ISSN 0288-4534

CODEN: KPPJAD

KONA

Powder andParticle Journal

No.35 (2018)

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

KONA Powder and Particle Journal No. 35 (2018) 

http://www.kona.or.jp

About this Journal

Editorial Board

KONA Powder and Particle Journal is a refereed scientificjournal that publishes articles on powder and particle scienceand technology. This journal has been published annually
since 1983 and is distributed free of charge to researchers,
members of the scientific communities, universities and research libraries throughout the world, by Hosokawa Powder
Technology Foundation (http://www.kona.or.jp/) establishedby Mr. Masuo Hosokawa in 1991.

Editor-in-Chief
K. Okuyama(Hiroshima Univ., Japan)
Asian / Oceanian Editorial Board
S. Biggs(Univ. of Queensland, Australia)
X.S. Cai(Univ. of Shanghai for Sci. & Tech., China)
T. Charinpanitkul(Chulalongkorn Univ., Thailand)
J. Hidaka(Doshisha Univ., Japan)
E. Iritani(Nagoya Univ., Japan)
H. Kage(Kyushu Institute of Technology, Japan)
Y. Kang(Chungnam National Univ., Korea)
A. Kawasaki(Tohoku Univ., Japan)
D.J. Lee(National Taiwan Univ., Taiwan)
J.H. Li(Chinese Academy of Science, China)
H. Makino(CRIEPI, Japan)
S. Matsusaka(Kyoto Univ., Japan)
M. Naito(Osaka Univ., Japan)
Y. Otani(Kanazawa Univ., Japan)
Pradip(TCS, India)
F. Saito(Tohoku Univ., Japan)
Y. Sakka(NIMS, Japan)
H. Takeuchi(Gifu Pharmaceutical Univ., Japan)
W. Tanthapanichakoon (Tokyo Institute of Technology, Japan)
C.H. Wang(National Univ. of Singapore, Singapore)
S. Watano(Osaka Pref. Univ., Japan)
Secretariat
T. Yokoyama(Hosokawa Powder Tech. Foundation, Japan)
L. Cui(Hosokawa Micron Corp., Japan)

The Chinese character “ 粉 ” in the cover is pronounced“KONA” in Japanese, and means “Powder”. The hand writ” is after the late Mr. Eiichi Hosokawa, founder often “
the Hosokawa Micron Corporation (http://www.hosokawamicron.co.jp).

About the CoverAir classification is an important step in production of manyindustrial powders. Among various types of equipment, thedeflector wheel classifier, where coarse particles are deflected on the outer edge of the deflector wheel and fine particles
follow the air flow through the deflector wheel, is the dominant separation device for obtaining fine powders of a given
size and narrow size distribution of color pigments, abrasive
powders and so on. Using high-speed camera, effective particle behavior in separation process of deflector wheel classifier was analyzed at high particle loading condition focusing
on the particle-particle and particle-wall collisions. In addition, the influence of process parameters such as revolution
rate and mass loading on the separation efficiency was presented with the consistent theoretical model. Please read thepaper on pp.172–185.

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

■ Publication Office

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

Headquarters of Hosokawa Micron Corporation■ Publication Date: 10 January 2018

KONA Powder and Particle Journal No. 35 (2018) <Editorial>
1

Editor's Preface<Review Papers>
3

Complexity in Pharmaceutical Powders forInhalation: A perspective

Anthony J. Hickey
14

Nanomaterials for Environmental Solar
Energy Technologies: Applications &Limitations

Yiannis Deligiannakis
32

Critical Review on Engineering Mechanical
Quality of Green Compacts using Powder
Properties

Hojae Yi, Anuranjan Pandeya, Apoorva
Karamchandani and Virendra M. Puri
49

Direct Permeation of Nanoparticles Across
Cell Membrane: A Review

Hideya Nakamura and Satoru Watano

Contents

KONA Powder and Particle Journal No. 35 (2018) 

66 Size Control of Polymeric Particle in SoapFree Emulsion Polymerization

Tetsuya Yamamoto and Ko Higashitani
80 Review; Risk Assessment of Aerosolized
SWCNTs, MWCNTs, Fullerenes and Carbon
Black

Toshihiko Myojo and Mariko Ono-Ogasawara
89

Nanoparticles Carrying Biological
Molecules: Recent Advances andApplications

Suryani Saallah and I. Wuled Lenggoro
112 Leading Edge of Coal Utilization
Technologies for Gasification andCokemaking

Kenji Kato and Keiji Matsueda

Contents

KONA Powder and Particle Journal No. 35 (2018) 

122 Powder Particles and Technologies for
Medicine Delivery to the Respiratory System:
Challenges and Opportunities

Tomasz R. Sosnowski
139 Development Tendency and Prospect of High
Performance Coal Utilization Power
Generation System for Low Carbon Society

Kenji Tanno and Hisao Makino<Special Contribution>
150 Historical Review of Pneumatic Conveying

George E. Klinzing

Contents

KONA Powder and Particle Journal No. 35 (2018) <Original Research Papers>
160 Analysis of the Periodic Motion in a Powder
Rheometer and Development of a New
Flowability Testing Method

Ming Li, Mikel Leturia and Khashayar Saleh
172

Separation Characteristics of a Deflector
Wheel Classifier in Stationary Conditions
and at High Loadings: New Insights by Flow
Visualization

Christian Spötter, Kurt Legenhausen and Alfred
P. Weber
186

Experimental Investigations of the Effect ofChemical Additives on the Rheological
Properties of Highly Concentrated Iron Ore
Slurries

Assefa Kebede Melorie and Deo Raj Kaushal
200 Compression and Relaxation Properties ofMunicipal Solid Waste Refuse-Derived Fuel
Fluff

Charley Sprenger, Lope G. Tabil and Majid
Soleimani

Contents

KONA Powder and Particle Journal No. 35 (2018) 

209 Photostability of Risperidone in Tablets

Yuki Fujisawa, Yoshiteru Takahashi, Reiko
Teraoka and Shuji Kitagawa
216

Simulation of Mechanical Degradation ofIron Ore Pellets in a Direct Reduction
Furnace

Fernando O. Boechat, Rodrigo M. de Carvalho
and Luís Marcelo Tavares
226

Effect of Particle Size and Cohesion on
Powder Yielding and Flow

Hao Shi, Rahul Mohanty, Somik Chakravarty,
Ramon Cabiscol, Martin Morgeneyer, Harald
Zetzener, Jin Y. Ooi, Arno Kwade, Stefan
Luding and Vanessa Magnanimo
251 Forces on Particles in Time-Varying
Magnetic Fields

Jaclyn D. Ray, James R. Nagel, Dave Cohrs and
Raj K. Rajamani

Contents

KONA Powder and Particle Journal No. 35 (2018) 

258 Applicability of Probabilistic Nucleation
Modelling for the Analysis of Microfluidics
Data

Florent Bourgeois, Sébastien Teychené and
Béatrice Biscans
273

The Friction Stress Distribution of Loose
Materials to Silo Walls in Deep Pyramidal
Silos

Xuewen Wang, Zhaojian Yang and Bo Li<Information Articles>
283 Symposium Reports
286 The 24th KONA Award(Awardee: Prof. Dr. Tadafumi Adschiri)
287

General Information

Some achievements of the research for the 24th KONA Award—Continuous production of organic
modified nanoparticles by supercritical hydrothermal synthesis (p.286).

Contents

KONA Powder and Particle Journal No. 35 (2018) 1–2/Doi:10.14356/kona.2018022

Editorial

Editorʼs Preface
Kikuo Okuyama, Editor-in-Chief
Hiroshima University, JapanAs the Editor-in-Chief, I am pleased to introduce the KONA Powder & Particle Journal, Issue No.35. Continuing
the years’ tradition, this issue contains high quality reviews and original research articles focusing on the industry-­oriented powder and particle technology. It is clear that continuous improvement has always been one of the spiritsof this Journal to meet the demand of the powder and particle technology society. Three years ago, this journal was
introduced to the J-STAGE (Japan Science and Technology Information Aggregator Electronic) to support bettertransmission to the readers, continued with the introduction of the Open Access policy last year.
The Editorial Committee, consisting of three editorial boards located in Europe, America, and Asia/Oceania, received more than 50 high-quality articles this year and anticipate to receive more in the future. To accommodate
this trend, the Editorial Manager® (EM) system was used to facilitate easy manuscript submission, reviewing, andtracking. The EM system allows the submitted articles to be immediately assessed by the Editorial Committee
members, thereby allowing the contributors to receive the decisions at their earliest opportunity and have sufficient
time to improve their manuscripts.
The increasing number of articles received by the editorial office reflects the growing research efforts concerning
powder and particle technology. The interest ranges from the fields of basic sciences of physics, chemistry, and biology, to the applied fields such as chemical and process engineering. This is in conjunction with the vast-growing
applications of powder and particle technology, such as heat-resistant materials, memory and recording media,
photo functional materials, and energy-supplying devices. The demand for high performance materials is escalatingeven more with the emerge of artificial intelligence and the Internet of Things. This is something that needs to be
anticipated and further explored by the powder and particle technology community. Researchers and engineers inthis field need to continuously develop efficient, scalable, and environmentally friendly manufacturing processes
for high performance materials. This also includes post-processing handling technology to realize fully functionalized materials with high purity. This is the message that we tried to convey through this year’s issue.
Our aim is to introduce high quality research throughout the world. In-line with the rapid advancement of thepowder and particle technology, we attempt to increase the publication frequency of this journal in the near future
while keeping the quality of the published articles. In the meantime, I hope this issue would be a valuable platform
for the discourse of powder and particle technology advancement.
Finally, I would like to thank Dr. Jusuke Hidaka, emeritus professor of Doshisha University, Japan, for his continuous dedication as the former Editor-in-Chief of KONA Powder and Particle Journal.

Copyright © 2018 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

Reviewer Appreciation

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

BAŁDYGA, Jerzy

KAWASAKI, Akira

RASTEIRO, Maria da Graça

BISCANS, Béatrice

KLINZING, George E.

ROSATO, Anthony D.

CASTRO, José Adilson de

KWADE, Arno

SAITO, Fumio

COPPENS, Marc-Olivier

MAKINO, Hisao

SAKAI, Mikio

FURSE, Cynthia

MATSUSAKA, Shuji

SEN, Surajit

GARCIA-CONTRERAS,

MEESTERS, Gabriel

SHINTO, Hiroyuki

LucilaMILANI, Paolo

SHIRAKAWA, Yoshiyuki

GOTOH, Kuniaki

MORI, Yasushige

SUZUKI, Hiroshi

GRADOŃ, Leon

MOUDGIL, BrijTAVARES, Luis Marcelo

HICKEY, Anthony

NAGAO, Daisuke

TOKORO, Chiharu

HUANG, Ching-Chung

NAKAMURA, Hideya

TSUJI, Takuya

INOUE, Yohei

OKUYAMA, Kikuo

VALVERDE, Jose Manuel

KANDA, Yoshiteru

PURI, Virendra

YOKOYAMA, Toyokazu

KANO, Junya

RAJAMANI, Raj

YOSHIDA, Mikio

Kikuo Okuyama
Editor-in-ChiefProf. emeritus, Hiroshima University
October 2017

2

KONA Powder and Particle Journal No. 35 (2018) 3–13/Doi:10.14356/kona.2018007

Review Paper

Complexity in Pharmaceutical Powders for Inhalation:
A perspective †Anthony J. Hickey
1

RTI International, USA

Abstract
Pharmaceutical aerosol powders intended for inhalation are required to have unique performance characteristics
that are highly dependent on their physico-chemical properties. A wide range of analytical methods have been
applied to study particle structure, size distribution, surface properties and subsequent behaviour of powders with
the intention of predicting their performance. However, particle interactions are dictated by complex fundamental
forces that impact on the efficiency and reproducibility of delivery and thereby the quality, efficacy and safety of
the final product. This manuscript reviews the interplay of physico-chemical properties of powder and thecomplex process and analytical variables that must be monitored and controlled to effectively predict powder
performance.
Keywords: powder, particle, drug, inhalation, characterization

1. Introduction
Understanding the role of powder properties in theirperformance can be likened to the aphorism of the blind
men and the elephant (Shah I., 1993). All methods, applied correctly, describe a specific feature of the particle
or powder. However, without knowledge of all of the features that define the whole object or population of objects
the conclusions about it/them may be misleading. The
challenge to the pharmaceutical research and development
community has been to collect sufficient information on
powder properties to allow prediction of behavior.
Interest in powder properties with respect to ensuring
efficient and reproducible performance in deliveringdrugs from inhalers has driven an enormous research effort over a period of more than 50 years. The complex interaction of fundamental aspects of physical chemistry,mechanical engineering, aerosol physics and the ability toidentify and consider all relevant variables has limited thedevelopment of comprehensive predictive models of product behavior (Hickey A., 2003). The current capacity to
use the knowledge of key parameters to guide product optimization appears to involve systematic consideration of
the most important factors but requires iteration with respect to unidentified variables or confounding of known†
1

Received 21 December 2016; Accepted 15 February 2017
J-STAGE Advance published online 8 April 2017
3040 Cornwallis Road, Research Triangle Park, NC 27709, USA
E-mail: ahickey@unc.edu
TEL: +1-919-541-6771 FAX: +1-919-541-6936

variables that lead to sub-optimal performance (Hickey A.
and Xu Z., 2013).
It is important to recognize that dry powders are
non-equilibrium systems (although time scales can belong) at all dimensional scales of scrutiny. The historicalview of individual particles as essentially unchanging objects has to be revised to reflect their ability to respond to
manufacturing, storage and general environmental conditions. This has implications for their interaction with eachother and the container or conveyor which influences bulk
powder properties.
The intent of this review is to describe the factors
known to contribute to dry powder inhaler product performance and then to discuss approaches to characterization that might account for interactions of these variables
or for unknown variables to contribution.

2. Methods of manufacture and particle
morphology
2.1 Milling
Milling has a history that can be traced through centuries for the processing of raw materials for food and pharmaceutical products. The desired particles size for aerosoldelivery of drugs to the lungs requires a high-energy
method to overcome the forces of attraction between molecules usually in the crystalline solid state to create alarge surface area (Hickey A. and Ganderton D., 2001;
Shur J. et al., 2012). The method, as depicted in Fig. 1,

Copyright © 2018 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/).

3

Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

Fig. 1

Schematics of (a) front view of an air jet mill and (b) side view showing the filter and collection vessel
separated by the cyclone behind the mill.

employed throughout modern times is air jet milling inwhich particles are carried on high a velocity gas stream(usually air or nitrogen) into an opposing high velocity
gas stream such that particles impinge on each other andthe walls of the mill shattering ultimately into respirable
sizes (1–5 μm) (Fig. 1a). These respirable particles arecollected by elutriation, in the figure passing into theplane of the image through a central tube and entering a
cyclone separator as shown in Fig. 1b (Hickey A., 1993).
In the example shown air then passes to a bag filter andexits while powder under the influence of impaction andsedimentation forces is collected in a vessel directly below the filter. This process can be continued for as long asnecessary to the capacity of the collection vessel and withattention to occlusion of the filter.
The production of particles by milling can be controlled
in terms of the processing variables of gas flow and temperature but cannot readily be controlled at the level ofthe individual particle production and the outcome of theprocess is highly dependent on the starting material interms of both composition and state which makes it a difficult process from which to extract general principles.
Each drug treated in this manner requires full characterization in order to guarantee quality and performance inthe final product.

2.2 Spray drying
Spray drying has been of increasing interest since overthe last 20 years as it became evident that the techniqueresulted in particles and powders with unique physico-­chemical and performance properties (Vehring R., 2008;
Van Oort M. and Sacchetti M., 2007). The ability to create low-density particles promoted the ability to efficiently disperse particles. Since most spray dried material
is amorphous in nature the influence on stability needs tobe addressed. For proteins and peptides this is a desirable

4

Fig. 2

Schematic of a spray drier illustrating the key elementsof solution feed, gas supply, temperature control andmonitoring and collection vessels before and after thesize selective cyclone separator.

solid-state form and is likely to be stable on storage. For
small molecular weight drugs the amorphous form is unlikely to be the most stable with respect to fluctuations inmoisture and temperature (Carstensen J., 1990). Consequently, since most drugs are of small molecular weight,
packaging considerations are required to ensure the stability of the final product most notably the use of moistureimpermeable wrapping, e.g. aluminum, or inclusion ofdesiccant where the response to equilibrium moisture
content and fluctuations are more modest (Atkins P. andCrowder T., 2004).
Fig. 2 illustrates the key components of a spray drier
including the liquid feed to the atomization nozzle, drying
gas supply, the drying tower, cyclone separator and collection vessels for coarse and fine particles. This is a simplified image as it does not show condensers, heater/cooler, recycling and feedback electronics that are integral
parts of this equipment.

Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

2.3 Supercritical fluid manufacture
Supercritical fluid manufacture showed great promise
as a means of accurately and reproducibly controlling
particle size and morphology when it first appeared as an
approach to the manufacture of drug particles in the
1990s (Van Oort M. and Sacchetti M., 2007). Several
methods were developed each of which had its merits but
all of which required multiple small batch production cycles to achieve pilot or production scale quantities of processed drug. Rapid expansion supercritical solutions orantisolvent techniques are the most prominent methods
using supercritical gases such as carbon dioxide.

2.4 Mixing/Blending
The modern history of dry powder inhalers can betraced back to the 1960s in particular to the Cromolyn
Sodium product delivered from a Spinhaler (Pfisons)(Sanders M., 2011). From the outset mixing/blending wasa central element of the powder formulation and the concept of attaching milled respirable particles to the surfaceof lactose carrier particles became the standard, which remains most common to this day. The importance of themixing process cannot be understated as it dictates boththe ability to fill the dosing containment unit (e.g. capsule,blister or reservoir) and the efficiency with which the drug
particles can be detached and enter the entraining air supply (Stewart P., 1986; Young P. et al., 2007).

3. Physico-chemical properties
3.1 Primary particle size and distribution
Primary particle size and distribution is an important
property to measure for aerosol products. The aerody-

Fig. 3

namic performance of aerosols depends on the ability to
input energy usually from the patient’s inspiratory airflow
to move the powder and disperse it into particles that canenter the lungs. This non-equilibrium phenomenon rarely
disperses drug completely into primary particle sizes.
However, by measuring the primary particle size and distribution an important metric for underlying quality as
well as a target for complete dispersion is established.
Primary particle size can be evaluated by two complementary methods an indirect population measurement.
Laser diffraction measurement can be conducted to assessparticles in liquid suspension or dry powders at high-­pressure drop, to allow sufficient shear to break the powders in individual particles (Behara S. et al., 2012; Jaffari
S. et al., 2013; 2014). Scanning electron microscopy allows imaging on a scale to visualize particles in respirable
size ranges (Hickey A. and Xu Z., 2013). Individual particles can be distinguished from aggregates. However, microscopy generally does not allow sufficient numbers ofparticles to be measured for quantitative statistical representation of the population of particles (Allen T., 1990).

3.2 Shape and density
Particle shape is an important property dictating their
behavior. Fig. 3 illustrates schematically important featuresof particle surfaces. While the ideal particle is spherical(Fig. 3a(i)) and is the basis for most measures of particle
size (equivalent spheres) most drug particles deviate fromsphericity and exhibit some form of surface rugosity(Fig. 3a(ii)) (Chew N. and Chan H-K., 2001). In the extreme the shape of the particle can be significantly distorted in one (needle or fiber, Fig. 3a(iii)) or two (plate or
flake) dimensions (Mullin J., 1993). The latter usually occurs because of restriction of crystal growth in one (plateor flake) or two (needle or fiber) dimensions. The shape of
the particle and surface functionality are inextricably

Schematics illustrating (a) (i) spherical, (ii) rugose or (iii) elongated Particle morphology and (b) Forcesof interaction at the interface between two particle surfaces.

5Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

linked since the surface may exhibit specific features
based on the action of impurities during crystallization or
the presence of different polymorphs or moisture at thesurface. Fig. 3b illustrates a variety of surface phenomena resulting from the presence of moisture, crystallinity,
electrostatics, discontinuities and, impurities. These surface functions increase the interaction of particles beyond
that resulting from the innate van der Waals forces.
Once features exist the way in which they borderthree-dimensional space with edges or corners createsboth a physical and energetic differential that impacts on
the likelihood of interaction with other surfaces.
Some mathematical approaches have been taken to depicting irregularly shaped particles with a view to correlating the numerical descriptor with subsequent behavior.
Fig. 4 shows two methods that have been applied. The
first is to inscribe the image of the particle periphery withradii from a central point that can then be described inpolar co-ordinates, distance from the origin for designated angles, from which Fourier coefficients can be derived that are correlated with a variety of shapes (Tian Y.
et al., 1994; Hickey A. and Concessio N., 1997). First,
second, third, etc. Fourier coefficients are considered torepresent roundness, squareness, triangularity, and so on.
Fractal analysis has been applied to the shape of particles as a means of expanding shape considerations beyond
conventional simple shape factors more descriptive terms
such as Fourier coefficients based on polar co-ordinates(Hickey A. and Concessio N., 1997). The Fractal dimension introduced for the first time the notion of non-integer
dimensions < 3D to convey greater information about theparticle than the usual one or two dimensional descriptors
obtained from imaging individual particles and subse-

Fig. 4

6

Depiction of (a) Polar co-ordinate image and the data
derived for analysis that would be fit to a Fourier series
to obtain coefficients and (b) The use of different
scales, top, to measure the surface by connecting
chords around the periphery, middle, to allow estimatesof the perimeter length to be plotted against the stride
length on a log-log scale, bottom, from which the Fractal Dimension, δ, is measured.

quently statistically aggregated into particle population
data represented by the number of particles observed andthen described in terms of average and distribution.
The aerodynamic behavior of aerosol particles is dictated by the particle size and other physical properties
including shape and density as described by Stokes’ equation. The importance of these properties was overlooked
until relatively recently when the potential to modify
them to enhance aerosol performance was realized(Crowder T. et al., 2002).
Spray drying may be employed to produce low-density
particles. The method involves the spraying of hollow
shell or highly porous particles (whiffle ball) that present
delicate membrane-like surfaces in various geometricstructures permeated by air (Vehring R., 2008; Van Oort
M. and Sacchetti M., 2007). These particles due to their
low density (somewhere between the true density of asolid particle and the density of air) may be quite large but
have a small aerodynamic diameter as described by
Stokes’ Law. In addition, the distance between the molecules of drug in the particle and those in adjacent particles
means that the van der Waals forces are much lower thana solid particle due to the reduced Lennard Jones potential(Telko M. and Hickey A., 2005; Dunbar C. et al., 1998).
Consequently, these particles require very little energy todisperse as an aerosol. Indeed, if placed on a flat surface
in room air the local convective air movement may besufficient to generate the aerosol.
Elongated particles are known to orientate longitudinally into the direction of the airflow (Davies C., 1979;
Gonda I. and el Khalik A., 1988; Fults K. et al., 1997).
Consequently, for specific length, cross-sectional area diameter and aspect ratio they have the capacity to move in
air predominantly as a function of their cross-sectional
area diameter suggesting a limited radius of gyration
while in motion in the two dimensions represented by thecross section (Lippmann M., 1990).
Most dry powder inhaler products employ blends of
drug with lactose. The surface properties of the drug andthe lactose play a significant role in their interaction and,
thereby, in the energy required to separate and dispersethem into primary drug and lactose particles (Xu Z. et al.
2011). The use of ∝-lactose monohydrate a monoclinic
crystal presents proportionately large flat surfaces to thesmaller drug particles (Hickey A. et al., 2007a and2007b). These surfaces are deceptive in their apparent
uniformity in that they can become discontinuous throughthe presence of impurities (Crowder T. et al., 2003). The
presence of impurities, moisture, amorphous lactose or
β-lactose monohydrate at the surface creates variablesurface energy densities for interaction with the drug
(Fig. 3b) (Hickey A. et al., 2007a). The potential for variation in nature and extent of drug binding gives rise to
non-uniformity in performance, which has implications

Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

for both quality and therapy (Telko M. and Hickey A.,
2005; Dunbar C. et al., 1998).
A variety of methods of analysis have been evaluatedfor their utility in characterizing surface forces including
thermal analysis (bulk polymorphic forms) inverse gas
chromatography (surface polar and non-polar forces,(Telko M. and Hickey A., 2007)), atomic force microscopy (surface free energy, (Begat P. et al., 2004)), static(Carstensen J., 1993) and dynamic (Hickey A. andConcessio N., 1996) angle of repose (bulk flow properties
as a measure of particle interaction), Faraday cage (standing electrostatic charge, (Smyth H. et al., 2004)), electronic samplers for charge determination as a function of
aerodynamic particle size (Telko M. et al. 2007; Telko M.
and Hickey A., 2014; Wong J. et al., 2015).

4. Complexity
The ability to predict powder performance has clear
implications for ensuring the quality and efficacy of apharmaceutical aerosol formulation. In addition, accurate
prediction would allow efficient and cost-effective product development with a high probability of meeting withregulatory approval by accommodating the desire for
quality by design.
It would be scientifically elegant to approach the desire
to predict powder performance from the perspective of
the fundamental underlying forces of interaction between
particles discussed earlier. However, the inability to separate these forces in the heterogeneous systems of whichpharmaceutical formulations are composed has confounded efforts to reduce the problem to basic principles.
Various groups have chosen to examine the problem fromthe perspective of probing powder systems experimentally to derive data on performance that can inform models that allow prediction of behavior (Hickey A. and XuZ., 2013; Steckel H. and Bolzen N., 2004; Jones M. andPrice R., 2006; Grasmeijer F. et al., 2013, 2014).
The powders employed for inhalation consist predominantly of blends with lactose or as spray-dried particles. It
is important in considering the dispersion properties of apowder to consider it as a function of quantifiable descriptors of the energy imparted by the airflow such as
Reynolds’ number, resistance or shear stress. These terms
can easily be described for most devices but it should be
noted that all devices include design features intended toaid in deaggregation such as baffles, tortuous channels orother impaction surfaces (Telko M. and Hickey A., 2005).
Consequently, when considering terms such as pressure
drop (at a fixed airflow rate) or airflow rate (at the defined device pressure drop) across or through the device
as a reference term for the energy imparted the design
features may make the data deviate from quantitative

generalizable relationships while giving qualitative information about formulation performance.
Fig. 5 illustrates a model of the proposed interactions
between drug and lactose assuming regions of different
surface energy density exist to which drug particles exhibit a range of binding properties. When subject to shear
and turbulence in air, in the mouthpiece or when passing
through or around a tortuous air path feature, impacting
on device surfaces and with other particles drug is liberated from the surface of lactose by the action of airflow
and constraints of the air path. Incomplete dispersion may
be explained by the heterogeneity of the surface energy
density.
Fig. 6 illustrates a second model proposed for interactions between drug and lactose assuming that not only isdrug associated directly with lactose but through cohesion
and incomplete mixing aggregates exist at the surface of
lactose that because of their larger size are stripped more
readily from the surface and then deaggregated by theshear, turbulence and impaction described earlier. Thismodel is not mutually exclusive with respect to the firstmodel but adds a layer of additional information thatmight help in formulation that being the cohesive or adhesive nature of the component particles.

Fig. 5 Schematic of small drug particles at the surface of large
lactose carrier particle depicting their liberation as afunction of airflow and air path features.

Fig. 6 Schematic of small drug particles at the surface of large
lactose carrier particles some in the form of aggregatesdepicting their liberation initially as a deaggregation
phenomenon in response to airflow.

7

Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

Fig. 7

Diagrams of (a) the rotating drum dynamic angle of repose measurement technique and (b) vibrating
spatula with mass detection.

4.1 Powder flow
The movement of most pharmaceutical powders is irregular but almost all processes in which powders play arole would be better served by uniform flow and behavior
including aerosol generation. Since the nature of powder
movement can vary it can be inferred that knowledge ofthis phenomenon would be useful in predicting a varietyof powder properties such as dilation followed by generation for aerosol formulations.
There are several methods for evaluating powder flow
properties and their underlying physics including rotating
drum (Hickey A. and Concessio N., 1996; Crowder T. etal., 1999, Crowder, T. and Hickey A., 1999), vibrating
spatula (Hickey A. and Concessio N., 1994; Crowder T.
and Hickey A., 1999) and critical orifice (Flodex, (Taylor
M. et al., 2000)). When oscillations in the motion of powder in a rotating drum or delivery from a vibrating spatula, as depicted in Fig. 7, are plotted in phase space atypical attractor is observed that can be characterized bya Fractal Dimension (δ) or Lyupanov Exponent reflecting
the divergence of each successive data point from the previous one. This single dimension, which can be viewed asa measure of irregularity in microflow can then be correlated with the ability to disperse powders as aerosols(Concessio N. et al., 1999; Crowder T. and Hickey A.,
2006). The predictive nature of this approach renders it apotentially useful tool for the characterization of powder
blends. Formulation optimization might be performed byranking powders in terms of flow (powders with small δflow better than those with large δ) as a predictor of theirability to effectively be disperse as aerosols.

from each other and surfaces during the aerosolization
process (Begat P. et al., 2004; Behara S. et al., 2011a;
2011b; 2011c). Drug entrainment onto the inspiratory flowof the patient is influenced by these interactions and consequently may result in variable efficacy (Grasmeijer F. etal., 2013; Behara S. et al., 2011d).

4.3 Powder aerosol dispersion equation
Collecting experimental data and developing a working
model, rather than a physical model might circumvent thephysical complexity of the models of interaction between
particles in a blend. One approach to measuring the interaction of particles and data collection is to investigate theenergy required to separate them in a standardized airflow
using an entrainment tube (Fig. 8a) and inertial impactor
for aerodynamic particle size measurement (Fig. 8b).
This approach has been explored for several drugs in lactose blends (Mansour H. et al., 2010; Xu Z. et al., 2010a,
2010b, 2010c). The detachment in response to applied
shear stress was considered analogous to desorption phenomena in which particles are removed from low energy
binding sites and increasing quantities are removed athigh shear as higher energy binding sites are evacuated(Xu Z. et al., 2010c). These experiments resulted in the
proposal of a powder aerosol dispersion equation (PADE)(Xu Z. et al., 2010c).

4.2 Cohesive adhesive balance
The cohesive adhesive balance (CAB) model refers to
the interaction between drug and lactose in the blend that
influence the energy required for detachment of particles

8

Fig. 8 Illustrations of (a) a standardized entrainment tube and;(b) its position with respect to a stacked, cascade impactor for aerodynamic particle size determination.

Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

5. Aerosol performance

5.4 Aerosol delivery rate

5.1 Laser diffraction volume diameter
determination

In evaluating the performance of DPIs the importanceof aerosol delivery rate (ADR) is often overlooked. The
APSD and delivered dose uniformity (DDU) are clearly
important quality measures for the product performancebut the relevance of ADR may not be as evident. The relevance of ADR only becomes obvious when the purpose of
a DPI is considered. Drug delivered as an aerosol from a
DPI is intended, within reasonable limits, to be controlledwith respect to the characteristics that may be importantin lung delivery and, therefore, in therapeutic effect. The
portion of the inspiratory flow on which the aerosol is delivered is critical to its site of deposition and the ADR, or
mass of aerosol powder delivered at different times withrespect to initiation of airflow is an important indicator of
performance in patients (Ziffels S. et al., 2015). Fig. 9 illustrates this point by adopting an approach of following
obscuration of a light source placed perpendicularly to thedirection of aerosol delivery as sampling into an inertial
impactor is performed (Fig. 9a). For illustration the aerosol dispersion is separated into three periods initially visualizing increasing mass, followed by peak mass andterminating in declining mass delivery (Fig. 9b). This ismeasured by a detector in which obscuration is the reciprocal of light detected. Differences in the shape of the obscuration curve indicate differences in ADR (Fig. 9c).
The complexity of dry powder inhalers can only befully grasped when the need for control at all scales spatial and temporal scrutiny is considered. Fig. 10 summarizes the dimensions, the properties, the processes and thecontrol variables that can be employed to influence eachof the systems. There are points in the preparation of dry
powders for inhalation where certain properties are
known to positively influence the aerosol performance ofthe powder. Arguably, great progress has been made withregard to qualitative understanding of which factors may
be important in supporting product development and by
iteration performance can be optimized sufficiently tomeet regulatory requirements.
Particle surface treatments such as smoothing (Young
P. et al., 2002), mechanical coating (Zhou Q. et al., 2013),
corrugation (Chew N. and Chan K-K., 2001) and the useof fines to obscure high surface energy density sites(Jones M. and Price R., 2006) are among the promisingstrategies to limit the influence of formulation variables
on performance. The use of standardized techniques toevaluate the formulation independently of the device allows initial optimization (Louey M. et al., 2006) and theuse of inspiratory flow profiles in sampling may be moresensitive to performance variation than constant flow
rates currently used (Dunbar C. et al., 2000). Ultimately,
the device and formulation combination must be evaluated (Behara S. et al., 2011d; Adams W. et al., 2012) toLaser diffraction instruments are used routinely formeasurement of particle size distribution of aerosol powders. When used with powder dispersion systems operating at different pressure drops or when dispersed insuspending liquid particles may be separated into primarysizes to establish the limit of efficient dispersion possible
with an effective dry powder inhaler (Young P. et al.,2007; Behara S. et al., 2012). The particle size obtained at
different dispersing pressure drops may be used to characterize the ease of deaggregation (resistance to deaggregation due to particle interactions).

5.2 Aerodynamic particle size distribution
The aerodynamic particle size distribution (APSD) is
generally measured by inertial impaction (Tougas T. etal., 2013). Inertial impactors size segregate powders using
a series of jets of decreasing orifice size through which air
is drawn, at a fixed rate by a vacuum. An increasing linear velocity at each successive collection stage is thereby
established. The combination of the mass of particles inthe distribution and range of linear velocities results insamples of decreasing particle size being sampled as anaerosol passes through each successive stage of the impactor.

5.3 Delivered dose
The dose delivered from the inhaler is that which leaves
the mouthpiece of the device for which a proportion, thefine particle dose, is considered in a size that is relevant topulmonary delivery (USP, 2011). The fine particle doseshould not be confused with the respirable dose. The fineparticle dose is designated as the entire dose below a specific particle size, usually 5mm unless otherwise stated,that is thought to be broadly relevant for pulmonary drugs
as a quality measure (Hickey A., 2004). The respirable
dose is derived from theoretical and experimental data onlung deposition and considers the probability of particles
over a range of sizes to penetrate to the lungs. Various
public and occupational health agencies have specificdefinitions for respirable dose (Hinds W., 1999). The factthat a single fine particle doses is equivalent to a range of
respirable doses based on the particle size distribution has
been considered elsewhere (Martonen T. et al., 1992) It is
important to note that caution must be exercised in interpreting fine particle dose, a quality measure, as a predictor of lung delivery.

9Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

Fig. 9(a) Arrangement of apparatus to follow light obscuration at the inlet to an inertial impactor; (b) Depictionof the density of particles in air (dictating light obscuration) at three intervals after (top to bottom) initiation of aerosol delivery during aerosol delivery; (c) The real-time measurement of obscuration at the detector corresponding with (b), initial, middle and end (top to bottom).

Fig. 10 Properties with respect to scale of scrutiny of a pharmaceutical dry powder aerosol formulation and theprocesses and variables that must be controlled to optimize desired performance characteristics withrespect to quality, safety and efficacy.

meet the regulatory requirements (US FDA, 1998). The
US Food and Drug Administration Guidance on a specific
dry powder product (combined fluticasone propionate andsalmeterol xinofoate) dry powder inhaler intended to leadto in vitro and in vivo bioequivalence (Apiou-Sbirlea G. etal., 2013) serves to emphasize the importance of understanding and controlling all phenomena described above(US FDA 2013). Greater progress is required in linking
the spectrum of known properties to defined process variables if sufficient knowledge and understanding is to begained to predict and efficiently control performance.

10

6. Conclusion
The complexity of powder behavior in DPIs can beconsidered at several levels. The first is the compositionand structure of individual particles. The second is thecomposition and structure of populations of particles atrest. The third is the motion of particles as a partially dilated flowing mass. The fourth is the motion of particles
as fully dilated dispersed aerosols. Each of these elements
is intricately woven into the overall performance of the
product dictating the delivered dose and its aerodynamic
particle size distribution. These performance measures in
conjunction with pulmonary function, anatomy and phys-Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

iology dictate efficacy and bioavailability of depositeddrug.
Acknowledging that complexity at all levels of scrutiny
in powder properties and behavior emphasizes the difficulty of attempting to control static variables and expecting controlled product performance. A comprehensive
understanding of the dynamics is central to managing
performance within acceptable limits.

