear impeller or tumble blenders, in line mixing by recirculation using low shear pumps, as in Campolo et al.,2015; Japper-Jaafar et al., 2009) are typically enforced
during polymer mixture preparation to avoid mechanicaldegradation. When polymers are injected at the wall,
small information is generally given on details of the injection system used which, per se, might induce degradation. Whichever the origin of mechanical degradation, thelimiting value of the shear rate able to produce chain scission can be measured by experiments. Scaling relationships have been derived to link the limiting shear rate to
the polymer molecular weight and to the strength ofchemical bonds (Vanapalli et al., 2006). As demonstrated
by Vanapalli et al. (2006), in a system properly designed
to avoid any local degradation, the local stress at theKolmogorov scale able to generate the molecular tension
leading to polymer covalent bond breakage inside the pipe
can be evaluated and the effect of polymer mechanicaldegradation can be accounted for. The loss of efficiencyof the additive as the mechanical degradation proceeds
has been analysed by Choi et al. (2000) in a rotating apparatus and by Soares et al. (2015) in pipe flow. Whichever
the flow configuration, the physical mechanism governing
degradation is independent of geometry. Kalashnikov(2002) found that for low enough additive concentration,
the initial value of the friction coefficient and its variations in the course of degradation are also independent of
the Weissenberg number. A half-degradation time can be
defined from theoretical considerations and measured inconnection with the flow hydrodynamics and network
characteristics to estimate the span over which periodic
polymer injection should be performed to maintain a desired level of DR.
A recent investigation focusing on the deformation ofpolymer molecules is reported in Shaban et al. (2018),
who used planar PIV to gather detailed measurements ofthe turbulent flow field in a channel when polymers(PAM) are exploited as DRA. Their data, together withthe rheological characterization (shear and elongational

viscosity) of the polymeric solution allowed to characterize the interaction between the polymer molecules andturbulence. Measurements of mean flow, second-orderturbulence statistics, and local strain-rate and rotation rate
obtained using time-resolved 2D-PIV, showed that the extent of polymer deformation strongly depends on thewall-normal location, and is caused mainly by the streamwise strain rates. In the log-layer, polymer molecules do
not exhibit significant stretching, since they were found tosample regions of strong rotation more often than regionsof strong shear. At a high polymer concentration, rotationand shear were found to be in balance both in the buffer
layer and in the log layer.
Another important physico-chemical aspect of DR isrepresented by the polymer microstructure, which nowadays can be designed ad-hoc to support the synthesis ofwell-defined macromolecules able to achieve desired supramolecular characteristics (D’hooge, 2015). Wever etal. (2013) used controlled synthesis to produce high molecular weight branched polyacrylamides, PAM, to be
used as drag reducing agents. The equilibrium conformation of polymers having the same molecular weight but
different microstructure were analysed using Dynamic
Light Scattering (DLS) to measure their hydrodynamic
volume; their intrinsic viscosity in solution was measured
by viscosity tests. Results showed that the molecular architecture of more branched (13 and 17-arm PAMs) polymers was more extended in solution than that of theirlinear (4 and 8-arm analogues) counterpart; as a consequence, the elastic response of polymers solutions wasenhanced, leading to an improved thickening efficiency
that supported the use of branched PAMs for application
in Enhanced Oil Recovery and DR. Controlling the microstructure of the polymer may also allow controlling its
extensional viscosity, which according to many authors,
can become much higher than the intrinsic viscosity (seeHousiadas and Beris (2004) and references therein). An
abrupt increase in the extensional viscosity that depends
on the extensional strain rate is therefore deemed to be a
key factor in turbulent DR (Hidema et al., 2013). Polymerinduced DR under different extensional strain rates
have been analyzed by image processing calculating thecurvature histogram of the interference pattern, which isrelated to the distribution of the velocity fluctuation. Results indicate that different processes of energy transfer
reduction are activated depending on the polymer type(flexible/rigid). Flexible polymers are stretched and oriented parallel to the streamwise direction, whereas rigid
rod-like polymers are only re-oriented parallel to thestreamwise direction without extension. In the normal direction, the energy transfers are prohibited by orientatedpolymers. The stretching process of flexible polymers(PEO) increased the extensional viscosity, which also prohibits energy transfer in the streamwise direction (Shaban

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Fig. 12 Interference images of turbulence in flowing soap films of PEO
solution at different extensional rates. Images refer to increasing PEO
solution (C = 0.5·10 –3 wt %, 1.·10 –3 wt % and 2.·10 –3 wt % from left toright) and increasing extensional rates ( = 250 s –1 and 350 s –1 from top
to bottom). Reproduced with permission from Hidema et al. (2013).

et al., 2018). Hidema et al. (2013) developed ad-hoc tests
in two-dimensional turbulence made by flowing soap
films to investigate DR by flexible polymers (e.g. PEO)
and rod-like polymers (e.g. HPC, hydroxypropyl cellulose) in the absence of shear flow. Using a grid to generate
extensional strain in a flowing solution containing polymers, Hidema et al. (2013) recorded the interference pattern of soap films with a video camera to observe theeffect of polymer stretching and polymer re-orientation on
2D turbulence. Fig. 12 shows the corresponding interference images of the turbulence in flowing soap films of
PEO-added solution at different extensional rate.

7. Conclusions and future perspectives
The discussion proposed in this review highlights anumber of crucial challenges for future research. Manyexperimental and numerical results indicate that thestructure of a turbulent flow laden with polymers and/or
fibers can be modified over a wide range of length scales
even for very small concentrations of the additives. Additionally, effects due to additives depend strongly and notstraightforwardly on the concentration: While the flow
statistics in the dissipation range of turbulence changesmoothly as a function of additive concentration, there isevidence that the inertial-range values of the structure
functions are modified only when the concentration exceeds a specific threshold (which is flow and polymer-type
dependent). Open issues are therefore related to the lackof a clearcut explanation of the qualitative change in theeffect of the additive above the critical concentration, andto the need for a better understanding of the exact ways inwhich the additives affect the energy cascade. Considering that the time criterion for the onset of DR does nothold in the bulk of the flow, a physical mechanism bywhich the polymers can affect scales much larger than78

their size has yet to be identified. A promising route toachieve this goal seems to be represented by the possibility to describe the effect of the polymer/fiber additive
through models derived from viscoelastic turbulence theory. In terms of available scaling laws, it appears that
more comprehensive datasets (both experimental and numerical) are needed to develop truly universal relations.
Datasets need to be expanded by including a wider rangeof polymer types, molecular weights, injection conditions(for processes involving polymer degradation) and flow
parameters to properly assess the universality of the scaling. This would lead to further improvement of existingcorrelations, which aim to predict mechanical degradationand the resulting loss of efficiency of drag reducers induced either by turbulence or by the injection system.

Acknowledgments
We are very grateful to Professor Soldati for the useful
discussions.

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Authors’ Short Biographies
Cristian Marchioli
Cristian Marchioli is Associate Professor of Fluid Mechanics at the University of
Udine, Editor of Acta Mechanica and former chairman of the COST Action “Fiber suspension flow modeling”. Currently, Prof. Marchioli sits in the scientific council of the International Center of Mechanical Sciences, where he coordinated several advanced
schools on particles in turbulence. His research interests involve multiphase flow modeling, from small-scale particle-turbulence interactions to large-scale modeling of gassolid/gas-liquid flows. Prof. Marchioli has published 50+ papers and 100+ conference
proceedings. He has also delivered several invited and keynote lectures at international
conferences.

Marina Campolo
Marina Campolo is Associate Professor in Chemical Engineering at the University of
Udine. She received her Laurea (M.S. - B.S.) in Industrial Engineering and got her Ph.D.
in 1999 in Chemical Engineering from the University of Udine. Her research interests
are in the area of process and environmental engineering with an emphasis on multiphase systems. Prof. Campolo has published 30+ papers and 50+ conference proceedings. Together with A. Soldati and A. Cremese, she received the 2007 Knapp award fromthe American Society of Mechanical Engineers.

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Review Paper

Agglomeration and Dispersion Related to Particle
Charging in Electric Fields †Mizuki Shoyama and Shuji Matsusaka *Department of Chemical Engineering, Kyoto University, Japan

Abstract
Electrostatic forces cause spontaneous movement of charged particles; subsequently, electrostatic technology is
attracting attention because of its application in powder handling processes, such as separation, classification,
dispersion, and collection. Dielectric and conductive particles are charged by induction in a strong electric field
and moved by Coulomb forces. The magnitude and polarity of the transferred charges are controlled by thestrength and direction of the electric field. The dielectric particles are also polarized in the electric field, and dipole
interactions occur between particles or in the particle layers, complicating the particle behavior. This review paper
presents induction charging, agglomeration, levitation, and other behaviors resulting from particle layers in electricfields. A series of particle phenomena occur in parallel electrode systems, which consist of a lower plate electrodeand an upper mesh electrode. Charged agglomerates are formed on the particle layers, levitated by the Coulomb
forces, and disintegrated with rotation when approaching the mesh electrode. The mechanisms of agglomerationand disintegration have been elucidated in multiple studies, including microscopic observations and theoreticalanalyses of particle motion, based on numerical calculations of the electric field. Furthermore, a new system is
proposed for continuous feeding of dispersed particles using electric fields and vibration.
Keywords: particle, electric field, charging, agglomeration, levitation, dispersion

1. Introduction
In powder handling processes, the deposition of charged
particles is a common phenomenon. The accumulationof charged particles on surfaces reduces operability andleads to lower productivity; thus, charged particles must
be removed from the surfaces. Fluid flow (Masuda et al.,
1994; Gotoh et al., 2015) and vibration (Kobayakawa etal., 2015; Adachi et al., 2017) are effective for removing
particles. Another effective method is the application of
external electric fields, which enables remote control ofthe motion of charged particles (Masuda et al., 1972; Calleet al., 2009; Kawamoto et al., 2011). Dielectric particles
and conductive particles can be charged by induction ina strong electric field and moved by Coulomb forces.
The magnitude and polarity of the transferred charge arecontrolled by the strength and direction of the electric field.
The dielectric particles are also polarized in the electricfield, and dipole interactions act between the particles or in
the particle layers; thereby, the particle behavior becomes†Received 13 June 2020; Accepted 28 July 2020
J-STAGE Advance published online 5 September 2020
* Corresponding author: Shuji Matsusaka;
Add: Kyoto 615-8510, Japan
E-mail: matsu@cheme.kyoto-u.ac.jp
TEL: +81-75-383-3054 FAX: +81-75-383-3054

82

more complicated.
The induction charging, agglomeration, levitation, andother behaviors resulting from particle layers in electricfields have been studied in detail (Shoyama and Matsusaka,
2017, 2019; Shoyama et al., 2019). Furthermore, a new
system has been proposed for the continuous feedingof dispersed particles using electric fields and vibration(Shoyama et al., 2018). Based on previous studies, thisreview paper summarizes the mechanisms of induction
charging, the control of particle behavior, and the concept
of its application.

2. Induction charging of single particles
When a conductive particle comes into contact with aninside wall of a parallel electrode with a different polarity,
the particle is charged to the same polarity as the electrode.
This phenomenon is called induction charging (Blanchard,
1958; Cho, 1964). Charges cannot pass through ideal dielectric materials; however, dielectric materials have a low
degree of conductivity on the surface or in the body. Thus,
various types of particles can be charged by induction.
The equilibrium charge of a conductive particle by induction is represented by (Cho, 1964)

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Mizuki Shoyama et al. / KONA Powder and Particle Journal No. 38 (2021) 82–93

q   1.65π  rf  0 D p2 E ex ,(1)

where εrf is the relative permittivity of the fluid, ε0 is the(1) permittivity, Dp is the particle diameter, and Eex is
vacuumthe external electric field strength.
The equilibrium charge of a dielectric particle is represented by (Wu et al., 2003)q   0.55 p π  rf  0 D p2 E ex ,

and
(2)

p

3rp
,
rp  2(2)

(3)

where εrp is the relative permittivity of the particle. The
particle charge as a function of time is expressed as(3)
qp t  qpe 1 exp t /  ,
(4)
and
(4)
  v 0 rp(5)where ρv is the volume resistivity of the particle.
(5)

3. Motion of charged particles between
parallel electrodes and other applications
Particles sufficiently charged by induction can be madeto levitate from the electrode by Coulomb forces, and thenmove toward the counter electrode. When the particles
come into contact with the counter electrode, their polarity
is inverted. Consequently, the particles move back to thefirst electrode and then oscillate between the electrodes(Cho, 1964). Highly conductive particles are charged
immediately after contact with the electrodes. For low
conductivity particles, charging takes time (Ohkubo and
Takahashi, 1996a, 1996b; Wu et al., 2003; Nader et al.,2009). However, if electrical resistance is extremely high,induction charging will not occur. Instead, contact charging
will dominate (Matsusaka et al., 2010; Matsusaka, 2011).
As the quantity of charge transferred by one contact
charging event is rather small, particles involved in contact
charging cannot be levitated.
In the above system, there can be both positively andnegatively charged particles between electrodes. To extract
unipolar charged particles, openings may be required in
one of the parallel electrodes. Replacing the upper plateelectrode with a mesh electrode allows the passage of
unipolar charged particles through the openings (Tada etal., 2004). When charged particles with the same polarity
are extracted from the revised system, these particles are
dispersed by their mutual electrostatic repulsion (Masuda,2009).
There are many electrostatic applications for the controlof particle position (Matsusaka et al., 2008), separation(Dwari et al., 2015), classification (Kawamoto, 2008), andsurface cleaning (Mazumder et al., 2007; Kawamoto et al.,2011). In addition, there are reports regarding particle levitation using various configurations of electrodes (Adachi
et al., 2016; Blajan et al., 2017). These electric fields allow
particles to move even in the absence of mechanical and/or
pneumatic systems. Thus, electrostatic techniques are expected to be used in various fields such as space exploration(Kawamoto et al., 2011; Adachi et al., 2016), and underatmospheric pressure.

4. Agglomeration and levitation in electricfieldsDielectric particles are polarized in an electric field andtend to form chain agglomerates along the direction of theelectric field because of the interactions between polarizedparticles (Hollmann, 1950; Pearce, 1954; Nakajima andMatsuyama, 2002). The interaction between dipoles is
illustrated in Fig. 1. A typical example of the applicationof this interaction is an electrorheological fluid (ERF),
which is a suspension of dielectric particles dispersed in
an insulating liquid. The ERF changes apparent viscosity
by forming chain-like structures of particles (Parthasarathy
and Klingenberg, 1996).
Shoyama and Matsusaka (2017) conducted experimentson the behavior of particles (glass beads: Dp50 = 100 μm)
in gases using parallel electrodes at a distance of 10 mm.
Fig. 2 schematically shows the experimental setup. Particle
layers with a thickness of 1 mm are placed on the lower
electrode, which is connected to a power supply, and theupper electrode is grounded. The behavior of the particles
in the external electric field is recorded by a high-speed
camera with a zoom lens.
When the voltage of the lower electrode is set to
VL = 5 kV, single particles and chain agglomerates levitatefrom the particle layers, as shown in Fig. 3. These phenomena can be explained as follows. (1) The dielectric particles

Fig. 1 Interaction between dipoles.

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Mizuki Shoyama et al. / KONA Powder and Particle Journal No. 38 (2021) 82–93(glass beads) are polarized in the upward electric field. (2)As mutual electrostatic interactions act between the particles, chain agglomerates are formed. (3) As the particle
surfaces have a relatively low conductivity, the electrons
move downward due to induction; consequently, the particles on the top surface of the particle layers are positively
charged. (4) The charged particles experience upward Coulomb forces in the electric field. (5) As the Coulomb forces
overcome the downward forces, the particles levitate.
Fig. 4a shows a simulation model for electric field calculation using FEM (COMSOL Multiphysics, COMSOL,
Inc.). A chain agglomerate is placed on the top surface of
1-mm-thick particle layers in a 3D Cartesian coordinate
system (x, y, z). The calculation domain is set to 5 Dp ×
3 3 Dp for the horizontal cross section and 10 mm forthe height, which is the same as the distance between theelectrodes in the experimental setup. The top and bottom
boundaries are set to zero and a given voltage, respec[51]tively. Periodic boundary conditions are applied at the sideboundaries. The charges of the agglomerate and the top
particle layer are given based on the experimental result.
The relative permittivity of the particles is also given forthe calculation.
Fig. 4b shows the calculated electric field strength Eexz
in the z-direction. The Eexz value in the region of z < 1 mm
is almost zero in an electrostatic equilibrium state, although
there are small fluctuations caused by particle arrangements. In contrast, the Eexz values within the agglomerate(z = 1 – 1.18 mm) are relatively high and fluctuate significantly at the particle contact points and on the top of theagglomerate.
Fig. 5 shows a series of images of a levitated particle atintervals of 2 ms. The particle moves upward, acceleratingin the electric field. Fig. 6 shows a series of images ofagglomeration and levitation at intervals of 10 ms. The
polarized particles form a straight-chain agglomerate bymutual electrostatic interactions, and the agglomerate
levitates at 60 ms.
Particle charge can be calculated based on the motion
analysis of levitated particles. A straight-chain agglomerate
moving in an electric field experiences a drag force Fd, agravitational force Fg, and an electrostatic force Fe. The
equation of motion of the agglomerate is expressed as

Fig. 2 A parallel electrode system.

Fig. 4 Electric field calculation using FEM: (a) simulation model and(b) calculated values along the axis of the chain agglomerate.

Fig. 3 Snapshots: (a) levitation of single particles and chain agglomerates and (b) formation of large agglomerates (glass beads:
D p50 = 100 μm, ρp = 2300 kg/m3, εrp = 7).

84

Fig. 5 Levitation of a single particle (glass beads: D p50 = 100 μm).

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layers, the electrostatic force Fe consists of the Coulomb
force Fex in the external electric field, the image force
Fi, the interaction force Fp between polarized particles,
and the gradient force Fgrad in a non-uniform electric field(Morgan and Green, 1997). That is,F e  F ex  Fi  F p  F grad .
Fig. 6 Agglomeration and levitation (glass beads: D p50 = 100 μm).

nm p

(6)

where n is the number of the primary particles constituting
the agglomerate, mp is the mass of each primary particle, va(6)
is the velocity of the agglomerate, and t is time. The massof each particle is defined as
mp 

6

,

(7)

where ρp is particle density. For a stationary fluid, Fd isgiven by (Kasper et al., 1985; Niida and Ohtsuka, 1997)(7)

Fd  3Da va ,(8)where μ is the viscosity of the fluid and Da is the volume
equivalentdiameter of the agglomerate, which is defined as(8)
1Da  n 3 Dp .

(9)

κ is the dynamic shape factor given by





 

where Fqi is the Coulomb force acting on the i-th particle in
the agglomerate, which is defined as(15)
Fqi  q i E ex ,(16)
where qi is the charge of the i-th particle, and Eex is the(16) electric field. Fi is expressed as (Weber, 1950)
external


Fi

 

(10)

where θm is the angle between the agglomerate axis andthe moving direction.   and   are the dynamic shape(10)
factors perpendicular and parallel to the moving direction,
respectively. That is,[53]
1.00 (n  1)[52]  1.16(n 2)
1.26 (n  3)1
   n q2
 rs rf  2i ,16π rf  0  rs   rf i 1 z pi

(17)

where εrs is the relative permittivity of the particle layers,
and zpi is the position of the i-th particle on the top surface(17)of the particle layers in the z-direction. When the axis of thechain agglomerate is parallel to the external electric field,
Fp is expressed as (Parthasarathy and Klingenberg, 1996)
2

Fp 

1
1  1
1 
(9)



 cos 2  m ,

(15)

i 1

dv a
 Fd  Fg  Fe ,dt

π Dp 3 pHere, Fex is expressed asn(14)
F ex   F qi ,(14)   1   Dp  4 2 2 ,3π  0  rf  rp 
 D p E ex8
  rp  2   d (18)where εrp is the relative permittivity of the particle. Fgrad isexpressed as (Hywel and Green, 1997)(18)
 1 31
2 .
D a grad E ex
Fgrad  π  0  rf rp(19)
4
 rp  2
Fig. 7 shows the experimental data (circles) regarding
the position of the levitated particle in the vertical direction(19)
z shown in Fig. 5. The solid lines in this figure are particle
trajectories calculated using Eq. (6). The experimental dataagree well with the solid line calculated with a charge of

(11)

and

1.00 (n  1)

(11)
  
1.03 (n 2) .
1.07 (n  3)

(12)

The gravitational force of the agglomerate is defined as(12)Fg  n mp g ,(13)where g is gravitational acceleration. When the agglomerate(13)is close to an object, such as the surface of the particle

Fig. 7 Particle position as a function of elapsed time with a parameter ofparticle charge (glass beads: D p50 = 100 μm).

85

Mizuki Shoyama et al. / KONA Powder and Particle Journal No. 38 (2021) 82–93

Fig. 8 Relationship between specific charge and the number of primaryparticles in levitating agglomerate (glass beads: D p50 = 100 μm).

0.134 pC, which is 58 % of the value calculated using Eq.
(1) and 75 % of the value calculated using Eq. (2). The
charge of a particle levitated from particle layers is generally smaller than the charge of a particle levitated from anelectrode because of the difference of εrs in Eq. (17).
Fig. 8 shows the relationship between specific charge, qm(= q/mp), and the number of primary particles constituting
a levitated agglomerate (n ≥ 2) or a single particle (n = 1).
The qm value decreases with an increase in n. When the
charge of the single particle is small, that is, the Coulomb
force is small, the particle cannot be levitated. However,when the magnitude of the total Coulomb force of theconstituent primary particles is large, the agglomerate canbe levitated from the particle layers.

Fig. 9 Images of particles levitated from particle layers at VL = 5 kV.

5. Effects of particle characteristics on
agglomeration and levitation
Fig. 9 shows the images of particles levitated from different types of particle layers. The applied electric voltage
is VL = 5 kV. For the glass beads (Fig. 9a) and alumina
particles (Fig. 9b), large numbers of both single particles
and chain agglomerates are levitated. In contrast, for the
ferrite particles (Fig. 9c), very few chain agglomerates arelevitated. This difference is mainly caused by the electrical resistances of the particles. In cases of low electricalresistance (ferrite particles: ρv = 0.8 Ω·m), particles are
immediately charged up by induction before forming
agglomerates, resulting in single-particle levitation. However, when there is high electrical resistance (glass beads:
ρv = 1.1 × 107 Ω·m; alumina particles: ρv = 0.3 × 106 Ω·m),particles take time to be charged; in the meantime, chain
agglomerates are formed on the particle layers. Although
the relative permittivity also affects the relaxation time ofcharge transfer, as shown in Eqs. (4) and (5), the differencein materials is small (glass beads: εrp = 7; alumina particles: εrp = 8.5; ferrite particles: εrp = 2.2). The effect of theapplied voltage on the agglomeration is also small, fitting
within a range of VL = 4 – 6 kV.

86

Fig. 10 Forces acting on a charged agglomerate just prior to its separation from particle layers.

To analyze the condition of levitation, the forces acting
on agglomerates on the top surface of the particle layers
should be studied. Fig. 10 shows the forces calculated
from the experimental values of particle diameter, particle
charge, and other physical properties for n = 3. Although
the polarization force Fp, image force Fi, and gradient force
Fgrad are small, the Coulomb force Fex and gravitational
force Fg are significantly large. That is, the dominant upward and downward forces are Fex and Fg, which increase
as a function of particle diameter. These analytical results
indicate that the concept of force balance is valid within apermissible error.

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6. Disintegration of agglomerates in nonuniform electric fields
The motion of charged particles is changed in a
non-uniform electric field. Fig. 11a shows an electric field
generated by parallel electrodes, which consist of the plateelectrode and mesh electrode. The electrode configuration
for the simulation is the same as those used in the experiment (see Fig. 2). The lines and arrows in this figure
indicate the electric potential and electric field direction,
respectively. The electric field is uniform in the lower area
but non-uniform in the upper area. Fig. 11b shows thedetails of the upper area, indicating that the non-uniform
electric field is directed to the center of the wire of the meshelectrode.
Fig. 12a shows a series of images of a chain agglomerate passing through the mesh electrode. The agglomerateconsisting of three primary particles moves upward, but
its velocity decreases with an increase in height. During
this movement, the agglomerate changes its state. Fig. 12bshows enlarged images of the same agglomerate. The
agglomerate is in a straight-chain structural state at the beginning. From top to bottom, the three primary particles aredenoted as P1, P2, and P3, respectively. After the agglomerate begins to rotate counterclockwise, P3 separates fromit and moves upward and to the right. The agglomerateconsisting of the two primary particles continue to rotate
counterclockwise; finally, P1 separates from P2. The prob-

ability of disintegration generally increases as a function of
the number of constituent primary particles.
When the forces acting on each primary particle in the
agglomerate are not the same, the agglomerate experiences
the forces in the circumferential as well as in the radial
direction. Fig. 13 illustrates the rotation models in anelectric field Eex for n = 2 and 3, respectively. θ is the angleof the agglomerate axis relative to the vertical, and φ is theangle between the agglomerate axis and the electric field
direction. That is,    ex ,(20)

where θex is the angle of the external electric field direction
at (20)the position of the agglomerate relative to the vertical.
Fig. 14 illustrates the torques acting on chain agglomerates with different values of φ. Here, it is assumed that the
charge q1 for the upper particle is larger than the charge q2
for the lower particle at φ = 0. The larger charge generates astronger Coulomb force; thus, the agglomerate experiencesa torque (Tq) around the centroid. The agglomerate also
experiences a torque (Tp) caused by the dipole interactions

Fig. 12 Disintegration of a chain agglomerate passing through the meshelectrode: (a) fixed-point images and (b) enlarged images of the agglomerate (glass beads: D p50 = 100 μm).

Fig. 11 Calculated electric field: (a) overview and (b) enlarged view.

Fig. 13 Rotation model of chain agglomerates in an electric field (a)n = 2 and (b) n = 3.

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Mizuki Shoyama et al. / KONA Powder and Particle Journal No. 38 (2021) 82–93
4

D 
(25)

Fpij F0  p  3 cos 2   1 e r  sin 2e  rij where rij is the distance between the two particle centroids.
er and eφ are unit vectors in the radial and circumferential(25) (27)より改変
directions,
respectively.
F0 is expressed as2⎛ ε −1 ⎞3
2 .
F0 =π ε 0 ε rf D p 2 ⎜ rp
⎟ E ex16⎝ ε rp + 2 ⎠

(26)

The
first and second terms on the right-hand side of Eq.
元の(25)は使用せず(25) represent the electrostatic interaction forces in the ra4
(26)
 D 
dial and circumferential
directions, respectively. Therefore,F p ij F 0  p  3 cos 2   1 e r  sin 2  e  ,the force acting
on
the
i-th
particle due to the other particlesr ij 
Fpφi in the circumferential direction is given by
4

n
D 
Fpi   F0  p  sin 2 e 
(25)
j 1
 rij (j ≠ i)(27)

Torque Tp caused by dipole interactions in the electric fieldis given by(j ≠ i).
Fig. 14 Torques acting on chain agglomerates (n = 2).

Tpin the electric field. Tp allows the particle axis to align withthe electric field direction.
Furthermore, an agglomerate consisting of n primaryparticles experiences a torque (Td) caused by the dragforces during rotation; therefore, the equation for rotationalmotion is expressed asIdω Tq  Tp  Td ,
dt

(21)

where I is the moment of inertia given bynI   m p ri 2 ,
i 1

(22)

where ri is the particle position relative to the axis of rota(21)and ω is the angular velocity. The magnitude of ω is
tion,
(22)
given by



d
.
dt

(23)

The torque Tq around the centroid caused by Coulomb
forces is given by(23) nT q  F q i  ri  .
(24)
i 1

The interaction force Fpij between particles polarized in
the electric field was defined by Klingenberg et al. (1989)(24)
and Washizu and Jones (1994). They considered an induced
field caused by the existence of the particles in the electricfield. A simple model was also presented by Klingenberg
et al. (1989) and Parthasarathy and Klingenberg (1996).
Using this simple model, the electrostatic interaction force
Fpij between the i-th and j-th particles is determined as88n Fpi  ri  .

(28)

i 1

(27)
In the same manner, torque Td caused by the drag forces
is given by(28) n
T d  F d i  ri 
(29)
i 1

where Fdi is the drag force of the i-th primary particle as afunction of the velocity vp. That is,(29)

Fdi  3Dp vpi ,(30)

The rotation of the agglomerate can be calculated using
Eq.(30)(21). The(8)
angularvelocity increases as a function of theより改変
spread of charge distribution in the agglomerate. Charge
distribution is generally caused by electrostatic induction
during levitation in the external electric field. The rotation
generates centrifugal force, which can cause the disintegra元の（30）は使用せず
tionof the agglomerate. The centrifugal force |Fc| acting on
a constituent
is given by.
F d i  3 π primaryμ D p v p iparticle
Fc  m p r  2

(31)

(30)
Fig. 15 shows the temporal variation of the adhesion
force(31)|Fa| and centrifugal force |Fc| based on the actual
particle behavior (see Fig. 12). The values of |Fa| and |Fc|
are calculated using the first term on the right-hand sideof Eq. (25) and Eq. (31), respectively. |Fa| is initially highbut decreases with time, whereas |Fc| increases with time
for both n = 3 and n = 2. Particle separation is initiated at
10 and 15 ms when |Fc| > |Fa| is satisfied. This implies thatthe centrifugal force plays a significant role in agglomerate
disintegration in the non-uniform electric field.

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7. Continuous feeding of dispersed particles
In powder handling processes, continuous feeding
and the control of particle motion are essential for stable
operation and the quality control of products. To realize
these operations, a conceptual system using electric fields
and vibration has been proposed (Matsusaka et al., 2013;
Kawamoto et al., 2016). This system can also be applied
to the electrostatic characterization of particles, where theparticles are charged by the contact potential difference(Mizutani et al., 2015). Shoyama et al. (2018) have developed a new system for continuous particle feeding anddispersion using both parallel electrodes and a vibrator.
The experimental setup is schematically shown in Fig. 16.
A mesh electrode is placed at a distance of 20 mm fromthe plate electrode, which is attached to an inclined acrylic
base. One of the electrodes is connected to a DC power
supply, and the other electrode is grounded. Particles are
fed at a constant flow rate and transported on the lower
electrode, which is vibrated to improve particle flowability.
Fig. 17 shows images of particle behaviors observed at
different applied voltages. The particles are levitated fromthe lower electrode and widely dispersed. When voltage
is applied to the upper electrode, the particles are more
widely spread than when a voltage is applied to the lower
electrode. The spread area of the particles increases as afunction of the absolute value of the applied voltage.

Fig. 18 shows the quantitative analysis of particle
dispersion for different applied voltages. For VU = 0 and
VL > 0 (Fig. 18a), the range of particle position increases
as a function of the value of VL, and the distributions aremonomodal. As for VL = 0 and VU < 0 (Fig. 18b), thedistributions are bimodal, and the range is obviously wider.
Fig. 19 illustrates the concept of the charging and the
motion of particles in this system. The upper virtual boundary is assumed to be zero. For VU = 0 and VL > 0 (Fig. 19a),
the electric field below the upper electrode is directed
upward. Particles that are positively charged on the lower
electrode experience upward Coulomb forces. The levitatedFig. 17 Effect of applied voltage on particle dispersion (alumina particles: D p50 = 48 μm, ρp = 3800 kg/m3).

Fig. 15 Comparison between centrifugal force and adhesion force(glass beads: D p50 = 100 μm).

Fig. 16 Experimental setup for continuous feeding of dispersed particles.

Fig. 18 Quantitative analysis of particle dispersion in the z-direction(alumina: D p50 = 48 μm): (a) VU = 0 and VL > 0; and (b) VL = 0 and
VU < 0.

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particles can pass through the mesh electrode due to particle inertia. However, there are limits to the maximum
heights of the particles under the effect of the gravitational
forces; thus, these particles are attracted to the upper electrode. After adhesion, their polarity is changed by induction
charging. The negatively charged particles levitate from theupper electrode. However, the Coulomb forces above theupper electrode drastically decrease with increasing height;
therefore, the particles cannot reach higher positions. The
polarities in Fig. 19b are opposite to those in Fig. 19a;
however, the motions of the particles are the same.
When VU < 0 (Fig. 19c), two electric fields are formed;
one is directed upward below the upper electrode, and theFig. 19 Concept of the charging and the motion of particles in this system: (a) VU = 0 and VL > 0; (b) VU = 0 and VL < 0; (c) VL = 0 and VU < 0;(d) VL = 0 and VU > 0.

other is directed downward above this electrode. Oncethe particles adhere to the upper electrode, their polarity
changes. As the Coulomb forces above the upper electrodeare directed upward, the particles can reach higher positions. Consequently, the polarity of the charged particles at
the higher position is opposite to that of the particles levitated from the lower electrode. The polarities in Fig. 19d
are opposite to those in Fig. 19c; however, the motions of
the particles are the same.
The polarity of charged particles is changed by theconditions; thus, some particles repeatedly collide with theelectrodes. Fig. 20 shows a series of a particle’s motions on
the lower electrode and the specific charge of the particle
qm. The upper figure indicates the particle position in thez-direction as a function of time. The experimental results(solid lines) agree well with the calculated results basedon the equation of motion (broken lines). The lower figure
indicates the variation of the specific charge estimated fromthe motion analysis. The particle motion can be classified
into three categories, namely, collision, adhesion, andlevitation. In the collision process, the charged particle isattracted to the lower electrode by the Coulomb force andrepeatedly collides with decreasing rebound height. The
absolute value of the negative charge of the particle decreases with the number of collisions because the particle
acquires some positive charge during each collision. Afterlosing its kinetic energy, the particle adheres to the lower
electrode. As the particle acquires a larger positive charge
by induction charging for a period of 15 ms, the polarityof the particle is changed to positive. When the Coulomb
force becomes sufficiently large, the particle is levitatedagain. Here, it is worth noting that the transferred charge
depends on the contact time.

8. Conclusions

Fig. 20 A series of a particle’s motions on the lower electrode and thespecific charge of the particle (alumina: D p50 = 48 μm, VL = +8 kV and
VU = 0).

90This review paper presents a series of particle phenomena occurring in parallel electrode systems consisting of alower plate electrode and an upper mesh electrode. Particle
layers are placed on the plate electrode. The mechanisms
of induction charging, the control of particle behavior, andthe concept of its application are summarized as follows:(1) Particles on the top surface of the particle layers arecharged by induction in a strong electric field even though
the particles are dielectric. These particles are also polarized and form a straight-chain agglomerate on the particle
layers by mutual electrostatic interactions.
(2) Single particles and agglomerates can be levitatedfrom the particle layers by Coulomb forces. When the
charge of single particles is relatively small, the particles
are not levitated. However, when the magnitude of thetotal Coulomb force of the constituent primary particles islarge, the agglomerates can be levitated. The charge of theMizuki Shoyama et al. / KONA Powder and Particle Journal No. 38 (2021) 82–93

primary particles decreases with an increase in the numberof primary particles in the agglomerate.
(3) In situations of low electrical resistance, particles are
immediately charged up by induction. When there is highelectrical resistance, particles take time to be charged.
Therefore, in the former, single particles are easily levitatedbecause of excessive charges on the surfaces. As for thelatter, agglomerates tend to be levitated.
(4) Levitated agglomerates disintegrate with rotation whenapproaching the mesh electrode. The rotation is controlled
by the torque, which is caused by the charge distribution
in the agglomerates. The rotation generates a centrifugal
force, which acts as a separation force.
(5) A new system is proposed for the continuous feeding ofdispersed particles using electric fields and vibration. Particle charge depends on the contact time of the electrode.
When voltage is applied to the upper electrode, particles
are more widely spread above the electrode than when avoltage is applied to the lower electrode. The spread areaof the particles increases as a function of the absolute valueof the applied voltage.

mp

mass of primary particle (kg)nnumber of primary particles constituting an agglomerateor single particle (–)

qm

specific charge (charge to mass ratio) (C/kg)

qcharge of primary particle (C)q∞equilibrium charge of primary particle (C)rparticle position relative to its axis of rotation (m)rijdistance between centroids of i-th and j-th particles (m)Tdtorque caused by rotational drag force (N·m)

Tptorque caused by the interaction between polarized primary particles (N·m)

Tqtorque caused by the difference in Coulomb force of eachprimary particle (N·m)

ttime (s)VLvoltage applied to the lower electrode (V)VU

voltage applied to the upper electrode (V)vavelocity of agglomerate (m/s)

vp

velocity of particle (m/s)

Nomenclaturex

horizontal or longitudinal directionytransverse direction perpendicular to the xz planeDavolume equivalent diameter of agglomerate (m)zdirection perpendicular to the xy planeDpparticle diameter (m)zpparticle position in the z-direction (m)Dp50

mass median diameter (m)ε0vacuum permittivity = 8.85 × 10 –12 (F/m)

Eexexternal electric field (V/m)εrfrelative permittivity of fluid (–)

Eexz

external electric field strength in the z-direction (V/m)εrprelative permittivity of particle (–)

eunit vector (–)εrsrelative permittivity of solid (or particle layers) (–)|Fa|magnitude of adhesion force (N)θangle of the agglomerate axis from the vertical (rad)|Fc|magnitude of centrifugal force (N)

θex

Fd

drag force (N)angle between external electric field direction and thevertical (rad)Feelectrostatic force (N)θmangle between the agglomerate axis and moving direction (rad)Fex

Coulomb force in external electric field (N)κdynamic shape factor (–)

Fggravitational force (N)



Fgrad

gradient force (N)dynamic shape factor perpendicular to moving direction(–)

Fi

image force (N)dynamic shape factor parallel to moving direction (–)

Fpinteraction force between polarized particles (N)[54]μviscosity of fluid (Pa·s)

Fpijinteraction force between i-th and j-th particles polarizedin electric field (N)

p
[55]

ρ

particle density (kg/m3)

ρv

volume resistivity of particle (Ω·m)

Fq

Coulomb force acting on primary particle (N)τrelaxation time (s)F(zp)

cumulative distribution of particle positions in the zdirection (–)φ

angle between the agglomerate axis and electric field
direction (rad)ggravitational acceleration (m/s2)

ωangular velocity of agglomerate (rad/s)

I

moment of inertia (kg·m 2)

91

Mizuki Shoyama et al. / KONA Powder and Particle Journal No. 38 (2021) 82–93

subscriptsiindex for primary particlerradial direction

φcircumferential direction

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Authors’ Short Biographies
Mizuki Shoyama
Mizuki Shoyama is a Researcher of Chemical Engineering at Kyoto University. She
earned her PhD from Kyoto University. She has worked as a development engineer in theaerospace division, IHI Corporation, and at Nuclear Fuel Industries, Ltd. Dr. Shoyama’s
current research interests include particle levitation on deposited particles with photoelectric charging and particle mixing using superimposed electric fields.

Shuji Matsusaka
Shuji Matsusaka is a Professor of Chemical Engineering at Kyoto University. He earned
his PhD from Kyoto University. He has held important positions in academic organizations in areas of powder technology, aerosol science, and electrostatics. He is an emeritus
editor-in-chief of Advanced Powder Technology. Dr. Matsusaka’s current research interests
include characterizing particle electrification, adhesion, and flowability, as well as thehandling of micro-particles and nano-particles in gases.

93

KONA Powder and Particle Journal No. 38 (2021) 94–109//https://doi.org/10.14356/kona.2021001

Review Paper

Recent Progress in Efficient Gas–Solid Cyclone Separatorswith a High Solids Loading for Large-scale Fluidized Beds †Chihiro Fushimi 1*, Kentaro Yato 1, Mikio Sakai 2, Takashi Kawano 3 and Teruyuki Kita 3
1

Department of Chemical Engineering, Tokyo University of Agriculture and Technology, Japan
Resilience Engineering Research Center, School of Engineering, The University of Tokyo, Japan
3
Project Center, TAKUMA Co., Ltd., Japan
2

Abstract
Circulating fluidized beds (CFB)s are important technical equipment to treat gas–solid systems for fluid catalytic
cracking, combustion, gasification, and high-temperature heat receiving because their mass and heat transfer rates
are large. Cyclones are important devices to control the performance of CFBs and ensure their stable operation;
heat-carrying and/or solid catalyst particles being circulated in a CFB should be efficiently separated from gas at
a reduced pressure loss during separation. In commercial CFBs, a large amount of solids (> 1 kg-solid (m3-gas) –1
or > 1 kg-solid (kg-gas) –1) is circulated and should be treated. Thus, gas–solid cyclones with a high solids loading
should be developed. A large number of reports have been published on gas–solid separators, including cyclones.
In addition, computational fluid dynamics (CFD) technology has rapidly developed in the past decade. Based onthese observations, in this review, we summarize the recent progress in experimental and CFD studies on gas–solid cyclones. The modified pressure drop model, scale-up methodology, and criteria for a single large cyclone
vs. multiple cyclones are explained. Future research perspectives are also discussed.
Keywords: gas–solid cyclone, circulating fluidized bed, high solids loading, design

1. Introduction
Circulating fluidized beds (CFB)s are commerciallyused for fluid catalytic cracking (FCC), and combustionand gasification of coal, biomass, and waste material because their heat and mass transfer rates are very large(Basu P., 2015; Grace J.R. et al., 1997; Gräbner M., 2015;
Lettieri P. and Macrì D., 2016; Li C.-Y. et al., 2017; Pecate
S. et al., 2019; Scala F., 2013; Stolten D. and Scherer V.,
2011). Recently, novel CFB solar receivers have been developed for concentrated solar power generation (Ansart
R. et al., 2017; García-Triñanes P. et al., 2016, 2018). In a
CFB, because heat-carrying and/or catalyst particles are
circulated to transfer heat between each reactor, fast andefficient gas–solid separation is extremely important for astable operation and reducing particle loss due to entrainment. Cocco R et al. (2017) investigated particle entrainment and clustering in a fluidized bed. Cyclones are

†

1
2
3

*

94

Received 8 August 2019; Accepted 23 September 2019
J-STAGE Advance published online 2 November 20192-24-16 Naka-cho, Koganei, Tokyo 184-8588, Japan
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
2-2-33, Kinrakuji-cho, Amagasaki, Hyogo, 660-0806, Japan
Corresponding author: Chihiro Fushimi;
E-mail: cfushimi@cc.tuat.ac.jp
TEL: +81-42-388-7062 FAX: +81-42-388-7409

widely used as primary gas–solid separators owing totheir simple configuration and ease of operation. A stable
operation of cyclones is important to reduce load in secondary gas–solid separators, makeup of the heat-carrying
and/or catalyst particles, and pressure loss. Thus, muchattention has been paid to the research and developmentof cyclones over the past several decades (Hoffmann A.C.
and Stein L.E., 2010).
In commercial CFB boilers where carbonaceous solids
are combusted to generate heat, a high solids-loading gas(CT > 10 kg-solid (kg-gas) –1 as defined in Eq (1)) shouldbe treated in the primary gas–solid separator in order toefficiently separate solids from the gas (Van de Velden M.
et al., 2007; Dewil R. et al., 2008).

kg
]
s
CT 
kg (1)
total mass flow rate of gas to cyclones [ ]stotal mass flow rate of solid to cyclones [Cortés C. and Gil A. (2007) extensively reviewed themodels developed for the flow behavior, velocity profiles,
pressure drop and collection efficiency in inverse-flow cyclones under the conditions of CT < 0.23 kg-solid (kggas) –1. Huard M. et al. (2010) comprehensively reviewed
gas–solid separators including cyclones, impact separators, and other separators with a riser top and downer

Copyright © 2021 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/).

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

bottom configuration. They summarized the solidsseparation mechanism and separation efficiency of eachseparator and reported that recent research on reverse-­
flow cyclones is directed toward the influence of high solids loadings on cyclone performance and computational
fluid dynamics (CFD) simulations. However, in the past,
CFD calculations were not highly reliable for large solids-­
loading cyclones and fast separators due to limitations on
computational power.
On the basis of such reviews and reports, in the current
review, we summarized progress in the past decade interms of experimental and numerical studies on highsolids-­loading gas–solid separators (mainly cyclones) in
fast solids-circulation systems in CFBs.

g


[
v  v


2
 


px

Chen J. and Shi M. (2007) analyzed pressure drop in areverse-flow cyclone with a tangential inlet by dividing
the total pressure loss into the four components, namely(1) expansion loss at the cyclone inlet, (2) contraction loss
at the entrance of the outlet tube, (3) swirling loss due togas flow and cyclone walls, and (4) dissipation loss of gas
dynamic energy in the outlet tube. They reported thatcomponent (2) has limited effect on the total pressure loss
and can be omitted. Based on this result, they proposed
the Chen-Shi (C-S) model to predict pressure drop in cyclones operating with (i.e., an inlet solid concentration(Cs) of 0.002 to 2 kg-solid (m3-gas) –1) or without dust gas
at ambient and high temperatures. Li S. et al. (2011) investigated cyclone pressure drop at a very high Cs (0.125–
4.42 kg-solid (m3-gas) –1) and inlet gas velocities (vi) of
13.2, 17.5, and 21 m s–1. They improved the C-S model topredict cyclone pressure drop more accurately and reported that component (4) in the C-S model should not be
included; further, they suggested that the swirl exponent
may be zero for high solids-loading conditions.
The improved C-S model can be described as follows
to estimate pressure loss in a cyclone (Li S. et al., 2011;
Chen J. and Shi M., 2007).


v

px
or

vi
K A D e2  rc2 

4Q De2  Dc2 

0.5nvcve vw rc D e  vi

g 2
v
ze
2

1





2
K A2 D e2  rc2

rc De n1
K A2 D e2  rc2 

]
2

gvi2
2

2
 C  2k ib g vi2
p1  1  s   1 g   1  2 1  c b  D e  2
fAs g w CSp b 
2  0.9Q

1.5

(5)

g vi
1.11 fK A AS '3w D e1.5n
2

2

(6)


f f air (1  3 Cs / g )

(7)

Db 2
4ab

(8)

4A
A s  s2 
1  D e2  4D el  4H b 
Db

2.1 Pressure-drop model


vze

'2
w

2
ze

(4)′

KA 

2. High solids-loading cyclones

2


(9)

2
2
1  B  4 H  H b   1  B   4D h H h w 1.11K A 0.21D e0.16 Re 0.06
1  f air A s K A D e

x ρg De

Re 

(11)

µg

 ' w 

(10)

 w

1  0.35 Cs / g n0
rc 0.38D e  0.5D e2

0.27

(12)
(13)
(14)

(2)

(3)

g vi2
2(4)

Fig. 1Comparison between model-predicted and experimental data (vi = 17.5 m s –1). Reprinted with permission
from Ref. (Li S. et al., 2011). Copyright: (2011)
WILEY-VCH Verlag Gmbh & Co. KGaA, Weinheim.

95Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

In the improved C-S model, geometric and velocity
variables were normalized with respect to cyclone diameter. As shown in Fig. 1, the performance predicted by the
improved C-S model agrees well with experimental datawhen C s = 1–5 kg-solid (m 3 -gas) –1, thus effectively
amending the overprediction of the original C-S model.

2.2 Multi-cyclone and non-uniform distributionof particles
In large-scale industrial reactors with high gas–solid
flow rates, small parallel cyclones are often preferred toachieve a high separation efficiency when the distributionof gas–solid flow at each cyclone inlet is uniform. However, it is difficult to place a refractory in such small cyclones (Nowak W. and Mirek P., 2013) and there is strong
evidence that gas–solid flow in parallel cyclones is
non-uniform, which reduces the total separation efficiency(Zhang C. et al., 2016).
Masnadi M.S. et al. (2010) examined gas–solid flow
distribution across two parallel and identical cyclones
based on an analytical model and compared flow distribution through parallel pipes. They confirmed the consistency of their analytical model by comparing theexperimental data of two identical cyclones (barrel diameter D = 101.6 mm). They reported that a non-uniform (ormaldistribution) gas–solid flow is unavoidable for a highsolids loading (upstream solids hold up > 0.01 %) and thatfouling can significantly affect maldistribution of gas–solid flow through the identical cyclones. Zhang N. et al.
(2010) calculated a three-dimensional full-loop CFB
boiler model with two parallel cyclones using an Eulerian
granular multiphase model. In their study, they found minor differences in the average solids mass flux (Gs) in thetwo cyclones (5.74 and 6.05 kg m–2 s–1) and pointed outthat the maximum Gs alternates between these two cyclones. Zhou X. et al. (2012) investigated gas–solid flow
through six parallel cyclones located asymmetrically on
the left and right walls of the riser (i.e., three cyclones on
the left and three cyclones on the right) in a CFB cost test
apparatus. They observed that the distribution of gas–solid flow was non-uniform across three cyclones on one
side and that the middle cyclone on each side exhibited
higher particle velocities while their Gs was lower thanthat of other cyclones. Jiang Y. et al. (2014) conducted numerical calculations on gas–solid flow hydrodynamics at
a CFB boiler test facility with six parallel cyclones using
an Eulerian-Lagrangian model and computational particle
fluid dynamics (CPFD). They validated simulation datausing experimental data obtained by electrical capacitance tomography (ECT) in cold model tests (at ambient
temperature and atmospheric pressure). The geometry of
the six cyclones was either axis-symmetric or point-symmetric, as shown in Fig. 2.

96

They also observed that the solids concentrations of thefour cyclones located at the corners of the chamber weregreater than those of others and stated that an “axis-­
symmetric” arrangement (case A) for cyclones is better
than a “point-symmetric” arrangement (case B) from theview point of uniform distribution of solids (Fig. 3).
Wang S. et al. (2017) investigated the hydrodynamics
of gases and solids in six parallel cyclones with central
symmetry and axial symmetry arrangements combinedwith a full-loop CFB by CFD and a discrete elemental
method (CFD-DEM, Fig. 4). They reported that for a uniform distribution of solid mass flux in parallel cyclones,
axial symmetry is better than central symmetry. The middle

Fig. 2

CFB model with 6 cyclones for CPFD calculation (a)Front view of simulation geometry, (b) Axis-symmetric, (c) Point-symmetric (units: mm). Reprinted withpermission from ref. (Jiang Y. et al., 2014). Copyright(2014) Elsevier B.V. *Numbers and characters are rewritten to improve the clarity.

Fig. 3Time-averaged particle mass flow rate distribution in
cyclones according to CPFD simulations. Reprinted
with permission from ref. (Jiang Y. et al., 2014). Copyright (2014) Elsevier B.V.

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

cyclones on both sides have higher solid velocity and solid
holdup than other corner cyclones (Fig. 5).
Shuai D. et al. (2017) also investigated the flow behavior of gas and solids in six cyclones in parallel in an annular furnace. They observed a non-uniform distribution ofGs and cyclone pressure drop (Δpc) in the six cyclones.
However, no regularity could be observed. The relative
deviation of Gs in the six cyclones was 8.0 % under typical operating conditions.

2.3 Design principles of multi-cyclones
The design principles of small multi-cyclones and alarge single cyclone were analyzed. Mo X. et al. (2015)
investigated the influence of wall friction and solid acceleration on the non-uniform distribution of gas–solid flowin two parallel cyclones. They reported that pressure drop
in cyclones has an inflection point with respect to theFig. 4

Table 1

Schematic of 6 cyclones in CFD calculation (a) Front
view of simulation geometry (b) Central symmetry (c)Axial symmetry arrangements (units: mm). Reprinted
with permission from ref. (Wang S. et al., 2017). Copyright (2017) Elsevier B.V.

mass flow rate ratio between solids and the gas (CT,inf, Eq.
(1)), which is around 0.5–3.33 kg-solid (kg-gas) –1, as calculated from the reported values. They also suggested
that the inflection point increases with an increase in thewall friction but decreases with an increase in solid acceleration. The inflection point has a large effect on non-­uniform gas–solid distribution in the two parallel
cyclones. As summarized in Table 1, the solid flow distribution is non-uniform when CT approaches CT,inf.
Zhang C. et al. (2016) analyzed multi-phase interactions and investigated instabilities in uniformity in twoparallel cyclones installed after a fluidized bed reactor.
They provided a novel design principle to avoid non-­uniform distribution of solids using CT and dimensionless
vortex finder diameter (dr) defined in Eq. (15). Fig. 6
shows a phase diagram of uniformity of the two parallel
cyclones as a function of fraction of solid flow to cyclone
1 (i.e. path 1) and CT. They reported that under the condition that inlet velocity of air is 15 m s–1, Reynolds number
is 3.08 × 105 and glass beads are used at 20 °C and101.3 kPa, a low solids loading (CT < 1.35), the uniform
distribution is stable but at CT = 1.35, there occurs a turning point from uniform to non-uniform distribution.
When CT > 1.35, the maldistribution of solids is stable.

Fig. 5Time-averaged solid flux distribution in cyclones.
Reprinted with permission from ref. (Wang S. et al.
2017). Copyright (2017) Elsevier B.V.

Summary of the three phases in two parallel cyclones. Reprinted with permission from ref. (Mo. X. et al. 2015). Copyright(2015) Elsevier B.V.
Dilute phase

Transition phase

Dense phase

CT,infCT << CT,inf

CT ~ CT,inf

CT >> CT,inf

Main contributor

Wall friction

Both greatly influence thepressure drop

Solid acceleration

Gas fraction in cyclone 1 (ψ)
and solids fraction in cyclone 1 (γ)ψ > 0.5 and γ > 0.5 orψ < 0.5 and γ < 0.5

ψ ~ 0.5 and highly unevensolid distribution at certain
flow perturbation

ψ > 0.5 and γ < 0.5 orψ < 0.5 and γ > 0.5

97Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

They found that dr should be less than 0.32 and that drstrengthens the swirl in a cyclone for enhancing the stability of uniformity and cyclone efficiency under this condition.
Fig. 7 shows a phase diagram of stability based on thedata in literature (Zhang C. et al., 2016). For parallel cyclones that treat high solids loading, dr should be smallenough to ensure the stable operation. These criteria arevery useful in the selection of single large cyclones ormulti-cyclones for uniform and steady operation.

Fig. 6

Phase diagram of stability of uniformity at different
mass flow rate ratios (CT) when inlet velocity of air is
15 m s –1, Reynolds number is 3.08 × 105 and glass
beads are used at 20 °C and 101.3 kPa. Reprinted withpermission from ref. (Zhang C. et al., 2016). Copyright(2016) John Wiley and Sons.

Fig. 7

Stability phase graph of the relationship between thestability of uniform distribution/maldistribution anddimensionless vortex finder diameter dr and mass flowrate ratio CT.
Ref. A: Jiang Y. et al. (2014)
Ref. B: Liao L. et al. (2011)
Ref. C: Zhou X. et al. (2012)
Ref. D: Zhang N. et al. (2010)
Ref. E: Wang F.J. et al. (2014)
Ref. F: Liu F. et al. (2014)
Reprinted with permission from ref. (Zhang C. et al.,2016). Copyright (2016) John Wiley and Sons.

98

dr 

vortex finder diameter [m]cyclone barrel diameter [m](15)

2.4 Cyclones in series
Wu X. et al. (2011) experimentally measured and calculated the pressure drop of two scroll-type cyclones connected in series for a wide range of solids loading(CT = 0–30 kg-solids (kg-gas) –1) and cyclone inlet velocity(vi = 16–24 m s–1). The experimental data showed that thecyclone pressure drop decreased dramatically as CT increased to 7.5 kg-solids (kg-gas) –1 after which it remained
almost constant.
Fushimi C. and Guan G. et al. developed a triple bed-­
combined CFB for coal gasifiers (Fushimi C. et al., 2011,2014; Guan G. et al., 2010, 2011) and experimentally investigated the hydrodynamics of silica sand (average
particle diameter of 126 μm) at a high flux (Gs in therange of 200–546 kg m–2 s–1) in cold model tests. In theseexperiments, three cyclones were connected in series
to separate solids from air. Separation efficiency at theoutlet of the third cyclone was 99.998 % when Gs wasFig. 8

Schematic diagram of the proposed iG-CLC system
Reprinted with permission from ref. (Wang X. et al.,2015). Copyright (2015) The American Chemical Society.

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

Fig. 9(a) Schematic diagram of the experimental setup of a fluidized bed, a riser, and a dipleg connected with acyclone, (b) the photograph of the fluidized bed and dipleg (non-operating status). Reprinted with permission from ref. (Wei Z.G. et al., 2016) under the terms of the CC-BY 4.0 license. Copyright: (2016)
The Authors, published by Springer Nature.

490–510 kg m–2 s–1. Meanwhile, Hoffmann A.C. and Stein
L.E. (2010) re­commended that the underflow pipes of series-connected cyclones should be independently sealed.

2.5 Combination of an inertial separator and acyclone for a high-flux CFB
Wang X. et al. (2015) developed a high-flux CFB reactor, comprising of a fuel reactor, an air reactor, a J-valve,a downcomer, and solid separation systems, for in situ
gasification chemical looping combustion (iG-CLC). They
optimized the iG-CLC system by developing an inertial
separator for primary gas-solids separation and a cyclone
for secondary gas-char and remaining solids separation to
improve operation stability and solid separation efficiency.
They reported that the selective separation efficiency ofcoal particles in the first-stage inertial separator was
77.7 % when the mass f low rate of the solid was
1021 kg h–1 and the overall separation efficiency after thesecond-stage cyclone reached 99.5 % when the mass flowrate to cyclone was 35 kg h–1 in their cold model tests.
In their subsequent work (Shao Y. et al., 2017), they
carried out three-dimensional full loop CFD calculation
using an Eulerian-Eulerian two-fluid model combinedwith the standard k-ε turbulence model for the gas phaseand the kinetic theory of granular flow for the solid phase
to investigate the hydrodynamics of coal and iron ore particles on the basis of the experimental results of coldmodel tests. They reported continuous and stable solid
circulation in the iG-CLC model when Gs was around400 kg m–2 s–1.

2.6 Design principles of the cyclone inlet and bodyfor high solids-loading multi-cyclones
Hoffmann A.C. and Stein L.E. (2010) recommended

Fig. 10 Diagram of fluidization regimes in a dipleg with theincrease of solid mass flux (Gs) (a) and (b) the dilute–dense coexisting falling flow, (c) the dense conveying
flow, (d) dense conveying flow with a high particle
concentration. Reprinted with permission from ref.
(Wei Z.G. et al., 2016) under the terms of the CC-BY
4.0 license. Copyright: (2016) The Authors, publishedby Springer Nature.

that 1) bends should be located at a distance of ten pipe
diameters or its equivalent before cyclone inlets to avoid
non-uniform distribution of gases and solids in the cyclone inlet piping and 2) a scroll or wrap-around type of
inlet should be used. At high solids or liquid loadings(> ~10 vol%), care must be taken not to restrict the discharge opening or the annular space around a vortex stabilizer.

2.7 Flow behavior of gas and solids in a dipleg
below cyclone
Wei Z.G. et al. (2016) examined the pressure of a catalyst powder (Sauter mean particle diameter of 63.6 μm)

99

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

flow in a dipleg (150 mm inner diameter and 9 m height)
μηtot = ηwall + ηvtx = 1 − lim +when Gs was in the range of 50.0 to 385.0 kg m–2 s–1.
μeFig. 9 shows the experimental apparatus consisting of
m
(16)
μlim
ηF (d j ) ΔRAi (d j )setup of a fluidized bed (600 mm i.d. and 8 m height), a∑
μe j =1
riser (200 mm i.d. and 12.5 m height), and a dipleg(150 mm i.d. and 9 m height) connected with a cyclone
where μlim is the limited loading ratio defined by Eq. (17).
(400 mm i.d.). The bottom of the dipleg was immerseddyinto the fluidized bed. Fig. 10 shows the observed fluid(17)µlim = K lim ⋅ ( e ) ⋅ (10 µe )d 50,Aization patter n in the dipleg. At small G s (G s <50.0 kg m–2 s–1) (cf. Fig. 3a, b), a dilute-dense coexisting
Here, the constant Klim = 0.02 for fine particles and 0.03
falling flow. The swirl flow (just below the cyclone), thefor coarse particles. For initial load, μe < 2.2 × 10−5, thedilute particle falling flow (in the middle) and the dense
exponent y has a value of 0.81 and for μe > 0.1, y = 0.15.
flow (bottom) were observed. In the dense flow, some asThe value of de is calculated using Eq. 18 (Mirek P., 2018).
cending gas bubbles were observed like a bubbling fluid18 g
0.5 0.9V de
ized bed. When Gs = 200.0–250.0 kg m–2 s–1 (cf. Fig. 3c),
(18)AW p  g  z e
no interface between the dilute particle falling flow andthe dense flow was observed. Pressure fluctuation intenWang J. et al. (2019) reported that when the solids loadsity reached a maximum in the fluidization pattern being
ing is higher than the limit loading (μe > μlim), dense partransformed. Further increase in Gs (Gs > 350.0 kg m–2 s–1)
ticles cannot flow through the rotating/swirling stream(cf. Fig. 3d), the fluidization regimes developed the dense
because of their high inertia; in this case, these particles
conveying flow with a high particle concentration.
hit the outside wall of the cyclone and descend to the bottom.
Mirek P. also described the particle size distribution of
the carryover, RF(d), and it can be determined using
3. Scale-up methodology and grade efficiency
Eq. (19).
The scale-up of cyclones is important for reactor designμ(1 − ηF (d ))and estimating separation efficiency. Mirek P. (2016, 2018)(19)
ΔRF (d ) = lim ⋅⋅ ΔRA (d )(1 − ηtot )μeinvestigated the scaling rules of cyclones in CFB boilers
and estimated the separation efficiency of cyclones by setThe total separation efficiency is determined byting up the following model (Eqs. (16)–(21)). In thisEq. (20).
model, the total separation efficiency of a cyclone ηtot isRF d 
the sum of the efficiency at the wall (ηwall) and in the inner(20)F d  1  (1  tot )RA (d )vortex (ηvtx) (Eq. (16)). A portion of the incoming solids
not collected by the wall is collected by the inner vortex,
which is based on the Muschelknautz model (Muschelknautz
E., 1972),
Table 2The same researcher summarized the scaling relationship using five dimensionless parameters sets shown in
Table 2. They compared estimation curves based on the

Scaling relationships and parameters used for the analysis of the cyclone performance in cold model tests (cf. Fig. 11).
Reprinted with permission from ref. (Mirek P., 2018). Copyright (2018) Elsevier B.V.

Scaling relationships

Parameters chosen independently

Notation

U 0 Gs,, PSD
u T pU 0

d32, ρp, ρg, Dr, μg, g

Set (1)

U0, Ar, PSDuT

ρp, ρg, Dr, μg, g

Set (2)U 0 Gs,, Fr, PSD
u T pU 0

ρp, ρg, Dr, μg, g

Set (3)

p
U 0 Gs
,
, Fr,
, PSD
g
u T pU 0

ρg, Dr, μg, g

Set (4)

ρg , μ g , g

Set (5)Rep ,Fr, Rep ,

100

p
g

,

Gs
d
,
, PSD
pU 0 Dr

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

Table 3Fig. 11 Influence of a set of scaling relationships on the total
grade efficiency curve based on the parameter setsshown in Table 2 and the Stokes equation. Reprinted
with permission from ref. (Mirek P., 2018). Copyright(2018) Elsevier B.V.

five dimensionless parameter sets and the Stokes equation(Eq. (21)).
Stk in, i  p  g  d 502 i
18 g Db

Estimate

Std. Error

P-value

β0

64.9524.70191.7896e–38

β1–6.86080.640627.4357e–25

β214.7211.28054.303e–28

β323.6733.23527.0839e–13

β414.7940.98611

3.2965e–44

β61.64860.40073

4.3607e–05

β7–2.2869

0.364196.0287e–10

Estimate

Lower

Upper

σ1

0.0011382

0.00035134

0.0036874

σ20.16095

0.134110.19315σ60.038589

0.028213

0.052781(21)

Fig. 11 shows the result. All the proposed scaling relationships resulted in a very high separation efficiency(> 99.4 %). However, the results strongly depended on theselected scaling relationships set (Mirek P., 2018).
Wang J. et al. (2019) recently conducted experiments
extensively and introduced sophisticated models to improve the prediction of grade efficiency of cyclone separators. They constructed generalized linear mixed-effects(GLME) models that are functions of the parameters (St,d , σ , d 50 , Re, Fr ) to understand and control grade
ξ
,H
Db
d 50
efficiency (ηF(d)) variation. Note σξ is the size deviation inparticle diameter at the inlet.
In their GLME models, the observed grade efficiency
vector (η) is considered to be a summation of the expectedgrade efficiency vector (μ) and the noise vector (e), whichis assumed to follow a normal distribution with mean 0(Eq. (22)).
η=μ+e

GLME model estimation parameters. Reprinted withpermission from ref. (Wang J. et al., 2019). Copyright(2019) Elsevier B.V.

(22)

The expected grade efficiency (μ) is represented by theGaussian regression model shown in Eq. (23),⎛ d ⎞g (µ ) = β0 + ( β1 + φ1)ln (St) + ( β 2 + φ2 )ln ⎜⎟⎝ d 50 ⎠⎛d ⎞+ β3ln(σ ξ ) + β 4ln ⎜ 50 ⎟ + ( β6 + φ6 )ln (Re) (23)
⎝ Db ⎠+ β7ln (Fr)Fig. 12The parity plot of fitted values based on the GLME
model and experimental results of the grade efficiency.
Reprinted with permission from ref. (Wang J. et al.,2019). Copyright (2019) Elsevier B.V.

ponent and has a normal distribution with a variance σi2.
The g(μ) and the expected grade efficiency (μ) are linked
in the following equations ((24), (25)).

g  μ  ln(ln( μ))(24)μ  exp[exp(g( μ))](25)

Table 3 lists the values estimated for the parameters(β0-7, σ1, σ 2, σ6) in Eq. (23), including a 95 % confidence
interval for random effects. Fig. 12 shows the parity plotof experimental results and fitted values predicted by using the GLME model. It can be seen that the GLME modeling predicts the experimental grade eff iciency
accurately. It is considered that the GLME model can provide setting conditions for cyclone separators (Wang J. etal., 2019).

where ϕi is a random effect corresponding to the ith com-

101

102
0.133 (Single)
0.094 (Dual)
0.04
0.15
0.168
0.04
0.072
0.3
0.148–0.428
0.24
0.19
0.025
0.19
0.15
0.282

Lee H. and Yook
S.J. (2014)

Haig C.W. et al. (2014)

Oh J. et al. (2014)

Xiong Z. et al. (2014)

Avci A. et al. (2013)

Yoshida H. et al. (2010)

Ahuja S.M. (2010)

Wang W. et al. (2010)

Zhang P. et al. (2019)

Karagoz I. et al. (2013)

Hsiao T.C. et al. (2015)

Mazyan W.I. et al. (2017)

Wu X. et al. (2011)

Li S. et al. (2011)

Experimental
and simulational

0.29

Demir S. (2014)

0.5
0.0723
0.072
0.547
0.14
0.3

Song J. et al. (2017)

Huang A.N. et al. (2018b)

Huang A.N. et al. (2017a)

Huang A.N. et al. (2017b)

Gao Z. et al. (2019)

Wei J. et al. (2017)

Yu X. et al. (2018)

0.100

Prabhansu et al. (2017)

Wei Z.G. et al. (2016)

0.6

Mirek P. (2018)

Experimental

Barrel diameter,
D [m]References

1.33–4.64

4–12

12–18

13.6–18.8

11–21

15

16–29

7–30

13.2–21

16–24

14

10–25

17–36.5

12–16

6.63–15.11

2.7–19.1

2.4–37.2

19–39

5.2–13.0

15–45

4.4–12.5
3.1–8.9

10–18

Inlet gas
velocity,vi [m s –1]

300, 600

2000

16.9

2.1

2.1

2–120

100–1000

63.6

263

55, 128

4–150

2–6

14

2.4

10.2

35 (Fly ash)
7 (Talc)

1.8

9.26

0.2–5.5

100–500

Particle size,
dp [μm]Summary of recent research on gas–solid cyclones. (continued on next page)

MethodTable 40.72–8.64

0.00149–0.00078

0–30

0.008

0.0001–0.0005

1.87, 7.87

Solid loading,CT [kg-solid(kg-gas) –1]

0.00025–0.00059

0.00179–0.000936

0.04

80.7

> 90

Tangential

Tangential

Tangential with slits

Tangential

Tangential

Tangential

RSM—

Euler Lagrange—

Tangential

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

CFD method
Above: Fluid
Below: Solid(Gs:50.0–
385 kg m –2 s –1)

Tangential

Tangential

Tangential

Tangential

Tangential

Tangential

Tangential

Tangential

Axial

Tangential

Tangential

Tangential

Tangential

Tangential

Inlet type

—

86–98

90–95

80–90

97

82–96

86.02–
95.72

99

99.5

95

Particle
recoveryratio [%]

0.125–4.42

0.002–0.010

0.00150.0002(< 1.5 vol%)0.00009–0.0003

Solid concentration,
Cs [kg-solid(m3-gas) –1]

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

0.200 × 0.200(square)2–20 (L/D)

0.33

0.00660.04

0.3302

0.025

4.21–5.07 (H/D)

0.031

0.3, 1.2, 0.9, 0.6,
0.186

0.25

2.5

0.2

0.19

0.3

0.29

0.07

3.35

0.07231, 1.7, 2.3 (L/D)

1.7 (L/D)

8.08

0.2

1,000

Su Y. et al. (2011)

Surmen A. et al. (2011)

Qiu Y. et al. (2012)

Winfield D. et al. (2013)

Shi B. et al. (2013)

Bogodage S.G. and Leung
A.Y.T. (2015)

Hsiao T.C. et al. (2015)

Misiulia D. et al. (2015)

De Souza F.J. et al. (2015a,b)

Yang J. et al. (2015)

Xu W. et al. (2016)

Schneiderbauer S. et al. (2016)

Kozołub P. et al. (2017)

Mazyan W.I. et al. (2017)

Siadaty M. et al. (2017)

Sun X. et al. (2017)

Wang S. et al. (2017)

Wasilewski M. and Brar
L.S. (2017)

Huang A.N. et al. (2018a)

Safikhani H. and Mehrabian P.
(2016)

Safikhani H. et al. (2018)

Zhang N. et al. (2010)

Chu K.W. et al. (2011)

Chu K.W. et al. (2017)

Simulational

Jang K. et al. (2018)

Barrel diameter,
D [m]References

Method

10–30

3.9

20

8.75, 17.5, 35

17

15, 18

8.84

16.34

16.04

14

5.55–9.49

13.4

23

10.67

3.5

0.0025–0.01

1030

16.70, 16.74

8–22

17.98, 20.21

Inlet gas
velocity,vi [m s –1]

0.4–10200–600000

2000

200

20, 21, 23, 19, 13

20, 21, 23, 19, 13

0.339–11.565

1600

1–5

2–6

40–80

0.6–40010

0.5–6.0

0.2–30

2–6

0–18

12.8

Particle size,
dp [μm]Table 4 Summary of recent research on gas–solid cyclones. (continued from previous page)

5–11 Medium to
Coal

0–2.5

1.0–2.7

0.224

Solid loading,CT [kg-solid(kg-gas) –1]–2–1(Gs: 4–8.5 kg m s )0.0016-0.153(< 0.03 vol%)(3 vol%)

0.003

0.001

(< 1.5 vol%)0.0084, 0.0088

Solid concentration,
Cs [kg-solid(m3-gas) –1]

57–75

60–62

> 99 %(> 3 μm)

80.4–
82.4

> 91.11

93

88

99

99.5

> 92

Particle
recoveryratio [%]

Tangential

Tangential

Tangential

Tangential

Axial

Axial

Tangential

Tangential

Tangential

Tangential

Tangential

Tangential

Tangential

Tangential, axial

Tangential

Tangential

Tangential

Inlet type

Euler

Euler Lagrange

Lagrange-Euler
hybrid

CFD method
Above: Fluid
Below: Solid

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

103

Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

4. Recent studies on other gas-solid cyclones
Table 4 summarizes the experimental and numericalstudies on gas–solid cyclones conducted in the last decade. Recently, a number of numerical studies using CFD
simulations have been conducted to investigate the velocities and volume fractions of gases and solids and pressure
drop in cyclones by varying their configurations. Most ofthese experimental and numerical studies were conductedunder dilute conditions (Cs or CT~0.001). Huang A.N. et
al. (2018a) investigated the effect of particle mass loadingon the hydrodynamics of solids and separation efficiency
using the Eulerian-Lagrangian approach with a two-way
coupling method for CFD and compared with the experimental results of laboratory-scale cyclones at C s of
0.0016–0.153 kg-solid (m3-gas) –1 and vi = 15 and 18 m s–1.
They reported that the overall separation efficiency increased from 74.5 % for a conventional cyclone to 80.7 %for a cyclone with a lower cone slit. More detailed experimental and numerical studies under high solids loading
conditions on gas–solid cyclones are expected in the future.

load) are required. In these operations, a high solids separation efficiency and control over the cut-off diameter are
required. We expect for future research, flow behavioursof gas and solids, and separation efficiency of solids in cyclones under non-steady state or transient operation conditions should be investigated.

Acknowledgements
This study was supported by a Grant-in-Aid for Scientific Research B (Kakenhi Kiban B, 17H03451) and the
Takuma research grant.