References
Adams W.P., Lee S.L., Plourde R., Lionberger R.A., Bertha
C.M., Doub W.H., Bovet J.-M., Hickey A.J., Effects ofdevice and formulation on in vitro performance of dry
powder inhalers, The AAPS Journal, 14 (2012) 400–409.
Allen T.A., Microscopy, in: Particle Size Measurement, fourthed., Chapman and Hall, New York, 1990, pp. 217–248.
Apiou-Sbirlea G., Newman S., Fleming J., Siekmeier R.,
Ehrmann S., Scheuch G., Hochhaus G., Hickey A., Bioequivalence of inhaled drugs: Fundamentals, challenges
and perspectives, Therapeutic Delivery, 4 (2013) 343–367.
Atkins P.J., Crowder T.M., The design and development of inhalation drug delivery systems, in: Pharmaceutical Inhalation
Aerosol Technology, second ed., Hickey A.J. (Ed.), Informa
Healthcare, New York, 2004, pp. 279–309.
Begat P., Morton D.A.V., Staniforth J.N., Price R., The cohesive-­adhesive balances in dry powder inhaler formulations I:
Direct quantification by atomic force microscopy, Pharmaceutical Research, 21 (2004) 1591–1597.
Behara S.R.B., Larson I., Kippax P., Stewart P., Morton D.A.V.,
Insight into pressure drop dependent efficiencies of dry
powder inhalers, European Journal of Pharmaceutical Sciences, 46 (2012) 142–148.
Behara S.R.B., Kippax P., McIntosh M.P., Morton D.A.V., Larson
I., Stewart P., Structural influence of cohesive mixtures ofsalbutamol sulphate and lactose on aerosolisation andde-agglomeration behaviour under dynamic conditions,
European Journal of Pharmaceutical Sciences, 42 (2011a)
210–219.
Behara S.R.B., Larson I., Kippax P., Morton D.A.V., Stewart P.,
An approach to characterising the cohesive behaviour of
powders using a flow titration aerosolisation based methodology, Chemical Engineering Science, 66 (2011b) 1640–
1648.
Behara S.R.B., Larson I., Kippax P., Morton D.A.V., Stewart P.,
The kinetics of cohesive powder de-agglomeration fromthree inhaler devices, International Journal of Pharmaceutics, 421 (2011c) 72–81.
Behara S.R.B., Kippax P., Larson I., Morton D.A.V., Stewart P.,
Kinetics of emitted mass—a study with three dry powder
inhaler devices, Chemical Engineering Science, 66 (2011d)
5284–5292.
Carstensen J., Solid state stability, in: McGinity J.W. (Ed.),
Drug Stability: Principles and Practices, Marcel Dekker,
Inc., New York, 1990, pp. 129–164
Carstensen J.T., Angle of repose, in: Carstensen J.T. (Ed.) Phar-maceutical Principles of Solid Dosage Forms, Technomic
Publishing Co, Inc., Lancaster, 1993, pp. 27–29.
Chew N.Y.K., Chan H.-K., Use of solid corrugated particles toenhance powder aerosol performance, Pharmaceutical
Research, 18 (2001) 1570–1577.
Concessio N.M., VanOort M.M., Knowles M.R., Hickey A.J.,
Pharmaceutical dry powder aerosols: Correlation of powder
properties with dose delivery and implications for pharmacodynamic effect, Pharmaceutical Research, 16 (1999)
828–834.
Crowder T.M., Hickey A.J., An instrument for rapid powder
flow measurement and temporal fractal analysis, Particle &Particle Systems Characterization, 16 (1999) 32–34.
Crowder T.M., Hickey A.J., The physics of powder flow:
Applied to pharmaceutical solids, Pharmaceutical technology., 24 (2000) 50–58.
Crowder T.M., Hickey A.J., Louey M.D., Orr N., Particulate
systems: manufacture and characterization, Interpharm/
CRC, Boca Raton, FL, 2003, pp. 9–26.
Crowder T., Hickey A., Powder specific active dispersion forgeneration of pharmaceutical aerosols, International Journal of Pharmaceutics, 327 (2006) 65–72.
Crowder T.M., Rosati J.A., Schroeter J.D., Hickey A.J., Martonen
T.B., Fundamental effects of particle morphology on lungdelivery: Predictions of stokes’ law and the particular relevance to dry powder inhaler formulation and development,
Pharmaceutical Research, 19 (2002) 239–245.
Crowder T.M., Sethuraman V., Fields T.B., Hickey A.J., Signal
processing and analysis applied to powder behavior in arotating drum, Particle & Particle Systems Characterization, 16 (1999) 191–196.
Davies C.N., Particle fluid interactions, J. Aerosol Sci., 10 (1979)
477–513.
Dunbar C.A., Hickey A.J., Holzner P., Dispersion and characterization of pharmaceutical dry powder aerosols, KONA
Powder and Particle Journal, 16 (1998) 7–45.
Dunbar C.A., Morgan B., Van Oort M., Hickey A.J., comparison of dry powder inhaler dose delivery characteristics
using a power criterion, PDA Journal of Pharmaceutical
Science and Technology, 54 (2000) 478–484.
Fults K.A., Miller I.F., Hickey A.J., Effect of particle morphology on emitted dose of fatty acid-treated disodium cromoglycate powder aerosols, Pharmaceutical Development andTechnology, 2 (1997) 67–79.
Gonda I., el Khalik A.F.A., Aerodynamic properties of different
crystal forms of hexamethylmelamine, The Annals of
Occupational Hygiene, 32 (1988) 379–390.
Grasmeijer F., Hagedoorn P., Frijlink H.W., de Boer A.H., Drugcontent effects on the dispersion performance of adhesive
mixtures for inhalation, PLoS ONE, 8 (2013) e71339.
Grasmeijer F., Lexmond A.J., Maarten V., Hagedoorn P., Hickey
A.J., Frijlink H.W., de Boer A.H., New mechanisms to
explain the effects of added lactose fines on the dispersion
performance of adhesive mixtures for inhalation, PLoS
One, 9 (2014) 1–11.
Hickey A.J., Lung deposition and clearance of pharmaceuticalaerosols: What can be learned from inhalation toxicology
and industrial hygiene?, Aerosol Science and Technology,

11Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

18 (1993) 290–304.
Hickey A.J., Pharmaceutical inhalation aerosol powder dispersion—An unbalancing act, American Pharmaceutical
Review, 6 (2003) 106–110.
Hickey A.J., Summary of common approaches to pharmaceutical aerosol administration, in: Pharmaceutical Inhalation
Aerosol Technology, second ed., A.J. Hickey (Ed.), Marcel
Dekker, Inc., New York, NY, 2004, pp. 385–421.
Hickey A.J., Concessio N.M., Flow properties of selected pharmaceutical powders from a vibrating spatula, Particle &Particle Systems Characterization, 11 (1994) 457–462.
Hickey A.J., Concessio N.M., Chaos in rotating lactose powder
beds, Particulate Science and Technology, 14 (1996) 15–25.
Hickey A.J., Concessio N.M., Descriptors of irregular particle
morphology and powder properties, Advanced Drug Delivery Reviews, 26 (1997) 29–40.
Hickey A.J., Ganderton D. (Eds.), Size reduction and classification, in: Pharmaceutical Process Engineering, Informa
Healthcare, New York, 2001, pp. 174–197.
Hickey A.J., Mansour H.M., Telko M.J., Xu Z., Smyth H.D.C.,
Mulder T., McLean R., Langridge J., Papadopoulos D.,
Physical characterization of component particles included
in dry powder inhalers. I. Strategy review and static characteristics, J Pharm Sci, 96 (2007a) 1282–1301.
Hickey A.J., Mansour H.M., Telko M.J., Xu Z., Smyth H.D.C.,
Mulder T., McLean R., Langridge J., Papadopoulos D.,
Physical characterization of component particles included
in dry powder inhalers. II. Dynamic characteristics, J
Pharm Sci, 96 (2007b) 1302–1319.
Hickey A.J., Xu Z., Balancing particle properties to achieveeffective inhaled drug delivery, Pharm Tech Japan, 29(2013) 183–188.
Hinds W.C., Aerosol technology: Properties and Behavior and
Measurement of Airborne Particles, second ed., John Wileyand Sons, New York, 1999, p. 251.
Jaffari S., Forbes B., Collins E., Barlow D.J., Martin G.P.,
Murnane D., Rapid characterisation of the inherent dispersibility of respirable powders using dry dispersion laser diffraction, International Journal of Pharmaceutics, 447 (2013)
124–131.
Jaffari S., Forbes B., Collins E., Khoo J., Martin G.P., Murnane
D., Evidence for the existence of powder sub-populations in
micronized materials: Aerodynamic size-fractions of aerosolized powders possess distinct physicochemical properties, Pharmaceutical Research, 31 (2014) 3251–3264.
Jones M.D., Price R., The influence of fine excipient particles
on the performance of carrier-based dry powder inhalation
formulations, Pharmaceutical Research, 23 (2006) 1665–
1674.
Lippmann M., Effects of fiber characteristics on lung deposition, retention, and disease, Environmental health perspectives, 88 (1990) 311–317.
Louey M.D., Van Oort M., Hickey A.J., Standardized entrainment tubes for the evaluation of pharmaceutical dry powderdispersion, Journal of Aerosol Science, 37 (2006) 1520–
1531.
Mansour H.M., Xu Z., Hickey A.J., Dry powder aerosols generated by standardized entrainment tubes from alternative12

sugar blends: 3. Trehalose dihydrate and D-mannitol carriers, Journal of Pharmaceutical Sciences, 99 (2010) 3430–
3441.
Martonen T.B., Katz I., Fults K., Hickey A.J., Use of analytically defined estimates of aerosol respirable fraction to predict lung deposition patterns, Pharmaceutical Research, 9(1992) 1634–1639.
Mullin J.W., Crystallization, third ed., Butterworth-Heinemann,
Oxford, 1993.
Sanders M., Pulmonary drug delivery: An historical overview,in: Smyth H.D.C., Hickey A.J. (Eds.), Controlled pulmonary drug delivery, Springer New York, New York, NY(2011) pp. 51–73.
Shah I., The blind ones and the matter of the elephant, in: Talesof the Dervishes, Arkana, London, 1993, pp. 25–26.
Shur J., Kubavat H.A., Ruecroft G., Hipkiss D., Price R., Influence of crystal form of ipratropium bromide on micronisation and aerosolisation behaviour in dry powder inhaler
formulations, Journal of Pharmacy and Pharmacology, 64(2012) 1326–1336.
Smyth H.D.C., Cooney D.J., Garmise R.J., Zimmerer R.O.,
Pipkin J.D., Hickey A.J., Dynamic electrostatic charge
determinations of dry powder blends for inhalation: correlations with dispersion performance influence of physicalform of captisol, in: Respiratory Drug Delivery IX, Volume
III, Dalby R.N., Byron P.R., Peart J., Suman J.D. and Farr
S.J. (Eds.), Davis Healthcare International Publishing,
LLC, River Grove, IL, 2004, pp. 805–807.
Steckel H., Bolzen N., Alternative sugars as potential carriers
for dry powder inhalations, International Journal of Pharmaceutics, 270 (2004) 297–306.
Stewart P.J., Particle interaction in pharmaceutical systems,
Pharmaceutical International, 7 (1986) 146–149.
Taylor M.K., Ginsburg J., Hickey A.J., Gheyas F., Composite
method to quantify powder flow as a screening method inearly tablet or capsule formulation development, AAPS
PharmSciTech, 1 (2000) 20–30.
Telko M.J., Hickey A.J., Dry powder inhaler formulation,
Respiratory Care, 50 (2005) 1209–1227.
Telko M.J., Hickey A.J., Critical assessment of inverse gas
chromatography as means of assessing surface free energy
and acid–base interaction of pharmaceutical powders, Journal of Pharmaceutical Sciences, 96 (2007) 2647–2654.
Telko M.J., Hickey A.J., Aerodynamic and electrostatic properties of model dry powder aerosols: A comprehensive studyof formulation factors, AAPS PharmSciTech, 15 (2014)
1378–1397.
Telko M.J., Kujanpää J., Hickey A.J., Investigation of triboelectric charging in dry powder inhalers using electrical low
pressure impactor (ELPI™), International Journal of Pharmaceutics, 336 (2007) 352–360.
Tian Y., Parasrampuria D., Kanke M., Hickey A.J., Manufacture
and in-vitro assessment of bromsulphthalein and phenolphthalein loaded polyester microspheres, Drug Development and Industrial Pharmacy, 20 (1994) 1159–1178.
Tougas T.P., Mitchell J.P., Lyapustina S.A., Good Casacade
Impactor Practices, AIM and EDA for Orally Inhaled Products, Springer, NY, 2013.

Anthony J. Hickey / KONA Powder and Particle Journal No. 35 (2018) 3–13

US FDA (Food and Drug Adminstration), November 1998,
Draft Guidance for the Industry, Metered Dose inhaler(MDI and Dry Powder Inhaler (DPI) Chemistry, Manufacturing and Controls Documentation.
US FDA (Food and Drug Administration), Draft Guidance on
Fluticasone Propionate; Salmeterol Xinafoate, September
2013.
USP (United States Pharmacopoeia), General Chapter <601>
Aerosols, Nasal Sprays, Metered Dose Inhalers, and Dry
Powder Inhalers, USP Rockville, MD, 34 (2011) pp. 218–
239.
Van Oort M.M., Sacchetti M., Spray drying and supercriticalfluid particle generation techniques, in: Inhalation Aerosols, Physical and Biological Basis for Therapy, Second
Edition, A.J. Hickey (Eds.), Informa Healthcare, New York,2007, pp. 307–346.
Vehring R., Pharmaceutical particle engineering via spray drying, Pharmaceutical Research, 25 (2008) 999–1022.
Wong J., Lin Y.-W., Kwok P.C.L., Niemelä V., Crapper J., Chan
H.-K., Measuring bipolar charge and mass distributions of
powder aerosols by a novel tool (BOLAR)., Molecular
Pharmaceutics, 12 (2015) 3433–3440.
Xu Z., Mansour H.M., Hickey A.J., Particle interactions in dry
powder inhaler unit processes: A review, Journal of Adhesion Science and Technology, 25 (2011) 451–482.
Xu Z., Mansour H.M., Mulder T., McLean R., Langridge J.,
Hickey A.J., Dry powder aerosols generated by standardized entrainment tubes from drug blends with lactose
monohydrate: 1. Albuterol sulfate and disodium cromogly-

cate, Journal of Pharmaceutical Sciences, 99 (2010a) 3398–
3414.
Xu Z., Mansour H.M., Mulder T., McLean R., Langridge J.,
Hickey A.J., Dry powder aerosols generated by standardized entrainment tubes from drug blends with lactose
monohydrate: 2. Ipratropium bromide monohydrate and fluticasone propionate, Journal of Pharmaceutical Sciences,
99 (2010b) 3415–3429.
Xu Z., Mansour H.M., Mulder T., McLean R., Langridge J.,
Hickey A.J., Heterogeneous particle deaggregation and its
implication for therapeutic aerosol performance, Journal of
Pharmaceutical Sciences, 99 (2010c) 3442–3461.
Young P.M., Chan H.-k., Chiou H., Edge S., Tee T.H.S., TrainiD., The influence of mechanical processing of dry powder
inhaler carriers on drug aerosolization performance, Journal of Pharmaceutical Sciences, 96 (2007) 1331–1341.
Young P.M., Cocconi D., Colombo P., Bettini R., Price R.,
Steele D.F., Tobyn M.J., Characterization of a surface modified dry powder inhalation carrier prepared by “particle
smoothing”, Journal of Pharmacy and Pharmacology, 54(2002) 1339–1344.
Zhou Q., Qu L., Gengenbach T., Larson I., Stewart P.J., Morton
D.A.V., Effect of surface coating with magnesium stearate
via mechanical dry powder coating approach on the aerosol
performance of micronized drug powders from dry powder
inhalers, AAPS PharmSciTech, 14 (2013) 38–44.
Ziffels S., Bemelmans N.L., Durham P.G., Hickey A.J., In vitro
dry powder inhaler formulation performance considerations, Journal of Controlled Release, 199 (2015) 45–52.

Author’s short biography
Anthony J. Hickey
Dr. Hickey is Distinguished RTI Fellow, at RTI International, Emeritus Professor of
Molecular Pharmaceutics of the Eshelman School of Pharmacy, and Adjunct Professor
Biomedical Engineering in the School of Medicine, at the University of North Carolina
at Chapel Hill. He obtained Ph.D. and D.Sc. degrees in pharmaceutical sciences from
Aston University, Birmingham, UK. He is a Fellow of the Royal Society of Biology, theAmerican Association of Pharmaceutical Scientists and the American Association for
the Advancement of Science. He received the Research Achievement Award of the Particulate Presentations and Design Division of the Powder Technology Society of Japanand the David W Grant Award in Physical Pharmacy of the American Association of
Pharmaceutical Scientists. He is a member of the Pharmaceutical Dosage Forms Expert
Committee of the United States Pharmacopeia.

13

KONA Powder and Particle Journal No. 35 (2018) 14–31/Doi:10.14356/kona.2018004

Review Paper

Nanomaterials for Environmental Solar Energy
Technologies: Applications & Limitations †Yiannis Deligiannakis
1

Laboratory of Physical Chemistry of Materials and Environment, Department of Physics, University of Ioannina, Greece

Abstract
Environmental remediation and energy production are currently listed among the priority tasks by administration
bodies, stakeholders and market competition. In this context, nanomaterials present competitive advantages interms of performance and production costs. In the present critical review, the current state of the art ofnanomaterials used in environmentally benign technologies exploiting solar irradiation such as H2 production,water-splitting and photocatalysis are discussed. Factors determining the overall efficiency are articulated in asingle “photophysical efficiency” equation. The physical meaning, limits and constraints of each factor are
analyzed, updated and examples are discussed. The article highlights the main structure-function relationships intandem with the limitations posed by the particle’s physicochemical properties, production method, and theprerequisites posed by regulatory bodies and market needs. Several misconceptions are highlighted with regard to
performance and yields that ultimately impact the end use of the nanomaterials. Current targets/limitations posedby the US Department of Energy are discussed as case studies. For context-coherence reasons, the present review
focuses on metal and metal-oxide nanoparticles, i.e. carbon nanomaterials are not covered herein.
Keywords: nanomaterials, semiconductor, H2, O2, photocatalysis, heterojunction

1. Introduction
The interconversion of different forms of energy ultimately determines environmentally benign technologies
that are quantifiable in a product/byproduct/cost balance(Chen X. et al., 2010; Froschl T. et al., 2012; Holdren J.P.,
2007; Kamat P.V, 2010). Research on interactions of solar
photons at particle interfaces or electrode surfaces boosts
technology, the economy, as well as environmental policy
interests. The energy content of the earth’s sunlight is 0.9
to 3.2 electron volts (eV) photon, i.e. 87 to 308 kilojoules
per einstein, i.e. “mole” of photons. On average, thismakes a total maximum ~120.000 TW of solar radiation
arriving on the earth’s surface (Lewis N.S. and Nocera
D.G., 2006). Today, the world’s energy consumption is 15
TW, which is estimated to rise to 30 TW by 2050 (Lewis
N.S. and Nocera D.G., 2006). In this context, if properly
exploited, solar energy input could provide a significant
contribution to our energy needs. This requires efficient/
low-cost/environmentally sustainable technologies utilizing readily available materials for the solar-conversion

†
1

14

Received 13 July 2016; Accepted 31 August 2016
J-STAGE Advance published online 18 March 2017
45110 Ioannina, Greece
E-mail: ideligia@cc.uoi.gr
TEL: +30-265-100-8662

process. Hydrogen (H2) combustion emits only water vapor without carbon emissions, thus it is an ideal fuel. H2
has the highest energy density of all fuels (143 kJ kg–1),
i.e. ideally 1 kg of H 2 can replace 2.6 kg of gasoline(Holdren J.P., 2007; Lewis N.S. and Nocera D.G., 2006).
Today, however, 96 % of the global demand for H2 is produced from fossil fuels (gasoline, coal). In this context,
nanophotocatalytic materials emerge as being among themost promising solutions for photonic-energy storage inthe form of H2. As we discuss herein, the same photophysical machinery can be used to catalyze the degradation/transformation of environmental pollutants such as
toxic organics of high-valency metals (Dong S. et al., 2015;
Fagan R. et al., 2016).
In the present critical review, the current state of the artof nanomaterials used in environmentally benign technologies exploiting solar irradiation via H 2 production,water-splitting and photocatalysis are discussed, using aunified nanomaterials-technology view as originally envisaged by A. Bard (Bard A.J., 1980). Solar photoelectrochemical (PEC) hydrogen production, since its original
conception in 1972 (Fujishima and Honda, 1972), surpassed the limit of 12 % efficiency in 1998 (Khaselev O.
and Turner J.A., 1998). Today, photocatalysis is envisaged
as a technology that can potentially provide a clean, cost-­
effective, domestically produced energy vector using solar energy (Lewis N.S and Nocera D.G., 2006; ENERGY.

Copyright © 2018 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/).

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

GOV, 2015). It should be underlined, however, that currently (2016), low-temperature (< 80 °C) H2 production
experiences strong research interest aimed at setting up
standards and parameters in parallel with cost reduction
and factory-­scale economy. In the 2015 report of the US Department of Energy on hydrogen production technologies(ENERGY.GOV, 2015), it is stated that photoelectrochemical H2 production based on semiconductor photoelectrodes
or photocatalysts is at an early stage of development. Thus
it requires advances in materials development and reactor
concept development. The progress on these fronts is envisaged through priority-ranked tasks: (a) in an initialstage, the study/development of high-­efficiency, probably
high-cost, materials to establish performance parameters,(b) attain a fundamental understanding of PEC hydrogenproduction vs. corrosion mechanisms, (c) then, in a laterstage, the study of durable, low-cost, probably lower-­
performance materials to improve efficiency by mitigating loss mechanisms, (d) finally, development of complex
multicomponent devices capable of achieving water splitting via optimization [light absorption]–[electron-holetransport]–[interfacial catalysis]. In this context, the fabrication of artificial photosynthetic systems can be directed
towards two targets: [a] direct conversion of abundantmaterials, e.g. H 2O and CO2 to fuels (H 2 , HCOOH,
CH3OH), (Chen Z. et al., 2010; Lianos P., 2011; Miller E.L.
et. al., 2010), or [b] production of electricity. Moreover,photochemical reactions could be employed to replace
other energy-consuming chemical processes, for example,
for pollution abatement or in chemical synthesis.
The present article is a review on the current status ofphotoactive nanomaterials used in such environmental
technologies. The aim is to highlight the common (nano)photophysical properties that determine their performance,
limitations and potential in technological applications.
Emphasis is focused on the materials’ physicochemical
properties in an effort to highlight the main factors that determine nanomaterials’ production targets and limitations.
A detailed tabulation of the literature data per material isbeyond the scope of the present review. The interested
reader is encouraged to consult pertinent reviews on photocatalysis (Teo W.Y. et al., 2012), heterogeneous photocatalytic water treatment using visible light-­responsive
photocatalysts (Dong S. et al., 2015), solar and visible-­light-active TiO2 photocatalysis for treating biocontaminants (Fagan R. et al., 2016), N-TiO2 for green energy
applications under UV/visible light (Devi L.G. and Kavitha
R., 2014), as well as alternative photocatalysts to TiO2
(Hernandez-Alonso et al., 2012). Moreover, the interested
reader is encouraged to visit a virtual issue published by
the American Chemical Society (JPCCSVI, 2016) wherea comprehensive set of review articles—up to 2013—isavailable.

2. The general photo-nano-technology concept
Solar electromagnetic radiation is consistent with thatof a black body at T = 5800 K with a radiation spectrum
peak at 0.8 eV. A significant part of this spectrum is in thevisible range of the spectrum (400–700 nm). The fractionof solar light which reaches the earth’s surface has a maximum power density of ~100 mW/cm2 (Holdren J.P., 2007;
Lewis N.S. and Nocera D.G., 2006). However, only photons with hν exceeding the semiconductors band gap (Eg),generate electron-hole (e –/h+) pairs. The overall power-­
conversion efficiency of single crystalline p-n solar cells
ranges from 10 to 30 %, yielding 10 to 30 mW/cm2. On
the other hand, when pursuing visible-light photocatalysts, Maeda and Domen (2007) have proposed that, before commercial development, photocatalysts must reacha quantum yield of 30 % at 600 nm. This seems a boldchallenge at present, however, as we discuss herein, this isexactly the driving-force for science and technology inthis field (ENERGY.GOV, 2015).
There are three main technology/research approaches
for the exploitation of solar photons. The common basisof these was originally conceptualized by Bard A. (1980),
as depicted schematically in Fig. 1.
Photoelectrochemical cells (PEC): In this generalscheme, Fig. 1, the archetypical Fujishima-Honda photoelectrochemical cell (PEC) (Fujishima and Honda, 1972)
is the combination of the n-type semiconductor as the anode and an inert electrode as the cathode immersed in theelectrolyte solution, see Fig. 1(A). PEC provides both therequired field for e –/h+ separation as well as considerable
spatial separation of the products to minimize recombination hurdles or unwanted product reaction. Until today,
the nanophotoelectrodes used are of n-type. Fewer examples of p-type nanophotoelectrodes exist, i.e. CuO,
Co-phosphates, IrO2, that will be discussed hereafter. The
definitions on efficiency for PEC devices are aligned withthose used for photovoltaics (PV) because the two fields
share many common characteristics, and they are inagreement with previous analyses of efficiencies for PEC
water splitting (Chen Z. et al., 2010; Rocheleau R. andMiller E., 1997). In energy terms, in a PEC it is light thatpumps the electrons “uphill” and provides the requiredenergy. Note that the PEC provides both the required field
for e –/h+ separation as well as the considerable spatial
separation of the reaction products to minimize unwanted
back-reactions.
The concept of PEC for H2O splitting for H2 production
has been discussed for decades since its first demonstration in 1972 (Fujishima and Honda, 1972), but the world-­
record solar-to-hydrogen (STH) efficiency of 12.4 % wasachieved almost two decades ago in 1998 (Khaselev O.
and Turner J.A., 1998). This technology combines theharvesting of solar energy and the electrolysis of water

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Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Fig. 1

Schematic description of the fundamental photoactive nanocatalytic systems. A fundamental differenceis the positioning of the energy levels of the redox couples vs. the photo-induced electrons’ and holes’
energy levels. For simplicity, external bias voltage is not included in these schemes. External bias, depending on polarity and voltage, will shift upwards or downwards the energy levels of e- and h+.

into a single device. When a semiconductor—with theright set of properties—is immersed in an aqueous electrolyte and irradiated with sunlight, the photon energy isconverted to electrical energy which is directly used to
split water into hydrogen and oxygen (chemical energy),
Fig. 1B. Thus, intermittent energy from sunlight is converted into an inherently more storable form of energy, i.e.
that of chemical bonds. An excellent account on the physicochemical, technical and economical issues of PECs isgiven by Chen et al. (2010).
For the direct PEC decomposition of water to occur,
several key criteria must be met simultaneously: (i) the
semiconductor system must generate sufficient voltage
upon photo-excitation to split H2O; (ii) the bulk band gap,
Eg, must match the energy of solar photons, preferably inthe visible spectrum, i.e. 2.0–3.0 eV; (iii) the band-edge
potentials at the surfaces must encompass the H+/H2 andH2O/O2 redox potentials; (iv) the system must exhibit
physicochemical resilience in aqueous electrolytes; (v) for
H2O splitting, the charge transfer from the surface of thesemiconductor to the solution must avoid corrosion and beenergetically/kinetically facile enough to reduce energy

16

losses due to kinetic overpotential. So far, no cost-­effective
material satisfies all of these technical requirements (ChenZ. et al., 2010). Here, we present a survey on some of the
key factors that may influence the efficiency.
Overal quantum yield vs. efficiency in PECs: Photo-­
induced e-transfer reactions are now well understood.
High quantum yields for photochemical e –/h+ separation
are very often reported. When these systems are coupled
to sacriﬁcial electron donors, such as methanol, or acceptors, such as persulfate, then H2 or O2 can be produced
from H2O (Chen Z. et al., 2010; Harriman A. et al., 1988).
When practical energy conversion is considered in realsystems, the use of sacriﬁcial systems gives a simplistic“efﬁciency” that should be revised when taking into account electrolyte redox-couple cycling. However, such
sacriﬁcial donors are useful in mechanistic studies because [a] they minimize e –/h+ recombination and [b] they
permit the examination of a light-driven half-cell reaction, i.e. oxidation or reduction, separately. Thus, from thepractical point of view, estimating separately the quantum
yield of H2 or O2 evolution in sacriﬁcial half-cycles is also
an effective method for rapidly screening new catalysts

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31(Chen Z. et al., 2010; Goldsmith J. et al., 2005).
Achieving high quantum yields in sacriﬁcial half-­
cycles implies the use of efficient key components (catalytic material/redox mediators/photosensitisers) that allow
a proof-of-concept level for overall water splitting. The
problem is to combine them in such a way that diminishes
e –/h+ and H2/O2 recombination. Control of e –/h+ recombination is a complex process, even in the simplest of such
systems, such as a Pt0-loaded n-semiconductor particle
coupled to an O2-evolving catalyst, see Fig. 1B. A highquantum yield can be achieved only if the forward electron transfer rate (solid arrows in Fig. 1B) at each branchin the chain is faster than the sum of all the reverse rates.
For example, in Fig. 1B, the forward electron transferfrom the semiconductor to the H2-evolving catalyst mustcompete effectively with e –/h+ recombination and alsowith e-transfer to the H2O-oxidation catalyst. Here, a key
hurdle is that the reverse reactions are fast because the reverse pathways have much higher driving forces than theforward ones. However, because e –/h+ recombination rates
are also strongly distance-dependent, it should be possible
to arrange the components in space in such a way that theforward pathway becomes kinetically competitive or evendominant. Photosynthesis is living proof of this principle.
On this front, the use of heterostructural nanoparticles containing all components (O2-evolving particle, main photoexcitable semiconductor, and e-­accumulating particle) is avery attractive technology that we discuss hereafter.
Photocatalysis: The concept of photocatalysis for environmental remediation, depicted in Fig. 1C, implies thatphotons are converted in a first step to chemical intermediates that are highly energetic, thus very reactive. Typically, these are hydroxyl radicals (●OH) or superoxide
radicals (●OO) and, in more rare cases, singlet-oxygen
radicals (●O) that are generated at the particle-solution interface (Teo W.Y. et al., 2012; Linsebigler A.L. et al.,1995), see Fig. 2.
When a semiconductor surface is irradiated by light(hν ≥ Eg), there is a generation of electron/hole pairs (e−/h+) via the promotion of an e- from the valence band
(lower energy level) to the conduction band (higher energy level). The surface water molecules and/or hydroxylions react with the holes on the valence band to generatehydroxyl radicals (●OH), which are a powerful oxidizing
agent (+ 2.80 V). In Fig. 1(C), this shows that a strong
ΔG gradient has to be overcomed for the degradation of
persistent organic pollutants: notice the energy level-­positioning differences in Figs. 1A, B, C.

Fig. 2

Photo-induced reactions and radical transient species
produced arising from the excitation of a photocatalyst
particle in aqueous solution. Reprinted with permission
from Ref. (Teo W.Y. et al., 2012). Copyright: (2012)
American Chemical Society.

3. Basic photophysical principlescharacteristics of photocatalytic
nanomaterials
In the context of photocatalysis, a reference solar spectrum (atmospheric mass, AM1.5) is commonly considered.
1.5 atmosphere thickness corresponds to a solar zenith
angle of z = 48.2°. Therefore, AM1.5 is useful to represent
the overall yearly average for mid-latitudes on Earth. The
solar intensity versus air mass (AM) is given by
I = 1.1 × I0 × 0.7 (0.678AM)
where solar intensity external to the earth’s atmosphere,
I0 = 1.353 kW/m2, and the factor 1.1 is derived assumingthat the diffuse component of sunlight is 10 % of the direct component. For AM1.5 this results in a solar power
density ~930 W/m2 (Würfel P., 2005)
In the fundamental Shockley-Queisser model, it is assumed that photons with energy below the band gap(hν < Eg) are not absorbed at all, while photons with energy far above the band gap (hν > Eg) are absorbed, but allthat excess energy is wasted as thermal energy (Shockley
W. and Queisser H. J., 1961).
Here, we notice that for (hν >> Eg), electrons are excited to an energy-level far above the conduction-band
minimum, and holes far below the valence-band maximum. After such an excitation, e – and h+ relax to the bandedges very rapidly (t < ns). If this relaxation could be
stopped, then the highly energetic “hot” h+/e – pair efficiency can theoretically considerably exceed the existing
theoretical limits posed by Shockley and Queisser for p-njunction photovoltaics (Shockley W. and Queisser H.J.,
1961). In practice, this is very difficult; thus far, even a
proof-of-principle laboratory demonstration of a complete
hot-electron device is lacking.

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Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

RR = h+/e – recombination rate

3.1 Formulation of the Photophysical Efficiency
Concept
In their report, Chen et al. (2010) make clear that solar-­to-hydrogen (STH) efficiency should be used as a common reference benchmark reporting. Other efficiency
parameters can also be used, providing insight into thefunctionality and limitations of a device; definitions arereviewed in (Chen Z. et al., 2010; ENERGY.GOV, 2015;
Lianos P., 2011). In all technological applications of photocatalysts, the photophysical efficiency of a given material is the core parameter that will determine its ultimate
eligibility. Then, scalability, cost and life-cycle issues
have to be taken into account to permit an industrial-scaleconsideration. The two main parameters are:•	Quantum efficiency = molecules of product produced per photon absorbed;•	Solar efficiency = molecules of product produced
per incident solar photon.
Focusing on the h+/e – production efficiency of a given
material, without reference to the subsequent interfacial
or liquid-phase reactions, we may use a ‘photophysical efficiency parameter’. The photophysical efficiency of aphotocatalyst concerns all processes inside the particle
that include the photon absorption until migration of theelectron and the hole to their first interfacial acceptors.
As detailed by Bolton (1978, 1985), the photophysicalefficiency parameter can provide a common base of discussion for all photodevices described in Fig. 1 (Bard A.J.,
1980). In this context, the overall catalytic efficiency of agiven photocatalyst can be formulated as follows:
Photophysical Efficiency = fparticle · ELP(1)

where the two factors fparticle and ELP are defined as follows:• fparticle = efficiency of electron-hole photoproduction•	ELP = energy level positioning of the e –/h+ relative
to their interfacial electron-acceptor and hole-­
acceptor, respectively.
The ELP factor takes into account the efficiency of energy-­
level alignment for the elementary-step, for example froma TiO2 nanoparticle to Pt0, in the TiO2-Pt0 system. Equation(1) can be further expanded by considering that fparticle
consists of two factors:
fparticle = fstructural · Rkinetic(2a)where the two factors fstructural and Rkinetic are defined asfollows
fstructural = ([α]/[SSA] [catalyst mass])(2b)

Rkinetic = ([Me][Mh]/[RR])

(2c)

with
α = solar-light absorbance efficiency

18

Me, Mh = mobilities of the electrons and the holes
and SSA=specific surface area of the catlyst.

3.2 Direct vs. Indirect Band-Gap Semiconductors:[A]-Direct band-gap semiconductor: For a direct bandgap semiconductor, α is related to the frequency of thelight, ν, according to the following formula:α  Α* hν  Εg

(3a)where α is the light-absorption coefficient, v = light frequency, h = Plank’s constant, Eg is the semiconductor’sband-gap energy, Α* is a frequency-independent constant,with formula (Würfel P., 2005)
3
2 qx 2υc
λ0 0  3 n(2mr )
A* 

(3b)

and
mr 

mh * me *mh *  me *(3c)is the reduced mass, based on the effective masses me*
and mh* of the hole and the electron, respectively. n is thereal part of the refraction index of the material, χ υc is a
crystal-matrix parameter usually taken equal to the lattice
constant for each material. q and ε 0 are the electron
charge and vacuum permittivity, respectively. This formula is valid only for light with photon energy larger, but
not too much larger, than the band gap (more specifically,
this formula assumes the bands are approximately parabolic), and ignores all other sources of absorption otherthan the band-to-band absorption in question, as well as
the electrical attraction between the newly created electron and hole.
[B]-Indirect band-gap semiconductor: On the other
hand, for an indirect band gap, the formula is:αhν  Eg  Ep 2  hν  Eg  Ep 2
E 
exp  p   1
 kT 

 E 
1  exp   p 
 kT 

(4)

where Εp the energy of the phonon i.e. a lattice vibrational
state, that assists in the transition; kT is the Boltzmann
thermal factor. This differentiates a so-called direct froman indirect semiconductor.
A direct band-gap semiconductor is formed when theminimum energy of the conduction band is at the same
k-position in the Brillouin zone to the maximum of thevalence-band, see Fig. 3. The notion of direct vs. indirect
band gap has profound impact on the e –/h+ lifetime andYiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Fig. 3

Indirect (Anatase TiO2) and direct (Rutile TiO2) bandgap semiconductors. Reprinted with permission from
Ref. (Zhang J. et al., 2014). Copyright: (2014) Royal
Society of Chemistry.

recombination dynamics: when the excited electrons
come back from the conduction band to the valence banddue to recombination of photogenerated e –/h+, they will
release their extra energy as photons of frequency v, i.e.
hν = Εg(5a)Moreover, the excited electrons must meet the transition
selection rule of momentum conservation,ħke(conduction band) – ħke(valence band) = ħqphonon(indirect band gap e –/h+ recombination)(5b)where ħ is the reduced Planck constant, ke(conduction band),ke(valence band) are the electron wave vectors at the conduction band and valence band, respectively, q is the wave
vector of the assisted phonon (Zhang J. et al., 2014). Using
this formulation, for a direct band-gap semiconductor:
ħke(conduction band) = ħke(valence band) => ħqphonon = 0(direct band gap e –/h+ recombination)(5c)i.e. only a photon without phonon is involved in e –/h+ recombination (Zhang J. et al., 2014). Examples are rutile andbrookite: an electron only emits a photon following recombination of photogenerated e –/h+. However, the recombination of photoexcited electron and hole in anatase is assisted
by a phonon, because ħke(conduction band) ≠ ħke(valence band) for
this indirect band-gap semiconductor (Zhang J. et al.,2014). Thus, the excited electrons cannot recombine directly with holes, resulting in an increase of the photogenerated electron–hole lifetime in anatase, relative tothat of rutile and brookite. As a result, the diffusion
length and reaction time of the electron and hole excitedin anatase also increase.
In this context, in general, direct band-gap semiconductors are expected to have higher h+/e- recombination
rates (shorter e – /h+ lifetimes) than indirect band-gap
semiconductors. Examples of common direct band-gap
semiconductors include ZnO and GaAs, while crystalline
Si forms indirect band-gap semiconductors. All quantum

dots are direct band-gap materials.
The direct or indirect band-gap character of BiVO4 has
been a matter of debate (Cooper J.K. et al. 2015; Walsh A.
et al., 2009). In an earlier report, Walsh et al. (2009) reported BiVO4 to be a direct-band-gap material, with a direct band-gap Eg = 2.4 eV, however recent data by Cooper
et al. (2015) suggest that BiVO4 is an indirect band-gap
semiconductor with a transition located at 0.2 eV below
the direct one at 2.4 eV. This very small energy-­
positioning difference dictates the difficulty for its detection (Cooper J.K. et al., 2015; Walsh A. et al., 2009).
Experimentally, the direct and indirect band gaps can result in resolvable differences in UV-vis transitions. Thus
direct and indirect band gaps can be estimated by theso-called Tauc analyis (Tauc et al. 1970) as follows: using
the UV-vis data for a given semiconducting material, we
typically plot (αhν)n versus (hv) where α is the measured
absorption coefficient in the UV-vis spectrum. To do this,we have to convert the x-axis from wavelength (λ) to eVusing the relationhv(eV) = 1240/λ in nm(6)This method can determine the optical bulk band gap (Eg)and, ideally, can distinguish between allowed direct(n = 2) and allowed indirect (n = 1/2) transitions (Tauc et
al 1970; Elliott R.J., 1957).

3.3 Effective mass-effect on e –/h+ transfer rates
The quantum efficiency of a photocatalyst is also affected by the transfer rate of photogenerated electrons andholes (Linsebigler A.L. et al., 1995). The transfer rate ofh+/e – can be indirectly assessed by the effective mass (m*)
of electrons and holes (Linsebigler A.L. et al., 1995). In
general, the transfer rate of photogenerated h+/e – is inversely proportional to their effective masses, i.e. thelarger the effective mass of photogenerated carriers, theslower their transfer rate. Thus the small effective masscan promote the migration of charge carriers and inhibit
their recombination. For example, the effective mass ofphotogenerated electrons and holes in CaZrTi2O7 havebeen estimated to be me* = 1.35m0 and mh* = 1.23m0, respectively (Liu J.J. et al., 2012). In NaBiO3, effective
masses of me* = 0.14m0 and mh* = 1.1m0 have been estimated, respectively (Liu J.J. et al., 2012; Zhang J., 2014).
For anatase TiO2, effective masses of me* = 0.0948 and
mh* = 0.1995 have been calculated (Zhang J., 2014). This
correlates with the fact that anatase TiO2 has a higher
photocatalytic activity than CaZrTi2O7 and NaBiO3 (Liu
J.J. et al., 2012, 2013; Zhang J., 2014).
Mobility-diffusion is intimately related with the e –/h+separation efficiency or the recombination rate RR inequation (2b). The case of Fe2O3 is very instructive: This
material has a great advantage in that it absorbs visible

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Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Fig. 4

Efficiency determining reactions in a photo-induced e–/h+
generation on a semiconductor nanoparticle. Reprinted
with permission from Ref. (Kudo A. et al., 2009).
Copyright: (2009) Royal Society of Chemistry.

light Eg = 2.2 eV (Miyauchi M. et al., 2002), but it suffersfrom a short hole-diffusion length (2–4 nm) (Formal F.L.
et al., 2010).
In summary, formulas (1–2) entail that the overall photophysical efficiency (PPE) is determined by three main
terms:– fstructural is determined by the energetic and solid-state
properties of a given photocatalyst. These are physicalproperties determined by the solid-state characteristics ofa given particle.
– Rkinetic is determined by the dynamic, kinetic characteristics of photogenerated e –/h+ in the photocatalyst.
These are determined by the crystal structure and also by
the defects, dopings, etc.
– the energy level positioning (ELP) factor describes theefficiency of the electron/hole transfer from the particle tothe first interfacial acceptor. These factors are often described in texts and visualized in pertinent reaction
schemes such as in Fig. 4.
Thus, equations (1, 2) offer a simple, compact form allowing an overview of the e –/h+ photogeneration efficiency. They indicate that in a given nanoparticle type,the factors f particle = fstructural · R kinetic are determineduniquely by its structure. Then, when in contact with anexogenous agent, electron level positioning will have tobe determined for each type of application, since thetypes of acceptors will be different in different experiments.

4. Practical Issues: Examples of common
limitations in data acquisition and analysis
4.1 Efficiency estimates
The energy levels of the conduction and valence bands,
as determined form their ideal structures and compiled by
Li and Wu (2015), are displayed in Fig. 5. Bolton et al.
(1985) considered the thermodynamics of photochemical
water splitting in detail and concluded that it is possible tostore about 12 % of the incident solar energy in the form

20

Fig. 5

Conduction-band and valence-band edge positions (ineV units) for selected semiconductors at pH 0.Left
Y-axes provide energies vs. the vacuum energy level.
Right Y-axes provide energies vs. the NHE energy
level. Reprinted with permission from Ref. (Li and Wu,
2015). Copyright: (2015) Royal Society of Chemistry.

of hydrogen, allowing for reasonable losses (a total of
1.0 eV) in the electron transfer steps and the catalytic reactions of water splitting. In practice, there have beenvery few reports of photocatalytic water splitting using
visible light (Hernandez-Alonso M.D. et al., 2009; Maeda
K. et al., 2006; Zou Z. et.al., 2001), and the best reported
quantum yield is so far about 6 % (Maeda K. and DomenK., 2008).
The solar power conversion based on semiconductor
p-n junctions and semiconductor-liquid junctions can bequite efficient. In such p-n junctions, charge recombination
is inhibited by the electric field that separates the light-­
generated minority and majority carriers (Hernandez-­
Alonso M.D., et al., 2009).
Photon-to-electron quantum yields approaching unityand power conversion efficiencies up to 18 % have beenreported with single-crystal photoelectrodes (Khaselev O.
et al., 1998). As noted above, if charge recombination reactions could be suppressed, then photocatalytic water
splitting could become similarly efficient. On this front,
significant advances have been made towards understanding photo-induced charge separation and interfacial

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

charge-transfer processes in semiconductor photocatalyst
assemblies (Tang J.W. et al., 2011). Thermodynamic andkinetic limitations determine the efficiency of electron
and hole transfer in semiconductor systems. The existenceof shallow surface traps may enhance the overall efﬁciency
by increasing the e –/h+ lifetime. In any case, it is worthemphasizing that as much as 90 % of the electron–holepairs recombine in less than 10 ns and consequently, photogenerated carriers available for surface reactions arequite limited. Values of quantum yield vary broadly withthe process considered.
As an example, for TiO2 reactions in solution, quantum
yields are typically around 1 % (Wang C. et al., 2002)
but they can exceed 5 % for some gas-phase reactions(Coronado J.M. et al., 2008). These values depend, as dictated by relations (1) and (2), on e –/h+ transfer at the particle
interface and the surface characteristics, but considering
exclusively the photoactivation process, TiO2 shows alimited performance. Thus in contrast to silicon, which
presents an internal quantum efﬁciency (IQE) close to
100 % under illumination at 600 nm (Svrcek V., 2004), in
TiO2, the absorbed photon-to-current efﬁciency is about
30 % at 360 nm (Lindgren T. et al., 2004).

4.2 Experimental Issues
Using diffuse-reflectance UV-vis spectroscopy, we typically measure the optical bulk band gap Eg of the semiconducting particles. One has to discriminate between a direct
or indirect band gap, allowed or forbidden transition.
As described in Section 3.2, UV-vis data are routinely
analyzed using Tauc plots (Tauc J. et al., 1970), i.e. (αhv)nversus (hv) and fitting the data with the appropriate
n-value, we can decide if we have allowed direct (n = 2),
forbidden direct (n = 2/3), allowed indirect (n = 1/2), andforbidden indirect (n = 1/3) transitions. An example isgiven in Fig. 6 where absorption data for a Cu2O material
are analyzed in the form of Tauc plots (Tauc J. et al.,1970). By plotting the (αhv)2 versus (hv), the band gap forthe allowed direct transitions is determined to be Egdirect= 2.4 eV, Fig. 6.
By plotting (αhv)1/2 versus (hv), the indirect opticalband gap is determined Egindirect = 2.0 eV, Fig. 6c. Attention should be paid to the fact that in nanoparticles, a
UV-vis-derived band gap for the bulk is not necessarily
valid for the surface. Moreover, the slope of the tangent to
the data is prone to subjective error and should be treatedwith caution.
Typical error-prone cases are the verification of ‘visible
light absorbance’. In cases where a semiconducting particle is just covered or intermixed with a colored substance,
this will give a change in the UV-vis profile. If this spectrum is analyzed by a typical Tauc plot, then this will result in the erroneous conclusion that the band gap of TiO2

Fig. 6(a) (αhν)2 versus (hv) for Cu 2O sample. (b) The band
gap for the allowed direct transitions is determined tobe Egdirect = 2.4 eV. (c) By plotting (αhν)1/2 versus (hν),
the indirect optical band gap is determined Egindirect= 2.0 eV. Reprinted with permission from Ref. (Chen,
Z. et al, 2010). Copyright: (2010) Cambridge University
Press.

has been narrowed, whereas it is just an overlap of two
UV-vis spectra.
This can be a common mistake even for the common
TiO2-Pt0 particle characterization where Pt0 particles aredeposited on the TiO2 surface for H2-generation applications. The color of Pt0 particles causes a shift of the TiO2
UV-vis, however this should not be interpreted as bandgap narrowing (Giannakas A. et al., 2016). Similarly, in
dye-sensitized solar cells (DSCC), the dye-covered particles give a visible-light absorbance band, however this is
not due to band-gap narrowing, see the example in Fig. 7.
As explained by Grätzel M. (2005), the basic mechanismof DSSC involves photoexcitation of the dye, donation ofelectrons by the dye on the conduction band of the semiconductor, and filling of the dye-hole via the counter-­electrode/electrolyte circuit.

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Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Fig. 7

The UV-vis spectrum of a Ru-based dye entails strong
absorbance bands at visible wave lengths, with no TiO2
band gap narrowing. Reprinted with permission from
Ref. (Grätzel M., 2005). Copyright: (2005) American
Chemical Society.

As a general guideline, the most interesting materials
will exhibit a band gap, Eg, of between 1.5 and 3.5 V, because it needs to be large enough to account for the thermodynamic energy requirements of water splitting (1.23 V).
In addition, conduction and valence-band potentials should
encompass the hydrogen and oxygen evolution reactions,both the reduction of protons (ENHE(H/H2) = 0.0 eV) and theoxidation of water (ENHE(O2/H 2O) = 1.2 eV) (Kamat P.V.,
2010).
Open-circuit potential is the maximum potential that a
PEC can provide under zero current flow. This is the simplest commonly used method to measure conductivity andflat-band potential VFB. In practical terms, to obtain measurable VFB data for a photoactive material, one has to usehigh illumination intensities. However, depending on thetype of material, high photon flux may cause photocorrosion or surface alteration of the material. This is evidenced as a non-linear change in the measured mVolts atincreased photon flux. Chen et al. (2010) exemplified thiseffect for a p-GaAsPN material using a tungsten 150-W
lamp, where for illumination intensities from 100 mW/cm2
to 600 mW/cm 2, the measured potential changed from~430 mV to 600 mV (Chen X. et al., 2010).
H2/O2 ratios are used in standard test protocols to provethat H 2O splitting occurs. This requires perfect gas-­shielding of the reactor components and thermal stabilityof the reaction set-up, particularly the illumination set-up.

22

Stability tests often take days of repetitive use (Kudo A.
and Miseki Y., 2009). In water splitting, both H2 and O2
should form with a stoichiometric amount, 2:1, in the absence of a sacriﬁcial agent. Often H2 is observed with alack of O2 evolution. In this case, the amount of H 2 evolution is usually small compared with the amount of aphotocatalyst. It is not clear if such a reaction is photocatalytic water splitting, and it is important to clarify that it
is not a sacriﬁcial reaction (Froschl T. et al., 2012; Kudo
A. and Miseki Y., 2009). Because the photocatalytic activity depends on the experimental conditions such as thelight source and type of reaction cell, the activities cannot
be compared with each other if the reaction conditions aredifferent from each other. Therefore, determination of aquantum yield is important. The number of incident photons can be measured using a solid-state photodiode under
non-saturating light-flux conditions. In a particle dispersion/slurry system, the real flux of photons absorbed by aphotocatalyst will be lower than the incident photons because of scattering. So the obtained quantum yield is anapparent quantum yield (Kudo A. and Miseki Y., 2009).
The apparent quantum yield is estimated to be smaller
than the real quantum yield because the number of absorbed photons is usually smaller than that of incident
light (Lewis N.S. and Nocera D.G., 2006).
In many cases, the most common test protocols in photocatalysis involve comparison versus the commercial
Degussa-P25-TiO2 for the degradation of dyes. However,extracting meaningful conclusions by such studies requires a complete data set that assesses the solid-state, interface and solution parameters. Ryu and Choi (2008)
have compared the photocatalytic performance of 8 commercial types of TiO2 for 19 different substrates. They
concluded that not one of the tested TiO2 is best for all thesubstrate types. As suggested (Ryu and Choi, 2008), multivariant statistical analysis, taking into account the key
physicochemical properties of the photocatalyst in relation to the photocatalytic mechanistics, may provide ameaningful insight into the real performance of a photocatalyst. Useful details of experimental design for generalphotocatalysis can be found in Ohtani B. (2008).
Deactivation of surface sites. Deactivation of surface
sites may occur in photocatalytic materials due to various
reasons such as surface (photo) corrosion or surface fouling, or due to adsorption of reaction products on the surface. This phenomenon, however small it may be, has tobe considered carefully (Dong S. et al., 2015).
Both these events result in deactivation of surface sites.
As an example, if we have a loss of L % in each catalytic
cycle, then, after k cycles, the remaining active sites are
given by equation (7)Nremaining = Nintial(1 – L)k(7)

Fig. 8 reveals that after just 100 cycles, a L = 0.01 % will

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Fig. 8 Total loss of surface sites, for a [loss/per cycle] factor L,
after N reaction cycles, estimated from equation (7).
After just 100 cycles, L = 0.01 % will result in the lossof ~ 40 % of the active surface sites.

result in more than 40 % loss of active surface sites.

4.3 Dispersed Powders vs. Electrodes
In nanosized materials, the ability to manipulate theparticle size permits the chemical properties in nanoparticles to be tuned. Thus, size control has tremendously extended the potential of nanomaterials. It is well known
that in its simplest form, water-splitting is the transformation of the energy of photons in electrons and holes andultimately to H2 and O2. Thus it is easy to anticipate that
if 100 % of input electrons (e-) can be successfully put towork and not lost, then a maximum amount of photons istransferred and stored in H2 molecules. Ideally, maximizing the surface of the cathode and anode materials, amaximum conversion of photons to e –/h+ pairs and ultimately to H2/O2 is feasible. Thus, using nanoparticles instead of bulk materials should boost the fundamental e –/h+transfer efficiency and therefore, in water splitting, seeFig. 9Fig. 9 (Teo W.Y., 2012). In this context, the know-how
gained from studies of PEC cells with bulk semiconductor
electrodes can be applied to the design of systems inwhich semiconductor nanoparticles are used (Chen X. etal., 2010; Getoff N., 1990; Kudo A. and Miseki Y., 2009).
For example, using powders of TiO2 with platinum dispersed on the TiO2-surface, each particle can be pictured
as a “short-circuited” PEC cell (Bard A.J., 1980; Chen X.
et al., 2010; Teo W.Y et al., 2012), where the TiO2-­
electrode and Pt-counter electrode are in physical contact(Chen X., et al., 2010; Bard A.J., 1980; Teo W.Y et al.,2012). Irradiation of such nanoparticulate systems still involves the e –/h+ pair formation and surface oxidation/reduction reactions, found in the cells but without externalcurrent flow.
Although nanopowders are obviously much simpler touse, the advantage of the large spatial separation between
the oxidation and reduction sites that occurs in bulk electrodes used in PEC, remains a weak point of the nanopowders (Teo W.Y. et. al., 2012). However, at a molecularscale, the distance between oxidation and reduction sites
on large-enough particles is still probably large comparedto those found in solution-phase photochemical redox reactions (Teo W.Y. et al., 2012) where the redox products
are in close proximity within the same solvent cage.
Keeping this in mind, the know-how of PEC electrodes
can serve as a useful guide to the design of the particle-­
based catalytic devices.

5. Choice of photocatalyst material
So far, nanocrystalline TiO2 is the most commonlyused photoactive material to build a photoanode. However, other oxides and other n-type semiconductors havebeen studied as well. Man I. et al. (2011) have explored
trends in electrocatalytic activity of the oxygen evolution

Conceptualization of the equivalence of a suspended nanoparticle system as a miniaturized PEC. Reprinted with permission from Ref. (Teo W.Y. et al., 2012). Copyright: (2012) American Chemical Society.

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Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Fig. 11 H2 evolution efficiency plot for various metal co-­catalysts. Reprinted with permission from Ref.
(Morales-­Guio C. G. et al., 2014). Copyright: (2014)
Royal Society of Chemistry.
Fig. 10 Oxygen evolution efficiency plot for various metal oxides. Reprinted with permission from Ref. (Man I. etal., 2011). Copyright: (2011) Royal Society of Chemistry.

reaction (OER) investigated on the basis of a large database of HO• and HOO• adsorption energies on oxide surfaces. Based on theoretically calculated overpotentials(Man I. et al. 2011), they have derived a universal scaling
relation between the adsorption energies of HOO• vs. HO.
Then, based on this, they have analyzed the reaction-freeenergy diagrams, ΔG, of many oxides and derived an“activity volcano”, see Fig. 10. This plot can provide a
universal descriptor for the oxygen evolution activity.
Fig. 10 suggests a fundamental limitation on the maximum oxygen evolution activity of oxide catalysts. For example, Fig. 10 suggests that Mn-oxide and Co-oxide, i.e.
much cheaper oxides than RuO2 or IrO2, should be promising co-catalysts for the O2 production reactions inwater-splitting heterostructures.
A similar “volcano activity” plot has been derived by
Morales-Guio C.G. et al. (2014), see Fig. 11, for the electron-accepting particles. This shows that the—expensive—
Pt 0, Pd0, Rh0 particles are the most efficient for H 2
production technologies. Cu0, Ni0, Co0 —as low-cost alternatives—are worth exploiting; however, avoiding their surface oxidation is a great limitation at present. Non-­oxidechalcogenide n-type semiconductors such as ZnS, CdS,
CdSe, etc. have been extensively studied for applicationin the photocatalytic (Kakuta N. et al., 1985) and photoelectrochemical (Hodes G. et al., 1976) production of H2.
The reason is that, with the exception of ZnS, they absorb visible light. However, these substances are vulnerable to oxidation (for example, CdS + 2H+ → Cd 2+ + H2S),
which dissolves the material and destroys it. In the presence of a sacriﬁcial agent, it is possible to harvest h+, thus
restricting the particle degradation in solution. Also, chalcogenide materials can be synthesized in the form of
core-shell nanostructures (Amirav L. and Alivisatos A.P.,

242010) which have greater stability. ZnS—in spite of its
highest Eg among all halcogenides—has been a popularresearch target since its CB and VB levels are favorably
placed, as can be seen in Fig. 5. Thus, ZnS possesses
strong oxidant and reductant power. It combines with
CdS, so that, by changing their proportions, the overall
light-absorbance can be tuned within a wide range. In themost advanced Z-scheme concept, the combination of two
semiconductors assists electron–hole separation anyway(see Section 4.1.5).

5.1 Bi-Vanadate-Based Nanostructures
Monoclinic sheelite BiVO4 is an n-type semiconductor
with a direct band gap of 2.4 eV, thus it absorbs visible
light, λ = 420–530 nm, and is stable in neutral electrolyte,
non-toxic and relatively cheap (Kudo A. et al., 1999).
BiVO4 has an optical penetration depth of lp = 100–
500 nm at λ = 420–530 nm. Compared to other common
O2-evolving photocatalysts such as WO3 or Fe2O3, BiVO4
has a relatively high CB edge (+ 0.02 eV) (Kudo A. andMiseki Y., 2009; Park Y., et al., 2013) and, as a consequence, requires less bias potential to raise the potentialof photoelectrons above the H+/H2 reduction potential(0.0 V). BiVO4 is thermodynamically favorable for thehalf-reaction of H2O oxidation, but requires an externallyapplied bias (Kudo A. and Miseki Y., 2009; Park Y. et al.,2013) for the water reduction half-reaction. The theoretical maximum STH efficiency is 9.1 % and the theoreticalmaximum photocurrent is 7.4 A/cm2 (Park Y. et al., 2013).
In the last decade, BiVO4 has arisen among the main materials for visible-light photocatalysis, despite its shortcomings, i.e. low e-conductivity and poor H2O-oxidation
kinetics. These undesired properties may be improved bymodiﬁcations, including the formation of heterostructureswith another semiconductor, charge mediator, or use of a
co-catalyst (Kudo A. et al., 1999; Kudo A. and Miseki Y.,2009). So far, the theoretical maximum STH efficiency

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

different oxygen evolution catalyst (OEC) layers, FeOOH
and NiOOH, resulted in a BiVO4/FeOOH/NiOOH photoanode that achieved a photocurrent density of 2.73 mA/cm2
at a potential as low as 0.6 V. The use of FeOOH andNiOOH reduces interface recombination at the BiVO4/
OEC junction, while creating a more favorable Helmholtz
layer potential drop at the OEC/electrolyte junction, Kim
et al. (2014).

5.2 Z-Scheme Nano Photo Structures

Fig. 12 Reduced graphene oxide on a visible-light BiVO4photocatalyst for enhanced photoelectrochemical
water splitting. Reprinted with permission from Ref.
(Ng Y.H., et al., 2010). (Copyright: (2010) American
Chemical Society.

9.1 % cannot be achieved due to serious charge recombination and low water oxidation kinetics. BiVO4 has anelectron-diffusion length of only ~10 nm and a hole-­
diffusion length of ~100–200 nm (Hong S.J., et al., 2011;
Li Z., et al., 2013). This causes excessive consumption ofelectrons by charge recombination. Doping BiVO4 with
Mo and W can significantly increase its electron- diffusion length to ~300 nm (Kudo A. et al., 1999). Poor kinetics for O2 evolution at the BiVO4 surface constrains its
efficiency. This can be improved by co-catalyst loadingon BiVO4.
In an innovative approach, Amal’s and Kudo’s groups(Ng Y.H., et al., 2010) demonstrated that a reduced
graphene oxide RGO/BiVO4 nanocomposite, see Fig. 12,
can achieve almost an 80-fold [i-V] enhancement in thephotoelectrochemical water splitting reaction. In the same
work (Ng Y.H. et al., 2010), BiVO4 was used successfully
as a visible-light-photocatalyst to photocatalytically reduce GO to reduced graphene oxide. Recently, Kim et al.
(2014) demonstrated that a nanoporous BiVO4 (SSA =31.8 m2/g) effectively suppresses bulk carrier recombination of BiVO4 without additional doping, manifesting anelectron-hole separation yield of 0.90 at 1.23 V. Use of two

A “Z-scheme” (Sasakia Y. et al., 2008) can be considered a special type of PEC-PEC tandem cell that imitates
the architecture of the two natural photo systems of green
plants, i.e. photosystem I and photosystem II. In the nanoZ-scheme approach, see Fig. 13, two semiconductors, I
and II, are bridged with a redox particle or a liquid-redox
couple mediator. Energetic considerations of the photodecomposition of water by semiconductor systems using
sunlight suggest that a single light-absorbing system necessitates the use of a semiconductor with a rather large
band gap of 2.5 to 3.0 eV (Chen X. et al., 2010; Kubacka
A. et al., 2012; Sasakia Y. et al., 2008). This stems fromthe fact that the requisite energy and driving forces must
suffice to overcome the redox barrier of 1.23 eV for water
splitting, see Fig. 13.
Alternatively, efficient utilization of solar energy forwater splitting may imitate the successful strategy ofgreen plants, that is, the use of two photo systems withthe absorption of two photons of lower energy per electron transferred. So far, several Z-schemes with two-­
heterostructured photocatalysts have been investigated in
H 2 and O2 production from water using solar energy(Chen X. et al., 2010; Kubacka A. et al., 2012; Sasakia Y.
et al., 2008).
These works have established that overall water splitting can be achieved by constructing a Z-scheme photocatalytic system using photocatalysts, each one being
active only for one of the half-reactions of water splitting(H2 or O2 evolution reactions) in the absence of sacriﬁcial

Fig. 13 An all-solid-state Z-scheme heterostructure.

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reagents. In general, a redox mediator is required to couple with two photosystems. In a further leap forward, toeliminate undesirable backward reactions caused by redox mediators (such as Fe3+/Fe2+), a Z-scheme system
without an electron mediator, i.e. an all-solid-stateZ-scheme photocatalyst, has attracted much attention, seeFig. 13. This advanced Z-scheme retards back-reactions
and increases the reaction efﬁciency. A number of all-­solid-state Z-scheme photocatalysts (Chen X. et al., 2010;
Kubacka A. et al., 2012) such as CdS-Au-TiO2 (Tada H. etal., 2006) have been demonstrated to exhibit high photocatalytic activity, far exceeding that of the single-component
systems. In all these multi-component Z-scheme photocatalyst systems without exception, the separation of e –/h+pairs is promoted within the two semiconductors and further improved by the coupled metal particle that acts as
the electron-transfer mediator, Fig. 13.

5.3 Visible-Light Energy Production
Visible light water splitting is a long-standing challengein photochemistry (Chen X., 2010; Grätzel M., 2001;
Youngblood W.J. et al., 2009). As shown in Fig. 14, theband structure of the particle determines the spectral
range of light absorption and the theoretical maximum
STH efficiency (Chen Z., 2010; Li J. and Wu N., 2015).
For example, the theoretical maximum STH efficiency is
only 0.22 % for SrTiO3 (Eg = 3.7 eV) and 1.3 % for anatase
TiO2 (Eg = 3.2 eV) (Li J. and Wu N., 2015; Miller E.L. etal., 2010; Youngblood W.J. et al., 2009).
TiO2 is a benchmark semiconductor, but it has a wideband gap (3.2 eV for anatase). Hence it can only absorb
UV light, which accounts for less than 5 % of total solar
radiation (Grätzel M., 2001; Miller E.L. et al., 2010). The
most effective approach to increase the STH efficiency isFig. 14 Solar-to-hydrogen (STH) efficiency and maximum
photocurrent trends vs. the band gap for photoactive
semiconductors. Reprinted with permission from Ref.
(Li J. and Wu N., 2015).Copyright: (2015) Royal Society of Chemistry.

26

to decrease the Eg in order to extend the light absorption
spectral range into the visible-light region (~43 % of total
solar radiation) and even the near-infrared light region(~80 % of total solar radiation). However, the band gap
must be large enough to meet the thermodynamic andkinetic requirements for water splitting. Thermodynamics
dictate the minimum energy required to overcome thestandard Gibbs free energy change (1.23 eV) for water
splitting. Thermodynamic losses (0.3–0.5 eV) should be
added to this value. Thus an overpotential of 0.4–0.6 eV
is required to enable a fast reaction (Asashi R. et al., 2001;
Liu G. et al., 2012). Therefore, an ideal band gap is 1.9–
2.3 eV.
Nitrogen-doping of TiO2 (Asashi R. et al., 2001) has
boosted research in visible-light photocatalysis. Other examples of innovative visible-light structures involve thefollowing:i) “Red anatase” TiO2, which has been prepared byheating anatase TiO2 microspheres with a pre-doped interstitial boron shell to between 580 and 620 °C in a gaseous NH3 atmosphere.
This material has achieved a high photoelectrochemical
water splitting activity (Liu G., et al., 2012). The UV-vis
absorption spectrum of red anatase TiO2 shows an extended absorption edge up to 700 nm, covering the fullvisible-light spectrum due to a band-gap gradient which
varies from 1.94 eV on the surface to 3.22 eV in the coreby gradually elevating the VB maximum, Fig. 15. The
approach for producing this red-TiO2 involved a predoping step, i.e. introduction of an interstitial boron gradient(Liu G. et al., 2012). This in turn improved the incorporation of substitutional N in the TiO2 bulk without introducing Ti3+ impurity levels (Liu G. et al., 2012). Structurally,
the interstitial boron dopant effectively weakened the surrounding Ti-O bonds to facilitate easier N-substitution
and increased the chemical stability of B-N co-doped

Fig. 15Structural characteristics of red anatase, prepared by
N-B-TiO2 sequential doping of TiO2. Reprinted withpermission from Ref. (Liu G. et al., 2012). Copyright:(2012) Royal Society of Chemistry.

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Fig. 16 Black TiO2 suboxide produced via flame spray pyrolysis. Reprinted with permission from Ref. (Fujiwara K.,
et al., 2014). Copyright: (2014) Elsevier.

TiO2. Moreover, the extra electrons from B-atoms compensated for the charge difference between the latticeoxygen and a substituted ion to maintain charge neutrality.
ii) “Black TiO2” can be produced by two different technologies: treatment of TiO2 particles under H2 at highpressures and temperatures (Chen X. et al., 2011), which
results in the formation of a Ti3+ shell by reduction of the
Ti4+. This Ti3+ shell has a distorted structure, which inturn creates additional interband states. This results inlight absorbance in the visible wavelengths (Chen X. etal., 2011).
Recently, we have discovered that a black TiO2 can beproduced by a scalable flame spray pyrolysis process in
one step (Fujiwara K. et al., 2014), Fig. 16. Reductant
combustion intermediates present during ﬂame synthesisof these materials partially induce strong TiO2 metal support interactions (SMSI), resulting in crystalline Ti-­
suboxides (Ti3O5, Ti4O7). The growth of such suboxides
can be controlled via control of the flame spray pyrolysis
conditions, allowing the light absorption intensity in thevisible spectrum to be tuned.

6. The notion of “renewable H2” production
Currently, industrial electrolysis uses clean water inorder to prevent the fouling of system components. However, the need for clean water prevents the exploitation oflarge-body sources such as seawater, industrial waste andmunicipal waste as water feed. This poses the challengethat the use of cheaper, alternative sources of water instead of purified distilled water should be envisioned as
the next target for truly unlimited production of “renew-

able H2”. At the consumer scale, H2 can be either produced
centrally or on-site. The market for on-site generation
systems is growing due to certain advantages associatedwith not needing transportation and delivery. Currently,
most of industrial-use H2 is produced by the steam reforming of natural gas or CH4 (Conway, B.E, and Tilak,
B.V. 2002; Holdren J.P., 2007) due to the availability andlow prices of natural gas at present. Next, after the steam
reforming of natural gas, the partial oxidation of petroleum oil is second in H2 production capacity.
So far, with regard to biofuels, most researchers choose
to study methanol, ethanol or glycerol as model fuels(Chen X. et al., 2010; Lianos P., 2011). There are threemain reasons for this: (1) methanol, ethanol or glycerol
give the highest yield; (2) they have been extensively
studied, so a lot of data and know-how on their use exists;and (3) they can be cost-efficient products of biomass.
Thus in a mature biomass-based market, methanol, ethanol or glycerol should be available and renewable. As an
example, glycerol, a waste byproduct material of biodiesel
production (Lianos P., 2011), is available in mass-­produced
quantities. In addition to small alcohols, other organics
such as sugars and organic acids have also been a popular
choice for photocatalytic H2 production (Chen X. et al.,2010; Lianos P., 2011).
Thus truly “renewable H2” production can be achieved
if the photocatalytic technology can exploit seawater orwastewater feed or via the use of small organics produced
via a sustainable process.

7. Next-decade targets
Currently, the long-term objective aimed at by the US
Department of Energy is the photocatalytic H2 production
based on a durable, semiconductor-based, solar-driven
water-splitting device with the following specifications:(1) solar-to-hydrogen (STH) efficiency > 20 %,(2) that can operate under at least 10–15 times solar concentration, and generate renewable hydrogen for < $2/
kg .(ENERGY.GOV, 2015)
In the same context, the US-DoE near-future objectives
specify the nanomaterials’ physicochemical standards asfollows: development of surface modifications that will
make the materials viable at high current densities. Thisis related to the need for highly efficient, durable materials for PEC water splitting using concentrated solar energy.
This is important since in order to minimise H2-production
costs, operation under high photon and electron flows
is identified as the most significant driver. Mechanicalsurface durability can be improved through the crystal
structure and surface engineering. To this end, surface
defects should be engineered in a balanced way, since
surface defects might be desirable for enhanced reactiv-

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ity; however, at the same time, too many surface defects
might decrease the durability of a nanocrystal.
In parallel, the optimization of existing materials or the
discovery of novel materials should incorporate the predictive power of theory and modeling. The target of 20 %STH efficiency targeted by the US-DoE is a feasible goal.
As a reference, a 10-fold solar light concentration with a
20 % STH gives approximately 160 mA/cm 2 (Conway,
B.E and Tilak, B.V., 2002; Lewis N.S. and Nocera D.G.,
2006). However, although the current H2 oxidation reaction rates in fuel cells achieve this range, i.e. 100–
1000 mA/cm2, a severe rate-limiting step is imposed by
the very slow O2 reduction reaction that typically imposes
low rates, i.e. as low as 10 –6 –10 –11 A/cm2 (Conway, B.E
and Tilak, B.V., 2002; Lewis N.S. and Nocera D.G., 2006).
Thus intensive research on novel or improved O2-reduction
materials is in high demand.
The US-DoE targeted (by 2018) an increase in chemical conversion process efficiency for PEC from 4 % to12 % (ENERGY.GOV, 2015; Miller E.L., et al., 2010).
This will require signiﬁcant breakthroughs in the development of new materials. The challenge can be seen
through Fig. 14, which allows an estimate of the fundamental solar absorption limitations in H2 production in
PEC for a number of the tested metal-oxide semiconductors (Li J. and Wu N., 2015; Miller E.L. et al., 2010). In
Fig. 14, the potentially achievable photocurrent levels andSTH conversion efﬁciencies of a given semiconductor/
electrolyte interface are related to the semiconductor bandgap. This is based on an idealized case where 100 % of
the photons in the solar spectrum with energies exceeding
the band gap are absorbed and converted. It must be
strongly emphasized that the STH efﬁciencies, as shownin Fig. 14, are only deﬁned in stand-alone material systems with sufﬁcient photo-induced potential to thermodynamically split water. To date, only very high-band-gap
materials have exhibited stand-alone water-splitting insingle junction conﬁgurations, as seen in Fig. 14. It isseen that the resulting STH efﬁciencies of these materials
is less than 1 % (Li J. and Wu N., 2015; Miller E.L., et al.,2010; Rocheleau R. and Miller E., 1997). Interestingly, today’s PEC performance status of a STH = 4 % has beenachieved in multi-junction conﬁgurations (Grätzel M.,
2001), not in a single-particle system. Thus, it is important
to emphasize that Z-scheme, multi-junction conﬁgurations are the way forward to create stand-alone water-­splitting systems. This will allow the use of some of thelow-Eg materials under a proper “branching” of the CB/
VB levels, see the concept in Fig. 13. If this is the casewith Z-scheme conﬁgurations, the photo-generated currents and therefore their STH efﬁciencies will not be constrained by the Eg value or e –/h+ transfer rates, but rather
by the semiconductor/electrolyte interface limitations.
Even in such Z-scheme conﬁgurations, achieving STH

28

performance ~15 % will require development of efﬁcientand stable semiconductors with the Eg near 2.0 eV. Ultimately, after the lab work, marketing of the most competitive
materials or devices will require low-cost nanomaterials
production and device synthesis. On this front, scalable
one-step particle production technologies such as flame
spray pyrolysis (Teoh W.Y. et al 2012; Ng, Y. et al., 2010;
Fujiwara K. et al., 2014), would contribute decisively.

8. Conclusions
Photoactive nanomaterials hold great potential for environmental technologies. These include the productionof electricity, energy-fuel production and photocatalytic
water remediation. Current targets posed by the US Department of Energy are discussed based on a 2015 report.
In contrast to the case of p-n junction photovoltaics where
the manufacturing cost of the required high-purity single
crystals emerges as the main objective (mostly commercial, rather than fundamental research), a key target for
the field of photoelectrochemical nanotechnology is thediscovery and development of new materials to advancethe field. These include:– raising the solar to hydrogen yields > 15 %,– manufacturing of all-solid-state Z-scheme photoactive
materials,– optmized materials for visible-light absorbance withenhanced quantum yields.

Nomenclature
Symbols and units should be listed in alphabetical order with
their definition and dimensions in SI units.
PEC

Photoelectrochemical cell

DoE

Department of Energy

NHE

Normal hydrogen electrode

RGO

Reduced graphene oxide

AM

Atmospheric mass

References
Amirav L., Alivisatos A.P., Photocatalytic hydrogen production
with tunable nanorod heterostructures, Journal of Physical
Chemistry Letter, 1 (2010) 1051–1054.
Asashi R., Morikawa T., Ohwaki T., Aoki K., Taga Y., Visible-­light photocatalysis in nitrogen-doped titanium oxides, Science, 293 (2001) 269–271.
Bard A.J., Photoelectrochemistry, Science, 207 (1980) 139–144.
Bolton J.R., The production of energy-rich compounds by thephotochemical conversion and storage of solar energy,

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

Solar Fuels Science, 202 (1978) 705–711.
Bolton J.R., Strickler S.J., Connolly J.S., Limiting and realizableefficiencies of solar photolysis of water, Nature, 316 (1985)
495–500.
Chen X., Shen S., Guo L., Mao S.S., Semiconductor-based photocatalytic hydrogen generation, Chemical Review, 110(2010) 6503–6570.
Chen X., Liu L., Yu P.Y., Mao S.S., Increasing solar absorption
for photocatalysis with black hydrogenated titanium dioxide nanocrystals, Science, 331 (2011) 746–750.
Chen Z., Jaramillo T.F., Deutsch T.G., Kleiman-Shwarsctein A.,
Forman A.J., Gaillard N., Garland R., Takanabe K., Heske
C., Sunkara M., McFarland E.W., Domen K., Miller E.L.,
Turner J.A., Dinh H.N., Accelerating materials development for photoelectrochemical hydrogen production: Standards for methods, definitions, and reporting protocols,
Journal of Materials Research, 25 (2010) 3–16.
Conway B.E, Tilak B.V., Interfacial processes involving electrocatalytic evolution and oxidation of H+ and the role ofchemisorbed H+, Electrochemical Acta, 47 (2002) 3571–
3594.
Cooper J.K., Gul S., Toma F.M., Chen L., Liu Y., Guo J., Ager
J.W., Yano J., Ian D., Sharp On the Indirect Bandgap and
Optical Properties of Monoclinic Bismuth Vanadate Journal of Physical Chemistry C, 119 (2015) 2969–2974.
Coronado J.M., Sanchez B., Portela R., Suarez S., Journal of
Solar Energy & Engineering, Solar photocatalysis for theelimination of trichloroethylene in the gas phase, 130(2008) 011–016.
Devi L.G., Kavitha R., Review on modiﬁed N-TiO2 for green
energy applications under UV/visible light: selected results
and reaction mechanisms, RSC Advances, 4 (2014) 28265–
28299.
Dong S., Feng J., Fan M., Pi Y., Hu L., Han X., Liu M., Sun J.,
Recent developments in heterogeneous photocatalytic water
treatment using visible light-responsive photocatalysts: A
review, RSC Advances, 5 (2015) 14610–14630.
Elliott R.J., Intensity of optical absorption by excitons, PhysicalReview, 108 (1957) 1384–1389.
ENERGY.GOV (U.S. Department of Energy), US-DoE Efficiency and Renewable Energy, Hydrogen, Fuel Cells andInfrastructure Technologies Program—Multi-Year Research,
Development and Demonstration Plan; 2015. <https://energy.
gov/sites/prod/files/2015/06/f23/fcto_myrdd_production.
pdf> accessed 21.12.2016.
Fagan R., McCormack D.E., Dionysiou D.D., Pillai S.C., A
review of solar and visible light active TiO2 photocatalysis
for treating bacteria, cyanotoxins and contaminants ofemerging concern, Materials Science in Semiconductor
Processing, 42 (2016) 2–14.
Formal F.L., Gratzel M., Sivula K., Controlling photoactivity inultrathin hematite ﬁlms for solar water-splitting, Advanced
Functions Materials, 20 (2010) 1099–1107.
Froschl T., Behm R. J., Hormann U., Husing N., Kubiak P.,
Kaiser U., Kucerova G., Landfester K., Pfanzelt M., Weiss
C.K., Wohlfahrt-Mehrens M., High surface area crystalline
titanium dioxide: potential and limits in electrochemicalenergy storage and catalysis, Chemical Society Review, 41(2012) 5313–5360.
Fujishima A., Honda K., Electrochemical Photolysis of Water at
a Semiconductor Electrode., Nature, 38 (1972) 37–38.
Fujiwara K., Deligiannakis Y., Skoutelis C.G., Pratsinis S.E.,
Visible-light active black TiO2-Ag/TiOx particles, Applied
Catalysis B-Environmental, 9 (2014) 154–155.
Getoff N., Photoelectrochemical and photocatalytic methods ofhydrogen production: a short review, International Journalof Hydrogen Energy, 15 (1990) 407–417.
Giannakas A., Antonopoulou M., Konstantinou I., Deligiannakis
Y., EPR and Photocatalytic Study of Pt-Loaded N-TiO2,
NF-TiO2, ACS Catalysis, (2016) Submitted.
Goldsmith J.I., Hudson W.R., Lowry M.S., Anderson T.H.,
Bernhard S., Discovery and high-throughput screening ofheteroleptic iridium complexes for photoinduced hydrogenproduction, Journal of American Chemical Society, 127(2005) 7502–7510.
Grätzel M., Photoelectrochemical cells, Nature, 414 (2001) 338–
344.
Grätzel M., Solar Energy Conversion by Dye-Sensitized Photovoltaic Cells Inorganic Chemistry, 44 (2005) 6841–6851.
Harriman A., Pickering I.J., Thomas J.M., Christensen P.A.,
Metal oxides as heterogeneous catalysts for oxygen evolution under photochemical conditions, Journal of ChemistrySociety, Faraday Transactions I, 84 (1988) 2795–2806.
Hernandez-Alonso M.D., Fresno F., Sureza S., Coronado J.M.,
Development of alternative photocatalysts to TiO2:Challenges and opportunities, Energy Environmental Science, 2(2009) 1231–1257.
Hodes G., Manassen J., Cahen D., Photoelectrochemical energy
conversion and storage using polycrystalline chalcogenide
electrodes, Nature, 261 (1976) 403–404.
Holdren J.P., Energy and sustainability, Science, 315 (2007) 737.
Hong S.J., Lee S., Jang J.S., Lee J.S., Heterojunction BiVO4/
WO3 electrodes for enhanced photoactivity of water oxidation Energy Environmental Science, 4 (2011) 1781–1787.
JPCCSVI (Journal of Physical Chemistry C Special Virtual Issue),Solar Fuels. Photocatalytic Hydrogen Generation, <http://pubs.
acs.org/page/jpccck/vi/solarfuels.html> accessed 21.12.2016.
Kakuta N., Park K.H., Finlayson M.F., Ueno A., Bard A.J.,
Campion A., Fox M.A., Webber S.E., White J.M., Photoassisted hydrogen production using visible light and coprecipitated ZnS-CdS without a noble metal, Journal of Physical
Chemistry, 89 (1985) 732–734.
Kamat P.V., Environmentally Benign Photocatalysts in: Anpo
M. (Eds), Springer, 2010.
Khaselev O., Turner J.A., A monolithic photovoltaic-­
photoelectrochemical device for hydrogen production via
water splitting, Science, 280 (1998) 425–427.
Kim, T.W., Choi K-S., Photoanodes with Dual-Layer Oxygen
Evolution Nanoporous BiVO4 Catalysts for Solar Water
Splitting, Science, 343 (2014) 190–194.
Kubacka A., Fernández-García M., Colón G., Advanced nanoarchitectures for solar photocatalytic applications, Chemical
Reviews, 112 (2012) 1555–1614.
Kudo A., Omori K., Kato H., A novel aqueous process for preparation of crystal form-controlled and highly crystalline
BiVO4 powder from layered vanadates at room temperature