Nomenclature
As: Total area of the contact surfaces between gas flow and thecyclone wall, As = ÃsπD b2/4 [m 2]
Aw: Sedimentation area of the cyclone wall [m 2]a: Cyclone inlet height [m]b: Cyclone inlet width, b = b D b [m]B: Diameter of the cyclone dust exit, B = B D b [m]5. Conclusions and future prospects

 [m]c: Width of the inlet cutting into the cyclone body, c = cb

Cs: Inlet solid concentration [kg-solid (m3-gas) –1]

In this review, recent progress in high solids-loadinggas–solid cyclones has been summarized. The improved
C-S model proposed by Li S. et al. (2011) is highly usefulfor predicting pressure drop in cyclones. For commercial-­
scale CFBs, 2 to 6 multi-cyclones are often used in parallel. However, the non-uniform distribution of solids in theparallel section is a problem. Mo et al. investigated the effect of wall friction and solid acceleration on the non-­uniform distribution of gas–solids flow and found that the
inflection point has a significant influence on the maldistribution of gas–solids in two cyclones in parallel. Zhang
C. et al. (2016) found that the phase graph of the stabilityof uniform distribution/maldistribution of solids in twoparallel cyclones as functions of CT (kg-solid (kg-gas) –1)
and dr.
To improve the scale-up methodology, Mirek P. (2018)
summarized and modified the Muschelknautz model byapplying five sets of scaling relationships and found that
all the employed sets of scaling relationships resulted in avery high separation efficiency (> 99.7 %). The GLME
model developed by Wang J. et al. (2019) can predict
grade efficiency with a large prediction variability.
It is expected that CFB boilers will be used for biomass
co-combustion to reduce CO2 emissions due to power
generation. In waste-treatment plants, CFB incinerators
may be used in the future because of their high thermal
efficiency and operability. In CFB boilers used for power
generation, non-steady-state operations (rapid changes in104

CT: Mass flow rate ratio between solids and gas [kg-solid(kg-gas) –1]
CT,inf: Solids loading at the inflection point [kg-solid (kg-gas) –1]
d: Feed particle diameter [m]de: Cut size for separation at wall [m]dr: Dimensionless vortex finder diameter [–]d32: Sauter mean particle diameter [m]d50: Mass mean particle diameter in feed [m]d50,A: Median particle diameter in feed [m]D b: Cyclone barrel diameter [m]D h: Cyclone hopper diameter, D h = D h D b [m]Dc: Diameter of core flow, Dc = 2rc [m]De: Cyclone outlet diameter, De = D e D b [m]Dr: R iser hydraulic mean diameter, 4A(cross-sectional area ofthe flow)/P(wetted perimeter of the cross-section) [m]e: Noise vector [–]f: Friction coefficient [–]fair: Friction coefficient for dust-free gas flow [–]Fr: Froude number based on Dr, (U02/gDr) [–]Fr, H : Froude number based on H, (vi2/gH) [–]g: Gravitational acceleration [m s –2]
Gs: Solids mass flux [kg m–2 s –1]
Hb: Cyclone barrel height, Hb = H b D b [m]
H: Cyclone body height, H = H D b [m]Chihiro Fushimi et al. / KONA Powder and Particle Journal No. 38 (2021) 94–109

Hh: Cyclone hopper height, Hh = H h D b [m]ηtot: Total separation efficiency [–]k i: Correction coefficient of expansion loss [–]ηvtx: Separation efficiency in cyclone vortex [–]Klim: Constant for calculating the limited load ratio [–]l: Insert depth of the cyclone outlet, l = l D [m]ηwall: Separation efficiency at wall [–]bn: Swirl exponent [–]ϕi: Random effect of the ith component [–]σi: Standard deviation of ϕi [–]σξ: Size deviation of particle diameter at inlet [–]Δp1: Expansion loss at the cyclone inlet [Pa]ψ: Gas fraction in cyclone 1 [–]Δpb: Cyclone body pressure drop [Pa]γ: Solids fraction in cyclone 1 [–]Δpc: Cyclone pressure drop [Pa]Δpx: Outlet pressure drop [Pa]Abbreviations

Q: Cyclone inlet gas flow rate [m3 s –1]
r: Radius of cyclone barrel [m]CFB: Circulating fluidized bed

rc: Radius of core flow, rc = rc r [m]CFD: Computational fluid dynamics

RAi(d): Residue of the inner feed [–]CPFD: Computational particle fluid dynamics

Re: Reynolds number, viD bρg/μg [–]Rep: Particle Reynolds number, U0 d32ρg/μg [–]C-S: Chen and Shi

RF(d): Residue of the emitted dust [–]DEM: Discrete elemental method

Stk in,i: Stokes number [–]ECT: Electrical capacitance tomography

uT: Terminal velocity of particles [m s ]FCC: Fluid catalytic cracking

U0: Superficial gas velocity [m s ]GLME: Generalized linear mixed-effects

3 –1
V : Gas flow rate [m s ]iG-CLC: In situ gasification chemical looping combustion–1–1

vi: Gas velocity at the cyclone inlet [m s –1]

PSD: Particle size distribution

vz: Axial gas velocity [m s –1]
vze: Axial gas velocity in the outlet annular region [m s –1]
vzw: Axial gas velocity near the outlet wall [m s –1]
vθ: Tangential gas velocity, vθ = vθ vi [m s –1]vθ : mean tangential velocity in the outlet tube [m s –1]vθc: Tangential gas velocity at the radius [m s ]–1vθCS: Tangential gas velocity at the imagined control surface[m s –1]vθe: Tangential gas velocity in outlet annular region [m s –1]vθw: Tangential gas velocity near the cyclone wall, vθw = vθwvi[m s –1]
Tangential gas velocity near the cyclone wall for dustv’θw: 
laden gases [m s –1]
y: Exponent for calculating the limited load ratio [–]z e : Mean centrifugal acceleration at the reference radius [m s –2]

Greek alphabets
μ: Expected grade-efficiency vector [–]μe: Initial load [kg kg–1]
μg: Gas viscosity [Pa s]
μlim: Limited load ratio [kg kg–1]
ρg: Gas density [kg m–3]
ρp: Particle density [kg m–3]
η: Observed grade-efficiency vector [–]ηF(d): Grade efficiency [–]References
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Authors’ Short Biographies
Chihiro Fushimi
Chihiro Fushimi is Associate Professor of Department of Chemical Engineering at
Tokyo University of Agriculture and Technology. He obtained B.S. M.S. and Ph.D. in
Chemical System Engineering from The University of Tokyo, Japan in 1999, 2001 and
2004, respectively. He was a visiting scholar at University of Hawaii at Manoa, USA, a
researcher at the Research Institute of Innovative Technology for the Earth, Japan andResearch Associate of Institute of Industrial Science at The University of Tokyo. He is
also a Visiting Professor at Curtin University of Technology, Australia in 2019. He has
20 years of research experience related to thermochemical conversion of carbonaceous
materials, fluidization, and process design and development of power generation and biochemicals plants with 75 refereed journal publications and 4 book chapters.
Kentaro Yato
Kentaro Yato is a master student of Department of Chemical Engineering at Tokyo
University of Agriculture and Technology. He holds B.S. in Chemical Engineering from
Tokyo University of Agriculture and Technology, Japan. His current research topic is development of an efficient gas-solid separator under high solids loading conditions.
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 of Tokyo in 2006. Then, he became Assistant Professor in 2007 and Associate Professor in 2008
in The University of Tokyo. He is Visiting Reader at Imperial College London since 2016.
He extensively studies modelling of granular flows, multi-phase flows and the heat transfer,and besides the parallel computation techniques. He is a world-leading professor in computational granular dynamics, and hence, has delivered lots of invited lectures in conferences.
He holds important posts in powder technology community, such as Director of Society of
Powder Technology of Japan and Head of Simulation & Modelling Division in Associationof Powder Process Industry and Engineering, JAPAN. At present, he is also Associate Editor of Chemical Engineering Science and Editor of Granular Matter.
Takashi Kawano
Takashi Kawano currently works in Takuma Co.,Ltd. He obtained Ph.D. in Civil Engineering from Tohoku University, Japan. He has experiences on research, design and development of anaerobic digestion and thermochemical conversion of biomass. He is now
involved in biomass power plant design.

Teruyuki Kita
Teruyuki Kita is a section manager of the maintenance department in Takuma
Co.,Ltd. He earned his Ph.D. degree from Tokyo University of Agriculture and Technology in 1999. He has about 25 years’ experience in design and development of the fluidized bed boiler. He has currently managed the section for maintenance and operation
support of Boiler Power Generation plants.

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KONA Powder and Particle Journal No. 38 (2021) 110–121/https://doi.org/10.14356/kona.2021008

Review Paper

Screening of Ternary Intermetallic Catalysts Is Possible Using
Metallurgical Synthesis: Demonstration on Heusler Alloys †Takayuki Kojima 1,2*, Satoshi Kameoka 2 and An-Pang Tsai 2#
1
2

Frontier Research Institute for Interdisciplinary Sciences (FRIS), Tohoku University, Japan
Institute of Multidisciplinary Research for Advanced Materials (IMRAM), Tohoku University, Japan

Abstract
Intermetallic compounds are becoming hot materials as catalysts because they show unique catalytic properties
that originate from a unique electronic structure and an atomic ordered surface. Ternary intermetallic catalysts
have rarely been reported, which is likely due to the difficulty in synthesizing their supported nanoparticles, thetypical form for catalysis research; however, there could be novel catalysts in ternary systems because they havemuch more elemental combinations than binary systems. They are expected to exhibit novel properties due to thesynergy between three elements. Metallurgical methods, such as arc-melting, can easily synthesize intermetallic
compounds even in ternary (or more) systems if they are thermodynamically stable. Thus, only metallurgicalsynthesis enables screening for ternary intermetallic catalysts. The catalyst screening of Heusler alloys, which area group of ternary intermetallic compounds popular in other research fields, such as magnetics, has been
conducted using metallurgical synthesis. The screening revealed fundamental catalytic properties of Heusler
alloys for several reactions and identified good catalysts for the selective hydrogenation of alkynes. The
systematic control of catalysis was also demonstrated by the substitution of fourth elements using a feature of
Heusler alloys. This paper describes the importance of ternary intermetallic catalysts with practical examples ofHeusler alloy catalysts and discusses future prospects.
Keywords: intermetallic catalyst, Heusler catalyst, intermetallic compound catalyst, Heusler alloy catalyst,
ternary intermetallic compound, Heusler alloy

1. Introduction
A “catalyst” is defined as a material that promotes achemical reaction but is not consumed and not irreversibly
modified during the reaction. The mechanism of reaction
promotion occurs when a reaction pathway changes intoanother pathway with a lower activation barrier, as illustrated in Fig. 1. The change in the pathway sometimes
changes the product species, as shown in Fig. 1(b,c). Thus,
catalysts are necessary to make a massive amount of products with a lower energy cost and fewer waste materials(unfavorable byproducts) and to remove harmful species.
A chemical reaction, including elementary steps of a catalytic reaction, proceeds through an exchange of electrons.
Therefore, an electronic structure of catalysts dominates a

†

1
2

*

#

Received 3 March 2020; Accepted 16 March 2020
J-STAGE Advance published online 29 April 2020
6-3, Aza Aoba, Aramaki, Aoba-ku, Sendai 980-8578, Japan
2-1-1, Katahira, Aoba-ku, Sendai 980-8577, Japan
Corresponding author: Takayuki Kojima;
E-mail: takayuki.kojima.b4@tohoku.ac.jp
TEL: +81-22-217-5723 FAX: +81-22-217-5723
An-Pang Tsai passed away on May 25, 2019.

110

catalytic reaction. Obviously, a surface is also importantfor solid-state catalysts because the reaction proceeds on
the surface.
Intermetallic compounds have a unique electronic structure completely different from a mixed state of component
metals (Tsai A.P. et al., 2004; 2017) and have an atomicordered structure even at the surface (Furukawa S. andKomatsu T., 2017). Thus, they are becoming hot materials
for catalytic applications (Armbrüster M., 2014; Tsai A.P.
et al., 2017; Furukawa S. and Komatsu T., 2017). Althoughalmost all reports on intermetallic catalysts have discussed
binary systems, there could be novel catalysts in ternary
systems because there are much more potential elemental
sets: 85,320 ternary and 3,240 binary systems are possible
among 81 elements, and 13,026 ternary and 6,441 binary
compounds have been validated according to Dshemuchadse J. and Steurer W. (2015). Ternary intermetallic
catalysts are also expected to exhibit novel properties dueto the synergy between three elements. Catalyst research
is mostly conducted by chemists, typically using nanoparticles supported by oxide fine particles; however, thesynthesis of ternary intermetallic nanoparticles requiresconsiderable efforts to identify the appropriate conditions.

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Takayuki Kojima et al. / KONA Powder and Particle Journal No. 38 (2021) 110–121

Fig. 1 Schematic illustration of a binding reaction between A and B atoms (a) without a catalyst, (b) with a catalyst, and (c) with another catalyst.
Blue Gaussian-like lines schematically represent the height of the activation energy for each elementary step. The activation barriers in all elementary steps in (b) and (c) are lower than that in (a). The AB molecule desorbs from the surface easily in (b) but hardly in (c). The ABA molecule forms
more easily than AB in (c).

The use of nanoparticles is impossible for the screening ofternary intermetallic catalysts with changing component
elements. This is the reason for the lack of studies on ternary systems.
On the other hand, metallurgical methods, such asarc-melting, can easily synthesize most intermetallic compounds even in ternary (or more) systems if they arethermodynamically stable. Intermetallic compounds areusually brittle, being easily crushed into powder. Thus, thescreening of ternary intermetallic catalysts is possible. We
have investigated Heusler alloys as new catalysts using
metallurgically synthesized samples (Kojima T. et al.,2017, 2018, 2019a, 2019b). Heusler alloys are a group of
ternary intermetallic compounds described as X2YZ with
L21 structure (body-centered cubic basis, called “fullHeusler” in a narrow sense), as shown in Fig. 2 (Kojima
T. et al., 2018) (there are also other types, including XYZwith C1b structure, which lacks one of two X sites in theL21 structure, called “half-Heusler”) (Kojima T. et al.,2019a). They are popular as magnetic (spintronic) (GrafT. et al., 2016), thermoelectric (Nishino Y. et al., 2001),
and shape memory materials (Planes A. et al., 2009), andthey have been studied as topological materials nowadays(Manna et al., 2018). Although their catalytic properties
were unknown, we hypothesized that there are novel catalysts in the numerous elemental sets (Fig. 2). The abundant
choice of elements also enables the substitution of various
elements in a wide composition range (e.g. X2YZ1–xZ’x), bywhich electronic structures can be fine-tuned. This tuning is
a common practice in the aforementioned fields but is also
applicable for the precise control of catalytic properties(called the ligand effect, Fig. 2). Obviously, the fourth
element substitution changes the type of surface element,by which catalytic properties can be controlled (called theensemble effect, Fig. 2). Considering these advantagesof Heusler alloys, we have conducted the screening forvarious reactions to reveal their fundamental catalytic
properties and to identify novel catalysts.

2. Sample preparation and characterization
Heusler alloy (X = Fe, Co, Ni, or Cu; Y = Ti, Mn, or Fe;

Fig. 2 Crystal structure of Heusler alloys (L21 type), schematic illustration of elemental substitution effects, and typical components of X, Y,
and Z. DOS means electron density of states. Components are not restricted to the periodic table in the figure; for example, Fe and Mn
sometimes occupy Y and X sites, respectively, and lanthanoids, alkali
metals, and alkaline earth metals can be components (Yin M. et al.,2016). The figure was excerpted from Ref. (Kojima T. et al., 2018)licensed under CC BY-NC (http://creativecommons.org/licenses/
by-nc/4.0).

Z = Al, Si, Ga, Ge, or Sn) ingots were prepared from puremetal pieces (purity: > 99.9 %) by arc-melting and wereannealed in Ar atmosphere. For the annealing, the ingot
was put on (into) an alumina piece (tube) or wrapped bya Ta or Mo foil in a quartz tube that was then sealed using
a hydrogen gas burner after a cycle of evacuation and Ar
purge. Although an annealing condition depends on alloys,
we currently adopt 1000 °C 48 h for homogenizing followed by 600 °C 72 h for atomic ordering in many cases.
The condition for each sample used in previous works has
been described in Kojima T. et al. (2017) and (2018). The
ingot was crushed using a pestle and mortar into powderthat was then sieved to 20–63 μm for a catalytic reactionand < 20 μm for a structural evaluation using X-ray diffraction (XRD).
Before the XRD, a sample powder was annealed at
600 °C for 1 h to remove the strain. The XRD revealed that
all the samples used in the published works (Kojima T. et111

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al., 2017, 2018, 2019a, 2019b) were (almost) single phasewith a highly ordered L21 structure, although few samples
had a tiny amount of second phases, as shown in Fig. 3.
Some Heusler alloys disorder their atomic arrangements byheating, transforming the phase from L21 to B2 (disordering between Y and Z atoms) followed by A2 (disordering
between all atoms), which is referred to as “ordered alloys”
rather than “intermetallic compounds” (Kojima T. et al.,2019a). Thus, a degree of ordering should be evaluated. A
long-range order parameter is typically used for the evaluation, which is estimated from an XRD intensity ratio of asuperlattice and fundamental peaks (Warren B.E., 1990).
Webster’s model using parameters of S and α is easily
usable for Heusler alloys, where a high S means a highordering of X atoms and a low α means a high ordering of
Y and Z atoms (Webster P.J. and Ziebeck K.R.A., 1973).
All the samples had high S and low α (Kojima T. et al.,2017). Note that the superlattice peaks, such as 111 and 200
peaks, are essentially weak when the atomic numbers of thecomponents are close, such as Co2FeGe (Fig. 3), because
an intensity in the superlattice peaks is proportional to thesquare of the difference of the atomic numbers.
A specific surface area of catalysts was estimated using
the Brunauer-Emmett-Teller method for Kr adsorption
isotherms at 77 K, which is a typical method for surface
area estimation. Although the values per weight distributed
from 0.047 to 0.13 m2 g–1 depending on atomic weights,
the values per volume were similar (4.0–8.3 × 105 m–1) due
to the sieving into 20–63 μm, as shown in Table 1.
Catalytic tests were conducted using a flow reactor, as
shown in Fig. 4. An appropriate amount of catalyst pow-

Fig. 3 XRD patterns for Ni2TiAl (red) and Co2FeGe (blue) powders.
Intensity was normalized by the height of a 220 peak. Co2FeGe showeda peak of a second phase, which was likely CoGe.

112

ders was set on quartz wool in a quartz tube. Before thereactions, the catalyst was heated at 600 °C for 1 h underH2 gas flow to remove surface oxides and strain. A gaseous
reactant was introduced from a mass flow controller withan inert carrier gas. A liquidous reactant was introduced
using a plunger pump with the carrier gas, followed byevaporated using an electric furnace surrounding thequartz tube so that the reaction took place in the gas
phase. Unreacted and produced gaseous species and theirconcentrations were analyzed using a gas chromatograph.
When the amount of gas products was large (e.g. > 10 % ofcarrier gas), a flow meter was used for analysis along with
Table 1

Specific surface area of catalysts.

Catalyst

Surface area perweight [10 –2 m 2·g–1]

Surface area pervolume [105 m–1]

Fe2TiSn

7.1

6.0

Co2TiAl

11

7.3

Co2TiGe

8.4

6.8

Co2TiSn

7.0

5.9

Co2MnSi

8.8

6.5

Co2MnGa

6.1

5.1

Co2MnGe

6.7

5.7

Co2MnSn

5.6

5.1

Co2FeGa

4.7

4.0

Co2FeGe

5.4

4.7

Ni2TiAl

13

8.3

Ni2TiSn9.5

7.9

Ni2MnSn

8.9

7.7

Cu 2TiAl

12

7.4

Fig. 4 Schematic illustration of a catalytic reaction system. The illustration is highly simplified.

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the gas chromatograph (used in section 5). The details of
the reaction conditions have been described in the original
papers (Kojima et al., 2017; 2018; 2019b).

Fig. 6(c) due to high resistivity to oxidation. These results
indicate that not only activity but also durability can becontrolled by choosing the appropriate X, Y, and Z.

3. Oxidation of carbon monoxide

4. Hydrogenation of alkynes

As a simple oxidation reaction, the oxidation of carbon
monoxide (CO + 1/2O2→CO2) was conducted (Kojima etal., 2017), which is an important reaction for removal of
harmful CO gas produced from combustors, including automobile engines. Co-based Heusler alloys showed higher
activity than other alloys, as shown in Fig. 5 (higher activity means higher conversion (reaction rate) at lower temperature). A hierarchy of activity of X in X2TiSn, X2TiAl,
and X2MnSn seemed roughly similar to that of pure Fe,
Co, Ni, and Cu powders. This indicates that a main active
element in Heusler alloys is X for CO oxidation. During acycle of heating and cooling, the hysteresis of the activity
was observed in most alloys, as shown in Fig. 6(a,b). Thiswas due to the irreversible oxidation of catalysts, which
was indicated by the excess consumption of O2; however, Co2TiSn showed very small hysteresis, as shown in

4.1 Catalytic properties
As a simple reduction reaction, the hydrogenation ofalkynes (CnH2n–2 + aH2→bCnH2n + (a–b)/2CnH2n+2) was
conducted (Kojima et al., 2017, 2018); such hydrogenationof hydrocarbons is important in various fields, including
petrochemical industry. For propyne (C3H4) hydrogenation,
most Heusler alloys showed very low activity (Kojima etal., 2017). This is likely due to the residual surface oxides
of Al, Si, and Ti and due to the surface segregation of Sn.
Co2(Mn or Fe)(Ga or Ge) alloys were active. Interestingly,
Co2MnGe and Co2FeGe showed high alkene selectivity(fraction of alkene in products: CnH2n/(CnH2n + CnH2n+2))(Kojima et al., 2018). Fig. 7 shows alkyne conversion (percentage of reacted alkyne) and alkene selectivity during thehydrogenation of alkynes (C3H4, C2H2) in the presence ofFig. 5 CO conversion (percentage of reacted CO) in CO oxidation by (a) X2TiSn, (b) X2TiAl, (c) X2MnSn, and (d) pure X catalysts using a reactantof [1.2 %CO / 0.4 %O2 / 98.4 %He]. 66.7 % is the ideal CO conversion because the reactant is CO-rich (CO:O2 = 3:1). After Ref. (Kojima T. et al.,2017), reproduced with permission by ACS (https://pubs.acs.org/doi/abs/10.1021/acsomega.6b00299). Further permissions related to the material excerpted should be directed to the ACS.

Fig. 6 CO conversion in CO oxidation by (a) Fe2TiSn, (b) Ni2TiSn, and (c) Co2TiSn using a reactant of [1.2 %CO / 0.4 %O2 / He balance] during
heating and cooling cycles. After Ref. (Kojima T. et al., 2017), reproduced with permission by ACS (https://pubs.acs.org/doi/abs/10.1021/
acsomega.6b00299). Further permissions related to the material excerpted should be directed to the ACS.

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Fig. 7 Alkyne conversion and alkene selectivity in the reaction using
the reactant of (a1,b1,c1) [0.1 %C3H4 / 10 %C3H6 / 40 %H 2 / 49.9 %He]or (a2,b2,c2) [0.1 %C2H 2 / 10 %C2H4 / 40 %H 2 / 49.9 %He] for (a1,a2)
Co2MnGe, (b1,b2) Co2FeGe, and (c1,c2) Co2FeGa. After Ref. (Kojima
T. et al., 2018) licensed under CC BY-NC (http://creativecommons.org/
licenses/by-nc/4.0).

Fig. 8 (a1,b1,c1) C3H4 conversion and C3H6 selectivity in the reaction
using the [0.1 %C3H4 / 40 %H 2 / 59.9 %He] reactant and (a2,b2,c2)
C3H6 conversion in the reaction using the [0.1 %C3H6 / 40 %H 2 /59.9 %He] reactant for (a1,a2) Co2MnGe, (b1,b2) Co2FeGe, and (c1,c2)
Co2FeGa0.75Ge0.25. After Ref. (Kojima T. et al., 2018) licensed under CC
BY-NC (http://creativecommons.org/licenses/by-nc/4.0).

a large amount of alkenes (C3H6, C2H4). In general, alkene
selectivity decreases with an increase in alkyne conversion
as Co2FeGa (Fig. 7c1,c2), which is due to the promotion ofalkene adsorption along with the consumption of strongly
adsorbed alkyne molecules. In contrast, Co2MnGe andCo2FeGe kept high selectivity even when the conversion
was high enough (Fig. 7a1–b2). Fig. 8 shows the results of
C3H4 hydrogenation without C3H6 and C3H6 hydrogenation
without C3H4. Fig. 8 (a1–b2) indicate that Co2MnGe andCo2FeGe essentially do not have ability to hydrogenate
alkenes in contrast to Co2FeGa0.75Ge0.25 (Fig. 8c1,c2) as an
example of ordinary catalysts.
The selective hydrogenation of alkynes in alkene feedstocks is a crucial process to remove alkyne impurities
that hinder the polymerization of alkenes in the process to
produce polyalkenes, such as polyethylene (Borodziński
A. and Bond G.C., 2006, 2008). In industry, the selectivehydrogenation is achieved by the precise control of reac-tion conditions, including temperature, pressure, H2 concentration, and the introduction of CO gas as an inhibitor
because Pd-based practical catalysts do not have essential
selectivity. Therefore, these Heusler alloy catalysts would
be useful in terms of replacing noble metals.

114

4.2 Elemental substitution effects
The effects of elemental substitution were investigatedfor C3H4 hydrogenation using Co2MnxFe1–xGayGe1–y catalysts (Kojima et al., 2018). Fig. 9 shows the results of the
Mn and Ga substitutions for Fe and Ge, respectively, of
Co2FeGe. The reaction rate and the selectivity systematically changed with the amount of the substitution (Fig. 9a).
The Mn substitution increased the reaction rate while maintaining high selectivity. The Ga substitution significantly
increased the reaction rate but decreased selectivity.
An experimental apparent activation energy (Ea)Takayuki Kojima et al. / KONA Powder and Particle Journal No. 38 (2021) 110–121

changed with a d band center (εd) calculated for bulk
states (Fig. 9b). εd means an average energy of d states,
dominating a strength between adsorbates and metals; thatis, higher (lower) εd makes higher (lower) energy levelsof the adsorbates, resulting in lower (higher) occupationof anti-bonding states. Thus, εd affects relevant energy
quantities in elementary steps, such as adsorption energy
and activation energy (Nørskov J.K. et al, 2011). The goodcorrelation between Ea and εd in Fig. 9(b) proves that theelectronic modification by elemental substitution certainly
affected the elementary steps. Actually, the fine modification of electronic structures was achieved in good accordance with the calculated results, which was indicated byphotoelectron spectroscopy and first-principles calculation,
as shown in Fig. 10. These results indicate that a precise
control of catalytic properties through the fine-tuning ofelectronic structures is possible by elemental substitutionof Heusler alloys.
As a result of further experiments and analyses, including the estimation of reaction orders and the deduction ofreaction mechanisms, the Mn and Ga substitution effects
were concluded to be mainly ligand and ensemble effects(Fig. 2), respectively (Kojima et al., 2018). In other words,
Mn substitution changes catalysis through the modificationof the whole electronic structure, while Ga substitutionchanges catalysis through the replacement of surface Ge
atoms by Ga atoms that have a greater ability to adsorb
molecules. In addition, Mn-Fe substitution and Ga-Ge
substitution affect catalysis independently. For example,
Mn substitution for Co2FeGa caused a similar change incatalysis to that for Co2FeGe, while Ga substitution for
Co2MnGe caused a similar change in catalysis to that for
Co2FeGe (Kojima et al., 2018). Therefore, the fine-tuningof catalysis is possible depending on the target reaction by(1) choosing a main active element X and sub-elements Y
and Z, (2) substituting Y to optimize electronic structures,(3) and substituting Z to optimize surface ensembles.
Furthermore, this precise controllability would be usefulto reveal a general relation between electronic structuresand catalysis, which are only partially understood thus far.

5. Steam reforming of methanol
The steam reforming of methanol (SRM: CH3OH + H2O→3H2 + CO2) is a candidate to produce hydrogen from asafe hydrogen carrier, which is often studied using intermetallic catalysts (Tsai A.P. et al., 2004, 2017; Armbrüster
M. et al., 2014; Furukawa S. and Komatsu T., 2017). As
another type of reaction different from those mentioned
above, SRM was used to investigate Heusler alloy catalysts(Kojima et al., 2019b). Among the 14 Heusler alloys listed
in Table 1, most alloys did not produce H2 at a low temperature of ≤ 450 °C, as shown in Fig. 11(a–d). Several alloys

Fig. 9 Elemental substitution effects on (a) C3H4 reaction rate at 50 °C
and C3H6 selectivity at 200 °C and (b) Ea and εd in the reaction using
the [0.1 %C3H4 / 40 %H 2 / 59.9 %He] reactant. Mn substitution for Fe
and Ga substitution for Ge of Co2FeGe are represented. The rate is relative to that of Co2FeGe per surface area. The figure was excerpted from
Ref. (Kojima T. et al., 2019a) licensed under CC-BY, which was remadeusing the data in Ref. (Kojima T. et al., 2018) licensed under CC BY-NC(http://creativecommons.org/licenses/by-nc/4.0).

did not produce H2 even at 600 °C, as shown in Fig. 11(e).
Surface microstructural changes, such as the formation offine particles, were observed in most alloys that showed acertain activity, as shown in Fig. 12(a–d). In many catalysts consisting of group 8–10 metals, the first step of SRM
is the decomposition of methanol (CH3OH→2H2 + CO)(Sá S. et al., 2010). This reaction is structure sensitive; thatis, larger particles show a lower reaction rate per surface
area. Thus, the diameter of 20–63 μm was likely too large,
while the precipitation of fine particles yielded activity.
In particular, Ni2TiAl exhibited high activity due to theformation of Ni fine particles, as shown in Fig. 13(a,b).
A higher activity at 400 °C during cooling than heating
implies fine particle precipitation at ≥ 450 °C (Fig. 13a).
A Ni3Al catalyst is known to precipitate Ni fine particles
during methanol decomposition through the selective oxidation of Al (Chun et al., 2006). On the other hand, Ni2TiAl
likely precipitates Ni fine particles through the selective
oxidation of Ti, as shown in Table 2. Co2TiAl showeda similar change in catalytic properties along with fineparticle precipitation (Kojima et al., 2019b). In contrast,
Cu2TiAl did not form Cu fine particles as indicated by thedecrease in the surface Cu composition after the reaction

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Fig. 10 (a) DOS calculated for the bulk and (b) valence band spectra of hard X-ray photoelectron spectroscopy (HAXPES). The figure was excerpted from Ref. (Kojima T. et al., 2018) licensed under CC BY-NC (http://creativecommons.org/licenses/by-nc/4.0).

Fig. 11 Production rates of H 2 and byproducts (CO, CO2, CH4) in the reaction using a reactant mixture of CH3OH and H 2O (molar ratio 2:3) fed at
0.07 g min –1 corresponding to 20 μmol s –1 of CH3OH. After Ref. (Kojima T. et al., 2019b), reproduced with permission by ACS (https://pubs.acs.org/
doi/abs/10.1021/acsomega.9b01837). Further permissions related to the material excerpted should be directed to the ACS.

Fig. 12 Surface microstructures after the SRM reaction observed by scanning electron microscopy for (a) Co2MnSn, (b) Ni2MnSn, (c) Co2TiSn,
and (d) Ni2TiSn.

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Table 2 Surface composition [%] of X, Y, and Z in X2YZ before andafter SRM reaction analyzed by X-ray photoelectron spectroscopya.

Catalyst

ReactionXYZ

Ni2TiAl

Before

8

19

74

After

13

36

51

Before

13

19

68

After

23

46

31

Before

13

11

76

After

4

41

56

Co2TiAlCu 2TiAla

After Ref. (Kojima T. et al., 2019b), reproduced with permission by
ACS (https://pubs.acs.org/doi/abs/10.1021/acsomega.9b01837). Further permissions related to the material excerpted should be directedto the ACS.

Table 3 Standard Gibbs energy of oxide formation (ΔG°) [kJ (O21 mol) –1] at 400 °Ca.

Element

Oxide

ΔG°

Fe

Fe3O4

–444

Co

CoO

–373

Ni

NiO

–355

Cu

Cu2O

–239

Ti

TiO2 (rutile)

–821

Mn

MnO

–665

Al

Al2O3 (α)

–976

Sn

SnO2

–442

Fig. 13 Results of SRM for (a,b) Ni2TiAl and (c,d) Ni2TiAl with O2
pretreatment. (a) and (c) show the production rates of H2 and byproducts during heating and of H 2 during cooling. (b) and (d) are surface
microstructures after the reaction. After Ref. (Kojima T. et al., 2019b),
reproduced with permission by ACS (https://pubs.acs.org/doi/abs/
10.1021/acsomega.9b01837). Further permissions related to the material
excerpted should be directed to the ACS.

a

After Ref. (Kojima T. et al., 2019b), reproduced with permission by
ACS (https://pubs.acs.org/doi/abs/10.1021/acsomega.9b01837). Further permissions related to the material excerpted should be directedto the ACS.

(Table 2), thus not gaining activity. Standard Gibbs energies of oxide formation (ΔG°) are similar between Co
and Ni but fairly different between them and Cu, as shownin Table 3. This is likely the reason for the difference inthe structural change. Co2MnSn and Ni2MnSn showedsimilar structural changes (Fig. 11a,b) (Kojima et al.,2019b). Co2TiSn and Ni2TiSn also showed similar structural changes (Fig. 11c,d), but Fe2TiSn showed a differentchange, likely due to the difference of ΔG° between Co, Ni,
and Fe (Kojima et al., 2019b). These results indicate thatthe tendency of structural changes through oxidation is determined by a balance of the oxidizability of components.
The activity of Ni2TiAl was enhanced by preheating under[1 %O2/99 %He] flow at 500 °C for 1 h before the reaction
due to the enhancement of the Ni fine particle precipitation,
as shown in Fig. 13(c,d). Co2TiAl showed similar resultsby O2 preheating (Kojima et al., 2019b).
Many alloys mainly produced CO as a byproduct, meaning that methanol decomposition predominantly occurred.

Fig. 14 Production rates of H2 and CO in the decomposition of methanol fed at 0.04 g min –1 (20 μmol s –1) for Co2FeGe. After Ref. (Kojima
T. et al., 2019b), reproduced with permission by ACS (https://pubs.acs.
org/doi/abs/10.1021/acsomega.9b01837). Further permissions related tothe material excerpted should be directed to the ACS.

In contrast, all the alloys containing Mn mainly produced
CO2 as a byproduct (Fig. 11a,b). During the reaction, allthese alloys formed MnO (Kojima et al., 2019b), which catalyzes a water-gas shift reaction (CO + H2O→H2 + CO2),
eventually achieving SRM by converting CO that was
produced by methanol decomposition. This study revealed
a variety of structural changes through oxidation, whichsuggests a development of multi-functional catalysts
consisting of several phases using Heusler alloys as a117

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precursor. Intermetallic compounds are atomically homogeneous in essence, even in ternary systems. This is anadvantage of being used as a precursor of catalysts withless inhomogeneity.
Co2FeGe was active for methanol decomposition using apure methanol reactant without steam, as shown in Fig. 14.
Interestingly, the initial metallic state was likely active because a certain activity appeared even at ≤ 400 °C and because a significant structural change was not observed after
the reaction at 600 °C (Kojima et al., 2019b). A specificelectronic structure or a specific reaction field created byatomic ordered structures might be suited to this reaction.
The origin of the activity is attractive to be studied.

6. Perspectives
For other reactions, we are currently investigating thedehydrogenation of 2-propanol and the methanation ofcarbon monoxide. Screening for the dehydrogenation of
methylcyclohexane (MCH) and its reverse reaction, thehydrogenation of toluene, was also conducted; however, noactivity was observed in the tested alloys. These molecules,
which have a six-membered ring, are highly stable, andmost studies on MCH dehydrogenation have used Pt-based
nanoparticles (Nakano A. et al., 2017). Thus, the diameterof 20–63 μm (surface area: ca. 0.1 m2·g–1) was considered
too large to exhibit activity. Aside from an extreme case,such as MCH dehydrogenation, even ammonia synthesis,
which must break a very stable triple bond of N2, can beachieved by good intermetallic catalysts (LaCoSi, LaRuSi)
with a surface area around 1 m2·g–1 (Gong Y. et al., 2018;
Wu J. et al., 2019). Intermetallic compounds are usuallybrittle and thus easily crushed into powder with surface
areas over 1 m2·g–1 by ball-milling, which may reduce
the particle size down to < 100 nm depending on milling
conditions as well as other milling methods, including beadmilling and jet milling (Yokoyama T. and Huang C.C.,
2005). Thus, screening is possible using metallurgicallysynthesized powders for most reactions without extremely
stable reactants.
Although we have adopted arc-melting for synthesis,
powder metallurgical methods are applicable, such as sintering and mechanical alloying, from pure metal powders.
Simply, sintering can be done by annealing tablets made bypressing, for example, at > 10 MPa. Mechanical alloying
can be done by ball-milling for a long time, for which theequipment is much less expensive than that for arc-melting.
Instead of sealing the quartz tubes for annealing, using a tubular furnace under N2 flow is simple, which can be easily
self-built, although air contamination should be excluded
for easily oxidizable powders. For arc-melted ingots,
annealing, for example, at 800 °C for 48 h is sufficient for
many systems, though we have adopted longer conditions

118

to surely obtain high-quality samples. The variation ofquality among samples in different systems is smaller inmetallurgical synthesized powders than chemically synthesized nanoparticles. This is an advantage for the correct
discussion with reducing uncertainty. This is also suitable
for an informatic approach to predicting new catalysts
because a smaller variation of quality reduces the numberof data sets required to ensure accuracy.
After identifying new catalysts by screening, a specificsurface area must be enlarged for practical application.
Supported nanoparticles are normally used but not easy
to synthesize in ternary intermetallic compounds, as mentioned; however, the synthesis is possible for experts and/or through considerable effort. Supported Co2FeGa andCu2NiSn nanoparticles were successfully synthesized with
sufficient quality: the L21 structure, small second phases,a small size, and a small size distribution (Basit L. et al.,2009; Wang C. et al., 2010, 2012, 2014; Wang C.H. et al.,2010; Ernst S. et al., 2019). One reason for the lack of reports on ternary intermetallic nanoparticles is that there wasno specific application until recently. Thus, research to develop ternary intermetallic nanoparticles would increase inrelation to catalytic applications. Recently, a novel method
to synthesize supported nanoparticles has been developed,
which achieved the preparation of several nanometer-sized
Au, Pt, Ag, Cu, and Ni particles from micrometer-sized
powders by ball-milling under a gas flow of CO/O2/He(Schreyer H. et al., 2019). This dry metallurgical method
can be attractive for intermetallic nanoparticles.
Aside from our studies, there are few early studies
on Heusler alloy catalysts: the theoretical calculation
for ammonia dissociation by Ni2MnGa and Co2CrGe(Senanayake N.M., 2016) and the screening of supported
Heusler alloy catalysts (Mueller U. et al., 2018). BASF
did not obtain a sufficient quality of samples in the latterstudy but then succeeded in the development of the aforementioned Cu2NiSn nanoparticles (Ernst S. et al., 2019).
Recently, experimental studies have been conducted onmethanol synthesis using Ni2FeGa (Smitshuysen T.E.L.,
et al., 2020) and on ammonia dissociation using Co2CrGe(Chao H. et al., 2019). For other ternary intermetallic
catalysts, aforementioned RTX (R: rare earth, T: transition
metal, X: p-block element) compounds (LaCoSi, LaRuSi)
have been recently reported on ammonia synthesis, whichwere prepared by arc-melting (Gong Y. et al., 2018; Wu J.
et al., 2019). In these catalysts, the property as an electride,the ability for hydrogen storage, and an electron transferfrom La to active elements (Co, Ru) play key roles. Thus,
ternary systems exhibit novel catalytic properties that are
not realized in binary systems. The screening of ternary intermetallic catalysts would be accelerated for the potential
discovery and development of novel catalysts.

Takayuki Kojima et al. / KONA Powder and Particle Journal No. 38 (2021) 110–121

Acknowledgements
We are grateful to Prof. Shinpei Fujii of Kagoshima
University and to Dr. Shigenori Ueda of National Institutefor Materials Science for collaborating with us for the electronic structure evaluation by first-principles calculationand HAXPES. The HAXPES was conducted at BL15XU
at SPring-8 under the approval of NIMS Synchrotron X-ray
Station (proposal no. 2017B4905). This work was partially
supported by JSPS KAKENHI grant number JP19H02452,
the Hattori Hokokai Foundation, the Iwatani Naoji Foundation, the Noguchi Institute, and NIMS microstructuralcharacterization platform as a program of ‘Nanotechnology
Platform’ (project no. 12024046) of MEXT, Japan. We
also thank the supports from the Program for Creation ofInterdisciplinary Research from FRIS, Tohoku University,and from Dynamic Alliance for Open Innovation Bridging
Human, Environment and Materials.
Sections 3–6 were partly written based on the review
paper in Japanese (Kojima T., 2020).

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Authors’ Short Biographies
Takayuki Kojima
Dr. Kojima majored in materials science during his student career (2001–2006: Kurume
National College of Technology; 2006–2013: Tohoku University for bachelor, master,
doctoral). He researched magnetic material thin-films when he was a graduate student.
He then came up with the idea of using Heusler alloys as catalysts, which are popular as
magnetic materials, inspired by Prof. A.P. Tsai’s lecture on “like electronic structure, likecatalysis”, and began conducting catalytic studies in Tsai’s group in 2014. He is currently
researching catalysts and functional materials, including magnetic materials, through aninterdisciplinary approach as an Assistant Professor of FRIS.

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Authors’ Short Biographies
Satoshi Kameoka
Dr. Kameoka is an Associate Professor at the Institute of Multidisciplinary Research for
Advanced Materials (IMRAM), Tohoku University. He received his PhD from Universityof Tsukuba in 1996. In 2004, he moved to IMRAM as a Research Associate. His researchinterests are catalysis by metals and alloys. He has performed collaborative research with
Prof. Tsai and Dr. Kojima in studies on the metallurgy for advanced catalysis materials
since 2002 and 2014, respectively.

An-Pang Tsai
Dr. Tsai was an outstanding researcher who is well-known for the first discoveries of astable quasicrystal and a binary quasicrystal. Most quasicrystals were discovered by him. He
received his PhD from Tohoku University and many honors, including the Medal of Honor
with Purple Ribbon (Japan), and was elected as a member of Academia Sinica (Taiwan). He
became a Professor of IMRAM in 2004 after working at the Institute for Materials Researchof Tohoku University and the National Institute for Materials Science (NIMS). He began
research on catalysis from a metallurgical viewpoint about 20 years ago. He passed away on
May 25, 2019 (age 60).

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Review Paper

Particle Preparation and Morphology Control with Mutual
Diffusion Across Liquid-Liquid Interfaces †Kazunori Kadota 1 and Yoshiyuki Shirakawa 2*
1
2

Department of Formulation Design and Pharmaceutical Technology, Osaka University of Pharmaceutical Sciences, Japan
Department of Chemical Engineering and Material Science, Doshisha University, Japan

Abstract
Advanced functional materials require sophisticated control of particle characteristics. The bottom-up process has
been extensively used to produce functional materials for controlling the particle properties of composite
particles. We propose crystallization at liquid-liquid interfaces as an advanced particle formation method. This
review introduces crystallization at a liquid-liquid interface based on several case studies used in various
applications. Conventional crystallization has been generally used to produce crystals and particles withhomogeneous particle properties. Liquid-liquid interfacial crystallization makes it possible to create composite
particles with hetero-phase structures and interfaces. Liquid-liquid interfacial crystallization with an inkjet
technique can control the droplet size accurately, and the shape and particle size distribution are successfully
controlled in inorganic-organic composite particles. In addition, we succeed in creating organic-organic
composite particles using the interfacial crystallization by an ultrasonic spray nozzle. The coating efficiency oforganic particles on the particles is enhanced using the ultrasonic spray nozzle in comparison with anti-solvent
crystallization. In this study, the fabrication of inorganic-organic composite particles using a coaxial tube reactor
on the liquid-liquid interfacial crystallization is proven successful. These findings suggest that liquid-liquidinterfacial crystallization is a promising means of efficiently producing composite particles because of theirapplicability to infusion in various processes.
Keywords: composite particles, crystallization, liquid-liquid interface, morphology, supersaturation

1. Introduction
Fine particular material is employed in various industrial applications such as chemical, pharmaceutical, cosmetics, and food products. The physicochemical
properties of particles originally affect the performance orfeatures of products composed of powder. The ability tocontrol particle properties such as shape, morphology,
size, and size distribution is indispensable to developing
industrial fields (Provis et al., 2010; Saallah and Lenggoro,
2018; Fuji et al., 2013). Particle-generation approaches
that create fine particles can mainly be divided into two
processes: break-down and bottom-up (Yokoyama andHuang, 2005; Tavares, 2017; Opalski et al., 2019). The
bottom-up approach is commonly used to control the particle properties during fabrication processes. In particular,
the bottom-up approach has recently gained attention due†

Received 26 October 2019; Accepted 3 March 2020
J-STAGE Advance published online 29 April 2020
* Corresponding author: Yoshiyuki Shirakawa
Add: 1-3 Miyakodani, Tatara, Kyotanabe, Kyoto 610-0321, Japan
E-mail: yshiraka@mail.doshisha.ac.jp
TEL/FAX: +81-774-65-6596

122

to its several advantages such as lower energy processes,
lower cost, and simpler instrumentation (Sinha et al.,2013; Vece, 2019). Previously, numerous bottom-up approaches such as crystallization have been successful incontrolling particle properties for the purpose of obtaining powder products with different features (Fuchs et al.,2008; Horn and Rieger, 2001; Kadota et al., 2006;
Worlitschek and Mazzotti, 2004). The bottom-up approach has been extensively used in producing composite
materials in terms of controlling the particle properties ofcomposite particles (Leon et al., 2014). Hetero-phasestructures and interfaces in composite materials can provide additional functions to products and approaches thatcreation of interfaces and structures have been regarded
as a driving force of new innovative product development(Shirakawa et al., 2006; Shirakawa et al., 2010). Several
composite materials such as inorganic-organic andorganic-organic products have been developed. Inorganicorganic composite materials have gathered attention foruse in catalysts and photoelectronic materials, whereasorganic-organic composite materials are currently being
developed as biomaterial and pharmaceutical products(Alam et al., 2018; Lazzara et al., 2018).

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Composite materials using inorganic-organic ororganic-organic materials have been proceeded for delivering drugs and other bioactive molecules for over 30
years. Several products are ongoing or have been approved worldwide as nanocarriers of drug delivery systems (Natarajan et al., 2014). Most of these nanocarrier
products have focused on target drug delivery such as
cancer chemotherapy and effectively utilize the size advantage of nanocarriers to provide a favorable distributionof the drug carrier to the human body. Several researchers
have previously succeeded in generating sustained-releaseproducts to nanocarrier applications (D’souza and
DeLuca, 2006; Washington, 1990). The accomplishment
in sustained release of bioactive molecules has broken
ground as nanotherapeutics. As a representative productof composite materials, nanocarriers that provide spatiotemporal control of drug release contributed to the improvement in the therapeutic efficacy of drugs and the
reduction in toxicity. Among composite materials, nanocarriers confront tough and original challenges indrug-release kinetics control because of the large surface
area per volume ratio and small diffusion. For development of nanocarriers such as composite particles with favorable release kinetics for drug delivery applications,
understanding the mechanisms by which a carrier retains
and releases a drug (Lee and Yeo, 2015) is crucial.
The silica nanoparticles with porous and hollow structures for controlling release kinetics of drugs were previously prepared using bottom-up approaches (Li Z. et al.,2004). Porous hollow silica nanoparticles with drugs wereprepared through a sol-gel method and using a CaCO3
template method (Nakashima et al., 2018). The preparedporous hollow silica nanoparticles were utilized as a carrier to investigate the controlled release kinetics of model
substances. A drug injected into the inner core and fused
onto the surfaces of the silica nanoparticles was released
more gradually into a solution as compared to the generalsilica nanoparticles, exhibiting a typical sustained release
without any burst phenomena. The results showed thatporous hollow silica nanoparticles have a prospective potential in controlled drug delivery systems. Aw et al.
(2012) also applied porous hollow silica as a biocarrier ofdrug delivery systems of indomethacin (IMC) as a modelof a slightly water-soluble drug. The effectiveness of porous hollow silica as an oral-drug delivery system showeda high load capacity of drugs and sustained drug releaseover a long period. These natural materials based on silica
can be successfully utilized as a biocarrier for both oral
and implant drug delivery systems.
Except for silica, metal-organic frameworks (MOFs),
which are hybrid materials formed by bottom-up approaches such as the self-assembly of polydentate bridging ligands and metal-connecting points, have beengathering attention as new drug delivery systems (Rocca

et al., 2011). The MOFs have been reduced in size tonanometer sizes, and the nanoscale MOFs were developed
as biomedical applications because of several attractive
advantages over conventional nanomedicines, including
their chemical and structural diversity, intrinsic biodegradability, and high loading capacity. Nano MOFs havebeen employed to deliver anticancer drugs and other chemotherapeutics. Nano MOFs are attractive as potential
materials for the accurately effective delivery to targeted
cells or organs in vivo. Murugan and Krishnan (2018) focused renewed attention on mesoporous silica for the application of “on-demand” drug delivery because theconception of targeted and sustained delivery of therapeutic compounds has been oriented into a more effective andattractive approach of drug release. These drug delivery
systems have been extensively examined for site-specificdelivery of single and multiple therapeutic agents. Although various types of external stimuli have been widely
examined to bring about triggered and sustained drug release from mesoporous silica, chemo-responsive systems
provide more therapeutic effectiveness with minimal collateral damage commonly associated with external stimuli. Therefore, these systems have been interpreted as“on-demand” drug release in mesoporous silica carriersand could achieve different strategies in response to various types of chemical stimuli.
This review introduces several case studies for crystallization with mutual diffusion across liquid-liquid interfaces used in various applications. Crystallization at aliquid-liquid interface was developed to synthesize asymmetric particles and composite particles. This liquidliquid interfacial crystallization was applied to various
advanced processes, which enabled finding a new possibility for creating advanced functional materials.

2. Crystallization at liquid-liquid interface
Crystallization at liquid-liquid interfaces was proposed
as an advanced particle synthesis technique in our previous works (Kadota et al., 2007a; 2007b). This technique isa production method used to precipitate solute particles at
the interface in partially miscible liquids. As a representative example, emulsions prepared as templates in liquidliquid dispersion systems have been expanded in thebiomedical applications as tissue engineering materials
and drug carriers (Wu and Ma, 2016). Several studies
conducted by Ramsden (1903) and Pickering (1907) revealed another means of stabilizing droplets using solid
particles without surfactants (Fujii and Murakami, 2008).
Pickering emulsions can be widely employed in various
fields such as food, biomedicine, fine chemical products,
and cosmetics (Linke and Drusch, 2018). We developed aliquid-liquid interfacial crystallization using mutual

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diffusion phenomena between an aqueous solution and anorganic solvent that occurs at a liquid-liquid interface.
The techniques could be applied to various fields such as
chemical engineering, food industries, and pharmaceuticals (Mori et al., 2019b). For example, different kinds ofasymmetric particles were prepared through interfacial
crystallization, and the preparation of glycine particles
with porous structures was successful (Tanaka M. et al.,2011). Recently, Janus particles have been a unique classof multifunctional particles that combine two dissimilar
chemical or physical functionalities at their opposite sides
as asymmetric particles (Agrawal G. and Agrawal R, 2019).
An inkjet nozzle was installed to crystallization at
liquid-liquid interfaces, because there is a possibility thatan inkjet nozzle can control the shape and morphology ofparticles by preparing uniform spherical droplets (Tamura
et al., 2014). The inkjet technique has garnered significant
attention for universal particle production (Böhmer et al.,2006). Since the inkjet process can give narrow particle
size distributions and control over particle morphology
and precise dosage volume, this technique can be extended to manufacturing tablets for tailored medicine(Daly et al., 2015). Wijshoff (2010) fabricated polymer
particles using an inkjet process. In another study, thesize distribution and morphology of metal particles weresuccessfully controlled (Böhmer et al., 2006). We applied
the inkjet technique to liquid-liquid interfacial crystallization, and through an instillation, we present its effectiveness in controlling particle morphology and shape ascompared with the batch process.
Glycine and alanine were selected as solutes, and 1butanol and 2-butanone as solvents for crystallization at
liquid-liquid interfaces. Alanine has no crystal polymorph, but glycine has three crystal polymorphs (Chen J.

and Trout B.L., 2010). The organic solvents of 1-butanol
or 2-butanone were set next to the liquid-liquid interface
to contact with the aqueous solution. Fig. 1 depicts aschematic diagram of the experimental apparatus and an
instillation of particle precipitation with an inkjet nozzle.
In this apparatus, several droplets of the aqueous solution
were discharged from the inkjet nozzle into the organic
solvent with slight miscibility (Tanaka M. et al., 2011).
Alanine or glycine immediately precipitated at the interface of droplets. For the batch process, particles of aminoacids were obtained by mixing the aqueous solution withan organic solvent under fixed stirring. The emulsion including droplets of glycine or alanine solution in the organic solvent was stirred. The droplet size was estimatedfrom SEM photographs. The crystal structure of bothparticles was measured through powder X-ray diffraction(XRD). The internal structure of both particles was also
observed by SEM with cutting off particles using an ion
milling apparatus.
Fig. 2 displays the relation between the mean particle
size of alanine and the droplet size of instillation with theinkjet nozzle. The mean particle size of alanine was approximately 1.2-fold higher than aqueous droplet size in
1-butanol. Additionally, the mean particle size of glycine
was larger than the corresponding droplet. The results
suggest that the interface between the 1-butanol and aqueous solution expanded following their mutual diffusion
during crystallization. The particle size of alanine was almost monodispersed as the coefficient of variation, andthe control of the particle size was demonstrated to befeasible by controlling the droplet size using the inkjet
nozzle.
Figs. 3 and 4 show SEM photographs of glycine andalanine particles produced by the batch process and by

Fig. 1 Overview of the schematic experimental apparatus for instillation using an inkjet nozzle for liquid-liquid interfacial crystallization. Reprinted
with permission from Ref. (Tominaga et al., 2018). Copyright: (2018) Elsevier.

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instillation with an inkjet nozzle, respectively. In thebatch process, most alanine particles were needle-like andmost glycine particles were rod-like. In comparison withthe batch process, glycine and alanine particles precipitated by instillation with an inkjet nozzle had a sphericalshape. During this crystallization process by instillation
with an inkjet nozzle, the interface part immediately
reaches a supersaturated state once an aqueous solution
contacts an organic solvent. Consequently, instillation
process with an inkjet nozzle made spherical particles
since nucleation and crystal growth of the solute material
made progress along the spherical interface. Both particles prepared by the instillation exhibited more sphericaland uniform particle size distribution than those by thebatch process. The supersaturation ratio near the interface
required a tiny gradient in the droplets due to the limita-

Fig. 2 Change in mean particle size of alanine against droplet size
during the instillation process with an inkjet nozzle. Reprinted withpermission from Ref. (Tamura et al., 2014). Copyright: (2014) Elsevier.

Fig. 3 SEM photographs of alanine and glycine particles by the
non-inkjet process: (a) glycine particles using 1-butanol, (b) alanine
particles using 1-butanol. Reprinted with permission from Ref. (Tamura
et al., 2014). Copyright: (2014) Elsevier.

Fig. 4 SEM photographs of alanine and glycine particles during the instillation process using an inkjet nozzle: (a) glycine particles using
1-butanol (b) alanine particles using 1-butanol. Reprinted with permission from Ref. (Tamura et al., 2014). Copyright: (2014) Elsevier.

tion to the crystallization area with the spherical interfaceof the droplets. Observation of the cross section of glycine
and alanine particles by SEM emerged the presence ofporous hollow structures. In the saturated aqueous solutions of alanine and glycine, the amount of glycine solute
was greater than that of alanine solute in droplets. Thisdifference in the amount of solute between alanine andglycine in saturated solutions may lead to hollow structures of alanine and porous structures of glycine.
The crystal structures of glycine particles prepared byinstillation with the inkjet nozzle and by the batch process
were evaluated by XRD. β-Glycine, which is an unstable
polymorph, was identified in the instillation with inkjet
nozzle, whereas the glycine particles prepared by thebatch process were of the metastable α form (Matsumoto
et al., 2019). In general, the α and β forms of glycine precipitate preferentially at lower and higher supersaturation
ratios, respectively (Matsuoka 2005; Bouchard et al.,2008). Comparing the instillation to the batch process, thediffusion phenomenon within the strictly confined droplet
generates regions of higher concentration at the interface.
Consequently, several nuclei of glycine were homogenously formed within the well-defined droplet by the inkjet nozzle. It is likely that the concentration of aqueous
solution affects the size distribution and morphology ofparticles during interfacial crystallization (Fujii et al.,2007). According to Takiyama (2004), uniform crystals
can be easily prepared from an unsaturated solution inanti-solvent or cooling crystallization. Concentration dependence of the amino acid solution on particle size, size
distribution, and morphology was examined for the inkjet
process. The size distribution of glycine and alanine particles moved toward larger sizes with an increase in concentration. The morphology of glycine prepared byinstillation with an inkjet nozzle changed from sphericalto ellipsoidal with an increase in glycine concentration. It
is considered that the growth of glycine crystals proceeded along the minor and major axes depending on the
crystal form.
The alanine particles were prepared by instillation using two types of anti-solvents: 1-butanol and 2-butanone.
Here, the mutual solubility of 1-butanol and 2-butanone towater is different (Kitayama et al., 2009a). The surface
morphology of alanine particles prepared using 2butanone was coarser than that of particles prepared using
1-butanol. The difference in surface morphology derives
from the mutual diffusion behavior following the organic
solvent. Phase diagrams of water/1-butanol and /2butanone were previously reported (Kitayama et al.,2009b; Kadota et al., 2013; Deki et al., 2016). In the solubility of 1-butanol in water, the amount of water diffusing
into 1-butanol was much greater than that of 1-butanol
diffusing into water at 25 °C. The diffusion of the solution
from droplets could go ahead and performed with

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maintaining the spherical shape. The converse phenomenon occurred in the usage of 2-butanone and water. The
size of particles became larger than that of droplets because the diffusion of the organic solvent predominated in
the mutual diffusion at the interface. This different behavior in mutual diffusion affected the particle formation
with different shape and morphology.

3. Crystallization in a tube reactor
Another case study involved particle preparation of zirconia using a tube reactor (Kadota et al., 2016). Microchannels in tube reactors have attracted attention for
preparing many types of particles since production in asingle step is possible (Hattori et al., 2015). As part of an
inexpensive and simplified approach, zirconia particles,
which are widely used as a ceramic material with functional properties such as high mechanical strength, wereprepared by neutralization reaction at the interfacial
within a tube reactor. Micro reactors are generally applied
to gas-liquid or liquid-liquid reactions (Sotowa et al.,2007; Asano et al., 2016). Many kinds of micro-reactors
are utilized in various applications. A micro channel reactor was used for the synthesis of monodispersed zirconium dioxide particles in a continuous flow process. Size
distribution and morphology of zirconium dioxide particles were controlled by two types of coaxial tubular reactors.
Water and 1-butanol were prepared for applying interdiffusion in the liquid-liquid interface following their mutual solubility curves. Zirconium oxychloride was used asa starting ingredient. Ammonia solution and sorbitanmonooleate were mixed into 1-butanol for neutralization
with zirconium oxychloride. The flow rates of water and1-butanol in the tube reactor with a single step were adjusted by syringe pumps connected to the microchannel.
The crystal structure and morphology of zirconium dioxide particles were characterized by powder XRD and
SEM, respectively. Most zirconium dioxide particles exhibited spherical shape with uniform size by the coaxial
tubular reactor in the one-step process. In this synthesis,
droplets in the tube reactor were stabilized by the additionof a surfactant. The cross section of the zirconium dioxide
particle had a solid structure. Yamaguchi et al. (2004) revealed the flow dynamics and behavior of droplets in a
micro-reactor through simulations. The simulation results
demonstrated that the circulating flow occurred in thedroplets. Suryo and Basaran (2006) also showed the circulating flow in droplets generated by the micro-reactor
process. The particle size distribution of zirconium dioxide showed a monodispersed type. The mean particle diameter was nearly consistent with that of NaCl particles
prepared by the coaxial tube reactor. This result indicated126

Fig. 5 Schematic view of the experimental apparatus using in the twostep process.

that the particle size strongly related to the size of droplets in the reactor. In addition, the selected solvents affected the particle size regardless of the species of solute
substances. The design of liquid surface tension is necessary for further control of the particle size in the microreactor. The neutralization reaction between ammonia
and zirconium oxychloride occurred in the liquid-liquidinterface after ammonia was diffused into aqueous solutions from the solvent phase in the tube reactor. Concerning the morphology, the convected flow occurred in thedroplet, resulting in solid zirconia particles being formed
without a hollow structure.
A coaxial tube reactor of a two-step process was applied to synthesize zirconium dioxide particles with porous structures. One part involved the formation ofdroplets, and the other part involved the neutralization reaction in the liquid-liquid interface of the droplets. Schematic diagram of the experimental apparatus with thecoaxial tubular reactor is shown in Fig. 5. The two-stepprocess connected to reactors X and Y. Zirconium oxychloride solution was provided from the A side, 1-butanolthat included sorbitan monooleate was supplied from theB side, and 1-butanol including ammonia solution was
supplied from the C side. Most zirconia particles synthesized by the micro tube reactor in both the one- and twostep processes displayed a uniform size and sphericalshape. SEM images of the cross section of the zirconia
particles in the two-step process revealed their porous andhollow structure, resulting in the formation of zirconium
dioxide particles along the spherical interface.

4. Synthesis of organic-organic composite
particles in a spray atomization process
We introduced the synthesis of organic-organic composite particles by using an ultrasonic spray nozzle in theKazunori Kadota et al. / KONA Powder and Particle Journal No. 38 (2021) 122–135

interfacial crystallization. Glycine and starch were selected as model substances for the process (Gonda et al.,2015). Glycine and starch are commonly used as a model
drug for pharmaceutical products and as an excipient, respectively. The composite particles prepared in the ultrasonic spray process were compared with those in aconventional anti-solvent crystallization process. The
effect of using an ultrasonic spray nozzle on the polymorphism of glycine was also studied because the poly­morphism had affected the particle properties, particularly
its solubility.
The droplets from the aqueous glycine solution withstarch particles were ejected from the ultrasonic spraynozzle into 1-butanol, which are slightly miscible withwater. Ultrasonic atomization crystallization can be controlled by vibrating the spray nozzle with the ultrasonicoscillator. The contact or the operation time between
1-butanol and aqueous solution on the starch particles affects particle properties such as morphology and particle
size distribution because the supersaturated ratio increases at the interface between aqueous solution and organic solvent (Kadota et al., 2007c).
In an analysis of SEM photographs, the composite particles produced with 1-butanol were spherical as shown in
Fig. 6(a) and consisted of a starch core and glycine shell.
Fig. 6(b) is a SEM photograph of a cross section of thecomposite particles. The cross section of the particles
confirmed the appearance of coating particles or the coreshell structures of starch particles covered with fine glycine crystals. By contrast, composite particles of starchand glycine crystals produced by anti-solvent crystallization showed non-spherical particles with a wide particle
size distribution. Moreover, many needle-like glycine
crystals had already precipitated. From the comparison of
results between ultrasonic atomizing crystallization andthe anti-solvent method, we demonstrated that the production of the core-shell structure in the precipitation space
was limited during liquid-liquid interfacial crystallization, as shown in Fig. 7. In addition, ultrasonic irradiation
particularly affected the mean crystal size and size distribution of coating crystals. Consequently, the coating effi-

Fig. 6 SEM photographs of composite particles of starch with glycine
prepared by ultrasonic spray nozzle: (a) composite particles; (b) crosssection of composite particle framed by dot-line is the starch of the core
particle. Reprinted with permission from Ref. (Gonda et al., 2015).
Copyright: (2015) Elsevier.

ciency of fine crystals on starch would be affected.
Many studies on the effect of ultrasonic irradiation on
crystal size have been studied (Kurotani et al., 2009;
Kurotani and Hirasawa, 2010; Guo et al., 2005; Hatkar
and Gogate, 2012; Stelzer et al., 2013). Kurotani et al.
(2009) investigated the relation between the ultrasonic irradiation and the generation of the primary nucleation ofamino acids in supersaturated solutions. They succeededin obtaining the demanded crystal size of products by optimally adjusting the conditions of ultrasonic irradiationand supersaturation. Furthermore, Yoshizawa (2004)
classified microparticles into three structures from morphological control.
We reported the effect of operation time on the particle
morphology by liquid-liquid interfacial crystallization(Kadota et al., 2007b), and succeeded in controlling the
crystal growth rate and crystal shape by changing the operation time. The effect of operation time on the particle
morphology during ultrasonic irradiation was examined
under a constant glycine solution. The coating thicknessof starch particles was calculated from the size difference
between coated and bare particles. The shell thickness
was independent of the operation time after several minutes. This was because nucleation was promoted by theeffect of ultrasonic irradiation for a short time (Miyasaka
et al., 2006). Ultrasonic irradiation enabled the fine crystals to enhance crystal generation in the initial stage of
nucleation.
XRD patterns of the composite particles by the change
in the glycine solution concentration were measured. Bothα- and β-glycine crystals were coexistent on starch particles at lower glycine solution concentrations. However,
only β-glycine crystals were covered on the starch particles at higher glycine solution concentrations. This phenomenon can be explained by the Ostwald step rule
(Kitamura 1989; 2004). Initially, we investigated the variation of glycine polymorphism without starch particles
because of clarifying the polymorphic transformation ofglycine crystals on starch particles. XRD patterns ofFig. 7 Schematic of the composite particle. Guest particles on the core
particles precipitated through a liquid-liquid interfacial crystallization.

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glycine particles revealed that α- and β-glycine were precipitated and coexistent in all concentrations of glycine
solution without starch core-particles. This indicates thatthe hydroxy groups on the surface of starch particles act
as a template for β-glycine. The secondary nucleation of
β-glycine crystals may preferentially occur by adhesion ofglycine molecules, as β-glycine crystals are attracted byhydrogen bonds aligned on the starch particles. The effects of the template generated by additive addition on
crystalline polymorphism were previously revealed byKitamura (2004). The interaction between the core andguest molecules is a major factor in creating the composite particles. Both α- and β-glycine crystals were precipitated without core particles. β-Glycine crystals transformto α-glycine crystals for the solution-mediated phasewithout starch particles. With starch core particles, thehydroxy groups on the starch particle surfaces could
function as a template for β-glycine and stabilize βglycine structures. Furthermore, forming the solutionmediated phase on the starch particles may be difficult
because the β-glycine crystals on the core particles ofstarch are thick.

5. Synthesis of organic-inorganic composite
particles by using a tube reactor
We demonstrated in synthesis of the inorganic-organic
composite particles of NaCl and Indomethacin (IMC) by
using a coaxial tube reactor based on liquid-liquid interfacial crystallization (Hattori et al., 2015).
In the process, inorganic-organic composite particles
precipitated at the liquid-liquid interface by individuallyfeeding two different solute materials from 2-butanone
and the aqueous solutions. The ability of composites
strongly depends on the difference in precipitation rate
between two solutes and is directly related to controllingthe composite particle structures. NaCl has a relatively
higher precipitation rate. Therefore, we selected IMC witha low precipitation rate into 2-butanone. IMC exhibiting
analgesic activity is a non-steroidal anti-inflammatory.
Some research concerning IMC was previously investigated to improve its poor solubility in water (Zhang et al.,2011; Kigasawa et al., 1981).
The experimental apparatus for the coaxial tube reactor
used in this process is shown in Fig. 8. The flow rate in
the tube reactor was adjusted using a micro-syringe pumpsystem. Water was run through the inner tube, and the organic phase flowed through the outer tube. As a preliminary
experiment, the flow rate was varied to observe and comprehend flow patterns in the tube reactor. A previous study
showed that when flow patterns form in a micro-reactor,
the critical factors are the inertial force and the interfacial
tension (Zhao et al., 2006). We used the Weber number

128

for expressing flow patterns, and precipitated particles
were observed by SEM. The quantitative amount of IMC
was measured by Ultraviolet-visible (UV) spectroscopy.
Three types of flows (parallel, plug, and dispersed)
were observed by flow visualization in the tube reactor.
Dispersed flow consisted of water droplets suspended in
2-butanone that formed a spherical shape. The interfacial
tension of water and the inertial force of 2-butanone were
dominant in the dispersed flow with a high flow rate of
2-butanone. We produced NaCl crystals using the coaxial
tube reactor by parallel, plug, and dispersed flow formed
from the aqueous solution and 2-butanone. Precipitated
NaCl crystals were cubic with a hollow dispersed flow.
Channel blockages occurred in the parallel flow and werea major problem for continuous operations. The parallel
flow was not appropriate for liquid-liquid interfacial crystallization using the tube rector. The other two flows did
not show any blockages.
We calculated the nucleation and crystal growth rates
of precipitated crystals by the mass balance and numberof crystals to clarify the behavior of crystal nucleationand growth in the tube reactor. The calculation results
show that the crystal nucleation rate dramatically decreased at a residence time in the tube reactor. The crystallization growth rate moderately increased withincreasing residence time and gradually decreased thereafter. These results correspond to the change in the degreeof supersaturation. When NaCl solution reached a highsupersaturated ratio or an unstable state, several nuclei of
NaCl were generated in a short period of time. After nuclei were generated, NaCl concentration rapidly decreased
and the solution reached a meta-stable state for a limited
number of NaCl solutes in the droplet. This suggests that
this crystallizer helped to control the particle shape with anarrow distribution by the residence time.
Crystallization at the interface of the NaCl aqueous andFig. 8 Schematic of the experimental apparatus in the continuous operation. Reprinted with permission from Ref. (Hattori et al., 2015).
Copyright: (2015) Elsevier.

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IMC organic solutions was conducted in the tube reactor.
Then, it had to facilitate nucleation for the crystals of
IMC because the precipitation rate of IMC was very slow.
Some researchers have reported that ultrasonic irradiation
is effective at enhancing nucleation (Kudo and Takiyama,
2012; Guo et al., 2005; Kurotani et al., 2009; Miyasaka etal., 2006). The precipitation of IMC by ultrasonic irradiation to the liquid-liquid interface was examined. From theresults of the crystallization of NaCl and IMC in separate
operations, we expected that precipitation of composite
particles consisting of NaCl and IMC would occur. The
precipitation of NaCl/IMC composite particles in the dispersed flow was examined and composite particles wereobtained. The obtained particles had a spherical shape
and were aggregated particles consisting of many NaCl
primary crystals. SEM photos revealed that IMC precipitated only on the surface of the aggregated NaCl particles.
The aggregated composite particles of NaCl/IMC had anear mono-dispersion size distribution. We can proposethat the precipitation mechanism of the composite particles in the dispersed flow can be expressed as shown in
Fig. 9. The precipitation of IMC dominantly occurred on
the surface of NaCl from the kinetic crystallization parameters (Mersmann, 1998; Kawashima et al., 2002).
NaCl crystals were first precipitated at the interface of
2-butanone and the aqueous solutions and agglomerated
during the flow of the droplet. Second, the droplet transferred to the area with ultrasonic irradiation, and IMC
crystals were precipitated on the aggregated NaCl particle
surface under ultrasonic irradiation. Then, NaCl/IMC
composite particles were formed. This process in a dispersed flow can realize the fabrication of composite particles in one path continuously.