29

Yiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

and its photocatalytic and photophysical properties, Journalof American Chemistry Society, 121, (1999) 11459–11467.
Kudo A., Miseki Y., Heterogeneous photocatalyst materials forwater splitting, Chemical Society Review, 38 (2009) 253–
278.
Lewis N.S., Nocera D.G., Powering the planet: Chemical challenges in solar energy utilization, Proceedings of the
National Academy of Science of the United States America,
103 (2006) 15729–15735.
Li J., Wu N., Semiconductor-based photocatalysts and photoelectrochemical cells for solar fuel generation: a review,
Catalysis Science Technology, 5 (2015) 1360–1384.
Li Z., Luo W., Zhang M., Feng J., Zou Z., Photoelectrochemicalcells for solar hydrogen production: current state of promising photoelectrodes, methods to improve their properties,
and outlook, Energy Environmental Science, 6 (2013) 347–
370.
Lianos P., Production of electricity and hydrogen by photocatalytic degradation of organic wastes in a photoelectrochemical cell: The concept of the Photo fuel cell: A review of are-emerging research field, Journal of Hazardous Materials,
185 (2011) 575–590.
Licht S., Wang B., Mukerji S., Soga T., Umeno M., Tributsch H.,
Over 18 % solar energy conversion to generation of hydrogen fuel: theory and experiment for efficient solar water
splitting, International Journal of Hydrogen Energy, 26(2001) 653–659.
Lindgren T., Lu J., Hoel A., Granqvist C.G., Torres G.R.,
Lindquist S.E., Photoelectrochemical study of sputterednitrogen-doped titanium dioxide thin films in aqueous electrolyte, Solar Energy Materials & Solar Cells, 84 (2004)
145–157.
Linsebigler A.L., Lu G.Q., Yates J.T., Photocatalysis on TiO2
Surfaces-Principles, Mechanisms, and Selected Results,
Chemical Reviews, 95 (1995) 735–758.
Liu G., Yin L., Wang J., Niu P., Zhen C., Xie Y. Cheng H., A red
anatase TiO2 photocatalyst for solar energy conversion,
Energy & Environmental Science, 5 (2012) 9603–9610.
Liu J.J., Chen S., Zhu Y., Electronic structures and effective
masses of photogenerated carriers of CaZrTi2O7 photocatalyst: First-principles calculations, Solid State Communication, 152 (2012) 1650–1654.
Liu J.J., Chen S.F., Liu Q.Z., Zhu Y.F., Zhang J.F., Correlationof crystal structures and electronic structures with visible
light photocatalytic properties of NaBiO3, Chemical Physics Letters, 572 (2013) 101–105.
Maeda K., Teramura K., Lu D., Takata T., Saito N., Inoue Y.,
Domen K., Photocatalysts releasing hydrogen from water,
Nature, 440 (2006) 295.
Maeda K., Domen K., New Non-Oxide Photocatalysts Designed
for Overall Water Splitting under Visible Light, Journal of
Physical Chemistry C, 111 (2007) 7851–7861.
Maeda K., Domen K., Effect of post calcination on photocatalytic activity of (Ga1-x Zn x)(N1-xO) solid solution for overallwater splitting under visible light, Journal of Catalysis, 254(2008) 198–204.
Man I., Su H.-Y., Vallejo F., Hansen H., Martinez J., Inoglu N.,
Kitchin J., Jaramillo T., Norskov J., Rossmeis, Universality

30

in Oxygen Evolution Electrocatalysis on Oxide Surfaces,
ChemCatChem Catalysis, 3 (2011) 1159–1165.
Miller E.L., Gaillard N., Kaneshiro J., DeAngelis A., Garland
R., Progress in new semiconductor materials classes forsolar photoelectrolysis, International Journal of Energy
Research, 34 (2010) 1215–1222.
Miyauchi M., Nakajima A., Watanabe T., Hashimoto K., Photocatalysis and photoinduced hydrophilicity of various metaloxide thin ﬁlms, Chemical Materials, 14 (2002) 2812–2816.
Morales-Guio C.G., Stern L-A, Hu X., Nanostructured hydrotreating catalysts for electrochemical hydrogen evolution,
Chemical Society Review, 43 (2014) 6555–6569.
Ng Y.H., Iwase A., Kudo A., Amal R., Reducing Graphene
Oxide on a Visible-Light BiVO4 Photocatalyst for an
Enhanced Photoelectrochemical Water Splitting, Journal of
Physical Chemistry Letter, 1 (2010) 2607–2612.
Ohtani B., Preparing Articles on Photocatalysis-Beyond theIllusions, Misconceptions, and Speculation, Chemistry
Letters, 37 (2008) 216–229.
Paracchino A., Laporte V., Sivula K., Grätzel M., Thimsen E.,
Highly active oxide photocathode for photoelectrochemical
water reduction, Nature Materials, 10 (2011) 456–461.
Park Y., McDonald K.L., Choi K., Progress in bismuth vanadate
photoanodes for use in solar water oxidation, Chemical
Society Review, 42 (2013), 2321–2337.
Rocheleau R., Miller E., Photoelectrochemical production ofhydrogen: engineering loss analysis, International Journal
Hydrogen Energy, 22 (1997) 771–782.
Ryu J., Choi W., Substrate Specific Photocatalytic Activities ofTiO2 and Multiactivity Test for Water Treatment Application,
Environmental Science Technology, 42 (2008) 294–300.
Sasakia Y., Iwasea A., Katoa H., Kudo A., The effect of co-­catalysts for Z-scheme photocatalysis systems with an Feelectron mediator on overall water splitting under visible
light irradiation, Journal of Catalysis, 259 (2008) 133–137.
Shockley W., Queisser H.J., Detailed Balance Limit of Efficiency of p-n Junction Solar Cells, Journal of Applied
Physics, 32 (1961) 510.
Svrcek V., Slaoui A., Muller J.-C., Silicon nanocrystals as light
converter for solar cells, Thin Solid Films, 451 (2004) 384–
388.
Tada H., Mitsui T., Kiyonaga T., Akita T., Tanaka K., All-solidstate Z-scheme in CdS–Au–TiO2 three-component nanojunction system, Nature Materials 5, (2006) 782–786.
Tang J.W., Cowan A.J., Durrant J.R., Klug D.R., Mechanism of
O2 Production from Water Splitting: Nature of Charge Carriers in Nitrogen Doped Nanocrystalline TiO2 Films andFactors Limiting O2 Production, Journal of Physical Chemistry C, 115 (2011) 3143–3150.
Tauc J., Menth A., Wood D.L., Optical and magnetic investigations of localized states in semiconducting glasses, PhysicalReview Letter, 25 (1970) 749–752.
Teo W.Y., Scott J.A., Amal R., Progress in Heterogeneous Photocatalysis: From Classical Radical Chemistry to Engineering Nanomaterials and Solar Reactors, The Journal of
Physical Chemistry Letters, 3 (2012) 629–639.
Walsh A., Yan Y., Huda M.N., Al-Jassim M.M, Wei S., Band
Edge Electronic Structure of BiVO4: Elucidating the RoleYiannis Deligiannakis / KONA Powder and Particle Journal No. 35 (2018) 14–31

of the Bi s and V d Orbitals, Chemical Material, 21 (2009)547–551.
Wang C., Rabani J., Bahnemann D.W., Dohrmann J.K., Photonic
efficiency and quantum yield of formaldehyde formationfrom methanol in the presence of various TiO2 photocatalysts, Journal of Photochemistry and Photobiology A, 148(2002) 169–176.
Wang L. Wei H., Fan Y., Liu X., Zhan J., Synthesis, opticalproperties and photocatalytic activity of one–dimensional
CdS@ZnS core-shell nanocomposites, Nanoscale Research
Letters, 4 (2009) 558–564.
Würfel P. The Physics of Solar Cells. Weinheim: Wiley-VCH(2005).
Youngblood W.J., Lee S.A., Maeda K. Mallouk T.E., Accountsof Chemical Research Visible Light Water Splitting Using
Dye Sensitized Oxide Semiconductors, 42 (2009) 1966–
1973.
Zhang J., Zhou P., Liu J., Yu J., New understanding of the difference of photocatalytic activity among anatase, rutile andbrookite TiO2, Physical Chemistry Chemical Physics, 16(2014) 20382–20386.
Zou Z., Ye J., Sayama K., Arakawa H., Direct splitting of water
under visible light irradiation with an oxide semiconductor
photocatalyst, Nature, 414 (2001) 625–626.

Author’s short biography
Yiannis Deligiannakis
Yiannis Deligiannakis is currently a full professor and head of the Lab of Physical
Chemistry of Materials & Environment, Dept. of Physics at the University of Ioannina,
Greece. He earned his PhD at the National Centre for Scientific Research “Demokritos”,
Athens, Greece (1991). Between 1991 and 2000, he worked as research associate at theSection de Bioenergetique, CEA, Saclay, Paris, France. In 2012-2013, he was a visiting
professor at the Particle Technology Laboratory, ΕΤΗ Zurich, lab of Prof. S. Pratsinis. He
has published over 140 ISI papers in materials science, catalysis, EPR spectroscopy, flame
spray pyrolysis. He holds 7 patents on nanomaterials and applications in environment-­
related technologies.

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KONA Powder and Particle Journal No. 35 (2018) 32–48/Doi:10.14356/kona.2018006

Review Paper

Critical Review on Engineering Mechanical Quality ofGreen Compacts using Powder Properties †Hojae Yi 1*, Anuranjan Pandeya 2, Apoorva Karamchandani 1 and Virendra M. Puri 1
1

Department of Agricultural and Biological Engineering, Pennsylvania State University, USA
2
Scientific and Digital Systems Delhi, India

Abstract
For processes involving particulate materials, mechanical properties of green compacts are of great interest when
they are final or intermediate products. Optimal quality of green compacts is achieved usually with empiricalapproaches, i.e., unexpected issues in processes or products’ quality are usually mitigated by time and resource
consuming trial-and-error methods. Issues of the powder compaction are commonly observed when there areproblems in feed materials or operational conditions even without any substantial change in a formula. Suchdivergent behavior of particulate materials is especially problematic for product developments and reliable
operations. It has been widely accepted hypothesis that properties of particles are determinants of mechanicalbehavior of powder during compaction and the quality of resulting compacts. With recent developments in nanotechnology, characterization and engineering of individual particles at a microscopic or sub-microscopic scale are
now feasible. Leveraging recent technological advancements, there has been a good progress in regard toquantitative understanding of mechanical relationships between properties of particles, particle system and final
product. This review highlights the recent developments and gaps in engineering mechanical quality of powder
compacts in conjunction with the characterization of particle systems and compaction at multiple scales.
Keywords: powder compaction, green compacts, compact quality, powder properties, particle properties

1. Introduction
Compaction is often employed as a terminal process for
manufacturing consumer goods and it affects the qualityof final products in the most direct way. Mechanical properties of compacts are especially important in post-­
production processes such as packaging, transportation,and end-use by consumers. For example, medicinal tablets
should not only maintain its integrity throughout packaging and subsequent handling but also provide appropriate
disintegration characteristics when administered into human body. Likewise, biomass pellets should preserve theirshape and size to ensure desired handling characteristics
throughout transportation with minimal crumbliness. On
the other hand, cosmetic compacts need to have desired
friability for consumer use as well as enough strength so†

Received 26 December 2016; Accepted 20 January 2017
J-STAGE Advance published online 8 April 20171
249 Agricultural Engineering Building, University Park, PA 16802,
USA
2
IDA House, R K R K Puram, Sector 4, RK Puram, New Delhi,
Delhi 110022, India* Corresponding author: Hojae Yi
E-mail: huy1@psu.edu
TEL: +1-814-865-2807 FAX: +1-814-863-1031

32

that they do not develop aesthetic defects during shippingand handling. Therefore, achieving and maintaining desired quality of compact is of great importance as a final
consumer product. Compaction is also utilized as a critical intermediate process, whose product’s properties are
crucial in reliable and efficient downstream processes
such as sintering of ceramic or compacted metal powders.
Ideally, compaction behavior and quality should be reasonably predicted during product development process,e.g., formulation, and novel particulate materials development. In reality, producing compact with minimal operational anomalies and desirable quality metrics is verymuch an art. Manufacturers regularly search for an efficient and sustainable window of operational parametersthat will reliably produce compacts’ characteristics satisfying often conflicting quality metrics. Balances between
operational maneuver, different mechanical quality metrics, and performance characteristics of compacts areusually achieved by tedious trial-and-error approaches
due to the lack of adequate scientific understanding of ora systematic approach to the powder compaction. One ofmajor reasons why compaction operation remains empirical, is because the fundamental understanding of powder
compaction is still elusive and, as a result, experiential
knowledge plays an essential role. However, the extent, toCopyright © 2018 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/).

Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48

which such empiricism can be applied, is limited becauseof particulate materials’ innate heterogeneity and variability. Novel materials or upstream processes require extended time in identifying optimal process parametersfrom scratch (Bell, 2005; Merrow, 1988). To address thisissue and enable a systematic approach in compaction
process and quality control, it is essential to expand ourknowledge of the fundamental mechanics of powder compaction and to develop quantitative relationships between
feed particulate materials’ properties, densification process parameters, and the mechanical quality metrics offinal products.
In addition to insufficient fundamental knowledge of
powder compaction, subjective quality metrics of compacts impose challenges to the consideration of the end
product quality. Many of quality metrics that are employed by industry have been developed and employedreflecting specific usages of particular products. For example, to evaluate adequate strengths of compacts for logistics or end use, one may use a ‘pass or fail’ test, in whicha product is dropped from a certain height to determine
breakages. Such tests provide only binary informationthat may provide limited usage as a quantifiable quality
metrics. Similar tests can be re-designed to measure massand height, at which the product begins to break. Obviously such a quality measurement requires more effort
and resources, but it will eventually pay-off when one has
the means to predict the quality of products based on
quantitative relationships taking properties of feed materials and operational parameters into the consideration.
Ideally, these types of tests can be replaced with a set ofstandardized tests that reflect various scenarios of logistical events, e.g., durability, friability, hardness, and solubility that may be relevant to a specific powder compact
product depending on the end use of the compacts.
Another challenge to the powder compaction process isthe quantitative powder properties characterization. In regard to properties of particulate feed materials, there are
two categories of properties that are relevant and meaningful in our context, namely physical and mechanicalproperties. Physical properties include bulk density, tap
density, particle density, particle size distribution, particle
shape, and so on. Even though these are fundamental
properties of particulate materials, direct relationships
between these and the final product’s properties are difficult to establish because of the stochastic properties ofparticulate materials, insufficient knowledge on the mechanics of the powder compaction process, and limited
understanding of how physical and mechanical propertiesof the powders affect the powder compaction process andproperties of compacts. Nonetheless, because of the dominant importance of mechanical properties of powder en
masse in the evolution of mechanical properties of compacts, there have been good amount of studies concerning

mechanical aspects of powder compaction especially at
the microscopic scale. Reflecting these, this review attempts to assess the current knowledge and to identify
subjects, studying which will aid the fundamental understanding of the powder compaction process and will enable a systematic engineering approach in efficient andreliable powder compact production. To that end, this review focuses on the quality metrics’ status quo withemphasis on how fundamental approach can help withpredicting and controlling the quality of compacts.

2. Compaction as a powder processing
operation
Unit operations involving particulate materials as raw
materials, have been well known to be prone to issues thatare difficult to mitigate through quantitative engineering
approaches (Ennis et al., 1994; Merrow, 1984, 1988). Furthermore, powder compaction is one of less addressed
powder processes in spite of its critical role in industrial
manufacturing. Powder compaction is utilized as a final
production process in various industries including pharmaceutical and nutraceutical tablets, cosmetic consumer
goods, biomass pellets, as well as an intermediate process
in ceramics and powder metallurgy. Compaction of powders is performed by mechanically pressing powder en
masse in dies to form a densified powder mass withenough mechanical integrity that can withstand externalloads during expected lifecycle. Green compacts are
made typically at ambient temperature through following
stages (Fig. 1): 1) Rearrangement of the particles by filling large pores accompanied with the increase in numberof contacts (coordination number); 2) packing of particles
resulting in decrease in porosity with the formation of localized agglomeration of particles, namely secondary andhigher order particle structures; 3) increase in the contact
area between particles accompanying elastic deformationof particles; and 4) contact enlargement through plastic
deformation of particles (Azami and Khoei, 2006;
Bortzmeyer, 1992; Castellanos et al., 2005; Cunningham
et al., 2004; Fayed and Otten, 1984; German, 2014; Yi etal., 2001).
Even though these stages of powder compaction havebeen established for decades, quantitative and fundamental understanding of how these stages contribute to theformation of green compacts is yet to be fully elucidated.
This is mainly due to the multiscale nature of the compaction process, which evolves towards different scales ofscrutiny, i.e., microscale (single particle, particle-particle
interactions), mesoscale (secondary and tertiary particle
structures), and macroscale (bulk powder system). Furthermore, due to powder system’s intrinsic stochasticity
in particle shapes and sizes in addition to the multiscale33

Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48

Fig. 1

Four stages of powder compaction. In the initial stage (Stage 1) of compaction, rearrangement of the particles by filling large pores accompanied with the increase in number of contacts (coordination number).
When the rearrangement of particles completes, volume of powder mass further decreases due to thepacking of particles with the formation of localized agglomeration of particles (Stage 2). Powder compaction advances with the increase in the contact area between particles accompanying elastic deformation of particles (Stage 3), then particle-particle contacts enlarge through plastic deformations ofparticles (Stage 4). As pressure increases further, the bulk density of powder mass gets close to the true
density of particles, which leads to the relative density of 1.0. Actual mechanisms of compaction overlaps in real-world compaction and the relative density, at which each stage initiates, varies depending on
various particle properties.

and multiphase nature, powder system is considered to be
an inherently complex system (de Gennes, 1999). As a result, many investigations of powder compaction are moreor less of troubleshooting nature. For example, issues ofpowder compaction have been identified by Blumenthal etal. (1997) in regards to powder metallurgy, by Alderborn
and Nystrom (1996) for pharmaceutical powder, and by
Ennis et al. (1994) for general granular materials.
On the other hand, there are established quantitativemodels describing powder compaction. Some phenomenological models include Heckel (Ilkka and Paronen,1993), Kawakita (Kawakita and Lüdde, 1971), andCooper-­Eaton model (Cooper and Eaton, 1962). Morephysically and mathematically rigorous models describe
powder compaction as a macroscopic phenomenon. Such a
constitutive model includes Cam-clay models (Dimaggio
and Sandler, 1971; Schofield and Wroth, 1968). Unfortunately, existing powder compaction models do not provide
fundamental understanding on how underlying particle’s
properties and particle interactions evolves up to macroscopic behavior of powder system during compaction.
Therefore, there exists inevitable limitation when one employs existing powder compaction models in predicting
and controlling powder compaction process and compact
properties.

34

3. Green compact quality
This review focuses on mechanical aspects of compact
properties among many quality metrics of powder compacts. This section briefly summarizes which mechanicalproperties of powder compacts are reviewed. A quantified
and systematic approach in determining the quality ofgreen compacts is an important step in engineering powder compaction. Accordingly, studies on powder compacts quality metrics are reviewed. Quality metrics of
powder compacts include fundamental metrics such as
density, strength, hardness as well as secondary or phenomenological properties including friability and otherdefects of powder compacts (Fig. 2).
One of the most important mechanical properties ofcompact is strength, i.e., the stress level at which a compact loses its mechanical integrity. Compact strength isrelated to the constitutive structure of a compact originating from the presence of ingredients, how homogeneously
different ingredients are mixed, deposited, and compressed. While the measurement of compact strength isusually performed at the macroscopic level, the origin of
defects develop and grow when a compact is subjected toa certain level of mechanical loading, which can often be
predicted by relative density distributions. The observation that the corresponding mechanical behavior is closely

Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48

Fig. 2

Green compact quality metrics. Right side branches include mechanical quality metrics that are reviewed
in this study. Quality metrics specific to compacts’ end users, which are in blue and on left branches, are
not reviewed.

related to the heterogeneous relative density distributionof a compact, suggests that the strength of compacts develops in relation to loaded powder system’s characteristic
stress distribution development pattern inside a powder
system. Since it is not practical to measure stress distribution of powder compacts during the compaction process,compaction behavior has long been described by change
in relative density of compact to the true density of particles. Relative density of a powder compact has been oneof actively investigated and widely used powder compact
quality metrics. Therefore, studies on powder compacts’density are reviewed first.
In following sections, studies involving powder compacts’ mechanical strengths from a more rigorous perspective are reviewed. In regard to quantitative mechanicalproperties of powder compacts, their integrity presents
two distinctive aspects i.e., development of discontinuityof a compact and localized breakage of powders at thesurface of a compact. The former relates more to defectsof compacts in a somewhat empirical sense. Considering
it wide usage, it is important to recognize empirical quality metrics. For example, mechanical quality metrics ofcompacts are often described or determined by inspecting
a presence of surface defects such as crack or capping. In
addition, such mechanical defects of powder compacts often arise from irregular or undesirable mechanical properties of compacts meaning that these can be regarded asindicators of mechanical strength of powder compacts.
Moreover, mechanical strength of compacts can be determined in a more empirical way. For example, one cansimply conduct a fail or pass test as a result of dropping a
product from a certain height. This type of test provides abinary result under very specific circumstances. Recog-

nizing broad usage of such approaches, studies involving
mechanical defects of powder compacts are reviewed.
Subsequently, studies involving mechanical strengths ofpowder compacts involving breakage or quantitative mechanical properties, which includes elastic moduli, parameters of powder compaction models, are reviewed. In
addition, mechanical strength of a compact’s surface has
been widely used as an indicator of mechanical propertiesof the entirety of powder compacts. Compacts surface’s
mechanical characteristic itself is of importance in somecases. Therefore, studies involving hardness tests or surface indentation test are also reviewed.
In addition, the properties of end product, i.e., powder
compacts, are often determined in the secondary or tertiary ways, most notably Rattler methods such as friability or durability test. In industry, mechanical strengths ofproducts in compressed powder form, are determined insuch empirical ways. For pharmaceutical products anddensified biomass, friability or durability test are commonly used to determine the level of mechanical integrityof products when they are subjected to a predeterminedsustained mechanical impacts. These type of tests generate quantitative quality metrics, but it is hard to correlatethem to fundamental properties of compacts, bulk powder, or particles because those tests represent specificmechanical environments. Nonetheless, considering its
popularity and frequent usage, studies involving Rattler
tests are reviewed.

3.1 Quality; Density and density distribution
Density is the most basic and fundamental property of
powder compacts. The term ‘bulk density’ is often used35

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to clarify that powder compact that inherently includes
voids between particles. Referring to the densities of ingredients, terms like ‘true density’ or ‘solid density’ areused. The relative density, i.e., ratio between bulk density
achieved by compression and ‘true density’ of particles, isoften used as a parameter indicating the degree of compaction or compaction behavior. Measurement of bulk
density of loose and compressed powders are rather
straightforward but ASTM D6683-14 (ASTM Standard
and D18.24 Committee, 2014) and ASTM D7481-09(ASTM Standard and D18.24 Committee, 2009) describe
standardized measurement procedures.
Considering that the density of bulk solid is determinedby its weight and volume whereas volume of bulk solidchanges upon compression, density can be an indicator ofa degree of compaction. Therefore, macroscopic volume
change of bulk solid has long been used to describe powder compaction or as an indicator of a degree of compaction. Some of most widely used descriptors of powder
compaction using macroscopic volume change and applied load includes Heckel, Kawakita, and Cooper-Eaton
equations (Alderborn and Nystrom, 1996; Fayed andOtten, 1984). Compressibility, which is based on the relative density of powder as described above, is still widelyused as a straightforward descriptor of mechanical behavior of powder in industry as well as researches. For example, Bonaccorsi and Proverbio (2006) measured relative
density (termed as green density) as an indicator of compaction quality for metallic powder compaction. Perez-­
Gandarillas et al. (2015)’s study used relative densitychange to explain tensile strength gain of compacts fordifferent granulated pharmaceutical formula. Due to thestraightforward measurement of relative density, which
can be determined using Pycnometer and simple weightmeasurement with known volume, in addition to the volume change during compaction makes this approach attractive especially from the practical point of view.
Similarly, Yohannes et al. (2015) used relative densitychange in investigating compaction behavior of powders
with different particle size distributions focusing on therole of fines. They report that fines do not affect the compressibility and strength past initial rearrangement state
and therefore fines can be disregarded in computationalmodeling using discrete particle approach. These recent
studies show the utility of bulk density of powder compaction. However, limitations of macroscopic relative
density of powder compaction exist as it lacks an ability
to predict or indicate local defects such as crack or capping. It is simply because bulk density is a lumped macroscopic measurement and does not explain underlying
mechanism of compaction. This can be complemented bymeasuring density distribution in compacts.
In addition, density or density distribution of compact
often used as measurement to validate compaction model.

36

Fig. 3

Apparent density distribution measured from cylindrical compacts of microcrystalline cellulose under
14 MPa when pressed from top. Recreated with thepermission from Huang and Puri (2000). Copyright:(2000) Taylor & Francis, Inc.

For example, Huang and Puri (2000) used density in validation of Adachi-Oka model implemented in a finite element approach (Fig. 3), Borowski (2011) Kadiri et al. (2005)
Michrafy et al. (2002), and Sinka et al. (2003) used density in validation of Drucker-Prager model solved with finite element models, and Aydin et al. (1994) and Michrafy
et al. (2004) used density in validation of non-linear elastic problem with finite element model by successive incremental solution. In addition, Kong and Lannutti (2000)
used density to validate discrete element model.
To this end, determination of density distribution of
powder compacts is an important characterization that isnecessary in fundamental understanding of powder compaction. Density of compacts can be measured with instrumented compaction unit, which can precisely trace
the change of height, therefore density can be determinedusing known weight of charge. This approach is used invery early studies such as Train (1956) and recent studies
such as Michrafy et al. (2003). As one of the earliest efforts of using density distribution in powder compaction
study, Train (1956) demonstrated that density of compact
is not homogeneous and neighbor of a stationary lower
punch wall has higher density compared to upper central
region. This difference of density is more pronouncedwith unlubricated die and attributes to defects of compacts such as capping. Therefore, the relationship between
density distribution and defects of compact has beenviewed as a quantitative predictor of compact quality.
One of major contribution to the developing density
gradient during compaction is die-wall friction. This relationship was investigated by Michrafy et al. (2003). This
study shows that friction between wall and die decreases

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while compaction progressed for different types of microcrystalline cellulose powders (PH101, PH102, and PH105)
by determining the friction coefficient between compact
and die wall using the transmission ratio (applied pressure/transmitted pressure), the transfer ratio (radial pressure/axial pressure) and the aspect ratio (height/diameterof tablet). Small caveat of this measurement is the use of
published value for the transfer ratio based on the stressmeasured at the upper punch instead of mean axial stressat a respective depth. In addition, Michrafy et al. (2003)’s
study also shows that measured relative densities arelower than both the Heckel equation, which is an exponential relation between applied stress by a punch and relative density, and a predictive model accounting for the
exponentially decaying mean axial stress inside a compact away from the surface, on which a stress is applied.
The gap between the measured value and predicted valuesof Heckel equation increases when the depth increases.
This observation suggests that stress decreases exponentially inside a powder compact during compaction. However, quantitative contribution of die wall friction to thecompaction behavior remains to be investigated since relative densities are experimentally determined only for
unlubricated case.
Alternatively, a destructive indentation hardness can beused in determining compact density. However, indentation hardness test is prone to breaking brittle compacts
during experiments. In addition, these methods cannot
characterize horizontal variability of compact densities,
which arises from the interactions with a die wall. Due tosuch limitations in regard to the accurate characterizationof density distributions, research on this particular subject
has been limited in spite of the importance of quantitative
measurement of powder compacts’ density distribution as
fundamental metrics of powder compaction.
Development of non-destructive (or non-invasive) methods has enabled determining the density of compacts
without mechanical disruptions of the test subject. X-ray
tomography (including computed tomography, namelyCT, or computerized axial tomography, namely CAT),
Nuclear magnetic resonance (NMR), Magnetic Resonance Imaging (MRI), and Ultrasound are most widely
accepted methods in non-destructive testing of materials(Banhart, 2008).
For example, the development of X-ray tomography has
been utilized in quantitative density distribution analysis
of compacts. Density distribution of alumina compact
was determined using X-ray imaging tracing embedded
lead balls (Aydin et al., 1994). Finite element model developed using their measurement demonstrated the contribution of the wall friction to the density distribution.
However, there were a substantial disagreement between
predicted and measured higher versus lower density regions that are attributed to assumed non-homogeneous in-ternal angle of friction throughout the assembly. This
heterogeneity of internal angle of friction of powder assembly is yet to be substantiated. Kong and Lannutti,(2000) utilized X-ray Computed Tomography (CT) to determine variances of density in alumina compacts especially for early compaction stages. To trace compaction,
they used tungsten marker, which may have interferedduring compaction. Richard et al. (2003) utilized X-ray
micro-tomography to investigate packing and compactionof glass beads based on void ratio. Although this is not a
direct measurement of compact density, it can be usefulapproach applicable to other types of particulate materials, whose density can be determined with about 10 μm
resolution. Sinka et al. (2004) explored the use of X-ray
CT scan in measurement of density distribution in microcrystalline cellulose compacts and showed spatial density
distribution can be determined quantitatively. Busignies
et al. (2006) also measured a density profile in microcrystalline cellulose compacts using X-ray tomography to
study the heterogeneous density of compacts and to investigate a correlation between mechanical properties ofcompacts and compact densities. However, X-ray tomography does not show clear density gradient inside binary
mixture compacts. However, this study reports preferential localization of a specific ingredient implying the origin of difference between mechanical properties of whole
compact versus mechanical properties of compact surface, such as indentation hardness. It should be noted thatthe root cause of such preferential localization of an ingredient is not clarified, which can be a result of less thanideal mixing or segregation during deposition of mixture
in a die. Miguélez-Morán et al. (2009) used X-ray CT tocharacterize roller-compacted ribbons of microcrystalline
cellulose showing higher compression in the middle thanedges. In addition, they developed correlation between
the relative density and localized indentation that follows
a log-normal relationship.
Nuclear magnetic resonance (NMR) also has been usedin studying density distribution of compacts as shown in
Djemai and Sinka (2006) but NMR is not as widely usedin this field. Caveats of NMR and X-ray based tomography techniques still exists that they are time-consuming
and costly. Additional point to X-ray is that the measurement depends on the chemical composition of the test
subject and a specific calibration for subject material isrequired for different formulations, which can be less thanstraightforward for industries using multi-ingredients. In
another effort, Garino et al. (1995) utilized MRI to determine density variations in powder compacts. In addition,
Glass and Ewsuk (1995) used ultrasound to determine relative density of alumina compact. Akseli et al. (2011) usedboth ultrasound and X-ray CT to determine density distribution of ribbon compacted microcrystalline cellulose ininvestigation of mechanical properties. They showed that37

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both methods have resolution to distinguish spatially distributed density in compacts. More interestingly, corre­
lation between ultrasonic measurement and tablet’smechanical strength (tensile strength) was found; which
was used in other materials whose mechanical propertiesare difficult to measure. It should be noted that the listed
non-destructive characterization techniques are still confined by limitations regarding resolutions high enough todistinguish individual particles.

3.2 Quality: Mechanical defects
Some of major issues of compacts include defects including crack, capping, and uneven surface (Fig. 4).
These defects are more qualitative in nature and often examined with a binary designation i.e., pass or fail. In manycases, local irregularity evolves into defective compacts,
it is not straightforward to predict or prevent powder compacts’ mechanical defects without fundamental understanding of powder compaction taking the stochasticity ofparticulate materials into consideration. This is especiallyproblematic during development of products since it ishard to know the risk of defective products a priori andhigher defect rate is found after they are fully formulated.
Then this situation requires an extensive investigation relying on trial-and-error approach to identify optimal (orworking) recipe of process parameters even without finding out actual causes. As an effort to mitigate this issue,
Akseli et al. (2014) presents a relationship between capping and process parameters including formulations. In
addition, Kuppuswamy et al. (2001)’s study is an attempt
to predict the risk of capping by indentation hardness andobserve crack development. Kuppuswamy et al. (2001) investigated detection of formula prone to capping using indentation hardness test attributing capping to the residual
die-wall pressure introducing microscopic cracks, whichis hypothesized to develop into cracks, therefore capping
due to insufficient plasticity. This study suggests that theplasticity of particles is related to localized defect development. This idea is in line with that too much elastic rebound after or during unloading may introduce local

Fig. 438

Typical compacts with no or common mechanical defects including capping, delamination, and crack.

defects or failure of compacts.
There have been studies to understand where these defects originate. In studying a relationship between
smoothness of surface and mechanical characteristics ofcompacts, Narayan and Hancock (2003) suggests thatbrittle bulk powder may indicate their propensity to bevulnerable to cracks or surface defects. It should be notedthat Narayan and Hancock (2003)’s study seems to refer
to bulk powder’s brittleness or ductility to their failure
behavior when compressed. In addition, this study did notinvestigate the underlying mechanism of how brittlenessof compact can be related to cracks or surface defects.
However, authors suggest roles of particle size distribution, shape, and bonding interactions in initial packing. In
addition, this study also implicitly connects brittleness orductility of compact (or powder mass under compaction)
to the same properties of particles, which would be interesting to find out how these are correlated. Recent advancement of experimental methods, which can determine
mechanical properties of sub-micrometer sized test specimen, definitely allow quantitative investigation of particles (Govedarica et al., 2012; Karamchandani et al., 2016).
Related to this subject, Ashby and Hallam (1986) and
Ashby and Sammis (1990) report theoretical investigation
on how microcracks develop and induce failure in solids.
Since powder compacts usually bear defects including
microcracks, application of such theories to powder compacts may assist quantitative prediction and control of
powder compact’s mechanical integrity. More fundamental origin of compact defects, excessive pores, were reported by Shinohara et al. (1999), in which the voids
created from the dimples of alumina particles, grainboundaries, prominently larger particles are proposed as
major culprits. Correlation between those major causes
and defects in the compacts were reported based on observatory investigation and it is expected that modelingapproach that can included such information at particle
scale and simulate larger scale compaction behavior willfurther substantiate this hypothesized origin of defects. In
addition, considering alumina particle surface being
smooth and spherical, the effect of asperity of more irregular particles on defective compact would be interesting.
In a more recent study, Garner et al. (2014) investigatedthe mechanism of crack development during ejection of
microcrystalline compacts using Druker-Prager model
implemented with a finite element method. Their study
suggests that microcracks develop during unloading as amechanism of relieving the radial wall stress. Also surface cracks develops when a compact is exiting die due toabrupt decreases of stresses following the elastic expansion whose rate can be controlled by adding tapper at theend of die. Recent advancement of nano-technology andcomputational power is expected to allow linking approaches taken by Garner et al. (2014) with the observa-

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tion of Shinohara et al. (1999), which will elucidate theorigin and mechanism of defects development during
powder compaction process.

3.3 Quality: Strength
Mechanical strength of powder compacts is one ofmost widely used quantitative metrics (Bonaccorsi andProverbio, 2006; Hayashi et al., 2013; Krycer et al., 1983a,
1983b; Mazel et al., 2014; Perez-Gandarillas et al., 2015;
Russell et al., 2015; Yohannes et al., 2015). Compact’s
mechanical strength is influenced by many parameters including temperature (Rouèche et al., 2006) or propertiesof particle including particle size (Narayan and Hancock,2005) in case of tensile strength. Finer particles tend toresult in stronger compacts owing to higher surface area
(Alderborn and Nystrom, 1996). However, it is notablethat the degree of this increase in compact strength varies
for different materials.
Compact strength is largely determined by compression
pressure (Fig. 5). A positive correlation between these
two are empirically known (Sinka et al., 2009), but exact
relationship is yet to be elucidated as there are many additional parameters to determine exact compact strength
such as loading rate, amount of charge (therefore the dimension of final compact), etc. A basic approach of determining mechanical strength of medicinal tablets can befound in United States Pharmacopeial Convention (2011).
Detailed procedure of mechanical tests are reviewed by
Amorós et al. (2008) and Podczeck, 2012. Mazel et al.
(2014)’s study is notable since they attempted to link practical engineering strength test to more rigorous Drucker-­
Prager yield criteria.

Fig. 5

Typical mechanical tests to determine strength of compacts. Loading in the major axis direction is used indetermining compressive strength of compacts (left),
whereas loading in the minor (or radial) axis direction
is used in determining tensile strength (right). The latter is often referred as a diametral test.

Sinka et al. (2009)’s study lists processing parameters
affecting eventual strength of compact. Notably, they suggested that the compaction behavior and ultimate prop­
erties of compacts originates from particle’s properties.
However, Sinka et al. (2009)’s have reported such causal
relations in a qualitative way. It is simply because of thedaunting numbers of intertwined parameters affecting thecompaction process. To be quantitative includes identifying dominant parameters and how large their contribution
is and finding out how compaction is happening including
the die-wall and loading-rate effects, and possibly mechanics at a scale, in which individual particles are scrutinized. Some specific aspect of processing parameter, suchas temperature, has been specifically shown to influencemechanical properties of pharmaceutical compacts Yorkand Pilpel (1973). Nonetheless, this generally accepted conjecture on causal relationship between particle’s properties
and compacts’ properties have been actively investigated.
For example, Zhang et al. (2014)’s study demonstrated an
implicit effects of ingredients on a biomass pellets. Similar result is shown for binders commonly used by Zhang
et al. (2003) or major ingredients of pharmaceutical compacts (Akseli, 2009; Pandeya and Puri, 2012).
Furthermore, relationships between surface area ofparticles and medicinal tablet’s tensile strength have beenstudied extensively (Fell and Newton, 1970; Jetzer, 1986;
Leuenberger, 1982; Riepma et al., 1990, 1991, 1992).
Particle’s morphology and ductility of compacts has beenreported by Galen and Zavaliangos (2005). Galen andZavaliangos (2005) examined the anisotropic strength ofcompacts and attributed the anisotropy especially in theductile powder compacts to the microscopic architectural
structure of deformed particles after the compaction. For
example, mechanism is different in each case. For ductile
powders, compaction involves the flattening of particles
which results in greater strength in the transverse direction due to increased crack deflection that results fromgreater particle overlap. For the brittle powder, it is proposed that particle fragmentation occurring along thecompaction direction weakens strength in the transverse
direction. Actual quantification of such a claim was notsubstantiated but it should be possible now due to the development of nano-technology and microscopy. This idea
is investigated further by Wang (2007).
In addition, particle size or particle size distribution’s
effect on a compaction process have been actively studied(Jiang et al., 2001; Kaerger et al., 2004; Koynov et al.,2013; Morsi et al., 2006). Effect of particle size on compact strength has been well documented (Khan and Pilpel,
1986; McKenna and McCafferty, 1982). In addition, effectof particle shape on a powder system has been investigated in detail, as well (de Bono and McDowell, 2016;
Mittal et al., 2001; Yi et al., 2002; Yi et al., 2001). However, study on the relationship between particle shape and39

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compact’s properties is scarce, which is thought to be because of the difficulty in quantification of particle shape.
Studies on discrete element model require a quantitativeand direct description of particle morphology and thisneed has prompted recent studies on quantitative descriptions of particles (Amberger et al., 2012; Coetzee, 2016;
Favier et al., 1999; Garcia et al., 2009; Kruggel-Emden etal., 2008; Křupka and Říha, 2015; Li et al., 2015; Rickman
et al., 2016; Wu et al., 2016; Zhao and Wang, 2016).
One of notable properties that has not been studied
from this perspective include actual mechanical properties of individual particle and evolution of contacts between particles during compaction in relation to bulk
responses of powder en masse during compaction ormechanical properties of resulting compacts. Recently,
there have been attempts to investigate mechanical properties of particle with powder compaction using nano-­indentation as a mean to determine particle’s mechanicalproperty (Cao et al., 2010; Govedarica et al., 2012). Furthermore Portnikov and Kalman (2015) investigated theeffect of temperature on elastic properties individual particles and showed that the effective modulus of elasticity
decreases while temperature of particles increases. Unfortunately, this approach is not widely performed probably due to the lack of a clear understanding on how one
can use such information in predicting or controllingcompaction operations.
In addition, one of the challenges of quantitative
characterization of mechanical strength of compact is its
stochastic nature originating from stochasticity of particle
sizes and shape of powder system. Such distributed natureof mechanical strength of compacts can be characterizedusing Weibull distribution as shown in Phani (1987).
Portnikov and Kalman (2014) established a mathematicalmodel describing the distribution of the effective modulus
of elasticity of individual particles including salt, potash,
granulated gold nano particles (GNP), zirconium spheres,and glass spheres. Russell et al. (2015)’s study demonstrates how stochastic strength of particle system can be

Fig. 640

quantitatively investigated using synthetic zeolitic granules whose D50 is 1.75 mm.
There also have been studies on the evolution of coordination number during powder compaction (German,2014). Nonetheless, knowledge on how coordination number and overall interaction between particles contributes
powder compacts’ mechanical integrity and responses isgenerally lacking. It is expected that efforts to elucidate
laws governing the evolution of mechanical properties
powder compacts from particle scale based on individual
particles and interparticle mechanics will expand leveraging those recent developments.

3.4 Quality: Hardness
The indentation hardness has been very widely used inindustry as a measure of the mechanical property of powder compacts owing to its straightforward and speedy
procedure. Accordingly, many studies used the indentation hardness as a characterization method of mechanicalproperties of compacts (Bonaccorsi and Proverbio, 2006;
Chtourou et al., 2002; Kuppuswamy et al., 2001; Tehrani
et al., 2010) as well as an evaluation metrics of a compaction process (Chtourou et al., 2002).
Although the indentation hardness is not a fundamental
mechanical experiment procedure, relationships between
indentation hardness and mechanical properties have been
actively developed and widely accepted. Few examples ofsuch studies can be found in Gent (1958), Gubicza et al.
(1996), Oliver and Pharr (1992), and Pavlina and Tyne
(2008). It should be noted that, these relationships are
specific to tip geometry of an indentor (Fig. 6) and subjected compacts especially in relation to the surface
roughness (Laitinen et al., 2013). Furthermore, it is moredifficult to establish relationships between hardness measurements and fundamental mechanical properties of materials with inelastic or stochastic mechanical responses(Ma et al., 2009) or when the indentation tip material andsubject material have comparable mechanical stiffness

Commonly used indentation hardness tip shapes shown from the front (top row) and the shape of indentation shown from the top (bottom row). Indentation hardness is measured by the depth of indentation
when subject surface is indented by a tip with specific geometry with a pre-set force.

Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48(Skrinjar et al., 2005). In other words, it is required for anindentation tip to be much harder than subjected powder
compacts with large enough dimension compared to theindentation to ensure an accurate hardness measurement,
which is not always straightforward to implement especially for novel materials or materials with less known
surface characteristics or mechanical properties.
Indentation hardness has been recognized as a usefuland promising tool in mechanical characterization of particles with the recent development in micro-indentation
tester, especially for the advancement of Atomic ForceMicroscopy (AFM) (Cao et al., 2010; Masterson and Cao,
2008; Meier et al., 2009; Willems et al., 1993) or nano-­indenter (Gibson et al., 2015; Govedarica et al., 2012;
Taylor et al., 2004). In general, a caution should be exercised when fundamental mechanical properties, such asYoung’s modulus and Poisson’s ratio when the simplest
elasticity is assumed, are estimated from indentation
hardness test results. For example, Govedarica et al.
(2012) used Sneddon (1965)’s equations which assumes
semi-infinite half-space of subject material compared tothe indentor geometry. Taylor et al. (2004) used Duncan-­Hewitt and Weatherly (1989)’s study based on a semi-­
empirical fracture mechanics to estimate brittleness basedon the ratio of the hardness and elastic modulus based on
the indentation geometry of a conventional Vickers Hardness test. Gibson et al. (2015) used a finite element modeling to estimate Young’s modulus and Poisson’s ratio using
a nanoindentation tests on micron-sized silica (SiO2) particles. It should be noted that Gibson et al. (2015) assumed
non-slip contact, which should be further substantiated asassumptions on contact may have a significant effect especially at the microscopic scales (Briscoe and Adams,
1987; Skrinjar et al., 2005; Thornton and Ning, 1998).
Despite above mentioned caveats, there have been efforts focused on the development of relationship between
particle’s properties and powder system’s behavior during
compaction or properties of compact. Most notably, Caoet al. (2010) performed AFM nanoindentation on individual pharmaceutical particles, e.g., acetaminophen crystallites, ibuprofen crystallites, sodium acetate trihydrate,
microcrystalline cellulose, ascorbic acid, tartaric acid andthe hydropropyl methylcellulose. They used film sample
for hydropropyl methylcellulose whereas other materials
were tested as crystalline particles. Elastic modulus wasdetermined based on the measured stiffness and contact
area following the Hertzian contact law. Correlating particle hardness and powder compact hardness, which isalso determined by AFM nanoindentation, a quantitative
relationship between particle hardness with powder compaction performance is obtained. It should be noted thatthe powder compaction performance has been determinedbased on quantitative metrics of mechanical properties ofcompacts. It is clear that there exist apparent cluster of in-gredients resulting compacts with poor or good mechanical quality in relation to the hardness of particles. Cao etal. (2010) study is notable as the first attempt to correlate
individual particle’s mechanical properties with the macroscopic powder compacts’ properties. There are plentiful
opportunities for further investigation such as appropriate
contact mechanics theory for AFM nanoindentation on
crystalline particles. For example, due to AFM nano-­indentor’s small geometry and unknown asperity of contact
surfaces of subject materials, Hertzian contact mechanics
may not be appropriate to estimate mechanical propertiesof particles (Carrillo and Dobrynin, 2012; Johnson, 1987;
Kendall, 1987). In addition, degree of crystallinity and effects of crystallographic properties, as Cao et al. (2010)
and Willems et al. (1993) assumed for the dominant faceof the crystal to play a major role on powder compaction,
are yet to be fully understood as actively investigatedfor cellulose (Pinto, 1999; French and Johnson, 2009;
Glasser et al., 2012). Further studies will produce quantitative correlation between macroscopic powder compacts
mechanical performance and individual particle’s properties.
Development of AFM also opened other in situ characterization of powder compacts as shown in Miguélez-­
Morán et al. (2009). In addition, it should be noted thatparticle interactions have been widely studied using AFM(Cleaver and Looi, 2007; Dobryden et al., 2013; M.
Götzinger and Peukert, 2004; Martin Götzinger andPeukert, 2003; Jones et al., 2003; Kani et al., 2007; Tanaka
et al., 2008; Tsukada et al., 2004) but mechanical properties of a single particle has not been studied as actively.
This is probably due to the mechanism of AFM’s measurement, which relies on the interactive force between
AFM cantilever tip and subject surface including mechanical contact force, van der Waals force, chemicalbonding, electrostatic force, magnetic forces, and so forth.

3.5 Quality: Rattler test
Rattler test is originally used to test paving bricks. It
was adopted to determine strength of metallurgic powder
compacts (Blumenthal et al., 1997). Typical rattler test
designates number and size of compacts to be tumbled inside a chamber of predetermined dimension. After a specific number of revolutions at a specified speed, the lossof weight including samples, which are broken during theprocedure, is recorded and compared to the original
weight of intact samples. Similar approach is used tomeasure of how green compact maintains its mechanicalintegrity. Such methods include friability test for pharmaceutical tablets, which is described in (USP29, 2016) anddurability test for biomass compacts (Fig. 7), which is described in ASABE Standard S269.4 (2002).
Some studies used durability to control or predict the41

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Fig. 7

Durability tester (left) fabricated in accordance with
the ASABE Standard S269.4 (2002) and a friability
tester (right) fabricated in accordance with US Pharmacopia standard.

quality of biomass compacts (Kaliyan and Morey, 2009;
Karamchandani, 2013; Wilson, 2010). Similar approaches
were used for pharmaceutical compacts (Vinogradov andKomarova, 1962) using the fundamental idea of friability
and not the standardized friability test (Krycer et al.,1983a; Sinka et al., 2009).
Since the friability test procedure’s simple concept andits ability to mimic conditions of handling of compacts,
durability or friability provide good quantitative measuresof mechanical property of compacts. However, the tertiary nature of the test procedure makes this test to behighly dependent on the dimension of the test device,
speed of the rotation, and the size of compacts in one test.
Furthermore, the accuracy of this test method is not fully
examined. The procedure of durability or friability test is
well established and the number of samples and repetitionis as well defined. Such dependency of test procedures
and equipment for biomass compacts are studied byTemmerman et al. (2006). No similar study is reported forfriability of smaller and lighter powder compacts. Furthermore, establishing correlative relationship between
friability and other mechanical properties may be of interest to overcome the caveat of this type of test.

4. Summary
As reviewed in this article, studies on powder mechanics
research have shown the feasibility of developing predictive
relationships between mechanical properties and quality
metrics of few types of powders. For example, pharmaceutical tablets are formed using powder ingredients suchas filler, binder, disintegrant, and active pharmaceuticalingredient, either by dry blending the ingredients or wet
granulation of the powder mix followed by compaction.
Pandeya and Puri (2012)’s study reports that a set of mechanical properties of powder en masse, such as springback index, compression index, and bulk modulus, were
found most suitable for predicting diametral strength, in-42

dentation hardness, and friability of compacts. This wasfound by developing predictive correlations for tablet
quality vs. dry and granulated powder’s mechanical properties that were determined using a medium pressure
flexible boundary cubical triaxial tester and mechanicalquality metrics of compacts.
In another study, similar approach was applied to biomass pelleting: Karamchandani et al. (2015) demonstrated
that ground biomass pellet’s quality can be related to mechanical properties of ground biomass. Especially, thisstudy showed that the fundamental mechanical properties
at low pressure range of compaction is capable of predicting properties of compacts produced at much higher pressure, which is thought to be due to the importance of earlystage of compaction including rearrangement and elastic
responses. This informs the significant importance ofmeasuring fundamental mechanical properties at low
pressure range as it is much more practical in industrial
laboratory than the measurement at higher pressure range,i.e., over 1 MPa.

5. Looking ahead: The role of microscaleinteractions
The above-mentioned two studies demonstrate that thequality of compacts can be rationally predicted based on
the characterization of feed materials’ mechanical properties. The key to these studies is employing quantitative
approaches both in the measurements of quality metrics
and characterization of feed materials. This quantitative
approach is the first step toward systematically establishing optimal compaction processes to produce compacts
with optimal quality; avoiding overshooting production
operation parameters as can be the case when using trial-­
and-error. To achieve this ultimate goal, one needs to understand particle properties’ role in and contribution to
the mechanical behavior of powder during densification.
The ability to predict behavior of powder during compaction based on mechanical characteristics of individual
particles and their interactions will provide a means to
implement quality control by design that takes the characteristics of the feedstock into account.
An analytical model, which describes how macroscopic
compaction mechanics evolves from mechanics of the underlying scales, is absent largely because of the lack of anadequate method to examine mechanics at the scale whereindividual particles can be scrutinized. The compaction
process evolves towards different scales of scrutiny, i.e.,
microscale (single particle, particle-particle interactions),
mesoscale (secondary and tertiary particle structures),and macroscale (bulk powder system). Accordingly, a
research question can be posed as how do a single particle’s properties and particle-particle interactions govern

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the evolution of compaction in powders (and powder mixtures) at different scales? For example, the change in formulation with similar (or same) base material is shown toresult in different characteristics of compacts (Souriou etal., 2009). Overall, recent advances in nano-technology,
computational capacity and modeling approach, such as adiscrete element modeling (DEM), have been actively explored in studies of many aspects of powder processing.
We believe that similar multi-scale approaches can be
successfully employed in addressing this question on the
powder compaction. In a multi-scale framework, properties of single particle and particle-particle interaction
characterized using Nano or MicroElectroMechanical
Systems (NEMS/MEMS) devices form the foundation ofa mesoscopic and macroscopic governing principles ofpowder compaction. Ultimately, such characterization are
hypothesized to be linked to fundamental mechanicalproperties of bulk particulate materials during compaction. This can be done using a fundamental tester such asa true Cubical Triaxial Tester (CTT) that is free of theconfounding effect of samples’ boundary conditions.
Through this approach, we believe that it is possible toformulate rational principles of compaction of powder en
masse based on the governing laws at multiple scales employing the mechanical properties of underlying scales,
and to develop and validate a multi-scale and multi-­
physics computational model of the evolution of compacts.
We envision that this approach will enable systematicallyengineering the optimization of powder compaction processes so that one can quantitatively predict and control acompact’s mechanical quality properties through the design and characterization of the powders that are used as
raw materials of powder processing.

References
Akseli I., Nano/micro/meso scale interactions in mechanicsof pharmaceutical solid dosage forms, PhD Thesis,(2009). Retrieved from http://adsabs.harvard.edu/abs/2009
PhDT........18A.
Akseli I., Iyer S., Lee H.P., Cuitiño A.M., A quantitative correlation of the effect of density distributions in roller-­compacted ribbons on the mechanical properties of tablets
using ultrasonics and X-ray tomography, AAPS PharmSciTech, 12 (2011) 834–853. DOI:10.1208/s12249-011-9640-z.
Akseli I., Stecuła A., He X., Ladyzhynsky, N., Quantitative
correlation of the effect of process conditions on the capping tendencies of tablet formulations, J. Pharm. Sci., 103(2014) 1652–1663. DOI:10.1002/jps.23951.
Alderborn G., Nystrom C., Pharmaceutical powder compaction
technology, Marcel Dekker, Inc., 1996. Retrieved fromhttp://www.diva-portal.org/smash/record.jsf?pid=diva2:
87597.
Amberger S., Friedl M., Goniva C., Pirker S., Kloss C., Approx-

imation of objects by spheres for multisphere simulations in
DEM, In ECCOMAS 2012, 2012.
Amorós J.L., Cantavella V., Jarque J.C., Felíu C., Green strength
testing of pressed compacts: An analysis of the different
methods, J. Eur. Ceram. Soc., 28 (2008) 701–710. DOI:10.
1016/j.jeurceramsoc.2007.09.040.
ASABE Standard S269.4, A., Cubes, pellets, and crumbles-­definitions and methods for determining density, durability,
and moisture content, (No. S269. 4).
Ashby M.F., Hallam S.D. (Née C., The failure of brittle solids
containing small cracks under compressive stress states,
Acta Metall., 34 (1986) 497–510. DOI:10.1016/0001-6160(86)90086-6.
Ashby M.F., Sammis C.G., The damage mechanics of brittle
solids in compression, Pure Appl. Geophys., 133 (1990)
489–521. DOI:10.1007/BF00878002.
ASTM Standard, and D18.24 Committee, Standard test methods
for determining loose and tapped bulk densities of powders
using a graduated cylinder (Standard No. D7481-09) (p. 4),
West Conshohocken, PA: ASTM International, 2009. DOI:
10.1520/D7481-09
ASTM Standard, and D18.24 Committee, Standard test method
for measuring bulk density values of powders and otherbulk solids as function of compressive stress (Standard No.
D6683-14) (p. 5), West Conshohocken, PA: ASTM International, 2014. DOI: 10.1520/D6683-14
Aydin İ., Briscoe B.J., Şanlitürk K.Y., Density distributions
during the compaction of alumina powders: A comparisonof a computational prediction with experiment, Comput.
Mater. Sci., 3 (1994) 55–68.
Azami A.R., Khoei A.R., 3D computational modeling of powder compaction processes using a three-invariant hardening
cap plasticity model, Finite Elem. Anal. Des., 42 (2006)
792–807. DOI:10.1016/j.finel.2006.01.011.
Banhart J., Advanced tomographic methods in materials
research and engineering, OUP Oxford, 2008.
Bell T.A., Challenges in the scale-up of particulate processes—
an industrial perspective, Powder Technol., 150 (2005)
60–71. DOI:10.1016/j.powtec.2004.11.023.
Blumenthal W.R., Sheinberg H., Bingert S.A., Compaction
issues in powder metallurgy, MRS Bull., 22 (1997) 29–33.
DOI:10.1557/S0883769400034710.
Bonaccorsi L., Proverbio E., Powder compaction effect on
foaming behavior of uni-axial pressed PM precursors, Adv.
Eng. Mater., 8 (2006) 864–869. DOI:10.1002/adem.
200600082.
Borowski G., Effect of friction for density distribution in die
compaction of powders, Postępy Nauki Tech., 10 (2011)
159–168.
Bortzmeyer D., Modelling ceramic powder compaction, Powder
Technol., 70 (1992) 131–139. DOI:10.1016/0032-5910(92)85040-3.
Briscoe B.J., Adams M.J. (Eds.), Tribology in particulate technology, A. Hilger, Bristol, England; Philadelphia, 1987.
Busignies V., Leclerc B., Porion P., Evesque P., Couarraze G.,
Tchoreloff P., Quantitative measurements of localized density variations in cylindrical tablets using X-ray microtomography, Eur. J. Pharm. Biopharm., 64 (2006) 38–50.

43

Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48

DOI:10.1016/j.ejpb.2006.02.007.
Cao X., Morganti M., Hancock B.C., Masterson V.M., Correlating particle hardness with powder compaction performance,
J. Pharm. Sci., 99 (2010) 4307–4316. DOI:10.1002/jps.22130.
Carrillo J.-M.Y., Dobrynin A.V., Contact mechanics ofnanoparticles, Langmuir, 28 (2012) 10881–10890. DOI:10.
1021/la301657c.
Castellanos A., Valverde J.M., Quintanilla M.A.S., Physics ofcompaction of fine cohesive particles, Phys. Rev. Lett., 94(2005) 075501. DOI:10.1103/PhysRevLett.94.075501.
Chtourou H., Guillot M., Gakwaya A., Modeling of the metal
powder compaction process using the cap model. Part I.
Experimental material characterization and validation, Int.
J. Solids Struct., 39 (2002) 1059–1075. DOI:10.1016/S00207683(01)00255-4.
Cleaver J.A.S., Looi L., AFM study of adhesion between polystyrene particles;—The influence of relative humidity andapplied load, Powder Technol., 174 (2007) 34–37.
DOI:10.1016/j.powtec.2006.10.017.
Coetzee C.J., Calibration of the discrete element method and theeffect of particle shape, Powder Technol., 297 (2016) 50–70.
DOI:10.1016/j.powtec.2016.04.003.
Cooper A.R., Eaton L.E., Compaction Behavior of Several
Ceramic Powders, J. Am. Ceram. Soc., 45 (1962) 97–101.
DOI:10.1111/j.1151-2916.1962.tb11092.x.
Cunningham J.C., Sinka I.C., Zavaliangos A., Analysis of tablet
compaction. I. Characterization of mechanical behavior of
powder and powder/tooling friction, J. Pharm. Sci., 93(2004) 2022–2039. DOI:10.1002/jps.20110.
de Bono J.P., McDowell G.R., Investigating the effects of particle shape on normal compression and overconsolidation
using DEM, Granul. Matter, 18 (2016). DOI:10.1007/
s10035-016-0605-5.
de Gennes P.-G., Granular matter: a tentative view, Rev. Mod.
Phys., 71 (1999) S374. DOI:10.1103/RevModPhys.71.S374;
J1: RMP.
Dimaggio F.L., Sandler I.S., Material model for granular soils, J.
Eng. Mech., (1971). Retrieved from/view.aspx?id=124117.
Djemai A., Sinka I.C., NMR imaging of density distributions intablets, Int. J. Pharm., 319 (2006) 55–62. DOI:10.1016/j.
ijpharm.2006.03.049.
Dobryden I., Yang X., Almqvist N., Holmgren A., Weber H.,
An atomic force microscopy study of the interaction
between magnetite particles: The effect of Ca2+ ions andpH, Powder Technol., 233 (2013) 116–122. DOI:10.1016/
j.powtec.2012.09.003.
Duncan-Hewitt W.C., Weatherly G.C., Evaluating the hardness,
Young’s modulus and fracture toughness of some pharmaceutical crystals using microindentation techniques, J.
Mater. Sci. Lett., 8 (1989) 1350–1352.
Ennis B.J., Green J., Davies R., The legacy of neglect in the
United-States, Chem. Eng. Prog., 90 (1994) 32–43.
Favier J.F., Abbaspour-Fard M.H., Kremmer M., Raji A.O.,
Shape representation of axi-symmetrical, non-sphericalparticles in discrete element simulation using multi-element
model particles, Eng. Comput., 16 (1999) 467–480.
Fayed M.E., Otten L., Handbook of powder science and technology, Van Nostrand Reinhold Company Inc, New York,44

NY 10020, 1984.
Fell J.T., Newton J.M., The prediction of the tensile strength oftablets, J. Pharm. Pharmacol., 22 (1970) 247–248.
DOI:10.1111/j.2042-7158.1970.tb08513.x.
French A.D., Johnson G.P., Cellulose and the twofold screw
axis: modeling and experimental arguments, Cellulose, 16(2009) 959–973. DOI:10.1007/s10570-009-9347-4.
Galen S., Zavaliangos A., Strength anisotropy in cold compacted ductile and brittle powders, Acta Mater., 53 (2005)
4801–4815. DOI:10.1016/j.actamat.2005.06.023.
Garcia X., Xiang J., Latham J.-P., Harrison J.P., A clusteredoverlapping sphere algorithm to represent real particles indiscrete element modelling, Géotechnique, 59 (2009) 779–
784. DOI:10.1680/geot.8.T.037.
Garino T., Mahoney M., Readey M., Ewsuk K., Gieske J.,
Stoker G., Min S., Characterization techniques to validate
models of density variations in pressed powder compacts(No. SAND--95-1615C; CONF-951033--12), Sandia
National Labs., Albuquerque, NM (United States).
Retrieved from http://www.osti.gov/scitech/biblio/100203.
Garner S., Ruiz E., Strong J., Zavaliangos A., Mechanisms ofcrack formation in die compacted powders during unloading and ejection: An experimental and modeling comparison between standard straight and tapered dies, Powder
Technol., 264 (2014) 114–127. DOI:10.1016/j.powtec.2014.
04.086.
Gent A.N., On the relation between indentation hardness andYoung’s modulus, Rubber Chem. Technol., 31 (1958) 896–
906. DOI:10.5254/1.3542351.
German R.M., Coordination number changes during powder
densification, Powder Technol., 253 (2014) 368–376.
DOI:10.1016/j.powtec.2013.12.006.
Gibson R.F., Jang H.-K., Simkhada S., Yu Q., Kim H.-I., Suhr J.,
Use of nanoindentation, finite element simulations, and a
combined experimental/numerical approach to characterize
elastic moduli of individual porous silica particles, Part.
Sci. Technol., 33 (2015) 213–218. DOI:10.1080/02726351.20
14.950396.
Glass S.J., Ewsuk K.G., Ceramic powder compaction (No.
SAND--95-1804C; CONF-9511208--1), Sandia National
Labs., Albuquerque, NM (United States). Retrieved fromhttp://www.osti.gov/energycitations/product.biblio.jsp?osti_
id=234692.
Glasser W.G., Atalla R.H., Blackwell J., Malcolm Brown R.,
Burchard W., French A.D., Klemm D.O., Nishiyama Y.,
About the structure of cellulose: debating the Lindman
hypothesis, Cellulose, 19 (2012) 589–598. DOI:10.1007/
s10570-012-9691-7.
Götzinger M., Peukert W., Dispersive forces of particle–surface
interactions: direct AFM measurements and modelling,
Powder Technol., 130 (2003) 102–109. DOI:10.1016/S00325910(02)00234-6.
Götzinger M., Peukert W., Particle adhesion force distributions
on rough surfaces, Langmuir, 20 (2004) 5298–5303.
DOI:10.1021/la049914f.
Govedarica B., Ilić I., Šibanc R., Dreu R., Srčič S., The use of
single particle mechanical properties for predicting thecompressibility of pharmaceutical materials, Powder Tech-Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48

nol., 225 (2012) 43–51. DOI:10.1016/j.powtec.2012.03.030.
Gubicza J., Juhász A., Tasnádi P., Arató P., Vörös G., Determination of the hardness and elastic modulus from continuous
vickers indentation testing, J. Mater. Sci., 31 (1996) 3109–
3114. DOI:10.1007/BF00354655.
Hayashi Y., Miura T., Shimada T., Onuki Y., Obata Y., Takayama
K., Prediction of tablet characteristics from residual stress
distribution estimated by the finite element method, J.
Pharm. Sci., 102 (2013) 3678–3686. DOI:10.1002/jps.23675.
Huang L., Puri V.M., A three-dimensional finite element model
for powder compaction: Time-dependent formulation andvalidation, Part. Sci. Technol., 18 (2000) 257–274.
DOI:10.1080/02726350008906838.
Ilkka J., Paronen P., Prediction of the compression behaviour of
powder mixtures by the Heckel equation, Int. J. Pharm., 94(1993) 181–187. DOI:10.1016/0378-5173(93)90022-8.
Jetzer W.E., Compaction characteristics of binary mixtures, Int.
J. Pharm., 31 (1986) 201–207. DOI:10.1016/0378-5173(86)90154-7.
Jiang G., Daehn G.S., Wagoner R.H., Inclusion particle size
effects on the cyclic compaction of powder composites, Scr.
Mater., 44 (2001) 1117–1123.
Johnson K.L., Contact mechanics, Cambridge university press,
1987.
Jones R., Pollock H.M., Geldart D., Verlinden A., Inter-particle
forces in cohesive powders studied by AFM: effects of relative humidity, particle size and wall adhesion, Powder
Technol., 132 (2003) 196–210. DOI:10.1016/S0032-5910(03)00072-X.
Kadiri M.S., Michrafy A., Dodds J.A., Pharmaceutical powders
compaction: Experimental and numerical analysis of thedensity distribution, Powder Technol., 157 (2005) 176–182.
DOI:10.1016/j.powtec.2005.05.025.
Kaerger J.S., Edge S., Price R., Influence of particle size andshape on flowability and compactibility of binary mixturesof paracetamol and microcrystalline cellulose, Eur. J.
Pharm. Sci., 22 (2004) 173–179. DOI:10.1016/j.ejps.2004.
03.005.
Kaliyan N., Morey V.R., Factors affecting strength and durability of densified biomass products, Biomass Bioenergy, 33(2009) 337–359. DOI:10.1016/j.biombioe.2008.08.005.
Kani T., Tamonoki M., Suzuki T., Tsukada M., Kamiya H.,
Influence of surface-adhered nanoparticles and nanoporous
structure on particle–particle interaction of silica, Powder
Technol., 176 (2007) 99–107. DOI:10.1016/j.powtec.2007.
02.006.
Karamchandani A., Predictive relationships for quality assessment of densified biomass using fundamental mechanicalproperties of ground corn stover, switchgrass, and willow(master of science dissertation), Pennsylvania State University, 2013.
Karamchandani A., Yi H., Puri V.M., Fundamental mechanicalproperties of ground switchgrass for quality assessment ofpellets, Powder Technol., 283 (2015) 48–56. DOI:10.1016/
j.powtec.2015.04.069.
Karamchandani A., Yi H., Puri V.M., Single particle mechanical characterization of ground switchgrass in air dry andwet states using a microextensometer, Powder Technol., 301(2016) 568–574. DOI:10.1016/j.powtec.2016.06.041.
Kawakita K., Lüdde K.-H., Some considerations on powder
compression equations, Powder Technol., 4 (1971) 61–68.
DOI:10.1016/0032-5910(71)80001-3.
Kendall K., Relevance of contact mechanics to powders-­
elasticity, friction and agglomerate strength, Tribol. Part.
Technol., (1987) 110–122.
Khan F., Pilpel N., The effect of particle size and moisture on
the tensile strength of microcrystalline cellulose powder,
Powder Technol., 48 (1986) 145–150.
Kong C.M., Lannutti J.J., Localized densification during thecompaction of alumina granules: The Stage I—II transition,
J. Am. Ceram. Soc., 83 (2000) 685–690.
Koynov A., Romanski F., Cuitiño A.M., Effects of particle size
disparity on the compaction behavior of binary mixtures ofpharmaceutical powders, Powder Technol., 236 (2013) 5–11.
DOI:10.1016/j.powtec.2012.07.046.
Kruggel-Emden H., Rickelt S., Wirtz S., Scherer V., A study on
the validity of the multi-sphere Discrete Element Method,
Powder Technol., 188 (2008) 153–165. DOI:10.1016/j.powtec.
2008.04.037.
Křupka A., Říha K., Minimal prerequisites for measuring
two-dimensional contour roundness in a particle classification context, Powder Technol., 284 (2015) 486–495.
DOI:10.1016/j.powtec.2015.07.018.
Krycer I., Pope D.G., Hersey J.A., An evaluation of tablet binding agents part I. Solution binders, Powder Technol., 34(1983a) 39–51. DOI:10.1016/0032-5910(83)87026-0.
Krycer I., Pope D.G., Hersey J.A., An evaluation of tablet binding agents part II. Pressure binders, Powder Technol., 34(1983b) 53–56. DOI:10.1016/0032-5910(83)87027-2.
Kuppuswamy R., Anderson S.R., Augsburger L.L., Hoag S.W.,
Estimation of capping incidence by indentation fracture
tests, Aaps PharmSci, 3 (2001) 54–65.
Laitinen O., Bauer K., Niinimäki J., Peuker U.A., Validity of the
Rumpf and the Rabinovich adhesion force models for alumina substrates with nanoscale roughness, Powder Technol.,
246 (2013) 545–552. DOI:10.1016/j.powtec.2013.05.051.
Leuenberger H., The compressibility and compactibility of
powder systems, Int. J. Pharm., 12 (1982) 41–55. DOI:10.
1016/0378-5173(82)90132-6.
Li C.-Q., Xu W.-J., Meng Q.-S., Multi-sphere approximation ofreal particles for DEM simulation based on a modified
greedy heuristic algorithm, Powder Technol., 286 (2015)
478–487. DOI:10.1016/j.powtec.2015.08.026.
Ma D., Ong C.W., Zhang T., An Instrumented Indentation
Method for Young’s Modulus Measurement with Accuracy
Estimation, Exp. Mech., 49 (2009) 719–729. DOI:10.1007/
s11340-008-9177-6.
Masterson V.M., Cao X., Evaluating particle hardness of pharmaceutical solids using AFM nanoindentation, Int. J.
Pharm., 362 (2008) 163–171. DOI:10.1016/j.ijpharm.2008.
06.015.
Mazel V., Diarra H., Busignies V., Tchoreloff P., Comparison ofdifferent failure tests for pharmaceutical tablets: Applicability of the Drucker–Prager failure criterion, Int. J. Pharm.,
470 (2014) 63–69. DOI:10.1016/j.ijpharm.2014.05.006.
McKenna A., McCafferty D.F., Effect of particle size on the45

Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48

compaction mechanism and tensile strength of tablets, J.
Pharm. Pharmacol., 34 (1982) 347–351. DOI:10.1111/j.20427158.1982.tb04727.x.
Meier M., John E., Wieckhusen D., Wirth W., Peukert W., Influence of mechanical properties on impact fracture: Prediction of the milling behaviour of pharmaceutical powders bynanoindentation, Powder Technol., 188 (2009) 301–313.
DOI:10.1016/j.powtec.2008.05.009.
Merrow E.W., Linking R&D to problems experienced in solids
processing (product page No. P-7034), Rand Corporation.
Retrieved from http://www.rand.org/pubs/papers/P7034.
html.
Merrow E.W., Estimating startup times for solids-processing
plants, Chem. Eng., 95 (1988) 89–89.
Michrafy A., Dodds J.A., Kadiri M.S., Wall friction in the compaction of pharmaceutical powders: measurement andeffect on the density distribution, Powder Technol., 148(2004) 53–55. DOI:10.1016/j.powtec.2004.09.021.
Michrafy A., Kadiri M.S., Dodds J.A., Wall friction and its
effects on the density distribution in the compaction ofpharmaceutical excipients, Chem. Eng. Res. Des., 81 (2003)
946–952. DOI:10.1205/026387603322482185.
Michrafy A., Ringenbacher D., Tchoreloff P., Modelling thecompaction behaviour of powders: application to pharmaceutical powders, Powder Technol., 127 (2002) 257–266.
Miguélez-Morán A.M., Wu C.-Y., Dong H., Seville J.P.K., Characterisation of density distributions in roller-compacted
ribbons using micro-indentation and X-ray micro-computed
tomography, Eur. J. Pharm. Biopharm., 72 (2009) 173–182.
DOI:10.1016/j.ejpb.2008.12.005.
Mittal B., Yi H., Puri V.M., McNitt A.S., Mancino C.F., Measurement of bulk mechanical properties and modeling theload-response of rootzone sands. Part 2: Effect of moisture
on continuous sand mixtures, Part. Sci. Technol., 19 (2001)
369–386. DOI:10.1080/02726350290057895.
Morsi K., Shinde S., Olevsky E.A., Effect of nickel particle sizeon the compaction behavior of rotator mixed and mechanically alloyed nickel and aluminum powders, Mater. Sci.
Eng. A, 426 (2006) 283–288. DOI:10.1016/j.msea.2006.04.
027.
Narayan P., Hancock B.C., The relationship between the particle
properties, mechanical behavior, and surface roughness ofsome pharmaceutical excipient compacts, Mater. Sci. Eng.
A, 355 (2003) 24–36; 24.
Narayan P., Hancock B.C., The influence of particle size on thesurface roughness of pharmaceutical excipient compacts,
Mater. Sci. Eng. A, 407 (2005) 226–233; 226.
Oliver W.C., Pharr G.M., An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments, J. Mater. Res., 7(1992) 1564–1583. DOI:10.1557/JMR.1992.1564.
Pandeya A., Puri V.M., Relationships between tablet physicalquality parameters and granulated powder properties: feasibility study, Part. Sci. Technol., 30 (2012) 482–496.
Pavlina E.J., Tyne C.J.V., Correlation of yield strength and tensile strength with hardness for steels, J. Mater. Eng. Perform., 17 (2008) 888–893. DOI:10.1007/s11665-008-9225-5.
Perez-Gandarillas L., Mazor A., Souriou D., Lecoq O.,

46

Michrafy A., Compaction behaviour of dry granulated
binary mixtures, Powder Technol., 285 (2015) 62–67.
DOI:10.1016/j.powtec.2015.05.003.
Phani K.K., A new modified Weibull distribution function, J.
Am. Ceram. Soc., 70 (1987) C-182. DOI:10.1111/j.11512916.1987.tb05719.x.
Pinto B.M., Carbohydrates and their derivatives including
tannins, cellulose, and related lignins, in: Barton S.D.,
Nakanishi K., Meth-Cohn O. (Eds.) , Comprehensive natural products chemistry, Volume 3, Pergamon, Oxford, 1999.,
Elsevier, 1999.
Podczeck F., Methods for the practical determination of themechanical strength of tablets—From empiricism to science, Int. J. Pharm., 436 (2012) 214–232. DOI:10.1016/j.
ijpharm.2012.06.059.
Portnikov D., Kalman H., Determination of elastic properties ofparticles using single particle compression test, Powder
Technol., 268 (2014) 244–252. DOI:10.1016/j.powtec.2014.
08.011.
Portnikov D., Kalman H., The effect of temperature on elasticalproperties of individual particles, presented at the 8th international conference for conveying and handling of particulate solids, Tel-Aviv, Israel, 2015.
Richard P., Philippe P., Barbe F., Bourl S. Hane, Thibault X.,
Bideau D., Analysis by X-ray microtomography of a granular packing undergoing compaction, Phys. Rev. E, 68 (2003)
020301.
Rickman D., Lohn-Wiley B., Knicely J., Hannan B., Probabilistic solid form determined from 2D shape measurement,
Powder Technol., 291 (2016) 466–472. DOI:10.1016/j.
powtec.2015.10.044.
Riepma K.A., Lerk C.F., de Boer A.H., Bolhuis G.K., Kussendrager
K.D., Consolidation and compaction of powder mixtures. I.
Binary mixtures of same particle size fractions of different
types of crystalline lactose, Int. J. Pharm., 66 (1990) 47–52.
DOI:10.1016/0378-5173(90)90383-F.
Riepma K.A., Veenstra J., de Boer A.H., Bolhuis G.K., Zuurman
K., Lerk C.F., Vromans H., Consolidation and compactionof powder mixtures: II. Binary mixtures of different particle size fractions of α-lactose monohydrate, Int. J. Pharm.,
76 (1991) 9–15. DOI:10.1016/0378-5173(91)90338-O.
Riepma K.A., Zuurman K., Bolhuis G.K., de Boer A.H., Lerk
C.F., Consolidation and compaction of powder mixtures:
III. Binary mixtures of different particle size fractions ofdifferent types of crystalline lactose, Int. J. Pharm., 85(1992) 121–128. DOI:10.1016/0378-5173(92)90141-N.
Rouèche E., Serris E., Thomas G., Périer-Camby L., Influenceof temperature on the compaction of an organic powder andthe mechanical strength of tablets, Powder Technol., 162(2006) 138–144. DOI:10.1016/j.powtec.2005.12.005.
Russell A., Schmelzer J., Müller P., Krüger M., Tomas J.,
Mechanical properties and failure probability of compact
agglomerates, Powder Technol., 286 (2015) 546–556.
DOI:10.1016/j.powtec.2015.08.045.
Schofield A., Wroth P., Critical state soil mechanics, McGrawHill, London, New York etc., 1968.
Shinohara N., Okumiya M., Hotta T., Nakahira K., Naito M.,
Uematsu K., Formation mechanisms of processing defects

Hojae Yi et al. / KONA Powder and Particle Journal No. 35 (2018) 32–48

and their relevance to the strength in alumina ceramics
made by powder compaction process, J. Mater. Sci., 34(1999) 4271–4277. DOI:10.1023/A:1004611105281.
Sinka I., Cunningham J., Zavaliangos A., The effect of wall
friction in the compaction of pharmaceutical tablets withcurved faces: a validation study of the Drucker–Prager Cap
model, Powder Technol., 133 (2003) 33–43. DOI:10.1016/
S0032-5910(03)00094-9.
Sinka I.C., Burch S.F., Tweed J.H., Cunningham J.C., Measurement of density variations in tablets using X-ray computed
tomography, Int. J. Pharm., 271 (2004) 215–224. DOI:10.
1016/j.ijpharm.2003.11.022.
Sinka I.C., Motazedian F., Cocks A.C.F., Pitt K.G., The effect ofprocessing parameters on pharmaceutical tablet properties,
Powder Technol., 189 (2009) 276–284. DOI:10.1016/j.
powtec.2008.04.020.
Skrinjar O., Larsson P.-L., Storåkers B., Local contact compliance relations at compaction of composite powders, J. Appl.
Mech., 74 (2005) 164–168. DOI:10.1115/1.2165240.
Sneddon I.N., The relation between load and penetration in theaxisymmetric Boussinesq problem for a punch of arbitrary
profile, Int. J. Eng. Sci., 3 (1965) 47–57. DOI:10.1016/00207225(65)90019-4.
Souriou D., Goeuriot P., Bonnefoy O., Thomas G., Doré F.,
Influence of the formulation of an alumina powder on compaction, Powder Technol., 190 (2009) 152–159. DOI:10.
1016/j.powtec.2008.04.074.
Tanaka M., Komagata M., Tsukada M., Kamiya H., Evaluationof the particle–particle interactions in a toner by colloid
probe AFM, Powder Technol., 183 (2008) 273–281.
DOI:10.1016/j.powtec.2007.07.039.
Taylor L.J., Papadopoulos D.G., Dunn P.J., Bentham A.C.,
Mitchell J.C., Snowden M.J., Mechanical characterisationof powders using nanoindentation, Powder Technol., 143–
144 (2004) 179–185. DOI:10.1016/j.powtec.2004.04.012.
Tehrani M., Al-Haik M.S., Dyck C., Khraishi T., A practicalroute for the characterization of zinc powder compacts withthe aid of instrumented indentation and scratch tests, Mater.
Sci. Eng. A, 528 (2010) 494–499. DOI:10.1016/j.msea.
2010.09.033.
Temmerman M., Rabier F., Jensen P.D., Hartmann H., Böhm T.,
Comparative study of durability test methods for pellets
and briquettes, Biomass Bioenergy, 30 (2006) 964–972.
DOI:10.1016/j.biombioe.2006.06.008.
Thornton C., Ning Z., A theoretical model for the stick/bounce
behaviour of adhesive, elastic-plastic spheres, Powder
Technol., 99 (1998) 154–162. DOI:10.1016/S0032-5910(98)00099-0.
Train D., An investigation into the compaction of powders, J.
Pharm. Pharmacol., 8 (1956) 745–761.
Tsukada M., Irie R., Yonemochi Y., Noda R., Kamiya H.,
Watanabe W., Kauppinen E.I., Adhesion force measurementof a DPI size pharmaceutical particle by colloid probe
atomic force microscopy, Powder Technol., 141 (2004) 262–
269. DOI:10.1016/j.powtec.2004.03.008.
United States Pharmacopeial Convention, USP35 NF30, 2012:
U. S. Pharmacopoeia National Formulary, United States

Pharmacopeial, 2011.
USP29, General Chapters: <1216> Tablet friability, USP29NF24, United States Pharmacopeial Convention, Retrieved
July 14, 2016, from http://www.pharmacopeia.cn/v29240/
usp29nf24s0_c1216.html.
Vinogradov G.A., Komarova L.M., Investigation of the friability of metal powders in connection with rolling conditions,Sov. Powder Metall. Met. Ceram., 1 (1962) 17–22.
DOI:10.1007/BF01135025.
Wang W., Towards an improved understanding of strengthand anisotropy of cold compacted powder, PhD Thesis,(2007). Retrieved from http://adsabs.harvard.edu/abs/2007
PhDT.......106W.
Willems G., Celis J.-P., Lambrechts P., Braem M., Vanherle G.,
Hardness and Young’s modulus determined by nanoindentation technique of filler particles of dental restorative
materials compared with human enamel, J. Biomed. Mater.
Res., 27 (1993) 747–755.
Wilson T.O., Factors affecting wood pellet durability (Master of
Science Dissertation), The Pennsylvania State University,
2010.
Wu Y., Wu X., Yao L., Brunel M., Coëtmellec S., Lebrun D.,
Gréhan G., Cen K., 3D boundary line measurement of
irregular particle with digital holography, Powder Technol.,
295 (2016) 96–103. DOI:10.1016/j.powtec.2015.11.061.
Yi H., Mittal B., Puri V.M., Li F., Mancino C.F., Measurement ofbulk mechanical properties and modeling the load-­responseof rootzone sands. Part 1: Round and angular monosize andbinary mixtures, Part. Sci. Technol., 19 (2001) 145–173.
Yi H., Mittal B., Puri V.M., MCNitt A.S., Mancino C.F.,
Measurement of bulk mechanical properties and modelingthe load response of rootzone sands. Part 3: Effect oforganics and moisture content on continuous sand mixtures, Part. Sci. Technol., 20 (2002) 125–157. DOI:10.1080/
02726350215335.
Yohannes B., Gonzalez M., Abebe A., Sprockel O., Nikfar F.,
Kang S., Cuitino A.M., The role of fine particles on compaction and tensile strength of pharmaceutical powders,
Powder Technol., 274 (2015) 372–378. DOI:10.1016/j.
powtec.2015.01.035.
York P., Pilpel N., The tensile strength and compression
behaviour of lactose, four fatty acids, and their mixturesin relation to tableting., J. Pharm. Pharmacol., 25 (1973)
Suppl:1P-11P.
Zhang L., Xu C.C., Lei H., Wang H.L., Ning T.T., Hao W., Hu
X.D., Effects of addition of various ingredients during pelletizing on physical characteristics of green tea residue pellets, Appl. Eng. Agric., 30 (2014) 49–53. DOI:10.13031/
aea.30.10160.
Zhang Y., Law Y., Chakrabarti S., Physical properties and compact analysis of commonly used direct compression binders, AAPS PharmSciTech, 4 (2003) 489–499. DOI:10.1208/
pt040462.
Zhao B., Wang J., 3D quantitative shape analysis on form,
roundness, and compactness with μCT, Powder Technol.,
291 (2016) 262–275. DOI:10.1016/j.powtec.2015.12.029.