6. Preparation of a Pd-supporting TiO2
catalyst using the inside surface
Capsulation is a basic technique for adding functions toparticles (Kameta, 2014; Mori et al., 2019a). We introduced the synthesis of hollow titanium dioxide particles
by using the inkjet process and showed the functionalization by charging Pd particles on the inside surface(Tanaka T. et al., 2016). We prepared the titania particles

Fig. 9 Precipitation mechanism of composite particle with ultrasonicirradiation in a dispersed flow. Reprinted with permission from Ref.
(Hattori et al., 2015). Copyright: (2015) Elsevier.

during the liquid-liquid interfacial sol-gel process with an
inkjet nozzle and made an evaluation of the photocatalytic
activity of the composite titania particles (Kadota et al.,2014).
Titanium tetraisopropoxide (TTIP) and hexane wereused as a starting precursor of preparing titania particles
in the sol-gel process and as an organic solvent to create
the liquid-liquid interface with water, respectively. Acetonitrile was selected to vary the reaction rate of water because of being miscible with water but unfavorable forhexane. The aqueous solution was fed from the inkjet
nozzle into the TTIP solution by controlling 1000 drops
per second for 1 hour. The precipitated titania particles
were a porous and hollow structure. For comparison ofparticle properties by inkjet nozzle, titania particles werealso synthesized by using a pipette.
A photodeposition process of palladium on the porous
hollow titania particles was performed (Ismail et al., 2013;
Maicu et al., 2011; Camposeco et al., 2014). Porous hollow
titania particles were added to an aqueous solution that
included ethanol, and ultrasound was irradiated toward
the suspension. Then, a palladium chloride solution wasadded to the suspension. The palladium chloride solution
was charged into the particles under a low pressure to
support palladium on the inner portion of the porous hollow titania particles. The palladium precipitated in the
porous hollow titania particles. The suspension was irradiated with a black light in the dark, resulting in that palladium was supported on the titania hollow particles in a
reduction of the number of palladium ions by the photocatalytic effect of titania. Prior to the examination of its
photocatalytic effect, we examined the titania particle
properties such as inner structure and pore characteristics. The element mapping state of Pd on the titania particles was evaluated by using an energy dispersive X-ray(EDX) analyzer. It was connected to a field emission typescanning electron microscope (FE-SEM). The photocatalytic performance between Pd supported on titania particles and non-supported titania particles was compared byevaluating the photocatalytic degradation of methylene
blue solution (Nuno et al., 2015). Here, crystal structuresof titania had three distinct polymorphisms (anatase, rutile, and brookite) and the photocatalytic activities werevery sensitive to the crystal structures (Wen et al., 2015;
Koelsch et al., 2004). The titania structure was controlled
through the calcination of the particles.
The morphology and appearance of the titania particles
prepared with and without the inkjet process were observed. Most titania particles prepared by the normal
batch process without inkjet nozzle were irregular-shaped
particles, whereas most of those prepared with the inkjet
process displayed spherical particles with uniform size
distribution. According to the observation of crosssection, titania particles had porous hollow structures,

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indicating that the crystal growth of titania particles occurred along the spherical interface. As describedin section 4, the crystal growth of particles progressedalong the interfacial droplet. This growth behavior of particles indicates the specific phenomena in liquid-liquid interfacial crystallization. Additionally, the particle size
distribution of the titania prepared by the inkjet process
was strictly narrower than that of the titania prepared by
the batch process. The typical pore size distribution of titania particles prepared by the inkjet process was exhibited,
whereas there were no peaks of the pore size distributionof titania particles prepared by the batch process.
The use of Pd supported on the surface of the porous
hollow titania particles inside was expected to enhance
the photocatalytic performance of titania. We compared
the photocatalytic performances between the titania particles prepared by the non-inkjet and inkjet processes. Irrespective of preparing methods, the concentration of
methylene blue gently decreased with increasing the irradiation time of ultraviolet-C (UV-C). In comparison of
degradation rate, the titania particles synthesized by the
inkjet process showed a slightly effective photocatalytic
degradation than those by the non-inkjet process. This isbecause the photocatalytic activity of the titania particles
by the inkjet process was advanced by increasing the specific surface area during photocatalytic degradation. This
result could be supported by the specific surface area
evaluated by BET.
Palladium element examination using EDX indicatedPd particles adhered on the inner surface of the hollow titania particles. The insertion of palladium onto the innersurfaces required the transmission of UV light to make aphotocatalytic reduction of palladium chloride salt inside
the hollow particle. Although the transmittances of titania
generally show low values at wavelengths in the region ofultraviolet light (Chen X. et al., 2011), UV light can betransmitted through the titania shells with reduction of
the electronic excitations. A previous study found thattransmittance through ultrathin films of anatase-type titania rapidly increased for ultraviolet light wavelengths ofmore than 350 nm (Rezazadeh et al., 2015). In this study,titania particles by the inkjet process hardly showed any
excited electrons because of having amorphous structures(Piccinini et al., 2013). UV light with 365-nm wavelength
was irradiated on the porous titania particles relatively forthe long time, and UV light was consequently transmitted
through the shell to the inner surface of the porous hollow
titania particles with the reduction in electronic excitation.
Then, the palladium could be supported on the inner surface of the titania particles.
Fig. 10 shows the degradation behavior of methylene
blue with the Pd-supporting titania particles. The concentration of methylene blue in the Pd-supporting titania particles gently decreased with increasing of UVC irradiation

130

time, whereas the concentration of methylene blue in the
non-supported particles was an almost constant. The
Pd-supporting titania particles showed a faster rate ofphotocatalytic degradation than the non-supported titania
particles. The results indicated that the photocatalytic activity was improved by support of palladium to the titania
particles, whereas the non-supported particles did not exhibit any photocatalytic activity. Camposeco et al. (2014)previously investigated that the photocatalytic activity oftitania was enhanced by adding support palladium particles on titania with a photodeposition method. The palladium was supported onto the titania particles with anamorphous structure which electrons are hardly excitedunder solar irradiation. Fig. 11 shows that the porous hollow titania particles supported by palladium on the outerand inner surfaces exhibited a faster rate of photocatalytic
degradation than that for the palladium-supported titania
particles prepared by the non-inkjet process. The result
was attributed to the increase of the specific surface area.
Importantly, the synthesis of the titania particles with ahigh specific surface area was needed even when the palladium was supported onto the titania particles. We havesucceeded in synthesizing the Pd-supported titania catalyst using the sol-gel process with the inkjet nozzle, resulting in the improvement of the photocatalytic activityof titania particles supported by palladium on the innerand outer surface of titania hollow particles.

7. Release properties of vitamins from TiO2
porous hollow particles
Another example of functionalization by charging vitamins into the hollow particles was profiled (Tominaga etal., 2018; 2019).
Titania particles with a porous hollow structure wereprepared using the interfacial sol-gel processing preparation (Kadota et al. 2014) as described in the previous
section. L-ascorbic acid encapsulated inside the porous
hollow particles of titania by using two methods. The first

Fig. 10 Degradation behavior of methylene blue with photocatalytic titania particles obtained by different processes. Reprinted with permission from Ref. (Tanaka et al., 2016). Copyright: (2016) Elsevier.

Kazunori Kadota et al. / KONA Powder and Particle Journal No. 38 (2021) 122–135

Fig. 11 Change in methylene blue concentration of three types of titania particles prepared under different conditions. Reprinted with permission from Ref. (Tanaka et al., 2016). Copyright: (2016) Elsevier.

method was immersion preparation. Titania particles wereadded to the L-ascorbic acid aqueous solution. The supernatant solution was taken and dried in a desiccator until
completely dry. The second method was the preparation
by feed of a discharged solution containing L-ascorbic
acid from the inkjet nozzle.
In vitro release study of L-ascorbic acid from the titania particles was conducted by using a dialysis bag
method (Wang et al.. 2008; Hanson 1982; Toomari andNamazi, 2016; Lasoń et al., 2016; Huang et al., 2017;
Stebbins et al., 2017; Wei et al., 2010; Tanabe et al., 1988)
in phosphate buffer saline as release media. A photostability test was conducted on the sample to investigate
whether the effect of inhibiting degradation of L-ascorbic
acid could be obtained by encapsulating L-ascorbic acidinto the titania hollow particles. After irradiating UV, we
conducted the same release test using the same amount of
L-ascorbic acid as the encapsulated amount.
XRD analysis was performed on the obtained samples
to confirm the crystal structural change by calcination
treatments. From the XRD patterns, the samples without
calcination were in an amorphous state, and those withcalcination at 900 °C for 6 h were transferred to a rutile
structure. The shape of titania particles was maintained ina uniform spherical shape even after the calcination treatment and encapsulation operations.
The cross sections of the samples and element mappingof the inner surface were evaluated using SEM and EDX,
respectively. According to EDX evaluation, the samples
derived from the encapsulating operation of L-ascorbic
acid were detected. The results of element mapping revealed that L-ascorbic acid adhered to the inner wall surface of titania particles when prepared by this process.
The release profile of L-ascorbic acid from the titania
particles was evaluated by using the UV-vis spectrophotometry. A peak of UV detection was observed within theabsorption wavelength region from 244 nm to 265 nm(Liao et al., 2001). From the UV data, we found that
L-ascorbic acid can be encapsulated using the immersion
method. However, no peaks were observed for some sam-Fig. 12 Time evolution of L-ascorbic acid concentration released froma sample (L-Asc) and bare specimen after UV irradiation for 12 h. Reprinted with permission from Ref. (Tominaga et al., 2018). Copyright:(2018) Elsevier.

ples in the absorption wavelength region of L-ascorbic
acid. This causes the oxidation of L-ascorbic acid and the
production of dehydroascorbic acid during the preparationof titania particles. The comparison of photostability results between pure L-ascorbic acid and encapsulated samples are shown in Fig. 12. The release rate of L-ascorbic
acid reached approximately 94 % within 4 h and maintained a release rate of 90 % or more for a long time.
However, pure L-ascorbic acid was completely released in
2 h. Accordingly, the release rate at that time was approximately 77 %. Therefore, it is considered that the remaining ~23 % was degraded by UV spectroscopy. Based onthese circumstances, the degradation of L-ascorbic acidcould be inhibited by encapsulation in the titania porous
hollow particles.

8. Conclusion
Particle modification for functionalization and improved powder handling is a critical technique in powder
technology. It can be realized by the sophisticated construction of composite structures in a wide range fromnano- to micron-scale. In this study, we introduced thefabrication of composite particles with liquid-liquid interfaces and heterogeneous nucleation. The control of material transfer at liquid-liquid, liquid-solid, and solid-solid
was a major factor in the production of complicated composite structures.

Acknowledgments
The authors express their gratitude to Professors Jusuke
Hidaka, Yoshinobu Fukumori, Hideki Ichikawa, andYuichi Tozuka as well as to Drs. Atusuko Shimosaka andMikio Yoshida. All works were produced from major
contributions by members of the Powder Technology131

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Laboratory at Doshisha University. Some works werepartially supported by a grant from the Japan Society for
the Promotion of Science KAKENHI (No. 16K06837)(Tokyo, Japan).

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Authors’ Short Biographies
Kazunori Kadota
Dr. Kazunori Kadota is an Associate Professor at Osaka University of Pharmaceutical
Sciences. He received his Ph.D. in 2007 from Doshisha University. He then worked at
Eisai Co., Ltd., a pharmaceutical company, from 2007 to 2013. He started an academic
carrier at Osaka University of Pharmaceutical Sciences in 2013. His research is in thefield of pharmaceutical science technology and food engineering based on particle technology.

Yoshiyuki Shirakawa
Dr. Yoshiyuki Shirakawa is a Professor at Doshisha University. He received his Ph.D.
in 1993 from Niigata University. He started an academic carrier at Niigata University as
a post-doctoral student for JSPS Research Fellowship Sciences in 1993 and worked at
Osaka and Doshisha Universities. His research interests are composite particle synthesis
by crystallization and mechano-chemical processes and materials designs using computer simulations.

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KONA Powder and Particle Journal No. 38 (2021) 136–154/https://doi.org/10.14356/kona.2021013

Review Paper

Consideration of Metal Organic Frameworks
for Respiratory Delivery †Ian E. Stewart 1*, Ignacio Luz 1* and Ninell P. Mortensen 2
1 Center for Engineered Systems, RTI International, USA

2 Center for Analytical Chemistry and Pharmaceutics, RTI International, USA

Abstract
Metal organic frameworks (MOFs) have garnered increased attention over the past 20 years. Due to their porosity,
high surface area, and nearly limitless customization and tunability MOFs have been designed for applications
ranging from gas storage and separation to catalysis to sensing to biomedical engineering. Within the latter
category, MOFs offer an appealing function for drug delivery as they can be loaded with multiple therapeuticmoieties tailored to target specific disorders with triggered and controlled release characteristics. However, there
is an unmet need to assess their viability for pulmonary treatment via inhalation. Targeting pulmonary disorders
including infectious diseases by delivering medication directly to the lungs attacks the primary site of infection
rather than relying on systemic distribution. The inherent advantage of this strategy is maximizing local lungconcentrations of the drug. An introduction to inhaled therapies is provided here as a preamble to a brief summaryof the current development state of MOF drug delivery systems. This review is intended to highlight the relative
disparity between research toward MOFs as pulmonary drug delivery vehicles compared to other delivery
platforms. Prospective biomedical applications for inhalable MOFs are also discussed.
Keywords: metal organic frameworks, aerosol, coordination polymer, pulmonary delivery, dry powders

1. Introduction
Inhalation therapies continue to be important treatments
for several pulmonary diseases including asthma, cystic
fibrosis (CF), and chronic obstructive pulmonary disorder(COPD). Aerosol delivery can achieve a high local drugconcentration in the lungs while minimizing systemic
exposure, thus potentially resulting toxicity and patientadherence, generating promise as a therapeutic strategy forother pulmonary diseases and infections such as tuberculosis (TB). Metal organic frameworks (MOFs) are emerging
drug delivery tools. MOFs offer, in addition to drug delivery, the inclusion of metals, presenting multiple therapeuticmoieties tailored to target specific disorders with triggered
and controlled release characteristics.
Metals have a long history of being utilized to treat various ailments. Cu has been used for treating pulmonary disorders, sanitizing water, and treating wounds (Borkow G.
and Gabbay J., 2005; Grass G. et al., 2011; Ladomersky E.
†

Received 27 May 2020; Accepted 1 July 2020
J-STAGE Advance published online 21 August 2020
* The authors contributed equally to this work. Please direct
correspondence to Ian Stewart;
Add: 3040 East Cornwallis Road, Research Triangle Park, NC,
27709, USA
E-mail: istewart@rti.org
TEL: +1-919-541-5933

136

and Petris M.J., 2015). Eye ailments were treated with Zn
compounds (Giachi G. et al., 2013). The Chinese had used
gold to manage many disorders (Huaizhi Z. and YuantaoN., 2001). However, it was not until the 20th century thatmetals began to be better understood and utilized by the
medical community.
As medicine has progressed into modern times and theessential biological processes associated with metals are
known, the applications taking advantage of unique traitsof metal (particularly transition metal) complexes as diagnostic, treatment, and preventative medicinal components
have opened up. Since the relatively recent discovery of
the anticancer Pt-based complex cisplatin in the mid-20th
century (Lippert B., 1999; Rosenberg B. et al., 1969), theuse of metals in medicine is largely centered on anticancer
activity (Franz K.J. and Metzler-Nolte N., 2019; Ndagi
U. et al., 2017), though there are other promising applications. Ag, Co, and Cu have antibacterial and antiviral uses
(Borkow G. and Gabbay J., 2005; Chang E.L. et al., 2010;
Clement J.L. and Jarrett P.S., 1994; Zhao G. and Stevens
S.E., Jr., 1998), Ti and Ti-alloys are used for prosthetics
and implants (Zhao L. et al., 2009), and Cu, Rh, Ru, andZn have been explored for anti-malarial efficacy ( Navarro
M. et al., 2005; 2010; Sánchez-Delgado R.A. et al., 1996).
The nano-biotechnology research field has blossomed
in recent decades: silver nanoparticles (Ag NPs) have

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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become popular as bactericidal (Baker C. et al., 2005;
Martínez-Castañón G.-A. et al., 2008) and anticancer
agents (Foldbjerg R. et al., 2011; Ong C. et al., 2013) whilegold nanoparticles (Au NPs) have shown promise in awide variety of applications from imaging to drug delivery(Giljohann D.A. et al., 2010; Murphy C.J. et al., 2008).
There are many comprehensive reviews detailing the useof metals in medicine (Dabrowiak J.C., 2017; Guo Z. andSadler P.J., 1999; Lemire J.A. et al., 2013; Medici S. et al.,2015) and the inclusion of metals in biomedical researchis expanding from its arguable origins in the 1960s (Franz
K.J. and Metzler-Nolte N., 2019).
An intriguing 21st century approach to implementing
metals in medicine is the use of metal organic frameworks(MOFs). The extensive interest in MOFs over the past two
decades has garnered interest from a variety of disciplines
including the medical community. There is an immense
amount of customization available to a researcher when
considering MOFs as a drug delivery platform: elevatedporosity for drug encapsulation, unique drug and metal
combinations, and controlled release via tuning linkages
within the frameworks (i.e. cleavage of coordination bondin acidic media), to name a few. Thus, it is surprising that,compared to oral and injectable routes of administration,
there is a lack of consideration of MOFs for aerosol delivery of therapeutics. This may, however, correlate to a similar lack of research in the biological fate of inhaled metals.
While pulmonary administration of drugs is not suitablefor every treatment approach, there are advantages in targeting the lungs. The intent of this focused review is to firstprovide a cursory introduction to inhalation technology for
drug delivery followed by a brief MOF background andreview of current MOF applications in the biomedical field.
The sparse activity with respect to MOFs for aerosolized
delivery to the lungs will be apparent and should motivate
future research in this area.

2. Aerosols for pulmonary therapy
In ~1500 B.C., the first use of inhaled drugs was recorded by the Egyptians. Individuals struggling to breathe
were instructed to inhale vapours from hot black henbane(Hyoscyamus niger) (Breasted J.H., 1930). The Greeks also
used Cu to treat pulmonary diseases (400 B.C.) (Borkow G.
and Gabbay J., 2005). While inhaled therapies continued
to evolve over the centuries, a breakthrough came in the
1950s with the invention of a portable metered dose inhaler(MDI) that reliably delivered medication to the lungs
and ushered in modern pulmonary delivery (Stein S.W.
and Thiel C.G., 2017). Inhaled therapies have progressedover recent decades and are now predominantly used todeliver therapies to the lungs to treat chronic ailments
such as asthma (Alangari A.A., 2014), CF (Agent P. andParrott H., 2015), and COPD (Patton J.S. and Byron P.R.,
2007; Sims M.W., 2011). Research into inhaled drugs forother applications including antivirals (Jefferson T. et al.,2006; Zhou Q. et al., 2015), anticancer (Lee W.-H. et al.,2015; Zarogoulidis P. et al., 2012), gene therapy (Laube
B.L., 2015; Davies L.A. et al., 2014), peptide and protein
delivery (Okamoto H. et al., 2002), and antibacterials(Banaschewski B. and Hofmann T., 2019; Muttil P. et al.,2009) is ongoing. This is especially apparent in the latterarea as emergence of drug resistant bacterial strains necessitates novel treatment regimens (Van Duin D. and Paterson
D.L., 2016; Ventola C.L., 2015). The general reasoning
is straightforward: deliver the cure to the site of infection
rather than ingesting or injecting the drug (Fig. 1).
Pulmonary administration of therapeutics allows for direct drug delivery to the target organ. First pass metabolism
is avoided thus limiting possible systemic side effects at
a presumably much lower dose compared to other routesof administration (Borghardt J.M. et al., 2018; Lipworth
B.J., 1996; Stein S.W. and Thiel C.G., 2017). Conversely
there has also been an interest in using inhalation to rapidly
deliver drugs, such as insulin, systemically to other partsof the body (Henry R.R. et al., 2003; Hickey A.J. and Da
Rocha S.R., 2019; Laube B.L., 2005; Mortensen N.P. andHickey A.J., 2014). In either case, designing a molecule forinhalation is no trivial task. There are challenges associatedwith formulating an active pharmaceutical ingredient (API)into a respirable aerosol capable of producing the desired
therapy. These include broad considerations such as
excipient inclusion, pharmacokinetic/pharmacodynamics(PK/PD) of the inhaled formulation, drug product manufacturing, physicochemical properties, and stability which
are recounted more thoroughly elsewhere (Hickey A.J. and
Da Rocha S.R., 2019; Huaizhi Z. and Yuantao N., 2001;
Maa Y.F. and Prestrelski S.J., 2000; Mortensen N.P. et al.,2014). Though arguably, the first hurdle to be overcome
when considering pulmonary delivery is producing an
aerodynamic diameter suitable for respiration and delivery

Fig. 1 Rationale for aerosol delivery to the lungs. This method presents
higher lung concentrations of the drug compared to systemic delivery.
Reprinted from Journal of Controlled Release, 240, A.J. Hickey, et al.,Inhaled drug treatment for tuberculosis: Past progress and future prospects, Pages 127–134, Copyright (2016), with permission from Elsevier(Hickey A.J. et al., 2016a).

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to the lower airways.
The lungs contain a vast network of internal branches
that confer an enormous canvas for particle deposition.
Fig. 2 shows a diagram of adult lungs and corresponding
cross-sectional areas of the 24 bifurcating airway generations, increasing from 2.54 cm2 to 104 cm2. However, it isgenerally accepted that only particles with an aerodynamic
diameter of roughly 1–5 μm will be respirable. The aerodynamic diameter of a particle, which equates the particle
to a sphere of unit density with the same settling velocity
regardless of its actual shape and density, is defined, in
simplified form from Stokes’ law, as

d ae = d v

p


(1)

where dae is the aerodynamic diameter, dv is the equivalent
volume diameter equal to the non-spherical volume diameter of the particles in question (can be determined experimentally (DeCarlo P.F. et al., 2004)), ρp is the density of theparticles and χ is the dynamic shape factor. Full derivations
and considerations can be found in the literature (Crowder
T.M. et al., 2002; DeCarlo P.F. et al., 2004; Hickey A.J.
and Edwards D.A., 2018). One generally cannot rely on
the geometric mean size of particles (found via opticaltechniques) and their bulk/tapped density to predict aerodynamic diameter and size distributions without detailed
knowledge of the particle’s density and considerations forany internal cavities and shape factors. Indeed, particle
diameter and density do not need to both be explicitly
specified (Edwards D.A. et al., 1997; Hickey A.J. and
Edwards D.A., 2018). Rather, an experimentally deter-

mined descriptor of an aerosol’s aerodynamic particle
size distributions (APSD) can be measured via inertial
impaction. This mass based characterization will generate
an APSD from which mass median aerodynamic diameter(MMAD or the median particle size at which 50 % of
the aerosol mass lies below and above calculated from alognormal cumulative distribution), geometric standard
deviation (GSD), and fine particle fraction (FPF) can be
determined. These are several basic standard quantifiable
attributes for aerosol drug characterization prior to in vivo
experiments that give the researcher a detailed idea ofparticle behaviour under the influence of an airstream. The
theory and practice of inertial impaction can be found in theliterature (Marple V.A. et al., 2003; Mitchell J.P. and Nagel
M.W., 2003). The United States Pharmacopeia (USP),
among other compendiums such as European Pharmacopoeia (Ph. Eur.), contain several useful chapters detailingproper characterization of pharmaceutical aerosols to better
anticipate performance prior to in vivo studies (see forexample chapters <601> and <1601> in the USP). Finally,
research regarding predicting in vitro – in vivo correlations
and airway modelling is also available (Byron P.R. et al.,2010; Hofmann W., 2011; Olsson B. et al., 2013).
Many factors contribute to inhaled aerosol deposition
including airway geometry, temperature and humidity,
particle solubility and crystallinity, and the breathing patterns of the individual. However, there are three primary
outcomes dictated by aerodynamic particle size which aresummarized in Fig. 3 (Finlay W.H., 2019; Labiris N.R.
and Dolovich M.B., 2003). Particles with MMAD larger
than ~5 μm typically a) impact the back of the throat andFig. 2 a) Breakdown of lung branching generations and b) corresponding surface area. Compiled figure: a) adapted with permission from (Kleinstreuer C. et al., 2008), Copyright 2008 by Annual Reviews; b) reprinted from xPharm: The Comprehensive Pharmacology Reference, Robert M. Lust,
The Pulmonary System, Pages 1-6, Copyright (2007), with permission from Elsevier (Lust R.M., 2007).

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Fig. 3 Summary of particle size and regional pulmonary deposition percentage. The curve on the right gives an estimation of particle size vs. deposition percentage corresponding to the alveolar region (solid black line), airways (dashed line), and mouth and throat (solid gray line). This figure isfrom Loco-regional administration of nanomedicines for the treatment of lung cancer, Gabriela Garrastazu Pereira, Amanda Jane Lawson, et al., Drug
Delivery (Garrastazu Pereira G. et al., 2016), 2016 Taylor and Francis, reprinted by permission of the publisher (Taylor & Francis Ltd, http://www.
tandfonline.com). Originally adapted from Springer Nature, Nature Reviews Drug Discovery, Inhaling medicines: delivering drugs to the bodythrough the lungs, Patton J.S. and Byron P.R., Copyright 2007 (permission granted for the present publication as well) (Patton J.S. and Byron P.R.,
2007).

conducting airway above the 10th lung generation, b) areswallowed and never reach the lungs, or c) are removed in
the upper airways via mucociliary clearing. Particles with
MMAD ~1–5 μm deposit via impaction and gravitational
sedimentation. Lastly, particles < 1 μm generally arrive
through diffusion or Brownian motion; there is a chancethey are exhaled due to slow settling in the airways. There
are other considerations involved in the inhalation of particles at lower primary size in the nano range (Muralidharan
P. et al., 2015; Paranjpe M. and Müller-Goymann C.C.,
2014; Yang W. et al., 2008; Zhang J. et al., 2011). Thus
particles with mass median aerodynamic diameter between
1–5 μm have the best chance of reaching the lower airways.
(Labiris N.R. and Dolovich M.B., 2003; Patton J.S. andByron P.R., 2007). Additionally, alveolar macrophages
have evolved to phagocytose particles in this size range(especially 2–3 μm). This spurs the design of aerosolized
treatments for bacteria that reside in the macrophage,such as Mycobacterium tuberculosis (Mtb), the causative
organism of TB (Biggs D.L. et al., 2003; Champion J.A. etal., 2008; Edwards D.A. et al., 1997; Gharse S. and FiegelJ., 2016; González-Juarrero M. and O’Sullivan M.P., 2011;
Skoczen S.L. et al., 2011). Other factors to consider forparticle size engineering are: controlled release strategies(Adi H. et al., 2010; Cook R.O. et al., 2005; Smyth H.D.
and Hickey A.J., 2011), specific lung disease target and API(which could help determine necessary size and releasekinetics of the aerosol particles) (Patton J.S. and Byron
P.R., 2007), and inspiratory flow of the individual patient(Kleinstreuer C. et al., 2008; Labiris N.R. and Dolovich
M.B., 2003).
It is worthwhile to note again that it is the aerodynamic
diameter that is important for respirable particles. For example, it has been shown that engineered porous particles

with seemingly irrespirable (> 5 μm) mean geometric sizes
were actually more suitable for respiration compared tosolid particles at a similar size (Edwards D.A. et al., 1997).
For more detailed pharmaceutical aerosol formulation
troubleshooting, design considerations, and synthetic strategies, the reader is directed to the literature for reviews(Finlay W.H., 2019; Hickey A.J. and Da Rocha S.R., 2019;
Pilcer G. and Amighi K., 2010; Vehring R., 2008).
Respirable therapeutic aerosols can be delivered fromseveral devices (Hickey A.J. and Da Rocha S.R., 2019;
Ibrahim M. et al., 2015; Sims M.W., 2011). Pressurized
metered dose inhalers (pMDIs) and nebulizers deliver an
API from solution or suspension. Both devices offer a classical view of an aerosol mist or cloud that delivers the drug
directly from a liquid formulation that is atomized to form
aerosol droplets. In both devices, careful consideration isneeded when selecting surfactants, cosolvents, and, in thecase of the pMDI, propellants that do not a) degrade the
API or b) impact resulting APSD. Nebulizers offer a morepredictable delivery simply depending on the tidal breathing pattern of the individual while the device is continuously generating and aerosol. On the other hand, pMDIs
require more coordination between device and patient. Dry
powder inhalers (DPI) contain a solid dosage form of the
API and are gaining increasing attention for pulmonary
delivery (De Boer A.H. et al., 2017; Frijlink H.W. and De
Boer A.H., 2004; Timsina M.P. et al., 1994). While there
is still some coordination necessary for delivering drug tothe patient, the devices can be made cheaply, do not rely
on a power supply or compressed air (as with nebulizers),
and only depend on the inspiratory flow of the individual
to disperse the powder. There are unique physical mechanisms to consider when dispersing dry powders in the micrometer size range including electrostatics, Van der Waals,

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and capillary forces (Dunber C.A. et al., 1998; Hickey A.J.,
2018). However, a solid dosage form offers better chemical
stability compared to those in solution. And while pMDIs
and nebulizers are more or less dependent on the device todictate APSD, dry powders can be manufactured to wellcontrolled particle sizes as via milling, physical mixing,
supercritical fluid, or spray drying (Telko M.J. and Hickey
A.J., 2005; Vehring R., 2008).
Given the rise in impactful research in the fields of
medicinal metals and inhalational therapies from the mid1900s, there is very little overlapping study. Fe-chelatesdelivered via nebulization have been suggested as an
option for CF treatment (Musk Jr. D.J. and Hergenrother
P.J., 2008). However, there are not many groups suggesting
delivering metals therapeutically to the lungs. This may be
due to a lack of specific research into metals as a pulmonary
therapy as well as a concern over inflammation and toxicity (Bierkandt F.S. et al., 2018; Borm P.J.A. et al., 2006;
Donaldson K. et al., 2002; Jamuna B.A. and Ravishankar
R.V., 2014; Nel A. et al., 2006; 2013). However, there isevidence that a variety of transition metals can be advantageous in the treatment of pulmonary bacterial ailments. Ag,
Cu, Fe, Pd, and Zn have been suggested for tuberculosis(TB) (Chao A. et al., 2019; Ellis T. et al., 2018; Palazzo F.
et al., 2013; Pieters J., 2008; Poole K., 2017), Ag and Pt forlung cancer (with some evidence of dose-dependent toxicity) (Foldbjerg R. et al., 2011; Ndagi U. et al., 2017), andAg, Cu, and Zn for viruses, including coronavirus (Bright
K.R. et al., 2008; Raha S. et al., 2020; Ranford J.D. et al.,
1993; Shittu M.O. and Afolami O.I., 2020; Skalny A.V. etal., 2020). Indeed, with the emergence of drug resistance,
novel therapeutics and unique drug delivery strategies areneeded to overcome said resistance to traditional regimens.
Utilizing metals may be an intriguing option provided
toxicity concerns are addressed (Allahverdiyev A.M. et al.,2011; Chen C.-W. et al., 2014; Ong Y.C. et al., 2019; Sloan
D.J. et al., 2013; Turner R.J., 2017; Van Duin D. and Paterson
D.L., 2016). MOFs and coordination polymers are an
emerging class of materials that may be suitable as a drugdelivery vehicle to the lungs.

3. Biomedical applications of MOFs
MOFs are highly crystalline and porous coordination
polymers that are assembled by the formation of multiple
coordination bonds between inorganic metal nodes (either metal ions or metal oxide clusters) and multidentateorganic ligands. MOFs offer structural designability at
the molecular level together with tunable porosity andchemical functionalization. Due to their tailored features,
especially elevated surface area and hybrid organicinorganic compositions, MOFs have been studied for a
myriad of applications such as gas storage and separations

140(Sumida K. et al., 2012) , nonlinear optics (Yu J. et al.,2012), catalysis (Corma A. et al., 2010; He X. and Wang
W.-N., 2019; Luz I. et al., 2010), sensing (Kreno L.E. et al.,2012), or molecular-based magnetisms (Coronado E. et al.,2013). During the last decade, MOFs have also been considered for medical applications ranging from preciselycontrolled release of drugs to imaging (Chen W. and Wu
C., 2018; Della Rocca J. et al., 2011; He C. et al., 2015a;
McKinlay A.C. et al., 2010).
Nano and micro sized MOF particles are required to
exploit certain biologically relevant mechanisms (Novio
F. and Ruiz-Molina D., 2017). For instance, particle sizes~500 nm influence the circulating time in the blood stream
and facilitate their introduction into cells by endocytosis.
Particles smaller than 250 nm are most suitable for crossing the vascular endothelium (Giménez-Marqués M. et al.,2016). Fortunately, MOFs of many size ranges can be easily prepared by conventional methods (i.e., solvothermal/hydrothermal synthesis, microwave-assisted, sonochemical) (Stock N. and Biswas S., 2012) or alternative methodologies ranging from microemulsion and templating (Luz I.
et al., 2017; 2019) to spray-drying (Carne-Sanchez A. et al.,2013) and continuous-flow techniques (Friščić T., 2011).
MOFs also exhibit a high external surface-area-to-volume
ratio which aids in colloidal stability, biocompatibility,
recognition capabilities, and biodistribution (Oh M. andMirkin C.A., 2005). Showcasing their potential for stability in biological pH, MOFs can be made to withstandpH as low as 1.2 (as in the gastrointestinal tract) (Ding
M. et al., 2019; Rojas S. et al., 2018) and there have evenbeen reports of manufacturing MOFs with local “buffer”
environments that were appropriate for pH 1.5–12.5 (HeH. et al., 2018).
The surface of MOF nano- and micro-metric crystals
can be functionalized to address specific biological andmedical needs via two attachment techniques: covalent (i.e.
condensation, click chemistry, and conjugation reactions)or non-covalent (i.e. electrostatic interactions, dispersion
forces, and hydrogen bonding) (Sapsford K.E. et al., 2013).
On one hand, organic or inorganic nanomaterials have been
considered to address the challenges related to the use of
conventional treatments, diagnosis, monitoring, and control of biological systems (i.e., drug resistance, systemic
toxicity, poor treatment efficacy, and safety) (Patra J.K. etal., 2018). But MOFs are hybrid organic-inorganic materials that offer potential advantages compared to these purelyorganic or inorganic carriers for biomedical applications.
These advantages are: size control over nano and microscale and the ability to compose MOF superstructuresof individual MOF sub-components; tailored structures(physicochemical properties including metal-ligand compositions, crystallinity, particle size, and morphology)
allowing for the incorporation of multiple functionalities
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release (accounting for biological compatibility and stability in physiological environments); large surface areas andporosities to facilitate higher drug loading capacity; weak
coordination bonds that ensure MOFs are biodegradable(Wu M.X. and Yang Y.W., 2017).
Biodegradability and stability of MOFs are arguably
the most important concerns that need to be addressed
prior to potential therapy. The decomposition of MOFs at
a desired region is recommended to avoid endogenous accumulation. As illustrated by Fig. 4, three main approaches
have been developed to incorporate drugs or biologically
active components in MOFs and are classified by thetype of interaction (bond strength) between them. They
include 1) encapsulation of the drug within the MOF poresystem (weak interaction) (Horcajada P. et al., 2008), 2)
the drug is the organic linker in the MOF via coordinationbond (medium interaction) (Rojas S. et al., 2017), and 3)
the drug is bonded via post-synthetic modification to the
MOF framework via covalent bond (strong interaction)(Taylor-Pashow K.M.L. et al., 2009). This variety of possibilities enables the pinpoint triggered release of therapy
at the target by different biologically induced stimuli,
such as pH, temperature, magnetic field, ionic species,
pressure, or even light radiation. For bio-applications,the precise chemical stability of MOFs is also crucial toenable targeted drug release and avoid the excessive early
decomposition and/or accumulation of the MOF individual
chemical constituents. The most widely investigated approach is pH-responsive MOF carriers, especially for cancer therapy (Wu M.-X. and Yang Y.-W., 2017), because theacidic tumor microenvironment can disassemble the MOF
scaffold via cleavage of the coordination bonds (which aresensitive to external acidic pH), thus releasing the hybrid
components. Therapies targeting endo-lysosomal release of
MOF cargo in macrophages may benefit from this strategy
as well since the pH value in a macrophage lysosome isbetween 4–5 while the phagosome remains neutral (Chen
T.-T. et al., 2018; Russell D.G. et al., 2009).
The first examples considering MOFs as potential drugdelivery systems via drug encapsulation (Fig. 4a) within

the MOF pores were reported by Horcajada et al. (Horcajada P. et al., 2006; 2008). These MOFs (intended forgeneral administration) were built from low-toxic iron andmulti-carboxylate ligands (MIL-100, MIL-101, and MIL53) and were suggested for the delivery of the drug ibuprofen, exhibiting high drug-storage capacity and a complete
drug-controlled release under physiological conditions.
The large “breathing” effect of the flexible framework of
MIL-53 was demonstrated to be an interesting feature forpotential applications in drug delivery. The same groupalso reported the first biodegradable therapeutic MOF withpellagra-curative, vasodilating, and antilipemic properties(BioMIL-1) (Horcajada P. et al., 2008). This MOF was
built up from a non-toxic Fe species and a therapeutically
active linker nicotinic acid (Fig. 4b). The release of thedrug, a constituent of the framework, was achieved via
degradation of the hybrid crystalline phase simulated physiological conditions (Miller S.R. et al., 2010).
The ability to combine metals and organic molecules
in a single element in the MOF hybrid structure (Fig. 4b),
opens up the possibility of pursuing synergetic effects
between metal and drug upon delivery via frameworkdegradation (Rojas S. et al., 2017). For example, in thework by Tamames-Tabor et al., azelaic acid was combined
as a linker with an endogenous transition metal cation,in this case Zn2+ (Tamames-Tabar C. et al., 2015). The
authors asserted that since both linker and metal exhibitedinteresting antibacterial and dermatological properties forthe treatment of skin conditions, both components should
be combined into a biocompatible and bioactive MOF(BioMIL-5), which they found to be stable in water andin bacterial culture medium. The progressive slow releaseof both active constituents allowed growth suppression of
Staphylococcus epidermidis over 7 days, suggesting that
this MOF can be a good candidate for future bio applications in skin care and cosmetics.
Taylor-Pashow and coworkers demonstrated that bothan optical contrast agent (BODIPY dye) and an anticancer
prodrug (ethoxysuccinato-cisplatin) could be covalently
bonded to the free amine functionalization of (Fe)MIL-

Fig. 4 Strategies for drug inclusion within MOFs: a) encapsulation of the guest drug within the MOF host pore system (weak interaction); b) the guest
drug acts as organic linker within the MOF host bonded by coordination bonds (medium interaction); c) the guest drug is bonded via post-synthetic
modification to the MOF host framework via covalent bond (strong interaction).

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101(NH2) nanocrystals via post-synthetic modifications(see Fig. 4C). These constituents were then released upondisassembly of the MOF framework under acidic conditions present in a tumor environment. In addition, the rateof cargo release was further controlled by coating the MOF
sub-constituents with an inert silica shell. The potential
utility of this multicomponent MOF drug system for
optical imaging and anticancer therapy was demonstrated
in vitro using HT-29 human colon adenocarcinoma cells(Taylor-Pashow K.M.L. et al., 2009).
Research concerning the toxicity of MOFs and overall
regimen implications (Sajid M., 2016) continues to be
conducted. It is thought that MOF constituents will progressively break down in the body; however, since thefield maturing, there is still work that needs to be doneto elucidate MOF toxicity and pharmacokinetics further(regardless of administration route), both at the superstructure level and for the fate of each sub-constituent (HeC. et al., 2015b; Horcajada P. et al., 2012; Novio F. andRuiz-Molina D., 2017; Sun C.-Y. et al., 2013). On the other
hand, the desirable triggered release and biocompatibility
properties, along with their large surface areas and highporosities, have positioned MOFs as promising materials
for drug delivery and other therapeutic applications (Beg S.
et al., 2017; Giménez-Marqués M. et al., 2016; Horcajada
P. et al., 2012; Liang Z. et al., 2018; Wu M.-X. and Yang
Y.-W., 2017; Rojas S. et al., 2018). MOF lung delivery via
a systemic route (Simon-Yarza T. et al., 2017) has been
considered but the manufacture and delivery of MOFs as
an aerosol has not until recently been explored.

4. Facile generation of MOF aerosols via
spray drying
The wide applicability of MOFs has generated wide appeal across scientific research fields as summarized above.
MOFs are especially gaining traction in the medical field
for enhancing drug delivery via oral (Abuçafy M.P. et al.,2018; Chen Y. et al., 2018) and intravenous (Bian R. et al.,2015; Zhao H.-X. et al., 2016) routes. One area that has
thus far remained largely unexplored is the use of MOFs
as inhalation therapies for pulmonary disorders. This is
despite the existence of a relatively facile manufacturingmethod commonly used to generate respirable microparticles: spray drying.
Spray drying is used as a controllable, continuous
process to generate solid nano- and micro-particles fromsolution for various applications from food additives to fuelcells to ceramics to pharmaceuticals (Eldridge J.A. et al.,2014; Ramavath P. et al., 2014; Santana L.P. et al., 2008;
Ziaee A. et al., 2017). Its main pharmaceutical application
is manufacturing amorphous particles from an otherwise
water insoluble API for use in solid dosage forms, i.e.

142tablets. Among other things, this strategy increases drug
product bioavailability (Baghel S. et al., 2016). As mentioned above, however, dry powders suitable for therapeutic inhalation delivery can also be produced with aspray dryer. Recently, spray drying has been demonstrated
by Carne-Sanchez et al. (Carne-Sanchez A. et al., 2013;
Garzón-Tovar L. et al., 2016) as a versatile continuous flow
method to assemble nanoMOFs into micrometric hollow
spherical superstructures (Fig. 5). This strategy conceptually mimics the standard emulsions used to confine thesynthesis of MOF materials but does not require secondary
immiscible solvents or surfactants, which can reduce production time and cost. In the work by Carne et al. in 2013,
the generality of this continuous flow strategy was provenfor a broad range of MOFs (i.e. ... HKUST-1, Cu-BDC,
NOTT-100, MIL-88A, MIL-88B, MOF-74, UiO-66, andZIF-8, among others). Members of this research group
have also demonstrated the synthesis of UiO-66 in aqueous
solution (Avci-Camur C. et al., 2018), addressing one of thechallenges currently precluding the industrial exploitationof nanoMOFs: the lack of water-based, efficient methods
for their synthesis. This unique MOF morphology obtainedby spray drying (the arrangement of MOF nanocrystal
sub-components into hollow spherical microparticulate
superstructures) can seemingly address three attributes ofaerosolized drugs: 1) generation of hollow, low density
spherical particles suitable for respiration, 2) potential for
MOF microparticle disassembly into MOF nanocrystals
suitable for a wider range of endocytosis, and 3) controlled
pH-triggered coordination bonds to be cleaved under acidic
macrophage or tumor environment releasing the active
drug(s). A review of MOF spray drying can be found in theliterature (Troyano J. et al., 2020).
The synthesis of MOFs via spray drying starts withatomization of a precursor solution into microdroplets
using a two- or three-fluid nozzle (Fig. 5). This step is
accomplished by simultaneously injecting the solution at
and compressed air or nitrogen. Each precursor droplet
contacts (and is suspended by) a gas stream heated to acertain temperature. The solvent then begins to evaporate
causing the precursors to diffuse radially to the droplet
surface (Fig. 5b). It is important to note that spray drying
can be utilized under completely aqueous conditions andthe inclusion of organic solvents is not necessary, but can
aid in the formulation process (dissolving solutes, impacting precipitation rate of the solid particles, etc.). As theevaporating droplet shrinks, precursor concentrations at
the droplet surface increase until supersaturation is reachedat which point MOF nanocrystals begin forming and arranging into a well-packed shell at the drop surface. Spraydrying is a mature technology that can be transferred frombench to pilot to manufacturing scale in many industries,
including pharmaceutical (Dobry D.E. et al., 2009; Kemp
I. et al., 2016; Poozesh S. and Bilgili E., 2019). TheoreticalIan E. Stewart et al. / KONA Powder and Particle Journal No. 38 (2021) 136–154

Fig. 5 Spray drying synthesis of spherical hollow HKUST-1 superstructures. a, b) Schematic showing the spray-drying process used to synthesize
HKUST-1 superstructures. c) Photograph of the spray-dryer. d–f) Representative FESEM images showing a general view of the spherical HKUST-1
superstructures. Scale bars: 5 mm (d), 500 nm (e, f), 200 nm (f, inset). Reprinted by permission from Springer Nature: Nature Chemistry, A
spray-drying strategy for synthesis of nanoscale metal–organic frameworks and their assembly into hollow superstructures, Arnau Carné-Sánchez etal., Copyright 2013(Carne-Sanchez A. et al., 2013).

and experimental considerations for particle engineering
via spray drying can be found elsewhere (Vehring R., 2008;
Vehring R. et al., 2007).
The discovery that this robust technique could be used
to manufacture hollow hybrid microparticles incorporating
metal species, i.e. MOFs, had the potential to initiate more
research toward their aerosol characterization specificallyfor pharmaceuticals. But there have been very few accounts suggesting the use of MOFs for pulmonary delivery
and even less using this widely available and scalable
manufacturing technique.

5. Aerosolized MOFs for pulmonary therapy:
Pioneer works and future prospects
The specific potential for aerosol delivery of MOFs for
pulmonary therapies has recently begun to appear in theliterature. Hu et al. showed that budesonide (an anti-asthmadrug) can be loaded into γ-cyclodextrin (CD) MOFs thatexhibit acceptable respirable particle sizes (MMAD justunder 5 μm), good cell viability and biocompatibility in
A549 human lung alveolar cells, similar budesonide distribution and PK as the commercial control, and were welltolerated in rats when administered via insufflation (DP-4R
Penn-Century insufflator) (Hu X. et al., 2019). However,this version of MOF does not contain transition metals.

Iron based MOFs (MIL-88A(Fe) and MIL-100A(Fe))
were shown to be endocytosed by alveolar macrophagesin vitro subsequently accumulating in acidic regions where
airway-based pathogens, such as Mtb, are known to reside(Guo A. et al., 2019). Wyszogrodzka et al. (Wyszogrodzka
G. et al., 2018) reported that Fe-MIL-101-NH2, a widely
studied biocompatible Fe-MOF carrier for drug delivery,
can be an effective carrier for isoniazid (INH), a first-line
anti-TB drug. This group demonstrated that MOF particles
accumulate in the cell cytoplasm. They reported sustained
drug release inside cells in contrast to fast dissolution of
crystalline INH powder. Additionally, these MOFs had
low cytotoxicity and can serve as MRI contrast agents; i.e.
a theranostic system combining diagnostics and delivery.
Their work was extended to theophylline, an anti-asthma
and COPD drug, loaded into Fe-MIL-100 microparticles(via traditional MOF synthetic routes). As in the previous
case, the drug was found to have sustained release in vitro
and was nontoxic against human epithelial cells and murine
macrophages after uptake. There were minor increases
in reactive oxygen species which subsequently returned
to baseline after 72 h. (Strzempek W. et al., 2019). Thesestudies showcased promise for biocompatibility of MOFs
for lung delivery, but aerosol characterization was lacking.
Even with the discovery that MOFs could be spray dried
into hollow spheres in size ranges suitable for respirationin 2013 (Fig. 5), there are very few accounts utilizing this143

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proven aerosol generation technique as a possible drug
product manufacturing mechanism. Anti-TB MOF delivery
to the lungs would be a reasonable therapy target considering that MOFs and MOF composites have been suggested
for use as antimicrobial applications previously (Shen M.
et al., 2020; Wyszogrodzka G. et al., 2016). To reach thisend, designing MOFs to efficiently deposit in the lungs via
dry powder aerosol to locally attack TB can be realizedby spray drying. To the best of our knowledge, there are
only three reports that characterize aerosolized spray dried
MOFs for potential pulmonary delivery – all motivatedby anti-TB potential. This strategy is understandable as
DPIs have shown promise as an alternative treatment
for TB with benefits over standard oral and intravenous
regimens such as lower systemic toxicity, local access to
the lung granulomas containing Mtb, and avoiding painful
injections. Activity in this research area is well documented(Braunstein M. et al., 2019; Dharmadhikari A.S. et al.,2013; Hickey A. et al., 2016a, b; Mehta P. et al., 2018). Ina more recent work using the same MOF-based delivery
system as above, Wyszogrodzka et al. produced MOFs
where INH was encapsulated in Fe-MIL-101-NH2. Afterwards, it was combined with poly(lactide-co-glycolide)
and leucine via spray-drying leading to a microparticle
composite (Fig. 6a) (Wyszogrodzka-Gaweł G. et al.,2019). This MOF exhibited good aerodynamic properties,
controlled release of INH, uptake by macrophages in vitro,
low cytotoxicity, and extended their theranostic application. Importantly this was the first reported use of MOFs
as a dry powder for inhalation. Similarly, Fernandez-Paz
et al. recently produced nanoparticle aerosols from (Fe)MIL-100 MOFs and various biocompatible carbohydrates(i.e. mannitol) via spray drying (Fernández-Paz C. et al.,2020). Notably, these MOF composite particles did not
result in an inflammatory response when delivered to rats
intratracheally and the release of the intact MOF constitu-

Fig. 6 SEM images and schemes for two recent MOF-based aerosol
drug delivery systems prepared via spray drying: a) active drug encapsulated in inactive MOF and combined with excipient (drug@MOF/
excipients), SEM extracted from reference (Wyszogrodzka-Gaweł G.
et al., 2019); b) active metal and active drug are combined to form a
metal-drug bioMOF, SEM extracted from reference (Luz I. et al., 2020).

144

ent nanoMOFs embedded within the superstructure carrier
was determined to be uniform along the lungs, reaching thebronchioles and alveoli. Therefore, state-of-the-art MOFs
can be spray dried, subsequently filled with drugs, andutilized as aerosolized microparticles using soluble gluelike excipient components. However, despite the existenceof the initial work of Carne-Sanchez et al. (Carne-Sanchez
A. et al., 2013) demonstrating the continuous-flow preparation of several MOF compounds via spray drying, theutilization of “pure” MOF hollow spheres, i.e. where all
metal and organic MOF components are considered active(bioMOFs), as aerosolized drug caariers was not considered in these first publications (Horcajada P. et al., 2012;
Rojas S. et al., 2017).
Our group has experience with the preparation of inhalable anti-TB drugs via spay drying and the characterizationof dry powder aerosols (Durham P.G. et al., 2016; Durham
P.G. et al., 2015; Hickey A.J. et al., 2020; Mortensen N.P. etal., 2014; Pitner R.A. et al., 2019; Stewart I.E. et al., 2019).
Given the rise in multi drug resistant (MDR) and extensively drug resistant (XDR) TB (Sloan D.J. et al., 2013;
Van Duin D. and Paterson D.L., 2016), novel treatments arenecessary including via a) inhalation, b) new drugs, and/orc) inclusion of metals. Therefore, we recently developed aspray drying procedure for preparing Cu-POA (pyrazinoicacid) hollow spherical microparticles (Fig. 6b). Our choiceof Cu was based on evidence of its anti-TB potential (Festa
R.A. et al., 2014; Neyrolles O. et al., 2015; Speer A. et al.,2013; Wolschendorf F. et al., 2011) as well as demonstrated
in vitro synergy with other known anti-TB drugs (Manning
T. et al., 2015a; 2015b; 2017; Speer A. et al., 2013). POA
has been explored as an anti-TB candidate since it isconsidered a prodrug of pyrazinamide (PZA), a current
first line TB drug experiencing drug resistance from Mtb(Durham P.G. et al., 2015; Via L.E. et al., 2015). Our results
show that this potential anti-TB MOF can be spray dried in
one step from a mostly aqueous solution, excipient-free, toproduce a dry powder with APSD suitable for respiration(Luz I. et al., 2020). The use of pure metal-drug compounds
linked by coordination bonds can enable the controlled
local release of the organic drug and the metal “codrug”
simultaneously, in this case Cu2+ and POA (Fig. 6b). Thisapproach avoids the use of unnecessary inactive components, i.e. organic ligands or metal ions typically found in
MOF carriers. These do not contribute to the therapeutic
treatment and only provide structural roles, thus removing
them can reduce possible toxic contributions. As well,since the polar functional groups of POA are coordinatedto the Cu, moisture uptake can be avoided. However, that is
not to say excipients are unnecessary during spray drying
the formulation process in general; indeed excipients are acommon formulation strategy to prevent moisture ingress,
encapsulate particles, control release, or aid in dispersion(Bosquillon C. et al., 2001; Gordon M.S. et al., 2000;

Ian E. Stewart et al. / KONA Powder and Particle Journal No. 38 (2021) 136–154

Sarrate R. et al., 2015; Telko M.J. and Hickey A.J., 2005).
Rather this is an alternative approach that designs inhalable MOFs or coordination polymers composed of solely
therapeutic metal and organic components. In addition to
mitigating the risk of possible toxic responses higher doses
can be achieved (no excipient).
To facilitate this design, non-essential MOF properties
for drug release applications can be obviated dependingon the requirements of the delivery system, i.e. porosity or
crystallinity. This unleashes a myriad of possibilities fordesigning multifunctional drugs containing the suitable
metal-drug components linked by stimuli-responsive coordination bonds widening the range of pulmonary diseasetargets. These materials may be considered as MOFs, if
porous and crystalline, or simply as coordination polymer
particles (CPP) if amorphous or non-porous (Novio F. etal., 2013).
Although TB has been the primary potential target formost of the early work on spray dried therapeutic aerosolized MOFs, it is certainly not the only potential pulmonary
target. As mentioned above, lung cancer, other chronic
conditions such as asthma, and viruses might benefit froma unique respirable therapy that includes coordination
metal-organic components. As well, using the lungs as a
strategy to deliver drugs via MOFs systemically can also
be considered once more information on toxicity and pharmacology is discovered.
Considering MOFs can be fabricated to remain stable inneutral solution, it may be possible to formulate active species for inclusion in nebulizers and pMDIs as suspensions(Wang G.-Y. et al., 2014). Indeed, metal-phenolic (Fe) capsules have recently been explored as nebulized drug carriers for pulmonary delivery while not specifically definedas MOFs. Accumulation in alveolar macrophages with low
inflammation was indicated in vivo which suggests that
MOFs could be utilized in similar nebulizer applications(Ju Y. et al., 2020). MOFs can also be spray dried into aerosolized microparticles for use in DPIs. Since MOFs andtraditional organic APIs are capable of being spray dried
separately as well, this might enable combination therapyof several distinct inhaled (or otherwise administered)drugs; synergistic and additive effects might be possible
with the inclusion MOFs. Additionally, several APIs and/or
metals could be coordinated to the MOF scaffold. This may
aid in controlled release and the well-triggered delivery ofseveral medications at their appropriate time.

6. Conclusion
The goal of this review was to briefly present two
promising individual areas of research (MOFs and aerosol
drugs) whose potential intersection has not been, to ourknowledge, thoroughly investigated. While there is risk

associated with utilizing inhaled metals as a therapeutic
agent given toxicity concerns, there exists dose-dependent
toxicity associated with almost any drug. Moreover, MOF
metal and organic synthetic components can be diluted orconcentrated to adjust their final concentration levels toreflect a desired therapeutic window. Therefore, expanding
the use of metals in medicine to include pulmonary administration should not be discounted as there are inherent
tradeoffs with any regimen once a toxicity threshold isestablished. To facilitate this work we believe MOFs, as
an emerging class of drug delivery vehicles, offer a uniqueapproach toward inhaled therapy. They are capable ofbeing formulated into highly porous, hollow microparticles or manufactured as low-density dry powders withappropriate aerodynamic diameters thus hurdling the firstbarrier for use as a pharmaceutical aerosol. However, there
is a need for further contributions toward characterizing the
aerodynamic performance of MOFs to ensure suitability
for pulmonary delivery and assessing or connecting theiractivity and efficacy toward specific lung targets in vitro
and in vivo. We believe considering this area of researchoffers great potential for collaboration and advancement
over several disciplines including materials science, aerosol physics, biology, pharmacology, and medicine.

NomenclatureAPI

active pharmaceutical ingredient

APSD

aerodynamic particle size distribution

BDC

benzene-1,4-dicarboxylate

BODIPYboron-dipyrrometheneCFcystic fibrosis

COPD

chronic obstructive pulmonary disorderCPcoordination polymers

CPP

coordination polymer particle

CD

cyclodextrin

DPI

dry powder inhaler

EPR

enhanced permeability and retention effect

FPF

fine particle fraction

GSD

geometric standard deviation

HKUST

Hong Kong University of Science and Technology

INH

isoniazid

MMAD

mass median aerodynamic diameter

MDI

metered dose inhaler

MOF

metal organic framework

MILmaterials of Institute LavoisierMRI

magnetic resonance imaging

NPnanoparticle

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Ian E. Stewart et al. / KONA Powder and Particle Journal No. 38 (2021) 136–154

NOTT

University of NottinghamPDpharmacodynamicPKpharmacokinetic

PLGA

poly(lactide-co-glycolide) acidpMDI

pressurized metered dose inhaler

POA

pyrazinoic acidTB

tuberculosis

UiO

University of Oslo

USP

United States Pharmacopeia

ZIF

zeolitic imidazole frameworkdae

aerodynamic diameterdv

volume diameterρpparticle densityχdynamic shape factor

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Authors’ Short Biographies
Ian E. Stewart
Dr. Stewart is a Research Chemist in the Engineered Systems Center within the Technology Advancement for Commercialization Division at RTI International. He has abackground in materials chemistry, specifically oxidation resistant metal nanomaterials forelectronic applications. Dr. Stewart’s present role involves the formulation and characterization of inhalable solutions toward airway pathogen treatment. Dr. Stewart received his
B.S (chemistry) from Randolph-Macon College and his Ph.D. (nanomaterials chemistry)from Duke University. Prior to his current position at RTI International, Dr. Stewart was a
postdoctoral scientist at the same institution where he helped developing polymeric nanomaterials and hydrophobic coatings.

Ignacio Luz
Dr. Luz is a Research Chemist at RTI International with over a decade of experience developing novel advanced technologies and materials based on Metal Organic Frameworks(MOFs) to solve technological challenges in energy, health, and environmental applications, including catalysis, electrocatalysis, photocatalysis, energy materials and storage,
drug delivery as well as gas separations and storage. Dr. Luz received his B.S. (Chemical
Engineering) from the Polytechnical University of Valencia, Spain, and his M.S. and Ph.D
(Chemistry) from the Instituto de Tecnologia Quimica (Valencia, Spain). He also worked
as Postdoctoral Researcher at Lawrence Berkeley National Laboratory Berkeley (Berkeley,
California).

Ninell P. Mortensen
Dr. Mortensen is a Research Biologist in the Center for Analytical Chemistry and Pharmaceutics at RTI International. She has experience with nanomaterial in vitro and in vivo
exposure studies and serves as a Principle Investigator on research programs investigating
the biological impact of early life exposure to engineered nanomaterials and addressing theneeds for reference materials in nano- and microplastics research. Dr. Mortensen received
her B.S. and M.S. (Biology) from the University of Copenhagen, Denmark, and her Ph.D.
(Biotechnology) from the Technical University of Denmark. She held a Postdoctoral Fellowships at University of Tennessee and Oak Ridge National Laboratory (Biotechnology).

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Review Paper

Mechanochemical Preparation of Mineral Based Adsorbent andIts Effective Purification Ability for Wastewater †Huimin Hu and Qiwu Zhang*
School of Resources & Environmental Engineering, Wuhan University of Technology, China

Abstract
With the economic development, environmental pollution is getting worse in many developing countries including
China. Traditional processing as CaO neutralization of acidic solutions is still a burden to many local governmentsof China and development of new process with lower cost is highly required. Mining exploitation produces large
amounts of tailings in which industrial minerals such as carbonates, silicates and others have been left without
proper utilization. Based on the intensive investigations in the field of mechanochemistry, we propose to use thesemineral samples to deal with the purification of heavy metal polluted water by enhancing their reactivity throughmechanochemical activation. The industrial minerals such as silicates (serpentine and kaolinite), carbonates (calcite)
have been studied for the purposes on removal of contaminants from solution. In addition, the synergistic effects
from mixtures of calcite with other material have been investigated to give their excellent adsorbent performancefor purification of the wastewater. This review summarizes the recent progresses for mechanochemical preparationof mineral based adsorbent and its effective purification ability for toxic matter-containing wastewater.
Keywords: mechanochemical preparation, non-metallic mineral, industrial minerals, adsorbent, purification,
waste water, milling

1. Introduction
Industrialization of the human society may begin withthe exploitation of various kinds of minerals. Mineralprocessing has been an important technique to support thedevelopment of civilization. The applicable minerals canbe categorized mainly into two groups: the first one is metallic mineral resource such as hematite, magnetite, chalcopyrite and galena, which are used to produce metals suchas iron, copper and lead, and another one is non-metallic
mineral resource, so called as industrial minerals, such as
silica, gibbsite, clay, calcite, mica and talc, which are usedparticularly as additives and fillers in the productions ofpaper, plastic, paint, as well as raw materials in the productions of cement, ceramic, glass and so on. Metallurgicalprocessing of metallic minerals is also a main source toemit heavy metals to pollute the environment, but strange
though it may seem, the abandoned mines are actually theother source, seeping pollutant into the environment with
underground water or raining.
A key technology enabling to develop new applications
for processing these industrial minerals is mechanochem†

Received 22 May 2020; Accepted 22 June 2020
J-STAGE Advance published online 17 July 2020
* Corresponding author: Qiwu Zhang;
Add: 430070 Wuhan, China
E-mail: zhangqw@whut.edu.cn

ical activation, mainly triggered by a simple operation ofball milling, which is widely used in mineral processing
for concentration and enrichment of target minerals. When
powder particles are trapped between balls colliding inside
a mill pot, then the particles deform elastically and/or plastically, and are finally fractured into fine fragments, which
are easily agglomerated due to the mechanical activation.
The force of the impact during the grinding acts on the
powder particles, leading to crystallographic bonds broken
and new surface is produced. The new surfaces createdenable the particles to aggregate and agglomerate eachother easily and this leads to an increase in the degree inthe activation of solid material. Profound changes affecting
the surface as well as the chemical, physicochemical andstructural properties may also take place. This is manifested by the presence of a variety of crystal defects suchas increased number of grain boundaries, dislocations,vacancies and interstitial atoms, stacking faults, and deformation with rupture of chemical bonds. The presence ofsuch crystal defects enhances the diffusivity of chemicalcomponents in the solid.
We have been doing investigations from the viewpointof mechanochemistry, involving a wide range from mineralprocessing, materials synthesis, metallurgical extraction
to detoxification of hazardous materials. Accumulationsof our obtained knowledge and understanding of thenature of mechanochemistry allow the development of

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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new mechanochemical route for preparing mineral based
adsorbent and its effective purification ability for toxic
matter-containing wastewater. This review gives brief
points reflecting our recent issues in this field, with related
publications listed.

2. Current status in heavy metal
pollution and applications of industrial
minerals activated and modified bymechanochemical treatment in order topurify wastewater
At the early stage of economic growth, developing countries may face serious environmental problems, and one ofthem is the heavy metal pollution. The large amounts ofmetal sulfate wastewater produced in the mining and otherindustries are the major cause of heavy metal pollution to
the environment. The solution to such problem requires imminent action. In this regard, the action would be important
to work out it by two approaches; one is a positive one
improving the processing efficiency, reducing the amountof waste emissions, and the second is a passive one purifying and decontaminating wastewater. Lime precipitation
is currently the main method for purification purpose, but
it has brought us obvious disadvantages such as high pH
of water, high water percentage to the sediment, difficult
filtration and so on. The use of non-metallic minerals forthe purification purpose does not cause normally significant negative problem, so that it would be recommended inpractical application, if such disadvantages are improved.
One of the methods for improving them would be chemical
modification of adsorbents.
Heavy metal contamination is a growing concern inthe world, inadequate polluted water and/or wastewater
treatments, coupled with increased industrial activity, havebrought about serious heavy metal contamination in rivers,
lakes, water reservoirs and so on, spreading over the vast
area. However, popular technological methods for remov­‑
ing heavy metals from water sources such as membrane
filtration, activated carbon adsorption and electrocoagulation are not always feasible for developing countries due to the viewpoints of economy and infrastructure.
As a result, many researches have been attempted for theapplicability of low-cost adsorbents to remove heavy metals in the solution. Several scientific papers discussed on
the use of alternative adsorbents such as agricultural waste,soil, mineral deposits, aquatic and terrestrial biomass andwaste materials.
On the other hand, clay minerals, which are typicalnon-metallic minerals, exhibiting the adsorbent characteristic, and have been excavated as sedimentary or residual
deposit from the earth. This implies that the minerals arenormally cheap and abundant natural resources found156

easily in the world. The minerals have been examined
as adsorbents of many contaminants in mainly aqueous
solutions. Clay minerals are very reliable and an environmentally friendly remediation material for heavy metal
contaminated media. Also, several methods are available
for the modification of clay minerals in order to increase
their adsorption capacity. However, in order to take firstpreference in the use of clay minerals as heavy metal remediation materials compared to other methods, further technological investigations are required, leading to determine
the best modification type for clay minerals as well as theirleast dosage required for the adsorption of heavy metals.
Similar to the clay minerals, carbonate minerals such as
calcite and dolomite are also widely studied as economical
adsorbents to dispose in heavy metal polluted water byneutralizing typical acidic wastewater. Due to the relatively
low capacity in these raw minerals as absorbents, chemical
modification is, in general, required to enhance the adsorption ability as well as its regeneration and reduce the waste
sludge amount after the disposal.
Grinding operation of the raw mineral samples has
widely been used to reduce the particle size, to increase thespecific surface area together with mechanical activationsites on the surfaces. This activation leads therefore toenhancement in the reactivity with heavy metals when it issuspended in the polluted water and its removal efficiency
from the solutions. Besides the physical changes in particle
size, structural deformation and so on, intense grinding
a solid can induce its physicochemical changes, namely
mechanochemical effects, by which high reactivity of theground solid toward heavy metal removals in the solution
may be expected. This result is, therefore, linked with considerable reduction in the amounts of the mineral samples
with keeping efficient performance for environmental remediation. This special modifying method based on mechanochemical effects particularly resulting from intense ball
milling is fully investigated and discussed in our group andserves as the main contents of this review paper.

3. Activation and modification of nonmetallic minerals by milling
3.1 Hydrated magnesium silicate: Serpentine
Serpentine, (Mg, Fe)3Si2O5(OH)4, is a generic term fora typical class of hydrous magnesium-rich phyllosilicate
minerals. At present, serpentine is generally associatedwith some metal deposits in nature and often abandoned asa gangue mineral, which is not only a waste of serpentine
resource, but also a serious impact on the environment.
Serpentine has unique characteristics of phyllosilicate minerals on the adsorption of heavy metal ions, however the
raw sample gives limited capacity on heavy metal removal

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Fig. 1 Changes in dissolved Mg2+ concentration (a) and pH value (b) in the solution with the rotational speed of the stirred mill when the serpentine
activated was dispersed in it (Huang et al., 2017).

from environmental pollution. When serpentine is modified
and activated mechanically by milling, structural damage
to this mineral would be a drawback, obstructing the use of
its unique characteristics. However, if milling this mineral
makes it possible to maintain its adsorption ability withkeeping increment in the specific surface area, there would
be possible to increase its reactivity to other species such as
heavy metal ions and contaminants in solution.
One typical feature of serpentine milled is the gradualtransformation of its crystalline structure to amorphousstate, which is commonly observed with hydrated phyllosilicates by intense dry grinding. Investigations into further
changes with the ground serpentine sample have revealed
interesting phenomena. We have ground serpentine sample
by a stirred mill, followed by a dissolution test on the sample into a distilled water. Typical results on this work areshown in Fig. 1 (Huang et al., 2017). The serpentine samples milled for 2 h at different speed were dispersed into
distilled water for 4 h without any other chemicals, as seenin Fig. 1(a), Mg2+ ion content in the water increases rapidly
with increase in mill speed and level off over 400 rpm
milling operation. This means that the serpentine activatedis dissolved into the water with releasing Mg2+, while theraw sample without activation has not shown such obvious
dissolution behavior of Mg2+ in the water. This suggeststhat the serpentine milled has transformed into activatedstate even more than brucite of which an industrial mineral form is magnesium hydroxide, the chemical formula
Mg(OH)2. Furthermore, Fig. 1(b) show the pH of the water
when the serpentine samples activated are dispersed in asa function of mill speed. As seen, the pH is changed from6.25 in the initial stage to 10.8 at 500 rpm in mill speed,
and it increases drastically in the rage from 200 to 400 rpm.
According to the data on XRD analysis of the sample, thestructural change in the sample is remarkable in the samemill speed range as described above. Both changes in
specific surface area and crystalline structure may affectthe Mg ions release and pH increase. It is understood thatat mild milling with speed lower than 300 rpm, increase

Fig. 2 Changes in remaining copper concentration with the dosage ofthe activated serpentine at different milling speed (rpm) of the mill with
10 mg/L initial Cu 2+ concentration (Huang et al., 2017).

in specific surface area may occur as the main factor andstructural changes occur mainly at milling speed around
600 rpm, respectively.
We have extended the investigation on the reactivity ofserpentine sample activated by the mill at different conditions to find out its adsorption ability in several polluted
solution with Cu and Ni ions. The dosage, initial concentration of the solution and other factors were changed andtested in the experiments. A typical result on the adsorptionof Cu2+ in solution by the serpentine sample activated under different mill speeds in the range from 200 to 400 rpm
is shown in Fig. 2. At first, it is recognized from the figurethat the activated serpentine sample exhibits the adsorption
ability to Cu2+ in the solution. In addition, the residual Cu2+
ion content in the solution is decreased with an increase in
the dosage of the sample, depending on the mill speed. The
residual Cu2+ content becomes extremely low as the mill
speed is increased, especially in the range from 300 rpm or
more. In all cases for the sample activated, the content ismuch lower than that for the raw sample without activation.
The residual Cu2+ content in the solution for the sample

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activated at 400 rpm in mill speed and 0.1 g/L in dosage
is about 0.5 mg/L or less, which reaches the Environmental Protection Agency (EPA) the copper discharge limit(1.00 mg/L). We also found that the sample activated by
the milling under the condition of 400 rpm or higher brings
about a remarkable effect on its adsorption capacity, whileserpentine raw material itself has not obvious adsorption
ability to Ni or Cu ions. To be concrete, we have confirmedthat the capacity of the activated sample at the rotational
speed of 600 rpm in the Ni and Cu solution reaches
226.04 mg/g and 538.84 mg/g, respectively.
We have examined adsorption behavior of the serpentine sample activated to alkali metals such as alkali
cesium (Cs) ions in the solution. Normally fixing alkali
Cs ions is a difficult task but of significant importance inradioactive wastewater treatment at nuclear power stations.
Our approach started with the active Mg in the groundserpentine with an aid of phosphate anions, for example,(PO4)3–, incorporating alkali Cs in solution base to form acomplex phosphate as a struvite structure of (CsMgPO4).
It is noted that the struvite, NH4MgPO4·6H2O, itself issparingly soluble in neutral and alkaline conditions, but
readily soluble in acid. A solution with three alkali ions ofNa, K and Cs of phosphates to provide PO43–, was preparedin the experiment, and the serpentine samples activated for
2 h for different speeds were dispersed in it. Fig. 3 (Lei etal., 2019) is a result demonstrating changes in removal rateof three alkali ions in the solution with milling speed in
the mill. The removal ions means their adsorption by the
sample. As seen, the removal rate of only the Cs ion by
the sample is increased marginally in the slow speed millrange, bit it increased rapidly in the speed range from 300
to 400 rpm, and reaches 95 % or more. This implies that Cs
ion is transferred to precipitates which are adsorbed into
the serpentine sample or settled down in the vial. According to the analysis by XRD, it was found that the serpentine

Fig. 3 Removal rates of Cs, Na and K ions in the solution with theserpentine sample activated by the stirred mill as a function of milling
speed (Lei et al., 2019).

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structure is broken at the speed over 400 rpm, suggesting
release of active Mg in the solution. In fact, most of Cs
ions in the solution is removed by the activated serpentine
sample to form precipitation. The precipitation sample
was checked by XRD analysis, then it was conformed to
be CsMgPO4 which is the struvite phase. Therefore, thisactivation technique to serpentine sample would be a promising and alternative one for adsorbing Cs in radioactive
wastewater. Of course, the raw serpentine sample does
not show such high adsorption behavior for Cs ions. It isinteresting to note that both Na and K ions remain in thesolution. The properties of alkali elements are very similar,
and methods for Cs precipitation usually cause a similareffect to others like K and Na ions. This means that quite alarge amount of serpentine sample has to consume for K or
Na removal. It is known that alkali elements have different
radius size and exhibit some slight difference in the stability when forming struvite phase. If such small difference isapplied for selective precipitation of Cs ion on the groundserpentine, both disposing of radioactive Cs source and enrichment of it are achieved. The characteristics of K and Cs
ions to the mechanical activated serpentine were not foundin conventional chemical reactions. The key point is thatmechanochemical processing may offer special solutions tothose difficult cases and we are looking for the chances tosolve particularly the environmental issues.

3.2 Hydrated aluminum silicate: Kaolinite
Coagulant has been widely used in the pretreatment ofwastewater, and a simple and environment-friendly process
to prepare high-efficiency coagulants is highly desired withincreasing the amount of wastewater treatment. Kaolinite
Al2Si2O5(OH)4, as one of the industrial minerals of kaolingroup or clay minerals is a popular one, having 1:1 typelayered silicate consisting of Si-O tetrahedron and Al-O
octahedron. This mineral has been offered to industries ofpottery products, additives in medicines and foods, daily
necessities, agricultural soil, fertilizer reagent and so on.
We have attempted to develop a novel process to prepare
aluminum-based coagulant by the use of mechanochemical activation of kaolinite, followed by co-grinding withconcentrated sulfuric acid (H2SO4) solution. Fig. 4 shows
briefly the flowsheet for preparation process for suchcoagulant sample. The sample is composed of aluminum
sulphate, Al2(SO4)3, and it was then tested for removal ofpollutant in solution.
The composition, structure and morphology of the coagulant samples were characterized using X-ray Diffraction(XRD), Fourier Transform Infrared (FT-IR), Spectrometerand Scanning Electron Microscopy (SEM) and so on. Capacity of the prepared product as coagulant, compared withpure aluminum sulfate, was evaluated by the removal efficiency of turbidity, phosphate (PO43–), arsenate (AsO43–)

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Fig. 4 Flowsheet for preparation process for kaolinite base coagulant sample (Zhao et al., 2019).

and humic acid (Zhao et al., 2019). The final values of these
efficiencies are 99.9 % for turbidity clearing up, 91.2 % forphosphate, 89.6 % for arsenate and 92.3 % for humic acid,respectively. Moreover, during the preparation process, theformation of alum, was observed over a wide pH range
from 4.3 to 9.0. XRD analysis has demonstrated that areaction between kaolinite and sulfuric acid occurs during
the milling operation and Al sulfate is formed to work as
coagulant for the effectiveness confirmed as above.
Instead of the sulfuric acid addition, phosphoric acid
(H3PO4) was added to the kaolinite sample activated in order to modify kaolinite. In this case, the final product sample was formed as aluminum phosphate, Al-PO4, and was
also tested for removal of pollution in the solution. Since Al
phosphate is not water soluble, the sample keeps phosphateanions inside even in solution for adsorbing some target
substances. In the case of modifying kaolinite by phosphoric acid, part of the free hydrogen ion of phosphoricacid is combined with the hydroxyl groups in the kaolinite
structure, leading to the production of water molecules, sothat phosphoric acid is fixed onto amorphous kaolinite toform Si-O-Al-P binding, which offers good adsorption sites
for potassium ion (K+) (Lei et al., 2018).
The adsorbent through phosphoric acid modification of
kaolinite provides a new option for recovering potassiumfrom seawater and tailing wastewater. Further improvements may be obtained by together use with Mg-Al layered
double hydroxide or the Mg silicate of serpentine activatedas an example and the detailed information may be referred
to other publications. The coagulant sample would be a
promising one for pre-treatment process of sewage as well
as a new route to rich tailings of coal mining gangue etc.