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Author’s short biography
Hojae Yi
Dr. Hojae Yi is a Research Associate at the Pennsylvania State University. He earned
his Ph.D. degree from the Seoul National University in 2003. He joined the Pennsylvania
State University as a visiting scholar in 2000 for one year where he started his researcheson powder mechanics. Dr. Hojae Yi has been working at Department of Agricultural andBiological Engineering of the Pennsylvania State University since 2006. His current research interests include experimental studies and mathematical modeling on compaction
and flow behavior of particulate materials with emphasis on the multiscale approach.

Anuranjan Pandeya
Dr. Anuranjan Pandeya is currently working at Scientific and Digital Systems Delhi,
consulting and catering Food/Pharmaceutical research organizations and industry for
their instrumentation need. He is also guest faculty at Birla Institute of Technology,
Mesra (India). Dr. Pandeya has been involved in research in the area of powder flow andcompaction, particle characterization, and milling behavior of powders, presently andearlier as Ph.D. and post-doctoral scholar at Penn State University. Dr. Pandeya has
co-authored several papers in the area of powder and particulate science. He also presented paper and gave technical talks to industries and research institutes.

Apoorva Karamchandani
Apoorva Karamchandani is a doctoral candidate in the department of Agricultural
and Biological Engineering at Pennsylvania State University, working under the supervision of distinguished professor Virendra Puri. She received a B. Tech. degree in agricultural engineering from G.B. Pant University, Uttrakhand, India and a master’s degreefrom Penn State in the same discipline. At Penn State, Apoorva is working in the field of
powder mechanics including physical and mechanical characterization of particulates
and compaction. Her research explores the ways to improve the efficiency of biomass
densification process by developing a fundamental framework to predict end productquality.

Virendra M. Puri
Dr. Virendra M. Puri, University Distinguished Professor, has researched in the fieldof powder mechanics for over three decades. He served as Acting Director of the Particulate Materials Center and co-authored numerous publications. He is co-inventor andholder of patents in powder flow, deposition, and compaction and has copyright for
multi-purpose computational software on powder processing. Dr. Puri has served on
several Editorial Boards, International Advisory Boards, and Chairpersons of bulk
solids-related publications and professional activities. Professor Puri is member of
KONA North Americas Editorial Board and Co-Editor-in-Chief of Particulate Scienceand Technology. He has received several teaching and research awards.

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KONA Powder and Particle Journal No. 35 (2018) 49–65/Doi:10.14356/kona.2018011

Review Paper

Direct Permeation of Nanoparticles
Across Cell Membrane: A Review †Hideya Nakamura* and Satoru Watano
1

Department of Chemical Engineering, Osaka Prefecture University, Japan

Abstract
Nanoparticles have attracted much attention as a key material for new biomedical and pharmaceuticalapplications. For success in these applications, the nanoparticles are required to translocate across the cell
membrane and to reach to inside of the cell. Among several translocation pathways of nanoparticles, the direct
permeation pathway has a great advantage due to its high delivery efficacy. However, despite many research
efforts, key properties and factors for driving the direct permeation of nanoparticle and its underlying
mechanisms are far from being understood. In this article, experimental and computational studies regarding thedirect permeation of nanoparticles across a cell membrane will be reviewed. Firstly, experimental studies on thenanoparticle-cell interactions, where spontaneous direct permeation of nanoparticles was observed, are reviewed.
From the experimental studies, potential key physico-chemical properties of nanoparticles for their direct
permeation are discussed. Secondly, physical methods such as electroporation and sonoporation for delivering
nanoparticles into cells are reviewed. Current status of technologies for facilitating the direct permeation of
nanoparticle is presented. Finally, we review molecular dynamics simulation studies and present the latest
findings on the underlying molecular mechanisms of the direct permeation of nanoparticle.
Keywords: nanoparticle, direct permeation, cell membrane, non-endocytosis, physical delivery, computer
simulation

1. Introduction
With recent advances in nanoscience and nanotechnology, nanoparticles (NPs) have attracted much attention asa key material for the new biomedical and pharmaceuticalapplications. The NPs, defined as materials with at least
one dimension in the size range smaller than 100 nm, exhibit significant unique properties that can be useful forthe biomedical and pharmaceutical applications. The
highly tunable size, structure, and surface properties of
NPs at a nanometer scale can be exploited as carrier platforms for drug-, gene-, macromolecule-deliveries (Ranaet al., 2012; Shao et al., 2015; Wilczewska et al., 2012).
The fluorescence properties of semiconductor NPs can beused for bioimaging (Ekimov et al., 1985; Luo et al., 2012;
Weller et al., 1986; Yuan et al., 2013). The unique plasmonic properties of metal NPs can be exploited for simultaneous imaging and photothermal therapies (Dreaden etal., 2011; Huang et al., 2006; Jaque et al., 2014; Kennedy†
1*Received 5 April 2017; Accepted 20 June 2017
J-STAGE Advance published online 30 July 2017
1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan
Corresponding author: Hideya Nakamura;
E-mail: hnakamura@chemeng.osakafu-u.ac.jp
TEL: +81-72-254-9451 FAX: +81-72-254-9451

et al., 2011; Périgo et al., 2015; Xiong et al., 2014). The
magnetic properties of metal and metal-oxide NPs can beutilized for magnetic resonance imaging and magnetic
fluid hyperthermia treatment for cancer therapy (Fortin etal., 2007; Veiseh et al., 2011). Meanwhile, many experimental investigations suggest that use of NPs can cause
harmful effects: concerns about nanotoxicity have been
elicited. It has been reported that NPs can cause cell
membrane disruptions and significant increase in cell
death at cellular level (Kahru and Ivask, 2013; Pietroiusti,
2012). NPs can also cause negative physiological effects
such as inflammatory and immunological responses, resulting in adverse effects even at in vivo levels (Kim etal., 2013).
For success in the biomedical and pharmaceutical applications (i.e., for maximizing the NPs’ beneficial effects
and minimizing their potential adverse effects), the NPs
are required to be transported into the cell and localized
at targeted cellular component without any damage to thecell. When the NPs are transported into the cell, the mostcritical barrier is the cell membrane. The cell membrane
is a fundamental biological barrier and mainly composedof a lipid bilayer with membrane proteins. Transport ofextracellular matters into a cell is selectively regulated by
the cell membrane. Therefore, a key issue to realize the

Copyright © 2018 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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potential applications of NPs is development of a technology that can control the NP translocation across the cell
membrane. To develop such a technology, understandingof mechanisms of the NP translocation across a cell membrane is necessary.
Through many research efforts up to now, it has beenfound that translocation of NPs across a cell membrane
can be classified into two major pathways: endocytosis
and direct permeation (Beddoes et al., 2015; Ding andMa, 2015; Qu et al., 2013). Fig. 1 shows a schematic illustration of the NP translocation pathways. Endocytosis is
an intrinsic cellular function to take up extracellular substances into the cell. In the endocytosis, a small portion of
the cell membrane deforms and wraps extracellular NPs.
Subsequently, the cell membrane pinches off and an endocytic vesicle which encloses the NPs is formed. The NPs
enclosed by the endocytic vesicle are finally transported
into the cell, leading to the NP translocation across thecell membrane. The direct permeation is defined as a
non-endocytic translocation pathway. In this pathway,
NPs permeates across the cell membrane without confinement of the NPs by the endocytic vesicles, leading to direct delivery of the NPs into the cell.
According to the reviews of experimental investigations (Beddoes et al., 2015; Qu et al., 2013; Zhu et al.,2013), it has been recognized that the endocytosis is a major translocation pathway when NPs interact with thecells, while the direct permeation is a minor one. However, the endocytosis possesses a significant drawback forthe biomedical and pharmaceutical applications. The endocytosed NPs cannot often escape from the endocytic
vesicles and cannot reach to the targeted cellular component even after translocating across the cell membrane(Ding and Ma, 2015). This leads to low delivery efficacy
that is a critical issue for the biomedical and pharmaceutical applications. By contrast, in the direct permeation,

Fig. 150

NPs reach to inside of the cell without entrapment of NPs
by vesicles, resulting in high delivery efficacy. This is agreat advantage over the endocytosis, while the direct
permeation is a rare event as compared to the endocytosis. To overcome this issue and facilitate the direct permeation, some physical methods, where external forces suchas electric field or ultrasound are applied to the cell, arepromising (Al-Dosari and Gao, 2009; Mehierhumbert andGuy, 2005). The physical methods were originally developed for gene transfer into cells. Recently, these are exploited for the direct delivery of NPs (Carrasco et al.,2016; Huang et al., 2014; Kawano et al., 2006; Kim et al.,2011; Lin et al., 2009; Wang et al., 2014; Yang et al., 2011;
Zu et al., 2014).
Understanding of the mechanism of the direct permeation of NPs across the cell membrane with or without
external forces can greatly contribute to realize an ideal
NP delivery method with both high delivery efficacy andless damage to the cell. The direct permeation of NPs canbe controlled by two potential key factors: physico-­chemical properties of the NPs; nature and conditions of
the external forces. However, despite many research efforts, it is still very challenging to control the direct
permeation of NPs across a cell membrane. The key
properties and factors for controlling the NP direct permeation and its underlying mechanisms are far frombeing understood. This lack of understanding hinders thedevelopment of new technology which can control the NP
direct permeation, and also hinders the design of NPs
with suitable properties for their applications.
In this article, the existing studies regarding the direct
permeation of NPs across the cell membrane will be reviewed. Our aim is to present (i) potential key physico-­chemical properties of NPs for their direct permeation; (ii)potential physical methods for facilitating the NP direct
permeation; (iii) current understanding of the molecularTranslocation pathways of nanoparticles across cell membrane. Reprinted with permission from Ref. (Quet al., 2013). Copyright: (2013) Future Science Group.

Hideya Nakamura et al. / KONA Powder and Particle Journal No. 35 (2018) 49–65

mechanisms of the NP direct permeation. Firstly, experimental studies on the nanoparticle-cell interactions,where the direct permeation of NPs without applying external forces were reported, will be reviewed. From thisreview, we will extract insights into key physico-chemical
properties of NPs for their direct permeation. Subsequently, potential physical methods such as electroporation and sonoporation for facilitating the NP direct
permeation are reviewed. Finally, computational studies
will also be reviewed, and the latest findings on the underlying molecular mechanisms of the NP direct permeation will be presented.

2. Key physico-chemical properties of NPs fortheir direct permeation: insights fromexperimental studies
There are many factors that can affect the NP-cell
membrane interactions. Among the potential key factors,
physico-chemical properties of the NPs (e.g., size, shape,charge, hydrophobicity/hydrophilicity, surface chemistry,and others) can highly influence the NP-cell membraneinteractions. Although there are some reviews on the key
NP properties for the NP-cell membrane interactions including adhesion, endocytosis, and membrane disruption(Beddoes et al., 2015; Qu et al., 2013; Verma and Stellacci,
2010; Zhu et al., 2013), the potential key properties for the
NP direct permeation have not been reviewed. Herein, we
have surveyed numerous experimental studies and will discuss the potential key physico-chemical properties for theirdirect permeation across cell membranes. In this section,
we will only focus on the NP direct permeation without
applying external forces, i.e., passive permeation of NPs.
Table 1 shows a summary of experimental studies inwhich the direct permeation of NPs across a cell membrane was observed. First of all, size of the NPs can be an
important factor. In general, for NPs in the size range
from several tens to hundreds of nanometers, endocytosis
is a major mode of NPs’ translocation across a cell membrane. However, for very small NPs, it can be consideredthat the endocytosis may be unfavorable. Yi et al. (2011)
calculated an energy change resulting from the membrane
wrapping of a single NP using a thermodynamic theory
proposed by Helfrich (1973). Their results exhibited that ahigher energy cost was required for the membrane wrapping of a smaller NP, while the membrane wrapping of alarger NP was energetically favorable. Thus, it is expectedthat for the smaller NPs the direct permeation can be favorable (Ding and Ma, 2015). In fact, as seen in Table 1,
the size of NPs that exhibited the direct permeation ismostly less than 20 nm. Van Lehn et al. (2013) showedthat even with very tiny decrease in the NP size from
5.8 nm to 2.4 nm, amount of NPs entering into cells by

the direct permeation significantly increased. Jiang et al.
(2015) also reported that the uptake amount of NPs
through the direct permeation showed significant dependence on the NP size within a small range of 2 to 6 nm.
Although there is no general consensus yet, the experimental results imply that for delivering NPs into cells by
the direct permeation mode, size of the NPs seems to be
desired to be smaller than 50 nm at least. NPs smaller
than 10 nm are more preferred.
The surface charge of NPs can also affect the NP-cell
membrane interactions. Many studies regarding NP-cellinteractions have pointed out that positively charged NPs
are more likely to provide significant influence on the cell
as compared to neutral or negatively charged NPs due toattractive electrostatic interactions with the negatively
charged cell membranes (Beddoes et al., 2015; Cho et al.,2009; Verma and Stellacci, 2010). However, as shown in
Table 1, the direct permeation of NPs has been observed
regardless of the surface charge of the NPs: i.e., the NPs’surface charge may not be determinant for the direct permeation. As seen in Table 1, a positively charged NP exhibited higher uptake through the direct penetration
pathway than neutral and negatively charged NPs (Arvizo
et al., 2010; Cho et al., 2009), while a negatively charged
NP exhibited the direct permeation (Jewell et al., 2011;
Lund et al., 2011; Van Lehn et al., 2013; Verma et al.,2008). Van Lehn et al. (2013) reported that the negatively
charged gold NP directly penetrates into the synthetic
vesicle without disruption of the vesicle membrane, whileother studies reported that positively charged NPs can induce disruption of cell membranes, leading to cell death(Hong et al., 2004, 2006). Jiang et al. (2015) observed thatthe zwitterionic NP was primarily uptaken by the direct
permeation, while the positively and negatively charged
NPs were primarily uptaken by endocytic pathways. In
summary, from the current experimental findings it canbe considered that the NPs’ surface charge is not likely to
be a determinant of the NP direct permeation.
Hydrophobicity/hydrophilicity of the NPs can be an
important property, because the cell membranes are composed of amphiphilic phospholipid molecules. Goda et al.
(2010) found that their synthesized NP composed of amphiphilic random copolymer exhibited the direct permeation, while another NP composed of solely hydrophilicpolymer failed to penetrate into the cell. Liu et al. (2013)
reported that temperature sensitive pNIPAM particles
with a size of 3 μm, which is much larger size, can directly penetrate into phospholipid vesicles and Hela cells.
They considered that this is due to phase transition of thepNIPAM from hydrophilic to hydrophobic at an elevatedtemperature above its phase transition criterion. Fromthese studies, amphiphilic nature seems to be favorable
for the direct permeation, although further investigations
are necessary.

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Table 1 Summary of experimental studies in which direct permeation of nanoparticles across cell membrane was observed.
Nanoparticle properties
Reference

Material

Surfacecharge/potential

Surface modification(i) 24 mV(ii) –1 mV(iii) –38 mV(iv) –2 mV• CP70 and
A2780
• BEC
• ASM

• Serum-free
DMEM• Serum-freeBEGM• (i) showed higher cellular uptake• (i) directly penetrated into cells
without endosomal trap(i) 20 mV(ii) –10 mV(iii) –4 mV

SK-BR-3• McCoy’s 5awith FBS(i) showed direct permeation

Arvizo et al.
(2010)Gold10

Cho et al.
(2009)Gold

18(i) PAA(ii) Citrate(iii) PVA

Geiser et al.
(2005)

Gold

25

—

―

―
Amine terminatedsurface

Amphiphilic
10–12
co-polymer

Hong et al. Cationic(2004, 2006) dendrimers
Jewell et al.
(2011)Gold

Comments

Size
(nm)

Ligand terminals
with:(i) cationic(ii) neutral(iii) anionic(iv) zwitterionic

Goda et al.
(2010)

Culture/dispersion
Types of cell/
mediumb andmembranea
presence/absenceof serumc

10–100• Porcine lung
RPMI1640 withmacrophage
FBS• Human RBC

NP directly penetrated into both ofcells

2 to 4 mV

HepG2

NP showed direct permeation

Positively
charged• Supported• NaCl aq.
DMPC bilayer • RPMI1640 and• KB and Rat2 DMEM with FBS5(i) Structured anionic
Negatively
and neutral ligands
B16-F0charged (both)(ii) Neutral ligands(i) 18 mV(ii) –7 mV(iii) –43 mV

Hela cell

DMEM with FBS

NP formed holes on membranes,
followed by direct permeation

Serum-freeDMEM(i) was uptaken by direct permeation,
whereas (ii) was uptaken by endocytosis

Serum-free
DMEM• NP uptake decreased in larger NP
size at (i) and (iii), whereas the uptake
increased in larger NP at (ii)
• (ii) was uptaken by direct permeation, while (i) and (iii) were uptaken
by endocytosis

Jiang et al.
(2015)Gold

2–6

Ligand terminals
with:(i) cationic(ii) zwitterionic(iii) anionic

Leroueil etal.
(2008)Gold

5

Alkylamine

Positively
chargedSupported
NaCl aq.
DMPC bilayer

NP formed holes on membrane,
followed by direct permeation

Leroueil etal.
(2008)

SiO2

50

Amine terminatedsurface

Positively
chargedSupported
NaCl aq.
DMPC bilayer

NP formed holes on membrane,
followed by direct permeation• DOPC and • Sucrose buffer
DOTAP GUV solution• Hela cell
• DMEM

Direct permeation was observed at anelevated temperature, inducing phasetransition of NP from hydrophilic tohydrophobic

Liu et al.
(2013)

pNIPAM2700――(i) Glucose ligands(i) Neutral
HCT-116, HT(ii) Glucose-glutathi- (ii) Negatively 29, LS154T,
one mixed ligands
chargedand SW640

Lund et al.
(2011)Gold

4

Mu et al.
(2012)

SiO2

14

―

―

Nativo et al.
(2008)

Gold

16

Coated with cell
penetrating peptides

Rothen-­Rutishauser
et al.
(2006)

Gold

25

Rothen-­Rutishauser
et al.
(2006)

TiO2(anatase)

20–30

52

DMEM

NPs directly penetrated into cell

A549

DMEM with FBS

NP directly penetrated into cell―

Hela cell

DMEM with FBS

NP directly penetrated into cell(i) BSA coated(ii) Cationic ligand―

Human RBC

RPMI1640 withhuman serum

Both of NPs directly penetrated
into cell――

Human RBC

RPMI1640 withhuman serum

NP directly penetrated into cell

Hideya Nakamura et al. / KONA Powder and Particle Journal No. 35 (2018) 49–65

Table 1 Summary of experimental studies in which direct permeation of nanoparticles across cell membrane was observed (contd.).
Nanoparticle properties
Reference

Material

Size
(nm)

Surface modification

Surfacecharge/potential

Culture/dispersion
Types of cell/
mediumb andmembranea
presence/absenceof serumc

Comments• NPs directly penetrated into cell
regardless of the size
• NPs smaller than 3 nm showedsignificant increase in uptake
amountVan Lehn
et al.
(2013)

Gold

2.4–
5.8

Anionic ligand

Negatively
chargedHela cell

Van Lehn
et al.
(2013)

Gold

2.2

Anionic and neutral
ligands

Negatively
chargedDOPC vesicle Sucrose aq.

• NPs directly penetrated into
vesicles without disruption of
bilayers

Veiseh et al.
Iron oxide(2011)

54

Coated with PEG
and poly-arginine―• C6• MCF7DMEM with FBS• NP directly penetrated into cell(i) –30 mV(ii) –30 mV

DC2.4

Serum-free
RPMI640(i) directly penetrated into cells
without membrane disruption,
whereas (ii) was trapped inendosomes―

Verma et al.
(2008)Gold5(i) Structured or(ii) unstructured
anionic and neutral
ligands

Wang et al.
(2012)

CdSe/ZnS
quantum
dots

8

Zwitterionic ligand―

Human RBC

Serum-free PBS

NP directly penetrated into cellYu et al.
(2007)

Silver―Designed peptide―

NIH 3T3

Serum-free
DMEM

NP directly penetrated into cellaCP70 and A2780: human ovarian cancer cell lines. BEC: human bronchial epithelial cell line. ASM: human airway smooth muscle cell line.
SK-BR-3: human breast cancer cell line. RBC: red blood cell. HepG2: human hepatocyte carcinoma cell line. KB: human epithelial cell line. Rat2:
rat fibroblasts cell line. B16-F0: mouse melanoma cell line. Hela cell: human cervical cancer cell line. DMPC: 1,2-dimyristoyl-sn-glycero-3-­
phosphocholine. DOPC: 1,2-dioleoyl-sn-glycero-3-phosphocholine. DOTAP: 1,2-dioleoyl-3-trimethylammonium-propane. GUV: giant unilamellar
vesicle. HCT-116, HT 29, LS154T, and SW640: human colorectal cell lines. A549: human lung epithelial cell line. C6: rat glioma cell line. MCF7:
human adenocarcinoma cell line. DC2.4: mouse dendritic cell line. NIH 3T3: mouse embryonic fibroblasts cell line.
b
DMEM: Dulbecco’s modified Eagle’s medium. BEGM: bronchial epithelial growth medium. RPMI1640: Roswell Park Memorial Institute 1640
medium. PBS: phosphate buffered saline.
c
FBS: fetal bovine serum.

Surface modification of NPs is effective to control the
NP direct permeation. As seen in Table 1, variety offunctional groups, ligands, biomolecules, polymers havebeen investigated as surface modifiers to facilitate the NP
direct penetration. It has also been found that not only
types of modifiers but also their structural arrangement
can be a key factor for the NP direct permeation. Vermaet al. (2008) synthesized two kinds of gold nanoparticles
coated by anionic and neutral ligands with same size,
same surface charge, and same ligand composition. One
particle was coated in an ordered striped arrangement ofanionic and neutral ligands, while the another particle
was coated with the same two ligands in a random arrangement. They found that the former particle with theordered arrangement can directly permeate across the cell
membrane without the membrane disruption, whereas thelatter particle with the random arrangement was mostly
trapped in endosomes by the endocytosis. A similar result
has been observed in Jewell et al. (2011). A possible explanation on this effect is that the ligand pattern in theordered arrangement may be assumed to be more rigid,
resulting in the direct permeation across the cell membrane (a more fluid layer) without the membrane disruption, which is similar mechanism for cell penetrating
peptides (Verma et al., 2008).
With regard to material of the NPs, it seems that gold is
likely to exhibit the direct permeation across cell membranes as compared to other materials (Table 1). However, we are speculating that this is not attributed to thematerial but to the size requirement for the direct permeation. Size of the gold NPs is generally highly tunable.
Synthesis of gold NPs smaller than 10 nm is facile ascompared to other materials. This may be a possible reason behind the specificity of gold shown in Table 1.
The membrane properties can be important factors for
the NP direct permeation. Moreover, external environmental conditions such as pH, osmotic pressure, ionicstrength, and presence of serum proteins can also be important factors. However, influences of these factors on
the NP direct permeation have not been investigated.

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3. Physical methods for NP direct delivery
For direct delivery of extracellular objects into the cell,some physical methods have been developed. The physical methods here refer to physical manipulations to improve the efficacy (rate and extent) of the delivery of
extracellular objects. Over the past two decades, the following physical methods have been developed for thegene delivery into cells: electroporation; sonoporation;laser irradiation; magnetofection; etc. (Al-Dosari andGao, 2009; Mehierhumbert and Guy, 2005). In thesemethods, the cells are exposed to each type of external
force fields, forming transient defects and pores in the cell
membrane. This results in temporal enhancement of permeability of the cell membrane, leading to direct permeation of extracellular objects in the surrounding medium
across the cell membrane. Meanwhile, an increase in cellular mortality can often be a great concern in these physical methods, if cells are subjected to the excess stressderived from the applied external forces. With regard to
the direct delivery of NPs, the electroporation (Huang etal., 2014; Kawano et al., 2006; Kim et al., 2011; Lin et al.,2009; Zu et al., 2014) and sonoporation (Carrasco et al.,2016; Wang et al., 2014; Yang et al., 2011) have been utilized in recent. In the following, these studies will be reviewed.
Electroporation is a technique where an electric field (ahigh intensity electric pulse) is applied to cells. The electric pulse can cause local destabilization of the cell membranes followed by electric field-induced transient pores,
resulting in the direct delivery of extracellular objects
into the cell. More details of fundamental physics of theelectroporation can be found in many literatures (e.g.,
Al-Dosari and Gao, 2009; Gehl, 2003; Kotnik et al., 2015;
Mehierhumbert and Guy, 2005). The electroporation
treatment is able to be applied to cells adhered on a culture dish as well as cells suspended in a culture media.
Several types of electrodes for both types of cells havebeen developed and commercially available.
Recently, the electroporation has been utilized fordelivery of NPs into cells. These NPs include DNA-­
conjugated gold NPs with 100 to 200 nm diameter (Huang
et al., 2014; Kawano et al., 2006; Zu et al., 2014), silver
NPs with 80 nm diameter (Lin et al., 2009), and hollow
metal NPs coated with mesoporous silica layer with
65 nm diameter (Kim et al., 2011). These experimental
studies demonstrated significant enhancement of delivery
efficacy of NPs with the electroporation treatment. Huang
et al. (2014) and Zu et al. (2014) showed that with the electroporation treatment the dominant NP delivery pathway
into cells shifted from the endocytosis to the direct permeation. It should be noted that even NPs with relatively
large particle size (ca. 100 nm) can be directly delivered
into cells through the direct permeation pathway using

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the electroporation. However, negative impacts on cellularfunctions such as viability and cell differentiation were
somewhat found after the electroporation (Huang et al.,2014; Kim et al., 2011). To overcome this disadvantage,some efforts have been reported. Zu et al. (2014) foundthat both of high delivery efficacy of DNA-conjugatedNPs and low cell mortality can be achieved by adding
pristine gold NPs as an additive. They considered that thisis due to decreasing the electric resistance of the medium
with highly conducting gold NPs, resulting in much lower
applied intensity required for the delivery. A new electroporation system integrated with microfluidic devices has
also been proposed (Geng and Lu, 2013; Wang et al.,2010). In the microfluidic electroporation system, a single
cell can be manipulated and be exposed to uniform electric field, as compared to conventional batch electroporation where electric pulse is applied to a bulk cellsuspension. This can provide a precise control of electricfield per single cell, leading to improvement on the delivery efficacy and less cellular damage.
In order to realize an ideal electroporation-assisted NP
delivery with high delivery efficacy and less cellular damage, it is necessary to understand the mechanism underlying the NP permeation in an electric field. In particular,role of NPs’ physico-chemical properties on the mechanism of the NP permeation remains subject of investigation. Elucidation of this mechanism can greatly contributeto optimize design of the NPs and operating conditions of
the electroporation (e.g., strength and frequency of theelectric current, number of electric pulses, and so on).
Sonoporation is a technique where an ultrasound is applied to a suspension of cells and microbubbles. It has
been considered that an acoustic cavitation is a central
cause of enhancement of the permeability of the cell
membranes. Acoustic cavitation generated by the ultrasound irradiation can cause generation, oscillation, andcollapse of active bubbles. This results in a release of associated mechanical stresses such as radiation force,
micro-streaming, micro-jets, or shock waves, leading to thetransient pore formation across adjacent cell membranes.
According to this mechanism, the ultrasound-mediatedbubbles are necessary for the sonoporation. In clinical applications, ultrasound contrast agents consisting of microbubbles stabilized by surface active molecules such asproteins, polymers, and lipids have often been used forthe sonoporation-assisting agents. More details of fundamentals and historical development of the sonoporation
can be found in many literatures (e.g., Al-Dosari and Gao,2009; Kodama et al., 2006; Mehierhumbert and Guy,
2005; Zhou et al., 2014).
Recently, sonoporation-assisted NP deliveries havebeen investigated. Carrasco et al. (2016) employed ashock wave irradiation for delivery of mesoporous silica
NPs into human embryo kidney cells. Although no micro-

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bubble additives were used, they verified that the shock
wave irradiation significantly enhanced the delivery of
the mesoporous silica NPs with 200 nm diameter. Another approach in which NPs/microbubble composites aresynthesized and utilized for better delivery of NPs has
also been investigated. Wang et al. (2014) synthesized agold nanorod (AuNR)-microbubble composite, in which
AuNRs were encapsulated in perfluorocarbon gas filled
microbubbles (3 to 5 μm diameter) covered with a protein/
antibody shell. Amount of the AuNRs delivered into tumor cells showed significant increase when the AuNR/
microbubble composite was used with a sonoporation
treatment as compared to the control condition (without
encapsulation of AuNRs in microbubbles). This study
suggests that encapsulation of NPs in microbubbles canenhance the delivery performance of NPs in the sonoporation treatment. Yang et al. (2011) synthesized NP-­
embedded microbubbles composite in which Fe3O 4nanoparticles (12 nm diameter) were embedded in a polymer layer covering microbubble (3 to 5 μm diameter).
They showed that amount of Fe3O4 nanoparticles delivered
into tumor cells significantly increased by the ultrasoundirradiation. They also found that the Fe3O4-embedded microbubbles exhibited higher cell viability as compared toa control condition under the same ultra sound intensity.
This suggests that NPs/microbubble composites can reduce
damage to the cells associated with the sonoporation.
Many questions and issues still remain unsolved in thesonoporation-assisted NP permeation. Operating conditions of the sonoporation treatment (e.g., intensity, frequency, duration of the ultrasound irradiation) can be key
factors. Wang et al. (2014) and Yang et al. (2011) suggested that NP delivery rate can be controlled by theintensity and number of the ultrasound irradiation.
Physico-­chemical properties of NPs can also be importantfactors. Carrasco et al. (2016) found that a surface coatingof NP with cationic lipid molecules attenuate the decreasein the cell viability after the sonoporation treatment. Interaction between NPs and microbubble is also important
subject of investigation, when NPs/microbubble composites will be employed. Role of these potential key factors
should be investigated to optimize the sonoporation-­assisted NP permeation.

4. Molecular mechanisms of the NP direct
permeation: insights from molecular
dynamics simulations
Understanding of the mechanism of the direct permeation of NPs across a cell membrane can greatly contribute to synthesizing new NPs and to developing a new NP
delivery technique with high delivery efficacy and lesscellular damage. However, the molecular mechanism un-derlying the NP direct permeation is poorly understood.
Although a lot of experimental studies on the NP–cellmembrane interactions have been conducted, it is still
difficult to investigate the molecular mechanism using
current experimental techniques. One of the potential
ways to investigate the NP–cell membrane interactions is
a computational modeling. In particular, molecular dynamics (MD) simulations can be a powerful approach. In
the MD simulations, trajectories of individual atom canbe calculated so that dynamic evolution of the system
consisting of the NP, lipid molecules, and solvents can be
simulated at the molecular scale. This can provide deep
insights into the understanding of the NP-cell membraneinteractions. Coarse-grained MD methods have often
been adapted for the NP-cell membrane interactions. In
the coarse-grained MD methods, small groups of atoms
are represented by a single interaction sites as coarsegrained sites. This can greatly reduce the computationalload and enables to simulate the NP-cell membrane interactions with appropriate system size (larger than ten
nanometers) and length of time (longer than a few hundred nanoseconds). More details of the MD simulation
methods for the NP-cell membrane interactions can befound in the literatures (Ding and Ma, 2015; Qu et al.,2013; Rossi and Monticelli, 2016).
We surveyed MD simulation studies reported so far,and simulated final fates of NPs after interacting with alipid bilayer (model cell membrane) will be reviewed.
Fig. 2 shows summary of the final fates of NPs reported
in previous studies. The MD simulation studies suggestthat the final fates of the NPs will become either adhesion, penetration, or wrapping (Fig. 2(a)). Here, it should
be noted that the further permeation of the NPs across themembrane cannot be observed unless applying external
force on the NP (Fig. 2(b)) or adopting some additionalsettings (Fig. 2(c)). This review is focusing on the direct
permeation, thus, we will review the MD simulation studies which can be classified into groups of Fig. 2(b) and (c).
We here define the terms to distinguish between these
two groups: “biased” and “unbiased” MD simulations.
The biased MD simulations correspond to Fig. 2(b),where a NP was artificially forced to permeate across themembrane. Although this is far from a reality, the biased
MD simulations can provide insights into that how theNPs can be designed to achieve high permeability andlow cellular damage. On the other hand, the unbiased MD
simulations correspond to Fig. 2(c), where any external
forces are not exerted on the NP, but other additional settings are adopted. The unbiased MD simulations can provide insight into physical requirements for the direct
permeation of NPs across a lipid bilayer. In the following
sections, the biased and unbiased MD simulation studies
will be reviewed, respectively.

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Fig. 2

Summary of final fates of nanoparticles after interacting with lipid bilayer reported in MD simulation
studies.

4.1 Biased MD simulation studies
As mentioned above, the biased MD simulations, where
the NP is forced to permeate across the membrane by applying an external force to the NP, have been conducted
for investigating potential key NP properties for the NP
direct permeation across a cell membrane. The permeation process has been characterized by physical andthermodynamic properties such as the minimal driving
force required for the NPs to permeate lipid bilayers andthe potential of mean force (i.e., the free energy change)along the NP permeation across the cell membrane.
Song et al. (2011) investigated influence of NP size on
the direct permeation across a phospholipid bilayer bymeans of the biased MD simulation. They used gold NPs
in the range of 0.8 to 2.5 nm diameter and with nearly
spherical shape. They calculated the minimum driving
force required to permeate a DPPC bilayer at various NP
sizes. With a decrease in the size of gold NP, the driving
force was smaller. This result is similar with an experimental observation presented in Section 2: the smaller thenanoparticle, the easier it is for the direct permeation. The
minimum force for permeating whole bilayer (both firstand second monolayers) was ca. 100 to 500 pN in therange of the size of 0.8 to 2.5 nm. Song et al. (2011) also
reported that the minimum force calculated from theirunbiased MD simulations showed an agreement with an

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experimental result obtained from an atomic force microscopy (Vakarelski et al., 2007), although further investigations seem to be needed. They also calculated theminimum driving pressure, which was defined by theminimum force per cross-sectional area of the NP. They
found that the pressure required to permeate whole bilayer deceased with an increase in the nanoparticle size.
Shape of the NP is another key property. Some computational modeling studies on the role of particle shape in
the NP permeation have been performed. From the previous studies, a consensus has been addressed: the sharp
shape can be advantageous for the NP direct permeation.
Yang and Ma (2010) performed a MD simulation of the
NP permeation across a lipid bilayer (Fig. 3(a)). They calculated the minimum driving force of NPs with various
shapes (Fig. 3(b)) by means of the biased MD simulation.
Their result (Fig. 3(c)) revealed that the higher minimum
driving force was required at larger radius r (i.e., larger
contact area between particle and bilayer), while the minimum driving force was less sensitive to the particle
height h. Interestingly, the minimum driving force significantly decreased even at higher particle height in the caseof the V-shaped particle (the green circle plot in Fig. 3(c)),
where the local curvature at the contact surface between
the NP and bilayer was much higher and the disruption
area due to the particle permeation gradually increased as
the NP permeated into the membrane. The authors con-

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Fig. 3(a) Permeation behavior of elongated nanoparticle in biased MD simulation. (b) Various particle shapesand (c) minimum driving force for their direct permeation across lipid bilayer. Reprinted with permission from Ref. (Yang and Ma, 2010). Copyright: (2010) Nature Publishing Group.

cluded that the permeability of nanoparticles with anisotropic shapes can be determined by the contact area andthe local curvature: i.e., the direct permeation can be
more likely to occur at the smaller contact area and thehigher local curvature. They also demonstrated that theinitial orientation of the NP toward the lipid bilayerstrongly relates to the capability of the NP direct permeation across the lipid bilayer. Shi et al. (2008) investigatedpermeation behavior of carbon nanotubes (CNTs) withdifferent tube diameters. Their simulation result showed
the tube diameter can be a determinant of the permeation
mode of the CNTs: a CNT with smaller tube diameter(single-walled CNT) can directly permeate the bilayer via
a piercing mode, while a CNT with larger tube diameter(multi-walled CNT) is likely to translocate the lipid bilayer via a wrapping mode. Moreover, they proposed theoretical models for the piercing and wrapping modes
based on a vacancy diffusion theory and a fluid mechanics
theory for an imcompressible viscous fluid. As a result,they successfully explained that the dominant permeation

mode can switch from the piercing to the wrapping at a
critical radius as the tube radius increases.
In most of the biomedical and pharmaceutical applications utilizing NPs, surface modifications of the NPs havebeen frequently conducted to modify surface properties
such as surface charge, hydrophilicity/ hydrophobicity,and specific interactions with cells. This can control the
NP translocation across the cell membrane. Some biased
MD simulation studies have investigated that how surface
modifications of NP affect its permeation across a lipid
bilayer. Song et al. (2012a) performed a MD simulation of
permeation behavior of ligand-coated nanoparticles
across a DPPC bilayer. They used alkanethiol-coated gold
nanoparticles with different alkyl chain lengths. Bymeans of a biased MD simulation, influence of the ligand
length on the minimum driving force to permeate the bilayer was investigated. With an increase in the ligand
length, the minimum driving force for permeating thefirst layer of the lipid bilayer was reduced, while thehigher driving force was required to permeate the second57

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layer and whole lipid bilayer. This is due to the favorable
interactions between the hydrophobic lipid tails and hydrophobic ligands on the NP. This hydrophobic interaction becomes higher at longer ligand length, resulting in
reducing the minimum force for permeating the first layer(from hydrophilic to hydrophobic) and increasing theminimum force for permeating the second layer (from hydrophobic to hydrophilic). As presented in Section 2,
some experimental studies exhibited that the NP direct
permeation can be enhanced by surface modifications
with orderly arranged ligand structural pattern (Jewell etal., 2011; Verma et al., 2008), while its mechanism is still
unknown. This issue has been investigated by MD simulation studies. Li et al. (2012) investigated the direct permeation of ligand-coated NPs with two different types ofligand structural patterns: striated pattern with orderly
arranged hydrophilic and hydrophobic domains (“St” inFig. 4(a)), and randomly arranged pattern at the same ratio of the hydrophilic and hydrophobic ligands (“Rand” inFig. 4(a)). The simulation results demonstrated that the ligand structural pattern significantly affects the criticalforce for permeation of NPs across the lipid bilayer, andthe striated ligand pattern results in the lowest criticalforce (Fig. 4(b)). They also investigated the free energychange associated with the permeation of NPs across thelipid bilayer, (Fig. 4(c)). The NP with random ligand pattern encountered substantial energy minimum at the center of bilayer, while the NP with striated ligand pattern
flattened the energy minimum. This means that NP withstriated ligand pattern is likely to permeate the lipid bilayer as compared to the NP with random ligand pattern,which can be trapped in the hydrophobic region of thebilayer. The similar free energy change induced byswitching from random ligand structure to ordered ligand
structure has been also reported by Gkeka et al. (2013). Li
et al. (2012) conducted further analysis for understanding
why the NP with striated ligand pattern exhibited thehigher permeability. They indicated that the shallow energy minimum of the striated NP is attributed to lower
degree of freedom for rotation of the striated NP in thehydrophobic region of the bilayer. The rotation of the striated NP during permeation across the bilayer was foundto be constrained as compared to the NP with random ligand pattern due to the anisotropic ligand pattern. This
prevented the NP from further fitting with the hydrophobic tails of lipid molecules, avoiding to be trapped into a
deeper energy minimum when the NP passes across thehydrophobic region of the lipid bilayer.
Although biased MD simulations reported so far haveprovided deep insights into the molecular mechanism of
the NP direct permeation across cell membranes, many
aspects of the mechanism are still unknown. For example,
role of physicochemical properties of the NPs such as surface charge and mechanical properties (soft/rigid) on the58

Fig. 4(a) Ligand-coated nanoparticles with different surface
structural patterns. (b) Critical force for permeating
lipid bilayer at each nanoparticle with different surface
ligand patterns. (c) Free energy change associated withpermeation of various nanoparticles with different surface ligand patterns. Reprinted with permission from
Ref. (Li et al., 2012). Copyright: (2012) The Royal Society of Chemistry.

direct permeation across a cell membrane should be further investigated. Although many MD simulation studies
regarding these properties have been reported, most of theprevious studies have not focused on the permeation,
while they have focused on adhesion or penetration into alipid bilayer. Impact of the membrane properties such ascomposition of lipid molecules, bilayer phase, charge
property, membrane surface tension should also be analyzed using a biased MD simulation. Moreover, not only
the permeability of NPs but also changes of the lipid bilayer’s properties are important subjects to be investi-

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gated. From biased MD simulations, it has been observedthat significant structural changes of the lipid bilayer suchas pore formation and lipid flip-flop were induced by the
NP permeation, followed by excessive leakage of waters
and ions across the lipid bilayer (Oroskar et al., 2015;
Song et al., 2012b). Such membrane disruption induced by
the NP permeation should be analyzed further, providing
important insights into the cellular damage and toxicity
caused by the NP permeation.