3.3 Calcium carbonate: Calcite
As described, the conventional precipitation method is
not enough to solve the problems, due to large amount ofchemical reagents needed in order to neutralize wastewater,

besides difficulty in separation and recovery of precipitatedmetals and poor record for processing wastewater with
low-concentration of heavy metals. One of the important
issues would be to develop a sample exhibiting excellent
capability of removal amount for pollutants such as heavy
metal ions.
We have proposed a new method for preparation ofsuch samples by using wet stirred ball milling a calcite
sample (CaCO3) with solutions containing Pb2+, Cu2+.
Since precipitations of heavy metal ions are expected, awetting grinding rather than dry grinding was used for such
purpose. A systematic exploration was done to investigate
effects of several factors such as calcite dosage, milling
time and ball volume ratio in the milling on adsorbent
capacity of calcite activated for Pb2+ and Cu2+ in the wastewater. It is not easy to analyze in situ the samples in thesolutions directly, calcite activated by the milling as wellas the precipitates of heavy metals from the water werecharacterized by XRD, TG-DSC, FTIR and other analyticalmethods. Fig. 5 shows the lead (Pb) removal rate (%) in thesolution on the added ball volume to the solution (a) andthe copper (Cu) removal rate (%) on the Ca/Cu molar ratio(b), respectively. The initial concentrations were 0.5 mM
for Pb solution, and 1 mM for Cu solution, respectively,
and the pH was fixed at 6.51. In the experimental workon Pb removal, shown in Fig. 5(a), the conditions were as
follows; CaCO3/Pb2+ = 1 in moral ratio, 120 min in millingtime, 10 % in ball material ratio, and 200 rpm in rotation
speed of the stirred mill. As shown in Fig. 5(a), the initial
Pb2+ removal rate in the solution is 23.3 % at the agitation
test (0 % in ball volume ratio), but it increased rapidly withan increase in the ball volume ratio, and reaches to almost
100 % is at 8 in the ball volume ratio, then levelled off.
This suggests that the precipitation in the solution happens
during the wet milling of calcite and Pb ions in its millpot, even under low ball volume ratios in the range of 1
to 2 %. This precipitation happens more and more in thehigher ball volume range from 5 to 13 %. The precipitates

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Fig. 5 Pb removal rate (a) on the added ball volume ratio in the stirred
milling and Cu removal rate (b) on Ca/Cu ratio using calcite activated by
the stirred mill (Modified from Hu et al., 2017; 2019).

were confirmed as PbCO3, according to the XRD analysis.
Therefore, the remarkable increment range in Pb removal
rate seems to be effective period to form such PbCO3
precipitates and the milling with proper ball volume ratio
facilitates this precipitation of Pb ion on the calcite sample
surface in the solution. It may be noted that this milling
period would activate the calcite sample adsorbing the Pb
ion in the solution, and that no activation happens on the
calcite sample, resulting in only the physical adsorption of
Pb2+, which is insufficient to remove it, in the absence ofballs in the milling (Wen et al., 2020; Xiong et al., 2020;
Hu et al., 2019).
Similar trend in the Cu removal in the solution was also
observed, as shown in Fig. 5(b). Specific experimental
conditions were as follows: 1 mM in initial concentrationof Cu2+ solution, CaCO3/Cu2+ = 1 in moral ratio, 90 min
in milling time, 10 % in ball material ratio, and 200 rpm
in rotation speed in the stirred milling. It is found that the
Cu2+ in the solution can be precipitated from the solution,and the precipitates were confirmed as a solid of Cu4(SO4)(OH)6·2H2O. The removal rate is increased up to 99.62 %,at which the pH in the solution was 8.25. Then, the concentration of the solution with Cu2+ after the treatment
is 0.35 mg/L, which is much lower than the National

160

Emission Standards (Hu et al., 2017).
We have further extended the activated calcite sample toother metal ions such as iron (Fe), zinc (Zn) and cadmium(Cd). In the experiment, the calcite sample was milled
and activated by a planetary ball mill, which can give themilling strength higher than that by the stirred mill. Thismay cause easily mechanochemical reactions between
calcite and coexistent species. We have made a milling
experiment using the calcite sample and heavy metalsulfates. It is very interesting to note that, depending on
the type of element, the reaction behavior between metalsulfate and calcite were different: some were quite easy toform precipitation for efficient removals of the ions fromthe solution, but other metal ions remained in the solution, due to no reaction with calcite. The differences weremainly caused by two aspects: One is the characteristics ofdifferent metal ions, and another is the different conditionsof reactions. Within the scope our research experiment, thereactivity of ions to calcite has been put in the order of Pb2+ > Fe2+ > Cu2+ > Zn2+ > Cd2+, Ni2+. When the intensity ofmechanical activation is very high, the coprecipitation ofmultiple metals would occur. One plausible reason for suchdifferences in the reactivity may be attributed to the thermodynamic stability of hydrated ion, M(H2O)n2+, where
M denotes metal and n is the water coordination number.
When the coordination number of around water is six for
Fe2+, Ni2+, Cd2+, the spatial configuration of hydrated ion
is octahedron. The spatial configuration corresponding tofour for Pb2+, Cu2+, Zn2+ is a regular tetrahedron. The watermolecules in the form of octahedron are more difficult tobe removed away than those of the regular tetrahedron. It
is understood that Pb2+, Cu2+ and Zn2+ are easier to reactwith CaCO3 than Fe2+, Ni2+ and Cd2+ (Li et al., 2020). The
reaction mechanism between Fe2+ and CaCO3 seems to bea special case and will discuss in detail in the section 3.4,
which will introduce synergistic effects of a composites tosome anions of phosphate and arsenate.
Hydroxide precipitations of heavy metal ions takeplace with traditional alkaline neutralization, and calcium
hydroxide, Ca(OH)2, sample has been used as a chemical
reagent, and its amount may be a lot, depending on thescale of pollution site. As described, it is possible to use
calcite sample, CaCO3, activated by wet stirred ball millingto treat heavy metals. Due to the high reactivity with heavy
metal ions in the solution, it may be replaced with Ca(OH)2
used in traditional alkali precipitation, and also realizing
the chemical reaction of CaCO3 and heavy metal ions evenin equivalent molar and its solid concentration range lower
than the current process. When the milling speed is highenough to allow calcite enabling to react with almost all themetal ions in solution to form precipitates (solid phase), thepurpose of purification is environmental-­friendly achieved.
When the milling speed is controlled at mild condition,some metal ions may precipitate on the calcite surface, butHuimin Hu et al. / KONA Powder and Particle Journal No. 38 (2021) 155–167

others may remain in the solution. In this case, a mutual
separation for metal ions would be possible. More interestingly, it is possible to change the activation strength on theindustrial minerals like calcite (CaCO3) by a mill operated
under different conditions, the CaCO3 sample activatedshows different reactivity against the heavy metals in thesolution. By applying the difference in the reactivity, we
designed a new process to conduct a mutual separation ofthese metals by the use of calcite sample activated by a millwith solution containing the ions.
Fig. 6 shows the experimental data on mutual separationof different ions in the solutions with Cu-Ni (a), Cu-Co (b),Cu-Cd (c), Pb-Zn (d), Fe-Cu (e) and Fe-Mn (f) systems, respectively. In the case of (a) Cu-Ni separation, a mixture of
CaCO3, CuSO4, NiSO4 and few amount of distilled water(3 mL) was put into a pot of a planetary mill, and milled
for 30 min. The milling speed, Ca/Metal molar ratio and soon were changed, and the products after milling was takenout for evaluation. CuSO4 and NiSO4 are the componentof the solution, therefore no use of other chemicals is anadvantage of our method, and the same procedure was done
for other systems such as Cu-Co (b), Cu-Cd (c), Pb-Zn (d),Fe-Cu (e) and Fe-Mn (f). As seen in Fig. 6(a), with wide
range of Ca/Cu molar ratio, the residual ratio in Cu2+ is almost zero, implying that they are completely precipitated,while Ni2+ remains at 90 % or more in the solution over
the wide range of Ca/Cu ratio. Therefore, our sample prepared by wet milling of calcite and phosphates is possible
to separate mutually Cu2+ and Ni2+ in the solution. If one
would try this mutual separation by the traditional alkaline
neutralization process using a chemical reagent, Ca(OH)2,

it would not be achieved the purpose, and more than this,enormous amount of reagent would need to precipitate
these ions (Li et al., 2017a).
Similar results are seen in Fig. 6(b) and (c). As for thecase of selective precipitation of Cu from the solutions containing Co and Cu, the separation efficiency is not high incomparison with that in Cu-Ni system shown in Fig. 6(a),but the residual ratio in Cu is very low over the whole rangeof Ca/Cu ratio. This means most of Cu2+ is precipitated,while most of Co2+ ion is still remained in the solution (Liet al., 2016). In the case of Cd-Cu-Fe ions in the solution,
Cu and Fe ions are precipitated, while large amount of Cd
ion is remained in the solution, as seen in Fig. 6(c) (Li etal., 2017b). It is, therefore, recognized that the proposed
method could achieve mutual separation among Cd, Cu
and Fe ions at fairly high possibility, although the separation efficiency is not so high as the case of Cu-Ni system,
as shown in Fig. 6(a).
Selective lead (Pb) removal from metal-containing
wastewater such as acid mine drainage (AMD) is an important issue in environmental purification and secondary
resources recovery. Similar test on copper (Cu) or iron(Fe) removal was done using CaCO3 activated by wet ball
milling with the solution containing Pb2+. The Pb2+ in thesolution is precipitated to form PbCO3, and this is achieved
based on the reaction between Pb2+ and CO32– in the solution, as shown in Fig. 6(d) (Zeng et al., 2020). The removal
efficiency of Pb2+ from the solution is increased with anincrease in the molar ratio of CaCO3/Pb2+, and it reaches
over 99 % at 1.0 in the molar ratio of CaCO3/Pb2+, whilemore than 99 % Zn2+ is remaining in the solutions. During

Fig. 6 Summarized six groups of mutual separations between heavy metals by the use of CaCO3 sample activated (Modified form Hu et al., 2020; Liet al., 2016, 2017a, 2017b; Wang et al., 2019; Zeng et al., 2020).

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this removal change, the pH in the solution is changed fromabout 5.0 to 6.3. This result implies that the high selective
precipitation in Pb2+ is attained in the range over 1.0 in themolar ratio of CaCO3/Pb2+, without Zn as a contaminant.
Looking at the solution after separation of Pb, it is possible
to recover Zn as zinc carbonate, as an alternative precipitant to CaCO3 in the separation process.
Iron (Fe) impurity in manganese sulfate (MnSO4) solution will seriously affect the quality of manganese products
if it is not purified. Ferric ions (Fe3+) will precipitate evenin weak acidic solution, so that it is possible to remove Fe3+from the manganese sulfate solution by controlling andregulating the pH value in the solution. However, it is noteasy to remove Fe3+, and oxidization of ferrous ions (Fe2+)
into Fe3+ is normally conducted for iron impurity removal.
Our study was focused on removal of ferrous iron frommanganese sulfate solution by the use of calcite (CaCO3)
activated mechanically with manganese sulfate solution.
This sample preparation was also wet milling used by astirred ball mill. One of the results at 350 rpm in mill speed
are shown in Fig. 6(f), and the removal rate of ferrous
ions depends on the milling time as well as milling time,and it reaches approximately 100 % under the condition at
180 min in the milling time, 15 % in the ball/liquid volume
ratio and 3/1 in CaCO3/Fe2+ (Wang et al., 2019). Thus, selective ferrous iron (Fe2+) removal from manganese sulfate
solution can be achieved by the sample proposed. Thus
our sample preparation is to use calcite and the polluted
solution(s), and no use any chemicals. This method would
be useful for removing iron ion from manganese sulfate
solution. The iron impurity removal can be applied also for
purifying other solutions containing copper, nickel, cobalt
or zinc.
Thus, the phenomena on the reactivity of CaCO3 withheavy metals in the solution can be controlled by altering
milling operation, and it may not be easy to manage thisremoval results by the traditional process using alkaline
neutralization.

3.4 Composite of calcite with ferrous salt
The excessive use of pesticides, the discharge of municipal and industrial wastewater have led to a significant
increase of phosphorus levels in water bodies and serious
eutrophication pollution. For such high concentration
eutrophic water and industrial/agricultural phosphorus
wastewater, chemical precipitation treatment can immobil­
ize the phosphate as solid compounds without the need for
additional oxygenation or excessive post-treatment. This
treatment involves the addition of soluble salts of aluminum and iron or even rare earth to wastewater. Ferric (Fe3+)
salt is a kind of widely used reagent which is an economicaland environmental-friendly reagent rather than aluminumand rare earth salts, and has an excellent precipitation ability, similar to the ferric orthophosphate (FePO4) with freeof toxicity. Applications of Fe3+ generated via the oxidationof ferrous (Fe2+) salt have received much attention due toits cost performance rather than direct usage of Fe3+. The
main reason is that the precipitation reaction between Fe2+
and PO43– occurs in the process of transformation from
Fe2+ to Fe3+ hydroxyl oxides under aerobic condition,
which avoids the formation of FeOOH by hydrolysis of
Fe3+. At the same time, the oxidation process of Fe2+ isgreatly affected by OH–. We have noticed recently thatthe surface of CaCO3 could provide a boundary for metal
ions participation through the reaction with OH–, resulting
from the hydrolysis of CO32–, a successful alternative to
Ca(OH)2 with a clear advantage of final pH in neutral rangeof the wastewater for direct discharge after the treatment.
When Fe2+ was used with CaCO3, the Fe(OH)2 formed on
its surface could be easily oxidized into Fe3+ hydroxideeven in air, without addition of specific oxidant. It is interesting to note that the slowly generated fresh ferric compositions exhibit tremendous removal capacity for phosphate,
without evident formation of FeO(OH). Fig. 7(a), (b)shows the experimental results for the removals of botharsenite anions (for example, AsO33–) (a) and phosphateanions (for example, PO43–) (b) from the solutions. The
sample of calcite was mixed with the Fe2+ salt and milled

Fig. 7 Removal efficiencies of arsenite anions (a) and phosphate anions (b) with calcite and ferrous combination (Modified from Zhang et al., 2019a;
Li et al., 2018).

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by a planetary mill for some time. The results show thedramatic change in each anion, AsO33– and PO43–, from thesolution by the use of CaCO3 with Fe2+, which is oxidized
into ferric (Fe3+) species (Zhang et al., 2019a; Zhang et al.,2019b; Li et al., 2018).
The mechanism is as follow: At first, CaCO3 is added toFe2+ salt and it is agitated with phosphate (PO43–) solution.
Then, these components transform into an amorphous
Fe3+-P or Ca-Fe3+-P precipitates. During this change, phosphate removal proceeds in the solution and finally reaches
almost 100 % in removal rate. The concentration of phosphorus (P) in the solution is changed from 100 mg/L in theinitial stage down to 0.03 mg/L, which is definitely lower
than the discharge permissible limit (the National Emission
Standards) (USEPA Office of Wastewater Management,
2010). This can be achieved under the conditions as low
as 9 in a stoichiometric ratio of CaCO3/PO43– and 1.5 inratio of Fe2+/ PO43–. It is amazing that the final pH of thesolution does not change so much and remains arounda neutral range from 5 to 8. Therefore, it is possible todischarge the water after treatment without any further
additional treatment like acid neutralization used in the alkaline precipitation process. Mechanochemical ball milling
could significantly reduce the size of calcite (CaCO3) andenhance its reactivity to the anions and solubility in thesolution, hence it could promote the efficiency of simultaneous oxidation of Fe2+ during the process of phosphorus(P) removal from the solution. When the ball milling speed
was 600 rpm, the phosphorus removal process could becompleted within 4 hours. The increase of temperature in
the precipitation process could also promote phosphorus
removal efficiency due to simultaneous oxidation of Fe2+
with CaCO3. The percentage of P2O5 in the precipitate byagitation of Fe2+ and CaCO3 in the phosphate solution is ashigh as 19.4 %, which is enough grade as phosphate sourcein fertilizer production. Difference from the conventional
alkaline neutralization process with high concentrationof OH– group is the slow hydrolysis of CaCO3, resulting
in low concentration of OH– group for the formation of
Ferrous (Fe2+) in the solution or its compound (Fe(OH)2).
The ferrous (Fe2+) is oxidized easily by air into trivalent
Fe (Fe3+), achieving continuous formation of fresh ferriccomposition for phosphate precipitation and could avoid
its rapid formation and subsequent transformation into
stable FeO(OH) of large particle size to lose the activity.
Our method introduced has significant advantage in theuse of industrial mineral, CaCO3 and common material,
ferrous (Fe2+) salt, so that it may be possible to apply easily
to phosphate precipitation.
In the meantime, arsenic pollution in water is also considerable and serious environmental problems in the world,
and the damage of its toxicity to human health has broughta menace to our society. We have challenged to develop
an efficient method for removal of arsenic ion, As(V),from polluted solution by using active iron species fromferrous-calcium carbonate system (FeSO4-CaCO3). Fig. 8
shows a schematic diagram of the formation of ferric compound from ferrous sulfate (FeSO4) with CaCO3 for arsenic
removal. The basic idea of the ferric compound is similar tothe case of phosphate anion removal, but the small difference is that the relatively slow hydrolysis of CaCO3 would
release gradually OH– which played a role to regulate thegeneration of active iron species and ensured the sufficient
reaction time for adequately As5+ removal (Zhang et al.,2019c). At the same time, the reaction avoids the conversion of new ecological iron to low-reactive FeO(OH).

Fig. 8 Schematic diagram of the formation of ferric compound from ferrous (FeSO4) with CaCO3 for arsenic removal (Zhang et al., 2019c).

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Moreover, as the content of the arsenic-removing sedimentcan be significantly reduced by using CaCO3, the filtration
speed is increased by nearly 6 times, and the volume of
sediment is also reduced by about 2/3. The treating systemin this work shows superior properties such as large sediment size, small sediment volume and high filtration rate,
resulting in remarkable record in the processing of arsenic
removal. Non-oxidative direct removal of As3+ in solution
is possible by calcium carbonate with Fe3+, as shown in
Fig. 7(a), and the Fe3+ hydrated oxide (Fe(OH)3) would beformed on the surface of CaCO3 under the action of OH–
released by the slow hydrolysis, which is able to maintainhigh reactivity to As3+. When the Fe/As molar ratio is 4.5,
it can achieve directly precipitation of As3+ of about 100 %removal efficiency without pre-oxidizing from As3+ to As5+
by forming basic ferric arsenite of low solubility insteadof high-soluble ferric arsenite. This would open a new
approach for removal of arsenite anions in the solution
without preoxidation.

3.5 Composite of calcite with zero-valent iron
(ZVI)
As an efficient functional material to deal with environmental issues, zero-valent iron (ZVI) (Fe0) is widelyused from the viewpoint of high reduction potential andenvironmental-friendly property. In order to prepare ZVIwith high reactivity, many studies have been conductedwith the focuses on sample preparation, modification orprotection processes. To prevent the rapid oxidation of ZVIby oxygen dissolved in the process of the aqueous phasereaction, it is often necessary to pass through the inert gas
such as helium, or to use organic solvent such as ethanol
and acetone, to clean and preserve the ZVI product during
the purification. Furthermore, bare ZVI tends to agglomerate due to its fine particles and magnetic property, which
will hinder the adsorption and reduction capabilities. There
has been investigation on coating the surface of ZVI withstable materials such as clay, graphene, carbon nanotubes(CNT), activated carbon (AC) and so on. The methods
proposed are centered on protecting the fresh surface ofthe resultant ZVI and have achieved the desired results.
However, most of them are the stage of lab research, and it
would be better to enhance more, looking at the large-scale
application of ZVI to the environmental use, for example.
We have attempted to prepare adsorbent of ZVI coatedwith CaCO3 activated mechanochemically. Our expectation is to apply this ZVI-CaCO3 composite to the removalof As3+ in solution, and its idea is shown in Fig. 9. The
sample preparation starts from milling a mixture of CaCO3and ZVI in air, which remains as mixture after milling
operation. As shown in the figure, the change in adsorption
capacity of the product for As3+ is found to vary with the
CaCO3 content in the composite of (ZVI-CaCO3) prepared

164

Fig. 9 The adsorption capacity of the ZVI-CaCO3 samples to As3+ anions in the solution as a function of the content of CaCO3 in ZVI-CaCO3
system.

by the milling operation. Of course, neither ZVI nor CaCO3
show the adsorption capacity for the arsenic anions, but
the composite activated by the milling indicates clearly
increment in the adsorption capacity with the content of
CaCO3 in it and reaches the maximum value at about 50 %in CaCO3 content of the composite. The value, 50 %, in
CaCO3 content means the mass ratio of CaCO3 to ZVI as
1:1, enabling us to produce this composite in large scale
production.
As to the reaction mechanism of ZVI toward arsenic,
both oxidization and reduction may happen depending on
the atmosphere. With an oxidative atmosphere of air, oxidization mechanism proceeds to generate more high active
oxidative intermediates. When the oxidation from As3+ andFe2+ to As5+ and Fe3+, respectively, is accelerated by somereason, it results in the removal of As3+ from the solution.
However, in general, ZVI itself is very active substanceand the passivation layer formed on the surface of ZVI
will prevent from its reaction with other substance. Milling
operation to ZVI may cause some mechanical change likebreakage in the passivation layer, and this may trigger thereaction, causing the oxidization of the fresh surface. In
addition, the milling ZVI with CaCO3 makes it possible toform coated layer like the passivation one over the fresh
surface of ZVI without any agglomerates. This may be
the reason why the surface of ZVI in the composite is kept
detaching during the removal process of As3+ by the composite, ZVI-CaCO3. Thus, the milling the mixture of ZVI
and CaCO3 plays a big role to continuous exposure of fresh
ZVI surface promoting the excellent adsorption ability forarsenic anions.
Besides the oxidative effect of ZVI on arsenite with anaid of oxygen in air, another example for the composite of
ZVI and CaCO3 can be seen as follow: This phenomenon
is attributed to reductive ability of this composite, indicating the reduction precipitation of hexavalent chromiumHuimin Hu et al. / KONA Powder and Particle Journal No. 38 (2021) 155–167

Fig. 10 SEM images of different samples, (a) the raw Fe0 sample, (b) ground Fe0 sample at 500 rpm for 8 h, (c) mixture of Fe0 and CaCO3 milled at
500 rpm for 8 h and (d) removal (%) as a function of the dosage for four kinds of samples under the same conditions (Gu et al., 2019).

(CrO42–) in solution. A tremendous improvement in the removal reaction by using the composite of ZVI and CaCO3
was obtained, in comparison with the adsorption results forthe samples of raw ZVI, ground ZVI without CaCO3 addition. Fig. 10 shows SEM image of a mixture of the raw Fe0
sample, (a) ground Fe0 sample at 500 rpm for 8 h (b), ZVI
and CaCO3 milled at 500 rpm for 8 h (c), and CrO42- removal from the solution as a function of the dosage for thefour kinds of samples (d) ground by the stirred mill at thesame condition (500 rpm for 8 h). Fine CaCO3 particles innanometer size coated on the ZVI particles in micron-metersize are clearly observed from the SEM image, demonstrating the protective effect of CaCO3 fine particles to the ZVI
ones. Three kinds of samples, raw ZVI, ZVI ground andCaCO3 ground, did not exhibit observable performance forremoving CrO42–. This may be due to the passivation layeron the ZVI. However, the rate is increased drastically withan increase in the dosage of the sample for the ZVI-CaCO3
composite, and the value reaches 99.68 % at 1.0 in the
dosage. The milling time required to this highest value is
30 min, and the solution containing CrO42– (10 mg/L) is
obtained, and the ZVI mass ratio in the ZVI-CaCO3 composite is 30 wt.%. Addition of CaCO3 to the ZVI and its
milling for some time plays significant role in both removal
ability of CrO42– in the solution and protection of the fresh
surface of active ZVI, enabling us to give such superior
performance as ZVI. Besides the environment-friendlinessof the preparation process, waste solid materials containing
iron particles may be one of the candidates as the starting
sample in order to prepare such adsorbent of ZVI-CaCO3

composite for practical use (Gu et al., 2019).

4. Conclusion
A simple milling operation can be used as a typical modifying tool for preparing and modifying non-metallic (industrial) minerals to increase the capacity as absorbents forenvironmental remediation. Depending on the purposes,
either wet or dry milling operations is selected to achieve
excellent performance of the adsorbents for pollutant removals in the solution. Intenseness in milling operation isdepending on the milling conditions such as milling speed
and time, mill vial size, ball charge, sample charge and soon, but it is also important to find out the most effective
factor to trigger chemical changes of the target sample.
Milling a material causes mechanochemical activation and/or reaction to form the product which has unique properties
and they are not the same one prepared by different milling
conditions. In the precipitation of certain ions in solution,
it is important to analyze its mechanism chemically in thesolution, finding out the crucial aspects to remove a target
ion, for example effectively and selectively. This means theboth science and engineering knowledge and experience
are the key to develop new futuristic methods and materials.
In this review, we have introduced current situation in
wastewater treatment, and need adsorbents which would
be environmental-friendly ones as much as possible. Under
such circumstance, we have challenged and developed165

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several new mechanochemical routes for preparing mineralbased adsorbent with effective purification ability for toxic
matter-containing wastewater. The minerals chosen in theexperiments are non-metallic minerals such as hydrated
magnesium silicate (serpentine), hydrated aluminum silicate (kaolinite), carbonate (calcite), calcite with ferrous
compound and calcite with zero-valent iron. The mills used
are mainly stirred mill and planetary mill in laboratory
scale. The direction to prepare the adsorbent sample activated by the mill was shown in each section, and the main
results are also introduced.
We have applied some adsorbents prepared by our
methods to real and actual spots where solutions are contaminated with toxic substances and heavy metal ions in
China. We have also obtained good data as a practical use
so far, and in the near future, other spots will be selected forthe removal of contaminants in solution by the use of theadsorbents. In the meanwhile, based on the requirement,
it would be possible to prepare the adsorbent samples inlarge scale.

Acknowledgement
The authors are grateful to Emeritus Prof. Fumio Saito,
Tohoku University, for his invaluable comments and suggestion on this paper.

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chemosphere.2019.05.117
Zhang T., Zhao Y., Kang S., Li Y., Zhang Q., Formation of active
Fe(OH)3 in situ for enhancing arsenic removal from waterby the oxidation of Fe(II) in air with the presence of CaCO3,
Journal of Cleaner Production, 227 (2019c) 1–9. DOI:

10.1016/j.jclepro.2019.04.199
Zhao Y., Zhang Q., Yuan W., Hu H., Li Z., Ai Z., Li Y., Highefficient coagulant simply by mechanochemically activating kaolinite with sulfuric acid to enhance removal
efficiency of various pollutants for wastewater treatment,
Applied Clay Science, 180 (2019) 105187. DOI: 10.1016/j.
clay.2019.105187

Authors’ Short Biographies
Huimin Hu
Ph.D student, Wuhan University of Technology, China.
She received her Master’s degree (2015) in Environmental Science and Engineeringfrom Wuhan University of Technology, where she specialized in purification of heavy
metal wastewater through mechanically activated non-metallic minerals. She is now pursuing her Ph.D. in Environmental Science and Engineering under the supervision of Prof.
Qiwu Zhang at the Wuhan University of Technology. Her research is currently focused on
the development of perovskite-type oxide for wet catalytic oxidation of organic wastewater.

Qiwu Zhang
Professor, Wuhan University of Technology, China.
He obtained his bachelor and master degrees in 1984 from Wuhan University of Technology and 1987 from the graduate school in Beijing of Wuhan University of Technology,
China. He worked as an engineer in Zhengzhou Institute of Multipurpose Utilization of
Mineral Resources, China. He obtained his Ph.D degree in 1997 from Tohoku University,
Japan. He worked as a faculty member in Tohoku University from 1997 to 2014. In 2004 hevisited Ames Laboratory, Iowa State University as a research fellow. From 2015, he joined
the Wuhan University of Technology. His research interest is in the field of mechanochemistry, covering various applications of mineral processing, environmental purification,material science and energy transformation by applying the discovered phenomena frommechanical activation.

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KONA Powder and Particle Journal No. 38 (2021) 168–188/https://doi.org/10.14356/kona.2021003

Review Paper

Coal Particle Devolatilization and Soot Formation in
Pulverized Coal Combustion Fields †Nozomu Hashimoto 1* and Jun Hayashi 2
1
2

Division of Mechanical and Space Engineering, Hokkaido University, Japan
Department of Energy Conversion Science, Kyoto University, Japan

Abstract
In this paper, recent developments of the devolatilization model and soot-formation model for the numericalsimulations of pulverized-coal combustion fields, and the technology used to measure soot particles in pulverizedcoal combustion fields are reviewed. For the development of new models, the validation of the developed models
using measurement is necessary to check the accuracy of the models because new models without validation havea possibility to make large errors in simulations. We have developed the tabulated devolatilization process model(TDP model) that can take into account the effect of particle heating rate on the volatile matter amount and thedevolatilization-rate parameters. The accuracy of the developed TDP model was validated by using the laser
Doppler velocimetry data for the bench-scale coal combustion test furnace. The soot-formation model combinedwith TDP model for the large eddy simulation (LES) has been also developed. The spatial distributions of boththe soot-volume fraction and the polycyclic aromatic hydrocarbons were measured by virtue of laser-induced
incandescence (LII) and laser-induced chemiluminescence (PAHs-LIF). The accuracy of the developed sootformation model was validated by using the measured data.
Keywords: coal combustion, soot, devolatilization, numerical simulation, optical diagnostics, laser induced
incandescence

1. Introduction
Pulverized coal combustion has been introduced tomany coal-fired thermal power plants across the world.
However, since the CO2 emissions from coal-fired thermal power plants is larger than that from other power
plants, efficient operation of these power plants and introducing new types of fuel that can be produced from renewable energy is expected. To realize that, modificationsof coal-fired thermal power plants are needed. Because
the cost of modifying large-scale power plants would belarge, pre-evaluation of the modifications is necessary.
Numerical simulation of pulverized coal combustion field
can be a powerful tool for such pre-evaluation of themodifications or improvement of the operation for thecoal-fired thermal power plants. The research group of theauthors have conducted studies relating to the development of numerical simulation technology for coal com†

1
2*

Received 21 October 2019; Accepted 15 January 2020
J-STAGE Advance published online 31 March 2020
Kita 13 Nishi 8, Kita-ku, Sapporo 060-8628, Japan
Yoshidahonmachi, Sakyo-ku, Kyoto 606-8501, Japan
Corresponding author: Nozomu Hashimoto;E-mail: nozomu.hashimoto@eng.hokudai.ac.jp
TEL: +81-11-706-6386

168

bustion fields (Hashimoto N. et al., 2007, 2012a, 2012b,
2014, 2016b, 2017; Kurose R. et al., 2003, 2004, 2007,2009; Watanabe H. et al., 2009; Muto M. et al., 2015; Ahn
S. et al., 2017).
Fig. 1 illustrates an example of the prediction results ofa coal particle’s temperature in an actual large-scale coalfired boiler by the developed numerical simulation technology for coal combustion fields. Fig. 2 illustrates thecalculated O2 concentration distribution on the furnacewall surface and the comparison of measured and calculated O2 concentrations at the inspection windows on the
furnace wall for the same boiler as in Fig. 1. The circled
numbers in Fig. 2(a) indicate the locations of the inspection windows. Indeed, the simulation suggests that the O2
concentration at the inspection window at the rear side allabove the burner zone (➁ in Fig. 2(b)) is low compared to
the front side wall. However, discrepancies exist between
the simulation results and the measured data. Accordingly, room for improvement with respect to the accuracyof the numerical simulation exists, which can be achievedby understanding the processes involved in pulverizedcoal combustion fields.
Fig. 3 shows the basic concept of the pulverized coal
combustion process. When the pulverized coal particle isheated up, moisture evaporates from the particle at the

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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2. Coal-particle devolatilization
Coal-particle devolatilization is a crucial phenomenon
in the entire coal combustion process. Volatile matter
evolves from coal particles during the devolatilization
process. Indeed, both the devolatilization rate and thevolatile-matter amount affect the coal-combustion process
significantly. In this chapter, the models for the predictionof the devolatilization process are reviewed, as well as
methods that aim to unite the devolatilization processmodel and the numerical simulation of coal combustion
fields.

2.1 Models for devolatilization of coal particles

Fig. 1 Prediction of coal particle’s temperature in actual 915 MWthclass boiler.

temperature range of boiling point of water. The volatile
matter, which includes various gas species and tar,evolves from the particle by the devolatilization process:the gaseous fuels are rapidly oxidized by oxygen in a
combustion field. Indeed, it is well known that the majority of the tar is converted into soot particles in the secondary pyrolysis-reaction process. The soot particle emits
strong radiation same as the char particle. In addition, theoxidation process of soot particles is relatively slow compared to that of gaseous fuel species. The char combustion process after coal-particle devolatilization has beenstudied by many researchers across the world. This is because unburned carbon in fly ash that is captured from theexhaust gas is the major concern in the coal combustion
research field. Therefore, the researches on the devolatilization and soot formation processes in coal combustion
field have been limited. However, the devolatilization process and the soot formation process is very important for
the numerical simulation of coal combustion field, because the treatment of these processes strongly affects theprediction accuracy of the entire oxidation speed of thevolatile matter and temperature field of the burner zone.
The research group of the authors have conducted studies concerning two major elements: (i) developing thedevolatilization and soot-formation models for numericalsimulations of the coal combustion fields and (ii) measuring the soot particles present in the coal combustion fields
by using optical-diagnostic systems equipped with highpower lasers. In this paper, recent attempts to develop accurate numerical simulation technology for coal combustion field are reviewed.

Several devolatilization models have been developedby many researchers, such as the CPD model by Fletcher
T.H. et al. (1990), FG-DVC model by Solomon P.R. et al.
(1988), and FLASHCHAIN model by Niksa S. and
Kerstein A.R. (1991). In the CPD model, percolationlattice statistics are employed in order to describe thegeneration of tar precursors of finite size based on thenumber of cleaved labile bonds in the infinite coal lattice.
The FG-DVC model combines a functional-group modelfor gas evolution and a statistical model for tar formation,
including depolymerization, cross-linking, external transport and internal transport. Finally, in the FLASHCHAIN
model, the chemical constitution of coal in terms of typical refractory aromatic nucleus, two linkage types (labilebridges and char links), and a typical peripheral group arerendered, the labile bridges are regarded as the key reaction centers.
The following formula, which was proposed by
Badzioch and Hawksley (1970), is commonly used inmodeling the devolatilization process with respect to numerically simulating coal-combustion fields:dV K v (V *V )
dt

(1)

E
=
K v Av exp  − v 
 RTp (2)where, V represents the mass of volatile matter thatevolved from a coal particle (kg), V* represents the massof volatile matter in particle (kg), Av represents thepre-exponential factor for the volatile-matter evolutionrate equation (1/s), Ev represents the activation energy forthe volatile-matter evolution-rate equation (J/kmol), R
represents the gas constant (J/(mol K)), and Tp represents
the particle temperature (K).
V * = QV*’

(3)

where V*’ and Q are, respectively, the amount of volatile

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Fig. 2 Comparison of measured and calculated O2 concentrations at inspection windows on furnace wall surface for the 915 MWth boiler. Reprinted
with permission from Ref. (Hashimoto N. and Watanabe H., 2016b). Copyright: (2016) Elsevier B.V.

Fig. 3170

Basic concept of pulverized combustion process.

Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 4 V*/V*’ (Appropriate value for Q-factor) as a function of thecoal particle heating rate calculated by FLASHCHAIN model. Reprinted with permission from Ref. (Hashimoto N. et al., 2012a). Copyright: (2012) Elsevier B.V.

Fig. 5 Effect of the coal particle heating rate on Kv (in Eq. (1)) for
Newlands bituminous coal calculated by the FLASHCHAIN model.
Reprinted with permission from Ref. (Hashimoto N. et al., 2012a).
Copyright: (2012) Elsevier B.V.

matter obtained by proximate analysis and the Q-factor,
the latter of which is employed in order to identify therate at which the amount of volatile matter increases according to the high particle-heating rate in pulverizedcoal combustion fields. In the conventional model for numerical simulations of coal combustion, Av, Ev and Q are
treated as constant values for all coal particles regardlessof the particle-heating rate. However, the value of V* isdependent on the coal particle-heating rate. Therefore, appropriate values for Av, Ev, and Q are significantly affectedby the diameter of each particle, as well as how each particle is injected to the coal-combustion field. Indeed, such
effects are not considered in the conventional model.
To investigate the effects of the coal-particle heating
rate on Av, Ev and V*/V*’, the FLASHCHAIN model wasused to conduct devolatilization simulations. Fig. 4
shows V*/V*’, which represents appropriate values for the
Q-factor as a function of the particle-heating rate for different coal brands. Fig. 5 shows the effect of the particleheating rate on the devolatilization-rate coefficient, Kv, for
Newlands’ bituminous coal, which was predicted using
the FLASHCHAIN model. From these figures, it is evident
that both the volatile-matter amount and the devolatilization rate are significantly affected by the particleheating rate. We developed a new model to consider this significant effect of the particle-heating rate on the volatilematter amount and the devolatilization-rate parameters,
the details of which are reviewed in the next section.

cedure outlined below for a steady-state calculation.

2.2 Tabulated devolatilization process model
To consider the variation of the devolatilization rate
and the volatile matter amount for each coal particle in
the numerical simulation, the tabulated-devolatilizationprocess (TDP) model was developed. In the TDP model,
suitable values for the devolatilization parameters are automatically set for each coal particle according to the pro-

1. The devolatilization parameters are set at initial values(➀ in Fig. 6).
2. An iteration of the CFD calculation is carried out using
the devolatilization parameters (➁ in Fig. 6).
3. After the iteration, the particle temperature history ofeach coal particle calculated in the most recent CFD iteration is compared with the temperature histories inthe devolatilization database. The temperature history
from the data base that is closest to the particle temperature history calculated from the most recent CFD
iteration is selected (➂ in Fig. 6).
4. The devolatilization parameters accompanied with theextracted temperature history are used in the next CFD
iteration (➃ in Fig. 6).
Steps 2–4 are repeated until the CFD calculation converges. The procedure mentioned above is for the steadystate simulation. The procedure for unsteady simulations
such as the large eddy simulation (LES), will be reviewed
in Section 4.
In the TDP model, the mass fraction of volatile matterin the particle mvola (kg/kg-coal) changes depending on
the particle-heating rate. Indeed, variations in mvola imply
variations in the volatile matter calorific value and thechemical-element composition balance. Therefore, themole fractions of the postulated chemical species as­volatile matter vary depending on the value of mvola. This
result means that the calorific value and the elemental-­component balance of the volatile matter varies depending of the particle-heating rate. The detailed procedureused to conform both the calorific value and elemental
component balance of a coal particle in the numericalsimulation to the calorific value obtained by both proximate analysis and ultimate analysis is available in the relevant literatures: Hashimoto N. et al. (2012a, 2012b), andHashimoto N. and Shirai H. (2014).

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Fig. 6 Calculation flow chart of the TDP model for steady state numerical simulation. Reprinted with permission from Ref. (Hashimoto N. et al.,2012a). Copyright: (2012) Elsevier B.V.

The validation of the model was conducted using theoptical measurement data of the 760 kWth coal-combustion
test furnace (Fig. 7). A laser Doppler velocimetry (LDV)
was employed to obtain the particle-velocity distributionsin the test furnace. Fig. 8 shows a schematic of the measurement system.
Fig. 9 shows the comparison of radial distributions ofmean axial-particle velocities. Case 1 indicates the particle velocity predicted by the TDP model. Cases 2–4 indicate the particle velocities predicted by the conventionalmodel. The devolatilization rate parameters used for theconventional model are listed in Table 1. Cases 5–7 indicate the particle velocities predicted by the two competing
reaction-rate model (Kobayashi et al., 1977). The devolatilization-rate parameters for the two competing reaction
rate model are listed in Table 2. In Fig. 9, the mean axial
velocity, Uz, for the Case 1 (TDP model) is more agreeable with the LDV results compared to other cases, which
tend to underestimate the values of Uz around the central
axis. From the above results, it is clear that the TDP model(Case 1) is better at reproducing the coal-combustion
experiment than the other models.
Fig. 10 shows the selection probability of temperature
histories in the devolatilization database, when theparticle-temperature histories calculated in the CFD iteration are compared with the temperature histories in the
database (Fig. 6). Indeed, for the majority of particles, theheating rate is in the range of 104 –106 K/s. Moreover,large variations in the particle-heating rate exist according to the initial diameter as shown in Fig. 10: the smaller
the initial diameter is, the higher the particle heating rate

172

is. This result indicates that the particle-heating rateshould be considered for all coal particles in the field, because it is affected by particle diameter and the position atwhich said particle is injected into the combustion field.
Therefore, devolatilization models that consider the effectof the particle-heating rate on the devolatilization characteristics, such as the TDP model, are strongly recommended for the numerical simulations of pulverized-coal
combustion fields.

3. Soot formation in pulverized coal combustion
field
As discussed in Chapter 1, the majority of tar thatevolves from a coal particle is converted into soot particles as a consequence of secondary pyrolysis. These sootparticles emit the strong radiation same as the char particles. Therefore, accurate models with respect to the formation of soot particles can improve predictions abouttemperature distribution in pulverized-coal combustion
fields. Unfortunately, soot formation in pulverized coal
flames is yet to be fully understood. In this chapter, experimental research concerned with employing the optical
diagnostics of soot particles for coal combustion fields arereviewed as well as research concerning the developmentof soot-formation models for the LES of coal-combustion
fields. For the purposes of validation, the spatial distribution of the soot-volume fraction, which can be obtainedby employing a strong pulse laser is one of the most valuable data.

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Fig. 7 Computational domain for the validation of the TDP model for steady state simulation. Reprinted with permission from Ref. (Hashimoto N.
et al., 2012a). Copyright: (2012) Elsevier B.V.

Fig. 8 Schematic illustration of laser Doppler velocimetry for the 760 kWth coal combustion test furnace. ­Reprinted with permission from Ref.
(Hashimoto N. et al., 2012a). Copyright: (2012) Elsevier B.V.

Table 1 Parameters for the conventional model. Reprinted withpermission from Ref. (Hashimoto N. et al., 2012a). Copyright: (2012)
Elsevier B.V.

Case Ref.

Av [1/s]

Ev [J/kmol]

Q [-]

2

2.02 × 103

3.11 × 107

1.2

13

2.20 × 10

8

1.5

13

8

3
4

Tominaga et al., 1997
Solomon et al., 1983
Johnson et al., 1988

4.5 × 10
1.0 × 10

1.8 × 10

1.8

3.1 Pulverized-coal jet flame burner and theconditions for non-intrusive soot diagnostics
To obtain precise soot formation data with respect topulverized-coal flames, a simple co-axial pulverized-coaljet burner in CRIEPI (Hwang S.M. et al., 2005) was selected. The coal jet burner and the supplying system areillustrated in Fig. 11. Pulverized coal particles and air
were supplied to a combustion field from the main burner
port (diameter: 6 mm) as the “premixed coal/air flow”.
Methane was issued from a slit with a width of 0.5 mm

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Fig. 9 Radial distributions of average axial particle velocities. Reprinted with permission from Ref. (Hashimoto N. et al., 2012a). Copyright: (2012) Elsevier B.V.

Fig. 10 Probability of selection for heating rate in the devolatilization
database during the extraction process. Reprinted with permission
from Ref. (Hashimoto N. et al., 2012a). Copyright: (2012) Elsevier B.V.

Table 2 Parameters used for the two competing reaction rate models. Reprinted with permission from Ref. (Hashimoto N. et al., 2012a). Copyright:(2012) Elsevier B.V.

Case

Ref.

α1

α2

A1 [1/s]

A2 [1/s]
5

E1 [J/kmol]
7

E2 [J/kmol]
1.67 × 108

5

Kobayashi et al., 1977

0.3

1

2.0 × 10

1.3 × 106

Cho et al., 2007

0.38

0.8

3.7 × 105

1.46 × 1013

7.4 × 107

2.5 × 108

7

Ubhayakar et al., 1976

0.292

0.438

3.7 × 105

1.46 × 1013

7.4 × 107

2.5 × 108that was placed outside the main burner port, in order tostabilize the pulverized-coal flame.
Tables 3 and 4 show the properties of coal and the conditions for pulverized coal flame, respectively. Newlands
bituminous coal was selected as the fuel. The mass-based
median diameter measured by a laser diffraction particle
size analyzer was 33 μm, and the number-based average diameter was 25 μm. The air/coal mass ratio was set to 1.58.

3.2 Preparation of the laser-induced incandescence(LII) in the pulverized-coal flame
Although the laser induced incandescence (LII) is a
non-intrusive diagnostic that obtains the volume fractionof primary soot particles in the flame (Michelsen H.A.,
2017), both the laser-sheet profile and the laser-pulse fluence should be carefully adjusted when applying LII to
the pulverized-coal flame.
Fig. 12 shows the cross section of the laser-intensity
profile at the center of the measurement plane (the centerof the main burner port). A thin laser sheet was shaped byfour cylindrical lenses with focus lengths of f = –300 mm,
25 mm, 700 mm, and 2,000 mm. (Note that this opticalsetup was same in all experiments in this chapter). The
laser sheet has the Gaussian profile in the horizontal axis,
as shown in Fig. 12. The laser sheet thickness was definedby taking 1/e2 of the maximum intensity. The LII signals
obtained by the Gaussian profile (full sheet) and the ho-

1741.05 × 10

8mogeneous profile (partial sheet) were examined by
Hayashi J. et al. (2013), in order to understand the effectsof the laser profiles on the LII applied to the pulverizedcoal flame.
The relation between the signal intensity of the LII andthe laser-pulse fluences are shown in Fig. 13. The values
in Fig. 13 were normalized using the signal intensity of
the LII at a laser fluence of 0.1 J/cm2. Results obtained in
the non-combustion case were normalized by the signal
intensity of the LII in the Gaussian profile at the same laser fluence as other combustion cases. Indeed, from
Fig. 13, it is evident that three regions in the combustion
case exist: the heating region (a), the plateau region (b),and the superimposed region (c). In region (a), the signal
intensity of the LII increases with an increase in the laser
fluence. In this region, the laser fluence is insufficientwith respect to heating all the soot particles in the measurement area up to the sublimation temperature. In region (b), the signal intensity of the LII decreases slightly
with an increase in the laser fluence, ultimately plateauing. Indeed, these two regions—(a) and (b)—can also befound in the LII measurements of gaseous flames (Schulz
C. et al., 2006). For gaseous and spray (Hayashi J. et al.,2011) flames, LII was conducted with the laser fluence inthis plateau region. This is because the signal intensity of
the LII does not change with an attenuation of the measurement field. However, to apply LII to the context of apulverized-coal flame, the laser fluence should be care-Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 11 Schematic of the coal jet burner and supplying system. Reprinted with permission from Ref. (Hayashi J. et al., 2019). Copyright: (2019) Elsevier B.V.
Table 3 Properties of coal. Reprinted with permission from Ref.
(Hayashi J. et al., 2013). Copyright: (2013) Elsevier B.V.

Table 4 Experimental conditions. Reprinted with permission from
Ref. (Hayashi J. et al., 2013). Copyright: (2013) Elsevier B.V.

Item

Value

Item

Value

a

29.1 MJ/kg

Pulverized coal feed rate

1.49 × 10 –4 kg/s

Lower heating valuea

28.1 MJ/kg

Thermal input of coala4.19 kWa0.83 kW

Higher heating value

Proximate analysis

Thermal input of CH4

Moistureb

2.60 wt%

Air flow rate

1.80 × 10 –4 m3/s

Asha

15.20 wt%

CH4 flow rate

2.33 × 10 –5 m3/s

26.90 wt%

Bulk equivalence ratio

ϕ = 6.09

57.90 wt%

Reynolds number, Re

2,544

Volatile mattera
Fixed carbonaaUltimate analysis
Carbona
Hydrogen71.90 wt%a4.40 wt%

Nitrogena

1.50 wt%

Oxygena
Total sulfur

6.53 wt%aCombustible sulfura0.44 wt%a0.39 wt%

Based on the lower heating value

tion temperature so that all the soot particles emit enough
LII signals for the evaluation of the soot particle volume
fraction in pulverized coal flames. At the same time, it
should be mentioned that too high fluence of laser may
cause the overestimation of the volume fraction of sootparticles in pulverized coal flame due to the signals of LII
from the pulverized coal particles.

b

Dry basis, As received

fully controlled according to region (c). While region (c)is evident in pulverized-coal flames, it does not appear in
the LII measurements for the flames of both gaseous andliquid fuels. As shown in region (c) of Fig. 13, the signal
intensity of the LII re-increases with an increase in the laser fluence. This result is because the signals of the LII
from the pulverized-coal particles are superimposed onto
the signals of the LII from the soot particles. Indeed, the
LII signal in the non-combustion case, in which there areno soot formation, increases in the range of laser fluencewith higher than 0.2 J/cm2 (shown as the solid square in
Fig. 13).
These results suggest that sufficient fluence of the laser
is required to heat all the soot particles up to the sublima-

3.3 Simultaneous measurements of LII and Mie
scattering, and comparisons with OH-PLIF
In this section, the simultaneous measurements of Mie
scattering and the LII in the pulverized coal flame are
discussed in order to understand how the coal particles
and soot formation are related. Two-dimensional imagesof Mie scattering and the LII with OH-PLIF (Hwang S.M.
et al., 2005) are shown in Fig. 14, from which it is evident
that the signals of Mie scattering are strong near theburner port and it decreases with an increase in height
above the burner port (HAB). Contrastingly, the LII andthe OH-PLIF signals increase with an increase in HAB. It
is noteworthy that the full sheet (Gaussian) is adopted inFig. 14 for visualizing all signals. Moreover, from175

Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 12 The laser sheet profile (a) width of the laser sheet (1/e2value) = 0.1 mm, (b) height of the Gaussian laser sheet = 29.6 mm, (c)height of the homogeneous laser sheet = 10 mm). Reprinted with permission from Ref. (Hayashi J. et al., 2013). Copyright: (2013) Elsevier
B.V.

Fig. 14(b), it is evident that some discrete areas of sootare present near the burner port, the sizes of which increase with an increase in HAB. When the HAB reaches
roughly 135 mm from the burner port, the shape of thesoot-formation area changes from being discrete to being
streaky.
To understand the interaction of coal particles with respect to combustion reaction and soot formation, the averaged radial distributions of the signals of the Miescattering, the LII and the OH-PLIF at different HABs
(60 mm and 120 mm) are shown in Fig. 15. The signal intensities of the OH-PLIF and the LII increase with an increase in HAB, as observed in Fig. 14. The overlapping
region of signals expands with an increase in HAB; thisresult is due to the turbulent mixing and the expansion ofburned gas. Note that the peak value of the OH-PLIF signal, which is formed by the methane pilot flame, appears
at the furthest position from the burner center.
Fig. 16 illustrates the radial distributions of gaseous
temperatures and oxygen concentrations obtained by using the results of the numerical simulation with TDPmodel applied to the coal jet burner (Hashimoto N. et al.,2012b), at the same HAB in the experiment. Indeed, thelow oxygen concentration region expands in the radial direction with an increase in HAB, which corresponds tothe tendency of the LII signal shown in Fig. 15. Moreover,from Fig. 16, it is evident that the oxygen concentration at
the center line of the burner decreases with an increase in
HAB. This result suggests that the combustion reaction ofvolatile matter from pulverized-coal particles consumes
the oxygen even in the center of the flame. On the other
hand, the LII-signal intensity near the center is low anddoes not change with an increase in HAB. This is because

176

Fig. 13 The LII signal intensity as a function of the laser pulse energy; (a) heating up region, (b) decreasing region, (c) superimposed region. Reprinted with permission from Ref. (Hayashi J. et al., 2013).
Copyright: (2013) Elsevier B.V.

Fig. 14 The instantaneous distributions of (a) Mie scattering signals,(b) LII signals and (c) OH-PLIF signals. Reprinted with permission
from Ref. (Hayashi J. et al., 2013). Copyright: (2013) Elsevier B.V.

the temperature at the center of the burner was below
1,500 K, which is not sufficient for soot formation. In fact,
the signal intensity of the LII in the high-temperature
region (from r = 5 to 10 mm) increases with an increase
in HAB. In addition, since the signals of the Mie scattering can be found in the same region as the high signal intensity of the LII, a sufficient amount of volatile matterfor soot formation is supplied from the pulverized-coalparticles in this region. From Fig. 15, moreover, it is evident that the signals of the Mie scattering are low in theregion around the outer peak of the OH-PLIF signal,Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 15 The ensemble-averaged radial distributions of the Mie scattering signal, LII signal and OH radical chemiluminescence signal normalized by the maximum value at 120 mm; (a) h = 60 mm, (b)h = 120 mm. Reprinted with permission from Ref. (Hayashi J. et al.,2013). Copyright: (2013) Elsevier B.V.

where the gas temperature is high, and the oxygen concentration is minimal. This result means that the required
amount of volatile matter for soot formation cannot be
formed, because the number density of coal particles issmall in this region. Therefore, the signal of LII does notappear in this region in spite of the low oxygen concentration and the high gas temperature.
These results indicate that soot formation is enhanced
at locations if the following conditions are satisfied: highgas temperature, low oxygen concentration, and the existence of pulverized-coal particles.

3.4 Primary soot particle distribution
measurements in pulverized-coal jet flame
Primary soot-particle size is another important element, with respect to verifying the numerical-simulation
models of soot formation for pulverized-coal flames. The
spatial distribution of the primary soot particle size wasmeasured employing a combination of a time-resolved LII(TiRe-LII) and the SEM images collected by thermophoretic sampling (TS). Fig. 17 shows the schematic illustra-Fig. 16 The radial distribution of temperature and the O2­concentration (Obtained from Hashimoto et al. 2012b); (a) h = 60 mm,(b) h = 120 mm. Reprinted with permission from Ref. (Hayashi J. et al.,2013). Copyright: (2013) Elsevier B.V.

tion of TiRe-LII measurement. Fig. 18 shows the typical
SEM images of soot particles collected by TS, theprobability-density and the cumulative frequency functions of primary soot-particle size based on sphere equivalent volume of the soot particles (Hashimoto N. et al.,2016a). From Fig. 18(a-1), (a-2), and (a-3), it is clear thatthe number density of the soot particles on the SEM gridincreases with an increase in HAB. This is consistent
with the tendency of soot volume fraction measured by
the LII as shown in Fig. 15.
The red solid circles in Fig. 18(a-2), (b-2), and (c-2)
represent the cumulative plots of the primary soot-particle
sizes, which were calculated by randomly sampling theparticles obtained in the SEM images. The approximatedcumulative curves of the primary soot-particle sizes areshown as blue solid curves in Fig. 18(a-2), (b-2), and (c-2)
employing the log-normal function expressed by the following equation:

F

Dp

1
  ln Dp   ln Dp,m  
erfc  

2
σ 2
 


(4)

where Dp is the primary soot-particle diameter, and Dp,m177

Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 17 Schematic of measurement set up for time-resolved ­laser incandescence (TiRe-LII). Reprinted with permission from Ref. (Hashimoto N. etal., 2016a). Copyright: (2016) Japan Society of Mechanical Engineers.

is the median diameter based on the particle volume. The
parameters σ and Dp,m are determined by the least-squares
method in order to fit the curves to the measured diameter
distributions. The green dashed curves indicate the probability density function converted from the blue cumulative frequency curves, which are expressed by thefollowing equation:
P Dp 

 1  ln Dp   ln Dp,m   2
exp  σ
2π σDp 
 2 
1(5)

Indeed, the primary soot-particle size distribution
shifts to the larger side with an increase in HAB. This
­result indicates that primary soot-particle size increases
as said particles move downstream. Moreover, it is also
evident that the distribution of the primary soot-particle
size widens with an increase in HAB. This result meansthat the maximum value of the probability density function of primary soot-particle size decreases with an increase in HAB.
Fig. 19 shows the distributions of the primary soot-­
particle size and the soot-volume fraction. As shown in
Fig. 19, while the primary soot-particle size increases andthe region of soot expands in the radial direction, the radial position of the peak value of the soot-volume fraction
does not significantly change with an increase in HAB.

3.5 Simultaneous imaging of Mie scattering,
polycyclic aromatic hydrocarbons laser-induced
fluorescence, and soot LII with respect to alab-scale turbulent jet pulverized-coal flame
Since polycyclic aromatic hydrocarbons (PAHs) are
known as a soot precursor, information relating to theirformation is crucial with respect to the soot-formation
processes (Michelsen H.A., 2017 and Desgroux P. et al.,178

2013). In order to understand the transitional soot formation processes in the pulverized-coal flame, Hayashi et al.
(2019) conducted two different simultaneous measurements (“Mie scattering for coal particles with LIF for
PAHs” and “LIF for PAHs with LII for soot”) in the coal
jet burner.
In the following reviewed work, LIF measurement for
PAHs using a laser with a wavelength of 355 nm, which isreferred to the results reported by Bejaoui S. et al., 2014
and Aizawa T. and Kosaka H., 2008, were conducted. Mie
scattering and LII were conducted using the same wavelength as LIF, in order to achieve simultaneous measurements. Laser fluence was set to 0.25 J/cm2, in order toensure sufficient signal intensity. Two-dimensional distributions of the signals of Mie scattering, LIF, and LII are
shown in Fig. 20. The signal intensities of the pulverizedcoal particles (Mie scattering), PAHs (LIF signal), andsoot particles (LII signal) are represented in green, blue,
and red, respectively. Indeed, PAHs exist at the center
axis due to the turbulent mixing as shown in Fig. 20(b).
This occurs because the PAHs measured according to the
LIF are gaseous, and therefore, they follow the gaseous
flow. This trend is similar to that of the OH-LIF signal(Hwang S.M. et al., 2005). Conversely, the discrete regions of LII are observed apart from the center line asshown in Fig. 20(c).
The overlaid images of both the Mie scattering and the
LIF are shown in Fig. 21, from which it is evident that theexisting regions of pulverized-coal particles and PAHs
slightly overlap. Due to the configuration of this work, thedevolatilization tends to begin from the outer side of themain coal/air premixed flow. As a result, a continuous andhigh-intensity LIF signal can be found in the surroundingarea of the Mie-scattering signals. Subsequently, theLIF-signal region expands toward the central region due

Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 18 Typical SEM images of soot particles, probability density and cumulative frequency functions for p­ rimary soot particle diameter. Reprinted
with permission from Ref. (Hashimoto N. et al., 2016a). Copyright: (2016) Japan Society of Mechanical Engineers.

to the mixing of the surrounding gases. This result is consistent with the numerical results obtained by Hara et al.
(2015). Here, it is known that the volatile matter of PAHs
with two to three aromatic rings can be formed directlyfrom coal particles (e.g., Zhang L. et al., 2017). This resultmeans that PAHs can exist wherever coal particles exist,
so long as the temperature is sufficiently high for devolatilization.
In essence, the existing regions of LIF and LII do notcorrespond with each other—see Fig. 21(bottom). It isnoteworthy that the interference of the LII signal andPAHs-LIF signal cannot be excluded during the schemeof excitation and detection in this work. On the other
hand, the LII signal collected at 400 nm with the gate delayed by around 70 ns from the laser incident is unambig-

uously issued from soot incandescence. The signals of the
LII shown in Fig. 21(bottom) are well separated from theprompt signal of the LIF. While only a few overlapping
locations of LIF and LII are observed, which require careful interpretation, no ambiguity in assigning the prompt
signal to the LIF from PAHs exists in any other location.
The existing soot region (the regions of LII signal) is limited and discrete at the bottom of the jet flame; moreover,
the relative soot-volume fraction increases with an increase in HAB. However, the soot formation was inhibited in the center axis. This occurs because thetemperature in this region was relatively low and, moreover, because oxygen was still present at the relevant
HAB. Lee S.M. et al. (2004) measured the LIF of PAHs
using different wavelengths, showing that the displace-179

Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 19 Ensemble-averaged distributions of primary soot particle diameter and soot volume fraction. The color indicates the primary soot particle
diameter and the height indicates the soot volume fraction. R­ eprinted with permission from Ref. (Hashimoto N. et al., 2016a). Copyright: (2016) Japan Society of Mechanical Engineers.

Fig. 20 Two-dimensional distribution of Coal-Mie (in Green), PAHsLIF (in Blue) and soot-LII (in Red) at different HAB. Reprinted withpermission from Ref. (Hayashi J. et al., 2019). Copyright: (2019) Elsevier B.V.

ment of both small PAHs and soot is much larger thanthat of large PAHs. This result suggests that a necessary
period of time is required for the development of PAHs tosoot, during which time discrete regions form, as shownin Fig. 21.
The averaged radial-signal distributions of the Miescattering, LIF, and LII are shown in Fig. 22, from which
it is evident that the pulverized-coal particles are spatiallydistributed and, moreover, that the existing region of them
expands with an increase in HAB. The distribution of the
LIF signals expands from the fringe to the central axis ofcoal flame with an increase in HAB; this occurs because
the PAHs contained in the volatile matter is evolved fromthe pulverized-coal particles at high temperatures. Indeed, the signal distribution of LII does not expand fromthe fringe to the central axis of the coal flame with an increase in HAB.
The volatile-matter mass-fraction distribution for theradial direction at each HAB predicted by the numerical180

Fig. 21 Overlaid images of Coal-Mie (green) and PAHs-LIF (blue)(top), PAHs-LIF (blue) and soot-LII (red) (bottom) at different HAB.
Reprinted with permission from Ref. (Hayashi J. et al., 2019). Copyright: (2019) Elsevier B.V.

simulation conducted by Hashimoto et al. (2012b) isshown in Fig. 23. Indeed, a good correlation between themeasured LIF signals (Fig. 22) and the predicted volatile-matter mass fraction (Fig. 23) exists, even though
there are some discrepancies.

3.6 Numerical simulation for soot formation inpulverized-coal combustion fields
Pioneers for the development of soot-formation models
for the numerical simulation of coal-combustion fields are
Brown A.L. and Fletcher T.H. (1998), who developed amodel for RANS-based CFD software. The accuracy ofthis model was validated using data obtained by TS in alaminar-flow reactor (Ma J. et al., 1996). However, said
data were insufficient with respect to validating the accuracy of the model for a turbulent coal combustion field.
As mentioned in previous sections, the detailed data including two-dimensional soot-particle volume-fraction
distributions in the coal combustion field are now available. Xu K. et al. (2017) developed a soot formation modelfor RANS-based numerical simulations same as theNozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 23 Radial distributions of volatile matter obtained by Hashimoto
N. et al. (2012b). Reprinted with permission from Ref. (Hayashi J. et al.,2019). Copyright: (2019) Elsevier B.V.

Fig. 22 Radial distributions of Mie Scattering, PAHs-LIF and SootLII Reprinted with permission from Ref. (­Hayashi J. et al., 2019).
Copyright: (2019) Elsevier B.V.

model proposed by Brown A.L. and Fletcher T.H. (1998);
they validated the simulation using our measured data
(Hayashi J. et al., 2013). Muto M. et al. (2018) developed asoot-formation model for the DNS of coal-combustion
fields. They used the detailed chemistry for soot formation; their simulation results are yet to be validated. Our
research group developed a soot formation model for the
LES of coal-combustion fields (Takahashi H. et al., 2019).
We combined the soot-formation model proposed byBrown A.L. and Fletcher T.H. (1998) and the TDP model
proposed by Hashimoto et al. (2014), because the prediction accuracy of devolatilization strongly affects the sootformation, which is evident in Fig. 3.
In the developed model, the parameters V*, Av, and Ev
are stored in the devolatilization database. The databaseproduced by Hashimoto et al. (2012b) using the
FLASHCHAIN model was employed in the study. Since
LES is unsteady simulation, the extraction procedure introduced in Section 2.2, which was developed for steadystate numerical simulation, was modified so that the TDP
model can be applied for LES (Takahashi H. et al., 2019).
In the model, four temperatures, which are 500, 800,
1100, and 1400 K, were set to calculate the average particle heating rate for each group of particles with the same
initial diameter. The averaged heating rate of 100 particles is compared with particle heating rates in the devolatilization database. Then, the devolatilization parameters
associated with a heating rate in the database that is theclosest to the averaged particle heating rate calculated
from LES is selected are selected as new parameters forthe next time step.
In the developed model, soot was treated as a gas phase
substance. The conservation equation for soot particles isexpressed as follows:
ρgφ
 
φ
μ T 

γ φ
S φ , (6) ρgu j φ  ρg Ds
tx j 
x j
T x j 

where φ is either NC (soot particle number density) or YC(mass fraction of soot). Ds and γ represent the diffusion
coefficient for soot particles and the coefficient for thethermophoretic force acting on the soot, respectively. Ds
is calculated by the following equation:

Ds  μ / σρg(7)where μ, σ, and ρg represent the gas phase viscosity, theSchmidt number (= 700 (Brown A.L. and Fletcher T.H.,

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Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

1998)), and the density of the gas phase, respectively. SYC(source term of YC) is calculated by the following equation:=
SYC ρg (rFC − rOC)(8)

where ṙ FC and ṙOC are the rates of soot formation and oxidation, respectively. SNC (source term of NC) is calculatedusing the following equation:
S NC =

g NA
⋅ rFC − rAN 
N A  M C ⋅ C min(9)where ṙAN, MC, and Cmin represent the soot agglomeration
rate, the molecular weight of carbon, and the number ofcarbon atoms per incipient soot-particle, respectively. The
term γ in Eq. (6) is the thermophoretic-transport coefficient, which is calculated by the following equation:

γ

3

(10)

A
4 1  π  8

where A is the accommodation coefficient. The soot formation rate in Eq. (8) is calculated by the following equation:E 4 Ys, Ta ri 
− FCrFC = g ⋅  ∑ ⋅ AFC ⋅ e RT
 i =1 MWTa ri 

(11)where MWTari, AFC, EFC, and R represent the molecularweight of the tar species, the pre-exponential factor, theactivation energy, and the gas constant, respectively.
Ys, Tari represent the tar-mass fraction, and is obtained
from the TDP model. The soot-oxidation rate in Eq. (8) is
calculated by the following equation:rOC = SAv,c ⋅ pO 2 ⋅ T

−

1
E
− OC
2 ⋅A
RT
OC ⋅ e(12)

where SAv,C and pO2 represent the soot-particle surface
area per unit volume and the partial pressure of oxygen,
respectively. The shape of the soot particles is assumed to
be a perfect sphere, and SAv,C is calculated by the following equation:
1



2

2

SAv,C π  N C 3  6  YC 3  ρg  ρC 3

(13)

where ρ C is the soot particle density (= 1,950 kg/m 3(Brown A.L. and Fletcher T.H., 1998)). The soot-­
agglomeration rate in Eq. (9) is calculated by the following equation:
1

1

1

11
6M C  6  6κT  2  ρg ⋅ YC  6⋅rAN = 2Ca 
ρg ⋅ N C ) 6 (14)
(




 π ⋅ ρC   ρC   M C 

where Ca represents the collision frequency constant,which was set as 3 (Brown A.L. and Fletcher T.H., 1998).
The values for the pre-exponential factors and the activation energies for ṙ FC and ṙOC are listed in Table 5.
Radiative heat transfer was calculated using the­discrete-ordinate method (Fiveland W.A., 1984) with the182

Table 5 Pre-exponential factor and activation energy for transport
equation source terms. Reprinted with permission from Ref. (Takahashi
H. et al., 2019). Copyright: (2019) Elsevier B.V.

Term Ref.

Ev [J/mol]

A

ṙ FC

Ma et al., 1996 5.02 × 10 m ∙ mol ∙ sṙOCLee et al., 1962 1.09 × 104 m–1 ∙ s ∙ kg–1 ∙ K–1/2 164.5 × 103

8

3

198.9 × 103

S4 approximation. The coal-particle emissivity, ϵ p, wasassumed to be 0.85, according to Kurose et al., 2004. The
continuous phase absorption coefficient, ka, was calculated by the following equation:k
k g  ksa(15)

where kg and ks represent the gas-absorption coefficientand the soot-absorption coefficient, respectively. The
value for kg was set to 0.075, and ks was estimated by thefollowing equation (Wen Z. et al., 2003):=
k s 1.8644 × 10 3 f vsoot T(16)

where f vsoot and T represent the soot-volume fraction, andthe gas temperature, respectively.
Fig. 24 shows the overview of the computational domain for LES. The entire shape of the domain is a cylinder with a diameter of 200 mm and a length of 560 mm(–60 < HAB < 500 mm). The exit of the burner was set
to HAB = 0 mm. The number of nodes was about 1.8 million, and the number of fluid cells was about 2.0 million.
The time step of the calculation was set to 2 × 10 –5 s.
Fig. 25 shows the comparisons of soot-volume
fractions made between the measured and calculated data.
In the left-hand side of the figure, the direct photo of theflame and the measured soot volume fraction distribution
obtained by LII are shown. The soot-volume fraction was
obtained by the ensemble average of 500 shots of the LII
signal. Indeed, large soot-volume fractions can be observed at the outer region of the luminous flame. Moreover, from Fig. 25, it is evident that the soot-volume
fraction increases with an increase in HAB. These tendencies can be reproduced by numerically simulating soot formation, as can be seen in the right-hand side of the figure.
Fig. 26 shows the various comparisons of the radial
distributions. The tendency of the signal distributions ofMie scattering to expand radially with an increasing HAB
can be reproduced by the calculated distributions ofcoal-particle surface area in numerical simulation, as
shown in Fig. 26(a) and (b). In addition, the position of
the calculated peak of the soot-volume fraction is almost
consistent with the peak of the LII signal. Furthermore,
the expansion trends of the soot-volume fraction distributions are evident in both experimental and theoretical results. In Fig. 26(e) and (f), it is evident that the conditionsof low oxygen concentration, high gas temperature, andNozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 24 Computational domain for LES. Reprinted with p­ ermission
from Ref. (Takahashi H. et al., 2019). Copyright: (2019) Elsevier B.V.

the existence of sufficient pulverized-coal particles are
satisfied at the peak position of the soot-volume fraction.
This trend can be explained by the following: the peak
positions of the net soot-formation rate in Fig. 26(g) and(h) match the peak positions of the soot-volume fractionin Fig. 26(e) and (f). Negative net soot-formation rates areevident at both sides of the base of the soot-volume fraction peak, even though the soot-volume fraction steadily
increases at these positions with an increasing HAB. Thisis because, due to the turbulence mixing effect, the sootparticles diffuse from the soot-volume fraction peak toward both sides. Oxygen concentrations where a negative
net soot-formation rate is observed are higher than thoseat the soot-volume fraction peak. This higher oxygen concentration causes a higher rate of soot oxidation. This position results in a significant effect on the formation of ahigh soot-volume fraction area, even though the absolutevalue of the net negative formation rate is not significantly
high. Basically, the soot particles diffuse from the peak
position of the soot-volume fraction; accordingly, in these
positions, net soot does not form. This result is the reason
why the high soot-volume fraction area is limited to anarrow range of radial distance.
Fig. 27 shows the average gas temperature distributions
obtained by LES: (a) without soot radiation and (b) withsoot radiation. From the figure, it is evident that there is
the maximum gas-temperature difference of over 100 K
between two cases. This temperature difference is causedby the difference in radiation heat flux to surroundings
from the coal flame. Average heat flux at the position
100 mm far away from the burner central axis, with sootradiation was 2.95 × 102 W/m2 while the average heat flux
without soot radiation was 2.69 × 10 –3 W/m2. This large
difference in heat flux causes significant differences in thepredictions of the gas-phase temperatures. Indeed, thisFig. 25 Comparison between measured (Hashimoto et al., 2016) andcalculated soot volume fraction. Reprinted with permission from Ref.
(Takahashi H. et al., 2019). Copyright: (2019) Elsevier B.V.

finding indicates the significance of a soot-formation
model for numerical simulations of pulverized-coal combustion fields. After all, if a soot formation model is notconsidered, the gas temperature can be significantly overestimated. Moreover, the accuracy of the gas-temperature
predictions significantly influences the majority of processes in coal combustion fields, such as the devolatilization of coal particles, the combustion reaction of volatile
matter, char-particle surface reaction, and the formationof pollutants such as NOx. Therefore, the soot formation
model such as the model in the reviewed study in thispaper should be employed for simulations of coalcombustion fields.

4. Prospects for research and development forcoal combustion
Although the great efforts for the development of
accurate numerical simulation technologies for coal

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Nozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 26 Comparison of the radial distributions for (a), (b) the soot LII signal (Hayashi J. et al., 2013) and the calculated soot volume fraction, (c), (d)the Mie scattering signal (Hayashi J. et al., 2019) and the ­calculated surface area of coal particles, (e), (f) the calculated gas temperature and the O2
concentration, and (g), (h) the net soot formation rate at a HAB = 60 and 120 mm, respectively. Reprinted with permission from Ref. (Takahashi H.
et al., 2019). Copyright: (2019) Elsevier B.V.

combustion fields have been made by various researchers,
there are still a large room for improving the accuracy ofthe simulation technologies for coal combustion fields.

184

Recently, the flamelet approach, which can treat detailed
chemistries with relatively low computational cost by employing the tabulation method, has also been applied forNozomu Hashimoto et al. / KONA Powder and Particle Journal No. 38 (2021) 168–188

Fig. 27 Effect of soot radiation on the ensemble-averaged gas temperature distribution. Reprinted with permission from Ref. (Takahashi
H. et al., 2019). Copyright: (2019) Elsevier B.V.

numerical simulations of coal combustion fields (e.g.,
Watanabe J. et al., 2017, Wen X. et al., 2019). However,the detailed chemistry for volatile matter combustion has
not been developed yet, because detailed molecular forheavy species such as tar cannot be identified due to its
complexity. Therefore, the postulated substances such as
C6H6 are employed as volatile matter, although actual tar
species are much heavier species than C6H6. Although themethods for flamelet approach have been already developed, the accuracy of numerical simulations cannot be
improved until the detailed chemistries for volatile matterand soot particles will be developed. Thus, the clarification of detailed chemistries for volatile matter and sootparticles is expected in the future. The accurate prediction
technologies for NOx emission from coal combustion
fields is another important issue. Although the NOx emission can be qualitatively predicted by the existing NOx
models (e.g., Hashimoto N. et al., 2017), developments ofmore accurate NOx formation/reduction models are expected to improve the accuracy of the prediction. The
prediction of ash behavior in boilers is also important issue (e.g., Matsui Y. et al. 2019).
In addition to those issues mentioned above, the plants
themselves require efficient use; moreover, new types offuel, such those produced from using renewable energy is
expected, because the CO2 emissions per unit of obtainedenergy from coal-fired plants are larger than those fromother energy plants. One of possible new type fuels forcoal-fired boiler is ammonia, which is promising energy
carrier in the future. Since ammonia does not have carbon
in its molecule, the direct combustion of ammonia can be

an option. Many researches have been conducted on thefundamental combustion characteristics of ammonia(Kobayashi et al., 2019, Okafor E.C. et al., 2019, Ichimura
R. et al., 2019, Hayakawa A. et al., 2015). Although verification tests and bench-scale tests using large-scale burners have been conducted for the mixed combustion ofammonia and pulverized-coal particles (Kobayashi et al.,2019), research is currently lacking with respect to thefundamental characteristics of mixed combustion of ammonia with pulverized coal particles.
Accordingly, our research group recently started to
conduct the fundamental research on the mixed combustion characteristics of ammonia with pulverized coal particle cloud (Hashimoto N. et al, 2019a, 2019b). The flame
propagation characteristics of an ammonia-coal particle
cloud in turbulent fields has been investigated by using a
fan-stirred constant volume vessel (Hadi K. et al., 2019).
The developments of the mixing combustion models using the experimental results from these researches for theammonia-coal particle cloud mixture for numerical simulations is expected in the near future.

5. Conclusions
In this review paper, recent progress of research concerning coal-particle devolatilization model and the sootformation in pulverized coal combustion fields is reviewed. Employing the developed models for coal particle
devolatilization and the soot formation can greatly improve the accuracy of numerical simulations for coal
combustion fields. The accuracy of the models has beenvalidated by the experimental data measured by various
optical diagnostics, such as LDV, LII, TiRe-LII, and LIF.
Since non-validated models can cause significant errors innumerical simulations, the use of our measured data by
various researchers will be welcomed.

Acknowledgements
Reviewed work in this paper were partly supported by
JSPS KAKENHI Grant Number 15637712, MEXT as“Priority issue on Post-K computer” (Accelerated Development of Innovative Clean Energy Systems), JST research promotion program Sakigake (PRESTO) Grant
Number JPMJPR1542 and JSPS KAKENHI Grant Number JP19180646.

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Authors’ Short Biographies
Nozomu Hashimoto
Dr. Nozomu Hashimoto is an Associate Professor of Division of Mechanical andSpace Engineering, Graduate School of Engineering at Hokkaido University. He­received a Ph.D. in Mechanical Engineering from Hokkaido University in 2004. He waspreviously employed at CRIEPI (Central Research Institute of Electric Power Industry)in Kanagawa, Japan as a Research Associate. His research interests are in multi-phasecombustion phenomena such as coal combustion, spray combustion, and flame spreadover solid material. Current main subjects are modelling and experiment for coal combustion, droplet evaporation, flame spreading over electric wire, and ammonia flame
propagation in turbulent fields.

Jun Hayashi
Dr. Jun Hayashi is an Associate Professor of Department of Energy Conversion Science at Kyoto University and is a Visiting Associate Professor at Osaka University. He
received a Ph.D. in Mechanical Engineering from Osaka University. He worked for
Osaka University as an Assistant Professor and a Lecturer. His current research interests
are in multi-phase combustion phenomena appearing in the industrial combustion facilities including internal combustion engines. His current subjects are a soot formation in
the multiphase combustion, a plasma assisted ignition/combustion and a flame structureof hypergolic fuels.

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Review Paper

Scaling-up the Calcium-Looping Process for
CO2 Capture and Energy Storage †Carlos Ortiz 1,2*, José Manuel Valverde 1, Ricardo Chacartegui 3,
Luis A. Pérez-Maqueda 4 and Pau Gimenez-Gavarrell 3
1Facultad de Física, Universidad de Sevilla, Spain
Universidad Loyola Andalucía, Spain
3
Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Spain
4
Instituto de Ciencia de Materiales de Sevilla, C.S.I.C.-Universidad de Sevilla, Spain
2

Abstract
The Calcium-Looping (CaL) process has emerged in the last years as a promising technology to face two key
challenges within the future energy scenario: energy storage in renewable energy-based plants and CO2 capture
from fossil fuel combustion. Based on the multicycle calcination-carbonation reaction of CaCO3 for both
thermochemical energy storage and post-combustion CO2 capture applications, the operating conditions for eachapplication may involve remarkably different characteristics regarding kinetics, heat transfer and material
multicycle activity performance. The novelty and urgency of developing these applications demand an importanteffort to overcome serious issues, most of them related to gas-solids reactions and material handling. This work
reviews the latest results from international research projects including a critical assessment of the technology
needed to scale up the process. A set of equipment and methods already proved as well as those requiring further
demonstration are discussed. An emphasis is put on critical equipment such as gas-solids reactors for both
calcination and carbonation, power block integration, gas and solids conveying systems and auxiliary equipment
for both energy storage and CO2 capture CaL applications.
Keywords: calcium looping, CO2 capture, energy storage, CSP, solar energy

1. Introduction
Achieving a sustainable energy transition towards a
low carbon society model is one of the main challenges
facing humanity in the coming years. The immediate effects of climate change on the environment require urgent
actions (IRENA, 2017). Despite important advances on
the implementation of renewable energies (IEA, 2015),
CO2 emissions continue to grow, mainly due to the increase in energy demand worldwide (IEA, 2019). Technology pathways to reduce emissions are focused on thelarge-scale implementation of renewable energy and Carbon Capture and Storage (CCS) technologies.
In the last years, the Calcium-Looping (CaL) process
has gained attention due to its huge potential to be integrated in future energy facilities as well as to retrofit ex-

isting ones. Due to the potential applications of CaL, theprocess is fully aligned with some of the most important
challenges to be solved within the future energy scenario(IRENA, 2018). Thus, the CaL process can be applied inboth renewable and fossil-fuel-based power plants as energy storage and CO2 capture systems, respectively. In
addition to these main applications, the CaL process isbeing investigated for other applications such as Enhanced Oil Recovery (EOR) or hydrogen production(Hanak et al., 2018b). Despite the CaL process in theseapplications being based on the same basic calcination/
carbonation reaction which has been used in a myriad ofother applications by humankind, the specific operating
conditions in each case can be very different as imposedby the application (Benitez-Guerrero et al., 2017b).
CaCO 3 (s) o CaO (s) + CO 2(g)†Received 13 June 2019; Accepted 4 September 2019
J-STAGE Advance published online 31 March 2020
1,3
Av. Reina Mercedes s/n, 41012 Seville, Spain
2
Av. de las Universidades, 41704 Dos Hermanas, Sevilla, Spain
4
Américo Vespucio n°49, 41092 Sevilla, Spain* Corresponding author: Carlos Ortiz;E-mail: cortiz7@us.es
TEL: +34 655783930∆H r0 =
178

kJ
mol

(1)

The CaL process relies on the multicyclic calcinationcarbonation of CaCO3 (Eqn. 1), which can be obtained
from limestone as the second most abundant material onearth after water. Regarding CO2 capture, the CaL process is especially advantageous for its high efficiency andlow CO2-avoided costs (Zhao et al., 2013). The standard

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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cycle for CO2 capture from flue gas streams uses CaO(previously derived from limestone calcination), to produce CaCO3 by carbonation at high temperature (~650 °C)(Eqn. 1).
As a thermochemical energy storage system (TCES),
the CaL process can be integrated in renewable power
plants, e.g. Concentrating Solar Power (CSP) plants, to increase the dispatchability of the system. The process
would work as follows: solar thermal power is used to decompose CaCO3 in a solar calciner according to Eqn. 1.
The resulting CaO and CO2 products are stored independently and when energy is demanded, CaO and CO2
react at high temperature (> 650 °C) in the carbonator torelease the stored energy while CaCO3 is regenerated(Chacartegui et al., 2016). The key advantages of TCES
systems in comparison with traditional and sensible heatbased energy storage are the higher energy density and its
capacity for long-term energy storage (Pardo et al., 2014).
On the other hand, depending on the TCES system andthe operation conditions, the energy consumption by­auxiliary equipment could be higher than in commercial
energy storage systems (Bayon et al., 2018; Ortiz et al., 2018a).
In recent years the study of the CaL process has attracted the attention of many researchers. A large numberof works have been focused on the CaL process, mainly
based on lab-scale analysis and process simulations(Blamey et al., 2010; Ortiz et al., 2019b; Perejón et al.,2016b). Pilot-scale demonstration plants up to 2 MWthhave demonstrated the efficiency of the process (Arias etal., 2013; Hanak et al., 2015).
Because of the huge potential scope for the applicationof the CaL process within the present energy technology
pathway in both renewable and non-renewable power
plants and in new or retrofitted facilities, a rapid technology advancement as well as a reduction of costs are expected. This manuscript reviews the latest advances andresults on an international level with a critical assessmenton the technology requirements to scale the process up.
Equipment and methods already proved as well as thoserequiring further demonstration are discussed.
This work is structured as follows: firstly, an overallsummary of the CaL process and its applications are carried out. Later, a summary of the latest international R&D
projects is present. Through the analysis of the main technology involved, a critical assessment of the current stateof the art of the technology is carried out.
Next, steps to facilitate the commercial employment of
the CaL process are finally drawn.

2. Current status and challenges on the road to
the CaL process employment on a large scale
Based on a very abundant, non-toxic, non-reactive and190

widely available natural material such as limestone, the
CaL process is considered a cost-effective technology forpost-combustion CO2 capture. As such it could be integrated in the short-term for its relatively easy integrationin currently existing fossil fuel power plants (Wang et al.,2011). Fig. 1 shows the typical CaL process schematic for
retrofitting power plants. Since flue gas from coal-fired
power plants typically contains a CO2 mole fraction in therange of 10–15 %, the optimum carbonation temperature
would be around 650 °C to achieve a high capture efficiency (~90 %) in the necessarily short residence times ofa few minutes (Romano et al., 2013).
Currently, there are several pilot-scale plants testing the
CaL process for post-combustion CO2 capture, with a total installed capacity around 5 MWth (Hanak et al., 2015).
The largest facilities are located in Hualien (1.9 MWth)(Chang et al., 2014), La Pereda (1.7 MWth) (Arias et al.,2013) and Darmstadt (1 MWth) (Ströhle et al., 2014).
However, several issues must be still addressed for a­successful employment of the technology on a larger
scale: to enhance the CaO multicyclic activity, achieving
an efficient CO2 capture energy integration and ensuring
adequate handling of the solids.
The CaO reactivity towards carbonation decays progressively with the number of cycles before reaching a
low residual value (Abanades, 2002; Perejón et al., 2016b;
Valverde, 2013a). Under CO2 capture conditions, the lossof multicycle activity is mainly due to the sintering of
CaO grains at high temperature, which reduces the surface area available for fast carbonation (Borgwardt, 1989).
As shown in Fig. 2, the evolution of CaO conversion with
the number of cycles is, however, highly dependent on the
carbonation-calcination conditions (temperature, reactor
pressure and atmosphere) (Benitez-Guerrero et al., 2017a)
and the type of CaO precursor used (Ortiz et al., 2016b).
Conditions that would optimize the integration of the CaL
process in CSP plants would involve calcination at lower
temperatures, whereas carbonation would be carried out
at higher temperatures under pure CO2. CaO deactivation
would be mitigated under these conditions if particles are
small enough to avoid pore plugging (Benitez-Guerrero etal., 2017a). On the other hand, the particle size is not a determining factor under CaL conditions to capture CO2,
for which the main limiting mechanism is CaO sintering(Manovic et al., 2009). Pore plugging at CaL conditions
can also be avoided if dolomite is used as CaO precursor
instead of limestone (Benitez-Guerrero et al., 2017a).
CaO deactivation, which can be partially counterbalanced
by introducing a certain amount of fresh CaCO3 as a
make-up flow (Romeo et al., 2009), leads to a large massof recirculating inactive solids, which in turn leads toseveral issues: i) equipment oversizing; ii) higher energy
consumption for cooling/heating; iii) lower energy storage density, and iv) higher energy consumption for solids

Carlos Ortiz et al. / KONA Powder and Particle Journal No. 38 (2021) 189–208

Fig. 1 Conceptual integration of the CaL process as a post-combustion CO2 capture system. The process was originally conceived as twointerconnected fluidized bed reactors (calciner and carbonator) (Shimizu et al., 1999).

conveying.
A proper energy integration is crucial for the feasibilityof the CaL integration on a commercial scale. Due to thehigh enthalpy of the reaction and the high turning temperature (~896 °C at atmospheric pressure under CO2), ahuge amount of thermal power is required and released
during the calcination and carbonation reactions, respectively. An adequate integration between both reactors isessential to reduce both the energy penalty in the power
plant and the equipment size, which critically determines
capital expenditures (Brown et al., 2016). Recent works
have been focused on this issue (Hanak et al., 2018a; Laraet al., 2013; Ortiz et al., 2016a; Spinelli et al., 2017).
Solids-­solids heat exchangers would be useful for improving the integration, albeit they are not available yet atthe commercial scale (see Section 4.6). The efficiency ofintegration greatly conditions the energy consumption per
kilogram of CO2 avoided (SPECCA), whose value for thealready mature technology based on amines is around
4 MJ/kg CO2 (CAESAR project, 2011). The CaL process
has the potential to reduce further this value to around
2–3 MJ/kg CO2 (Astolfi et al., 2019; Ortiz et al., 2016b;
Romano, 2013). Energy penalty values in the range of
3–9 % are reported in the literature (Perejón et al., 2016b).
Other challenges for the CaL employment on a large
scale are related to achieving an efficient solids handlingthrough the different components of the plant. This involves high-temperature particle conveying, reactors andstorage tank feeders to counteract the negative effect ofcohesiveness on the powder flowability if fine particles
are used (Espin et al., 2019; Valverde, 2013b) or attrition(Alonso et al., 2018; Ströhle et al., 2009).

Fig. 2 Effective CaO conversion (Xef) with the number of cycles (N)for limestone and marble (natural CaO precursors) for different CaL
conditions corresponding to (a) CSP energy storage (calcination under
He atmosphere at 725 °C, carbonation under pure CO2 at 850 °C) and(b) CO2 capture (calcination under 70 %v/v CO2 at 950 °C, carbonation
under 15 %v/v CO2 at 650 °C). ­Effective CaO conversion is defined as
the ratio of CaO converted to the total mass of sorbent including inert
solids if existing. Reprinted with permission from Ref. (Benitez-Guerrero et al., 2017a). Copyright: (2017) Elsevier.

The CaL process is also considered a promising technology for improving dispatchability in CSP plants bymeans of thermochemical energy storage. The process
was already proposed in the 1970–80s (Flamant et al.,
1980; Wentworth and Chen, 1976). The CSP-CaL integration has been the subject of recent works (Chacartegui etal., 2016; Sakellariou et al., 2015). A comprehensive review on the CSP-CaL system was published by Ortiz etal., 2019b. Fig. 3 shows the conceptual process schematicfor the CSP-CaL integration (TCES system). Due to thehigh temperature and the large enthalpy of the reaction,high thermal-to-power efficiencies could theoretically bereached from the CSP-CaL integration (> 45 % (Alovisio
et al., 2017)). Remarkably, the system uses widely available, non-toxic and cheap ($10/tonne (Hanak andManovic, 2017a)) limestone as a raw material and allows anotable increase in the dispatchability of CSP plants because of the high energy density of the system (Pardo et191

Carlos Ortiz et al. / KONA Powder and Particle Journal No. 38 (2021) 189–208

Fig. 3

Conceptual process for a thermochemical energy storage system (TCES) based on CaL.

al., 2014). A large number of lab-scale tests are being carried out to analyze the CaL process as a TCES system,
mainly related to the reaction kinetics (Kyaw et al., 1996;
Ortiz et al., 2018b; Salaudeen et al., 2018) multicyclic CaO
conversion (Benitez-Guerrero et al., 2017a, 2017b; Sarrión
et al., 2018) and process integration (Alovisio et al., 2017;
Chacartegui et al., 2016; Ortiz et al., 2019a).
The integration of the CaL process as a thermochemical storage system in CSP plants shares the same three
aforementioned drawbacks to be overcome for the integration as CO2 capture system. Indeed, the TCES systemis still far from commercial maturity. Currently only experimental solar calciners are available on a small scale ofa few kWs (Abanades and André, 2018; Flamant et al.,
1980; Meier et al., 2004). This is a major challenge that
requires a significant effort to bring the CaL technology
up to a commercial scale as a TCES system in CSP plants.

3. Current CaL research projects
During the last years, several research projects havebeen carried out worldwide with the aim of demonstrating
the feasibility of the CaL process on a pilot scale, from a
few kWth up to 2 MWth. Promising results from theseprojects are paving the way to scale up the process towards
a demonstration stage under a relevant environment.

3.1 CO2 capture projectsi) S CARLET: Scale-up of calcium carbonate looping
technology for efficient CO2 capture from power andindustrial plants (2014–2017) (SCARLET EU project,
2014)

192

The SCARLET project, funded by the European
Union’s Horizon 2020 research and innovation programme and recently finished, had the goal of validating
the feasibility of the CaL technology in an upgraded
1-MWth pilot plant. Successful operation of the pilot plantand optimization of the process parameters was demonstrated, which has been used to provide essential information for scaling up the process to a future 20-MWth pilot
plant.
ii) CEMCAP: CO2 capture from cement production(2015–2018) (CEMPCAP EU project, 2015)
CEMCAP was a project funded by the European
Union’s Horizon 2020 research and innovation programme.
It addressed the capture of CO2 from cement production
by integrating the CaL process. CEMCAP aimed to leverage to Technology Reediness Level (TRL) 6 cement
plants with a targeted capture rate of 90 %. Technoeconomic results based on process simulations showed thecost of CO2 avoided lies between 42–84 €/t CO2 depending on the CO2 capture system.
iii) CLEANKER: Clean clinker production by Calcium
Looping process (2017–2021) (CLEANKER EU project,
2017)
This project is also funded by the European Union’s
Horizon 2020 research and innovation programme. In thesame vein as the CEMCAP project, CLEANKER aims atdemonstrating at TRL7 the CaL concept in a configuration integrated with the cement industry. Entrained flow
technology is considered for the reactors.
iv) FLEXICAL: Development of flexible coal power plants
with CO2 capture by Calcium Looping (2016–2019)

Carlos Ortiz et al. / KONA Powder and Particle Journal No. 38 (2021) 189–208(FlexiCaL EU project, 2016)
FLEXICAL project, funded by the European Research
Fund for the Coal and Steel Commission, aims to develop
novel flexible calcium looping systems that can work
­under several flue gas loads. To this end, two process­options are tested on a pilot-scale: a highly load-flexible
plant concept and an energy storage system using CaO/
CaCO3 silos.
v) LEILAC: Low emissions intensity lime & cement(2016–2020) (LEILAC EU project, 2016)
This project is funded by the European Union’s Horizon
2020 research and innovation programme. The LEILAC
project is based on the use of an entrained flow reactor toenable an efficient capture of CO2 from lime and cement
production.

3.2 Energy storage projects
Below, several interesting projects about integrating
the CaL process as TCES are summarized:i) SOCRATCES: Solar calcium-looping integration forthermochemical energy storage (2018–2020) (Socratces
Project, 2018)
The SOCRATCES project, funded by the European
Union’s Horizon 2020 research and innovation programme, aims at exploring the feasibility of the CSP-CaL
integration by erecting a pilot-scale plant that will serve
to reduce the core risks of scaling up the technology as
well as allow further understanding of the process integration.
ii) Carbon Dioxide Shuttling Thermochemical Storage
Using Strontium (2014–2015) (Mei, 2015)
This project was awarded under the ELEMENTS program supported by the USA SunShot Initiative (DOE).
The project was based on the calcination/carbonation ofstrontium-based carbonates, which would allow discharging the stored solar energy at very high temperatures(over 1000 °C), however, this can hardly be achieved withcurrent CSP with tower technology. The much higher costof the sorbent precursor (SrCO3) –$580/tonne (Jin et al.,2018) – as compared to a price of around $10/ton for natural limestone (Hanak and Manovic, 2017a) is a serious
drawback for commercial expansion on a large scale.
iii) Regenerative Carbonate-Based Thermochemical
Energy Storage System for Concentrating Solar Power(2015–2016) (Gangwal and Muto, 2017)
Within the ELEMENTS program, the Regenerative
Carbonate-Based Thermochemical Energy Storage System for Concentrating Solar Power project was aimed atdeveloping a TCES for CSP based on reversible gas-solids

reactions of carbonate and silicate sorbent-based mate­rials on a bench scale. Overcoming the multicyclic CaO
deactivation was a key point of the project. A synthetic,
highly refined and tailored reinforced CaO sorbent exhibited a very stable multicycle behavior with a residual
sorbent capacity of around 0.3, although its use in practicewould be conditioned by a considerable increase of material costs and technical issues in the Ca-based synthetic
material fabrication.
iv) Demonstration of High-Temperature Calcium-Based
Thermochemical Storage System for use withConcentrating Solar Power Facilities (2014–2018)(Muto and Hansen, 2019)
This project, funded by the APOLLO program (DOE),
aimed to demonstrate a novel high-temperature calcium-­based thermochemical storage system for use in CSP facilities, which is directly related to the CSP-CaL system.
The results obtained are described in Muto and Hansen,
2019.
v) SOLPART: High-temperature Solar-Heated Reactors
for Industrial Production of Reactive Particulates(2016–2019) (Flamant et al., 2018)
This project is funded by the European Union’s Horizon
2020 research and innovation programme. The main objective of the SOLPART project is to develop, at hightemperature (800–1000 °C), a pilot-scale (30–50 kW)
24 h/day solar process suitable for supplying the thermalenergy requirement for CaCO3 calcination by high-temperature solar heat (Flamant et al., 2018). Although thisproject does not consider thermochemical energy storage,
its results are of utmost interest for the CaL process as
they would expand the knowledge on solar calcination,
high-­temperature solar reactors, the transport of high-temperature solid materials and high-temperature thermal
storage, all of which are fundamental for further development of the CaL process as a TCES.

4. Technology scale-up
The CaL process has been widely tested on a pilot scale(~2 MWth) as a post-combustion CO2 capture system(Hanak et al., 2015), while the first facilities are being developed to test it as a TCES system (Muto and Hansen,
2019; Socratces Project, 2018). Despite the promising preliminary results achieved on the pilot scale, several technological challenges must be overcome to permit scaling
up the technology. The main technologies needed thatare already available at commercial level as well as thoseunder development are reviewed next.

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4.1 Calciner
Achieving a proper calcination of particles is crucial
for a highly efficient CaL process. When applied to capture CO2, calcination under a high CO2 partial pressure
requires a temperature of around 930–950 °C to occur
over short residence times (few minutes) (Perejón et al.,2016b). The high enthalpy of the reaction and the high reaction temperature involves supplying a high amount ofenergy to the calciner, which can be satisfied by means of
oxy-combustion to ensure an almost pure CO2 stream at
the calciner exit ready to be compressed and stored or­reused. An important issue to be considered under theseharsh calcination conditions is the enhanced CaO sintering, which negatively affects CaO conversion at the carbonator (Maya et al., 2018). To decrease the calcination
temperature down to around 725 °C (Valverde and­Medina, 2016), the CO2 partial pressure should be reduced by introducing a certain amount of inert gas in thereactor such as steam or helium (Berger, 1927) that should
be separable from CO2. In the case of steam, CO2/H2O
separation could be carried out by condensation, whereas
if He is used, CO2/He selective membranes or Pressure
Swing Adsorption (PSA) could be employed. In thesecases, however, the energy penalty is increased as compared to calcination by oxy-combustion. Alternatively,
calcination could be carried out under partial vacuum(Beruto et al., 2004), which, however, raises the level ofcomplexity to avoid air leakages. Another option is toprovide the heat for calcination in an indirect way througha heat transfer wall or heat pipes (Hanak and Manovic,
2017b). This option would avoid the need of oxy-fuelcombustion, which contributes to most of the energy consumption in the CaL process (Ortiz et al., 2017b). On theother hand, heat transfer limitations are main challenges
yet to be solved. The LEILAC project is currently assessing the possibility of providing heat through a heat transfer wall from natural gas combustion (Hills et al., 2017).
In general, a large-scale calciner should provide: i)enough residence time for particles to reach the target
temperature and reaction completion; ii) fast calcination
under the required conditions for each application; iii)
good heat transfer coefficients; iv) minimization of thermal gradients and non-homogeneous conversion; v) prevention of particle attrition and agglomeration vi) proper
management of elevated gas and particle flow rates.
Calcination is a well-known process on a large industrial scale since it constitutes the basis of cement production. The commercial reactor in this case is a rotary kiln,
which consists of a steel tube with a length-to-diameter
ratio in the range of 10–38:1 (Schorcht et al., 2013) withmaximum working temperatures of ~2000 °C and scalable
to large sizes (> 200 m long) in order to produce around3600 tons/day (Schorcht et al., 2013). Usually, rotary kilns

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are coupled with particle preheaters where the gas effluent
from the calciner at 1000 °C preheats the solids entering
the kiln up to 700–800 °C. The existing knowledge on
calcination on a large scale from the cement industry may
play a key role for the development of the CaL process. In
fact, the synergy between the cement industry and the
CaL process has led researchers to investigate the integration of the CaL process in cement plants to capture theCO2 released during calcination in rotary kilns (De Lenaet al., 2019). CO2 emissions from cement plants represent
about 7 % of the total CO2 emission from large stationary
sources (Romano et al., 2014).
The CaL process for post-combustion CO2 capture wasoriginally conceptualized as a system of two interconnected fluidized bed (FB) reactors (calciner and carbonator) operating at ambient pressure (Shimizu et al., 1999).
To date, most of the process schemes and pilot test facilities are based on FB reactors including moving bed (MB),circulating fluidized bed (CFB) or bubbling fluidized bed(BFB) reactors (Hanak et al., 2015). FB reactors, which
are widely used in industrial processes, provide a large
gas-solids contact surface, thus enhancing heat/masstransfer (Yates and Lettieri, 2016). Fluidizability is critically conditioned by particle size (Valverde, 2013b). In thecase of fine cohesive powders (dp < 30 μm), interparticle
attraction forces prevail over hydrodynamic and gravitational forces (Castellanos et al., 1999), which leads to agglomeration, gas channeling and plugging phenomenathat hinder uniform fluidization (Raganati et al., 2018).
Fine particles, with a large surface-to-volume ratio, would,
however, provide a high gas-solids contact if fluidizable.
This represents an important advantage for the CaL process, as fast calcination is required. In its application forenergy storage, the negative effect of pore-plugging
during carbonation is minimized if fine particles are used,thus enhancing multicycle CaO conversion (BenitezGuerrero et al., 2017a). A number of fluidization-assisting
techniques have been proposed in the literature that could
be employed to enhance the flowability of fine particles in
the CaL process (Valverde, 2013b). Nevertheless, current
commercial cyclones would not be able to trap particles
elutriated in the fluidizing gas of a size below ~10 μm(Zhao et al., 2006).
Entrained-flow reactors, widely employed in the cracking industry (Chuachuensuk et al., 2013), can be an alternative technology to FB reactors for the calcination offine particles and as such, reactors are being investigatedfor both CO2 capture and energy storage CaL applicationsin (LEILAC EU project, 2016) and (Socratces Project,2018) projects, respectively.
Rotary kilns have been also proposed for CO2 capture
as pilot-scale prototypes (Chang et al., 2013; Wang et al.,2010) (Fig. 4). In addition to the maturity and scalabilityof this technology, efficient heat-mass transfer andCarlos Ortiz et al. / KONA Powder and Particle Journal No. 38 (2021) 189–208

Fig. 4 Calciner based on a rotary kiln for post-combustion CO2 capture. This configuration takes advantage of synergies with the cement industry.
Reprinted with permission from Ref. (Wang et al., 2010). Copyright: (2010) American Chemical Society.

gas-solids contact are key advantages of rotary kilns.
Moreover, the solids residence time can be accurately
controlled by adjusting the kiln rotation speed (Abanades
and André, 2018), which is critical to achieve efficient calcination in the face of unforeseen changes in reactor conditions, mainly temperature variations. Thus, an increaseof reactor temperature (with unwanted effects such as
promoting sintering) could be counterbalanced by increasing the amount of solids and/or reducing the solids
residence time. As in the case of entrained-flow reactors,
rotary kilns could be properly operated even for fine particles (Moumin et al., 2019).

4.1.1 Solar calcination
Solar calcination has attracted the attention of esearchers since the early 1980s (Badie et al., 1980; Flamant etal., 1980). Using concentrated solar power to carry out thecalcination reaction would allow: i) to store solar energy
by means of the CSP-CaL scheme (Chacartegui et al.,2016); ii) to reduce non-renewable fuel consumption in
CO2 capture applications with added technical, economicand environmental advantages (Tregambi et al., 2015) andiii) to reduce the high energy consumption associatedwith the endothermic reaction in industrial processes (i.e.
cement industry) (Flamant et al., 2018). Despite the huge
potential of solar calcination, solar particle receivers still
remain on the small demonstration scale (Moumin et al.,2019).
The main candidates such as solar calciners proposed
are based on diverse technologies such as falling particle
receivers (Ho, 2016), centrifugal reactors (Abanades andAndré, 2018) and fluidized bed receivers (Flamant et al.,1980). In general, solar particle receivers can be classified
by the way particles are irradiated, either directly or indirectly. In the latter case, heated tubes or other receptors

are used. A proper selection of the solar particle receiver
to be used for carrying out the calcination of CaCO3­particles is dependent on a multitude of factors, mainly
related to the reaction conditions (temperature, atmosphere composition, particle size) that determine the residence time required to achieve full decomposition. Solarreceiver characteristics (thermal emittance, solar absorptance, etc.) and thermal properties of the CaCO3 and CaO
particles entering the solar calciner also play a relevantrole. CaCO3 has a poor solar absorptance (Flamant et al.,1980). Thus, indirect heating would be preferred for­calcination (Ho, 2016). Since carbonation of CaO in the
carbonator reactor would not occur completely, a mixtureof CaCO3 and CaO solids would enter the solar calciner.
CSP with tower technology is the most suitable system for
integrating a solar-calciner because of the high temperature needed in the reactor close to the turning temperatureof the calcination/carbonation reaction.
 Falling particle receivers
Falling particle receivers are based on the direct heating of particles that fall while being irradiated by a beamof concentrated solar energy flux. According to Ho, 2016,
the most interesting features of falling particle receivers
are: i) unlimited maximum solar irradiance (> 2000 kW/m 2); ii) maximum temperature > 1000 °C; iii) thermal­efficiency between 50–90 %, and estimated cost of about
125 $/kWt, which could be lower than molten salt receivers cost (Ho, 2016; Mancini et al., 2011). On the other
hand, particle attrition is a critical issue that can be promoted in falling particle receivers. This technology seems
to be scalable to 10–100 MWe power tower systems (Ho,
2016).
Several previous works have analyzed the main characteristics of falling particle solar receivers. Siegel et al.

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developed a 2-MWt on-sun test of a falling particle­receiver. The performance model indicated that an
80 W/cm2 average flux will be required to achieve 900 °C
given an inlet temperature of 600 °C (Siegel et al., 2010).
When the particle mass flow is increased, the output­temperature is decreased, albeit thermal efficiency is improved. A possibility to increase the particles’ residence
time is to recirculate the hot particles into the curtain(Christian and Ho, 2013; Ho et al., 2013). Another possible
strategy to raise the particles’ outlet temperature is to­hinder the flow of falling particles by using chevron-likemeshes (Mehos et al., 2017). Ho et al. (Ho et al., 2016)
studied the performance of a 1-MWth high-temperature
falling particle receiver in an on-sun test with continuous
recirculation. Ceramic particles (with notably higher absorptance than CaCO3) were used in the test. The peak
particle temperatures reached were over 700 °C with athermal efficiency of ~65 % (Ho, 2016).
Falling particles receivers have a promising future because of their scalability potential, good performanceand lower complexity than other solar particle receivers.
However, pilot-scale experiments using CaCO3 particles
are still being performed to properly evaluate the potential of these receivers for the CSP-CaL integration.
 Centrifugal particle receivers
Since rotary kilns are currently used to carry out calcination on a very large scale, this technology is especiallyinteresting for the CSP-CaL integration. Nevertheless, for
its use as a solar receiver, the rotary kiln must be properly
adapted to enable heating by concentrated solar irradiation.
The main advantages of rotary kilns for solar calcination are (Abanades and André, 2018): i) adjustable residence time of particles by controlling the tube rotational
speed and tilting angle; ii) high temperatures achievablein the cavity; iii) solids conversion in continuous mode
and in a controlled atmosphere; iv) uniform radial heating; v) good heat transfer thanks to the direct contact of
the rotating particle bed with the hot tube walls; vi) possibility of operation in co-current or counter-current
flow, which allows solids preheating by the exhaust gas.
A calciner based on a solar rotary kiln technology was
proposed as early as 1980 by Flamant, Badie et al. (Badieet al., 1980; Flamant et al., 1980). The reactor is almost
horizontal, with an inclination of 5° to facilitate particle
transport. These works highlighted the relevance of theradiative properties of the solar reactor. A thermal efficiency of 0.1–0.3 was achieved with a maximum calcination conversion of 0.6 by using a 2-kWt solar furnace
reactor with a total absorptance of about 0.9–1 due to thecavity effect. Excellent transfer coefficients between the
bed and the internal wall were reported. Meier et al. developed two 10-kWth solar reactors to investigate solar

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Fig. 5 Conceptual schematic of an FB solar receiver with beam down
technology. The concept was presented in Chirone et al., 2013.

calcination. One of them was directly irradiated (Meier etal., 2004) while the other one was irradiated indirectly(Meier et al., 2005). Maximum conversion efficiencies of
20 % and 38 % were achieved for directly and indirectly
heated solar reactors, respectively, with a solar flux input
of 2000 kW/m2. For the directly irradiated reactor, thetypical efficiency obtained in several tests reached 13 %while the maximum efficiency was about 20 % (Meier etal., 2004).
An indirectly heated reactor design seems especiallyinteresting for the CSP-CaL integration since CO2 emissions are avoided. The indirectly heated reactor proposedby Meier at al. (Meier et al., 2005) consists of a tilted cylindrical steel drum with ceramic insulation. In this case,an adequate gas conveying system is needed to ensure
proper gas circulation across the receiver. Typical reactor
overall efficiencies vary between 25.2 and 34.8 %, depending on the rotational speed (8–18 rpm), mass flowrate (2–8 kg/h), and particle size (2–3 mm) (Meier et al.,2005).
Main reactor energy losses are caused by re-radiation(13.6 %), conduction (20.5 %), and sensible heat of the
products (20.2 %), whereas the remaining losses (14.2 %)are mainly due to loss of material and convection heatlosses. In this case, an improved reactor design incorporating a recovery thermal energy system and minimizing
heat loss by convection and conduction would raise efficiencies up to 70 %.
 Fluidized bed receiver
Fluidized bed (FB) reactors display higher thermal­inertia than rotary kilns. Therefore, continuous operation
is improved in the former, as the thermal regime can be
maintained in the case of small fluctuations of solar radiation (Flamant et al., 1980). Both rotary kilns and FB reactors have the potential for rapid employment since thetechnologies on which they are based are already maturein the cement industry and FB-boiler manufacturing, re-Carlos Ortiz et al. / KONA Powder and Particle Journal No. 38 (2021) 189–208

spectively.
Flamant et al. (Badie et al., 1980; Flamant et al., 1980)
proposed an FB reactor to carry out the CaCO3 decomposition. The total absorptance of the fluidized bed depends on both the particle emittance and the bed physicalproperties (porosity, particle size, fluidization regime)(Flamant et al., 1980). Salatino et al. (Salatino et al., 2016)
analyzed the thermal performance of a bubbling fluidized
bed of sand particles to store energy from CSP in a sensible form. To evaluate the hydrodynamics of the process,a near-2D f luidized bed prototype was constructed(­Migliozzi et al., 2017). The use of compartmented dense
gas f luidized beds was proposed by Chirone et al.
(­Chirone et al., 2013) (Fig. 5). These compartments are:i) the receiver, located around the cavity through which
concentrated solar rays enter by means of a beam-down
technology; ii) the heat exchanger section, where the­sensible heat of solids is released to a steam cycle; andiii) storage. Dynamic simulation results showed an overall thermal efficiency of up to 71 %. This study set thebases for the construction of a 100-kWt solar FB prototype within the SOLTESS project (Chirone et al., 2013).
A SOLTESS pilot-scale plant could be suitable to attainthe calcination of limestone, since the achievable temperatures reached 900 °C. Using CaCO3 instead of sand,or a mixture of both, would allow storing energy in bothsensible and thermochemical form as proposed in
Valverde, 2015.
Summarizing, in addition to particle size effects, theexistence of thermal gradients and the uncontrollability of
the flux profile across the reactor are important challenges
to be solved in both solar and non-solar calciners. In particular, solar calcination has specific issues to scale upsuch as: i) transfer losses in the high-temperature solar receiver, particularly re-radiation losses; ii) heat transfer toparticles by radiation and iii) problems derived from thermomechanical stresses imposed on the solar receiver.

4.2 Carbonator
A proper design of the carbonator reactor is critical toensure an adequate reaction between CaO and CO2, either
to release the stored energy in TCES schemes or to capture CO2 from the flue gas in non-renewable power plants.
Unlike calcination, carbonation does not occur completely
in the required short residence. Typically, limestone-­derived CaO conversion reaches a residual value after a
few cycles below 0.1 at conditions for CO2 capture(Abanades, 2002). Remarkably, CaO conversion is highly
dependent on the reaction conditions (Benitez-Guerrero
et al., 2017b) and the particles’ residence time in the carbonator (Perejón et al., 2016a). This shows the importanceof a correct sizing of the carbonator so that the particles
can react appropriately during a certain time of residence,

Fig. 6 Conceptual schematic of a continuous CFB carbonator reactor.
Reprinted with permission from Ref. (Charitos et al., 2011). Copyright:(2011) American Chemical ­Society.

which will enhance the efficiency of the reaction (Ortiz
et al., 2015).
A large-scale carbonator must provide: i) enough residence time of the particles to reach the target temperature and allow for a satisfactory carbonation conversion;ii) small thermal gradients and non-homogeneous conversion; iii) homogeneous heat transfer to the reactor’s wall;iv) small temperature differences between solids ­entering
the reactor and the carbonator temperature to avoid reactor cooling and the consequent reaction stop, and v) low
level of particle attrition and agglomeration.
Similarly to the calciner, most of the carbonators­proposed are based on FB reactors (Hanak et al., 2015).
Fig. 6 shows a schematic of a typical CFB carbonator­reactor. High carbonation efficiencies (~90 %) (Romano,2012) are achieved due to the good mass and heat transfer
coefficients achieved using fluidization. High-intensity
acoustic fields could improve the carbonation efficiency(Valverde et al., 2013), allowing even fluidization of cohesive particles. This issue is analyzed, together with otherassisting methods for fluidization in Raganati et al., 2018.
Nevertheless, fluidization-assisting techniques for improving fluidization and carbonator efficiency have beentested on a lab scale. Additional effort is required to bringthese options to large-scale FB reactors. The carbonator

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on a large scale for post-combustion CO2 capture is characterized by a large size (volume ~18 m3/MWe; solids­inventory ~1300 kg/MWe (Romano, 2012)). In contrast,
in a 100-MWth CSP-CaL plant, the carbonator size could
be significantly reduced (128–234 kg/MWe) (Ortiz et al.,2018b) because of the enhanced kinetics and the higher
multicycle CaO conversion at conditions for energy storage (Benitez-Guerrero et al., 2017a; Kyaw et al., 1998).
The use of entrained flow reactors has already been developed for carbonation on a pilot scale. This type of reactor is employed in the cracking industry (Chuachuensuk
et al., 2013) with the possibility of handling fine particles
that are difficult to fluidize in FB reactors. In the CSPCaL integration, the use of fine particles would serve toachieve a notably higher CaO conversion under TCES
typical conditions (high CO2 partial pressure and hightemperature at the carbonator) (Benitez-Guerrero et al.,2017a). In these conditions, carbonation is mainly limited
by pore plugging, which hinders the multicycle conversion of CaO particles larger than about 50 μm (Benitez-­
Guerrero et al., 2017a). Moreover, an entrained flow
carbonator could be more favorably integrated in cement
plants due to the typical small size of particles used in the
production of cement (Plou et al., 2019). CO2 capture efficiencies obtained in a kW-scale prototype are over 90 %for a Ca/CO2 molar ratio of 5 and solids residence times
just lower than 5 s (Plou et al., 2019). On the other hand,
the heat transfer coefficient in the entrained flow reactor
would be in the range of 100–200 W/m2K (Ma and Zhu,
1999), which is remarkably low compared to FB reactors(500–800 W/m 2K) (Li et al., 2016; Zhang and Koksal,
2006). Therefore the heat transfer between the cloud ofgas and particles and the reactor wall has a critical relevance in this type of reactor that must be optimized. The
heat transfer rate in the downer is closely related to thesystem hydrodynamics, the solids suspension density being the most influential factor (Ma and Zhu, 1999). Axial
distribution of the average heat transfer coefficient ofaround 150 W/m2K was found in (Ma and Zhu, 1999).
The higher the solids hold-up, the higher the heat transfer
coefficient.
In a recently published work (Turrado et al., 2018), thecarbonation was tested in a 6-m-long and 0.1-m-diameter
downer reactor for CO2 capture, where particles are injected at the top of the carbonator and move downwards
together with the gas. Considering just 3 seconds for thesolids residence time, the carbonation degree was around0.06 under a 15 %v/v CO2 atmosphere (typical concentration for post-combustion CO2 capture). The authors foundthat the higher the CO2 concentration, the higher the reaction rate, which is a relevant observation for CSP-CaL integration according to the proposed configuration in Ortiz
et al., 2018b, where carbonation takes place under a pure
CO2 atmosphere. Researchers at the University of Ohio

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tested a 120-kWth pilot plant in which the carbonator
was an entrained bed operated at 450–650 °C (Wang etal., 2010). A test campaign was performed to assess thesimultaneous capture of CO2/SO2 released by fuel combustion. The gas entering the reactor was preheated to thecarbonator temperature by means of auxiliary heaters.
Results showed almost 100 % CO2 capture levels (Ca:Cmole ratio of 1.6) by using particles of mass median diameter (D50) of 3 μm. The capture efficiency was decreasedusing larger particles due to the lower reactivity (particlesof sizes in the range 3–600 μm were tested). As expected,
the higher the particle residence time, the higher the conversion. A similar carbonator configuration was tested at
Cranfield University (Hanak et al., 2015). They also foundthat carbonation was enhanced as the particle size wasdecreased, which was attributed to the increase of thesurface-to-volume ratio.
De Castilho and Cremasco compared the performanceof downer and riser reactors (De Castilho and Cremasco,2012). Downer reactors present a more uniform flow inboth radial and axial profiles. At the entrance of thedowner, the flow is less complex and more predictable inthe center next to the solids feed (De Castilho and­Cremasco, 2012). Particle velocities are higher in downerreactors and are more diluted (Bolkan et al., 2003), which
has to be carefully assessed in the carbonator design. A
1D model of an entrained flow carbonator was proposedin Spinelli et al., 2018, and is currently being developedon a pilot scale within the SOCRATCES project (Socratces Project, 2018) to analyze the reactor behavior in the
CSP-CaL integration.
Typically, carbonation reactors are tested/simulated atambient pressure for post-combustion CO2 capture (Deanet al., 2011). On the other hand, carbonation under pressure (3–5 bar) would improve the thermochemical energy
storage efficiency by the direct integration with a CO2
Brayton cycle (Chacartegui et al., 2016; Ortiz et al.,2017a).

4.3 Power cycle
The high enthalpy of the exothermic carbonation reaction and the high reaction temperature require optimizing
the energy integration to maximize the process efficiency.
In the carbonator, it is crucial to extract the carbonation
heat released not only for enhancing power production but
also for keeping the reactor at the desired temperature andavoiding its increase to the equilibrium temperature,
which would stop the reaction (Ortiz et al., 2018b).
As usual in power block technology, the power cycle to
be integrated with the CaL process should be characterized by: i) a high efficiency (~45 %), taking advantage ofthe high temperature heat source (650–1000 °C depending
on both the CO2 partial pressure and the absolute pressure

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in the reactor) (Alovisio et al., 2017); ii) the use of turbomachinery available on a commercial scale; iii) the integration of high-efficiency heat exchangers (even forsolids-based configurations) to take advantage of the heatreleased during the CaL process; iv) minimum coolingand heating consumption from utilities, and v) water consumption for cooling to be as low as possible. Air coolingwould be preferred in CSP-CaL integration.
A Rankine power cycle has been proven to be especially suitable for CaL-based CO2 capture to take advantage of the heat released during carbonation (Perejón etal., 2016b). Rankine cycle technology is well known as itis the basic technology for both renewable and nonrenewable power production, which minimizes implementation risks. Moreover, the current Rankine cycle
state of the art shares some synergies with the carbonator
reactor. High efficiencies were reached by integrating a
supercritical steam Rankine cycle (Stein and Buck, 2017),
which is currently commercially used in fossil-based
plants with capacities higher than 400 MWe. Several
process schemes have been proposed to analyze the potential of integrating a Rankine cycle into the carbonator(Hanak and Manovic, 2017b; Martínez et al., 2011; Ortiz
et al., 2016a; Romano et al., 2012; Romano, 2013).
A supercritical steam cycle integrated into the CaL
process was proposed in Romeo et al., 2008, which
achieved a thermal-to-electric efficiency as high as 40.4 %with a reduced energy penalty (4.5 %). A detailed pinch
analysis on the retrofitting of a supercritical steam coal
power plant was presented in Romeo et al., 2010. Recently, a supercritical CO2 Brayton cycle was proposed to
be integrated for the decarbonization of coal-fired power
plants (Hanak and Manovic, 2016). It was possible to reduce the proposed supercritical CO2 cycle by 1 % pointsof the energy penalty of the CO2 capture process compared to the supercritical Rankine cycle-based-plants(Hanak and Manovic, 2016), although it must be taken
into account that supercritical CO2 technology has not yet
reached commercial maturity.
In contrast with integrating the CaL process in nonrenewable power plants, in which the steam power cycle
technology proposed is the same as in non-retrofitted
plants, the integration of the CaL process in CSP plants
as a TCES system could be compatible with a substantialchange in the power cycle. Most of the commercial CSP
plants are based on a sub-critical Rankine cycle process(Siva Reddy et al., 2013). Typical live steam operation
conditions are (T < 540 °C; 100 bar) (NREL, 2017). This
usually involves a cycle efficiency lower than 38 %(NREL, 2017), leading to an annual solar-to-electricity
conversion efficiency in the overall plant below 20 %(Yogi Goswami, 1998). The power cycle efficiency can beenhanced by integrating high-temperature (> 650 °C)
Brayton cycles, which requires higher heat temperaturesin the thermodynamic cycle (Stein and Buck, 2017). In thecase of the CSP-CaL process scheme, the most efficientconfiguration is by directly integrating a CO2 closed cycle(Alovisio et al., 2017; Ortiz et al., 2017a). The CO2 entering the carbonator in this case should be well above thestochiometric needs in such a way that the excess CO2 exiting the carbonator passes directly by a gas turbine forpower production. Thus, the heat of the carbonation reaction is directly delivered to the power cycle (gas turbine)by using CO2 as HTF. According to Chacartegui et al.,2016, the optimum pressure ratio (carbonator to outlet
turbine pressures) is around 3.2 bar by considering a carbonator temperature of 875 °C, which leads to plant efficiencies above 45 % (without considering solar receiverlosses). Other potential power cycles were analyzed (Ortiz
et al., 2017a), including direct and indirect integration of
Rankine cycles, supercritical CO2 cycles and combined
cycles.

4.4 Solids storage
Material storage is a key element for the CaL process
as a TCES. Previously proposed CSP-CaL integrations
include at least three storage vessels for the streams coming from the calciner (CaO and CO2 vessels) and for the
admixture of solids (CaCO3 and unreacted CaO) exiting
the carbonator (Fig. 3). Moreover, the use of solids­storage tanks in the CaL process integrated as a
post-combustion CO2 capture system could improve theplant efficiency and reduce CO2 emissions by adapting the
CaL operation to the power plant demand (Astolfi et al.,2019; Criado et al., 2017).
A proper sizing of the storage vessels plays a fundamental role in the CaL integration as a TCES system. A
guideline about storage sizing can be found in Bayon etal., 2018. Depending on the energy release criterion, theplant can be configured as a peaker (< 6 h of storage), intermediate or baseload plant. Despite the fact that longterm energy storage is a key advantage of TCES systems(Pardo et al., 2014), it was possible to operate the energy
storage at high temperatures (Ortiz et al., 2018a) with asimilar solar multiple as in current molten salts-based
power plants (Casati et al., 2015). High-temperature­storage simplifies the CSP-CaL process scheme. Smaller
storage tanks than in molten salts plants are expected
due to the higher energy storage density in the CaL process. Regarding CO2 storage, the preferred option is tostore it at high pressure (up to 75 bar) in order to guarantee liquid CO2 storage conditions (considering storage at
ambient temperature), and therefore reducing the storage
volume (Chacartegui et al., 2016). Recently, it has been
proposed to store the CO2 at atmospheric pressure (thusavoiding CO2 compression and therefore increasing theprocess efficiency) in huge vinyl buildings (Muto and199

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Hansen, 2019).
On a large scale, the storage system should accomplish
the following characteristics: i) storage size as small as
possible (to reduce costs) while ensuring sufficient storage
to meet the operating plant criteria; ii) proper filling reg­ulation and safety operation of the CO2 gas vessel; iii)
minimum cooling consumption from utilities; iv) ensure
an adequate atmosphere inside the CaO storage tank to
avoid carbonation, which would reduce the energy released to the power cycle; v) high-temperature solids­handling devices and lock hoppers if needed.
From a techno-economic perspective, the system musthave the highest energy density possible, which allows
maximizing storage capacity. In this regard, it is important to address the size of the vessels needed for solids
storage, which determines capital costs. To this end, a­recent work (Ortiz et al., 2018a) proposed an equation toestimate the energy density of the system considering theparticles’ porosity and their packing density, processcharacteristics (pressure and temperature in the reactors
and storage vessels) and conversion efficiency.
Most important factors for the solids storage vessel are:
● Capacity: to cover the expected dispatchability of theplant.
● Discharge rate: the storage vessels must deliver the­material to a downstream process (calcination/carbonation) at a required rate.
● Solids cohesiveness: prolonged contact between thestored particles under consolidation stresses possibly athigh temperature and in the presence of moisture,
which enhances interparticle attractive forces (Durán-­
Olivencia et al., 2020; Valverde, 2013b). Moisture migration, aging and recrystallization may lead todramatic gains in cohesive strength, agglomeration ofsmaller particles into larger ones, or caking (Prescottand Barnum, 2000). External forces such as vibrations
induced during transportation, expansion and contraction resulting from temperature changes can also significantly enhance consolidation. As a result, an increaseof the solids cohesiveness can hinder discharge fromthe container due to arching or ratholing.
● Attrition: the porous CaO formed upon calcination results in a friable solid (Blamey et al., 2010). Attrition ofparticles must be properly addressed.
● Safety and environmental concerns: determine explosion or burning risks and adopt adequate explosion/
fire-protection measures. Determine whether contaminants, atmospheric gases, humidity, and temperature
can adversely affect the material stored.

4.5 Solids conveying and separation
Solids conveying results are crucial for the CaL process
feasibility due to the large amount of solids, in some cases

200

Fig. 7 OLDS elevator schematic (OLDS elevator, 2019). Copyright:(2019) Olds ElevatorTM.

at very high temperature and under reactive (CO2) atmosphere, that must be moved in a large-scale plant. CaO
particle transportation from the calciner to the storagetank and then to the carbonator is a key issue. Carbonation of the particles must be avoided outside the carbonator which requires a controlled atmosphere in bothconveying systems and storage tanks. A solution is to­replace the CO2-rich atmosphere at the calciner exit by anitrogen atmosphere (system inertization), allowing to­reduce the temperature for storage without carbonation.
On a large scale, the solids and gas handling devices
must: i) be effective, continuous and reliable, and ii) avoid
particle segregation by size. Particles tend to congregate
towards the middle, while larger ones fall to the outside(Maynard, 2013; Mehos and Maynard, 2009). Anotherkey requisite is ensuring a low energy consumption. Typical values of consumed energy for the CaL process canbe estimated in the range of 3–5 MJ/ton each 100 m(Mills, 2003).
Available technologies to transport high-temperature
particles up and down the receiver include mine hoists,bucket elevators, pocket elevators, screw conveyors,
pneumatic conveyors, conveyor belts, cleated conveyor
belts, metallic belted conveyors, masses elevators, bucket
wheels, linear induction-motor-powered elevators andCarlos Ortiz et al. / KONA Powder and Particle Journal No. 38 (2021) 189–208

electromagnetic field conveyors (Ho et al., 2013). An
OLDS elevator (Fig. 7) is a vertical screw conveyor which
seems suitable to be integrated in the CaL process forhigh-temperature solids elevation, especially if the calciner is located at the top of a solar tower receiver.
Mechanical systems normally have a higher investment
cost but a much lower operating cost than pneumatictransport systems (Schorcht et al., 2013). Pneumatic conveying is a well-known technology used in many applications such as the cement and lime industry (Mills, 2003).
Therefore, it could expect to be feasible for the CaL process, even if fine particles are employed.
Belt conveyors are cost-effective only when there is arelatively high production rate and the transport distanceis long (De La Vergne and Mcintosh, 2000). Many typesof feeders exist for belt conveyors, but the most common
is the vibrating feeder. Screw feeders have been proposed
for the CaL process (European Commission, 2016; Hilz etal., 2017; Zhao et al., 2013), with particles size as small as~30 μm. One of the key parameters to calculate the volumetric characteristic curve of the screw conveyor is the
trajectory angle of particle motion, which affects the filling rate and the theoretical maximum mass flow rate.
Several correlations, validated against commercial screw
conveyors, predict the fill rate as a function of the rotation
velocities and pitches, as well as the outlet mass flow rate
as a function of the inclination angles, rotation velocities
and pitches (Li et al., 2018).
Solids feeders (hoppers) are critical when using fines
due to agglomeration (Turrado et al., 2018). Typical problems with solids hoppers when using cohesive particles
are arching or ratholing (Maynard, 2013; Mehos andMaynard, 2009). These effects might give rise to thepulsed inputs of solids (erratic flow) instead of stableflows. According to Turrado et al., 2018, 50 μm is theminimum size of the particles that allows a continuousand controlled flow of solids to be fed into the drop-tube
reactor. An option to improve the feeder performance
could be to introduce a fluidizing gas at the bottom of thehoppers to ensure mass flow operation by avoiding core
flow. Rotary airlocks are important for a dilute-phase system. They enable solids to be fed at a controlled rate into
the gas stream (Mehos and Maynard, 2009). This system
could be used in the calciner and carbonator to bring into
contact both streams (gas and solid particles).
Since gas and solids are stored separately, a separation
system must be considered in the plant. At the outlet ofthe calciner and carbonator, cyclone separators could be
used as primary separation devices for relatively coarse
particles, with a fabric filter downstream (depending on
the particle temperature) in order to remove fine particles(< 20 μm) from the CO2 flow.

4.6 Heat exchangers
An efficient use of the heat from the different hot
streams is critical for the process efficiency. In the case of
the hot CO2 stream exiting the calciner, a gas-gas heat exchanger as a heat recovery steam generator (HRGS)
within a secondary steam cycle could be employed, which
would generate enough power to carry out CO2 compression (Ortiz et al., 2018a). Another possibility is to use­solids-gas heat exchangers to release energy from the hot
CO2 stream for preheating the CaCO3 particles entering
the calciner (Chacartegui et al., 2016).
Suspension preheaters are well-known technology inthe cement industry as gas-solids heat exchangers. The
exhaust gases from the calciner flow through the cyclone
stages from bottom to top. Particles are added to the exhaust gas just before the uppermost cyclone stage. They
are separated from the gas in the cyclones and re-join it
before the next cyclone stage (Schorcht et al., 2013). By
using this solids-gas heat exchanger, the same exit temperature of the gas and solids streams is achieved from a
co-flow arrangement with a considerably high contact
surface. Suspension preheaters usually have between fourand six cyclone stages, which are arranged one above theother in a 50–120-m-high tower (Schorcht et al., 2013).
Due to high level of maturity of this technology, it seems
an optimum choice to carry out both CaCO3 particle preheating in the calciner side and particle cooling in the
carbonator side.
The grate preheater is another well-known technique inthe cement industry. Particles are fed onto a horizontal
grate which travels through a closed tunnel. A fan draws
the exhaust gas from the calciner into the top of the preheater. The temperature of the gas could be reduced from> 1000 °C to 150 °C while solids would be heated up to
700–800 °C (Schorcht et al., 2013). Another possible
solids-­gas direct heat exchanger was proposed by ­Shimizu
et al. (Shimizu et al., 2004). This heat exchanger is an­axial flow cyclone in which a quasi-counterflow heat­exchange is realized to recover the heat carried by theparticles. By using this design, an outlet gas temperaturemuch higher than the particle outlet temperature could be
attained. Fluidized bed designs are also a possibility toperform solids-gas heating with high heat transfer coefficients (up to ~600 W/m 2-K), but have a higher parasitic
power consumption and heat losses associated to fluidization (Ho et al., 2017).
Several solids-solids heat exchangers have been proposed to transfer heat between the CaO solids stream exiting the calciner and the CaCO3/CaO mixture comingfrom the carbonator, such as a cyclonic preheater(Martínez et al., 2013) or a mixing seal valve (Martínez etal., 2014). To avoid recarbonation of CaO during the cooling process, which notably affects the multicyclic conver-

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sion (Valverde et al., 2014), an indirect contact solids–
solids heat exchanger with one intermediate heat transfer
fluid recirculated within the bulk of both solids could be
employed, although this equipment is not fully developed
yet on a large commercial scale.

5. Next steps and remarks
The CaL process plays a central role in the next-­
generation post-combustion CO2 capture technologies.
The main improvements are related to enhance the multicyclic CaO conversion, ensure proper solids handling andefficiently recover the high-temperature heat released
during the process. As shown in sections 2–3, important
advances have been accomplished and the technology has
already been demonstrated on the MWt scale. No major
technical barriers have been found for its employment on
a commercial scale. Retrofitting coal-fired power plants
with the CaL process is considered a viable and competitivetechnology (Abanades et al., 2015). Next research projects
must aim at reaching a Technology Readiness Level(TRL) of 7–8, which implies a commercial demonstration
at full scale (IEA, 2014).
The CaL process for energy storage lies at a lower levelof maturity. Despite important advances to properly define and test the integration of the CaL process in CSP
plants (sections 2–3), the solar calciner (particle receiver)remains as a major technological challenge. Current projects aim to reduce the technological risks progressing
from a TRL-4 (technology validated in lab) to a TRL-5
level (technology validated in a relevant environment)(Flamant et al., 2018; Socratces Project, 2018). The hugeinterest for increasing dispatchability in CSP plants, thehigh technology development of the CaL process for CO2
capture as well as the important efforts for developing solar particle receivers (Ho et al., 2017) should contribute toaccelerating the employment of CSP-CaL integration on acommercial scale.

Acknowledgements
The research leading to these results has received funding from the European Union’s Horizon 2020 researchand innovation programme under grant agreement No
727348, project SOCRATCES and by the Spanish Government Agency Ministerio de Economía y Competitividad (MINECO-FEDER funds) under contracts CTQ201783602-C2 (-1-R and -2-R).

202

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Authors’ Short Biographies
Carlos Ortiz
Assistant Professor at Universidad Loyola Andalucia. PhD in energy engineering(2018). His research activity is focused on the CaL process for both CO2 capture andthermochemical energy storage applications. It comprises energetic and chemicals systems modelling. He has published over 25 papers mostly in Q1 journals with more than
600 citations.

José Manuel Valverde
Professor of electromagnetism and materials engineering. PhD in physics (1997). His
research activity has been focused on the study of fluidization and the mechanical properties of granular materials. A main subject of current interest is development of novel
techniques to enhance the CO2 capture efficiency of CaO-based materials by means of
the Ca-looping technology based on carbonation/calcination of natural limestone in fluidized
beds. He has published over 100 papers mostly in Q1 journals with over 1000 citations.
Ricardo Chacartegui
Professor of the Energy Engineering Department of the University of Seville. PhD inenergy engineering. His research is focused on thermal energy systems: design, development, and optimization. It comprises the analysis of novel cycle concepts and thermal
systems (supercritical CO2 cycle, HAT cycle, high-temperature fuel cell hybrid systems,
organic Rankine cycles, Stirling engines) combined with the improvement of existing
technologies (boilers, thermosolar, gas turbines, combined cycles, compressors) and systems development. He has an intense R&D activity with more than 40 papers publishedin Q1 and Q2 peer review journals since 2006 and more than 60 papers in international
congresses.
Luis A. Pérez-Maqueda
Senior scientist in the Institute of Materials Science of Seville, a joint research center
belonging to the Spanish National Bureau of Science and to the University of Seville.
His research is focused on the field of reactivity of solids. He is interested in solids-solids
and solids-gas reactions of interest in fields such as materials science, energy and environment. He has published about 190 scientific papers in international journals.

Pablo Gímenez-Gavarrell
Industrial and biomedical engineer (Polytechnic University of Valencia) and PhD on
thermal energy storage (University of Seville), with 4 years of experience in CSP. He
currently works at the University of Seville (PSI) teaching heat transfer and thermal engineering.

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Original Research Paper

Modulated Uniaxial Compression Analysis of Respirable
Pharmaceutical Powders †David Barona 1, Abouzar Shamsaddini 1, Maximilian Aisenstat 1, Kyrre Thalberg 2,
David Lechuga-Ballesteros 3, Behzad Damadzadeh 3 and Reinhard Vehring 1*
1 Department of Mechanical Engineering, University of Alberta, Canada

2 Inhalation Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca AB, Sweden
3 Inhalation Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca PLC, USA

Abstract
We describe a new instrument and method for measuring compressed bulk density of respirable pharmaceuticalpowders under low compression pressure: the modulated compression tester. The instrument modulates
compression and decompression steps, allowing scrutiny of the overall compression response of samples. Comparedto established methods for the determination of density and related parameters for pharmaceutical powders, this
instrument has the capability of measuring smaller samples. The relative humidity can also be controlled in the
instrument (3 % to 95 % RH), allowing assessment of the effect of moisture on compression response. We have used
the instrument to determine the compressed bulk density of Trehalose, Leucine, Trileucine, and Mannitol powdersof varying crystalline and amorphous compositions and particle size and size distribution, demonstrating that the
new modulated compression tester is suitable for low pressure (< 1200 kPa) density measurement of respirable
powders (< 10 μm) and expensive active pharmaceutical ingredients available in limited quantities (typical sample
mass requirement of < 100 mg). In addition, the modulation feature of the instrument allows the analysis of thetransition from plastic to semi-elastic compression response. The outputs and features of this instrument are usefulfor formulation development, quality control measurements, discerning between different or similar powders due
to differences in the compression response, and optimizing powder compression parameters for pharmaceuticalapplications.
Keywords: compressed bulk density, respirable powders, powder compression, powder elasticity, dry powder
inhalers

1. Introduction
Evaluation of the compression response of fine andrespirable pharmaceutical powders is of prime importancebecause of the implications it has on formulation development, manufacturing and quality of the final product.
Adequate characterization of the bulk powder properties
is needed through the entire product development lifecycle(de Boer et al., 2017; Sørensen et al., 2005). For solid dosage forms, knowledge of the particle density and powderbulk density are necessary for assessing the aerodynamic
properties (Feng et al., 2011), dispersibility (Boraey et al.,2013; Weiler et al., 2010) and parameters that influence
powder filling processes, such as flowability (Faulhammer†

Received 30 May 2020; Accepted 8 July 2020
J-STAGE Advance published online 29 August 2020
* Correspopnding author: Reinhard Vehring;
Add: 116 Street and 85 Avenue, Edmonton, Alberta, Canada, T6G
2G8
E-mail: reinhard.vehring@ualberta.ca
TEL: +1-780-492-5180 FAX: +1-780-492-2200

et al., 2014; Osorio and Muzzio, 2013). In order to assess
the quality of a final product, the properties of powdered
excipients and active ingredients must be precisely andaccurately characterized. It is therefore important tocharacterize the bulk density and compression responseof powders for manufacturing and quality control of final
pharmaceutical products.
Providing an unambiguous definition of powder density
is not straightforward because of the presence of voids
within particles and between neighboring particles in a
powder. This fact gives rise to a family of density definitions for pharmaceutical powders: true density, particle
density, bulk density and tapped density, among others.
The true density of a solid object excludes internal andexternal voids that are not a fundamental part of themolecular packing; thus, true density can be measured
reproducibly because it does not include pore volume inits determination (Brockhaus and Carlozzo, 1995). Particle
density is the ratio of the particle mass over the volume ofthe particle with external and internal voids, also known as
the hydrodynamic volume (Vehring, 2008). Bulk density is

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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the mass of the powder in a column divided by its volume,
where its volume is the hydrodynamic volume of the particle plus interstitial spaces between particles (USP, 2015).
Tapped density is obtained by mechanically tapping thepowder in a column at a specified frequency, duration andamplitude until no further volume change can be observed(USP, 2015).
Bulk density and tapped density are routinely usedin the pharmaceutical industry to characterize powders(Sørensen et al., 2005). However, bulk density of a powder
sample depends on how the sample was handled (USP,
2015). For instance, disturbing the powder sample canresult in rearrangement of the particles and a change inthe bulk density. In contrast, the tapped density techniquedeliberately disturbs the powder bed to improve sample
packing so that more repeatable density measurements
can be made. However, an inaccurate reading of the volume from the measuring cylinder can introduce errors. In
addition, bulk and tapped density measurements usuallyrequire large amounts of powder, typically using tens ofgrams (Sørensen et al., 2005; USP, 2015). This becomesa major drawback if expensive, rare, limited-quantity ordifficult-to-make samples require analysis. Furthermore,bulk and tapped density techniques are better suited forlarge particles and where the interparticle forces are small
compared to inertial forces. This way, when the powder ishandled or tapped, the particles can easily rearrange, andthe powder can achieve a repeatable bulk density.
The compression response of fine and respirable powders, which have a mean particle size of less than 10 μm,
is dominated by interparticle forces (Sarkar et al., 2017;
Shamsaddini-Shahrbabak and Vehring, 2012). The interparticle forces influencing the bulk density of powders
are also the interactions that interfere with powder flow
(USP, 2015). Particle size and shape are also known to beimportant determinants of powder flow and compression
response (Adeoye and Alebiowu, 2014; Kaerger et al.,
2004; McKenna and McCafferty, 1982; Patel et al., 2007).
Assessing the compressibility of fine respirable powders
is uniquely challenging given the increased influence ofcohesive forces (Thalberg et al., 2004; Weiler et al., 2010)
relative to inertial forces (Desai et al., 2001). The cohesive
forces in fine powders may also be influenced by surface
characteristics (e.g. rugosity, contact area), intermolecularforces (e.g. Van der Waals interactions), electrostatics, material properties and environmental conditions, in addition
to particle size and shape (Baldelli and Vehring, 2016;
Sarkar et al., 2017; Weiler et al., 2010). As a result, whencompared to powders with larger particles, fine powders
are typically more cohesive and display relatively poor
flowability and dispersibility; thus, they are not well suitedfor bulk or tapped density measurements.
The cohesive nature of fine and respirable powders
likewise holds implications for powder handling during

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manufacturing as well as for delivery efficiency from inhalation devices (Elia et al., 2016; Rudén et al., 2018; Weiler
et al., 2010). Powder products that are meant for inhalation(e.g. dry powder inhalers) are compressed at low pressuresand packaged into capsules that require additional energy
upon use to disperse them for inhalation (de Boer et al.,2017; Faulhammer et al., 2014; Prime et al., 1997). In sucha case, it is important to use low compression pressureswhen packaging the powder product to achieve particle rearrangement, resulting in a loose powder compact. Utilizing low pressures when plastically compressing respirable
powders can also mitigate the deformation or fracturing of
the particles (Chen et al., 2017; Raut et al., 2016; Sørensen
et al., 2005; Vu et al., 2020), preserving the aerodynamic
properties of the particles, while minimizing the volume of
powder needed for each capsule. As a result, single-value
density measurements, such as bulk and tapped density,
are unsuitable for relatively cohesive respirable powders,so new methods are required for accurate and reproducible
Compressed Bulk Density (CBD) measurements.
For the overall compression response of fine powders tobe described, they must be actively compressed, taking into
consideration the entire compression curves and elasticityof the powders (Vu et al., 2020). Assuming there is no
moisture, a powder column is mostly a two-phase systemthat consists of air and particles. Generally speaking, whena powder is subjected to a compression force, it will go
through a series of either reversible or irreversible compression stages. The former occurs as a result of material
elasticity and the latter is due to plasticity of the powder(Chen et al., 2017; Vu et al., 2020). The first stage of thecompression process is seen as the displacement of thegaseous phase by the solid phase (powder packing andparticle rearrangement) within the bulk as a result of thecompression force, leading to the reduction of the bed
volume (Klevan et al., 2009; York, 1978). After this stage,
many air gaps between particles are filled, yet the particles
themselves have not fractured or deformed. Once the bed
has reached a sufficiently close packing, it starts showing
elastic response to the applied force. At higher compression
force, non-elastic materials or those elastic materials thathave yielded may show permanent, plastic deformation,and particle fracture and further packing become possible.
At very high pressures, the powder bed acts like a solidbody.
A powder’s compression response strongly depends on
the way that particles pack together. When powder is subjected to an axial force, this external force brings the particles closer to one another and causes the volume to reduce.
This stage may be referred to as the particle rearrangement
stage (Bolhuis et al., 1996; Tousey, 2002; Vu et al., 2020;
Yap et al., 2008). It is therefore possible, experimentally, todetermine the pressure at which the powder is compressedand starts showing significant reversible response; this isDavid Barona et al. / KONA Powder and Particle Journal No. 38 (2021) 209–225

the transition pressure from plastic to elastic deformation.
In general, CBD measurements are based on uniaxiallycompressing a powder sample and measuring its density
under a defined pressure. A number of studies involving
low-pressure compression of pharmaceutical powders havebeen reported (Faulhammer et al., 2014; Heda et al., 1999;
Kostelnik et al., 1968; Llusa et al., 2014; Nikolakakis etal., 1998; Podczeck and Lee-Amies, 1996; Sheikh-Salem
and Fell, 1981; Sørensen et al., 2005, 2006). A previous
report has also used a commercial compression instrumentthat can accommodate milligram powder quantities forbulk density measurements (Sørensen et al., 2005). Whilethese studies have demonstrated the use of low-pressurecompression for bulk density measurements and the useof small sample quantities, none has experimentally differentiated the compression response of respirable powders
between densification due primarily to particle rearrangement, i.e. plastic deformation, from densification due tosemi-elastic particle or powder deformation. The ability
to experimentally identify these compression responses
is only achievable at low pressures and is important forestablishing suitable compression pressures for packaging
or processing respirable powders. The instrument in thispaper is similar to the commercially available Geopyc
1360 (Micromeritics, Norcross, GA), which can only handle larger sample masses, as well as the Texture Analyzer(Stable Micro Systems, Surrey, UK), which is designed fora variety of uses, but is not specifically for density measurements of fine respirable powders and does not have RH
control capabilities.
We report here the development of a uniaxial low-pressure
and modulated compression instrument for CBD measurements of fine and respirable pharmaceutical powders. The

focus of this paper is to demonstrate the capabilities of the
new instrument and its ability to differentiate between very
similar respirable powders at low compression pressures.
We also show details of the modulation compression technique and introduce a new parameter for powder elasticity,which can be used to easily distinguish between plastic andsemi-elastic compression response.