4.2 Unbiased MD simulation studies
As mentioned before, the MD simulation studies suggest that NPs cannot permeate across a lipid bilayer unless exerting an external force to the NP. However,experimental studies demonstrated that NPs can directly
permeate across a cell membrane without exerting external
force on the NP. Thus, a fundamental question remains
unsolved: what are the physico-chemical requirements
leading to the NP direct permeation? A few unbiased MD
simulation studies have investigated to solve this issue.
These unbiased MD simulations demonstrated that whensome additional settings are adopted, an NP can directly
permeate across a lipid bilayer. So far, the following special settings have been found to induce the NP direct permeation: the reversible reaction between NP and ligands(Ding et al., 2012), multiple NPs (Li et al., 2013), application of an external electric field (Shimizu et al., 2016).
Ding et al. (2012) proposed a new type of ligand-coated
NP and demonstrated that their NP can directly permeate
across a lipid bilayer (Fig. 5). Their ligand-coated NP
consists of hydrophilic rigid core and amphiphilic ligands.
As their uniqueness, they adopted a reversible reaction
between the core particle and the ligands. In an aqueous
environment, the hydrophilic head of the ligand binds
onto the surface of the core particle. This results in thehydrophobic surface of the ligand-coated NP before interacting with a lipid bilayer. Due to this hydrophobic na-

Fig. 6

ture, the NP can spontaneously penetrate into thehydrophobic region of the membrane at first. Meanwhile,the ligand starts to break off in the hydrophobic region of
the membrane due to reversible reaction responding thehydrophobic environment surrounding NP. Once the ligands leave from surface of the core particle, the hydrophilic surface of the core particle is exposed. Since thehydrophilic nature is unfavorable to stay in the hydrophobic region of the membrane, the NP is spontaneously
pushed away and finally permeates across whole lipid bilayer. Although it is actually hard to synthesize such typeof ligand-coated NPs, this study provides deep insight
into a strategy of the particle design for the NP direct permeation pathway.
In reality, number of NPs interacting with a cell membrane is huge. Moreover, the NPs may form an aggregation, and this aggregation may interact with a cell. Thissituation can be very different from a situation when the
single primary NP interacts with a cell membrane. Thus,
understanding of the NP-cell membrane interactions

Fig. 5

Direct permeation behavior of ligand-coated nanoparticle by adopting a reversible reaction between nanoparticle and ligands. Reprinted with permission from Ref.
(Ding et al., 2012). Copyright: (2012) American Chemical Society.

Interaction of multiple peptide-conjugated nanoparticles with a lipid bilayer. Core of the nanoparticle isin red. The peptides are in yellow and pink. For the clarity, the peptides are not displayed at 130 ns, 1500
ns, and 2400 ns. Reprinted with permission from Ref. (Li et al., 2013). Copyright: (2013) The Royal Society of Chemistry.

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when there are multiple NPs is an important issue. Li etal., (2013) performed an unbiased MD simulation study
on the interactions of peptide-conjugated NPs with a lipid
bilayer (Fig. 6). The simulation result showed that when
the NP interacted with a bilayer as a single particle any
permeation of the NP was not observed. However, theyfound that when multiple NPs interact with a bilayer someNPs can permeate across the bilayer (Fig. 6). This NP
permeation was induced by a pore-mediated process: i.e.,

multiple NPs cooperatively interact with a membrane andform a transmembrane pore. This is the similar mechanism of the transmembrane pore formation induced bymultiple antimicrobial peptides (Leontiadou et al., 2006).
Such cooperative interaction can be one of the potential
mechanisms of the NP direct permeation.
As reviewed in Section 3, application of external force
fields can be an effective way to directly deliver NPs intoa cell, although its mechanism is largely unknown. We

Fig. 7. (a) Nanoparticle behavior without both external force on particle and electric field. (b) Nanoparticle behavior with external force on particle but without external electric field. (c) Nanoparticle behavior withexternal electric field but without external force on particle. Membrane potential that lower than themembrane breakdown intensity was applied (V = 0.8Vc). (d) Nanoparticle behavior under excessive applied membrane potential that is equal to the membrane breakdown intensity (V = Vc). Waters were notshown for clarity in (a) to (d). Ions were not shown in (a) and (b). Reprinted with permission from Ref.
(Shimizu et al., 2016). Copyright: (2016) The Royal Society of Chemistry.

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focused on the electroporation-assisted NP delivery andinvestigated for the first time the NP permeation across alipid bilayer under an external electric field by means ofan unbiased MD simulation (Shimizu et al., 2016). We
used an alkanethiol-coated cationic gold nanoparticle
with 4 nm diameter for the simulation. This is a typicalNP for the biomedical and the pharmaceutical applications, and the direct permeation of this type of NP acrossa cell membrane have been observed (Table 1). Our study
will be introduced in the following.
First of all, we investigated the NP behavior without
the external electric field. The final fate of the NP was adhesion on the hydrophilic surface of the lipid bilayer, andthe NP permeation across the bilayer was not observed(Fig. 7(a)). We also performed a biased MD simulation,i.e., the NP was forced to move downward across the bilayer by applying external force, while the electric field
was not applied. Even in this case, the NP did not permeate across the bilayer, and partial wrapping of the NP by
the bilayer was observed (Fig. 7(b)). Consequently, it was
confirmed that the NP cannot permeate across a lipid bilayer without an external electric field. However, a drasticchange of the NP behavior was observed when an external electric field was applied: the NP directly permeatedacross the lipid bilayer (Fig. 7(c) and (d)). Detail of thispermeation process was as follows: (i) the NP adhered
onto the hydrophilic surface of the bilayer; (ii) the NP
penetrated into the bilayer while forming a hydrophilicpore in the membrane around the periphery of the NP; (iii)
the NP finally permeated across the whole bilayer throughthe hydrophilic pore without membrane wrapping andpulling out of lipid molecules. Interestingly, as shown in
Fig. 7(c), this NP direct permeation can be induced evenunder a lower applied membrane potential than the membrane breakdown potential. This implies that prior application of excessive electric field to form transmembranepores before delivering NPs may not be necessary. Moreover, under a lower membrane potential than the membrane breakdown intensity (Fig. 7(c)) the transmembranepore generated by the NP permeation immediately resealed after the NP permeation, while the persistent transmembrane pore was formed under an excessive membranepotential that is equal to the membrane breakdown potential (Fig. 7(d)). We also evaluated degree of the membrane
disruption caused by the NP permeation by analyzing thelipid flip-flop and permeation amount of waters and ions
across the membrane. The degree of the membrane disruption in the direct permeation pathway with self-resealingof the membrane (Fig. 7(c)) was significantly less andnegligible as compare to the direct permeation with persistent transmembrane poration (Fig. 7(d)).
To investigate a key factor in the direct permeation of
the NP, combined effects of the intensity of applied membrane potential and affinity of the NP for the membranesurface were investigated. Unbiased MD simulations using three different lipid bilayers (LB-1, LB-2, and LB-3 inFig. 8) were conducted. Through the potential-of-meanforce analysis, we confirmed that the NP used in ourstudy has a strong affinity with surface of the LB-3
(DPPC/DPPG leaflet), while less affinity with surfaces of
the LB-1 and LB-2 (DPPC leaflet). We then conductedsystematic unbiased MD simulations in each lipid bilayer
under various applied membrane potentials. Fig. 8 showsa summary of the results. Following four modes of the NP
behaviors were observed: (a) no adhesion; (b) adhesion on
the membrane surface; (c) direct permeation with self-­
resealing of membrane; (d) direct permeation with persistent transmembrane poration. As shown in the result,occurrence probability of these four modes can strongly
depend on affinity of the NP with membrane as well as
applied membrane potential intensity. In particular, when
we focused on the direct permeation pathway with self-­
resealing of membrane (the blue bar in Fig. 8), this ideal
pathway is likely to occur in the LB-3: i.e., the case inwhich there is a strong affinity between the NP and surface of the membrane. The strong affinity can result in
exclusion of the water and ions at the interface between
the NP and the hydrophilic head group of the membrane.
This leads to less remaining water and ions in the transmembrane pore during the NP permeation, preventing
nucleation of the persistent hydrophobic pore and enhancing the self-resealing of the membrane after the NP permeation. In summary, our finding from the unbiased MD
simulation with external electric field suggests that bycontrolling the external electric field as well as the NP
surface properties in a suitable range, an ideal NP delivery pathway, where the NP can be directly delivered into
the cell with high delivery efficacy and less cellular damage, can be achieved.
Our study can also provide insights into the issue ofwhat the physico-chemical requirements can lead to the
NP direct permeation. One of the key requirements may
be “gradient” across the cell membrane. In actual NP-cellsystem, many intrinsic gradients such as pH difference,osmotic pressure, ionic concentration, resting transmembrane potential can be observed between outside and inside of the cell. These gradients can be a key for the NP
direct permeation. Lin and Alexander-Katz (2013) demonstrated that a NP can directly permeate across a lipid bilayer under a transmembrane potential induced by theionic imbalance across the bilayer. It is also well known
that lipid composition of the two leaflets of the biologicalcell membrane is highly asymmetric. This asymmetriclipid composition can be a potential key property for the
NP direct permeation. Role of these gradients and its
combined effects with the NP physico-chemical properties in the NP direct permeation across a cell membrane
should be investigated in further studies.

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Fig. 8

Occurrence probabilities of four modes of NP behaviors as a function of dimensionless applied membrane potential at different affinities between NP and membrane surface. V is applied membrane potential. Vc is the membrane breakdown potential. Results were within five independent simulation runs.
Reprinted with permission from Ref. (Shimizu et al., 2016). Copyright: (2016) The Royal Society ofChemistry.

5. Summary
In this article, we focused on the direct permeation of
nanoparticles (NPs) across a cell membrane and reviewed
the related literatures on both experimental and modelingstudies. First of all, we surveyed experimental studies
where a spontaneous direct permeation of NPs across acell membrane was observed, and reviewed the potential
key physico-chemical properties of NPs for the direct
permeation (Section 2). The experimental studies suggestthat size, hydrophobicity/hydrophilicity, and structuralarrangement of surface ligands can be critical NP properties for the direct permeation: much smaller size (smaller
than 10 nm), amphiphilic nature, and ordered ligand pattern can be favorable for the NP direct permeation. However, a general consensus of the NP properties is not yet
obtained and further investigations are necessary. Subsequently, potential physical methods for facilitating the NP
direct permeation were surveyed (Section 3). Amongthem, electroporation- and sonoporation- assisted NP delivery were reviewed. Many studies demonstrated that byutilizing these physical methods a variety of NPs can bedirectly delivered into cells and the delivery efficacy ofNPs can be significantly enhanced, while cellular damages are always concerned. To overcome this negative

62

impact, it is necessary to investigate the mechanism underlying the NP permeation under external force fields. In
particular, role of NPs’ physico-chemical properties on
the mechanism of the NP direct delivery by the physicalmethods is an important issue to be solved. Finally, MD
simulation studies on the NP permeation across a lipid
bilayer were reviewed (Section 4). From review of thebiased MD simulations, potential key NP properties forthe direct permeation were discussed. The size, shape,and structural arrangement of surface ligands can be key
properties for the direct permeation, although many aspectsof the mechanism are still unknown. From the unbiased
MD simulations, potential physico-chemical requirements
leading to the NP direct permeation were reviewed.
According to the recent MD simulation studies, the reversible reaction between NP and ligands during the permeation, cooperative interaction induced by multiple NPs,
and application of an external electric field can result in
the direct permeation of NPs across a cell membrane.
Despite the recent experimental and theoretical progress on the NP-cell membrane interactions, many questions remain and many issues are still unsolved. For
example, it is necessary to perform the experimental investigation and computational study under an identicalsystem and condition. This will enable to validate theHideya Nakamura et al. / KONA Powder and Particle Journal No. 35 (2018) 49–65

simulation results with the experimental results. New experimental systems and techniques as well as new computational methods are necessary to fill the gap between“the real system” and “the ideal system”. This will greatly
contribute to the comprehensive understanding of the NP
direct permeation and the development of new direct delivery technology with high delivery efficacy and less cellular damage.

Acknowledgements
This work was supported by the Hosokawa Powder
Technology Foundation Research Grant. This work wasalso supported by the Japan Society for the Promotion of
Science, KAKENHI Grant Number 1281208200 and
1581210400.

References
Al-Dosari M.S., Gao X., Nonviral gene delivery: principle, limitations, and recent progress, The AAPS journal, 11 (2009)
671–681.
Arvizo R.R., Miranda O.R., Thompson M.A., Pabelick C.M.,
Bhattacharya R., David Robertson J., Rotello V.M., Prakash
Y.S., Mukherjee P., Effect of nanoparticle surface charge at
the plasma membrane and beyond, Nano Letters, 10 (2010)
2543–2548.
Beddoes C.M., Case C.P., Briscoe W.H., Understanding
nanoparticle cellular entry: A physicochemical perspective,
Advances in Colloid and Interface Science, 218 (2015)
48–68.
Carrasco G., López-Marín L.M., Fernández F., Salas P., Loske
A.M., Millán-Chiu B.E., Biomimetic coat enables the use ofsonoporation to assist delivery of silica nanoparticle-cargoes
into human cells, Biointerphases, 11 (2016) 04B303.
Cho E.C., Xie J., Wurm P.A., Xia Y., Understanding the role ofsurface charges in cellular adsorption versus internalization
by selectively removing gold nanoparticles on the cell surface with a I2/KI etchant, Nano Letters, 9 (2009) 1080–
1084.
Ding H., Ma Y., Theoretical and computational investigations of
nanoparticle-biomembrane interactions in cellular delivery,
Small, 11 (2015) 1055–1071.
Ding H.M., Tian W. De, Ma Y.Q., Designing nanoparticle translocation through membranes by computer simulations, ACS
Nano, 6 (2012) 1230–1238.
Dreaden E.C., Mackey M.A., Huang X., Kang B., El-Sayed
M.A., Beating cancer in multiple ways using nanogold,
Chemical Society Reviews, 40 (2011) 3391.
Ekimov A.I., Efros A.L., Onushchenko A.A., Quantum size
effect in semiconductor microcrystals, Solid State Communications, 56 (1985) 921–924.
Fortin J.-P., Wilhelm C., Servais J., Ménager C., Bacri J.-C.,
Gazeau F., Size-sorted anionic iron oxide nanomagnets as

colloidal mediators for magnetic hyperthermia, Journal of
the American Chemical Society, 129 (2007) 2628–2635.
Gehl J., Electroporation: theory and methods, perspectives for
drug delivery, gene therapy and research, Acta Physiologica
Scandinavica, 177 (2003) 437–447.
Geng T., Lu C., Microfluidic electroporation for cellular analysis and delivery, Lab Chip, 13 (2013) 3803–3821.
Gkeka P., Sarkisov L., Angelikopoulos P., Homogeneous hydrophobic–hydrophilic surface patterns enhance permeation of
nanoparticles through lipid membranes, The Journal of
Physical Chemistry Letters, 4 (2013) 1907–1912.
Goda T., Goto Y., Ishihara K., Cell-penetrating macromolecules: Direct penetration of amphipathic phospholipid polymers across plasma membrane of living cells, Biomaterials,
31 (2010) 2380–2387.
Helfrich W., Elastic properties of lipid bilayers: theory and possible experiments, Zeitschrift für Naturforschung C, 28(1973) 693–703.
Hong S., Bielinska A.U., Mecke A., Keszler B., Beals J.L., Shi
X., Balogh L., Orr B.G., Baker Jr J.R., Holl M.M.B., Interaction of poly (amidoamine) dendrimers with supported
lipid bilayers and cells: hole formation and the relation totransport, Bioconjugate chemistry, 15 (2004) 774–782.
Hong S., Leroueil P.R., Elizabeth K., Peters J.L., Kober M.M.,
Islam M.T., Orr B.G., Baker Jr J.R., Holl M.M.B., Interaction of polycationic polymers with supported lipid bilayers
and cells: nanoscale hole formation and enhanced membrane permeability, Bioconjugate chemistry, 17 (2006)
728–734.
Huang S., Deshmukh H., Rajagopalan K.K., Wang S., Goldnanoparticles electroporation enhanced polyplex delivery
to mammalian cells, Electrophoresis, 35 (2014) 1837–1845.
Huang X., El-Sayed I.H., Qian W., El-Sayed M.A., Cancer cell
imaging and photothermal therapy in the near-infrared
region by using gold nanorods, Journal of the American
Chemical Society, 128 (2006) 2115–2120.
Jaque D., Martínez Maestro L., del Rosal B., Haro-Gonzalez P.,
Benayas A., Plaza J.L., Martín Rodríguez E., García Solé J.,
Nanoparticles for photothermal therapies, Nanoscale, 6(2014) 9494.
Jewell C.M., Jung J.M., Atukorale P.U., Carney R.P., Stellacci F.,
Irvine D.J., Oligonucleotide delivery by cell-penetrating“striped” nanoparticles, Angewandte Chemie—International Edition, 50 (2011) 12312–12315.
Jiang Y., Huo S., Mizuhara T., Das R., Lee Y., Hou S., Moyano
D.F., Duncan B., Liang X., Rotello V.M., The interplay ofsize and surface functionality on the cellular uptake of sub10 nm gold nanoparticles, ACS Nano, 9 (2015) 9986–9993.
Kahru A., Ivask A., Mapping the dawn of nanoecotoxicologicalresearch, Accounts of Chemical Research, 46 (2013) 823–
833.
Kawano T., Yamagata M., Takahashi H., Niidome Y., Yamada
S., Katayama Y., Niidome T., Stabilizing of plasmid DNA
in vivo by PEG-modified cationic gold nanoparticles andthe gene expression assisted with electrical pulses, Journalof Controlled Release, 111 (2006) 382–389.
Kennedy L.C., Bickford L.R., Lewinski N.A., Coughlin A.J.,
Hu Y., Day E.S., West J.L., Drezek R.A., A new era for

63

Hideya Nakamura et al. / KONA Powder and Particle Journal No. 35 (2018) 49–65

cancer treatment: gold-nanoparticle-mediated thermal therapies, Small, 7 (2011) 169–183.
Kim S.T., Saha K., Kim C., Rotello V.M., The role of surfacefunctionality in determining nanoparticle cytotoxicity,
Accounts of Chemical Research, 46 (2013) 681–691.
Kim T., Momin E., Choi J., Yuan K., Zaidi H., Kim J., Park M.,
Lee N., McMahon M.T., Quinones-Hinojosa A., Bulte
J.W.M., Hyeon T., Gilad A.A., Mesoporous silica-coatedhollow manganese oxide nanoparticles as positive T1 contrast agents for labeling and MRI tracking of adipose-­derived mesenchymal stem cells, Journal of the American
Chemical Society, 133 (2011) 2955–2961.
Kodama T., Tomita Y., Koshiyama K., Blomley M.J.K., Transfection effect of microbubbles on cells in superposed ultrasound waves and behavior of cavitation bubble, Ultrasoundin Medicine & Biology, 32 (2006) 905–914.
Kotnik T., Frey W., Sack M., Haberl Meglič S., Peterka M.,
Miklavčič D., Electroporation-based applications in biotechnology, Trends in Biotechnology, 33 (2015) 480–488.
Leontiadou H., Mark A.E., Marrink S.J., Antimicrobial peptides
in action, Journal of the American Chemical Society, 128(2006) 12156–12161.
Li Y., Li X., Li Z., Gao H., Surface-structure-regulated penetration of nanoparticles across a cell membrane, Nanoscale, 4(2012) 3768.
Li Y., Computer simulation studies on passive recruitment
dynamics of lipids induced by the adsorption of charged
nanoparticles, Physical Chemistry Chemical Physics, 16(2014) 12818.
Li Z., Ding H., Ma Y., Translocation of polyarginines and conjugated nanoparticles across asymmetric membranes, Soft
Matter, 9 (2013) 1281–1286.
Lin J., Alexander-Katz A., Cell membranes open “doors” forcationic nanoparticles/biomolecules: insights into uptake
kinetics, ACS Nano, 7 (2013) 10799–808.
Lin J., Chen R., Feng S., Li Y., Huang Z., Xie S., Yu Y., Cheng
M., Zeng H., Rapid delivery of silver nanoparticles into living cells by electroporation for surface-enhanced Raman
spectroscopy, Biosensors and Bioelectronics, 25 (2009)
388–394.
Liu J., Lu N., Li J., Weng Y., Yuan B., Yang K., Ma Y., Influenceof surface chemistry on particle internalization into giant
unilamellar vesicles, Langmuir, 29 (2013) 8039–8045.
Lund T., Callaghan M.F., Williams P., Turmaine M., Bachmann
C., Rademacher T., Roitt I.M., Bayford R., The influence ofligand organization on the rate of uptake of gold nanoparticles by colorectal cancer cells, Biomaterials, 32 (2011)
9776–9784.
Luo Z., Yuan X., Yu Y., Zhang Q., Leong D.T., Lee J.Y., Xie
J., From aggregation-induced emission of Au(I)–thiolate
complexes to ultrabright Au(0)@Au(I)–thiolate core–shell
nanoclusters, Journal of the American Chemical Society,134 (2012) 16662–16670.
Mehierhumbert S., Guy R., Physical methods for gene transfer:
Improving the kinetics of gene delivery into cells,
Advanced Drug Delivery Reviews, 57 (2005) 733–753.
Oroskar P.A., Jameson C.J., Murad S., Surface-functionalized
nanoparticle permeation triggers lipid displacement and64

water and ion leakage, Langmuir, 31 (2015) 1074–1085.
Périgo E.A., Hemery G., Sandre O., Ortega D., Garaio E.,
Plazaola F., Teran F.J., Fundamentals and advances in magnetic hyperthermia, Applied Physics Reviews, 2 (2015) .
Pietroiusti A., Health implications of engineered nanomaterials,
Nanoscale, 4 (2012) 1231.
Qu Z.G., He X.C., Lin M., Sha B.Y., Shi X.H., Lu T.J., Xu F.,
Advances in the understanding of nanomaterial–biomembrane interactions and their mathematical and numericalmodeling, Nanomedicine, 8 (2013) 995–1011.
Rana S., Bajaj A., Mout R., Rotello V.M., Monolayer coatedgold nanoparticles for delivery applications, Advanced
Drug Delivery Reviews, 64 (2012) 200–216.
Rossi G., Monticelli L., Gold nanoparticles in model biologicalmembranes: A computational perspective, Biochimica etBiophysica Acta (BBA)—Biomembranes, 1858 (2016)
2380–2389.
Shao K., Singha S., Clemente-Casares X., Tsai S., Yang Y.,
Santamaria P., Nanoparticle-based immunotherapy forcancer, ACS Nano, 9 (2015) 16–30.
Shi X., Kong Y., Gao H., Coarse grained molecular dynamics
and theoretical studies of carbon nanotubes entering cell
membrane, Acta Mechanica Sinica, 24 (2008) 161–169.
Shimizu K., Nakamura H., Watano S., MD simulation study of
direct permeation of a nanoparticle across the cell membrane under an external electric field, Nanoscale, 8 (2016)
11897–11906.
Song B., Yuan H., Jameson C.J., Murad S., Role of surface
ligands in nanoparticle permeation through a model membrane: a coarse-grained molecular dynamics simulations
study, Molecular Physics, 110 (2012a) 2181–2195.
Song B., Yuan H., Jameson C.J., Murad S., Permeation of nanocrystals across lipid membranes, Molecular Physics, 109(2011) 1511–1526.
Song B., Yuan H., Pham S.V, Jameson C.J., Murad S., Nanoparticle permeation induces water penetration, ion transport,
and lipid flip-flop, Langmuir, 28 (2012b) 16989–17000.
Vakarelski I.U., Brown S.C., Higashitani K., Moudgil B.M.,
Penetration of living cell membranes with fortified carbon
nanotube tips, Langmuir, 23 (2007) 10893–10896.
Van Lehn R.C., Atukorale P.U., Carney R.P., Yang Y.-S., StellacciF., Irvine D.J., Alexander-Katz A., Effect of particle diameter and surface composition on the spontaneous fusion ofmonolayer-protected gold nanoparticles with lipid bilayers,
Nano Letters, 13 (2013) 4060–4067.
Veiseh O., Kievit F.M., Mok H., Ayesh J., Clark C., Fang C.,
Leung M., Arami H., Park J.O., Zhang M., Cell transcytosing poly-arginine coated magnetic nanovector for safe andeffective siRNA delivery, Biomaterials, 32 (2011) 5717–
5725.
Verma A., Stellacci F., Effect of surface properties on nanoparticle-­cell interactions, Small, 6 (2010) 12–21.
Verma A., Uzun O., Hu Y., Hu Y., Han H.-S., Watson N., Chen
S., Irvine D.J., Stellacci F., Surface-structure-regulated
cell-membrane penetration by monolayer-protected
nanoparticles, Nature Materials, 7 (2008) 588–595.
Wang S., Zhang X., Yu B., Lee R.J., Lee L.J., Targeted nanoparticles enhanced flow electroporation of antisense oligonu-Hideya Nakamura et al. / KONA Powder and Particle Journal No. 35 (2018) 49–65

cleotides in leukemia cells, Biosensors and Bioelectronics,
26 (2010) 778–783.
Wang Y.H., Chen S.P., Liao A.H., Yang Y.C., Lee C.R., Wu
C.H., Wu P.C., Liu T.M., Wang C.R.C., Li P.C., Synergistic
delivery of gold nanorods using multifunctional microbubbles for enhanced plasmonic photothermal therapy, Scientific Reports, 4 (2014).
Weller H., Schmidt H.M., Koch U., Fojtik A., Baral S., HengleinA., Kunath W., Weiss K., Dieman E., Photochemistry of
colloidal semiconductors. Onset of light absorption as afunction of size of extremely small CdS particles, Chemical
Physics Letters, 124 (1986) 557–560.
Wilczewska A.Z., Niemirowicz K., Markiewicz K.H., Car H.,
Nanoparticles as drug delivery systems, Pharmacological
Reports, 64 (2012) 1020–1037.
Xiong R., Raemdonck K., Peynshaert K., Lentacker I., De CockI., Demeester J., De Smedt S.C., Skirtach A.G., Braeckmans
K., Comparison of gold nanoparticle mediated photoporation: vapor nanobubbles outperform direct heating fordelivering macromolecules in live cells, ACS Nano, 8(2014) 6288–6296.
Yang F., Zhang M., He W., Chen P., Cai X., Yang L., Gu N., Wu
J., Controlled release of Fe3O4 nanoparticles in encapsulated microbubbles to tumor cells via sonoporation andassociated cellular bioeffects, Small, 7 (2011) 902–910.
Yang K., Ma Y.-Q., Computer simulation of the translocation of
nanoparticles with different shapes across a lipid bilayer,
Nature Nanotechnology, 5 (2010) 579–583.
Yi X., Shi X., Gao H., Cellular uptake of elastic nanoparticles,
Physical Review Letters, 107 (2011) 98101.
Yuan X., Tay Y., Dou X., Luo Z., Leong D.T., Xie J.,
protected silver nanoclusters as cysteine-­
Glutathione-­selective fluorometric and colorimetric probe, Analytical
Chemistry, 85 (2013) 1913–1919.
Zhou Q.L., Chen Z.Y., Wang Y.X., Yang F., Lin Y., Liao Y.Y.,
Ultrasound-mediated local drug and gene delivery using
nanocarriers, BioMed Research International, 2014 (2014)
1–13.
Zhu M., Nie G., Meng H., Xia T., Nel A., Zhao Y., Physicochemical properties determine nanomaterial cellular
uptake, transport, and fate, Accounts of Chemical Research,46 (2013) 622–631.
Zu Y., Huang S., Liao W.-C., Lu Y., Wang S., Gold nanoparticles enhanced electroporation for mammalian cell transfection, Journal of Biomedical Nanotechnology, 10 (2014)
982–992.

Author’s short biography
Hideya Nakamura
Dr. Hideya Nakamura is an Associate Professor at Department of Chemical Engineering in Osaka Prefecture University. He received his Ph.D. in 2008 from Osaka Prefecture
University. He then worked as a Post doc associate in Particle Engineering ResearchCenter (PERC), University of Florida. From 2010, he started his carrier as a faculty at
Osaka Prefecture University. He is currently working on modelling and experimental
studies on nanoparticle-cell membrane interactions. His current projects also include
computational modelling of powder handling processes as well as functionalization ofparticulate materials for next generation secondary batteries.

Satoru Watano
Prof. Satoru Watano, specialized in Chemical Engineering, received his Ph.D. from
Osaka Prefecture University (OPU) in 1995. He became professor at OPU in 2005. Currently, he is the vice dean of College of Engineering at OPU. He is the board directors of
The Society of Powder Technology Japan and the council member of Japan Society of
Pharmaceutical Machinery and Engineering. His research area covers (i) measurement,
control, optimization of powder handling processes (ii) particle design and modificationof surface properties, (iii) design and handling of nano-particles, (iv) numerical modeling and simulation of particulate systems, and (v) development of innovative powder
handling processes.

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KONA Powder and Particle Journal No. 35 (2018) 66–79/Doi:10.14356/kona.2018012

Review Paper

Size Control of Polymeric Particle in
Soap-Free Emulsion Polymerization †Tetsuya Yamamoto 1* and Ko Higashitani 2
1
2

Department of Materials and Design Innovation Engineering, Nagoya University, Japan
Department of Chemical Engineering, Kyoto University-Katsura, Japan

Abstract
The process of synthesis of polymeric particle in soap-free system was observed in-situ on the molecular scale byusing an atomic force microscope (AFM). Using cationic water-soluble initiators enabled all of the polymericmaterials to be adsorbed on the mica surface electrostatically. This adsorption technique of polymeric materials
in the bulk obtained the AFM images of them throughout the reaction and to discuss the real growth mechanismof polymeric particles. The followings are found; the polymeric materials are continuously generated in the bulk
throughout the reaction; and they make a contribution to the particle growth. Furthermore, soap-free emulsion
polymerization (SFEP) of aromatic vinyl monomer using oil-soluble initiators was studied to synthesize micronsized particles. Oil-soluble initiator, such as AIBN, worked like a water-soluble initiator in SFEP to preparemonodispersed particles with negative charges, probably because of the pi electron cloud of phenyl ring in amonomer. The addition of an electrolyte enabled secondary particles in the bulk to enhance hetero-coagulation
rate for particle growth. Changing the concentration and valence of electrolyte enabled us to control the size in
SFEP using AIBN. These methods enabled reaction time to be reduced for the synthesis of micron-sizedpolymeric particles in soap-free system.
Keywords: soap-free emulsion polymerization (SFEP), AFM, initiator, electrolyte, size control, coagulation

1. Introduction
Polymeric particles are widely used as materials for the
making the functional products in many industries, suchas toner particles, medicines, cosmetics, and so on (Svec
F. and Frechet J.M.J., 1996). Emulsion polymerization is
one of the most popular and typical methods in the polymerization for synthesis of the polymeric particles.
However, the polydisperse particles were prepared. Because the performance of the products depends on theuniformity of the raw materials, the development of theclassification technique for particle size was indispensablefor enhancement of the quality of the products (Yamamoto
T. et al., 2009; Yamamoto T. et al., 2011; Yoshida H. et al.,2010). The low density of the polymeric particles prevented the precise classification from being successful.
Although the soap-free emulsion polymerization (SFEP),
where the surfactants were not utilized, was synthesis
†
1
2

*

66

Received 23 May 2017; Accepted 4 July 2017
J-STAGE Advance published online 31 August 2017
Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
Kyoto University-Katsura, Nishikyo-ku, Kyoto 615-8510, Japan
Corresponding author: Tetsuya Yamamoto
E-mail: yamamoto.tetsuya@material.nagoya-u.ac.jp
TEL: +81-52-789-3378 FAX: +81-52-789-3271

method for sub-micron polymeric particles with small standard deviation of the size (Arai M. et al., 1979; Goodall
A.R. et al., 1977), it was difficult to make the micron-­sized particles by this method. The micron-sized particles
have generally been synthesized by dispersion polymerization using organic solvents and stabilizers (Kawaguchi
H., 2000; Lok K.P. and Ober C.K., 1985; Song J.S. et al.,2006; Tseng C.M. et al., 1986; Ugelstad J. et al., 1992).
Recently, using 2,2’-azobis[N-(2-carboxyethyl)-2-2-­
methylpropionami dine] hydrate as a water-soluble initiator in SFEP enabled to synthesize micron-sized polymericparticles (Gu S. et al., 2004; Gu S.C. et al., 2002; Yamada
Y. et al., 2005). Thus, the size of polymeric particle wascontrolled by the various polymerization methods.
Because it was too difficult to observe the synthesis
process of particle directly with molecular scale (Hergeth
W.-D. et al., 1992; Shouldice G.T.D. et al., 1995), thegrowth mechanism in the polymerizations was discussed
by many studies using the macroscopic data, such as thechange of particle number concentration with reaction
time, the mass balance, the measurement of particle size
using an electron microscopy (Feeney P.J. et al., 1984;
Fitch R.M., 1997; Harkins W.D., 1947; Smith W.V., 1948;
Song Z.Q. and Poehlein G.W., 1989). These macroscopic
data give us some fundamentals to estimate the macro-

Copyright © 2018 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/).

Tetsuya Yamamoto et al. / KONA Powder and Particle Journal No. 35 (2018) 66–79

scopic mechanism, but were not enough to make the real
growth mechanism clarified with molecular scale. Hence,
we still did not know the role of polymeric materials remained in the bulk solution, such as oligomers. However,in 2003, a single polymer were able to be observed in-situ
by atomic force microscope (AFM) (Arita T. et al., 2003;
Arita T. et al., 2004). That was to say that the direct observation of the growth process of polymer particle would
be possible. In this paper, a SFEP of styrene in water wasstudied on the molecular scale by using an AFM to clarify
the growth mechanism. A water-soluble cationic initiator
was used for all the polymeric products to adsorbed on
the negatively-charged mica surface electrostatically andfor all the adsorbates to be observable directly by in-situ
AFM method.
Furthermore, on the basis of the growth mechanism withmolecular scale, the size of the polymeric particles in SFEP
could be changed from sub-microns to microns. Hence, toinvestigate the effect of the solubility of initiator in wateron particle size, 2,2’-azobis(2-methylpropionamidine) dihydrochloride (V-50) was used as a water-soluble initiator,
2,2’-azobis(2-methylpropionit rile) (AIBN), dimethyl
2,2’-azobis(2-methylpropionate) (V-601) and 2,2’-­Azobis(2-methylbutyronitrile) (V-59) as an oil-soluble
initiator in SFEP. AIBN, V-601, and V-59 (Yoshida E.,
2010a, b) were dissolved slightly in water to change thenumber of radicals decomposed from the initiator inwater and the generation rate of the particles in bulk.
When using oil-soluble initiator for SFEP, the influence of
the addition of the electrolytes, other monomer, andwater-­soluble initiator to the system on particle properties
were also investigated.
Thus, this paper describes further two experimental results: 1) investigation of the preparation of polymeric particles through SFEP using an oil-soluble initiator, and 2)
development of a synthesis technique for size control ofpolymeric particles through SFEP with an oil-soluble initiator.

2. Experimental
2.1 Materials
The water was purified using the Milli-Q purification
system (Millipore), and, nitrogen gas was then bubbled into
the water to remove the dissolved oxygen gas. A styrene
monomer (Tokyo Chemical Industry) was washed with a
10 % sodium hydroxide (Wako Pure Chemical) solution toremove the polymerization inhibitors, and was then purified by distillation under reduced pressure using a rotary
evaporator (EYELA). 4-Fluorostyrene, 4-bromostyrene,
4-chlorostyrene, 2,3,4,5,6-pentafluorovinylbenzene, vinylcyclohexane, methyl methacrylate (MMA), and benzyl
methacrylate (BMA) (Tokyo Chemical Industry), werealso used, as received, as a monomer in SFEP by oil-­soluble initiator.
A water-soluble initiator, V-50 (Wako Pure Chemical),
4,4’-azobis(4-cyanovaleric acid) (V-501, Wako Pure
Chemical), and a oil-soluble initiator, AIBN (Sigma
Aldrich), V-601 (Wako Pure Chemical), V-59 (Wako Pure
Chemical), were also used as radical initiators without
further purification. They were monomers and azo compounds with chemical structures as shown in Fig. 1.
AIBN, V-601, and V-59 do not dissolve in water as thoroughly as V-50, which was used as an initiator in emulsion polymerization (Qiu J. et al., 1999), as shown in
Table 1. Therefore, they are not generally used as initiators for SFEP. In this study, the solubility of the initiatorin water is an important factor to control the generation
rate of secondary particles in bulk for size control ofpolymeric particle, hence these three initiators were usedas radical initiators for the SFEP of styrene.
Potassium chloride, anhydrous calcium chloride(Katayama Chemical), and anhydrous aluminum chloride(Kishida Chemical) were used as electrolytes without further purification to promote the coagulation for the particle growth.