2. Materials and methods
2.1 Materials
With the exception of crystalline Leucine (raw material), all powder samples used in this study were
produced by spray drying and contain particles withmass median aerodynamic diameters (MMAD) in the
respirable range (≤ 10 μm). D-(+)-trehalose dihydrate(177,613, Fisher Scientific Co., Ottawa, ON, Canada),
Trileucine (BCBP2254V, Sigma-Aldrich Corp., St. Louis,
MO, USA), L-Leucine (AC125121000, Acros Organics,
New Hampshire, NH), and D-mannitol (SLBH1429V,
Sigma-Aldrich Corp., St. Louis, MO, USA) are pharmaceutical excipients and were used to produce the powder
samples for this study. These excipients were chosen on
the basis of their different effects on particle formation,cohesiveness and mechanical properties (Vehring, 2008).
Most of these excipients were spray-dried by themselves
or in mixtures to produce the samples shown in Table 1
and to allow CBD measurements of different formulations,particle sizes and particle size distributions. Monodisperse
samples had a particle size distribution with a geometricstandard deviation (GSD) of 1.1 while polydisperse

Table 1 Materials and formulations used for compressed bulk density tests, including fully crystalline and fully amorphous materials, different particle sizes and different particle size distribution. The Mass column shows the range of masses needed for a measurement; the geometric standard deviation (GSD) and mass median aerodynamic diameter (MMAD) columns correspond to the size distributions of the spray dried powders (note that the
100 % Leucine sample was the raw material and was not spray dried); and ρt,mix corresponds to the calculated true density of each material or mixture.

#

Trehalose[% w/w]

1

Leucine[% w/w]

Trileucine[% w/w]

Mannitol[% w/w]

100

Mass [mg]GSD

78.7–79.5(rawmaterial)

58.9–59.3

1.6

2.5

1.53

MMAD
[μm]

ρt,mix[g/cm3]
1.29

2

100

3

99.6

0.4

86.4–91.7

1.1

9

1.53

4

99

1

103.9–110.2

1.1

9

1.52

5

95

5

72.8–77.3

1.1

9

1.50

6

80

20

63.2–68.5

1.6

2.5

1.48

7

75

25

40.0–42.6

1.6

2

1.47

8

75

25

38.2–40.3

1.6

4.5

1.47

9

55

45

34.6–37.4

1.6

3.6

1.42

10

100

68.3–69.7

1.1

10

1.51

11

100

64.4–65.7

1.6

3.5

1.51

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Fig. 1 SEM images of the materials and formulations tested and reported in this paper. The numbering of the images corresponds to the materials
and formulations listed in Table 1. For direct comparison, all images are at the same magnification and show a scale bar of 2 μm. An SEM image forsample #8 was not available; however, it was expected to have similar morphologies to those shown for sample #7 since the composition was the sameand the size difference was small. These formulations show a range of particle sizes and morphologies ranging from spherical and smooth to highly
rugose and wrinkled.

samples had a particle size distribution with a GSD of 1.6.
The median sample mass of the materials and formulations
listed in Table 1 was 66 mg. All samples were stored ata relative humidity (RH) below 5 % and between 22 and23 °C in a desiccator for several weeks before being used
for measurements.
Field Emission Scanning Electron Microscopy (Zeiss
Sigma FE-SEM; Carl Zeiss, Oberkochen, Germany) wasused to assess particle size and morphology. Powder
samples were mounted directly onto aluminum ScanningElectron Microscope (SEM) stubs (Product 16111; Ted
Pella, Inc.; Redding, CA, USA). Subsequently, the samples
were sputtered with a gold coating (Denton Vacuum Desk
II; Moorestown, NJ, USA) to a thickness of 10 to 15 nm.
Images ranging from magnifications of 500× to 20000×
were taken at a working distance of 5.3 to 6.3 mm using
an accelerating voltage of 3 to 4 kV. Scanning Electron

212

Microscope images of these samples are shown in Fig. 1
to show the differences in particle sizes and morphologies.
The experimental set-up for monodisperse andpolydisperse spray drying has been discussed elsewhere(Ivey et al., 2018b; Wang et al., 2019). The aerodynamic
particle size distributions were measured in-line with thespray drying process using a time-of-flight aerodynamic
particle sizer (3321, TSI, Shoreview, MN, USA) (Ivey etal., 2018a).
The solid phase of the powder samples was assessedusing Raman spectroscopy to determine whether they were
amorphous, crystalline or a mixture of the two. A custom
dispersive Raman spectroscopy system was utilized forthis purpose. The system included a 671 nm diode-pumped
solid-state laser (Ventus Solo MPC6000; Laser Quantum,
Stockport, UK). A detailed description of a similar apparatus has been published elsewhere (Wang et al., 2017).

David Barona et al. / KONA Powder and Particle Journal No. 38 (2021) 209–225

Samples were placed into a closed sample chamber under
nitrogen to prevent moisture exposure. All spectra were
measured at a temperature between 22 and 23 °C and atless than 5 % RH.

2.2 Methods
2.2.1 Modulated compressed bulk density instrument
The new powder compression apparatus consisted
primarily of a linear actuator, a piston, a sample cavity
and a load cell (shown schematically in Fig. 2). These
components were housed inside an enclosure that allowedeasy access for sample loading and unloading, servicing,alignment of the sample holder and cleaning. The linear
actuator and the load cell were connected to a computer forcontrol and data acquisition.
A powder sample was loaded into the sample holder(a stainless-steel die with a cylindrical cavity) which
was then placed on top of the load cell and tared. Upon
measurement, a piston coupled to a non-rotary, linear actuator (Physik Instrumente, M-229.26S, 25 mm, Karlsruhe,
Germany) exerted an axial force on the sample. The diameter of the piston used for measurements was designed suchthat an engineering fit (sliding fit) was obtained with thesample holder cavity. The resulting clearance of 0.1 mm
reduced the friction between the piston and the sample
cavity while preventing the powder from flowing out of
the sample cavity when compressed. The sample cavity
had an internal diameter and height of 5 and 6 mm, respectively, which resulted in powder sample masses of usuallyless than 100 mg; this small sample mass requirement isuseful for testing expensive, limited-quantity, rare or difficult-to-make samples.
A stepper motor controller (Physik Instrumente, C-663
Mercury Step, Karlsruhe, Germany) interfaced with theactuator and was controlled by a computer running custom
software. The load cell (FuTeK, LRF400- FSH04041,
Irvine, CA, USA), with a maximum load capacity of
44.5 N and a maximum load deflection of 0.117 mm, wasused to measure the force being exerted on the powder bed
during compression; the measured force was converted topressure using the known geometry of the sample die. A
USB controller (FuTeK, USB220, Irvine, CA, USA) wasused to interface with the load cell.
The RH of a small volume of approximately 200 cm3
around the sample can be precisely maintained at 0 % orcontrolled in 1.0 % increments between 3 % and 95 %RH using a humidity generator (RH-200, VTI, Hialeah,
FL). This feature is unique to this instrument and allows
measurements under different environmental conditions
depending on experimental requirements. Previous similar measurements on fine pharmaceutical powders lackthe capability of density measurements under real-timeand precise relative humidity conditions (Antikainen and
Yliruusi, 2003; Kaerger et al., 2004; Nordström et al.,2009; Sørensen et al., 2005; Thalberg et al., 2004). For themeasurements reported in this study, the RH control capabilities of the instrument were used to maintain 0 % RH.

2.2.2 Control and data acquisition
A custom program with a graphical user interface wasdeveloped using a system design platform (LabVIEW,
National Instruments 2011, Austin, TX, USA) to simultaneously control the instrument and acquire its data. This
program was also used to define the measurement criteria
and automate each measurement, which simplified instrument operation and reduced operator-induced systematic
errors. The program was used to modulate the displacementof the piston, resulting in compression and decompression
cycles on the powder. Harmonic, sawtooth, triangular wave
and other custom modulation profiles can be used to study
powder compression.

2.2.3 Modulated compression profile
For the results discussed here, a triangular modulation
mode was used for its simplicity. The triangular wave
mode used consisted of a series of linear compression anddecompression segments and was defined by specifying
the velocity, acceleration and deceleration of the linear
actuator, as well as the compression and decompression
displacements for each segment of a compression cycle.
These compression and decompression segments wererepeated until the measurement limits or hardware limitsof the instrument were reached. An example of a triangularmodulation profile is presented in Fig. 3 along with thepressure exerted on a powder during a measurement.

2.2.4 Modulated compressed bulk density (mCBD)
measurement

Fig. 2

Schematic of the instrument and its principal components.

A cylindrical stainless-steel die, which is the sample
holder, was loosely filled with powder sample using aspatula. The spatula was used to level the surface of thepowder so that it was flush with the top edge of the cavity.

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The previously tared die was then placed on a weighingbalance to determine the mass of the powder. The uncompressed sample volume was assumed to equal the volumeof the sample holder’s cavity. The die was then placed on
the load cell, which was tared before commencement of ameasurement. The position of the compressing piston was
adjusted for each measurement and zeroed by carefully
bringing the ram near the top of the sample cavity until
it touched just off on the powder inside the cavity. The
piston then advanced into the cavity at a rate defined by
the user and compressed the powder. The parameters used
for the density measurements discussed in this study were
fixed at 0.01 mm/s for the velocity of the piston, 0.2 mm/s2
for the acceleration and deceleration rates, a compression
displacement of 0.06 mm per cycle and a decompression
displacement of 0.02 mm per cycle. Based on these parameters, an individual compression and decompression cycle
took approximately 8 seconds.
The position of the piston was logged continuously by
the program and was used to determine the instantaneousvolume of the sample. The force exerted on the sample wascontinuously measured with the load cell, and pressure
was calculated by taking the ratio of the compression force
measured to the cross-sectional area of the piston. For acrystalline Leucine powder (sample #1 from Table 1),
Fig. 3 shows a sample modulated displacement profile(solid black trace, left axis) and the changes in compression
pressure changes over time (dotted red trace, right axis).
The modulated compression profile allowed for theobservation of plastic compression due to particle rearrangement and semi-elastic compression of this sample. It
can be seen that the compression pressure remains close tozero kPa upon decompression for the first ~250 seconds inthe measurement, while it deviates away from zero kPa af-

Fig. 3 A sample modulated displacement profile is plotted (solid black
trace) on the left axis as a function of time. The compression pressure
exerted on the powder (calculated from the force measured by the loadcell) is plotted (dotted red trace) on the right axis as a function of time.
The compression pressure on the powder remains close to zero kPa
upon decompression for the first ~250 seconds. Powder measured wascrystalline Leucine (sample #1 from Table 1).

214

ter ~250 seconds (corresponding primarily to semi-elastic
deformation of the powder).
The compressed bulk density was calculated at each stepby dividing the sample mass by the instantaneous sample
volume. At the end of a measurement, the data was combined into a graph that shows the compressed bulk density
as a function of compression pressure (see Fig. 5).

2.2.5 Powder elasticity ratio
A parameter for powder elasticity was derived from thedata to identify regimes of plastic and semi-elastic deformation during the compression process and to establish thetransition point between the two. The calculation was basedon the assumption that the powder compressed like a springwhen behaving elastically. In this case, following Hooke’s
law, the force on the powder is linearly proportional to asmall compression displacement by a stiffness constant.
For a modulated compression displacement, and for perfectly elastic response, the stiffness constant will be thesame when calculated for the decompression segment andthe compression segment; the ratio of these two stiffness
constants will be 1. However, for plastic or semi-elastic
response, the two stiffness constants will be different, andthe calculated ratio will be zero or less than 1, respectively.
The powder elasticity ratio was calculated from the compression pressures (obtained directly from the measured
forces) and the displacements of the compression piston
for each compression and decompression segment. The
powder elasticity ratio was calculated as the ratio of thechange in pressure between the start and end of an individual compression-decompression cycle, over a displacement
ratio as follows:

PD
PC
E
S D
1
S C
1

(1)

where ∆PC is the change in pressure between the start andend of a compression segment, ∆PD is the change in pressure between the start and end of a decompression segment,∆SD is the change in displacement between the start andend of a decompression segment, and ∆SC is the change indisplacement between the start and end of a compression
segment. The value of the powder elasticity ratio ranges
from zero for completely plastic response, to one for completely elastic response.
Fig. 4 shows a plot of a subset of the compression displacement and compression pressure data for crystalline
Leucine (sample #1 from Table 1) between 2.2 and 2.9 mm
and up to 250 kPa, respectively, for the sample measurement shown in Fig. 3.
Fig. 4 shows that up to ~100 kPa and up to a displacement of 2.65 mm, the measured force between the powder
and the compression piston returned to zero at the end of

David Barona et al. / KONA Powder and Particle Journal No. 38 (2021) 209–225

each decompression segment; the calculated powder elasticity ratio was zero and the powder compressed plastically.
However, as the pressure on the powder increased beyond~100 kPa, the measured force between the powder and thecompression piston was not zero at the end of each decompression segment. Hence, the calculated powder elasticity
ratio was greater than zero and the powder compressedsemi-elastically.
The powder elasticity ratio was calculated discretely foreach cycle in the modulation profile. Because of this, thetransition pressure from plastic to semi-elastic compression
response was estimated at the mid-point of the two compression pressures measured at the end of two consecutive
compression segments, where the first value corresponds tothe maximum compression pressure measured during thelast plastic cycle and the second value corresponds to the
maximum compression pressure measured during the firstsemi-elastic cycle. The transition density was estimated by
calculating the average value of the densities measured at
the maximum compression pressures and the minimum decompression pressures and then finding the average density
at the estimated transition pressure (see Fig. 5, top). The
accuracy of the transition pressures and densities can be
improved by using finer modulation profiles.
As can be seen in the amorphous Trehalose sample
measurement shown in Fig. 5 (bottom), the powder elasticity ratio clearly shows the transition from plastic tosemi-elastic compression when compared to the smoothprofiles of the CBD data (Fig. 5, top).

Fig. 5, where the CBD profile was bound by the densities
measured at the maximum and minimum displacements
for each cycle in the modulation profile (labeled as Max
Compression Pressure and Min Compression Pressure, respectively). An average density for the powder, calculated
as the average of the maximum and minimum compression
pressures was also included with the CBD data. Pressure
data below 10 kPa were not plotted in the results as they
were highly variable and had been determined to bestrongly linked to previous powder handling (USP, 2015)
as well as piston-die friction (measured to be below 0.1 N
or 3 kPa when the instrument is aligned properly).
From the measurement of the powder elasticity ratioof 100 % amorphous Trehalose (sample #2 from Table 1)
shown in Fig. 5 (bottom), it can be concluded that thecompression response was entirely plastic up to a pressure of ~80 kPa. In this range the compression overcame

2.2.6 Data processing
The data collected from each measurement was processed to calculate the powder elasticity ratio, the compression pressure at which the powder transitions fromthe plastic to semi-elastic compression regime, and thecorresponding powder density. Graphs were generated
for the powder elasticity ratio and mCBD as shown in

Fig. 4 A subset of the compression displacement from 2.2 to 2.9 mm
and compression pressure data up to 250 kPa for crystalline Leucine(sample #1 from Table 1) shown in Fig. 3. Plastic response is seenfor pressures up to ~100 kPa; semi-elastic response starts at pressures> ~100 kPa.

Fig. 5 Sample data for spray dried 100 % amorphous Trehalose(sample #2 from Table 1). This sample measurement shows the outputsof the data processing, which includes powder density (yellow trace,top) and the powder elasticity ratio (black circles, bottom) as a functionof compression pressure in a logarithmic scale to clearly show powder
response at low pressures. Transition pressure denoting the change fromplastic to semi-elastic compression response is indicated by the blacksolid vertical line. Average density (black dotted trace, top) is calculated
from the densities at the maximum and minimum compression pressuresand is used to estimate the powder density at the transition pressure.

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frictional forces to rearrange the powder into closer
packing. At higher pressures the powder showed partiallyelastic response, but in the entire range of the measurement
the response remained partially plastic, indicating that rearrangement or irreversible deformation had still occurred.

3. Results and discussion
It was assessed whether the modulated compression
instrument is capable of differentiating between similar
respirable powders at low pressures. It was expected thatchanges in a powder’s composition, particle size or particle
size distribution result in different overall compression response, including different plastic or semi-elastic responses
to compression, allowing quantified measurements to be
used to tell different samples apart. Hence, the following
cases were tested: 1) powders with the same chemicalcomposition but consisting of different particle sizes orparticle size distributions, and 2) the same particle sizes
and particle size distributions but different composition.

3.1 Measurement repeatability
Repeatability of measurements is an important factor forcompressed bulk density measurements in the low-pressure
region. Powders may compact prior to the measurement
during storage or handling. This problem is accentuated if
only small sample masses are available such that friction
effects during the measurement become more prominent. A
successful technique must be able to identify the regions of
the compression profile that are repeatable and independentof sample history. To assess this capability, three representative powdered materials were tested in duplicate (i.e. two
replicates): 1) 100 % spray dried amorphous Trehalose as
an example of a cohesive respirable powder, 2) 100 % raw
crystalline Leucine as an example of a powder with larger
particle size and 3) a spray dried mixture of 55 % Trehalosewith 45 % Leucine as an example of a spray dried powder
with a dispersibility enhancing excipient. These correspondto samples #2, 1 and 9 from Table 1, respectively and werechosen for their differences in composition, true density,
particle size, particle morphology and solid state; they were
expected to have different compression responses. The
duplicate CBD measurements and powder elasticity ratios
are shown in Fig. 6.
The CBD data (Fig. 6, top) show three pairs of distinct
CBD profiles, with each duplicate pair closely overlappingin the region above 10 kPa. The profiles based on maximum and on minimum pressure are both reproducible
where the replicate measurements are within 1 % from theaverage density of the two samples for each composition at
any pressure above 10 kPa. The powder elasticity ratio data
(Fig. 6, bottom) also shows three distinct profiles for each

216

duplicate pair, showing transitions to semi-elastic compression response at similar pressures for each pair (verticallines) and reaching very similar final powder elasticity
ratio values at the end of the measurement. CBD values atcompression pressures below 10 kPa are also shown. At
pressures much below the transition pressure, variability
was high and the profiles were not reproducible.
As shown in Table 2, based on the powder densities at
the transition between the plastic and semi-elastic regions,
all duplicate measurements are within ~2 % of the average.
Similarly, the transition pressures are within ~12 % of theaverage. The main source of error in the estimated transition values is the method by which the powder elasticity
ratio is calculated. As discussed in the Methods section,
the powder elasticity ratio is only known discretely andcalculated once for each modulated compression cycle.
Because of this, the spacing with respect to pressure
between consecutive powder elasticity ratio values is
directly linked to the frequency of the modulation profile.
Although the experimental parameters chosen for thisstudy demonstrate excellent measurement reproducibility
as shown in Fig. 6 and Table 2, the accuracy of the transition values can be further improved by utilizing a finer
modulation profile. Other error sources are small and mostprominent at measurement pressures below 10 kPa. These
include powder history or handling prior to measurement(random), changes in environmental conditions (random),piston-die friction (systematic), load cell measurement
error (systematic), piston position control and knowledge(systematic) and mechanical hardware deflection (systematic). However, under proper sample preparation, instrument alignment, calibration, maintenance and operation,these additional errors do not contribute significantly to theoverall measurements.
As seen in these duplicate modulated compression
results, the low-pressure measurements made by this
instrument show excellent repeatability and the resulting
CBD and powder elasticity ratio curves can be used to differentiate between similar respirable powders. For the sakeof clarity, the results presented in the following sections
contain only a single measurement per sample tested andshow only the average CBD.

3.2 Ability to discriminate between powders
with the same composition but consisting ofdifferent particle sizes
To demonstrate the capability of the mCBD instrument
for testing the compression response of small amountsof fine and respirable pharmaceutical powders and discriminating between them, samples with the same composition but different particle sizes were first measured.
For instance, changes to the particle size will change thetotal number of contact points between particles in theDavid Barona et al. / KONA Powder and Particle Journal No. 38 (2021) 209–225

Fig. 6 Duplicate measurements of 100 % amorphous Trehalose, 100 % crystalline Leucine and a mixture of 55 % Trehalose and 45 % Leucine(samples #2, 1 and 9, respectively, from Table 1). The top figure shows the CBD profiles for each sample as a function of the maximum and minimumpressures reached from the modulated compression. The bottom figure shows the calculated powder elasticity ratio for each sample as a function ofpressure. Pressure is shown in both figures on a logarithmic scale to clearly show powder response at low pressures. Vertical lines indicate the pressuresat which the samples transition from plastic to semi-elastic compression response. Data from compression pressures below 10 kPa are included in the
top figure to show the high variability at very low pressures.
Table 2 Average transition pressures and densities from plastic to semi-elastic compression response for the duplicate measurements shown in Fig. 6.
Standard deviation is also shown as a percentage of the average values.

SampleTransition Pressure

Transition Density

Meas. 1 [kPa]

Meas. 2 [kPa]

Meas. 1 [kg/m3]

Meas. 2 [kg/m3]

100 % Amorphous Trehalose

77.2

81

770

788

100 % Crystalline Leucine

62.2

52.4

437

433

55 % Trehalose and 45 % Leucine

172

186

331

339

powder, affecting its overall cohesion and its compression
response. This is important, for example, in formulation
development to achieve certain powder characteristics (deBoer et al., 2017; Prime et al., 1997), as well as for quality

control to confirm that powders meet manufacturing specifications, e.g. during scale-up. In either case, the mCBD
instrument should be capable of measuring a difference inthe compression response of two powders with the same217

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composition but different particle size distributions.
Shown in Fig. 7 are two spray-dried powder samplesof 100 % Mannitol. The first sample was polydisperse(sample #11 from Table 1; GSD of 1.6 and a MMAD
of 3.5 μm), while the second sample was monodisperse(sample #10 from Table 1; GSD of 1.1 and an MMAD of
10 μm). Both samples were found to be crystalline using
Raman spectroscopy.
The mean mCBD measurements (Fig. 7, top) and thepowder elasticity ratio curves (Fig. 7, bottom) show twovery distinct compression profiles. Although the chemicalcomposition and solid phases were the same for both
samples, the compression responses were different. On
the other hand, the transition from plastic to semi-elastic
response was very similar at ~99 kPa and ~475 kg/m3 forthe polydisperse sample and ~101 kPa and ~468 kg/m3 forthe monodisperse sample. The polydisperse sample canachieve higher compressed bulk density with increasingpressure while compressing less elastically than the monodisperse sample. Since the polydisperse sample consists ofFig. 7 Comparison of two powders of 100 % crystalline Mannitol
but with different particle size distributions. Semi-logarithmic profilesof the average mCBD (top) and powder elasticity ratios (bottom) vs.
compression pressure show two different compression responses. The
pressures at which the powders transition from plastic to semi-elastic
compression response are indicated by vertical lines in both plots.

218

particles of different sizes, these differences in compression
response might be attributed to the smaller particles fillingthe interstitial spaces, resulting in a reduction in the void
space in the powder bed and higher bulk density (York,
1978). This can also be seen in the powder elasticity ratio
curves (Fig. 7, bottom), where after the transition point,
the elasticity of the polydisperse powder increased lesssharply, indicating that some of its particles can continue torearrange as the pressure increases. Conversely, the sharperincrease in the powder elasticity ratio for the monodisperse
powder is an indication that most particle rearrangement
has already occurred.
In this specific example, there was also a sudden decreasein the elasticity of the polydisperse powder at ~300 kPa ofpressure. This decrease corresponds to a release of stressin the powder that could be due to particle deformation
or fragmentation (Chen et al., 2017; Vu et al., 2020), or
could also be due to breakage of bridges or other structures
formed by the particles and which were previously heldin place by interparticle forces. This is further indicationthat the polydisperse powder may be undergoing further
rearrangement as the pressure increases, although it is not
currently possible to decouple this from particle damage inthe semi-elastic response region.
A second example shown in Fig. 8 compares the mean
mCBD measurements for a two-component formulation(75 % Trehalose and 25 % Leucine) spray dried into
two separate polydisperse powders with GSD of 1.6 andMMAD of 2 μm and 4.5 μm, respectively (samples # 7
and 8 from Table 1). In both samples Trehalose was fully
amorphous and Leucine was fully crystalline under Raman
spectroscopy.
As can be seen in Fig. 8 (top), the sample with thesmaller particle sizes (MMAD of 2 μm) achieved higher
densities than the sample with larger particle sizes (MMADof 4.5 μm); similarly to the previous example shown in
Fig. 7, these higher densities could be attributed to thesmaller particles being better at filling any interstitialspaces as the powder is compressed. From the particle morphologies shown in Fig. 1, it can be seen that the particles
were not spherical and had a significant external void fraction. Even though the compositions were the same and theoverall morphologies for particles from both samples werevery similar, the surface features of the smaller particles
had sharper curvatures, which may lead to smaller contact
points between particles, reducing particle cohesion (York,
1978). An alternative explanation to the CBD of these
two samples is that particles with a larger MMAD have alower particle density because Leucine takes a longer timeto crystallize (Baldelli et al., 2016), resulting in an overalllower density powder. In either case, whether it is the difference in particle density or the change in the particle cohesion due to the changes in particle size, the CBD profiles
are different for both samples, with the larger particle size

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resulting in an overall lower bulk density at any pressure.
Furthermore, the pressures and densities at which thepowder transitions from plastic to semi-elastic response
were different, with the sample composed of the smaller
sized particles reaching semi-elastic compression response
at higher pressures: ~91 kPa and ~422 kg/m3 for thesmaller particle size versus ~48 kPa and ~370 kg/m3 forthe larger particle size vs. for the smaller particle size. Thisis further indication of increased particle cohesion during
plastic deformation and particle rearrangement for thelarger particles; however, as can be seen in the powder elasticity ratio curves (Fig. 8, bottom), both traces converge
quickly in the semi-elastic regime, which is an indicationthat higher pressure was needed to overcome the increased
cohesion between larger particles.
In both examples, it is clear that the instrument can
detect differences in the compaction profiles that are directly or indirectly caused by changes in the particle size
distributions.

Fig. 8 Comparison of two polydisperse powders of 75 % Trehaloseand 25 % Leucine but with different MMAD. Semi-logarithmic profilesof the average mCBD (top) and powder elasticity ratios (bottom) vs.
compression pressure show two different compression responses. The
pressures at which the powders transition from plastic to semi-elastic
compression response are indicated by vertical lines in both plots.

3.3 Ability to discriminate between powders
with the same particle sizes but different
compositions
It is expected that the compression response of powders
is also a function of their composition and not just of theparticle sizes and distributions. For instance, the presenceof different materials on the surface of a particle can makethem more or less cohesive (Vehring, 2008). Again, thedegree of cohesiveness plays an important role in formulation development to achieve certain powder characteristics
such as dispersibility or flowability (de Boer et al., 2017;
Prime et al., 1997), as well as in quality control to assess
adherence to manufacturing specifications. In either case,the mCBD instrument should be capable of measuring a
difference in the compression response of powders withdifferent compositions but the same particle sizes.
The following measurements compare monodisperse
powders containing Trehalose and Trileucine with small
increments in the amount of Trileucine. It has been shownthat Trileucine, a surface-active amino acid, can be used
as a shell former in particle formation to achieve particles
with low cohesion and low density (Lechuga‐Ballesteros etal., 2008). It is expected that this will affect the compression response of these powders by allowing the particles
to slip past one another and rearrange more easily. All
samples had the same GSD (1.1) and MMAD (9 μm). The
following measurements compare the mean compression
response of 99.6 % Trehalose with 0.4 % Trileucine, 99 %Trehalose with 1 % Trileucine, and 95 % Trehalose with
5 % Trileucine (samples #3, 4 and 5 from Table 1, respectively). From the SEM images shown in Fig. 1, it can beseen that an increase in Trileucine content resulted in an
increase to the rugosity of the particles. This increase inrugosity is expected to lower the cohesive forces between
the particles (Baldelli and Vehring, 2016).
Because of the different formulations, the mean bulk
densities in these measurements are normalized by thetrue density of the particles in order to make meaningfulcomparisons between the density profiles. From this normalization, a value of 1 would correspond to a bulk densitythat equals the true density of the material, meaning thatthe compressed powder would be absent of any voids. Conversely, this normalized density can be used as a measureof the void space in a powder sample and of the packing ofparticles within a compressed bulk.
Comparing these measurements with the particle morphologies in the SEM images shown in Fig. 1, it can beseen that increasing Trileucine from 0.4 % to 1 % had asmall effect on the particle morphology, making the particles more rugose and with more external voids; however,
it is likely (Lechuga‐Ballesteros et al., 2008) that thisincrease in Trileucine resulted in a more dispersible (andmore flowable) and less cohesive powder that can achieve219

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higher densities upon compression more easily.
A further increase in Trileucine to 5 % resulted in aneven clearer difference between the mean compression
response of these powders as shown in Fig. 9 (top), where adifference in the mCBD and powder elasticity ratio curves
can be easily observed. However, increasing Trileucine
from 1 % to 5 % resulted in a decrease in powder density
upon compression. Comparing these measurements to the
SEM images shown in Fig. 1, it can be seen that such anincrease in Trileucine caused a strong change to the particle
morphology. The particles were much more rugose at 5 %Trileucine and the increased number and size of external
voids resulted in lower particle density. While the transitionpressures and densities calculated for both powders werevery similar, the increase in Trileucine (from 1 % to 5 %),and the corresponding change in the particle morphology,
resulted in a lower final powder elasticity ratio (Fig. 9
bottom). This means that the reduction in compressed bulk

density of the powder with 5 % Trileucine is not entirely
due to changes in particle cohesion but to a decrease in particle density caused by the increase of external void spacein the more rugose particles.
A similar comparison of two polydisperse powders
with the same particle size distributions and particle diameters (GSD of 1.6 and an MMAD of 2.5 μm), 100 %Trehalose versus 80 % Trehalose and 20 % Leucine, isshown in Fig. 10. Similar to Trileucine, Leucine is also a
surface-active amino acid used as a shell former in particle
formation to achieve particles with low cohesion and low
density (Feng et al., 2011). From the comparison of thesetwo powders, it is expected that the sample containing
Leucine will have enhanced powder dispersibility andreduced particle cohesion.
From these measurements, the mean compression response of both samples (Fig. 10, top) can be quantitatively
distinguished, where the presence of Leucine resulted in an

Fig. 9 Comparison of three monodisperse powders (GSD 1.1) withthe same particle sizes (MMAD 9 μm) of 99.6 % Trehalose with 0.4 %Trileucine, 99 % Trehalose with 1 % Trileucine and 95 % Trehalosewith 5 % Trileucine (samples #3, 4 and 5 from Table 1, respectively).
Semi-logarithmic profiles of the average mCBD normalized by true
density (top) and powder elasticity ratios (bottom) vs. compression pressure show different compression responses. The pressures at which thepowders transition from plastic to semi-elastic compression response
are indicated by vertical lines in both plots.

Fig. 10 Comparison of two polydisperse powders (GSD 1.6) with thesame particle sizes (MMAD 2.5 μm) of 100 % Trehalose and 80 % Trehalose with 20 % Leucine (samples #2 and 6 from Table 1, respectively).
Semi-logarithmic profiles of the average mCBD normalized by true
density (top) and powder elasticity ratios (bottom) vs. compression pressure show different compression responses. The pressures at which thepowders transition from plastic to semi-elastic compression response
are indicated by vertical lines in both plots.

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increase in the powder’s bulk density at a given pressure
and also resulted in an increased transition pressure andtransition density. The Leucine-containing powder is easier
to compress. This is an indication that powder dispersibility
is enhanced and particle cohesion is reduced, as expected.
Overall, the measurements show that small amounts ofdifferent respirable powders can be differentiated reliably
using the modulated compression technique. The compression behavior is determined by a variety of competing
factors including size distribution, cohesiveness and rugosity of the particles and their particle density. Being able toassess both bulk density and elasticity of the powder under
low pressure aids in the interpretation of the results.

4. Conclusions
Using modulated compression, this new density tester iscapable of distinguishing whether a compression step is reversible or irreversible and is therefore useful in revealing
the compression response of fine and respirable pharmaceutical powders under low applied pressures. By using modulated compression, bulk density measurements can revealtransitions between plastic and semi-elastic compression
responses, something not possible with non-modulated or
entirely linear compression methods.
Quantification of this transition can be used to determine
a pressure at which it can be assumed that the powder
handling history has been erased and reproducible results
can be obtained, e.g. for the purposes of selecting a suitablelevel of compaction for powder filling operations. Additionally, the ability to identify the transition point between
these two regimes can aid in making modifications to a
powder’s formulation (e.g. adding a dispersibility enhancer
to improve flowability) so that the resulting powder canachieve a desired bulk density at a given pressure before
the physical integrity of the particles is compromised. Thisis especially important for fine pharmaceutical powders
with a mean particle size smaller than 25 μm and in particular for respirable powders with a mean particle size
< 10 μm.
Selected tests presented in this paper demonstrate thatthe instrument can be used to easily discriminate between
similar fine and respirable powders with slight changes
in composition, particle size or particle size distribution,
based entirely on their compression response. This capability is particularly useful in quality control applications
where defined product attributes need to be maintained, orin formulation development where certain properties need
to be achieved.
The instrument, the control software and data processing have been designed and implemented such the tester
produces repeatable and reproducible measurements at
low pressures. The small sample mass requirement of

typically less than 100 mg is particularly useful in early
product development for performing CBD measurementsof expensive, limited-quantity, and rare or difficult-to-makepowders.

Acknowledgements
The authors acknowledge the support of AstraZeneca,
the Canada Foundation for Innovation, Alberta Advanced
Education and Technology, and the Natural Sciences andEngineering Research Council of Canada. The authors thankIsobel Tetreau for help with producing the final figures.

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Authors’ Short Biographies
David Barona
Mr. Barona is a student and staff member in the Department of Mechanical Engineering
at the University of Alberta. He graduated with a Bachelor’s degree in Aerospace Engineering from the Georgia Institute of Technology in Atlanta, USA. He has worked at the
University of Alberta since 2009 with the Surface Engineering and Instrumentation Lab,
the Particle Engineering group, and the Space Physics group. He is currently pursuing a
Master’s degree in Mechanical Engineering from the University of Alberta, specializingin the modulated compressed bulk density of respirable powders. His research interests
include particle engineering, surface engineering, spray drying and hardware design.

Abouzar Shamsaddini
Mr. Shamsaddini is a Project Execution Manager for ROSEN Group Ltd., global provider of In-line inspection technologies and services in Oil and Gas industries. Prior tothat, he was a member of the research and development department at UT Quality Inc., a
sub-division of RAE Energy. He was responsible for developing a state-of-the-art instrument for Ultrasonic Testing (UT) of pipeline girth welds with small footprints. Abouzar
holds a Master’s degree in Mechanical Engineering from the University of Alberta with afocus on Particle Engineering. During the course of his studies, he developed the Particle
Density Tester for respirable powders.

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Authors’ Short Biographies
Maximilian Aisenstat
Mr. Aisenstat was a co-op student in the Particle Engineering group in 2019. He graduated with a Bachelor’s degree in Mechanical Engineering with Biomedical Option from the
University of Alberta, and he will be returning to the Particle Engineering group to pursue
a Master’s degree in Mechanical Engineering in Fall 2020. His research interests include
particle engineering and spray drying.

Kyrre Thalberg
Kyrre Thalberg obtained a Master’s degree in Chemical Engineering 1981 from Lund
University, Sweden, and a Ph. D. in Physical Chemistry from the same university in 1990.
Since 1991, Kyrre has been working with AstraZeneca, first at the site in Lund originallycalled Draco, now in Mölndal, both in Sweden. He has provided key contributions to several inhalation products on the market, in particular the Turbuhaler® dry powder inhalers.
His current position has a focus on fundamental understanding, application and scale up of
dry powder formulations. Kyrre has authored or co-authored more than 30 publications ininternational journals.

David Lechuga-Ballesteros
Dr. David Lechuga-Ballesteros, Research Fellow at AstraZeneca, is a leading scientist
in the area of pharmaceutical material sciences and particle engineering. Dr. Lechuga has
co-authored over 100 publications including peer-reviewed articles, book chapters and abstracts, co-edited a special issue on respiratory and nasal drug delivery, and a book on drying technologies for biotechnology and pharmaceutical applications. Dr. Lechuga is named
as an inventor in over fifteen patents describing new drug crystal forms, novel formulations, or specialty particle engineering processing equipment. Dr. Lechuga currently servesin the Editorial Advisory Board of several leading Journals in the area of Pharmaceutics.

Behzad Damadzadeh
Behzad Damadzadeh is an Associate Scientist at AstraZeneca currently working in the
Inhalation Product Development (IPD) group in South San Francisco, California. Behzad
is an experienced scientist in the pharmaceuticals industry and his main expertise is on formulation and spray drying. He graduated with a Master’s degree in Chemical Engineeringfrom the Chalmers University of Technology in Gothenburg Sweden. He also obtained a
Master’s degree in Biomedical Engineering from Arizona State University (Tempe, Arizona). His area of interest includes formulation for pulmonary delivery of small molecules,
proteins and genetic material as well as physical and solid-state characterization of spraydried products.

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Authors’ Short Biographies

Reinhard Vehring
Dr. Vehring is a Professor in the Mechanical Engineering Department at the Universityof Alberta and holds the George Ford Chair in Materials Engineering. He graduated witha diploma in Mechanical Engineering from the Gerhard Merkator University in Duisburg,
Germany, and received a doctorate from the University of Bochum in the field of molecular
spectroscopy on microparticles. Dr. Vehring has held positions in academia and industry
advancing aerosol science and particle technology for more than 26 years. Before returning
to academia, he worked on pulmonary delivery of peptides, proteins, and small molecules
at Nektar Therapeutics and was part of the team developing Exubera, the first inhalable
insulin. Subsequently, he developed solid dosage forms for virus vaccines, monoclonal
antibodies, and oncology therapeutics at Medimmune, and supported FluMist, the firstnasally administered live attenuated influenza vaccine. Dr. Vehring was the lead inventor
for the co-suspension formulation technology which is used by Pearl Therapeutics to develop metered dose inhaler based therapeutics for respiratory diseases. At the University ofAlberta, Dr. Vehring directs the Particle Engineering facility focusing on advanced micro
and nanoparticle design and analysis.

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Original Research Paper

Effects of Powder Vibration and Time Consolidation
on Soft and Hard Wheat Flour Properties †Yumeng Zhao 1, Poonam Phalswal 2, Abhishek Shetty 3 and R.P. Kingsly Ambrose 1*
1

Department of Agricultural and Biological Engineering, Purdue University, USA
National Dairy Research Institute, India
3
Rheology Department, Anton Paar USA, USA
2

Abstract
Consistency and reliable flow are of great concern during the handling and processing of flour. In this study,
wheat flour was consolidated by normal stress and vibration, and rheological factors including bulk solid
compressibility, Warren-Spring cohesion strength, permeability, and wall friction were evaluated. Soft red winter(SRW) and hard red spring (HRS) wheat flours were vibrated for 5 and 10 minutes and compressed under 10 and
20 kPa for 12 and 24 h. After vibration, wall friction increased from 10.87° to 14.13° for SRW flour and decreased
from 11.00° to 7.10° for HRS flour, and the permeability decreased for both the flours. Consolidation time andstress had a significant effect (P < 0.05) on wall friction and compressibility. The HRS Carr index increased from25.77 to 38.48 when consolidated under 20 kPa for 24 hours, but the SRW Carr index decreased slightly from46.60 to 44.24. The SRW flour permeability decreased significantly (P < 0.05) when compression pressure wasincreased from 10 to 20 kPa. while HRS permeability was less affected by consolidation. The consolidation andvibration effects on bulk flour properties differed likely due to inherent differences in the composition andhardness of HRS and SRW.
Keywords: flour, time consolidation, plastic-elasticity, storage, vibration

1. Introduction
Wheat flour is one of the most important food productsin the world. The bulk powder properties of wheat flour,
including cohesiveness, flowability, wall friction, and permeability, are important for processing and handling,such as silo unloading and pneumatic transportation.
These properties are highly dependent on particle size,
shape, surface roughness, and composition (Molerus andNywlt, 1984). The U.S. has differentiated wheat into 6classes based on its composition and hardness. The flours
from different wheat classes differ in particle size, surface
fat and protein contents (Bian et al., 2015). Soft wheat
flour has less protein and more fat content, and smaller
particle size. Therefore, soft wheat flour is always cohesive than hard wheat flour (Bian et al., 2015). Studies also
have found that the soft wheat flour shows higher cohesiveness than hard wheat flour due to the particle’s roughsurface characteristics (Kuakpetoon et al., 2001). Due to†

Received 2 February 2020; Accepted 2 March 2020
J-STAGE Advance published online 29 April 2020
* Corresponding author: Kingsly Ambrose;
Add: 225 S University St, West Lafayette, Indiana 47907, USA
E-mail: rambrose@purdue.edu
TEL/FAX: +1-7654946599

226

flour particle size and compositional differences, soft andhard wheat flours could behave differently under similar
consolidation or vibration conditions. During storage andtransportation, minor changes in particle property contribute to significant changes in bulk powder properties.
Besides environmental conditions such as humidity and/or temperature changes causing consolidation, stress applied to the particle will affect bulk flour properties. Consolidation caused by the powder’s own weight has beenfound to reduce flowability (Teunou and Fitzpatrick,2000). During consolidation, with the variable of timeand deformation rate, particle surface contact and deformation can be distinguished as reversible elastic, irreversible plastic deformation, and viscoelastic deformation(Tomas, 2000). Many studies have reported that thesebulk powder property changes are mainly due to interparticle force changes (Domian and Poszytek, 2005; Teunou
and Fitzpatrick, 2000).
Discrete taps, or vibration, always exists during transportation or handling, which could lead to the segregationof granular materials (Jain et al., 2013). Studies haveshown that in particulate systems which are made ofcoarse and fine fractions, the coarse powder fraction
shifts upwards and fine powder fraction shifts downwards
during vibration. The particle size distribution affects the

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Yumeng Zhao et al. / KONA Powder and Particle Journal No. 38 (2021) 226–234

segregation tendency in particulate systems (Kawakita
and Lüdde, 1971; Parsons, 1976). A decrease in bulk volume is also found after vibration (Podczeck and Sharma,
1996). But, there are lack of studies that quantify this effect of segregation in wheat flour on their bulk characteristics. Furthermore, the vibration of cohesive powder
could result in self-agglomeration (Kahrizsangi et al.,2016). Both particle segregation or self-agglomeration are
undesirable for flour processing and handling. However,
the effects of vibration on flour properties are unexplored.
In addition, hard wheat flour and soft wheat flour differ incohesiveness and particle size distribution.
In this study, we have used different techniques to determine the important wheat flour handling and processing properties. Tests like compressibility (including
Hausner ratio, compressibility index, Carr index), permeability and Warren-Spring cohesion were used to assess
flowability of the flour samples.
Goal of this manuscript was to study the vibration andtime consolidation effects on soft and hard wheat flours
bulk properties. Flour compressibility, Warren-Spring cohesion, permeability, and wall friction after consolidationand vibration treatments were tested, in order to provide areference for bulk flour property changes after storage
and transportation.

2. Materials and methods

two replicates using the Morphologi G3-ID instrument(Malvern Panalytical, Inc., Westborough, MA, USA).
SRW had a mean particle circularity equivalent (CE) diameter of 11.97 ± 0.11 μm and a circularity mean of
0.83 ± 0.03, while HRS had a particle CE diameter of
16.91 ± 0.76 μm and a circularity mean of 0.78 ± 0.02
(Figs. 1, 2).
For consolidation, 50 g of flour was compressed using avented piston on an Anton Paar rheometer (MCR 502 series, Anton Paar, Graz, Austria) under 10 and 20 kPa for
12 and 24 h before testing. These compression pressures
were chosen to approximate stresses encountered during
flour storage (Domian and Poszytek, 2005). To mimic
handling, 50 g of flour was vibrated for 5 and 10 min using a tapped density tester (Agilent Technologies, Santa
Clara, CA, USA) before property measurements. All theexperiments were performed in triplicate to gauge for statistical significance. The complete design of experiment ispresented in Table 1.

2.2 Flour rheology tests
Bulk f lour properties including compressibility,
Warren-Spring cohesion strength, permeability, and wall
friction were determined before and after consolidationand vibration treatments using built-in test methods on
the Anton Paar MCR-502 rheometer.
Compressibility: Compressibility is a measure of the

2.1 Sample preparation
Soft red winter (SRW) and hard red spring (HRS)
flours were obtained from The Mennel Milling Company(Fostoria, OH, USA). The moisture content was determined using AOAC method 925.10 (AOAC, 2006), by
drying 2–3 g of flour at 130 °C for 2 h. The moisture contents of SRW and HRS were 12.71 ± 0.07 and 12.45 ±0.02 % w.b., respectively. SRW contains 7.6 % protein(14 % m.b.) content and HRS contains 12.8 % protein(14 % m.b.) (Miller and Hoseney, 1997; Bian, et al., 2015).
Flour particle size and shape factors were measured inFig. 1 Particle size number distribution of SRW and HRS flours.

Fig. 2 Images of HRS (left) and SRW (right) flour particles.

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Table 1 Summary of experimental parameter values used in the study.

Treatment
Sl. NoSampleTime-consolidation

Parameters measured

Vibration (min)Consolidation time (h)Pressure (kPa)

1

SRW

5, 10

12, 2410, 20Carr index, WS cohesion strength,
Permeability, Wall friction

2

HRS

5, 10

12, 24120, 20

Carr index, WS cohesion strength,
Permeability, Wall friction

relative volume change when a pressure (normal stress) isapplied and represents the density change under the applied normal stress. Carr index was used as an indicator
to describe the compaction mechanism in this study. Low
Carr index indicates low compressibility and a freeflowing powder. The Carr index is a characteristic of apowder’s compressibility and is often used as an indication of a powder’s flowability and is defined by the powder density before compression (ρ0) and after compression(ρt):
Carr Index  t  0t(1)Flour was compressed to 50 N. A Carr Index of 1 indicates an incompressible bulk solid (ρt = ρ0). This is interpreted as the best possible flowability a granular material
can have. The larger the value of Carr Index, the poorer
the flowability of the material (Abdullah and Geldart1999). In this study, the Carr index was obtained at 50 N
(25 kPa) load in order to mimic the normal load in a flour
storage silo.
Warren-Spring (WS) cohesion strength: This measurement is used to determine the cohesion of powders as afunction of applied normal stress. A homogenous powder
bed is created by consolidation at different normal
stresses of 3, 6 and 9 kPa using a vented piston and thenthe Warren-Spring geometry was used to measure thetorque at a very small rotational speed of 0.1 rpm. The cohesion strength can be derived from the torque (M) via a
simple moment balance by correlating the shear resistanceto the torque measured (Mohammed et al., 2011):

WS Cohesion Strength 

3M
2π(R03  Ri3 )(2)

where Ri and R0 are the radius of Warren-Spring geometry shown in Fig. 3. The maximum cohesion strength obtained during the rotation of probe is known as
Warren-Spring cohesion strength.
Permeability: Permeability is defined as the resistanceof fluid (air) through a compacted bed of powder. The
permeability was determined by measuring the pressure
gradient of air across a packed bed of length (L) at an airflow velocity (U) using the powder cell accessory at-

228

Fig. 3 Schematic diagram of a Warren-Spring geometry.

tached to the rheometer (Mishra et al., 2020) and is given
by Darcy’s law (Whitaker, 1986):

Permeability 

U  LΔp(3)

where Δp is the pressure drop in the compacted powder
bed, and η is the air dynamic viscosity. Consolidation offlour reduces the porosity; thus, permeability is an important factor when developing unloading strategies forwheat flour. Flour permeability was tested under 3, 6, and9 kPa pressure by measuring the resistance to airflow at
0.15 L/min.
Wall friction: This property measures the resistance
between powder and the container wall material. In thisstudy, the wall friction of flour on stainless-steel wasmeasured. A stainless-steel probe was used to measure
the wall friction at a rotational speed of 0.05 rpm under 3,
6, and 9 kPa pressure. Normal stress (σ) and shear stress(τ) were used to calculate the wall friction angle (Bian etal., 2015):

Wall Fricition  tan 1( )(4)

2.3 Data analysis
Each test used fresh samples and all the measurements
were conducted in triplicate. One-way ANOVA was used

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to determine the effect of vibration on powder properties
and two-way ANOVA was used for determining the effectof consolidation on powder properties as influenced byconsolidation pressure and time. Statistical analysis was
performed by Statistical Analytical System software (SASInstitute, Cary, NC, USA). P-values less than 0.05 wereconsidered significant difference.

During wheat flour transportation, bulk flours undergo
vibration inside the moving truck. The normal force applied to the flour particle during vibration is not as high as
inside a storage bin, but particles rearrange depending on
their differences in size and shape.
The Carr index (Table 2) reflects the percentage of volume change during compression, which is a good indicator of compressibility and powder flowability (Prescottand Barnum, 2000). HRS flours did not exhibit a significant difference in the Carr index values when vibration
time was increased from 5 to 10 min. Both HRS and SRW
flours were not significantly affected by vibration. But,
the Carr index of HRS flours was much lower than SRW
in similar to the observation by Bian et al. (2015). This indicated that vibration history did not affect the compressibility of the wheat flours. Though this study was limited
to tapping of 10-min in a lab-scale, the results indicatethat the flour compressibility is mainly affected by its own
particle properties and moisture content. Furthermore,this study was limited to the lab-scale tapping for 10 min
in maximum with 50 g of flour, it was not possible to fully
monitor the real transportation scenario where the wheat
flour could be subjected to several hours of vibration.
The wall friction angle decreased after vibration of
HRS flours but increased with vibration for SRW flours(Table 3). The differences in results could likely be due tothe differences in flour particle hardness. During the measurement of wall friction angle, the probe only touched
the top surface of the bulk flour. During vibration, HRS
particles might have been rearranged with large particles
moving to the surface (Knight et al., 1993), without formation of agglomerates. Thus, the wall friction decreased
with increase in particle size at the surface of bulk flour(Iqbal and Fitzpatrick, 2006). This mechanically induced
effect due to vibration is also called granular convection,or more commonly, the Brazil nut effect, in which mechanical agitation of a granular medium segregates theparticles, such that the largest particles end up on top(Ehrichs et al., 1995). For SRW, on the other hand, some
agglomerates were observed during vibration. Selfagglomeration of cohesive powder may occur during vibration (Kahrizsangi et al., 2016). The agglomerates
formed with the highly cohesive SRW flour particles,
during vibration, resulted in cohesive particles accumulating on the bulk flour surface. During the wall friction
test measurement, the SRW flour agglomerates on the topof the surface were deformed when in contact with thewall friction probe. This potentially could have crumbled
the loose agglomerates formed on the surface which inturn would have exposed the cohesive powder fraction to
the probe which led to an increase in wall friction angle.
Significant differences in permeability were not observed for both HRS and SRW flours, except for the SRW
flour tested at 6 and 9 kPa load (Table 4) where a statistical change was observed. Overall the result corresponded
well to the Carr indices, that compressibility is not affected by vibration. Though the results did not reveal significant changes, permeability decreased with vibration,
which indicated that rearrangement has some effect, but
not a major effect, on permeability.
Both HRS and SRW flours exhibited changes in WS
cohesion strength after vibration (Table 5) with an increased effect on SRW cohesiveness than the HRS flour.
Even at 5 min of vibration, the WS cohesion strength increased for both HRS and SRW flours but was not

Table 2 Carr index of wheat flour at different vibration times.

Table 3 Wall friction of wheat flour at different duration of vibration.

3. Results and discussion
3.1 Effects of vibration on flour bulk properties

HRS

SRW

Vibration time

Carr index

Vibration time

Wall Friction (°)

Control

36.95 (2.01) a

Control

11.00 (0.40) a

5 min

37.76 (1.24) a

5 min

7.03

(0.19) b

10 min36.99 (0.19) a

10 min7.10(0.63) b

Control

46.60

Control

10.87(0.83) a

5 min

45.26 (1.07) a

5 min

11.43 (0.71) a

10 min46.79 (0.95) a

10 min14.13(0.39) a

Values in parentheses are the standard deviations. Values followedby the same letters are not significantly different when comparedwithin HRS and SRW.

HRS

SRW

(1.04) b

Values in parentheses are the standard deviations. Values followedby the same letters are not significantly different when comparedwithin HRS and SRW.

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Table 4 Permeability of wheat flour at different vibration times.

Permeability (10 –12 m 2)
Vibration time
3 kPa
HRS

SRW

6 kPa

9 kPa

Control

16.75(0.70) a

13.03(0.48) a

11.82(0.38) a

5 min

15.92

(0.86) a

12.81(0.55) a

11.59(0.39) a

10 min15.78(1.13) a

12.93(0.64) a

11.62(0.45) a

Control

9.56 (0.43) a

5.64(0.13) a

4.54 (0.29) a

5 min

8.63 (0.53) a

4.79 (0.32) b

3.69 (0.16) b

10 min8.68 (0.46) a

4.90 (0.28) b

3.78 (0.08) b

Values in parentheses are the standard deviations. Values followed by the same letters are not significantly different when compared within HRS
and SRW.
Table 5 WS cohesion strength of wheat flour as influenced by the duration of vibration.

WS Cohesion strength
Vibration time
3 kPa
HRS

SRW

6 kPa

9 kPa

Control

0.70(0.26) a

0.91(0.09) ab

1.08(0.10) a

5 min

0.81

(0.05) a

1.02 (0.06) a

0.97(0.05) a

10 min0.63(0.22) a

0.87(0.01) b

1.00(0.10) a

Control

0.70 (0.13) a

2.26 (0.09) a

3.41(0.57) a

5 min

0.94

(0.08) a

2.49 (0.05) a

3.63(0.32) a

10 min0.66(0.18) a

1.50 (0.24) b

2.95(0.26) a

Values in parentheses are the standard deviations. Values followed by the same letters are not significantly different when compared within HRS
and SRW.

statistically different than the control samples. The WS
measurement probe penetrated 10 mm into the top of thecompressed powder bed before applying a torque to induce failure in the powder bed. This was approximately
about one third the volume of the powder bed. Vibration
which would have caused; granular convection of larger
particles to the top could potentially explain the drop in
Warren-Springs cohesion due to presence of higher sizedparticle fractions at the top. The limited number of agglomerates formed in SRW did not affect the cohesion
strength measurement unlike the wall friction angle. Highstandard deviation of WS cohesion strength is found for
SRW control sample at 9 kPa consolidation which could
be due to the high cohesiveness of the SRW powder.

3.2 Effects of time consolidation on flour
properties
During storage, the flour gets consolidated in the bin
and the bulk properties change, influenced by both consolidation time and stress. During consolidation, flour
may become gradually more compact when submitted tocompression stress over storage time (Teunou andFitzpatrick, 2000). Large compression stress may result in

230

Table 6 Carr index of wheat flours as affected by time consolidation.

Time (h)HRS

SRWPressure (kPa)

Control

Carr index
35.77 (0.85) a

121035.45 (0.44) a

12

2035.83 (0.58) a

24

10

37.68 (0.88) ab

24

20

38.48

(0.72) bc

46.60(0.39) ab

Control
121046.28 (0.67) ab

12

20

45.38

(2.14) ab

24

10

47.95

(0.22) b24

20

44.24 (0.67) a

Values in parentheses are the standard deviations. Values followedby the same letters are not significantly different when comparedwithin HRS and SRW.

more compacted powder, which increases the particle
contact surface and further affects the bulk powder properties.
SRW flour contains less protein than HRS, thus the
SRW particles are expected to be softer than HRS and theYumeng Zhao et al. / KONA Powder and Particle Journal No. 38 (2021) 226–234

particle deformation scenarios will be different. Duringconsolidation, the effects of time and stress had a positiveeffect on the Carr index as shown in Table 6.
For HRS flour, the Carr index was mainly affected byconsolidation time, and the values increased with time of
consolidation. This could be due to the irreversible plastic
deformation of HRS particles due to time consolidationand the smaller particles filled into the voids when conducting the Carr index measurements. However, for SRW
flour, the Carr index did not change significantly except at
compression duration of 24 h at 10 kPa load. The SRW
flour particle is soft and could elastically deform (reversible) during time-consolidation, therefore, the particle reverted to the original shape when the load was removed,
and the compressibility value did not change. The inconsistency in Carr index values at 10 kPa load when consolidated for 24 h could potentially be because of transient
effects in that the particle did not return to its original
shape.
For both HRS and SRW flours, when comparing 10 and
20 kPa pressure for the same consolidation time, the wall
friction angle significantly increased with increased pressure (Table 7). However, with increased consolidation
time, the wall friction angle decreased significantly for
SRW, from 12.93° to 11.40° under 20 kPa, while increased
from 9.45° to 11.07° for HRS flour.
Flour particles compressed under high consolidationstress could cause particle shape deformation and the increased surface contact area between the probe and bulk
flour could result in increased interparticle force between
particles and the wall. Therefore, the wall friction increased with the increase in pressure from 10 to 20 kPa
for both HRS and SRW flours.
The consolidation time, on the other hand, showed in-consistent results for both HRS and SRW flours. Domianand Poszytek (2005) and Tomas (2000) found that the angle of internal friction decreased with increasing consolidation time. The same trends were found for SRW andHRS flours under 10 kPa. HRS’s wall friction at 24 h and
20 kPa, in particular, increased from 12 h, which could be
because that the HRS was more affected by compression.
As expected, consolidation affected flour permeability(Table 8). With increased consolidation time and pressure, permeability decreased significantly for SRW flours.
For HRS, on the other hand, the lowest permeability wasobserved under 20 kPa pressure compressed for 12 h andthen increased with consolidation time. This could be dueto the differences in cohesiveness and particle size distriTable 7 Wall friction angle of wheat flour as affected by time consolidation.

Time (h)HRS

SRWPressure (kPa)

Control

Wall Friction (°)
11.00 (0.40) a

12

10

8.11

12

20

9.45 (0.39) ab24

10

7.26 (0.31) c

24

20

11.07 (0.29) ab

Control(1.16) c

10.87(0.83) a

12

10

10.27

(0.46) ab

12

20

12.93

(0.59) c

24

10

9.31

(0.09) b

24

20

11.40

(0.62) ab

Values in parentheses are the standard deviations. Values followedby the same letters are not significantly different when comparedwithin HRS and SRW.

Table 8 Permeability of wheat flour as affected by time consolidation.

Permeability (10 –12 m 2)
Time (h)HRS

SRWPressure (kPa)
Control

3 kPa

6 kPa

9 kPa

16.75 (0.70) a

13.03(0.48) a

11.82(0.38) a

12

10

13.23

(1.00) bc

12.35(1.08) ab

11.60(0.97) ab

1220

11.92 (1.03) c

10.41(0.69) b

9.81(0.86) ab

24

10

12.89

11.67

(1.33) ab

11.02(1.24) ab

24

20

15.89 (0.78) ab

13.13 (0.47) a

11.86(0.46) a

9.56 (0.43) a

5.64(0.13) a

4.54 (0.29) a

Control(2.02) bc

12

10

8.73 (0.23) ab

5.17(0.20) ab

3.90 (0.07) ab

12

20

3.19

(0.54) c

2.94(0.53) c

2.66(0.60) c

24

10

7.79 (0.74) b

4.86(0.18) ab

3.80(0.04) b

24

20

2.95

2.52

(0.34) c

2.16(0.19) c(0.27) c

Values in parentheses are the standard deviations. Values followed by the same letters are not significantly different when compared within HRS
and SRW.

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Table 9 WS cohesion strength of wheat flour as affected by time consolidation.

WS Cohesion Strength
Time (h)HRS

SRWPressure (kPa)
Control

3 kPa

6 kPa

9 kPa

0.70 (0.26) a

0.91(0.09) a

1.08(0.10) a

12

10

0.98

(0.42) a

1.14(0.04) a

1.18(0.14) a

1220

1.17 (0.30) a

1.18(0.17) a

1.18(0.10) a

24

10

1.08

(0.40) a

1.11 (0.19) a

1.04 (0.15) a

24

20

0.78

(0.04) a

1.04 (0.10) a

1.08(0.06) a

0.70 (0.13) a

2.26 (0.09) a

3.41(0.57) ab

Control
12

10

0.91

(0.05) a

2.58(0.16) a

4.66 (0.18) a

12

20

0.86

(0.36) a

2.33 (0.36) a

4.10 (0.37) ab24

100.55 (0.07) a

1.96(0.66) a

3.25

24

20

0.72 (0.26) a

1.98(0.40) a

3.66 (0.23) ab(0.79) b

Values in parentheses are the standard deviations. Values followed by the same letters are not significantly different when compared within HRS
and SRW.

bution of the flours. SRW is softer and more cohesive than
HRS, thus under consolidation, the bulk density increased, and bonding occurred between particles (Bian etal., 2015). With increasing bulk density and fewer voids
between particles, the permeability decreased. HRS particles are harder than SRW particles, thus the voids duringconsolidation remained, and the effect of pressure was not
significant.
Table 9 shows the WS cohesion strength values after
consolidation. Only SRW flour, after 24 h of consolidation
at 10 kPa pressure, exhibited a significant difference. This
indicated that consolidation has a limited effect on WS
cohesion strength. Similar to permeability, the SRW bulk
properties are more affected by consolidation because of
the flour particle’s own properties, and after 12 h and
10 kPa consolidation, cohesiveness increased significantly. This result agrees with Iqbal and Fitzpatrick(2006), that the time consolidation does not have an effecton flour’s effective angle of internal friction, which represented the cohesiveness of the powder.

4. Conclusions
HRS and SRW have different compositions, therefore
consolidation and vibration effects on the bulk flour properties differed. Vibration rearranges the particles inside
the container and helps cohesive flour powder form agglomerates, thus the compressibility, cohesiveness, permeability, and wall friction changed. After vibration,
smaller particles filled the interparticle voids and formed
a denser bulk with decreased permeability. Wall friction
demonstrated significant changes before and after vibration. Thus, rearrangement and uniformity of the flour

232

after transportation are attention-worthy. The rearrange­
ment possibly changed the particle size at the location
where WS cohesion strength was measured, which resulted in a decreased WS cohesion strength for SRW
flours. With vibration, segregation of flour can cause inconsistency of flour quality for downstream processing.
But the effect of vibration time on flour segregation is still
an unexplored area of research.
Time consolidation increases interparticle interactions.
Due to the differences in flour hardness, the effect of timeand pressure were not the same for SRW and HRS flours.
SRW flour was affected by pressure change while HRS
flour was affected by storage time. Because SRW flour issofter and more cohesive than HRS, the flour particles
tended to deform, and SRW flour was more compacted
under high pressure.
Particle size and shape, as well as surface chemicalcomposition, could also have changed after consolidation,
thus further studies on single-particle changes are neededin order to better understand the bulk property changes
under time consolidation.

Nomenclature
CE

Circular equivalent

HRS

Hard red spring flour

L

Packed bed of length

M

Torque by Warren-Spring geometry

Q

Airflow rate

Ri

Inner radii of WS geometry (Fig. 3)

Yumeng Zhao et al. / KONA Powder and Particle Journal No. 38 (2021) 226–234

R0

Outer radii of WS geometry (Fig. 3)

SRW

Soft red winter flour

WS

Warren-SpringσNormal stressτShear stress

ΔpPressure drop in the compacted powder bedηAir dynamic viscosity

ρ0

Powder density before compression

ρt

Powder density after compression

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Tomas J., Particle adhesion fundamentals and bulk powder consolidation, KONA Powder and Particle Journal, 18 (2000)
157–169. DOI: 10.14356/kona.2000022
Whitaker S., Flow in porous media I: a theoretical derivation ofDarcy’s law, Transport in Porous Media, 1 (1986) 3–25.
DOI: 10.1007/BF01036523

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Yumeng Zhao et al. / KONA Powder and Particle Journal No. 38 (2021) 226–234

Authors’ Short Biographies
Yumeng Zhao
Graduate research assistant in Agricultural and biological engineering at Purdue University, USA, with research area including particle and particulate system characterization, aerosol modeling, dust explosion prevention.

Poonam Phalswal
Undergraduate student in Dairy Technology at National Dairy Research Institute, India and a visiting undergraduate student at Purdue University, USA.

Abhishek Shetty
Lead Scientist for the Rheology division at Anton Paar USA. Dr. Shetty has over 10
years of working experience in the CPG and Advanced instrumentation space. His expertise lies in the following areas-Complex fluid rheology, Structure-property relationships, Polymer science and dynamics, Microfluidics, Surfactant science and technology,
Solids processing and handling, Powder rheology and characterization, Agglomeration,
Wet Granulation, Foam Granulation, Binders and Additives, and Colloidal suspensions.

Kingsly Ambrose
Associate Professor of Agricultural and Biological Engineering at Purdue University,
USA with research focus on studying and quantifying characteristics of compositionallycomplex solids of biological origin and relating single particle characteristics to bulk dynamics. Application areas include particle and powder characterization, particle modeling,
particle design, and dust explosion prevention. For additional details, please visit the following websites: https://engineering.purdue.edu/FFP and https://engineering.purdue.edu/
CP3

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KONA Powder and Particle Journal No. 38 (2021) 235–250/https://doi.org/10.14356/kona.2021010

Original Research Paper

A Semi-Automated DEM Parameter Calibration Technique of
Powders Based on Different Bulk Responses Extracted from
Auger Dosing Experiments †Bilal El Kassem 1,2, Nizar Salloum 2, Thomas Brinz 2, Yousef Heider 1* and Bernd Markert 1
1 Institute of General Mechanics, RWTH Aachen University, Germany
2 Robert Bosch Packaging Technology GmbH, Germany

Abstract
Discrete Element Method (DEM) proved to be an essential tool to optimize the industrial auger dosing process forpharmaceutical powders. During the DEM parameter calibration process of a certain powder, several parameter
combinations might lead to a similar bulk response, which could also vary for other bulk responses. Therefore,
a methodology is needed in order to narrow down the number of combinations and be at once close to reality
representation. In this study, a vertical auger dosing setup is used as a standard calibration device to extract threedifferent bulk responses, i.e., angle of repose, bulk density, and mass flow rate. Simulations using LIGGGHTS
software package are performed based on Design of Experiments (DoE) by varying four input factors, i.e.,
auger speed, particle-particle and particle-wall static friction coefficients, and particle-particle rolling friction
coefficient. The successful application of multivariate regression analysis (MVRA) results in predicting the bulk
behavior within the studied ranges of parameters. In this regard, clustering the different predicted behaviors of
the three responses together allows to dramatically reduce the admissible parameter combinations. Consequently,
an optimized set of calibrated DEM parameters is chosen, where the simulation results accurately match theexperimental reference data. This simple dynamic calibration tool proves to strongly verify and predict theflowability of free-flowing bulk materials.
Keywords: discrete element method, design of experiment, auger dosing, mass flow rate, multivariate regression
analysis, calibration

1. Introduction
Screw conveyors are utilized extensively in process engineering as mechanisms to transport bulk materials (e.g.,granular materials). As the screw rotates, bulk materials
are dispensed from the container and conveyed along thescrew casing. Although the mechanical system is quite simple, understanding and controlling the material behavior
towards an optimal process might be challenging (Moysey
and Thompson, 2005; Owen and Cleary, 2009; Roberts,1999). In fact, several problems might be experienced if
the machine is not designed properly in connection withthe conveyed material’s nature and mechanical behavior(Clearly, 2007; Owen and Cleary, 2009). These problems
can be defined, for instance, as surging and unsteady flow
rates, inhomogeneity of the product, inaccurate metering†

Received 20 December 2019; Accepted 26 March 2020
J-STAGE Advance published online 30 May 2020
* Corresponding author: Yousef Heider;
Add: Templergraben 64, 52062 Aachen, Germany
E-mail: heider@iam.rwth-aachen.de
TEL: +49-241-80-98282 FAX: +49-241-80-92231

and dosing, product degradation, high start-up torques, excessive power consumption, high equipment wear, variable
residence time, and segregation.

1.1 Screw feeding and DEM
Particle simulation is a popular approach to model andpredict the behavior of bulk materials involved in different
systems. These systems may include several applications
such as storing, transporting or processing granular materials, for instance, sand, semolina, pigments, pharmaceutical powders, crystallized products such as ammonium
sulfate, fertilizers, polyethylene powder, harvest products
or other bulk materials in food, chemical, mining or pharmaceutical industries. In this study, the DEM (Cundall
and Strack, 1979) is utilized to model granular flow at theparticle level. DEM has proven to be an effective and wellestablished approach to study stress and motion of particulate systems (Börner et al., 2016). In fact, DEM isapplied to simulate particle systems in different industrial
applications (Zhu et al., 2008) as e.g., in connection withscrew feeding process. In particular, DEM is used to model

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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the behavior of particles flowing in screw feeders in several
studies leading to a number of valuable findings (Fernandez
et al., 2011; Moysey and Thompson, 2005; Owen and
Cleary, 2009). Different responses obtained from DEM
modeling of screw conveyor process showed a good agreement with analytical and experimental reference results.
These responses include mass flow rate, required screw
power, and particle transfer velocity (Owen and Cleary,
2009, 2010; Shimizu and Cundall, 2001). Pezo et al., 2015
studied the influences of screw length and different screw
design types on the performance of screw conveyor-mixer
during material transport. In this, DEM modeling and experimental validation were performed, where it was shownthat the modified screw conveyor geometry leads to better
mixing quality.
In order to decrease the computation time in DEM, ascaling-up principle based on coarse-graining method isimplemented by increasing the size of particles introducedin the system while maintaining the size of the systemgeometry (Bierwisch, 2009; Ciantia et al., 2016; Sinnott
and Cleary, 2016; Wang et al., 2016). This leads in reducing
the computational costs of the DEM simulations. In this,the number of particles is decreased dramatically, i.e., by ascaling factor of S3. It is important to notice that the upscaling should not affect the velocity of the moving geometries
and the gravitational acceleration.

1.2 Calibration approaches
Notwithstanding the wide range of applicability of DEM,
choosing a set of micromechanical parameters sufficient
for representing the macroscopic behavior of granular material lacks always a calibration process. Therefore, many
research works can be found in the literature and are dedicated to this aim. The conventional calibration approachis the “trial and error”, where in many cases, one factor ischanged at a time to reach a certain relation between the
inputs and outputs of the system. A comprehensive review
that addressed to the angle of repose (AoR), measurements
techniques, suitable applications and the role of several
parameters are presented by Al-hashemi and Al-amoudi,2018. As an assessment for the improvement of DEM
calibration approaches, Coetzee, 2017 addressed various
calibration approaches, which covered over 25 years ofrelated studies. Roessler et al., 2018 developed a standard
calibration scheme for the DEM parameters of free-flowing
bulk materials using a modified drawdown test to solve
the problem of ambiguity. In a sandpile test, Zhou et al.,2002 investigated the impact of particle-particle as well
as of particle-wall coefficients of friction, i.e., static andsliding on the angle of repose. They were able to establish
a power-law relationship between the extracted AoR and
the input parameters and revealed that all friction coefficients followed a positive dependency, whereas particle

236

size followed an opposite one. Aside from the DEM, othermethods, for instance, macroscopic porous media mechanics, can be implemented to obtain the behavior of granularmaterials on larger scales and realize important behaviors
such as fracturing and consolidation (Heider et al., 2018;
Obaid et al., 2017; Pillai et al., 2018). However, thesemethods postulate the continuity of the material and don’t
explicitly describe the interactions between the particles.
For that reason, our underlying study will focus mainly on
the DEM approach.
More efficient approaches are being recently following
systematic data analysis such as Design of Experiments(DoE). Based on DoE, El Kassem et al., 2018 calibrated theAoR value of a pharmaceutical powder by varying the coefficients of rolling friction and restitution. In an advanced
study, El Kassem et al., 2020 developed a systematic numerical approach, using DoE and multivariate regression
analysis (MVRA), to efficiently study the influence ofdifferent DEM input parameters on various bulk responses.
The statistical prediction model of the AoR and porosity,of free-flowing and cohesive powders, accomplished agood quantitative agreement between DEM simulation andexperimental data results. In a roller compaction processapplication, Souihi et al., 2013 utilized an orthogonal partial least squares (PLS) regression to study the outcomesof a reduced central composite face-centered design in
DoE. Yan et al., 2015 employed a parametric multi-levelsensitivity approach to analyze the influence of DEM input
parameters, namely coefficients of friction and restitution,
and Young’s modulus (Y), on AoR and particle flow rate ina discharge system from a flat bottom cylindrical container.
Principal component analysis (PCA) is used to weight thecontributions and sensitivity of each parameter on the bulk
responses. The study showed the significant effect of thecoefficient of static friction and the insignificant impact ofthe particle restitution coefficient and Y. The reduction in Y
values showed insignificant impact, where this is compliedwith (Lommen et al., 2014), in such, decreasing the shear
modulus’ value (e.g. from 107 and 1011 Pa) has no influenceon the DEM results. Relying on experimental measurements, Johnstone, 2010 applied DoE to perform various
calibration and validation techniques.

1.3 Scope of this work
The existence of a large number of parameter combinations outputting the same bulk behavior in simulations
is considered a bottleneck for many DEM users. In thisstudy, a novel semi-automated DEM calibration approachthat focuses on the ambiguity problem is developed. An
auger dosing application is used to output three different
bulk responses, namely angle of repose, mass flow rate,
and bulk density. Unlike most of the studies involving
screw conveying machines, a vertical-oriented micro auger

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is used in this work to represent an auger dosing processof free-flowing pharmaceutical powder. The objective of
this research work is first to perform a parametric study
and then to calibrate free-flowing powder using DoE and
MVRA. A quadratic D-Optimal design model is used tosetup an optimized number of combinations to be simulated. A simulation tool is realized by an open-source
software LIGGGHTS® (Kloss et al., 2012), where thesimulations were carried out in parallel computing toolbox.
An analytical mass flow rate test for dynamic powderdischarge using an auger is derived and verified by our
DEM simulations and experiments. The auger dosing
performance is studied in dependence on auger speed,
particle-particle coefficients of static and rolling friction
and particle-wall static friction coefficient. Although thecoefficient of friction between particles and boundaries isa significant affecting parameter, it is not widely includedin the literature. This work extended the scope of previous studies by including this factor into the parametricstudies. In this study, the level of effectiveness of thesecoefficients is investigated to check how they impact fourstudied responses, i.e., mass flow rate, angle of repose, bulk
density, and translational kinetic energy. Meanwhile, as it
is almost impossible to measure the energy output on the
single-particle scale experimentally, the energy dissipationof the particles is only identified through DEM.
In this work, the DEM parameter combinations are
reduced efficiently to reach an almost solitary combinationof parameters by superimposing three output prediction
contour plots. Calibrations are done based on the bulk behaviors obtained from the experiments and thus the regression analysis model is validated. By this, it is well clarified
that using multiple calibration tests lead to more accurate
and realistic results and thus reduce the ambiguity. As aresult, the simple auger dosing machine can be considered
as a standard calibration device for advanced industrial
applications.

2.1.1 Particle size and shape description
Dynamic image analysis of particle size and shape bymeans of Camsizer XT from Retsch Technology GmbH
was performed. It measured the volume moment mean
(D[4,3]). The D[4,3] identifies around which central point(center of gravity) of the frequency the volume/mass
distribution would rotate. Compared to other particle sizes
calculation methods, the above-mentioned method is characterized in such a way that it does not demand the numberof particles in its estimation. In addition, the Camsizer XTassists in estimating the particle shape, where the particles
are outlined in two-dimensional images in terms of theminimum and maximum Feret diameters (Femin, Femax).
In this, Femin and Femax are the length of the minor and of
the major axis, respectively. Based on ratio of Femin withrespect to Femax one computes the aspect ratio (ASR),
where values in the range [0, 1] reflects the elongation of aparticle and, thus, the deviation from a spherical shape. In
particular, small values represent elongated particles andhigher values represent spherical particles.
According to Li et al., 2002, the circularity or roundness(Ro) is a further factor that determines to what degree a particle possesses a spherical shape. This factor is estimatedbased on the projected area (A) of the particle and the total
perimeter of the projection (P) asRo 

4 π A.
P2

2.1.2 Density
The particle (material or true) density (ρp) was determined using the Ultrapyc 1200e, Automatic Density
Analyzer from Quantachrome Instruments (USA). In this,a pycnometer measures the material density of the powder
samples using an inert helium gas. It measures the volume
by applying the principle of Archimedes of displacement
and the technique of gas expansion according to Boyle’slaw.

2. Materials and methods

2.2 Experimental investigation

2.1 Sample description and characterization

2.2.1 Bulk density

In this research work, a pharmaceutical crystalline lactose
monohydrate powder, called SpheroLac 100, produced by
the German company MEGGLE Wasserburg GmbH & Co.
KG was used. It is a typical dry non-cohesive (free-flowing)
powder used in different applications, such as in capsulefilling, blends, premixes, sachets, and trituration. In thefollowing, methods used to characterize the powder with
its particle size, shape and density are discussed. These
will be used later on in the setup and analysis of the DEM
simulations. The characterization tests were repeated threetimes to ensure repeatability and accuracy of the results.

(1)

In order to visualize the height of the powder bed andcompare the DEM simulation with the experiment, a simple test using a transparent glass tube of an inner diameter
24 mm and a total height of 94 mm was utilized. Initially,a mass of 6 g of SpheroLac 100 was filled inside the tube
where then the volume was recorded and thus the bulk
density (BD) was obtained.

2.2.2 Auger dosing
An auger powder container with an inner diameter of
64 mm and a total height of 224 mm was used in running themass flow rate (ṁ) experiments of SpheroLac 100 powder.

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It consists of a cover, a funnel, an opaque cylindrical glass
tube, a shaft connected to a rotational motor, and an auger.
The geometry and the dimensions of the auger, including
the inner and outer diameters, the pitch and the auger fillingvolume per 1 revolution, which is used to conduct the experiments, are illustrated in Fig. 1. Theoretically, the auger
filling volume represents the maximum volume a material,
which could be filled in one complete rotation.
The auger dosing container encloses a stainless-steel
funnel (1.4404) with an upper diameter of 63 mm, a lower
opening diameter of 6 mm and an inclination angle of 45°.
The auger is connected directly to the drive shaft of an
overhead stirrer rotating motor RZR 2102 control from
Heidolph Instruments (Germany). A laboratory weighingbalance XPE 204 from Mettler Toledo (Germany), used asa catch scale, is placed under the outlet of the auger dosing
container to record the powder mass flow every 0.2 s.
The dosed powders are collected in a container made ofborosilicate 3.3 glass (Fig. 2). The XPE 204 is placed on aRegupol sound 17 isolation pad to avoid the transmissionof any external vibration into it. The XPE 204 has readability down to 0.1 mg and a capacity up to 220 g. HTermsoftware is used on a computer to record the values of mass

flow over time. In addition, an ionization device Static Line
LC is used to neutralize electrostatic charges. The container
was placed at a distance of 80 mm from the bottom of thecatching container, where, initially, was loosely filled with
6 g of the tested powder.
The volumetric mass flow rate (ṁ) is calculated using
the difference in mass (∆m) obtained from the XPE 204
divided by the difference in time (∆t) between consecutive
weighing balance measurements:m g/s m g
.
t s

(2)

To ensure repeatability, the test was repeated three times
at three different auger rotational speeds, i.e., 400, 600 and
800 rpm, where an average of the obtained ṁ was considered as an experimental reference value at each speed. Afterdosing, the formed AoR inside the catching container wasmeasured. The AoR prescribes the slope of a discharged
conical heap of loose bulk solid material (Marigo et al.,2014). It represents a cohesiveness characteristic of a powder (Zhou and Qiu, 2010). It is widely a familiar method tocharacterize powders according to their flowability (Krantz
et al., 2009; Lumay et al., 2012). It is frequently applied tocalibrate DEM simulation parameters as the angle of theheap formed upon the settlement of the powder depends on
the strength of the inter-particulate friction.

2.3 Design of experiment (DoE)

Fig. 1 Illustration of the auger geometry used in the tests.

DoE is an efficient optimized tool to design a matrix
of experiments (in our case simulations) to be executedand consequently generate a reliable process model. It
is mainly used to identify the cause-effect relationshipbetween factors and responses in a studied system orprocess (Sundararajan, 2018). The DoE methodology
was implemented to examine the effects and interactionsof DEM input parameters on the output bulk responses.
This approach helped in facilitating the DEM calibration
procedure. To acquire the maximum quantity of information from the minimal number of simulations, D-Optimal
design, based on the least square method (Eriksson et al.,2008), with a quadratic model type, was adopted using
Cornerstone 6.1.1.1.

2.4 Multivariate regression analysis (MVRA)

Fig. 2 Experimental setup of the auger dosing tests in (a) front CAD
view and (b) laboratory equipment setup.

238

MVRA is a statistical approach used to evaluate the variation of several response variables and hence build a regression model. In the underlying study, this approach was used
to examine and interpret the variation and effect of various
DEM input parameters on the studied bulk responses. By
employing Cornerstone, the collected data values from theexperiments are standardized in such a way that the original variables are scaled to have a mean value of of 0 andBilal El-Kassem et al. / KONA Powder and Particle Journal No. 38 (2021) 235–250

a variance of 1. The standardization step is initially done
since one of the investigated parameters has a different
measurement unit than the others. The coefficient of determination (adjusted R2) was used to describe the goodnessof fit of the model which in turn represents the proportionof the variability of the data explained by the model. A highlevel of confidence (±95 %) was considered in the DoE
analysis. As a representation of the effect of each input parameter on the studied bulk responses, an adjusted responsegraph was used. The response values are tuned to averageout the effects of the other input parameters. Moreover, aPareto graph is applied to figure out the relative range ofeffect of each particular studied DEM input parameters. It
shows the orthogonally-scaled effects of the parameter on
the studied responses. In particular, applying orthogonalscaling to the values of a parameter αi yields scaled values
βi in the range [–1, 1]. This is defined as βi: = (αi – MS)/RS with MS = (αmax + αmin)/2 and RS = (αmax – αmin)/2, see,e.g., (Triefenbach, 2008). Moreover, a prediction model
based on the regression analysis was built, which helped in
predicting and figuring out the best-optimized combination
between the parameters studied.
Fig. 3 illustrates the general flowchart followed in thesystematic calibration approach. From the auger dosing
experiments, the results of the bulk responses to be studied
are considered as the reference targets. The DEM input
parameters are varied according to DoE design model andstudied in the following regression analysis. The prediction
model is then used to calibrate the parameters by selecting
an optimized parameter combination, where a good fit isobtained between the simulation results and the experimental data.

3. DEM simulations
3.1 Contact models
In our DEM simulations, the particles are considered as
rigid bodies, where they have translational and rotational
degrees of freedom assigned to their center of mass. In this,particle interactions are modeled using Newton’s equationsof motion, contact laws for force and overlap relationships. In this study, the soft-particle approach, originallyproposed by Cundall and Strack, 1979 is followed, where
the particles are allowed to overlap with each other (small
deformation) when coming in contact. Consequently, theelastic and plastic deformations and the frictional forces
between the particles can be determined (Zhu et al., 2007).
Various interactions, i.e., forces and torques due to gravity, deformations under collisions, and static and rolling
frictions might take place as two particles i and j endure
contact. In this study, Hertz-Mindlin contact model (Hertz,
1882; Mindlin, 1949) was applied to calculate these resulting forces. Translational and rotational equations of motionof a particle i are expressed by the following equations:

dv i
mi 
dt

 Fijn  Fijt   mig ,

(3)

dωi

dt

 Ri  Fijt  τ ijr  ,

(4)

Ii

where mi, ɡ, Ii, vi and ωi are the mass, gravity vector,
moment of inertia, translational velocity and rotational velocity of particle i, respectively. The interplay between two
particles i and j at time t results in normal and tangential
forces, i.e., Fijn and Fijt , respectively. Ri refers to the vector
between the particle i center and the contact point, where
Fijt is applied. Moreover, τ ijr represent the torque resulting
from the rolling friction between the two particles.
In this regard, the rolling friction in DEM is utilized asa correction parameter that allows to use spherical particle

Fig. 3 General flowchart of the calibration process.

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shapes instead of representing the real shapes of the particles (Iwashita and Oda, 2000; Wensrich and Katterfeld,2012). To represent the rolling friction in our study, thealternative elastic-plastic spring-dashpot (EPSD2) rolling
resistance model was used, which is initially proposed by
Ai et al., 2011 and extended by Iwashita and Oda, 2000.
The mentioned model is implemented to compute thetorque τ ijr ,t t at an incremental time step as| τ ijr ,t t |  r R * | Fijn | ,(5)where μr is the rolling coefficient and R* is the equivalentradius. In this model, the damping torque is disabled forsimplicity.
For the purpose of having a stable integration scheme,
the time step (∆t) was set to a value less than 20 % of thecritical time step (Rayleigh time, TR). TR is calculated
based on the Rayleigh wave propagation, where the elastic
wave propagation from one particle to the adjacent contacting particle can be computed according to the following
equation (Li et al., 2005).
Gt  TR .
0.1631ν  0.8766
R(6)

In this, R, ρ, G and ν are the particle’s radius, density,
shear modulus and Poisson’s ratio, respectively.

Table 1

The considered DEM input parameters throughout the study.

Material parameter/contact model

Symbol

Unit

Value

Young’s modulus funnel
and augera

YF

GPa

200

Young’s modulus catchingcontainerb

YC

GPa

67.8

Young’s modulus particle

Yp

GPa

0.026

Poisson’s ratio funnel andaugeraν

0.28

Poisson’s ratio catchingcontainerb

ν

0.21

Poisson’s ratio particle

ν

0.3

Particle diameter (aftercoarse-graining)dp

Coefficient of restitution
particle-particle

epp

0.2

Coefficient of restitution
particle-wall

epw

0.2

Coefficient of rolling
friction particle-wall

μr,pw

0.2

Coefficients of restitution
and friction wall-wall

0.2

Factory settings

Simulation time step

The DEM numerical simulations were carried out using
LIGGGHTS® -Premium 4.X, which is an open-source
software from DCS Computing GmbH (Linz, Austria).
They were conducted on an eight-node high-performancecluster that uses 64 CPUs (Intel Xeon 2.60 GHz). The
post-processing of the simulations was carried out using the open-access ParaView software, version 5.4.1
64-bit from Kitware Inc. (New York, NY, USA). SolidWorks version Premium 2016 from Dassault Sysèmes(Vélizy-Villacoublay, France) was used to model the 3D
CAD parts applied in the DEM simulations. Thereafter, the3D models were spatially discretized using the open-accessGmsh, version 3.0.6 (Geuzaine and Remacle, 2009).

Acceleration due togravity

The Young’s modulus and Poisson’s ratio values of thefunnel and the auger, as they are considered stainless steel,and the catching container (borosilicate 3.3 glass) wereselected from the literature (Geuzaine and Remacle, 2009;
MakeItFrom, 2019a). Following the recommendations(Govender et al., 2015; Marigo and Stitt, 2015), Young’s
modulus for the particle was reduced within a certain per-240

gNumber of particles

3.2.1 Simulation setup

3.2.2 Simulation conditions and input parameters

690

Contact law parameters

Filling mass

3.2 Simulation procedure and parameters

μm

6
22705

ɡ

s

2.62 × 10 –6

m/s2

9.81

a (MakeItFrom, 2019a), b (MakeItFrom, 2019b)

missible limit in order to reduce computational costs. The
boundary conditions, like coefficients of restitution androlling friction between the particle and the walls (stainlesssteel and glass) were assumed to be constant throughout thesimulations. The particle size was scaled-up six times using
the coarse-graining method identified by Bierwisch et al.,2009. Table 1 presents the applied DEM input parametersin the auger dosing DEM simulations.
On the other hand, one process parameter andthree-particle properties were varied (Table 2) in the context of the DoE: auger rotational speed (ω), coefficient ofstatic friction (μs,pp) and coefficient of rolling friction (μr,pp)
between particle-particle and coefficient of static friction(μs,pw) between particle-wall. Three values were selected
for each of the parameter, which include a low, a center,and a high value, see, (Roessler and Katterfeld, 2019;
Wilkinson et al., 2017) for reference. Based on the DoE,
only 20 simulation runs were required.

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3.2.3 DEM studied responses
Four main factor responses were studied in this work,i.e., angle of repose (AoR), bulk density (BD), mass
flow rate (ṁ), and the overall translational kinetic energy(TKE). The BD was determined inside the funnel after theinsertion and settlement of the particles. After opening thefunnel, ṁ and the average of TKE were computed and thennormalized (NA-TKE) over the total time of dosing (DT)of the particles. The AoR was determined in the catchingcontainer after the particles were settled down at the end of
the dosing process. Fig. 4 shows a cross-sectional view of

the initial state of the funnel filled with 6 g of powder using
ParaView software.
Table 3 presents the DoE matrix followed in performing
the parametric and calibration study. The results cover thedosing of 5.2 g, which is the common linear steady state of theparticle flow (dosing) for all the simulations. This is becauseof having big mass flow fluctuations at the end of the dosing
due to the very low amount of powder left inside the funnel.

Table 2 List of the parameters varied in the DoE simulations related
to the auger dosing.

Parameter

Symbol

Unit

Value

Auger rotational speedωrpm

400, 600, 800

Coefficient of static
friction (par-par)μs,pp0.3, 0.55, 0.8

Coefficient of static
friction (par-wall)μs,pw0.1, 0.25, 0.4

Coefficient of rolling
friction (par-par)μr,pp0.1, 0.4, 0.7

Table 3Fig. 4 Illustration of the initial state of particles filled inside thefunnel.

DoE matrix and DEM results for the considered 20 simulations.

Runω (rpm)

μs,pp

μs,pw

μr,pp

AoR (°)BD (g/cm3)

ṁ (g/s)NA-TKE (μJ/s) DT (s)

1

400

0.3

0.1

0.1

29.3

0.764

0.39950.0340

13.0

2

400

0.3

0.1

0.7

35

0.761

0.37120.0267

14.0

3

400

0.3

0.4

0.1

29.3

0.767

0.25850.0135

20.2

4

400

0.3

0.4

0.7

34.5

0.753

0.25200.0107

20.8

5

400

0.55

0.25

0.4

37

0.742

0.26890.0112

19.2

6

400

0.8

0.1

0.1

33.5

0.748

0.37800.0283

13.8

7

400

0.8

0.1

0.7

40.3

0.730

0.3346

0.0265

15.6

8

400

0.8

0.4

0.1

33.5

0.752

0.24710.0139

21.2

9

400

0.8

0.4

0.7

39.5

0.724

0.23010.0138

22.8

10

600

0.55

0.4

0.1

32.8

0.759

0.3677

0.0362

14.2

11

600

0.8

0.1

0.4

36.4

0.733

0.48720.0594

10.6

12

600

0.8

0.25

0.7

40

0.723

0.37960.0352

13.8

13

800

0.3

0.1

0.7

38.4

0.757

0.66740.0992

7.8

14

800

0.3

0.25

0.4

36.8

0.759

0.55380.0663

9.4

15

800

0.3

0.4

0.1

30.2

0.767

0.49460.0778

10.6

16

800

0.55

0.1

0.1

32

0.753

0.67820.1102

7.6

17

800

0.55

0.4

0.7

41.5

0.734

0.45230.0616

11.6

18

800

0.8

0.1

0.7

40

0.729

0.5974

0.1095

8.8

19

800

0.8

0.25

0.1

33.8

0.754

0.54580.0694

9.6

20

800

0.8

0.4

0.4

36.2

0.735

0.44820.068911.6

241

Bilal El-Kassem et al. / KONA Powder and Particle Journal No. 38 (2021) 235–250

4. Results and discussion
4.1 Material characterization
In this section, the results obtained from the experimental tests are summarized. In particular, Table 4 presents theresults of the particle size, shape and density of the SpheroLac 100 powder. The particle shape in LIGGGHTS was set
as spherical since the powder has high ASR and Ro values.

4.2 Experimental results
4.2.1 Bulk density
Since the funnel used in the auger dosing experiment is
not transparent, the exact height of the powder inside thefunnel cannot be determined. Therefore, a transparent glass
tube was used instead. After filling 6 g of powder inside theglass tube, the average powder height inside the tube was
17.5 mm (Fig. 5). As a result, the average calculated BD in
the experiment is 0.758 g/cm3.

4.2.2 Mass flow rate

The results of the ṁ tests of SpheroLac 100 at thethree rotational speeds are illustrated in Fig. 6. A linear
regression of the mass curves (with capital M) was done,
where the coefficient of determination (R2) of the linear
Table 4

Particle size, shape and density of SpheroLac 100 powder.

SpheroLac 100

D[4,3] (μm)

ASR

Ro

ρp (g/cm3)

115

0.746

0.891

1.5361

Fig. 5The BD experimental result.

regression of the mass curves was equal to 1 in all theexperiments. The slopes of these linear curves represent ṁ,
namely 0.2568 g/s, 0.3744 g/s and 0.5074 g/s at speeds of400, 600 and 800 rpm, respectively. The left graph column
represents the mass M (g) and the right graph column represents ṁ (g/s) where both are plotted over time (s).

4.2.3 Angle of repose
After the dosing was completed, the powder collected in
the catching container formed a heap. For each experiment,
the AoR was determined by considering the average value
between the left and right angles, i.e., θ1 and θ2, respectively.
Table 5 summarizes the results of ṁ and the AoR fromthe auger dosing experiments. The values of ṁ at the threedifferent speeds and the averaged AoR, besides the BD,
are the macroscopic reference values, which were usedin the DEM calibration simulations by validating the prediction models (explained in section 4.4). It is also worth
mentioning, that it was not possible for us to measure the
TKE experimentally. Therefore, TKE will be discussed in
the DEM parametric study but it was not considered as aparameter in the calibration process.

4.3 Parametric study
In this section, the effect of the studied parameters on
multiple bulk responses will be discussed in terms of manner and extent. Fig. 7 illustrates the effects on the studied
responses in an adjusted response graph. Each of the given
box plots (row-wise) corresponds to a bulk response, andeach of them (column-wise) coincides with a DEM input
parameter. The data points shown in Fig. 7 represent the
points obtained from the simulations and the effect drawn(curve) from them. These data points are adjusted to average out the effects of the other factors included in themodel.
The regression models of the four responses have shownhigh adjusted R2 values, which indicates very good fits tothe determined data points. Table 6 lists the values of theadjusted R2 of the four studied responses.

4.3.1 Factors affecting the angle of repose

As can be seen from Fig. 7(a), all the studied parameters have a significant effect on the AoR but with varying
levels of effectivity. For a more comprehensive illustration
Table 5

Fig. 6 The results of the ṁ tests at three different auger rotational
speeds.

242

Summary of the experimental results of the AoR and ṁ.

ω (rpm)AoR (°)

ṁ (g/s)400

33.2

0.2568600

33.40.3744800

33.2

0.5074

Bilal El-Kassem et al. / KONA Powder and Particle Journal No. 38 (2021) 235–250

Fig. 7

Adjusted response of the (a) AoR, (b) BD, (c) ṁ and (d) NA-TKE as a function of the four varied DEM input parameters.

Table 6 Outline of the adjusted R2 values related to the four responses’models.

Adjusted R2

AoR

BD

ṁ

NA-TKE

0.975

0.983

0.998

0.986

of the individual and interactive effects of these parameters, Pareto chart is developed in Fig. 8. It shows theorthogonally-scaled effect of the input parameters on the
AoR. The bars being above the 0-axis signify the positiveeffect (proportional) of the corresponding parameters,
and the ones being below it signifies negative effect (antiproportional). The factors are distributed in descendingorder according to the level of positive or negative effects
from left and right, respectively. Consequently, it can beclearly seen that μr,pp is the most affecting factor on the
AoR in our system, where its increase increases the anglesof the heap. This is contradictory to most of the literature,
where it is stated that the biggest impact on the AoR is theμs,pp. This can be explained by that the introduction of therotating micro-auger in the system caused more a rotationalmotion of the particles around their center. The auger speed
has a small effect on the AoR. Moreover, it is important to
notice the almost negligible effect of μs,pw, which can beneglected from the list of affecting parameters on the AoR.

4.3.2 Factors affecting bulk density

Fig. 9 illustrates the orthogonally-scaled effects on the
BD. According to the parametric study, μs,pp and μr,pp can
be considered the only effecting parameters on the BD inthis study while the μs,pw has an insignificant effect. Theinteractions between μr,pp and both of μs,pp and μs,pw have

Fig. 8

Orthogonally-scaled effects of the model factors on the AoR.

Fig. 9Orthogonally-scaled effects of the model factors on the BD.

a negative impact on the BD, where, as they increase, theBD decreases.

4.3.3 Factors influencing the mass flow rate

Similarly, the orthogonally-scaled effects on the ṁ
are shown in Fig. 10. It is evident how the ω has the243Bilal El-Kassem et al. / KONA Powder and Particle Journal No. 38 (2021) 235–250

largest positive significance on ṁ, whereas μs,pw has thelargest negative impact on it. As the particle-wall friction
increases, the tendency of particle flow decreases dramatically leading to low mass output. It is important to noticethat although the major effect μs,pw is having on ṁ, it has notbeen considered before as a calibration parameter in manyother studies which now reveals its importance to be more
widely studied.

4.3.4 Factors influencing the kinetic energy

In Fig. 11, the influence of the studied DEM input factors on the NA-TKE, is demonstrated in a Pareto graph ofeffects. Once more, ω has the highest positive significant
effect followed by μs,pw, which has the largest negative
impact on the NA-TKE. It is noticeable that the μs,pp is
showing a negligible effect on the NA-TKE. The reason
for this is that the particles are basically being exposed toa rotary motion by the auger, therefore, the translational
contact between the particles was almost not existing.
Moreover, the rotation of the auger caused the particles
to rotate around themselves, rather than rotating aroundone common axis. This can be seen by the presence of
μr,pp as having some impact. Although the particles are
not showing a translational relative motion with respect
to each other, the μs,pw is still proven to be a very affecting
parameter on the NA-TKE. This means that the particles

Fig. 10

Orthogonally-scaled effects of the model factors on the ṁ.

Fig. 11 Orthogonally-scaled effects of the model factors on the NATKE.

244

are sliding on the boundary during dosing. Therefore, it isimportant to draw attention to the importance of calibrating
the roughness of the boundaries in DEM. Moreover, as the
NA-TKE basically represents the dynamics of the particles,
the AoR was measured when the NA-TKE reached thevalue of 0. This is because the AoR should be measured
when the particles get in rest (Qi et al., 2019).

4.4 Experimental validation of predictive models
A prediction model, based on the MVRA results, is built
and used to validate the robustness of the model. As μr,pp
and μs,pp have the highest significant impact on the AoR
and the BD, the contour plots were illustrated based onthese two parameters (Fig. 12a and Fig. 12b). Although,as explained in subsection 4.3.3, ω and μs,pw have thehighest impact on the ṁ, but due to the aim of finding the
optimal parameter combination between the calibrated
parameters by superimposing three contour plots together,
μr,pp and μs,pp were varied on the predicted contour plot ofthe ṁ (Fig. 12c) as well. As an illustration example to findout the best optimized DEM parameter combination, thepredicted contour plots were generated at ω = 800 rpm
and μs,pw = 0.347 (as an optimized value resulting from theoptimization algorithms in Cornerstone) as fixed values.
As can be seen from the above figures, wide ranges ofcombinations between μr,pp and μs,pp in each response leadto delivering the experimental reference values which are
the underlined values in the graphs. Therefore, consideringa single experimental bulk behavior highlights the problemof ambiguous parameter combinations in the calibration
process. Consequently, the three predicted contour plots
in Fig. 12 were superimposed. By this, the number ofadmissible combinations is dramatically minimized, wherea very small intersecting region between the reference
target values was found (see Fig. 13). Taking into accountthe minimized area of permissible combinations, the valid
range for μr,pp is between 0.1 and 0.2 combined with μs,pp
between 0.34 and 0.5. For more clarity, the intersecting
contour lines away from our reference target values areblurred in the graph. The contour lines of the BD and theṁ evidently intersect, whereas the contour line of the AoR(33.2°) is shifted around 0.3° ahead, which is accepted andwithin the range of the prediction model. In the context ofthe superimposing approach, one of the problems that may
occur is the non-intersection between the contour lines(Derakhshani et al., 2015). Roessler et al., 2018 added thatthe measurement error needs to be taken into consideration
to enable a significant overlap of the test results.
Cornerstone software offers an integrated optimization
algorithm to select an optimal unique set of parameters
combination that predicts the response values based on
the experimental reference target values. Based on the
optimization feature algorithm, that aims to match theBilal El-Kassem et al. / KONA Powder and Particle Journal No. 38 (2021) 235–250

target values with minimum deviation errors, a simulation
at 800 rpm was executed to validate our prediction model(confirmation run). In addition, two more simulations, atspeeds 400 rpm and 600 rpm, took place similarly basedon their prediction models as well which are not explained
here. Table 7 lists the different considered combinations
and related bulk responses.
Fig. 14 compares the experimental AoR and the simulation ones. The results show a very close matching between
the simulated heaps and the reference ones.
Using the selected optimized DEM input parameters, a

DEM simulation is performed to calibrate the BD with theexperiment. Fig. 15 represents the powder height of the
BD test in the experiment compared to that of the DEM
simulation, where they both show the same height(17.5 mm) and thus the determined BD was matching(0.758 g/cm3).
Fig. 16 represents the ṁ graphs of the three prediction
simulations, where the results of the DEM clearly matcheswith the experimental findings. This enhances as an

Fig. 13 Superimposed contour plot showing the permissible combinations of the AoR, BD, and ṁ that fulfill the experimental reference
values.

Fig. 14 Comparing the AoR of the (a) experiments and the (b) DEM
simulations.

Fig. 12 Predicted contour plots of the (a) AoR, (b) BD and the (c) ṁ byvarying μs,pp and μr,pp and having ω and μs,pw fixed.
Table 7

Fig. 15(b).

The BD results in experiment (a) and in the DEM simulation

DEM parameter combinations of the prediction model and the bulk responses.

Runω (rpm)

μs,pp

μs,pw

μr,pp

AoR (°)BD (g/cm3)

ṁ (g/s)NA-TKE (μJ/s)

DT (s)

21

400

0.523

0.375

0.1

33.1

0.757

0.25420.0119

20.6

22

600

0.313

0.36

0.32

33.8

0.758

0.384

0.0313

13.6

23

800

0.51

0.347

0.1

33.5

0.757

0.50530.0692

10.4

245

Bilal El-Kassem et al. / KONA Powder and Particle Journal No. 38 (2021) 235–250
Table 8 Evaluation of the calibrated parameter combinations of thesimulation results compared to that of the experiments.

ω (rpm)Bulk
behavior

Experiment

Simulation Deviation
(%)

400

AoR (°)

33.2

33.1

–0.3

BD (g/cm3)

0.758

0.757

–0.13

ṁ (g/s)0.25680.2542–1.01

DT (s)

20.4

20.6

0.98

AoR (°)

33.4

33.8

1.2

BD (g/cm3)

0.758

0.758

0

ṁ (g/s)0.3744

0.384

2.56

DT (s)

14

13.6

–2.86

AoR (°)

33.2

33.5

0.9

BD (g/cm3)

0.758

0.757

–0.13

ṁ (g/s)0.50740.5053–0.41

DT (s)

10.4

10.4

0

600

800

5. Conclusions

Fig. 16 Validating the ṁ of the DEM with the experiments at speeds(a) 400 rpm, (b) 600 rpm and (c) 800 rpm.

additional validation to our systematic MVRA using theauger dosing as a standard calibration device. It is shown inthe ṁ graphs, especially with speeds 600 rpm and 800 rpm
that, at the beginning of the powder flow, there is a small
deviation between the experiment and the simulation. In
fact, this is due to the acceleration of the motor until theauger filling volume is full with powder.
As it has been pointed out, the regression prediction
models qualitatively and quantitatively predicted theresults of the three experimental calibration tests. Table 8summarizes the results from the validation process andcompare them with the experimental reference values.
The maximum deviation is 2.86 % (in the case of theDT), where the overall mean deviation of the whole responses (12 results listed in Table 8) is 0.87 %.
Compared to (Roessler et al., 2018), our approach seems
to be more efficient and reliable, where we ran only 20
simulations (instead of 384 in their case) to reach the sameaccuracy of the results. Thus, our systematic approach is an
optimized procedure that saves time and money using DoE
and MVRA.

246

In this work, a standard calibration method for calibrating non-cohesive powders by tremendously reducing theambiguity of the DEM parameters selection is established.
It is based on an auger dosing principle, which calibrates
three bulk material properties at the same time, namely
AoR, ṁ and BD in relation to the auger speed, particleparticle beside particle-wall static friction coefficientsand particle-particle rolling friction coefficient. The study
analysis was done through a highly systematic statistical
approach using MVRA. With only 20 simulations, aparametric study of DEM input parameters on the bulk behaviors was performed followed by generating very robust
prediction models. This parametric study explained how
the aforementioned bulk behaviors depend highly on theparticle level interactions and properties. The simulation
results used to build a prediction model showed how ahigh number of different parameter combinations can leadto the same bulk responses. This study proved that using
the superimposing principle by combining the prediction
contour plots of the bulk responses evidently lead to a very
narrow region that matches greatly with the experimental
reference values. One optimized solution combinationof DEM parameters through the prediction model was
selected, where their results agreed significantly with theexperimental data. A number of conclusions extracted fromthis study can be summarized as follows:
・ Individual calibration tests are not sufficient to calibratea material in DEM where the ambiguity for the admissible parameter combinations is high.
・ The auger dosing machine can be used to extract threeBilal El-Kassem et al. / KONA Powder and Particle Journal No. 38 (2021) 235–250

reference bulk responses, i.e., AoR, BD, ṁ.
・ Using the D-optimal design model, the superimposing
principle of three predicted contour plots from the
MVRA and the optimization algorithm in Cornerstone
proved to be a robust approach to eliminate ambiguity.
・ μr,pp was shown to have an overwhelmed effect overμs,pp.
・ Using the presented auger dosing machine, a uniqueoptimized parameter combination was identified andexperimentally validated.
For the future work, process optimization should be
carried out by studying and validating more material properties and bulk behaviors. In addition, the study should be
extended to cover cohesive powders.

Acknowledgements
This research did not receive any specific grant fromfunding agencies in the public, commercial, or not-forprofit sectors.

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Authors’ Short Biographies
Bilal El Kassem
Bilal El Kassem, M.Sc., is a PhD candidate at Robert Bosch Packaging Technology
GmbH, in Stuttgart, Germany, under the supervision of Prof. Bernd Markert from RWTH
Aachen University. He received his B.Sc. degree in Mechatronics Engineering from Rafic
Hariri University, Lebanon in 2012, and received his M.Sc. degree in Computer Aided
Production in Mechanical Engineering from RWTH Aachen University, Germany, in 2016.
His current research focuses on optimizing auger dosing process using discrete element
methods and analyzing the experimental powder flow behavior using regression analysis.
Nizar Salloum
Nizar Salloum, M.Sc., is a PhD candidate at Robert Bosch Packaging Technology GmbH,in Stuttgart, Germany, under the supervision of Prof. Stefan Heinrich from Hamburg University of Technology. He received his B.Sc. degree in Mechanical Engineering from LebaneseInternational University in 2016, and received his M.Sc. degree in Computational Mechanicsof Materials and Structures from University of Stuttgart, in 2019. His current research focuses on optimizing mixing and filling processes of pharmaceutical powders using discreteelement methods.

Thomas Brinz
Dr. Thomas Brinz is a department leader at Robert Bosch Packaging Technology GmbH,in Stuttgart. He received his Diploma degree in Chemistry from University of Ulm, in
1999, and received his PhD degree in Chemistry at the same university, in 2003. His has 16
years of industrial expertise in lab automation solutions and high throughput technologies
in pharmaceutical applications.

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Authors’ Short Biographies
Yousef Heider
Dr. Yousef Heider is working since May 2014 as Lecturer at RWTH Aachen University
in Germany. He was between Oct. 2018 and Sept. 2019 a visiting Associate Research
Scientist at Columbia University, USA, and worked between July 2011 and April 2014 in
the field of renewable energies (R&D) at the company Ed. Zueblin AG in Germany. He
received his Ph.D. degree in Computational Porous Media Dynamics from the Universityof Stuttgart, Germany, in 2012 under the supervision of Prof. Wolfgang Ehlers. He holds
his Master’s degree (2007) in Computational Mechanics of Materials and Structures fromthe University of Stuttgart.

Bernd Markert
Prof. Bernd Markert is full professor at RWTH Aachen University and director of the Institute of General Mechanics since 2013. He received his diploma degree in Civil Engineeringfrom the University of Stuttgart in 1998 and finished his PhD degree also there under thesupervision of Prof. Wolfgang Ehlers in 2005. He completed his habilitation (venia legendi
and facultas docendi) for Mechanics in 2011. His current research focuses on the broad fieldof Digital Engineering involving advanced modeling and simulation methods as well as
computational intelligence.

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KONA Powder and Particle Journal No. 38 (2021) 251–259/https://doi.org/10.14356/kona.2021002

Original Research Paper

The Properties of Kaolin from Different Locations
and Their Impact on Casting Rate †Mervat Said Hassan Badr 1, Shuaishuai Yuan 1, Jiaqi Dong 1, Hassan El-Shall 1, Yamile A.
Bermudez 2, Diana C. Ortega 2, Jorge E. Lopez-Rendon 2 and Brij M. Moudgil 1*
1
2

Center of Particulate and Surfactant Systems, Materials Science & Engineering, University of Florida, USA
Sumicol S.A.S., - Suministros de Colombia, Colombia

Abstract
It has been well known that mineral samples from different locations and origins can exhibit a significant shift intheir properties and behavior. The present study of three samples of kaolin from a wide set of origin of deposits,
composition, and ceramic properties, provided an important and perhaps a unique opportunity for investigating
the interdependence of mineralogy, chemical composition, particle morphology, and surface property with theirrheological behavior in ceramic applications such as casting rate. The X-ray diffraction patterns of kaolin samples#2 and #3 suggested low crystallinity with Hinckley Index (HI) ranging between 0.78 and 0.8. On the other hand,kaolin sample #1 was highly ordered with HI of about 1.21, and it had higher quartz content. This free quartz
could enhance the permeability and hence increase the casting rate. The abundance of divalent ions (Ca2+ andMg2+) in samples #2 & #3 could result in the collapse of the electrical double layer and reduction of zeta potential,
consequently, coagulation of the particles leading to an increase of viscosity and dispersant demands. The
morphology study suggested the platelet particles in samples #2 & #3 would lead to slower dewatering, thus,
lower casting rate than that of the blocky (lower aspect ratio and narrower size distribution) particles in sample #1.
Keywords: kaolinite, kaolin, clay, powder, particles, casting

1. Introduction
Kaolin has a global market with an estimated value of
5.42 billion USD in 2018 (Kumar S., 2019). The market
size is expected to grow continuously due to the increasing demand of ceramic products in a wide variety of applications (Dondi M. et al., 2008), such as whiteware(Sanz A. et al., 2018), paper (Frías M. et al., 2015), construction (Heah C. et al., 2011), paint (Ahmed N.M.,
2013), drilling fluid (Au P.-I. and Leong Y.-K., 2013), etc.
Furthermore, kaolin has great potential to be tailored formore innovative products including rapid-casting clays,engineered paper with kaolin coating, and nanocomposites (Dondi M. et al., 2003; Murray H.H., 2000). Theseadvanced applications require more in-depth knowledgeof the structure-property-behavior relationship of kaolin,which is not fully understood. In fact, it is difficult tocomprehend the complexity because kaolin samples ex†

1
2*

Received 11 April 2019; Accepted 9 May 2019
J-STAGE Advance published online 2 November 2019Gainesville, FL 32611, USA
Carrera 48 No.72 Sur 01, Antioquia, Sabaneta, Colombia
Corresponding author: Brij M. Moudgil;
E-mail: bmoudgil@perc.ufl.edu
TEL: +1-352-846-1197

hibit different particle size, size distribution, shape, chemical composition, surface chemistry and charge due totheir diverse geological conditions and processing parameters.
The main scope of the present study is to investigate
the kaolin properties that impact the rheological behavior.
The key characteristics of the kaolin samples include
mineralogy, the degree of kaolin crystallinity, chemistry,morphology, particle size, size distribution, shape andshape distribution, surface chemistry, interfacial properties, and the interaction with various deflocculants or dispersants.

2. Materials and methods
2.1 Materials
Three kaolin samples #1, #2, and #3 were carefully selected. Sample #1 was coarse-grained kaolin that had
been engineered to achieve improved casting rate. Thiskaolin is currently commercialized by an American kaolin producer. The original geological source of the primary kaolin was from Georgia (USA). Sample #2 was
wet-processed kaolin from Colombia, South America.

Copyright © 2021 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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The raw material for this sample was primary kaolin. Wet
processing of this raw material resulted in a kaolin slurry
which, in turn, was filter pressed to obtain the kaolin represented by Sample #2. Sample #3 was produced from themechanical processing of Sample #2.

2.2 Methods
X-ray diffraction (XRD). The phase of each kaolin sample, as well as the crystallinity, was characterized using
Panalytical X'Pert Powder with a 1400 W Cu X-ray tube.
Thermal gravimetric analysis (TGA). The weight loss
due to dehydroxylation, phase transition, or thermal decomposition of each kaolin sample was measured and analyzed using TGA/SDTA851e.
Scanning electron microscopy (SEM). The texture, particle morphology of the kaolin sample was analyzed using
the micrographs obtained by Hitachi S3000 SEM.
The zeta potential of kaolin particles was measured using Zeta Reader Mark 21.
The casting rate was measured following the protocol
described by Eygi et al. (Eygi M.S. and Ateşok G., 2008)

3. Results and discussion
3.1 Mineralogical composition
The X-ray diffraction patterns of the three kaolin samples are illustrated in Fig. 1. Samples #2 and #3 were observed to be disordered and poorly crystalline andcontained traces of quartz and very sparse mica (illite).
Their Hinckley Index (HI)—a measure of crystallinity ofFig. 1252

XRD patterns of kaolin samples #1, #2, and #3. Sample#1 showed very sharp and narrow reflections lines andalmost very smooth background revealing the high degree of crystallinity Ka = kaolin; Qz = Quartz, II = Illite. Samples #2 & #3 showed broad, asymmetricalpeaks towards low 2θ value, which suggested an average smaller crystallite size based on the increased
width of the diffraction peaks.

kaolin ranged between 0.78 and 0.8. Kaolin was indicatedby its characteristic reflection peaks at 7.14 Å (001), and3.56 Å (002), quartz (SiO2) at 3.33 Å and illite at 10 Å.
Sample #1 was highly ordered with HI of almost 1.21
and characteristic peaks at 7.14 Å (001) and 3.56 Å (002),
which suggested higher quartz content compared withsamples #2 and #3.
The measurement of HI (degree of crystallinity of kaolin) is shown in Fig. 2 using the range of 2θ 19–22° of
kaolin samples. The calculated I (020)/I (1Í0) ratios ofstudied kaolin samples were 0.63, 1.09 and 1.10 for samples #1, #2, and #3, respectively. The smaller the value,
the higher the crystallographic order of kaolin (Qiu X. etal., 2014). The average flake thickness of kaolin along thec-axis was calculated using the Debye-­Scherrer equation,LKλβ cos θ(1)

in which L is the crystallite size; K is the Scherrer constant that depends on the shape and size distribution of
the crystal; λ is the wavelength of incident X-ray; β is thefull width at half maximum (FWHM); θ is the Bragg angle. The estimation of crystal size using FWHM of (001)peak is shown in Fig. 3. Table 1 summarizes the calculated results of kaolin samples from XRD patterns. According to the FWHM (001) data of the three kaolinsamples, the average flake thickness along the c-axis ofsamples #1, #2, and #3 were 517 Å, 160 Å, and 152 Å, respectively (as shown in Table 1). It was evident that sample #1 had thicker flakes than samples #2 and #3, which is
supported by the SEM images.
From the XRD patterns of kaolin samples, it was clearthat sample #1 was highly ordered kaolinite with HI of
1.21 and average flake thickness along the c-axis of 517 Å;
while kaolin samples #2 and #3 had HI of 0.8–0.76 and an
average flake thickness along the c-axis of 152–160 Å, respectively. Moreover, the narrow and sharp (001)Fig. 2

XRD patterns at 2θ 19–22° of kaolin to measure thedegree of crystallinity of kaolin (Hinckley Index, HI)
and crystallographic order using I (020)/I (1Í0) ratios.

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Fig. 3
Table 1The FWHM measurement of the (001) XRD peak revealed the crystallite size of kaolin particles.

Calculated results of kaolin samples.
Sample #1

Sample #2

Sample #3

HI

1.21

0.80

0.76

I(020)/I(1Í0)

0.63

1.09

1.10

FWHM (001)0.151°

0.334°

0.32°

Crystallite Size

517 Å

160 Å

152 Å

Number of Unit
Layer

76

28

32

diffraction peak with an FWHM of 0.15° was characteristic of sample #1. Whereas the FWHM (001) of samples #2
and #3 was about 0.33°. Poor crystallinity of samples #2
and #3 kaolin resulted in irregular morphology and subsequently in poor rheological behavior.

Fig. 4

Differential thermal analysis of kaolin samples.

3.2 Thermal gravimetric analysis (TGA)
3.2.1 Low-temperate endothermic region
The peak observed in TGA curves of samples #2 and#3 at 53 °C could be due to dehydration of poorly crystallized kaolin (#2 and #3) or due to the loss of adsorbed water (Δm = 2.211%). It could also be due to the trace of
hydrated halloysite (its characteristic peak at 10 Å overlapped with illite peak).
However, low-temperature endothermic peak at 252 °C
in DTA curves of samples #2 and #3 could be attributed
to amorphous materials–goethite FeO(OH) or gibbsite
Al(OH)3 (Δm = 0.941%). Samples #2 and #3 seemed to be
stained with iron. Also Fe2O3 content of these samples
was higher than in sample #1. Generally, highly crystalline goethite is known to produce a maximum at 280 °C.
However, low crystalline goethite is known to produce apeak at 250 °C in TGA curves (Fig. 4 and 5).
Additionally, sample #1 had shallow losses below

Fig. 5Derivative thermos-gravimetric curves of the samples.

200 °C (Δm = 0.585%) as compared to samples #2 and # 3.
This could be the result of a reasonable degree of crystallinity, in the case of sample #1, whereas the weight losses
observed in the other samples could be attributed to thepresence of less ordered kaolinite, halloysite and/or amorphous materials.

3.2.2 Medium-temperature–endothermic region
The DTA curve for kaolinite showed an endothermic

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Fig. 6

Thermo-gravimetric curve of kaolin Sample #1.

peak in the range 400–600 °C due to the dehydroxylationof samples #2 and #3. These peaks were associated with aweight loss of 11 % contaminated kaolinite (Fig. 6). In
the case of sample #1 kaolin, the dehydroxylation peaktemperature ranged between 440–700°C and a 9.6 %weight loss. The dehydroxylation of sample #1 comparedwith that of samples #2 and #3 could be attributed to thedifference in the degree of crystallinity as well as the degree of substitution of Al in the octahedral sheet by Fe invarious samples. Low degree of crystallinity and the relatively higher degree of structurally substituted Fe caused
a low dehydroxylation temperature of samples #2 and #3.
Sample #1 was distinguished mainly by the decrease inpeak intensity around 530 °C indicating lower kaolinite
content. Also, the peak was broader and more curved to
the right for samples #2 and #3. These characteristics
could be attributed to the higher thickness of the crystals
and/or the higher degree of crystallinity.

the maximum mass loss was 533 °C. On the other hand,
the mass loss of samples #2 and #3 was 12.3455 % that
occurred at 520 °C. The mass loss for samples #2 and #3
was higher compared with that of sample #1 and could becorrelated to the higher percentage of kaolin in samples#2 and #3 (90.18 %) as compared to 80.5 % for sample #1.
The metakaolin was a disordered layer structure withsome hydroxyls present (1/8) and probably had the same
Al/Si as kaolinite plus the vapor phase which was considered to be pure H2O (Roy R. et al., 1955). Metakaolin
eventually becomes amorphous with additional heating(Brindley G. and Nakahira M., 1959).
The conversion of quartz during the calcination of kaolin was masked by the big and very broad dehydroxylation peak of clay minerals generally within the same
temperature range. So, the calculation of quartz and illite
associated with kaolin of studied samples should be basedon XRD patterns.

3.2.3 High-temperature-exothermic region

3.3 Phase and chemical analysis

The main difference was observed at the exothermic
peak around 1000 °C (Fig. 4). This peak was wider andless pronounced in samples #2 and # 3 than that for Sample #1. Besides, it developed at a temperature of 10–15 °C
lower than for Sample #1. One possible explanation forthis difference in DTA behavior would be a higher degreeof crystallinity and, eventually, a larger crystallite thickness for Sample #1 in comparison to samples #2 and #3.
The dehydroxylation of kaolinite occurred between 600–
700 °C along with the formation of metakaolin. The phase
was further transformed into either γ-alumina or
aluminum-­silicon spinel with the presence of amorphoussilica.
The major loss in mass was observed in the temperature range from 400 to 900 °C indicated by an endothermic peak in Fig. 4. The total mass loss observed on the
TG curve was 11.035 % for sample #1 (Fig. 6). DTG andDTA curves of sample #1 showed that the temperature at

254

The chemical analysis of the investigated samples given
in Tables 2 & 3 agreed with the mineralogical composition of the samples determined by the X-ray diffraction(Figs. 1–3) and DTA-TG (Figs. 4–6) analysis, as well as
confirmed by the SEM micrographs (Figs. 9–11). Basedon the normal weight loss at 400–700 °C corresponding
to dehydroxylation of kaolinite, the kaolin/halloysite content ranged between 78–80 % for sample #1 as comparedwith 87–89 % for samples #2 and # 3. The higher quartz
and illite content in sample #1 may explain the lower content of kaolin in sample #1.
On the other hand, samples #2 and #3 had higher Fe2O3,
TiO2, CaO, MgO compared with sample #1. Generally, Fe
could be located in two forms: 1) Fe- substitution in octahedral and tetrahedral sheets of kaolin, or 2) as amorphousiron (staining iron). Also, the Fe had a significant influence on the rheological properties of kaolin. High K 2O%

Mervat Hassan Badr et al. / KONA Powder and Particle Journal No. 38 (2021) 251–259

Table 2

Chemical composition of kaolin samples.

Component (%)

Sample #1

Sample #2

Sample #3

SiO2

52.9

45.8

45.6

Al2O3

33.1

37.0

36.8

Fe2O3

1.20

2.17

2.18

TiO2

0.37

0.58

0.58

CaO

0.00

0.02

0.01

MgO

0.07

0.15

0.16

Na2O

N.D

N.D

N.D

K 2O

0.74

0.47

0.46

BaO

0.01

<0.01

0.01

P2O5

0.01

0.01

0.01

MnO

0.02

0.02

0.03

SO3

N.D

N.D

0.001

PPI de 110 °C a
1000 °C

11.7

13.9

14.2

Table 3Mineralogical composition of kaolin samples.

Minerals% (Semi-Quantification)#2 & #3. This could affect the interaction between clay
particles in aqueous suspension, thereby influencing theirflocculation properties.

3.5 Physical properties
3.5.1 Particle sizes and size distribution
The particle size distribution of the three samples issummarized in Table 4, which did not reveal any significant differences.

3.5.2 Specific surface area (SSA) and cationexchange capacity (CEC)
The higher SSA and CEC (methylene blue index, MBI)of samples #2 and #3 could be attributed to the imperfectly stacked poorly crystallized kaolin with a lot of
curly, rough and eroded edges compared to sample #1(well-crystallized books of kaolin). High CEC of samples#2 and #3 using MBI could be attributed to the exposureof more charged sites for the exchange to occur. The SSA
and CEC of kaolin appeared to increase with a lower degree of crystallinity as refer to Table 4.

3.5.3 Morphological Analysis

Sample #1

Sample #2

Sample #3

Quartz (Qz)

10–12

1–3

1–3

Mica/Illite

7–9

4–6

4–6

Gibbsite (G)

N.I.

1–2

1–2

Kaolinite/Halloysite

78–80

87–89

87–89

Others (Fe, Ti oxides/
Fe hydroxides)

<1

1–2

1–2

in sample #1 compared with the other two samples revealed the presence of mica mineral. Illite impurity was
indicated in XRD patterns of kaolin.
The presence of divalent ion in terms of Mg followed
by Ca in abundance in samples #2 and #3 kaolin could result in the compression of the electrical double layer resulting in the lower zeta potential of these samples. Low
zeta potential would result in higher interaction between
clay particles and an increase of viscosity and finally, theflocculation of clay particles.

3.4 Zeta potential
The zeta potential of the three kaolin samples was measured at specific pH to obtain the isoelectric point (IEP)
as plotted in Fig. 7. The IEP of all three samples were interpolated to be 3~4, which agreed with the literature values (Au P.-I. and Leong Y.-K., 2016). Sample #1 exhibiteda slightly higher isoelectric point as compared to samples

SEM m ic rog r aph s ( F i g s . 8 –10) r eve a le d t he

Fig. 7
Table 4

Zeta potential of the Kaolin samples.

Physical properties of kaolin samples.

Sample#1#2#3

SSA (m 2/g)

8.5

26.3

24

MBI (meq/100g)

1.6

7.1

6.7

DV 10 (μm)

0.37

0.35

0.35

DV 50 (μm)

2.3

2.21

3.57

DV 90 (μm)

15.67

11.34

13.06

% Coarse (100–9.21) μm

18.8

15.1

20.2

% Medium (9.21–0.96) μm

50.8

48.8

55.4

% Fine (0.96) μm

30.4

36.1

24.4

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Fig. 11 Casting rate of different kaolin samples.
Fig. 8The SEM image of kaolin sample #1 showed blocky
particles with relatively low aspect ratio, which exhibited faster dewatering and high casting rate.

Fig. 9The SEM images of sample #2 showed the thin-platelet
with a high aspect ratio, which was responsible forslow dewatering and casting processes.

phology could have enhanced the dewatering and casting
rate of sample #1.
The morphology of samples #2 and #3 (Figs. 9–10) was
different from sample #1. This morphology revealed thepoorly crystalline structure of these samples. The platelets had curly, rough, highly eroded edges with high aspect ratios. The eroded edges revealed the partial
dissolution of this kaolin and explained the presence ofamorphous materials that covered the platelets. Thesesurface defects were strongly associated with the adsorption characteristic of this kaolin. The packing of plate-likeparticles (samples #2 & #3) could result in a lower casting
rate of the samples than that of the sample with blocky
particles (lower aspect ratio). The densely-packed platelets of samples #2 and #3 would lie flat in the casting
mold, thereby slowing down the dewatering process.

3.6 Slip casting performance
The present investigation offered a good opportunity to
study the property-performance relationship of kaolin. It
was observed that the slip casting rate of kaolin sample #1
was significantly higher as compared to samples #2 & #3
(Fig. 11) in which the particles were more platy (higher
aspect ratio) and exhibited lower crystallinity. The low
casting rate of kaolin samples #2 & #3 also could be attributed to the high slip viscosity and the abundant divalent cations. For these reasons, kaolin samples #2 & #3
were less suitable for most of the traditional applications
unless they are further treated or modified specifically.

Fig. 10 The SEM images of sample #3 showed the thin-­platelet with a high aspect ratio, which was responsible for slow dewatering and casting processes.

morphological characteristic of kaolin samples.
Kaolin sample #1 had revealed more regular pseudo-­
hexagonal edges smooth surface, thicker flakes, andsmaller diameter to thickness ratio (Fig. 8). During thegrinding process, these particles tended to become morerounded, resulting in better packing. This blocky mor-

256

4. Conclusions
Three kaolin samples from different geological origins
were characterized and the relationship between theirproperties and slip casting performance was studied.
Overall, it was found that kaolin sample #1 exhibited asignificantly higher slip casting rate than the other two
samples. Characterization showed that kaolin sample #1
had the highest crystallinity among the three samples
studied, and its particles exhibited the most globularMervat Hassan Badr et al. / KONA Powder and Particle Journal No. 38 (2021) 251–259

shape as compared to the other samples. The globular
shape of the particles could be one of the key elementsthat were beneficial to the dewatering process leading tofaster slip casting. The thermal gravimetric analysis confirmed that kaolin sample #1 exhibited less weight loss in
low to medium temperature endothermic regions than theother two samples. It could be due to less moisture content of sample #1 and thus less dehydroxylation due to ahigher degree of crystallinity. Nevertheless, further investigation is needed to fully understand the complex natureof different kaolins and their rheological behavior.

Acknowledgments
The authors acknowledge the financial support fromthe Center for Particulate and Surfactant Systems (CPaSS)at the University of Florida, National Science Foundation(NSF Grant No. 1362060) and the industrial partners of
CPaSS. Any opinions, findings and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the
National Science Foundation/Sponsors.

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Authors’ Short Biographies
Mervat Said Hassan Badr
Dr. Mervat S. Hassan Badr is a retired Professor and Head of Ore Evaluation Laboratory at the Central Metallurgical Research and Development Institute (CMRDI), Cairo,
Egypt. Dr. Hassan has expertise in the field of applied mineralogy and rheology, specifically synthesis, modification, and characterization of clay minerals and advanced ceramic materials. She has done extensive work on the clay minerals for environmental
and agricultural applications, as well as for advanced paper and drilling industries.

Shuaishuai Yuan
Shuaishuai Yuan is currently a Ph.D. candidate at McGill University, Canada. She received her B.Eng. in Materials Science and Engineering from Jiangsu University, China
in 2014, and M.S. degree in Materials Science and Engineering from the University of
Florida, USA in 2016. During May 2015–April 2016, she worked under the supervisionof Prof. Brij Moudgil and Dr. Parvesh Sharma at the Center for Particulate and Surfactant Systems (CPaSS), UF focusing on engineering functionalized clay particles forvalue-­added products.

Jiaqi Dong
Jiaqi Dong received his B.S. in Materials Science and Engineering from Illinois Instituteof Technology in 2013. He then attended University of Florida as a graduate student andreceived 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 is metallic
nanoparticle synthesis and functionalization using fluidics.

Hassan El-Shall
Dr. Hassan El-Shall was a Professor Emeritus, until his passing away in 2017, at the Department of Materials Science and Engineering, University of Florida. He had been serving
as Associate Director for Research at the Particle Engineering Research Center, since 1994.
He also served as Associate Director at the Florida Institute of Phosphate Research from1986–1992. Dr. El-Shall possessed 39 years of diverse experience in research, teaching,
management and industry experience in the areas of applied surface and colloid chemistry,mineral processing, chemical and engineering. Dr. El-Shall had published over 165 technical papers in prestigious journals including Powder Technology, Mineral and Metallurgical
Processing, and Journal of Mineral Processing.

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Authors’ Short Biographies
Yamile A. Bermudez
Yamile A. Bermudez studied chemical engineering at Antioquia University, Colombia
and received her M. Sc. in Materials and Processes from the National University ofColombia. She joined Sumicol S.A.S., one of the companies of the Corona CeramicGroup in Colombia in 2006 as a lab technician and was promoted to R&D engineer in2010. After spending eight years in this position, she was transferred to the sanitary waredivision of Corona, where she is currently a process engineer in charge of technical aspects of sanitary ware production.

Diana C. Ortega
Dr. Diana C. Ortega studied geology at EAFIT University, Medellín, Colombia andreceived her M.Sc. in Minerals Engineering from Camborne School of Mines, UK and
her Ph. D. in Materials Science and Engineering from the National University ofColombia. Diana joined Sumicol S.A.S., an industrial minerals producer, in 1993 as a researcher in industrial minerals applications and has been with Sumicol since then. She iscurrently head of the recently created Minerals Technical Center at Sumicol S.A.S. anddirector of IDIMAP, Industrial Research Group on Materials Design from Minerals andProcesses.

Jorge E. Lopez-Rendon
Jorge E. Lopez-Rendon studied Geology at the Mining Faculty, National University ofColombia. Then he joined Sumicol S.A.S., an industrial minerals producer and spent a tenyear period as an exploration geologist and head of the minerals research lab, after whichtime he founded the Geology Department of EAFIT University and was there for ten years
as Director and researcher. Subsequently, he came back to Sumicol as Manager of the
R&D Division and was in charge of several industrial minerals processing and industrial
application projects for fifteen years. He currently is a consultant in industrial minerals for
Sumicol and other companies.

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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Original Research Paper

Fabrication and Characterization of Prussian Blue-Derived
Iron Carbide-Iron Oxide Hybrid on Reduced Graphene
Oxide Nanosheets †Alowasheeir Azhar 1‡, Jacob Earnshaw 2‡, Mohamed Barakat Zakaria 1,2*, Ping Cheng 2,
Yusuf Valentino Kaneti 1, Md. Shahriar A. Hossain 2,3, Saad M. Alshehri 4,
Tansir Ahamad 4, Yusuke Yamauchi 2,5,6 and Jongbeom Na 1,2*
1 International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Japan
2 Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Australia

3 School of Mechanical & Mining Engineering, Faculty of Engineering, Architecture and Information Technology (EAIT), The University of

Queensland, Australia
4 Department of Chemistry, College of Science, King Saud University, Saudi Arabia
5 School of Chemical Engineering, The University of Queensland, Australia
6 Department of Plant & Environmental New Resources, Kyung Hee University, South Korea

Abstract
This work demonstrates the fabrication of a nanoporous iron carbide-iron oxide/reduced graphene oxide (IC-IO/
rGO) hybrid via a controlled one-step thermal treatment of Prussian blue (PB)/GO hybrid at 450 °C under N2 flow.
The PB/GO hybrid is initially prepared through the in-situ deposition of PB nanoparticles on the GO sheets throughelectrostatic interactions. The morphological analysis of the hybrid reveals the uniform coverage of the rGO sheets
by IC-IO nanoparticles and the even distribution of carbon (C), oxygen (O), and iron (Fe) on the rGO nanosheets.
As a result of the hybrid composition and controlled morphology, the surface area of the obtained IC-IO/rGO hybrid(~40 m 2/g) is significantly enhanced compared to those of the calcined GO sheets and PB nanoparticles (without
GO).
Keywords: metal-organic frameworks, porous coordination polymers, metal oxides, metal carbides, graphene
oxide

1. Introduction
Metal-organic frameworks (MOFs) or porous coordination polymers (PCPs) have attracted significant interestas porous materials because of their high surface area,large pore volume, controllable composition and poresize, etc. (Wang Z.-L. et al., 2018; Salunkhe R. R. et al.,2016; Kaneti Y. V. et al., 2017). Prussian blue (PB) and its
analogues (PBAs) exhibit several attractive characteristics,
such as open framework structures, high thermal stability,and good redox activity. These CPs have been employedin numerous applications, including drug delivery (Lin W.
et al., 2009), energy storage (Paolella A. et al., 2017), sep-

†

‡
1
2

*

Received 27 May 2020; Accepted 21 July 2020
J-STAGE Advance published online 29 August 2020
Authors with equal contribution
1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
Brisbane, Queensland 4072, Australia
Corresponding authors: Mohamed Barakat Zakaria and Jongbeom
Na;E-mail: m.barakat@uq.edu.au; j.na@uq.edu.au

260

aration (Bureekaew S. et al., 2008), and so on (Doty F. etal., 2009; Ishizaki M. et al., 2013). Nevertheless, the poor
conductivity and low chemical stability of PB presents
major challenges for their practical applications (Salunkhe
R. R. et al., 2015). Therefore, extensive efforts are needed
to enhance the stability and conductivity of PB and its derived materials. To date, PB and PBAs have been employed
as novel precursors for obtaining various transition metalcompounds, including metal oxides and metal carbides(Azhar A. et al., 2019a). Generally, the calcination of PB
in air produces iron oxide (IO) as a result of the removal of
the cyano-group and the oxidation of the iron species. Ourgroup previously synthesized PB and completely transformed it into nanoporous iron oxide hybrids (Azhar A. etal., 2019b), such as β-Fe2O3 (Machala L. et al., 2013), andmixed crystalline phases of iron oxide (α, γ and β- phases)(Roy X. et al., 2011). On the contrary, when pure PB was
heated under inert atmosphere, the formation of metallic
iron and iron carbide (IC) (Fe7C3, Fe2C, and Fe3C) was
observed (Zakaria M. B. et al., 2016). Very recently, purenickel carbide (Ni3C) was successfully prepared from

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Alowasheeir Azhar et al. / KONA Powder and Particle Journal No. 38 (2021) 260–268

cyano-bridged CPs through a thermal treatment under inert
atmosphere at 450 °C (Zakaria M. B. et al., 2019). Despitesome progress, the construction of PB-derived metal carbide/carbon hybrids are still rarely reported.
Recently, carbonaceous materials, such as graphite,
graphene oxide (GO), reduced graphene oxide (rGO),
and carbon nanotubes (CNTs) have been widely used toenhance the functional performance of PB-based materials(Daneshvar F. et al., 2018; Azhar A. et al., 2018). The
oxygen-containing functional groups on the surface of thetwo-dimensional (2D) GO nanosheets can serve as excellent sites for the in-situ growth of PB nanostructures (LeeT. et al., 2015). Our group has demonstrated the fabricationof several cyano-bridged CPs grown on GO nanosheets bya variety of methods (Zakaria M. B. et al., 2019). Herein,
we report the synthesis of a hybrid material combining GO
sheets with PB nanoparticles which can be subsequently
transformed into a nanoporous IC-IO/rGO hybrid under
nitrogen atmosphere at 450 °C. The obtained IC-IO/rGO
hybrid has been thoroughly characterized in terms of its
composition, morphology, thermal decomposition behavior, and textural properties.

2. Experimental
2.1 Chemicals
Sodiumferrocyanide(II)decahydrate(Na4[Fe(CN)6]·10H2O, ≥ 99 %) was purchased from
Sigma-Aldrich (Japan). The sulfuric acid solution (H2SO4,
98 %) was obtained from Nacalai Tesque (Japan). Potassium hydroxide (KOH), sodium nitrate (NaNO3, ≥ 99 %),and ferric chloride hexahydrate (FeCl3·6H2O, ≥ 98 %)were sourced from FUJIFILM Wako Corporation (Japan).
Graphite nanoplatelets (N008-100-N, thickness ~100 nm)
were obtained from Angstron materials (USA). Potassium
permanganate (KMnO4, ≥ 99 %) and hydrogen peroxide
solution (H2O2, 30 wt.% in H2O) were purchased from
Kanto Chemicals (Japan). All chemicals were utilized asreceived without further purification.

2.2 Preparation of GO nanosheets
The thin GO nanosheets were fabricated by employing
the modified Hummer’s approach (Tanaka S. et al., 2017).
In the first step, 0.33 g of graphite powder and 0.17 gof NaNO3 were mixed together and stirred. Following
this, 7.67 mL of concentrated H2SO4 solution was slowly
poured into this suspension and then stirred for 1 h. Next,
1.0 g of KMnO4 was added into the mixture solution which
was placed in an ice bath below 20 °C. The mixture wassubsequently stirred at 35 °C for 2 h and distilled water(83 mL) was added into this mixture solution under strong

stirring. After that, 1.67 mL of aqueous H2O2 solution(30 % w/w) was added into the suspension. The final GO
suspension was washed a number of times with a diluted
HCl solution and distilled water. Finally, this GO suspension was sonicated in distilled water to exfoliate the GO
sheets. The GO sheets were collected by centrifugation andsubjected to repeated washing with distilled water, before
being dried at ambient temperature, followed by a final
drying in vacuum at 60 °C overnight. The as-prepared GO
powder was dispersed in water to prepare an aqueous GO
solution (2 mg mL–1) to be used in subsequent steps.

2.3 In-situ deposition of PB nanoparticles on GO
nanosheets (PB/GO hybrid) and conversion toiron carbide-iron oxide/rGO hybrid
Typically, 40 mL of 0.299 mM FeCl3·6H2O solution
was poured into the GO solution (20 mL, 2 mg mL–1) andstirred for 0.5 h. The mixture solution was slowly mixed
with 40 mL of Na4[Fe(CN)6]·10H2O solution (0.358 mM)
and stirred for further 0.5 h, before being aged for twodays. The product was isolated via centrifugation andwashed multiple times with water and ethanol, and finallydried at room temperature. The porous IC-IO/rGO hybrid
was achieved by calcining the PB/GO hybrid at 450 °C
for an hour under nitrogen (N2) flow with a ramping rateof 5 °C min–1. For comparison, pristine PB nanoparticles
without GO sheets were also prepared and heated under thesame conditions.

2.4 Characterization
The purity and compositions of the samples werechecked by X-ray diffraction (XRD) with a Rigaku
RINT 2500X diffractometer utilizing Cu Kα (1.5406 Å)
radiation. Nitrogen sorption isotherms were collectedusing a Quantachrome Autosorb at 77 K. To dehydrate
the samples, they were subjected to degassing at 250 °C
for 16 h prior to the BET measurement. Morphologicalobservations of the products were conducted using bothscanning electron microscope (SEM, Hitachi SU8000)
and transmission electron microscope (TEM, JEOL JEM2100F). The infrared (IR) spectra of the samples were collected using a Thermoscientific Nicolet 4700 spectrometer(Waltham, MA, USA). Raman spectroscopy measurements
were performed using a Horiba-Jovin Yvon T64000 Raman
spectrometer. Thermogravimetry (TG) measurements werecarried out with a Hitachi HT-Seiko Instrument Exter 6300
under N2 atmosphere from 30 to 550 °C at a ramping rateof 5 °C min–1.

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Fig. 1 (a, b) SEM images of (a) GO nanosheets and (b) PB nanoparticles. (c) SEM and (d) TEM images of the as-synthesized PB/GO hybrid.

Fig. 2 Wide-angle XRD patterns of GO, PB, PB/GO hybrid and IC-IO/
rGO hybrid. For comparison, the XRD pattern of calcined PB without
GO is also shown.

3. Results and discussion
The PB/GO hybrid was obtained by the in-situ
deposition of PB nanoparticles on the GO sheets (Azhar A.
et al., 2019b). First, the GO sheets were synthesized by the
exfoliation of graphite based on the modified Hummer’s
method (Tanaka S. et al., 2017). The SEM image of the
prepared GO sheets (Fig. 1a) shows a two-dimensional(2D) crumpled sheet-like structure. The zeta potential
measurements reveal the change in the surface chargeof the GO sheets from negative to positive charge after
the modification with PB nanoparticles. The morphologyof the PB/the GO hybrid is depicted in Fig. 1c, whichshows the wrapping of the PB nanoparticles by the GO
sheets (i.e., the surface of the GO sheets is bumpy.). The
TEM image further shows that the PB nanoparticles are
successfully deposited on the surface of the GO sheets

262(Fig. 1d). For comparison, pristine PB without GO sheets
was also prepared (Fig. 1b). Fig. 2 shows the XRD patternof the PB/GO hybrid which reveals the diffraction peaks
belonging to face-centered cubic (fcc) phase of PB (JCPDS
No. 73-0687) (Cao L. et al., 2010). Importantly, after themodification with PB, the primary diffraction peak belonging to the GO nanosheets disappears, possibly due to thenearly complete surface coverage of the GO sheets by the
PB nanoparticles (Islam M. N. et al., 2018).
Further compositional analyses of the PB nanoparticles, GO sheets, and PB/GO hybrid were carried out
using fourier-transform infrared (FTIR) spectroscopy. The
FTIR spectrum of the PB/GO hybrid (Fig. 3a) shows thepresence of strong bands belonging to the cyano (CN)group of PB (Fe2+-CN-Fe3+) (Ge C.-X. et al., 2018).
The peaks originating from oxygen-containing functionalgroups (Vermisoglou E. et al., 2014) on the GO surface issignificantly reduced following the modification with PB
nanoparticles, indicating the complete reduction of GO to
reduced graphene oxide (rGO) (Ren S. et al., 2012) and theformation of PB on GO sheets.
The thermal degradation of PB under nitrogen flow
was studied by TGA (Fig. 4). The TG curve of pure PB
shows multi-step weight loss (Sun D. et al., 2019). In thefirst stage, lattice water and adsorbed water moleculesin the structure are removed at temperatures between 30
and 210 °C. The second weight loss (210–420 °C) can be
attributed to the loss of the cyano (CN) group present in the
PB nanoparticles, and the final weight loss above 420 °C iscorrelated to the formation of IC. The thermal stability ofthe pure GO nanosheets under inert atmosphere was also
investigated by TG measurements (Fig. 4). The evaporation of adsorbed water molecules and the removal of labile
oxygen functional groups occur at ~250 °C and no further

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Fig. 4 TGA data of (a) PB and (b) GO. The measurement was carriedout in N2 atmosphere.

Fig. 3 (a) FTIR spectra of GO, PB, PB/GO hybrid, and IC-IO/rGO
hybrid. (b) Raman spectra of GO and IC-IO/rGO.

weight loss is observed (Park S. et al., 2011).
As depicted in Scheme 1, the thermal treatment of the
PB/GO hybrid at 450 °C under N2 atmosphere results in theformation of the IC-IO/rGO hybrid. The crystal structure ofthis hybrid after calcination was examined by wide-angle
XRD (Fig. 2). Some peaks are assignable to iron carbide(Fe3C, IC) (Fletcher D. et al., 2019), while the other peaks
at 35.5° and 62.9° can be attributed to iron oxide (γ-Fe2O3)(Zhu K. et al., 2018), suggesting the presence of multipleiron phases after the heat treatment. Compared to the calcined PB (without GO), the relative intensity of the IO peakin the IC-IO/rGO hybrid is increased, which may be due tothe reaction of iron species with oxygen functional groupsof GO sheets.
Fig. 5a displays the SEM image of the IC-IO/rGO hy-

brid, which is composed of irregular and porous structuresdue to the removal of the organic group after calcination.
Also, some IC-IO hybrid nanoparticles can be observedon the surface of the GO nanosheets. The TEM image
clearly reveals the uniform decoration of the rGO sheets
by IC-IO nanoparticles (Fig. 5b). The corresponding elemental mapping images in Fig. 5c–f confirm the uniform
distribution of carbon (C), oxygen (O), and iron (Fe) on therGO nanosheets.
The N2 sorption isotherms of the calcined PB and the
IC-IO/rGO hybrid are given in Fig. 6. The specific surface
area of the IC-IO/rGO hybrid (38.7 m2/g) is significantly
larger than those of the calcined GO sheets (1.25 m2/g)(Zakaria M. B. et al., 2019) and calcined PB (18.2 m2/g).
This is likely due to the presence of IC-IO nanoparticles
which may serve as effective spacers between the GO
sheets, thus preventing the stacking of the GO sheets
during the thermal treatment.
The FTIR spectrum of the IC-IO/rGO hybrid (Fig. 3a)clearly shows the disappearance of many oxygencontaining functional groups, which suggests the successful reduction of GO sheets to reduced GO (rGO) (Liu H.
et al., 2015). Additionally, a weak IR band belonging to
the CN group is also observed. Raman spectra of the GO
sheets before and after the thermal treatment are comparedin Fig. 3b. The D and G bands are clearly observed. However, the positions of the D and G bands are shifted after the

Scheme 1 Schematic illustration of the in-situ growth of PB nanoparticles on GO sheets (PB/GO hybrid) and the subsequent thermal decomposition
to IC-IO/rGO hybrid.

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Fig. 5 (a) SEM and (b) TEM images of the IC-IO/rGO hybrid obtained by the thermal treatment of the PB/GO hybrid at 450 °C for 1 h under N2 atmosphere. (c) HAADF-STEM image of the IC-IO/rGO hybrid and (d–f) the corresponding elemental mapping for (d) carbon, (e) oxygen, and (f) iron.

thermal treatment. Compared to the ID/IG value of pure GO(1.02), the ID/IG value of the IC-IO/rGO hybrid is higher(1.12), suggesting the increase of structural defects in the
GO sheets after calcination.

4. Conclusions
In summary, we have successfully achieved the in-situ
deposition of PB nanoparticles on the surface of GO sheets
through the interaction of PB with the oxygen-containing
functional groups of GO nanosheets. This PB/GO hybrid
can be converted to the IC-IO/rGO hybrid via a onestep thermal treatment at 450 °C under N2 flow withwell-retained morphology. This finding indicates that thepresence of rGO during thermal treatment helps to promote
the formation of iron carbide at high temperatures. The surface area of the obtained IC-IO/rGO hybrid (~40 m2/g) is
superior to those of the calcined GO sheets and the calcined
PB without GO. This hybrid material composed of multiple
compositions may have many potential applications in supercapacitors and oxygen reduction reaction (ORR).

Acknowledgements
Fig. 6 (a) N2 adsorption-desorption isotherms of PB calcined at 450 °C
and the IC-IO/rGO hybrid. (b) SEM image of calcined-PB nanoparticles.

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This work was conducted at the Queensland node ofAlowasheeir Azhar et al. / KONA Powder and Particle Journal No. 38 (2021) 260–268

the Australian National Fabrication Facility (ANFF-Q),
a company established under the National Collaborative
Research Infrastructure Strategy to provide nano and microfabrication facilities for Australian researchers. S.M.A.,
T.A., and Y.Y. thank Researchers Supporting Project Number (RSP-2020/6), King Saud University, Riyadh, Saudi
Arabia.

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Authors’ Short Biographies
Alowasheeir Azhar
Dr. Alowasheeir Azhar received her BSc in Energy Engineering (2013), MSc in Applied
Science and Chemistry (2015) from Tokai University (Japan), and Ph.D. (2019) in Department of Nanoscience and Nanoengineering at Waseda University (Japan). She received theCustodian of The Two Holy Mosques’ overseas scholarship program (2007 to 2019) from
Kingdom of Saudi Arabia. Her current research interest is the design for hybrid materials
and nanoporous materials.

Jacob Earnshaw
Jacob Earnshaw received his BSc (Chemistry) degree from the School of Chemistry andMolecular Biosciences at the University of Queensland, Australia in 2018. Currently, he isan Honours student under the supervision of Professor Yusuke Yamauchi, and his researchpursues the synthesis of nanoarchitectured materials for energy storage and electrocatalysis.

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Authors’ Short Biographies
Mohamed B. Zakaria
Dr. Mohamed B. Zakaria is a senior researcher at Australian Institute for Bioengineeringand Nanotechnology (AIBN), the University of Queensland, Australia and a Lecturerof Physical Chemistry, Department of Chemistry, Faculty of Science, Tanta University,
Egypt. He received his BSc in Chemistry and MSc in Physical Chemistry from Tanta University. Then, he received his PhD in Engineering in 2016 from Waseda University, Japan.
He did his postdoctoral research at NIMS-MANA, Tsukuba, Japan as a JSPS Fellow from2016–2018. His area of interest is in the fields of Chemistry, Materials Design, Hybrid
Materials, Energy, Catalysis, Dielectric Capacitors, Ferroelectric Materials, and Applied
Nanomaterials.

Ping Cheng
Ping Cheng received a MSc in biotechnology in 2019 at the University of Queensland.
He is currently studying for Ph.D. in the group of Prof. Yusuke Yamauchi, Australian Institute for Bioengineering and Nanotechnology. His research interests include environmental
applications and biological applications of porous materials.

Yusuf Valentino Kaneti
Dr. Yusuf Valentino Kaneti received his PhD from the University of New South Walesin July 2014 under the supervision of Prof. Aibing Yu. He joined the group of Prof. Yusuke
Yamauchi at the National Institute of Materials Science as a JSPS Postdoctoral Fellow
in September 2016. He is now working as a MANA Research Associate at NIMS. His
research interest is focused on the fabrication of functional porous materials for energy andenvironmental applications.

Md. Shahriar A. Hossain
Dr. Md Shahriar A. Hossain is currently a Senior Lecturer in the School of Mechanicaland Mining Engineering at UQ. He obtained his Ph.D degree in Materials Science andEngineering, The University of Wollongong (UoW), Australia in 2008. He was then employed as a Postdoctoral Research Fellow at the University of Geneva, Switzerland. He
was awarded the prestigious DECRA Fellowship from the Australian Research Council(ARC) in 2013. His research experience in various institutes and in industry around theworld has been mainly focused on fabrication and characterization of superconducting
materials and magnetically triggered nanoparticles for medical and energy applications.

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Authors’ Short Biographies
Saad M. Alshehri
Prof. Saad M Alshehri received his Ph.D. in Inorganic Chemistry from the Leicester
University, England in 1992. He worked at Northeastern University, Boston and the
Leicester University as a post-doctoral fellow. Prior to join to King Saud University, Prof.
Saad was an Assistant Professor of Chemistry at King Khalid Military Academy, Riyadh,
Saudi Arabia. His research interests are in synthesis of inorganic materials and their industrial applications. He has synthesized heat resistant and thermally stable material. He has
also investigated inorganic and hybrid materials for electro-catalyst and for energy storage
devices such as electrodes for lithium ions batteries and supercapacitors.

Tansir Ahamad
Dr. Tansir Ahamad received his PhD degree in 2006 from Jamia Millia Islamia, New
Delhi (INDIA). After his graduation, he was employed as a post-doc at the University ofWestern cape (South Africa). At the conclusion of his post-doc position he joined King
Saud University, Saudi Arab in 2008 and was employed as an Assistant Professor. From
March 2020, he has started his academic employment as a full professor in the departmentof Chemistry at King Saud University. His major research interest is in the fabrication of
porous nanomaterials, organic-inorganic hybrid materials, and their applications in energy
and environments.

Yusuke Yamauchi
Prof. Yusuke Yamauchi received his bachelor’s degree (2003), master’s degree (2004),
and PhD degree (2007) from Waseda University, Japan. After that, he joined the National
Institute for Materials Science to start his research group. Currently, he is a full professor at
the School of Chemical Engineering and a senior group leader at AIBN in The Universityof Queensland. He concurrently serves as an associate editor of J Mater Chem A (RSC) and
Chem Eng J (Elsevier). He has published over 750 papers with >36,000 citations (h-index
97, Web of Science®). He was selected as the Highly Cited Researchers in Chemistry in
2016–2019.

Jongbeom Na
Dr. Jongbeom Na received his Ph.D. degree (2017) from the Department of Chemical
and Biomolecular Engineering at Yonsei University (Republic of Korea). Until 2018,
he worked as a Research Engineer at Chemical Laboratory of SK Chemicals Co., Ltd.
Currently, he is working as a research fellow at AIBN, the University of Queensland and
MANA, NIMS. His major research interest is in the design and synthesis of functional
nanomaterials, organic-inorganic hybrid materials, and their applications.

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Original Research Paper

Polymer-Particle Enhanced Visible Light Range Photocatalytic
Activity on Textile Applications †Asena Cerhan Haink 1,2 and G. Bahar Basim 3*
1 Department of Electrical and Computer Engineering, Technical University of Munich, Germany
2 Department of Mechanical Engineering, Ozyegin University, Turkey

3 Department of Materials Science and Engineering, University of Florida, USA

Abstract
Extension of photocatalytic activity within the visible light range has an immense importance on the ability of
manufacturing self-cleaning textiles that are active indoors. This study focuses on assisting problems, which havedelayed the commercialization of the photo-catalytically active textiles by following innovative technologicaldevelopments in nanotechnology. Polymeric additives are utilized to prepare composite photocatalytic particles
with the ability of extending light absorption in the visible light range. Techniques are introduced to avoid thedeterioration of the composite particles during their application on textiles in addition to uniform coating strategies
to enable an optimized concentration for improved photocatalytic efficiency. It is demonstrated that the titania(TiO2) particles in anatase form extended absorption in the visible light range in the presence of branched titania
particles. Correspondingly, an optimized dip coating process is evaluated for textile manufacturing, providing asystematic methodology to enable the production of self-cleaning textiles to be able to manufacture them withcommercialization potential.
Keywords: self-cleaning textiles, visible light range photocatalytic activity, polymer titania composites

1. Introduction
Increasing environmental pollution, inevitable massconsumption of raw materials and, the most recently
faced challenges in hygiene standards due to the Covid-19
pandemic keep forcing societies to make smart use ofresources, including textiles. Notably, the high ecologicalcost of the conventional cleaning methods utilized fortextiles encourages the market to introduce new and more
technologically smart products. Photocatalytically active
materials are known for their efficiency in self-cleaning,
and their implementation can promote fast sanitizationin the cases of efficient cleaning as well as sanitization
against the spread of diseases (Saunders-Hastings et al.,2017). One fundamental challenge remains to be promoting the photocatalytic activity in the visible light range
to enable applications indoors through understanding
nano-technology principles and the photocatalytic activityof the selected additives.
Catalysts are substances that can accelerate reactions†

Received 19 April 2020; Accepted 9 June 2020
J-STAGE Advance published online 17 July 2020
* Corresponding author: G. Bahar Basim;
Add: Gainesville, FL 32611, USA
E-mail: gbbasim@ufl.edu
TEL: +001-352-846-3557 FAX: +001-352-846-1196

through lowering the free activation enthalpy of the reaction (Wubbels, 1983). Accordingly, photocatalysis canbe defined as a photoreaction in the presence of a catalyst
where a chemical modification of one molecular entity
results from the initial absorption of radiation by anothermolecular entity called a photosensitizer. The catalyst
might speed up the photoreaction by interaction with thesubstrate in its ground state or with a primer photoproduct(Castellote and Bengtsson, 2011). The nature of photocatalysis is based on solid-state chemistry and knowledge
on the crystal structure. Hence, nonstoichiometric and anyother alternative imperfections such as impurities that can
act as dopants that change the electronic properties affectthe photocatalysis functionality of materials (Castellote
and Bengtsson, 2011). The most commonly utilized photocatalytic materials are zinc oxide (ZnO), cadmium sulfide(CdS), iron(III)oxide (Fe2O3), tungsten trioxide (WO3),
tin oxide (SnO2), zinc sulfide (ZnS) and titanium dioxide(TiO2) (Cerhan et al., 2018; Dumitrescu et al., 2015). It isalso common to use blends of these primary compounds inmanufacturing. Among all the alternatives, titanium dioxide (TiO2) is the most commonly used photocatalyst for the
textiles due to its superior performance and light color thatis the most suitable for the manufacturing of the optic whitetextile products (Patra and Gouda, 2013). TiO2 has threepolymorph forms varying in crystal structures as rutile,

Copyright © 2021 The Authors. Published by Hosokawa Powder Technology Foundation. This is an open accessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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brookite, and anatase. When considering the enhancementof the photocatalytic activity, surface structure, composition, atomic and molecular scale surface dynamics, as wellas the electronic properties play an important role. It isnecessary to evaluate the adsorption and bonding of atoms
and molecules on the surfaces to understand the mechanisms of self-cleaning ability. Among the polymorphs oftitanium dioxide, anatase is the most thermodynamicallystable form of titania amid the three nanocrystal types. The
anatase powders with higher crystallinity are favored forphotocatalysis since higher crystallinity provides a smaller
quantity of defects acting as recombination sites in the
middle of photogenerated electron and hole combination(Filippo et al., 2015). It is more active than the rutile phaseas a photocatalyst, although its band gap value, 3.27 eV, ishigher than the rutile’s bandgap, which is 3.05 eV (Filippo
et al., 2015; Hümmelgen, 2012; López and Gómez, 2012).
Anatase powders tend to agglomerate despite the highphotocatalytic performance (Kiwi and Rtimi, 2016; Qiu etal., 2012). The commercial Degussa-P25 powder contains
anatase and rutile forms blended in a ratio of 3:1 and hasa bandgap energy of 3.26 eV (López and Gómez, 2012).
P-25 titania is commonly used as a benchmark for photocatalysts (Ohtani, 2008; Rui et al., 2014).
The challenge of standard photocatalytic semiconductor
activity is known to be the fact that it takes place in theultraviolet light range. In order to enhance the photocatalytic activity into the visible spectrum the formation ofbonds between photocatalytic particles and pure elemental
dopants or synthesized particles are needed. Beyond thestandard dopants (Cerhan et al., 2018; Dumitrescu et al.,2015) advanced particles are introduced in this study
named as branched particles with controlled synthesis andparticle size distribution. The core-shell particle decorated
with polymeric branches can actively control the binding
event by pairing ion, metal complex recognition, andhydrogen-bond recognition (Randazzo et al., 2012).
Application of the visible light range photocatalytic
activity enhancing nano-systems on textiles requires modifications to the textile manufacturing processes. Manufacturing of self-cleaning textiles at an industrial scalerequires the integration of the selected photocatalytic
system to the standard coating processes. Traditionally,
this will be performed by following two steps; (i) development of photocatalytic additives that can be added
into the selected finishing solutions without settling and,(ii) enabling their effective and homogeneous coatingon the textiles at the optimized dosages. It is agreed that
self-cleaning textiles with photocatalytic activity should
maintain high-quality textile standards with the application of functionalized films promoting the increase in thepotential market applications and meeting the variations
in demands. Self-cleaning textiles decorated with photocatalytic materials possess the self-cleaning property, and270

hence they can actively clean themselves without a needfor conventional laundry. This attribute provides significant
benefits concerning the prevention of environmental pollution and cost savings in addition to the spontaneous active
cleaning of the textiles even throughout their utilization
before and after washing. Consequently, many scientificstudies conducted on the textiles are linked to the desire
to produce eco-friendly photocatalysis reactions. Although
there are potential solutions proposed to widen the diversity of applicable photocatalytic materials, there is stillroom to perfect the applications due to the variation in the
demand and the limitations in the activity within the visible
light range (Kiwi and Rtimi, 2016).
In this study, photocatalytic materials and self-cleaning
textiles are evaluated in the context of composite nanoscale additives promoting secondary bonds to adjust initialenergy levels for enhanced photocatalysis action. Titaniumoxide particles in anatase crystalline structure were madeinto composite photocatalytic agents through polymeric
additives names as branched titania were coated on textiles
in DI-water as well as standard finishing solution to support the implementation of the final combination suitable
for self-cleaning textile standards. A commercial titania(Degussa P25) coating was compared to the anatase withand without the polymeric branching at various selectedconcentrations to optimize photocatalytic activity, particularly under visible light. The branched titania particles weresynthesized and characterized for particle size and stability
in addition to optimization of the most effective coating
concertation for photocatalytic activity by analyzing absorbance and stain removal ability in solutions as well as postcoating on textiles.

2. Experimental approach
2.1 Materials
The procedure for the synthesis of branch titania particles is adapted from an earlier study by S.A. Simakov
and Y. Tsur. The technique is based on the hydrolysisprecipitation procedure, by using TiOSO4・2H2O as a precursor and water as a hydrolyzed preparation medium.
Diethy­lene glycol monomethyl ether (DEGME) was used
as a surface modifier to form the desired branches utilized
for stability as well as an enhanced attachment onto thetextile surface. The necessary chemicals were obtained
from Sigma-Aldrich and used as received to conduct theparticle synthesis reactions.
The advanced textiles utilizing nanotechnology in thecoating processes, including the self-cleaning textiles,
are generally preferred to be manufactured from either
cotton or elastin type fibers and their blends (Akbar
and Bahar Basim, 2019). Thus, the textile was selectedAsena Cerhan Haink et al. / KONA Powder and Particle Journal No. 38 (2021) 269–280

to be a blend of 35 % elastin and 65 % cotton for thecoating procedure. In addition, a hydrophobic finishingsolution was preferred by the manufacturer’s recommendation based on its common implementation in textile
production. The selected finishing solution is composedof Setasil KF 1320 (amino-functional micro silicon emulsion) Setas Chemicals, Serisoft 210 (non-ionic softener)
Serboy Chemicals, Walline PE (polyethylene) Geochem
Chemicals and acetic acid (Sigma-Aldrich for pH balance)
at a total concentration of 2.7 % (w/v) in DI-water andmeasured pH of 3.52 (Akbar et al., 2017). These polymericand polyethylene structures provide holding on the textile
surface for additives by crosslinking (Andrienko, 2015).

AFM based size analyses were also conducted by further
dilution of the particles in DI water and drying a drop ofsample on a freshly cleaved mica surface. After drying
the suspensions on the cleaved mica substrate, samples
were analyzed by AFM (Nanomagnetics Ambient AFM)
in contact mode by scanning 5 × 11 μm and 3 × 5 μm size
images to determine the individual particle size. Particle
size measurements obtained from the two techniques arecompared to evaluate stability as well as the relationship to
the performance on the photocatalytic activity.

2.2 Methods

In order to evaluate the photocatalytic efficiency of various particulate systems, initial experiments were conductedby preparing suspensions and measuring their stain bleaching ability under the UV light. 10 ml solutions of photocatalytic components were prepared and mixed with 2 ml
methylene blue dye (MB+) solution to make a 2 × 10–4 M
concentration of the active dye. The prepared suspensions
were exposed to 365 nm UV light for 5 minutes to observe
the discoloration of methylene blue by the degradation of
the methylene blue as a function of time. The solutions
were compared for the change in color by taking pictures
before and after the UV light exposure at 365 nm. The absorbance spectrums of the solutions were also attained as afunction of time by using a Shimadzu UV1280 UV-visible
spectrometer as methylene blue degradation occurs.

2.2.1 Synthesis and particle size characterization of
branched titania particles
Branched titania preparation procedure was carriedout in a continuously stirred closed glass flask at room
temperature by adding 20 g of TiOSO4・2H2O powder(≥ 29 % Ti Sigma-Aldrich) to 180 ml of diethylene glycol monomethyl ether solution (≥ 99 % Sigma-Aldrich)and 40 ml of DI-water. After mixing for 90 hours, thesolution pH was increased by the dropwise addition of adilute NH4OH solution diluted from ammonium hydroxide
solution of 26 % (Sigma-Aldrich) to pH 10. The additionof the NH4OH solution changed the mixture into a whitecolor suspension, and the resulting precipitates wereseparated by centrifugation. Following the separation by
centrifugation, particles were washed three times with adiluted NH4OH solution followed by DI-water to avoid
creating bonds with the counter-ions of the salt used as aligand structure (SO4–2). The suspension was centrifuged
after each washing step to separate the precipitates without
significant loss of synthesized particles and to remove thecounter-ions and ligand structure within the remaining
solution. Finally, the precipitates were dried at 80 °C, anda white powder was obtained (Simakov and Tsur, 2007).
The baseline and synthesized branched titania particle
size was measured using two methods; (i) static light scattering technique by Coulter LS 13 320 and, (ii) using an
atomic force microscope (AFM). Commercially obtained
anatase powder and the laboratory synthesized branchedtitania particles were prepared as dilute suspensions in
DIW and finishing solution separately at 0.1 wt % by mixing 0.01 g powder in 100 ml DIW or solution. Since thepowders are prone to agglomeration (Simakov and Tsur,2007) suspensions were ultrasonicated multiple times until
all the agglomerated particles were suspended in the solution. Consecutive particle size distribution analyses were
performed by Coulter LS 13 320 until a single peak was
observed on the size distribution curve, verifying that thestabilization of the suspension was achieved. Furthermore,

2.2.2 Evaluation of photocatalytic cleaning
2.2.2.1 Optimization of photocatalytic activity ofparticle suspensions

2.2.2.2 E valuation of photocatalytic activity on
textilesISO 10678:2010 standard “Determination of the photocatalytic activity of surfaces in an aqueous medium by
the degradation of methylene blue” was used to determine
the photocatalytic particle concentration efficiency on
cleaning (Mills, 2012). This standard method requires themeasurement of the rate of photocatalytic bleaching of
MB+ in aqueous solution via UV/VIS spectrometry (Millsand McFarlane, 2007). The ISO 10678 standard was used
to evaluate the absorbance performance of the coated textiles by measuring the efficacy methylene blue degradationin the presence of the coated textiles in solutions as they
are exposed to UV light. The textiles samples treated withdifferent coatings were cut into 10 cm2 and dipped into abeaker filled with a 2 × 10–4 M MB+ solution followed by
UV exposure. A sample of the solution was collected every
20 minutes, and the absorbance values were measured toevaluate the efficiency of photocatalytic degradation as afunction of time.
In addition, stain tests were performed on the coatedtextiles by cutting them into 10 cm2 pieces and dipping intoa 2 × 10–5 M methylene blue solution for 20 seconds. The
stained textiles were dried in an oven at 36 °C and exposed271

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to UV light at 365 nm wavelength for a week. The stain
bleaching was evaluated by taking pictures on daily basis.
The UV light at 365 nm wavelength (Philips FluorescentLight Bulb TL-D F15T8) was utilized during the analyses.

2.2.3 Zeta potential measurement of coated textiles
The zeta potential of the baseline and coated textile
samples were measured by using Electro-kinetic Analyzer(Anton Paar SurPASS) as a function of pH of the circulating electrolyte. The textile samples were placed in acylindrical cell with supporting disks, which have holes
to allow the liquid flow. After the placement of the textile
sample into the cylindrical cell, the cylindrical cell wasplaced in between the electrodes to bind to mobile pistons
to allow variation in the distance between the electrodes
and adjusting pressure applied to the sample specimen. The
liquid flow was provided with a 1 mM KCl solution and thepH titration was performed by adding 50 mM HCl solution
at each time interval, as directed by the Attract 2.0 software
data analyzer of the SurPASS instrument. The isoelectric
points of the coated textiles, which is the pH value where
the zeta potential of the materials is zero, was determinedbased on the data attained from Attract 2.0 software. The
data is plotted as a scatter graph of zeta potential as a function of pH is fitted to a polynomial correlation by utilizing
MS Excel software. The isoelectric points were determinedthrough placement of zero value for pH in the equations foreach individual textile sample.

2.2.4 Bandgap energy determination
To determine the bandgap of the photocatalytically
active samples, solutions prepared with anatase andbranched titania concentrations in finishing solution were
deposited on the glass slides. The glass slide was used inplace of textiles to benefit from transparency of the glass
for spectroscopy as the textiles cannot be analyzed as
substrates due to their inhomogeneous opaque structure.
The chemical bath deposition method was used to deposit
the prepared solutions on the ultrasonically cleaned glass
substrates, and the glass substrates were dried in glass
Petri dishes at room temperature. The transmittance andabsorbance measurements of the deposited thin films wereobtained by Shimadzu UV1280 UV-visible spectrometer.
The graphs were evaluated by using OriginLab software
for the thickness and bandgap energy of the films.
The light energy which initiates a photocatalytic reaction
must be at least equal, or higher, than the energy bandgap.
The band energy plays a role as the threshold energy for thephotocatalytic reaction. The absorption method is used forthe identification of forbidden band energy, simply known
as the bandgap energy. In this method, specification of
the forbidden band energy is evaluated from the relation
between the absorption coefficient and the forbidden band
energy, as given in Eq. (1).

272

(hv) n  (hv  Eg )(1)

where, h, v and α represent the Planck constant, the frequency, and the absorption coefficient, respectively. In thismethod, a graph of (αhv)n versus hv is drawn. The energy
value, [(αhv)n = 0], is determined by Tauc plot throughplotting to the linear portion of hv representing the bandgap
energy of examined material against (αhv)n (Godet et al.,1991). When the n value in the Eq. (1) is chosen to be 2, direct bandgap energy of material can be determined. If the nvalue is 1/2, the determined value is defined as the indirect
bandgap value of the material (Akaltun et al., 2011; Astam,
2016; Cerhan-Haink and Basim, 2020).
1
ns 2  Tm   2ns (1  Tm ) 2 


nf 


Tm




1/2

 12t  2(nf 2 1  nf12 ) 

(2)

(3)

The maximum or minimum peak of the transmittancegraph was obtained from the UV-VIS spectrometer andwas used for the analysis of thin film thickness evaluationaccording to Eq. (2) and Eq. (3). Tm, λ, t are the maximum
peak parameters of transmittance, wavelength corresponding to maximum peak center, and thickness of the film,
respectively. The thickness of the thin films was calculated
by substituting amplitude of the first maximum peak, Tm1,
and amplitude of the second maximum peak, Tm2, values
into the Eq. (2) and replacing the values in the Eq. (3). The
ns represents the refractive index of the glass used to coat
the nanoparticle solutions (Swanepoel, 1983).

2.2.5 Water vapor transmission rate analysis on
textilesThe methods of measuring water vapor transmission rate
(WVTR) represents the permeability of the coated textiles
to water vapor (Hu et al., 2001). The highly permeablefilms are generally preferred in products for daily use suchas in self-cleaning textiles. In order to provide humanskin respiration continuity after the coating procedure, thewater vapor transmission rate is measured through a modification of the wet cup method described by the ASTM E
96-95 standard (Hu et al., 2001). In this method, the textile
sample is used as a cover on a cup filled with DI-water andthe change in mass is recorded as a function of time. The
weight change is due to the evaporation of water throughthe textile and Eq. (4) is used to determine the water vapor
transmission rate.
WVTR =

mass H 2O losttime × area

(4)

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The textiles were prepared for water transmittancetests by cutting 10 cm square samples to cover the topof the beakers after adding 100 ml DI-water in eachbeaker. The system was weighed to follow the change
in mass in weekly periods under ambient conditions(22 °C and 20 % humidity-winter and the 35 °C and 50 %humidity-summer). The system mass change was recorded
for 700 hours (~30 days).

3. Result and discussion
3.1 Characterization of nano-particle systems in
DI-water and textile finishing solution
The size distribution and shape of powders change thetotal surface area of the particles and affect the rate of reactions, stability as well as product appearance and texture.
Hence, particle size measurement is one of the indicatorsof quality and performance of suspensions for a successful
implementation of the nanoparticles on textiles. Fine particles with high total surface area speed up chemical reactions and dissolution rates while simultaneously becoming
more prone to settling due to the loss of suspension stability. Unstable suspensions lead to inhomogeneous coatings
since the photocatalytic particles settle out of liquid suspension and cannot hold on to the textile surface properly.
Therefore, the particle size of anatase and branched titania
were measured in DI-water as well as finishing solution byusing static light scattering via Coulter LS 13 320 as wellas through AFM scanning.
Table 1 summarizes the mean particle size measurements obtained by Coulter LS 13 320. It can be seenthat the anatase particles were similar in size both in
DI-water and finishing solution with 0.087 ∓ 0.005 μm and0.084 ∓ 0.001 μm mean diameter, respectively. The consistency in the measured mean size with a controlled standard
deviation indicates the stability of the anatase particles inboth environments. We have demonstrated in the earlier
studies that the titania particles are more stable in the finishing solution which has a pH of 3.52 as compared to the
DI water which has a pH of ~6 (Cerhan-Haink and Basim,
2020). This is due to the fact that the isoelectric point of
anatase is at pH 5.8 (McNamee et al., 2005) and hence

retains more positive surface charge in the finishing solution with pH 3.52 as compared to the DI water with pH of
6. Stability of the suspensions is expected to reduce when
the pH is close to the iso electric point (i.e.p) of the system
due to the fact that the particles retain no surface charge at
the i.e.p (Ney, 1973). If the suspension is to be stabilized,
one of the ways to do this is to change the pH away fromthe i.e.p to increase the electrical repulsion in between theparticles (Salopek et al., 1992). Alternatively, mechanicalvibration can be induced through effective ultrasonication.
In this case, titania particles were stabilized in both suspensions through rigorous ultrasonication as can be seen fromthe consistent mean size measurement values.
In the case of branched titania, measurements showed amean size of 0.55 ∓ 0.003 μm with tight control on the standard deviation for the solutions prepared in the DI-water
background. In the presence of the finishing solution, on
the other hand, the mean size increased almost twice andmeasured to be 1.029 ∓ 0.058 μm. It is believed that in thepresence of the ingredients of the finishing solution, such as
the silicon particles, the branches created on the titania particles attach to these additives and measure larger in mean
size as compared to the DI-water based measurements. The
increase in the variance of the measurement also supports
the proposed concept in the finishing solution environment.
In order to understand the stability and verify the proper
size of the synthesized branched titania particles, morphological particle size analyses were conducted by AFM
scanning. Particles deposited on mica substrates were characterized and summarized in Table 2. The scanning of theanatase versus the branched titania particles with the AFM
technique allows the characterization of the particles in theirdried form. It can be seen that the mean sizes of the anataseand the branched titania particles are much closer measured
as 0.277 ∓ 0.035 μm for anatase and 0.244 ∓ 0.118 μm
branched titania. This is an indication that the branchedtitania particles have similar size cores but measure larger
due to the presence of polymeric branches in the solution
background. Furthermore, the standard deviation of particle size measurements obtained with light scattering on
branched silica particles is lower as compared to the AFM
measurements, while the particle sizes measured with AFM
are almost half of the mean size measured by the Coulter
LS 13 320. The smaller size measurement by AFM can be
attributed to the fact that the branches attached to the main

Table 1 Change of material stability depending on zeta-potential size.

Photocatalytic particle

Mean Particle
size (μm)

Standard
Deviation (μm)

Anatase in DIW

0.087

0.005

Anatase in F.S.

0.084

0.001

Branched titania in DIW

0.541

Branched titania in F.S.

1.029

Table 2 AFM scanning results for mean particle size evaluations ofanatase and branched titania.

Photocatalytic particle

Mean Particle
size (μm)

Standard
Deviation (μm)

0.003

Anatase

0.277

0.035

0.058

Branched titania

0.244

0.118

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particle are collapsed by drying, whereas they are extended
effectively in the solution environment for the light scattering measurements. Furthermore, the presence of the silicon
and the polymeric additives in the finishing solution also
results in the measurement of a larger size which is more
pronounced with the branched structure of titania.

3.2 Optimization of photocatalytic activity withmethylene blue solution
Optimization of photocatalytic activity initially studied
by using MB+ and the experimental setup adopting ISO
10678 standards. Fig. 1 illustrates the stain bleaching on
suspensions prepared by 0.001, 0.01 and 0.1 wt % anatasein DI water and finishing solution for optimization of photocatalytic activity as a function of titania particle addition.
It can be seen that in DI-water, anatase did not show any

photocatalytic activity even under the UV light. When we
conducted the same tests in finishing solution, on the other
hand, 0.1 wt % anatase concentration showed significant
degradation of methylene blue under the UV light changing
the color of the suspension to white. It can be concluded
that the presence of finishing solution helps activate theanatase under the UV light, which can be attributed tothe additives like silicon in the active ingredients of thefinishing solution.
Further improvement in the photocatalytic activity
was obtained with the addition of branched titania to the
0.1 wt % anatase solutions. Fig. 2 illustrates the change inthe color of methylene blue solutions in finishing solution
as a function of the branch titania doping at 0, 0.001, 0.01,
and 0.1 wt % concentrations. As it can be seen in Fig. 2,
finishing solution by itself did not show photocatalytic
activity as observed by no change in the methylene blue

Fig. 1 Methylene blue stain bleaching on suspensions prepared by 0.001, 0.01 and 0.1 wt % anatase in (a) DI water and (b) finishing solution for optimization of photocatalytic activity as a function of titania particle addition.

Fig. 2 Optimization of anatase/branched titania mix ratio in both finishing solution by methylene blue degradation analyses.

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color. This is consistent with the observation of no stain
bleaching on the textiles which were coated only with thefinishing solution in our earlier studies (Cerhan Haink andBasim, 2020). The optimal photocatalytic performance wasobtained with 0.1 wt % anatase with 0.001 wt % branchedtitania doping as per the visual observations. Nevertheless,the determination of the photocatalytic activity according
to the color change can be misleading a better quantification is needed. As an example, appearances of 0.1 wt %anatase doped with 0.001 wt % 0.01 wt % branched titania
after UV exposure are similar. Therefore, the methylene
blue degradation for these solutions was also evaluated by
UV spectrophotometer absorbance tests as a function oftime, as can be seen in Fig. 3. The decrease in the absorption is an indication of better transmittance in the solution
and hence indicates the cleaning of the solution by thephotocatalytic activity. Comparing the absorption peaksof the 0.1 wt % anatase (Fig. 3a), 0.1 wt % anatase dopedwith 0.001 wt % branched titania (Fig. 3b) and 0.1 wt %anatase doped with 0.01 wt % branched titania (Fig. 3c)show that the UV absorption peaks representing methylene
blue degrades fastest for the combination of 0.001 wt %branched titania with anatase. Consequently, better photocatalytic cleaning efficiency is observed in the presenceof 0.001 wt % branched titania in 0.1 wt % anatase. The
speed of photocatalytic degradation can also be seen in Table 3, where the absorption delta is tabulated as a functionof time for the selected three treatments. This observation
highlights the fact that the ingredients in the finishing solution can enhance the kinetics of the photocatalytic activity
when the polymeric branches interact with the silicon in
the environment. It can be suggested that the polymericbranches on the titania particles can induce the synergistic
effect of better particle attachment on the textile surfaces
while simultaneously enhancing the photocatalysis.

3.3 Evaluation of photocatalytic efficiency on
the textiles coated with the optimized nanoparticle systems
Fig. 3 Absorbance versus wavelength representing the MB+ degradation under the cool light as a function of time for, (a) 0.1 wt % anatase,(b) 0.1 wt % anatase doped with 0.001 wt % branched titania and (c)0.1 wt % anatase doped with 0.01 wt % branched titania in finishingsolution.

In order to observe the photocatalytic performance ofthe textiles coated with the optimized particulate systems,
absorbance tests were also conducted on the textiles coatedwith the selected optimal nano-particle combinations andcompared to the industrial standards. Fig. 4 illustrates the

Table 3 Absorption delta for methylene blue degradation in finishing solution with 0.1 wt % anatase, 0.1 wt % anatase doped with 0.001 wt %branched titania and 0.1 wt % anatase doped with 0.01 wt % branched titania as a function of time.

SolutionsTime (minute)0

0.1 wt % Anatase0.01 wt % Branched titania

3.985

0.1 wt % Anatase0.001 wt % Branched titania

3.863

0.1 wt % Anatase

3.898

2

3

4

6

3.929
3.801
3.789

8

10

3.142
3.100

3.313

9

2.857

12
2.703

2.497
2.571

2.504

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absorbance tests performed for textile samples coated with
0.1 wt % anatase, 0.1 wt % anatase doped with 0.001 wt %branched titania, and 0.1 wt % P25 (used as a benchmark
to compare photocatalytic activeness) in the finishingsolution. It can be seen that the textile coated with the
optimized solution, which is 0.1 wt % anatase doped with
0.001 wt % branched titania, degraded the methylene blue
solution most effectively with a high drop in the absorbance value indicating efficient photocatalytic activity. The
optimized combination of the nanoparticle system resulted
in a significantly better performance relative to the standard
P25 and even anatase coated by themselves.
To better observe the stain removal efficiency of thecoated textiles, the stain tests were also performed, as canbe seen in Fig. 5. The textiles coated with the specified
particle combinations were stained in one half and compared to the unstained half as they are exposed to UV lightand pictured daily basis. Branched titania particles weresynthesized by following the procedure described in theliterature (Simakov and Tsur, 2007). It was illustrated by
SEM micrographs that the diethylene glycol monomethyl
ether attached on the titania surface and extended out asbranches. It was also reported by XPS measurements thatthe binding energy of the carbon atoms and the oxygen
atoms was detected to be around 250 eV and 530 eV, respectively (Simakov and Tsur, 2007). In this study, the UV

light energy applied on the textile samples coated with thebranched titania was around 3.4 eV and the textiles were
exposed to UV source which was 15 cm away from thetextile surface in the CAMAG UV Cabinet. Therefore, thepolymer degradation is not expected to occur under the experimental set-up. Furthermore, no particular color change
was observed on the branched titania coated textiles within
the duration of the experimental evaluations. Furthermore,
the stain test results also demonstrated that the textile sample coated with 0.1 wt % anatase and 0.001 wt % branchedtitania in the finishing solution showed the maximum levelof stain discoloration based on the visual judgment of stain
bleaching by the human eye. This observation is in anagreement with the absorbance measurements performedon the textiles coated with the same particle combinations.

3.4 Zeta potential of coated textiles
The textiles coated with photocatalytic particles werecompared to the baseline uncoated textile to analyze anychanges in the surface charge as a function of the solution
pH. The zeta potential analyses were carried out for the uncoated textiles and the textile samples coated with 0.1 wt %anatase, 0.001 wt % branched titania and the optimal
photocatalytic concentration of 0.1 wt % anatase dopedwith 0.001 wt % branched titania in the finishing solution.
Fig. 6 illustrates the measured surface potentials as afunction of pH to be very similar regardless of the surface
treatment. It can be seen that the i.e.p of all the textile samples was measured between pH of 2.5 and 3, indicating thatthe procedure of photocatalytic enhancement by coatingwith various particle systems maintain a consistent surface
finish while improving the photocatalytic efficiency.

3.5 Bandgap energy determination for optimal
particle combination
Fig. 4 Absorbance values of textiles coated with 0.1 wt % Degussa P25,
0.1 wt % anatase and, 0.1 wt % anatase doped with 0.001 wt % branchedtitania dipped into methylene blue solutions under exposure to 665 nm
wavelength light as a function of time.

Fig. 5 Discoloration scale of textiles coated with 0.1 wt % Degussa
P-25, 0.1 wt % anatase, and 0.1 wt % anatase doped with 0.001 wt %branched titania in finishing solution.

276

To quantify the photocatalytic efficiency of the optimized particulate system, band gap energy measurements
were conducted as described in the experimental evalua-Fig. 6 The zeta potential as function of pH of un-coated textile andtextiles coated with anatase concentrations doped with 0.001 wt %branched titania in finishing solution.

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tions. The transmittance and absorbance of the thin films
prepared from the solutions composed of 0.1 wt % anataseand 0.1 wt % anatase doped with 0.001 wt % branchedtitania in finishing solution were measured to determine
the thickness and bandgap energy as shown in Fig. 7 andFig. 8.
The film thicknesses (t) were attained by placing peakvalues of transmittance into Eq. (2) and Eq. (3), respectively. Furthermore, the thickness values were used todetermine the energy bandgap for the thin films generated.
The bandgap value of the 0.1 wt % anatase doped with
0.001 wt % branched titania was calculated to be 2.8 eV.
This bandgap corresponds to the visible light range of
443 nm, according to the Plank-Einstein relationship(Landsberg, 1978). The band-gap energy, or in other words,
the initial energy for photocatalysis being in the visible
light range, means that the photocatalytic activity is plausible under the visible light exposure. Whereas the band

gap energy of the pure anatase at 0.1 wt % concentration in
the finishing solution was determined to be 3.31 eV, which
is close to the value reported in the literature (3.26 eV)
but still corresponding to the UV light region (400 nm).
Thus, the enhanced performance with the optimized
anatase, branched titania combination can be attributed tothe energy bandgap shift into the visible light range in thepresence of the polymeric additive doping. This observation also aligns with the earlier findings in the literaturesuggesting the core-shell particle decorated with polymericbranches can actively control the binding event by pairing
ion, metal complex recognition, and hydrogen-bond recognition (Randazzo et al., 2012). Furthermore, textiles havean inherently rough surface and they are not conductive
and hence the photocatalytic reaction should be considered
as independent from any change in the surface area of the
textiles by the addition of particles. The surface charge
evaluations also do not indicate a significant change to

Fig. 7 Thickness and transmittance graphs of thin films coated with(a) 0.1 wt % anatase and (b) 0.1 wt % anatase doped with 0.001 wt %branched titania in finishing solution.

Fig. 8 Band gap energy and absorbance graphs of thin films coated with(a) 0.1 wt % anatase and (b) 0.1 wt % anatase doped with 0.001 wt %branched titania in finishing solution.

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Table 4 Water vapor transmission rate for uncoated and coated textiles under the winter and summer conditions.

Type of Textile

WVTR (%) (20 °C-20 %RH)

WVTR (%) (35 °C-50 %RH)

Uncoated

34.12 ± 0.37

77.26 ± 0.36

0.1 wt % Anatase in finishing solution

34.61 ± 0.48

75.61 ± 0.59

0.1 wt % Anatase and 0.001 %w Branched titania in F.S.

33.80 ± 1.43

72.52 ± 0.99

infer that an increase in the surface area would make theobserved photocatalytic activity improvement.

3.6 Water vapor transmission evaluation for daily
usage evaluation of the textiles
The water vapor transmission through the textiles is avital factor affecting the thermo-physiological comfortof people wearing the textiles by allowing respiration ofhuman skin (Arabuli et al., 2010). After coating the textiles
with the selected particulate systems, the permeability
could change due to the reduction of the textile porosity,
which may limit the breathability of the garment.
Textiles coated with 0.1 wt % anatase and 0.1 wt %anatase doped with 0.001 wt % branched titania in thefinishing solution were exposed to the WVTR analyses
for detecting water vapor transmission rates. The weightchange of the full experimental set-up as a function oftime is summarized in Table 4 as evaluated for winterand summer conditions. It can be seen that the WVTR isaround 35 % for each textile sample for winter set up under
22 °C and 20 % moisture environment. The WVTR values
measured in winter were lower than the values measured insummer 35 °C and 50 % moisture, which were measured
to be around 75 %. The results were statistically the sameother that the trend of slightly lower values observed withthe textiles coated with the 0.1 wt % anatase doped with
0.001 wt % branched titania. It can be concluded that thephotocatalytically more active coating combinations areequality suitable for the daily use.

4. Summary and conclusions
Extension of photocatalytic activity into the visible
light range through modification of the bandgap energy
was accomplished by polymeric branches decorated ontitania particles. Branched titania synthesis was performed
chemically, and the particle size measurements conductedin the solution and post drying suggested the free elongation of the polymeric branches from the core particle inthe solution environment. An optimal concentration wasestablished with 0.1 wt % anatase doped with 0.001 wt %branched titania in a hydrophobic finishing solution. The
composite branched titania particles, in combination withthe anatase in finishing solution, achieved a 2.8 eV band-278

gap corresponding to the visible light range with 443 nm
wavelength. The synergistic effect of the branched titania
particles in the presence of anatase was further confirmedby measuring the bandgap of 0.1 wt % anatase in finishingsolution, which was found to be 3.1 eV. It was further
demonstrated that the implementation of the optimized particle combination to the textile finishing process enhanced
the self-cleaning efficiency in addition to better attachmentof the particles on the textile surface through the polymeric branches. In summary, the new polymeric branchedparticles have the synergy of better coating capability on
textiles with an enhanced photocatalytic activity that canbe extended into the visible light range.

Acknowledgements
The authors acknowledge the financial support fromthe Eureka PhotoCat project E!8080 and Kivanc Tekstil
Company in Adana Turkey.

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Authors’ Short Biographies
Asena Cerhan Haink
Asena Cerhan Haink is a second-year PhD student in Electrical and Computer Engineering at the Technical University of Munich. She holds two masters degrees in Physics andMechanical Engineering. She has a MSc Thesis, from Physics, on the characterization of
the photovoltaic semiconductor. For her second MSc Thesis, she wanted to have a better
understanding of the photocatalytic efficiency at the textiles. To do so, she focused on thephotocatalysis mechanism in terms of optical characterization besides to self-cleaning
textiles quality characterization. For her PhD Thesis, her research focusses on the morphological characterization of organic thin film systems. She can be contacted at: asena.
cerhan-haink@tum.de

G. Bahar Basim
Dr. Bahar Basim is a Professor of Practice at the University of Florida Department ofMaterials Science and Engineering. She is an expert on electronic materials and particle
science and technology. She has received the European Commission Marie Curie PeopleAward in 2010 for her research on nanoscale protective oxide film. She has numerous international patents and applications on nanotechnology, microelectronics, coatings, and surface science in addition to many technical papers, books, and presentations. Her researchcontinues on chemical mechanical planarization, thin films, interfaces, novel nanoparticle
development and nano-structuring of biomaterials.

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Information Article

Book Review“Nanoparticle Technology Handbook (third
edition)” edited by Makio Naito, Toyokazu
Yokoyama, Kouhei Hosokawa and Kiyoshi Nogi

Elsevier B.V., 3rd ed. 2018, 904 p.
ISBN: 978-0-444-64110-6,
DOI: 10.1016/C2017-0-01011-X

A “powder”, which is an assemblage of small solid particles, exhibits very unique behavior. For example, depending on the circumstances, a powder can behave like a gas, a liquid, or a solid. Furthermore, because of the larger
specific surface area relative to its bulk counterpart, powders can have very distinct properties. This is especially truefor “nanoparticles”. The unique behavior and properties of particle and powder give them a wide range of industrial
applications that makes them ubiquitous in our daily lives. Particles and powder are also building blocks to makepromising materials for creating scientific and technical innovations in the future.
Mr. Masuo Hosokawa, the chief editor of the first edition of this Handbook, was a pioneer in this industry. When he
was the President of Hosokawa Micron Corp., he founded Hosokawa Powder Technology Foundation in 1991 to contribute to the advancement of powder technology on a global scale, and published the first issue of “KONA Powder
and Particle Journal” in 1983. Since then, KONA has been published annually, and distributed worldwide.
Mr. Hosokawa proposed the concept of “nanoparticle technology” long before the United States President Bill
Clinton’s National Nanotechnology Initiative in 2000. One of the activities of the Foundation was to publish the
Nanoparticle Technology Handbook in Japanese in 2006, which was translated into English and published its first edition of this Handbook in 2007. Nanoparticle technology advanced considerably after 2007, prompting Mr. Hosokawa
to start preparing an updated second edition of the Handbook. He unfortunately passed away on March 31, 2010
before the second edition was published in 2012.
Because nanoparticle technology has rapidly evolved since 2012, and has been applied more broadly in new
areas, Mr. Yoshio Hosokawa, the second President of Hosokawa Powder Technology Foundation and President of
Hosokawa Micron Corporation decided to publish a third edition of the Handbook. In this third edition, the applications section of the Handbook has been updated to include the most recent advances in nanoparticle technology.
Nineteen chapters have been added. The 79 chapters in the applications section are organized into four categories asshown in Table 1. The third edition has totally 877 pages including fundamental part as shown in Table 1. Over 140
experts in nanotechology and/or powder technology contributed to this new edition.
Nanoparticle technology is a new and revolutionary technology. It handles the preparation, processing, applicationand characterization of nanoparticles and has become the core of nanotechnology as an extension of conventional fineparticle/powder technology. Nanoparticle technology
plays an important role in the implementation of nano­technology in many engineering and industrial fields.
I hope the third edition will give readers state-ofthe-art information and knowledge to develop theirown innovative technologies and new products, further
enhancing our understanding of the fundamentals of
nanoparticle technology.

281

Table 1

Contents

FUNDAMENTALS
1. Basic Properties and Measuring Methods ofNanoparticles
1.1. Size Effect and Properties of Nanoparticles ......................3
1.2. Particle Size .......................................................................91.3. Particle Shape ..................................................................10
1.4. Particle Density ...............................................................13
1.5. Melting Point, Surface Tension and Wettability ..............17
1.6. Specific Surface Area and Pore .......................................19
1.7. Composite Structure ........................................................22
1.8. Crystal Structure ..............................................................27
1.9. Surface Characteristics ....................................................31
1.10. Mechanical Property ........................................................34
1.11. Electrical Properties .........................................................37
1.12. Magnetic Properties .........................................................40
1.13. Optical Property of Nanoparticle .....................................44
2. Structural Control of Nanoparticles
2.1. Structure Construction and Function Adaptation of
Nanoparticles ...................................................................49
2.2. Particle Size .....................................................................55
2.3. Particle Shape ..................................................................69
2.4. Composite Structure ........................................................76
2.5. Pore Structure ..................................................................91
2.6. Nanoparticle Design for Drug Delivery System ...........100
2.7. Nanotubes (Carbon Nanotube) ......................................105
3. Characteristics and Behavior of Nanoparticles and Its
Dispersion Systems
3.1. Introduction of Nanoparticle Dispersion andAggregation Behavior ...................................................109
3.2. Single Nanoparticle Motion in Fluid .............................114
3.3. Brownian Diffusion .......................................................120
3.4. Adsorption Properties and Wettability of
Nanoparticle Surface .....................................................121
3.5. Interactions Between Particles ......................................123
3.6. Aggregation and Dispersion, Characterization
and Control ....................................................................149
3.7. Rheology of Slurry ........................................................158
3.8. Simulation of Colloidal Dispersion System ..................162

4. Control of Nanostructure of Materials
4.1. Assembly of Nanoparticles and Functionalization ....... 169
4.2. Nanoparticles-Arranged Structures .............................. 170
4.3. Nanopore Structure ....................................................... 181
4.4. Nanocomposite Structure.............................................. 193
4.5. Structure Control of Nanoparticle Collectives
by Sintering and Bonding ............................................. 212
4.6. Self-Assembly............................................................... 239
5. Characterization Methods for Nanostructure ofMaterials
5.1. Nanostructure and Function (Characterizationof Local Nanostructure) ................................................ 255
5.2. Crystal Structure ........................................................... 256
5.3. Surface Structure .......................................................... 265
5.4. Nanopore Characterization ........................................... 282
5.5. Grain Boundaries and Interfaces .................................. 288
5.6. Evaluation Methods for Oxide Heterostructures .......... 297
Evaluation Methods for Properties of Nanostructured
6. 
Body
6.1. Functionality of Nanostructures and Their
Characteristic Evaluation .............................................. 301
6.2. Mechanical Properties .................................................. 306
6.3. Thermophysical Properties ........................................... 318
6.4. Electric Properties......................................................... 325
6.5. Electrochemical Properties ........................................... 338
6.6. Magnetic Properties ...................................................... 349
6.7. Optical Properties ......................................................... 352
6.8. Catalytic Property ......................................................... 357
6.9. Properties of Gas Permeation and Separation
Membranes ................................................................... 360
7. Environmental and Safety Issues with Nanoparticles
7.1. Introduction................................................................... 365
7.2. Nanoparticles and Environment ................................... 365
7.3. Safety of Nanoparticles................................................. 379
7.4. Removal of Nanoparticles ............................................ 388

APPLICATIONS
Category A- Medical, Cosmetic, BiologicalApplication 1 - Development of New Cosmetics Based on Nanoparticles ............................................................................................ 399
Application 2 - Design of Nanoparticles for Oral Delivery of Peptide Drugs ....................................................................................... 407
Application 3 - Development of Photocatalyst Inserted Into Surface of Porous Aluminosilicate ......................................................... 415
Application 4 - Nanoparticle Formation of DNA (Globule Transformation) ......................................................................................... 419
Application 5 - Addressing of Nanoparticles by Using DNA Molecules ............................................................................................... 423
Application 6 - Development of the Thermoresponsive Magnetic Nanoparticle and Its Deployment in the Biotechnology
Field .............................................................................................................................................................................. 427
Application 7 - Pinpoint Drug and Gene Delivery ................................................................................................................................. 435
Application 8 - A Cancer Treatment Strategy That Combines the Use of Inorganic/Biocomplex Nanoparticles With
Conventional Radiation Therapy .................................................................................................................................. 439
Application 9 - Development of Functional Skin Care Cosmetics Using Biodegradable PLGA Nanospheres ..................................... 445

282

Application 10 - PLGA Nanoparticle Design and Preparation for DDS and Medical Device ................................................................. 451
Application 11 - PLGA Nanosphere Technology for Novel Nanomedicine and Functional Cosmetics .................................................. 461
Application 12 - Delivery to the Brain ..................................................................................................................................................... 469
Application 13 - Bioimaging With Quantum Dots ................................................................................................................................... 473
Application 14 - Application of Quantum Dots for Biomedical Engineering .......................................................................................... 479
Application 15 - Application of Polymeric Nanoparticles and Polymeric Micelles for Treatment of Biofilm Infection
Disease .......................................................................................................................................................................... 481
Category B- Energy, Batteries, Environmental
Application 16 - Development of High-Performance Electrochemical Reactors .................................................................................... 487
Application 17 - Superior Thermal Insulation Film With Transparency Achieved by Hollow Silica Nanoparticles .............................. 493
Application 18 - Development of Fuel Cells ............................................................................................................................................ 499
Application 19 - Mechanical Synthesis of Composite Oxide and Its Application for SOFC Cathode .................................................... 505
Application 20 - A Dye-Sensitized Solar Cell Utilizing Metal Nanoparticle ........................................................................................... 511
Application 21 - Room Temperature Fabrication of Electrode-Solid Electrolyte Composite for All-Solid-State
Rechargeable Lithium Batteries ................................................................................................................................... 517
Application 22 - Enhancement of the Performance of Insulating Materials ............................................................................................ 525
Application 23 - Collection Technology for Nanoparticles in Flue Gas .................................................................................................. 529
Application 24 - Powder Technology and Nanotechnology Contributed for Clean Utilization of Coal .................................................. 533
Application 25 - Zeolite Membrane ......................................................................................................................................................... 539
Application 26 - Development of Nanoparticle Composite Technique for Low Pt-Loading PEFCs....................................................... 543
Application 27 - Novel Recycling of Fiber–Reinforced Plastics by Using Nanoparticle Bonding ......................................................... 547
Application 28 - Improvement of Lithium-Ion Battery Performances by Controlling Nanocomposite Structure................................... 551
Application 29 - Dendrimers and Their Application to Organic Electronics Devices ............................................................................. 559
Application 30 - Ceramic Filter for Trapping Diesel Particles ................................................................................................................. 563
Application 31 - Development of Exhaust Catalyst ................................................................................................................................. 569
Application 32 - Electrical Conductive CNT-Dispersed Si3N4 Ceramics ................................................................................................ 575
Application 33 - Preparation of Solid Electrolyte Particles and Solid-Solid Interfaces for All-Solid-State Batteries ............................. 579
Application 34 - Development and Multi-Functionalization of High-Functional Separation Membranes .............................................. 585
Application 35 - Development of a High-Performance Secondary Battery by Controlling the Surface Structure .................................. 591
Category C: Electronic and Magnetic Materials, Memories, Light Emitting Materials, Displays
Application 36 - Development of Bright Phosphors Using Glasses Incorporating Semiconductor Nanoparticles ................................. 597
Application 37 - Closely Packed Colloidal Crystal Assembled With Nanoparticles and Its Application for Smart Materials
With Tunable Structural Color...................................................................................................................................... 601
Application 38 - Practical Issue of Nanosized Colorant Particles ............................................................................................................ 607
Application 39 - Expression of Optical Function by Nanostructure Using Femtosecond Laser Processing ........................................... 613
Application 40 - Ceramic Fillers for High Frequency Dielectric Composites ......................................................................................... 619
Application 41 - Material Design of Electronic Liquid Powder Used in Novel-Type Bistable Reflective Display(QR-LPD) ..................................................................................................................................................................... 625
Application 42 - Sensing Based on Localized Surface Plasmon Resonance in Metallic Nanoparticles .................................................. 631
Application 43 - Development of Photonic Crystal Resonators for Terahertz Wave Sensing by Using Nanoparticle
Stereolithography.......................................................................................................................................................... 635
Application 44 - AC Overhead Transmission Line Audible-Noise Reduction Measures Using Surface Improvement .......................... 637
Application 45 - Development of Photonic Crystals Based on Nanoparticle Assembly.......................................................................... 643
Application 46 - Microelectronics Packaging by Metal Nanoparticle Pastes .......................................................................................... 647
Application 47 - Development of Novel Ferroelectric Materials ............................................................................................................. 651
Application 48 - Development of Magnetorheological Fluid by Using Iron Nanoparticles and the Application to Haptics
Devices ......................................................................................................................................................................... 655
Application 49 - High Performance Wiring Based on Nanowelding Technology for Printed Electronics .............................................. 661
Application 50 - Development of New Phosphors ................................................................................................................................... 667
Application 51 - Development of Optical Memory Using Semiconductor Nanoparticles....................................................................... 671
Category D- Synthesis, Dispersion, Processing
Application 52 - Nanoparticle Synthesis, Dispersion, and Functionalization for Industrial Application ................................................ 675
Application 53 - Supercritical Hydrothermal Synthesis of Nanoparticles ............................................................................................... 683

283

Application 54 - Nozzle-Free Inkjet Technology ..................................................................................................................................... 691
Application 55 - Dispersion of Fine Silica Particles Using Alkoxysilane and Industrialization .............................................................. 695
Application 56 - Barium Titanate Nanoparticles Synthesized Under Sub- and Supercritical Water Conditions ..................................... 701
Application 57 - Surface Modification of Nanoparticles by Silane Alkoxides and Their Application in Silicone-Based
Polymer Nanocomposites ............................................................................................................................................. 705
Application 58 - Formation of Thick Electronic Ceramic Films With Bonding Technique of Crystalline Fine Particles andTheir Applications ........................................................................................................................................................ 711
Application 59 - Development of New Materials by the Mild Dispersion of Nanoparticles in Slurries by Bead Milling ...................... 715
Application 60 - Three-Dimensional Structural Analysis of Nanocomposite Materials Containing Nanoparticulates ........................... 721
Application 61 - Dispersion Control of Al2O3 Nanoparticles in Ethanol ................................................................................................. 727
Application 62 - Liquid–Crystalline Inorganic Nano- and Fine Particles ................................................................................................ 731
Application 63 - Fabrication Technique of Organic Nanocrystals and Their Optical Properties and Materialization ............................. 739
Application 64 - Instantaneous Nanofoaming Method for Fabrication of Closed-Porosity Silica Particle ............................................. 745
Application 65 - Creation of Boron Nitride Nanotubes and Possibility for a Series of Advanced Nanocomposite Materials ................ 751
Application 66 - Fabrication of Functional Ceramic Devices Produced by Three-Dimensional Molding Using
Microstereolithography ................................................................................................................................................ 759
Application 67 - Morphology Control of Particles and Their Patterning ................................................................................................. 765
Application 68 - Development of Ceramic-Bonded Carbon .................................................................................................................... 777
Application 69 - Nano/Microcomposite Particles: Preparation Processes and Applications ................................................................... 781
Application 70 - Generation of Metal Nanoparticles Using Reactive Plasma Arc Evaporation .............................................................. 787
Application 71 - Synthesis of Nanoparticles by Radio Frequency Induction Thermal Plasma ............................................................... 791
Application 72 - Self-Assembly of Oxide Nanosheets: Precise Structural Control and Its Applications ................................................ 797
Application 73 - Fabrication of Ceramics With Highly Controlled Microstructures by Advanced Powder Processing.......................... 801
Application 74 - Surface Modification of Inorganic Nanoparticles by Organic Functional Groups ....................................................... 809
Application 75 - Evaluation and Applications of Dispersing Carbon Nanotube in the Polymers............................................................ 813
Application 76 - Development of Polymer–Clay Nanocomposites by Dispersion of Particles Into Polymer Materials ......................... 819
Application 77 - Development of Dispersion and Composing Processes of Nanoparticles and Their Application
to Advanced Firefighter Uniform ................................................................................................................................. 823
Application 78 - Preparation of Metal Nanoparticles and Their Application for Materials ..................................................................... 829
Application 79 - Nanotechnology Challenge in Mechanochemistry........................................................................................................ 839
Index�������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������� 845

Author’s Short Biography
Makio Naito
Makio Naito is a professor at the Joining and Welding Research Institute (JWRI), Osaka
University in Japan. He received his Ph. D. degree in chemical engineering from Nagoya
University in 1987. He served as the President of The Society of Powder Technology,
Japan from 2015 to 2019. His publications cover a wide range of studies in the fields ofadvanced materials and novel powder processing and characterization. He has authoredor coauthored more than 300 refereed journal papers and 120 review articles. He has
contributed 80 books, edited 27 books and holds more than 60 patents. He has received
several prestigious awards including the Richard M. Fulrath Award from the American
Ceramic Society (ACerS) in 2002 and the KONA Award in 2019. He has been a Fellow of
the ACerS since 2010, and serves on the ACerS Board of Directors from 2020. He has beena Professional Academy Member of the World Academy of Ceramics since 2012, and has
served on the Academy’s Advisory Board since 2018.

284

KONA Powder and Particle Journal No. 38 (2021) 285–286/https://doi.org/10.14356/kona.2021022

Information Article

3rd International Hosokawa Powder Technology Symposium
Held in China
As the special event aiming at the globalization in Asia of the Hosokawa Powder Technology Foundation, the 3rdInternational Hosokawa Powder Technology Symposium took place on Tuesday, November 19, 2019, at the Shanghai Institute of Ceramics of the Chinese Academy of Sciences (SICCAS) in China. This International Hosokawa Powder Technology Symposium was held abroad for the third time after the first one (2014, at Hosokawa Alpine AG in Augsburg,
Germany) and the second (2017, at Hosokawa Micron Powder Systems Div. in New Jersey, U.S.A.) organized by the
Hosokawa Powder Technology Foundation (HPTF). It was co-organized by the SICCAS and the Society of Powder Technology, Japan (SPTJ) and supported by the Hosokawa Micron Corporation (HMC) and Hosokawa Micron (Shanghai)
Powder Machinery Co., Ltd. (HMS). At the symposium, five lectures were given on the theme of “Powder and Particle
Technology for Advanced Materials” after the opening remarks of President Yoshio Hosokawa.
In the first lecture, high-purity, ultra-fine powder production and processing technologies for advanced materials suchas ultra-high temperature heat-resistant rocket members, reflectors, and transparent materials were presented. Then the
new nanoparticle size measuring devices, and the in-situ and real-time nanoparticle measurement using this device wasintroduced. The third lecture was concerning the functional materials based on the form of natural organisms to create
new innovative functionalities. After the lectures by the Chinese professors, two presentations were given from the
Hosokawa Group on the application of powder processing technology to various industrial product fields, and the development and commercialization of cosmetics and pharmaceuticals using PLGA nanoparticles. Finally, Mr. Uchida of
HMS closed the conference with the closing remarks.
The symposium was attended by about 130 people from universities and industries in China and the neighborhoodcountries including Japan, Korea, and Taiwan. At the venue, a panel exhibition was also made to inform the participantsof the activities of the Foundation, introducing the history and main business contents. The latest issue of the KONA
Powder and Particle Journal was displayed as well. HMS also exhibited panels to introduce the company and the powder
processing machines. The SICCAS was founded in 1928. The lecture hall on the fourth floor was a high-grade inclined
conference room with heavy chairs in all rows. Attendees were given a copy of lecture slides in English, printed in color,along with a program brochure. After the lectures, moving to the middle-sized meeting room on the 14th-floor, a social
gathering was held using the lobby in front of the room, where discussions between the lecturers and participants continued, and personal exchanges were cultivated. At the lobby, there were a few large, colorful pots and a large, beautiful ceramic screen on display that seemed to be fine arts closely related to the ceramics research and technology, and thefabulous cultural tradition of China.
This first international symposium held in Asia was very successful with interesting lectures and many participants
who have been provided with good chances to increase knowledge about the leading powder and particle technology andto get in contact with the people concerned. Without the very kind and active cooperation and assistance of especiallythe people in Shanghai, those of SICCAS and HMS, it could not have been such a great meeting at all. Following this
symposium, the International Symposium on Powder Processing Technology for Advanced Ceramics was organized by
the SICCAS and the SPTJ and sponsored by the HPTF at the same venue for the next two days. There were lively talks
and discussions on powder processing technology for advanced ceramic materials.

Lecture scenery

People involved in the lecture285

3rd International Hosokawa Powder Technology Symposium
Theme: “Powder and Particle Technology for Advanced Materials”
Place: Shanghai Institute of Ceramics, Chinese Academy of Sciences (SICCAS)
Date: Tuesday, November 19, 2019
Organizer: Hosokawa Powder Technology Foundation (HPTF)
Co-organizer: Shanghai Institute of Ceramics, Chinese Academy of Sciences (SICCAS)
The Society of Powder Technology, Japan (SPTJ)
Sponsor: Hosokawa Micron Corporation (HMC), Hosokawa Micron (Shanghai) Powder Machinery Co., Ltd. (HMS)➢ Welcome address Mr. Yoshio Hosokawa, President of Hosokawa Powder Technology Foundation,
President of Hosokawa Micron Corporation, Japan➢ Lecture 1: High purity and ultrafine powder for advanced ceramics
Prof. Dongliang Jiang, Shanghai Institute of Ceramics, Chinese Academy of Sciences, China➢ Lecture 2: A novel nanoparticle sizer and in-situ in-line real time nanoparticle sizing
Prof. Xiaoshu Cai, Institute of Particle and Two-phase Flow Measurement, University of Shanghai for
Science & Technology, China➢ Lecture 3: Bio-inspired morphology genetic materials
Prof. Di Zhang, Prof. Jiajun GU, State Key Lab of Metal Matrix Composites, School of Materials Scienceand Engineering, Shanghai Jiao Tong University, China➢ Lecture 4: Application of powder processing technology in the field of industrial materials
Ms. Xiangqun Yan, Assistant Section Manager, Powder Processing Department, Hosokawa Micron
Corporation, Japan➢ Lecture 5: Development and commercialization of cosmetics and pharmaceuticals utilizing PLGAnanoparticles
Dr. Aiko Sasai, Assistant Section Manager, Materials Business Department, Hosokawa Micron Corporation,Japan➢ Closing remarks
Mr. Yoshinori Uchida, Managing Director, Hosokawa Micron (Shanghai) Powder Machinery Co., Ltd., China➢ Social gathering

HMS supporting team with the Foundation members

286

The Opening address by Mr. Y. Hosokawa at the social
gathering in front of the ceramic screen (right: Mr. Y.
Uchida, left: Ms. X. Yan)

KONA Powder and Particle Journal No. 38 (2021) 287/https://doi.org/10.14356/kona.2021023

Information Article

The KONA Award 2019
The KONA Award 2019 was presented to Dr. Makio Naito, Professor of Joining and Welding Research Institute,
Osaka University, Japan. He has conducted ground breaking and foundational studies contributing to novel powder processing technology to develop advanced materials to address energy and environmental issues. He aimed to develop
smart powder processing techniques to support green and sustainable manufacturing of advanced materials. He has proposed and advanced new concept to achieve direct bonding between particles by activating their surfaces with mechanical energy, without any externally applied heat or added binders of any kind in the dry phase. By introducing controlled
composite particles made by the direct bonding as precursors, new microstructure electrodes for Molten Carbonate Fuel
Cells (MCFC) and Solid Oxide Fuel Cells (SOFC) have been created. Based on this concept, Professor Naito has produced electrodes for SOFC that operate at lower temperature, and developed other new materials such as fibrous
nanoparticle compacts having high thermal insulation performance at the high temperatures. By making use of particle
bonding, he has developed a new one-pot processing method to synthesize nanoparticles without applying extra heat.
Furthermore, the one-pot processing method can combine the synthesis of nanoparticles and their bonding with otherparticles to make nanocomposite granules in one step. Nanostructured granules of active materials for the cathodes andanodes for lithium ion batteries have been successfully synthesized by this novel method. Now, Professor Naito is developing electrodes for all-solid-state lithium ion batteries in collaboration with industry partners to reduce the huge thermal energy consumption traditionally required to manufacture high quality powders and ceramics.
Professor Naito has also conducted research on powder processing to increase the performance and reliability of advanced ceramics, which is a very important issue in engineering ceramics. He has developed characterization tools to
examine the evolution of large defects in ceramics during processing. Applying these tools in the ceramics manufacturing process, he has elucidated the failure mechanism, and demonstrated that very few large particles and/or large pores
will significantly degrade the fractural strength of ceramics manufactured through traditional routes. His achievements
and publications have been cited by numerous researchers, and are recognized in many review articles and journals
worldwide. Several characterization tools developed by his research group have been adopted by the International Organization for Standardization (ISO) for Technical Committee, TC 206 (Fine Ceramics).
As President of The Society of Powder Technology, Japan, he has contributed significantly to the development of powder technology, and presented many lectures to various material researchers on developing innovative synergetic materials.
He also has contributed to the publication of many books to establish a foundation of international infrastructure on powder
technology. The “Nanoparticle Technology Handbook” published by Elsevier is one example of the books he has edited.
Due to the worldwide problems with the COVID-19, the presentation ceremony of the KONA Award 2019 did not takeplace at the 54th Symposium on Powder Technology, which had been originally planned to be held in September, 2020 inTokyo, Japan but decided to be postponed.

Selected research achievements for the KONA Award 2019: One-pot processing methods developed by applying particle bonding
principle.

287

KONA Powder and Particle Journal No. 38 (2020) 288/Doi:10.14356/kona.2021024

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
	Original review papers and some limited number of original
research papers of high quality submitted to the KONA
Editorial Committees, and refereed by the reviewers and editors.
Submission of Papers
It is now possible to submit your paper online via Editorial
Manager® for KONA Online Paper Submission and Peer Review
System. For all further information, please go to the journal’s
homepage on http://www.kona.or.jp/jp/journal/info.html.
Publication in KONA is free of charge.
Publication Schedule
KONA is published annually. The publication date is around
January 10th.
Subscription
KONA is distributed free of charge to senior researchers atuniversities and laboratories as well as to institutions and libraries
in the field throughout the world. The publisher is always glad toconsider the addition of names of those, who want to obtain thisjournal regularly, to the mailing list.
Instructions to Authors(1) Language
All submissions should be written in good English. Authors may
choose either British or American English, provided that the chosen
style is used consistently. Authors from non-English-speaking countries
are encouraged to use a professional English editing service toproofread their manuscript.

(2) Manuscript format•	Electric files should be submitted to the Editorial Secretariat byonline. Authors’ short biography with less than 100 words perperson and color photographs of all the authors should be
attached to the final version.
•	The structure of manuscripts should follow the following order;
title, authors, affiliations, abstract, graphical abstract, keywords,
main text, (acknowledgement), (appendix), (nomenclature), references. The items with parentheses are not mandatory.
•	Full postal addresses must be given for all the authors. Indicate
the corresponding author by the asterisk mark“*” after thename. Telephone and fax numbers and e-mail address should
be provided for the corresponding author.
•	Abstract should not exceed 200 words.
•	G raphical abstract should be a concise, visual summary of thearticle which will be displayed in the contents list both online
and print.
•	The appropriate number of keywords is 5 or 6.
•	The maximum pages printed in KONA are supposed to be:
15 for an original paper and 25 for a review paper.
•	Symbols and units should be listed in alphabetical order with
their definition and dimensions in SI units.
•	The color figures will appear in color both on the KONA
Website (http://www.kona.or.jp) and also in the paper version.
•	Concerning references, the alphabetical system should be
adopted. Please use reference management software such as
Endnote to manage references as far as possible.
List: References should be arranged first alphabetically andthen further sorted chronologically if necessary. More than one
reference from the same author(s) in the same year must be
identified by the letters “a”, “b”, “c”, etc., placed after the yearof publication.
Examples:- Reference to a book:trunk Jr. W., White E.B., The Elements of Style, fourth ed.,S
Longman, New York, 2000.

- Reference to a chapter in an edited book: ettam G.R., Adams L.B., How to prepare an electronic version ofM
your article, in: Jones B.S., Smith R.Z. (Eds.), Introduction to theElectronic Age, E-Publishing Inc., New York, 2009, pp.281–304.

- Reference to a journal publication:
 suji Y., Tanaka T., Ishida T., Lagrangian numerical simulation ofTplug flow of cohesionless particles in a horizontal pipe, Powder
Technology, 71 (1992) 239–250. DOI: 10.1016/0032-5910(92)88030-L

Text: All citations in the text should refer to:
1. 
Single author: the author’s name (without initials, unlessthere is ambiguity) and the year of publication;
2. Two authors: both authors’ names and the year of publication;
3. Three or more authors: first author’s name followed by “etal.” and the year of publication.
Citations may be made directly (or parenthetically). Groups ofreferences should be listed first alphabetically, then chron­ologically.
Examples:“as demonstrated (Hidaka J. et al., 1995; Tsuji Y., 1992a, 1992b,
1993). Mori Y. and Fukumoto Y. (2002) have recently shown ....”(3) Copyright and permission•	The original paper to be submitted to KONA has not been
published before in any language or in any journals or media; it
is not submitted and not under consideration for publication inwhole or in part elsewhere.
•	Authors are responsible for obtaining permission from the
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for which copyright exists.
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License to all works published by the Journal. Copyright stays
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Free electronic publication of KONA is available at http://www.kona.or.jp288

Online ISSN : 2187-5537
Print ISSN : 0288-4534

Powder andParticle Journal
Impact factor:

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Indexed in Scopus, Web of Science and DOAJ

<Diamond Open Access>1983(No.1)
1990(No.8)
2009(No.27)
2013(No.31)

First publication
3 editorial blocks worldwide
Registered in Web of Science
Registered and published on J-STAGE

URL: https://www.jstage.jst.go.jp/browse/kona

About the journal

KONA Powder and Particle Journal is a peerreviewed, international, interdisciplinary andDiamond OA journal that publishes articles on
powder and particle science and technology.
This journal has been publishedannually since 1983 and is distributed
free of charge to researchers, membersofthescientificcommunities,
universities and research libraries
throughout the world, by Hosokawa
PowderTechnology
Foundation
established by Mr. Masuo Hosokawa
in 1991.

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Characterization
Computer simulation
Nanotechnology
Material science
Powder process
Particle formation
Dry powders & granules
Aerosols & Colloids & Slurry
Metals & Ceramics & Minerals
Organic-inorganic composites
Biomaterials & Pharmaceuticals
Secondary battery, Fuel cell
Electronic materials
3D printerRecyclingetc.

URL: http://www.kona.or.jp/

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