Fig. 1 Chemical structure of the following monomers and initiators: (a) MMA; (b) BMA; (c) V-50; (d) AIBN; (e)V-601; (f) V-59; (g) V-501.

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Tetsuya Yamamoto et al. / KONA Powder and Particle Journal No. 35 (2018) 66–79

Table 1 Solubility in water and constant rate of decomposition of V-50, AIBN, V-601, V-59, and V-501.
V-50

AIBN

V-601

V-59

V-501

Solubility inwater [wt%]23.2(20 °C)

0.04 × 10 –3(25 °C)0.3(30 °C)

water- insoluble

soluble in hot
water

Constant rate ofdecomposing [s-1]1.2 × 10 –4(70 °C)a

4.0 × 10 –5(toluene at 70 °C)b

4.6 × 10 –5(toluene at 70 °C)

2.3 × 10 –5(toluene at 70 °C)c

1.9 × 10 –5(69 °C)a(Anon., 1985). b(Talât-Erben M. and Bywater S., 1955). c(Overberger C.G. et al., 1949).

Table 2 Experimental conditions of SFEP of styrene toobserve the growth processes by AFM.
Water
[g]

Styrene[g]

V-50[g/10g-water]

Temperature
[°C]

Water
[g]

Monomer[mmol/L]

Initiator[mmol/L]Electrolyte[mmol/L]

Temperature
[°C]

120

5.88

0.186

70

15

64

2.03

0~7

70

2.2 Polymerization reaction
For the observations of the growth processes by AFM,
the SFEP of styrene was carried out in a reactor of
500 mL with four necks for stirring mechanically with a
Teflon turbine blade, purging the nitrogen gas, condensing the reflux with cold water, and sampling an aliquot of
the solution with a pipette. The temperature of the reactor
was controlled with a water bath. The experimental conditions of SFEP of styrene employed are listed in Table 2.
The polymerization reactions were performed as follows.
First, a given amount of pure water was poured into thereactor under nitrogen atmosphere, and heated up to agiven temperature, agitating with the impeller speed of
180 rpm. Secondary, styrene monomer was added in thereactor after the temperature and agitation were settled.
At last, a solution with water and V-50 was added forstarting the reaction.
For size control of polymeric particle, the SFEP of various monomers using mainly oil-soluble initiator was carried out in a 30 ml reactor. The rotation speed of theimpeller in the reactor and temperature of the reactor
were controlled by a heater equipped with a magnetic
stirrer (EYELA, RCH-20L). The experimental conditions
for the polymerization employed are listed in Table 3.
Similarly, as the above paragraph, the polymerization reactions were examined as follows. Given amounts of purewater, initiators, and electrolytes, (whose concentration
was defined as Ce), were poured into the reactor, andmonomer was then added. The reactor was agitated with a
130 rpm impeller by a magnetic stirrer, where the surface
between the water and monomer phases was not disturbed
to prevent the formation and solidification of any monomer droplets with the dissolved oil-soluble initiators. And
then, the reactor was heated up to 70 °C by an electricheater. About setting the monomer concentration in thepolymerization, when the concentrations of styrene and68

Table 3 Experimental conditions of SFEP for synthesis of
micron-sized particle.

aluminum chloride were 640 mmol/L and 0.07 mmol/L,
respectively, 89.5 wt% of the monomers were not consumed to form the particles and were solidified by AIBN
to obtain the polymeric plate. Thus, the monomer concentration was determined to be 64 mmol/L. Because thesynthesized particles did not exhibit good dispersion stability at a reaction time, tr > 420 min after starting polymerization with electrolytes, the longest reaction time was
360 min.

2.3 In-situ observation by atomic force
microscopy
Observation of the in-situ molecular-scale images of all
the material transferred on the mica surface was examined by the atomic force microscope (AFM), a Nanoscope
III (Digital Instruments). Samples were prepared as follows. A drop of the solution was taken from the reactor attr and then cast on the mica surface in water, such thatcationic polymers synthesized by V-50 initiator were adsorbed on the mica surface with negative charges electrostatically (Hahn J. and Webber S.E., 2004). After setting
the mica plate to the AFM liquid cell, the excessive polymeric materials were removed by injection of pure water
into the cell to terminate the reaction.
Three dimensional and height images of polymericproducts adsorbed on the mica surface were obtained by
the tapping-mode procedure. The in-situ interaction
forces between the AFM probe tip and surface of polystyrene particle fixed on the mica surface were measured following the contact-mode procedure, where the cantileverwith a spring constant of 0.58 N/m was used. All the experiments using AFM were examined at the room temperature of 25 ± 2 °C.

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2.4 Measurement of size and zeta potential ofparticle
The field emission scanning electron microscope (FESEM) (JSM-6340FS, JEOL, S-5200, Hitachi High-­
Technologies) was operated to determine the particle size.
The samples were prepared as follows; a small amount ofsolution was taken from the reactor at tr and then a dropof the solution cast on the freshly cleaved mica plate. The
specimen was dried, and then covered with a thin platinum or osmium film using the chemical vapor deposition
method (E-1030, Hitachi High-Technologies, Osmium
Plasma Coater OPC60A, Filgen). The number-averaged
particle size, Dp, was calculated using averaging the datafrom 200 to 1000 particles in SEM photographs. The coefficient of variation of the particle size distribution, Cv,
was then calculated using Dp and standard deviation (GuS. et al., 2004).
The ZETASIZER (ZETASIZER 2000, MALVER N
Co., Ltd.) was used to evaluate the surface potential of thesynthesized particles. The sample of polymer colloid was
diluted with the deionized water at a pH of ca. 7.5.

Fig. 2Growth curve of polystyrene particles synthesized with
V-50 in SFEP evaluated by FE-SEM.

Fig. 3

AFM analysis of the particle at tr = 100 min: (a) AFM
three-dimensional image of particles top and (b) the
corresponding force curves between a probe tip and aparticle top. (a) Reprinted with permission from Ref.
(Yamamoto et al., 2005). Copyright: (2005) Elsevier
B.V.

3. Results and discussion
3.1 Growth curve at reaction temperature 70 °C
and observation of particle growth by AFM
The growth curve of PSL particles prepared by SFEP
using V-50 is shown in Fig. 2. Because it was found thatparticle continued to grow at least up to tr = 300 min, thepolymeric products at tr < 300 min was observed by AFM
to clarify the growth mechanism.
Fig. 3a shows the three-dimensional AFM image ofparticle at tr = 100 min. Fig. 3b shows the interactions between the AFM probe tip and the top of particle surface.
It was found that the AFM images of particle tops werevery smooth at tr = 100 min as shown in Fig. 3a. The features obtained from these data showed that (A) particles
were formed by the hard core covered with the soft shell
composed of polymeric materials, such as monomers forswelling, oligomers, embryos, and nuclei, and (B) the
thickness of the soft shell was measured to be ca. 4 nm at
tr = 100 min as the yellow area drawn in Fig. 3b indicated.
To study what kind of molecular-scale polymeric products existing in the bulk, the polymeric materials at
tr = 100 min adsorbed on the mica surface were observedby in-situ AFM. Fig. 4 showed that a lot of non-spherical
nanoparticulates were observed, and the average height of
the nanoparticulates at tr = 150 min coincided approximately with the surface roughness of the particle asshown in Fig. 5. From these observations, it was foundthat polymeric particulates generated continuously in thebulk solution during the polymerization reaction. As far
as the monomers and initiator radicals existed in the bulk,
the nucleation of particles always occurred throughout
this process. The above results indicated that the deposition of the polymeric materials formed in the bulk on theparticle surface as well as the growth by swelling mono-

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Fig. 4

AFM image of polymeric materials at tr = 150 min.

Fig. 6

AFM image of particle top at tr = 150 min.

Schematic representation of particle growth mechanism in SFEP by water-soluble initiator.

mers resulted in the rapid growth of particles aroundtr = 150 min. This was confirmed by the fact that the particle surface had some roughness as indicated by Fig. 5.
As far as the most of monomers were remained in thebulk at the beginning of the reaction, the deposition ofnano polymeric materials and swelling by monomers
would be occurred simultaneously. That was why particles grew with a smooth and soft shell surface as shownin Fig. 3. However, when the most of monomers was consumed, the thickness of the soft shell became thin and thedeposited polymeric materials kept their shape as theywere, because the amount of monomers in the bulk was
too small to make deposited polymers dissolved, as shownin Fig. 5 (Yamamoto T. et al., 2005; Yamamoto T. et al.,2004).

70

Fig. 5

3.2 Growth mechanism of polystyrene particles
and control of particle size with water-soluble
initiator concentration
We summarized the experimental results obtained so
far and proposed the molecular-scale growth mechanism
for particles in SFEP of styrene by V-50, as shown in Fig. 6(Yamamoto T. and Higashitani K., 2007; Yamamoto T. etal., 2006a; Yamamoto T. et al., 2006b). When the growthof particles was not observed in terms of the growth plot,
the particle surface did not become smooth. Although thepolymeric materials still remained in the bulk, they could
not make a contribution to the particle growth probably
because hydrophobic interaction between the surfaces ofparticles swollen by monomers in the bulk did not work.
Herein, about the size control of polystyrene particle,
the effect of the initiator concentration on the particle size
was discussed. Assuming that the final particle size be-Tetsuya Yamamoto et al. / KONA Powder and Particle Journal No. 35 (2018) 66–79

came smaller with initiator concentration increasing has
been accepted widely in many processes of particle formation. LaMer diagram (Lamer V.K. and Dinegar R.H.,
1950) indicated that the nucleation had to be terminatedwithin the period of particle formation to prepare particles with uniform size. On the other hand, it was wellknown that the final size of particles became larger as initiator concentration increased in the case of SFEP of styrene. This tendency was reverse to the case as the above
description and was also obtained in our experiments, as
shown in Fig. 7.
The experimental data in this study explained the reason for this reverse tendency. As discussed so far, thenucleation occurred in the bulk throughout the polymerization reaction. However, the total number of particles
was determined at least the end of the nucleation period,
where the particle growth was so rapid because of the absorption of monomers from the bulk and the simultaneous
coagulation among polymeric products. The size of growing particles became different from that of nuclei at thisperiod. Therefore, the polymeric materials nucleated secondary adsorbed on the surface of larger particles, rather
than coagulated with each other, probably because thesystem would be stabilized by their adsorption according
to the Ostwald-Ripening law (Wagner C., 1961). If thismechanism is true, almost all the polymeric materials

synthesized after nucleation will make a contribution to
the growth of particles. The number of the polymericmaterials was enlarged with concentration of initiatorincreased. That was why the final particle size became
larger as initiator concentration increased.

3.3 SFEP of aromatic vinyl monomer using AIBN
From here, the oil-soluble initiator was used in SFEP
replacing water-soluble initiator. Firstly, the polystyrene
particle was prepared by SFEP using oil-soluble initiator,
AIBN. The polymerizations were performed under theconditions listed in Table 3, without electrolytes. The
monodispersed particles with a diameter of 340 nm and azeta potential of –44.8 mV were prepared as shown in
Fig. 8a and Table 4 (Yamamoto T., 2012). The surface
potential was so negative that the polystyrene particles
showed good dispersion stability after the polymerization.
It was believed that, generally, the origin of charge ofthe particles synthesized by SFEP was the functionalgroup decomposed from the initiator, such as sulfate group,
to show good dispersed stability. Although the nitrilegroup, which was decomposed from AIBN, was electron-­attractive functional group, it did not have such negative
charges compared with the ionic functional group originated from a water-soluble initiator, such as potassium
persulfate (Arai M. et al., 1979; Munro D. et al., 1979).
Hence, to investigate why the synthesized polystyrene
particles by AIBN were charged negatively in water, theinfluence of the pi electron cloud of the aromatic vinyl
monomer on surface properties of the particle synthesized
through SFEP was studied changing kind of monomer for
Table 4 Zeta potential of the particles and particle size measured by FE-SEM in SFEP using aromatic vinyl
monomer and AIBN at Ce = 0.

Fig. 7

Fig. 8

Influence of V-50 concentration on particle size.

Monomer

Zeta potential [mV]Particle size [nm]Styrene

–44.8

340

MMA

0.00

1000

BMA

–38.8

900

FE-SEM photographs of polymeric particles prepared by AIBN with the following monomers at
tr = 360 min: (a) styrene; (b) MMA; (c) BMA. When vinylcyclohexane was used as a monomer, the particle was not synthesized.

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the SFEP using AIBN.
Secondary, the SFEP of MMA using AIBN was examined according to the experimental recipes listed inTable 3. As the SEM image (Fig. 8b) showed, the synthesized particles were spherical and the average size wasabout 1.0 μm. However, the dispersion stability was unstable because of the low surface potential, therefore, theparticles were coagulated with each other and sedimented
soon after finishing the polymerization. Another methacrylic monomers, BMA, which included phenyl ring
(Fig. 1b), were polymerized in SFEP replacing MMAs to
improve the dispersion stability. SFEP of BMA with
AIBN was examined according to the conditions listed inTable 3. As indicated in Fig. 8c and Table 4, the particles
with a size of 0.90 μm and a zeta potential of –38.8 mV
were synthesized under the same conditions. This zeta
potential would be originated from pi electron cloud in
BMA monomer (Yamamoto T., 2013).
Finally, 4-fluorostyrene, whose pi electron density inthe phenyl ring was smaller compared with styrene monomer because the electron could be attracted by functionalgroup of fluorine atom from the pi electron cloud on thephenyl ring, was applied to the system of SFEP by AIBN
as a monomer. 4-Bromostyrene, or 4-chlorostyrene wasalso selected as a monomer in the polymerization for thesame reason. In addition, 2,3,4,5,6-pentafluorovinylbenzene, whose pi electron density on the phenyl ring wasmuch smaller because the five fluorine atoms on the phenyl ring attracted pi electron, and vinylcyclohexane,
which did not have pi electron cloud, were chosen as amonomer for the SFEP. SFEP of these monomers wereconducted by AIBN under the conditions listed in Table 3
at Ce = 0. When vinylcyclohexane was used as a monomer, the particles were not detected by FE-SEM. As sum-Fig. 972

marized in Fig. 9, as the number of fluorine atoms on aphenyl ring increased or the electron negativity of thefunctional group was strengthened, the surface potentialof the particle was reduced with its size larger because theelectron density did not concentrate on phenyl ring but
was delocalized more attracting from the fluorine atoms
and the electron density in the phenyl ring became lower.
Clearly, the electron density in phenyl ring in the monomer was related strongly with the zeta potential of thesynthesized particle through SFEP by AIBN.
From these results, it was possible to think that the particles with good dispersion stability were not able to be synthesized in the SFEP using AIBN and monomer without
the phenyl ring. That was to say the pi electron cloud of thephenyl ring in the monomer was one of the origins of thenegative charge of the polystyrene particles. The present
study made it clear that the electron density of the pi electron cloud in the aromatic monomer used in SFEP influenced the surface charge of the particles prepared with
AIBN (Yamamoto T., 2015). Thus, change of the pi electron density on the phenyl ring in the monomer for SFEP
by AIBN enabled the size of the particle to be controllable.
In this way, the polymeric particles were able to besynthesized even using oil-soluble initiator in SFEP. The
advantage of using oil-soluble initiator in SFEP was thatthe ions were not generated in the bulk. In the case ofionic initiator with high water solubility, although theparticles were charged by the initiator, the counter ionswere in the bulk. Hence, the influence of the ions in thebulk on the experimental results did not need to be considered. The polymer colloid prepared through thismethod using oi-soluble initiator was appropriate for thefundamental research.

Schematic representation for influence of the strength of the pi electron cloud of the aromatic vinyl
monomer on negative charged particle for the SFEP using AIBN.

Tetsuya Yamamoto et al. / KONA Powder and Particle Journal No. 35 (2018) 66–79

Fig. 10 Particle size or zeta potential as a function of themonomer mole fraction of MMA for the soap-freeemulsion copolymerization of MMA and styrene by
V-50.

Fig. 11 Particle size or zeta potential as a function of themonomer mole fraction of MMA for the soap-freeemulsion copolymerization of MMA and styrene by
AIBN.

3.4 Size control by copolymerization in SFEP

Table 5 Zeta potential of the polystyrene particles and particle
size measured by FE-SEM in SFEP using V-50,
AIBN, V-601, and V-59.

In this section, the technique for controlling of particle
size in SFEP was developed by changing the mole fraction of MMA in copolymerization of styrene and MMA
without surfactant. At first, Fig. 10 shows the particle size
or zeta potential as a function of the monomer mole fraction of MMA in the copolymerization of styrene and
MMA using a typical initiator, V-50, under the conditions
listed in Table 3 at Ce = 0. Particle size showed nearly
constant with the mole fraction of MMA increased. The
dispersion stability of the synthesized particles showed sostable, and the zeta potential exhibited no dependency on
the mole fraction of MMA. Positive value of zeta potential of the particles was originated from the functionalgroups of the V-50 water-soluble initiator and so high thatthe coagulation for the enlargement of particle size were
not occurred. Hence, the size of particle became constantas the mole fraction of MMA increased.
In contrast, in the case of this copolymerization by
AIBN, the dispersion stability of the synthesized particle
depended on the monomer used in the copolymerization.
Fig. 11 shows the effect on surface properties of the
MMA monomer ratio to the total monomers for the copolymerization of MMA and styrene; the particle size increased with increasing mole fraction of MMA. The
surface potential of the synthesized particles became
smaller with the mole fraction of MMA increasing because the proportion of phenyl rings in the particle, which
was attribute to the styrene monomers and would be theorigin of the negative charge, decreased. Hence, coagulation between particles during the copolymerization was
promoted for size enlargement as the ratio of MMA increased (Yamamoto T. and Kawaguchi K., 2016).

Initiator

Zeta potential [mV]Particle size [nm]

V-50

53.4

160

AIBN

–44.8

340

V-601

–47.9

310

V-59

–41.5

460

3.5 SFEP of styrene with various oil-soluble
initiators
To study the influence of oil-soluble initiator on particle
properties; zeta potential and particle size, in the SFEP ofstyrene, V-601 or V-59 was used as an initiator according
to the recipe as listed in Table 3 at Ce = 0. The experimental data are summarized in Table 5. Each polymericparticle showed the dispersion stabile at tr > 360 min because of high surface potential.
The atoms of nitrogen and oxygen in negatively polarized were included in V-59 and V-601, respectively. Thus,
they also could function like AIBN initiator. We thoughtthat the AIBN was more hydrophilic than V-59 because
V-59 obtained two more hydrophobic groups, CH2, than
AIBN to prepare more hydrophobic particle and its size
became larger for the coagulation. In the case of the SFEP
using V-601, the electron more can be attracted by thefunctional group of the decomposed initiator, carbonylgroup, from the pi electron cloud on the phenyl ring instyrene monomer because the electronegativity of oxygen
atom was higher than those of atoms composed of the initiators. Hence, the surface potential of the particles by73

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V-601 was the highest in Table 5 to synthesize the smallest particle among oil-soluble initiators in the present research. These experimental data suggested that thesurface properties of the particle prepared through SFEP
with oil-soluble initiator were controlled by electronegativity of the component atoms of the initiator.
These experimental data showed one of the reasons
why the particles with negative charge was synthesized in
SFEP even using AIBN, although it was not clarifiedcompletely yet. In addition, the functional group decomposed from the oil-soluble initiator or changing the electron density of the phenyl ring by substituent group of thephenyl ring could explain the results about surface properties of the particles prepared with oil-soluble initiators,
qualitatively. Hence, it was found that the pi electron
cloud on the phenyl ring in the monomer was related
strongly with negative value of zeta potential of the polystyrene particle prepared through SFEP with AIBN.

3.6 Size control by electrolyte in SFEP
On the basis of the above experimental data, discussion, and proposed growth mechanism, oil-soluble initiator enabled the surface potential of the synthesizedparticles to be smaller and the coagulation to be occurred
easily during growth process to make the size enlarged.
To study the influence of cationic ion on particle size,
SFEP of styrene with potassium chloride, calcium chloride, or aluminum chloride at Ce = 0.7 mmol/L was performed for 360 min using AIBN by the experimental
recipes listed in Table 3. Fig. 12 shows the FE-SEM photographs of the synthesized polystyrene particles. It was
found that the sizes became larger with the help of electrolyte compared with Fig. 8a. The addition of an electrolyte helped to reduce the surface potential and theelectrical double layer by counter ions against the chargeof the particles, as DLVO theory indicated (Verwey E.J.W.
and Overbeek J.T.G., 1948), hence, the surface potentials
were reduced. Repulsive interactions between the particles formed in the bulk were weakened, and coagulations
between the particles occurred easily, so the size of theparticle became larger according to our proposed growthmodel (Yamamoto T. and Kawaguchi K., 2015; Yamamoto

T. et al., 2006b; Yamamoto T. and Yokoyama T., 2015).
As Schulze-Hardy rule indicated (Overbeek J.T.G., 1980),
the coagulating effect was larger at the same concentration of electrolyte with increasing the valence of the ion(Verwey E.J.W. and Overbeek J.T.G., 1948). Here, as divalent or trivalent electrolytes, calcium chloride or aluminum
chloride was applied to the SFEP to research the coagulation effect on particle growth. FE-SEM images in Figs. 12b
and c show the particles synthesized at tr = 360 min by
SFEP with calcium chloride and aluminum chloride, respectively, under the condition of Ce = 0.7 mmol/L. The
size of the particles prepared with calcium and aluminum
chlorides became enlarged compared with those preparedwith potassium chloride, compared with Fig. 12a. Particles with a number-averaged size of 2.17 μm and a Cv of
11.1 % were able to be synthesized even at tr = 360 min,by the addition of aluminum chloride as shown in
Fig. 12c. These data showed that the size of particle waslarger with the valence of electrolyte increasing, which
agreed with the DLVO theory from the point of the coagulation.
Similarly, the previous research showed that an electrolyte, such as sodium chloride, helped the silica particle
size to be enlarged (Nakabayashi H. et al., 2010). The coagulation process controlled by the solubility of the initiator and the electrolyte concentration in the aqueous phase
played an important role to make micron-sized particles
in SFEP.
Fig. 13 shows the influence of the concentration of potassium chloride on size of the particle synthesized by
SFEP with AIBN for 360 min changing the concentrationof potassium chloride from 0.007 mmol/L to 7 mmol/L,under the experimental conditions in Table 3. It was
found that the particle size became larger with the concentration increasing. When the concentration of potassium chloride was at Ce = 7 mmol/L, a number-averaged
size and Cv of the synthesized particles were 2.04 μm and
5.4 %, respectively. This experimental data showed thatthe reaction time for making micron-sized monodispersed
particles in a one-batch system was reduced. Thus, in thesystem of SFEP of styrene using AIBN, controlling thesize of the polystyrene particles size was achieved changing the valance of electrolyte and its concentration.

Fig. 12 Effect of the following electrolyte at the concentration of 0.7 mmol/L on particle size through SFEP ofstyrene using AIBN. (a) KCl (Dp = 0.97 μm); (b) CaCl2 (Dp = 1.04 μm); (c) AlCl3 (Dp = 2.17 μm).

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The amount of polymeric radicals at the beginning of
the polymerization using AIBN was much smaller thanthat of V-50 because both the decomposition rate and water solubility of AIBN were much smaller than those of
V-50, as listed in Table 1. Hence, the number of particles
at the beginning of the polymerization of AIBN was muchsmaller than that at the beginning of the polymerizationof V-50, and the consumption rate of the monomer was
smaller in the case of AIBN. This makes it possible tothink that the size was smaller, Dp = 0.23 μm, even whenthe electrolytes were added to the system by V-50 because
the number concentration of final particles in the polymer
colloid using V-50 was larger, and the period for particle
growth was reduced. Secondary particles were formed
continuously in the bulk and deposited on the large parti-

cle surface to make a contribution to particle growth inboth cases. However, the rate of generation of polymeric
radicals in the case of SFEP by AIBN was so slower thatparticles continued to grow for a longer time and became
larger. Also, the electrolyte in the system worked like acatalyst for promotion of the particle growth because secondary particles hetero-coagulations were occurred forthe growth efficiently by reduction of the thickness of theelectrical double layer, and prevented their self-growth.
This technique using an oil-soluble initiator and electrolyte for the preparation of micron-sized particles in water
would be effective in the field of industry, because organic
solvents and surfactants were not included in the system.
From these experimental results, it was possible to saythat the cationic ion in electrolyte played an importantrole to control particle size in SFEP using oil-soluble
initiator (Yamamoto T. and Kawaguchi K., 2015). Furthermore, nano particles with the size under 100 nm
were successfully synthesized taking ionic radius of thecounters ion in a water-soluble initiator into consideration(Yamamoto T. and Yokoyama T., 2015).

3.7 Size control using oil- and water-soluble
initiators in SFEP

Fig. 13 Influence of concentration of potassium chloride on
particle size through SFEP of styrene using AIBN. (a)Ce = 0.007 mmol/L (Dp = 0.78 μm); (b) Ce = 7 mmol/L(Dp = 2.04 μm).

From the results obtained so far, oil-soluble initiators
played the same role as typical initiator in the conventional SFEP. In this section, SFEP of styrene using bothoil- and water-soluble initiators was examined. To study
the effect of the concentration of V-501, Ci, on particle
properties, SFEPs of styrene were carried out changing Ci
at the constant concentrations of styrene monomer and
AIBN. The reason why V-501 was selected was that theparticles were synthesized in the SFEP using water-­soluble initiator with carboxyl groups at high pH becauseof ionized initiator radicals derived from the initiators (GuS. et al., 2004; Moribe H. et al., 2011; Yamada Y. et al.,2005). It was confirmed that the particles were not able tobe formed independently by V-501 in normal water.
Hence, the polystyrene particles were synthesized by
AIBN in this system. As shown in Fig. 14, the particle
size became enlarged as Ci was increased because of theFig. 14 SEM images of polystyrene particles through SFEP using AIBN with V-501 at the following concentration: (a) Ci = 0.7 mmol/L (Dp = 0.80 μm); (b) Ci = 1.4 mmol/L (Dp = 0.86 μm); (c) Ci = 2.0 mmol/L(Dp = 0.95 μm).

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reduction of surface potential with low pH. Similarly, theparticle size became larger through the hetero coagulation
mechanism even increasing the concentration of initiatorin the conventional SFEP of styrene by water-soluble initiator, such as V-50 and potassium persulfate (Goodall
A.R. et al., 1977; Munro D. et al., 1979; Yamamoto T. etal., 2004). This kind of growth improvement using V-501
could also be accepted with the hetero coagulation (Liu B.
et al., 2017; Yamamoto T. et al., 2016). Increase of theconcentration of oil-soluble initiator made the monomer
phase solidified furthermore. Thus, the addition of water-soluble initiator to the SFEP using oil-soluble initiator
was effective for making the particle size enlarged.

4. Conclusions
The molecular-scale investigation on the growth process of polystyrene particles in SFEP with a cationic andwater-soluble initiator by in-situ AFM method gave us
some followings at least qualitatively.
• Tiny polymeric particulates were generated in the bulk
throughout the polymerization, and their deposition on
the larger particle surface resulted in the particle growth.
• The particle size was increased with the water-soluble
initiator increased according to our proposed growthmechanism through hetero coagulation.
• Even though the tiny polymeric particulates were in thebulk, the particle growth was not observed when themonomers were consumed. The roughness of the surface depended on the balance of the polymeric nanoparticulates and the amount of monomers dosed.
SFEPs of aromatic vinyl monomer using oil-soluble
initiators were carried out to develop the technique forcontrolling particle size. Preparation of micron-sized
polystyrene particles through SFEP using oil-soluble initiators with electrolytes or water-soluble initiator wasachieved. The conclusions were as followings.
• When an oil soluble initiator, such as AIBN, V-59, and
V-601, was used in SFEP of styrene, the initiator was
dissolved a little in water and the monodispersed polymeric particles were prepared as the conventional
SFEP. The monodispersed particles showed negative
charges, which would be originated from the pi electron density of phenyl ring in styrene and the polarization of the functional groups decomposed from theoil-soluble initiators. Thus, even oil-soluble initiator
was useful for SFEP assuming that the negative charges
were given to the synthesized particles by aromatic vinyl monomer used in the polymerization and made acontribution to keeping their dispersion stability good.
• Surface charge and particle size were able to be controlled changing the pi electron density of aromatic vinyl monomer with functional groups.

76• Addition of an electrolyte was an effective method forenlargement of particle size because the secondary particles formed in the bulk made an contribution to particle growth through hetero-coagulation by reduction of
surface potential, and prevented their self-growth. The
larger effect by this method was obtained in the case of
the polymerization by an initiator with lower water solubility.
• The particle size became larger with the concentrationof electrolyte increasing in SFEP with an oil-soluble
initiator.
• At the same concentration of electrolyte for enlargement of particle size in SFEP, the coagulation for particle growth effect became larger with the valence of theelectrolyte increasing.
• Particle size in SFEP of styrene using AIBN was controllable changing the valence of electrolyte and its
concentration.
• When the copolymerization of styrene and MMA using
AIBN in the soap-free system, the surface charge andparticle size could be controlled changing the monomer
fraction of MMA.
• In addition of a water-soluble initiator, V-501, to thesystem using AIBN, the particle size became larger due
to the grow promotion through coagulation between
particles because of the reduction of surface potential
by weak acid of V-501 as the concentration of V-501
was increased and the polymerization was proceeded.
From the above conclusions, it was possible to say thatthe technique for control of size of the particle was developed through the polymerization in SFEP using electrolyte or initiators or combination of monomers with andwithout phenyl ring or water- and oil-soluble initiators.

Acknowledgement
This study was financially supported in part by Grantsin-Aid for Young Scientists (B) (No.23760721) and Grantin-Aid for Scientific Research (C) (No.25420817) from the
Ministry of Education, Culture, Sports, Science andTechnology of Japan.

Nomenclature
Ce

concentration of electrolyte (mmol/L)Ci

concertation of V-501 (mmol/L)

Dp number-averaged particle size (μm)
hdistance between surfaces (nm)F

force (nN)trreaction time (min)Tetsuya Yamamoto et al. / KONA Powder and Particle Journal No. 35 (2018) 66–79

References
Anon., Product Bulletin V-50, Wako Chemicals, USA, 1985.
Arai M., Arai K., Saito S., Polymer particle formation in soapless emulsion polymerization, Journal of Polymer Science:
Polymer Chemistry Edition, 17 (1979) 3655–3665.
Arita T., Kanda Y., Hamabe H., Ueno T., Watanabe Y.,
Higashitani K., In situ morphology of cationic flocculants
adsorbed on surfaces and their interaction forces investigated by atomic force microscopy, Langmuir, 19 (2003)
6723–6729.
Arita T., Kanda Y., Higashitani K., In situ observation of single
polymers adsorbed onto mica surfaces in water, Journal of
Colloid and Interface Science, 273 (2004) 102–105.
Feeney P.J., Napper D.H., Gilbert R.G., Coagulative nucleationand particle-size distributions in emulsion polymerization,
Macromolecules, 17 (1984) 2520–2529.
Fitch R.M., Ed., Polymer colloids: A comprehensive introduction, Academic Press, London, 1997.
Goodall A.R., Wilkinson M.C., Hearn J., Mechanism of emulsion polymerization of styrene in soap-free systems, Journal of Polymer Science: Polymer Chemistry Edition, 15(1977) 2193–2218.
Gu S., Akama H., Nagao D., Kobayashi Y., Konno M., Preparation of micrometer-sized poly(methyl methacrylate) particles with amphoteric initiator in aqueous media, Langmuir,
20 (2004) 7948–7951.
Gu S.C., Inukai S., Konno M., Preparation of monodisperse,
micron-sized polystyrene particles with an amphoteric initiator in soapfree polymerization, Journal of Chemical
Engineering of Japan, 35 (2002) 977–981.
Hahn J., Webber S.E., Deposition of cationic polymer micelles
on planar SiO2 surfaces, Langmuir, 20 (2004) 4211–4219.
Harkins W.D., A general theory of the mechanism of emulsion
polymerization, Journal of the American Chemical Society,69 (1947) 1428–1444.
Hergeth W.-D., Lebek W., Stettin E., Witkowski K., Schmutzler
K., Particle formation in emulsion polymerization, 2.
Aggregation of primary particles, Die Makromolekulare
Chemie, 193 (1992) 1607–1621.
Kawaguchi H., Functional polymer microspheres, Progress in
Polymer Science, 25 (2000) 1171–1210.
Lamer V.K., Dinegar R.H., Theory, production and mechanismof formation of monodispersed hydrosols, Journal of theAmerican Chemical Society, 72 (1950) 4847–4854.
Liu B., Fu Z., Han Y., Zhang M., Zhang H., Facile synthesis oflarge sized and monodispersed polymer particles using particle coagulation mechanism: an overview, Colloid andPolymer Science, 295 (2017) 749-757.
Lok K.P., Ober C.K., Particle-size control in dispersion polymerization of polystyrene, Canadian Journal of Chemistry,
63 (1985) 209–216.
Moribe H., Kitayama Y., Suzuki T., Okubo M., Effect of stirring rate on particle formation in emulsifier-free, organotellurium-mediated living radical emulsion polymerization(emulsion TERP) of styrene, Polymer Journal, 44 (2011)
205–210.
Munro D., Goodall A.R., Wilkinson M.C., Randle K., Hearn J.,

Study of particle nucleation, flocculation, and growth in theemulsifier-free polymerization of styrene in water by total
intensity light scattering and photon correlation spectroscopy, Journal of Colloid and Interface Science, 68 (1979)
1–13.
Nakabayashi H., Yamada A., Noba M., Kobayashi Y., Konno
M., Nagao D., Electrolyte-added one-pot synthesis for producing monodisperse, micrometer-sized silica particles up
to 7 microm, Langmuir, 26 (2010) 7512–7515.
Overbeek J.T.G., The rule of schulze and hardy, Pure andApplied Chemistry, 52 (1980) 1151–1161.
Overberger C.G., Oshaughnessy M.T., Shalit H., The preparation of some aliphatic azo nitriles and their decomposition
in solution, Journal of the American Chemical Society, 71(1949) 2661–2666.
Qiu J., Gaynor S.G., Matyjaszewski K., Emulsion polymerization of n-butyl methacrylate by reverse atom transfer radical polymerization, Macromolecules, 32 (1999) 2872–2875.
Shouldice G.T.D., Choi P.Y., Koene B.E., Nazar L.F., Rudin A.,
A novel way to study the initial stages of soap-free emulsion polymerizations: The intercalation of polystyrene
oligomers into hydrotalcite, Journal of Polymer Science
Part A: Polymer Chemistry, 33 (1995) 1409–1417.
Smith W.V., The kinetics of styrene emulsion polymerization,
Journal of the American Chemical Society, 70 (1948)
3695–3702.
Song J.S., Chagal L., Winnik M.A., Monodisperse micrometer-­size carboxyl-functionalized polystyrene particles obtainedby two-stage dispersion polymerization, Macromolecules,
39 (2006) 5729–5737.
Song Z.Q., Poehlein G.W., Particle formation in emulsifier-freeaqueous-phase polymerization of styrene, Journal of Colloid and Interface Science, 128 (1989) 501–510.
Svec F., Frechet J.M.J., New designs of macroporous polymers
and supports: From separation to biocatalysis, Science, 273(1996) 205–211.
Talât-Erben M., Bywater S., The thermal decomposition of
2,2'-Azo-bis-isobutyronitrile. Part II. Kinetics of the reaction, Journal of the American Chemical Society, 77 (1955)
3712–3714.
Tseng C.M., Lu Y.Y., El-Aasser M.S., Vanderhoff J.W., Uniform
polymer particles by dispersion polymerization in alcohol,
Journal of Polymer Science Part A: Polymer Chemistry, 24(1986) 2995–3007.
Ugelstad J., Berge A., Ellingsen T., Schmid R., Nilsen T.N.,
Mork P.C., Stenstad P., Hornes E., Olsvik O., Preparation
and application of new monosized polymer particles, Progress in Polymer Science, 17 (1992) 87–161.
Verwey E.J.W., Overbeek J.T.G., Eds., Theory of the stability oflyophobic colloids, Elsevier Publishing Company, New
York, 1948.
Wagner C., Theorie der alterung von niederschlagen durch
umlosen (ostwald-reifung), Zeitschrift für Elektrochemie,
Berichte der Bunsengesellschaft für physikalische Chemie,
65 (1961) 581–591.
Yamada Y., Sakamoto T., Gu S., Konno M., Soap-free synthesisfor producing highly monodisperse, micrometer-sized polystyrene particles up to 6 μm, Journal of Colloid and Inter-77

Tetsuya Yamamoto et al. / KONA Powder and Particle Journal No. 35 (2018) 66–79

face Science, 281 (2005) 249–252.
Yamamoto T., Synthesis of micron-sized polymeric particles insoap-free emulsion polymerization using oil-soluble initiators and electrolytes, Colloid and Polymer Science, 290(2012) 1023–1031.
Yamamoto T., Synthesis of nearly micron-sized particles bysoap-free emulsion polymerization of methacrylic monomer using an oil-soluble initiator, Colloid and Polymer Science, 291 (2013) 2741–2744.
Yamamoto T., Effect of the Amount of π; Electrons in aromatic
monomer on the surface potential of polymeric particles
obtained through soap-free emulsion polymerization using
AIBN, Chemistry Letters, 44 (2015) 1555–1556.
Yamamoto T., Fukushima T., Kanda Y., Higashitani K.,
Molecular-scale observation of the surface of polystyrene
particles by AFM, Journal of Colloid and Interface Science,
292 (2005) 392–396.
Yamamoto T., Harada Y., Fukui K., Yoshida H., Classificationof particles dispersed by bead milling using electrical fieldflow fractionation, Journal of Chemical Engineering ofJapan, 42 (2009) 720–727.
Yamamoto T., Harada Y., Tsuyama T., Fukui K., Yoshida H.,
Classification of particles dispersed by bead milling withelectrophoresis, KONA Powder and Particle Journal, (2011)
125–133.
Yamamoto T., Higashitani K., Growth processes of poly methylmethacrylate particles investigated by atomic force
microscopy, Advanced Powder Technology, 18 (2007) 567–
577.
Yamamoto T., Inoue M., Kanda Y., Higashitani K., AFM observation of growing poly isobutyl methacrylate (PiBMA)
particles, Chemistry Letters, 33 (2004) 1440–1441.
Yamamoto T., Kanda Y., Higashitani K., Nucleation and growth
process of polystyrene particle investigated by AFM,

78

Journal of Chemical Engineering of Japan, 39 (2006a)
596–603.
Yamamoto T., Kawaguchi K., Effect of electrolyte species on
size of particle through soap-free emulsion polymerizationof styrene using AIBN and electrolyte, Colloid and Polymer
Science, 293 (2015) 1003–1006.
Yamamoto T., Kawaguchi K., Relationship between surface
potential and particle size in soap-free emulsion copolymerization of styrene and methyl methacrylate using awater- or oil-soluble initiator, Colloid and Polymer Science,
294 (2016) 281–284.
Yamamoto T., Kawaguchi K., Takahashi Y., Particle size control
in the soap-free emulsion polymerization of styrene by anoil-soluble initiator with a weakly acidic water-soluble initiator, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 502 (2016) 1–5.
Yamamoto T., Nakayama M., Kanda Y., Higashitani K., Growthmechanism of soap-free polymerization of styrene investigated by AFM, Journal of Colloid and Interface Science,
297 (2006b) 112–121.
Yamamoto T., Yokoyama T., Effect of counter ionic radius ininitiator on particle size in soap-free emulsion polymerization of styrene, Chemistry Letters, 44 (2015) 824–825.
Yoshida E., Effect of azoinitiators on nitroxide-mediated photo-­
living radical polymerization of methyl methacrylate, Colloid and Polymer Science, 288 (2010a) 341–345.
Yoshida E., Effects of initiators and photo-acid generators on
nitroxide-mediated photo-living radical polymerization of
methyl methacrylate, Colloid and Polymer Science, 288(2010b) 901–905.
Yoshida H., Nishimura Y., Fukui K., Yamamoto T., Effect of
apex cone shape on fine particle classification of gas-­
cyclone, Powder Technology, 204 (2010) 54–62.

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Author’s short biography
Tetsuya Yamamoto
Tetsuya Yamamoto is an Associate Professor of the Department of Materials Innovation Design Engineering, Nagoya University. After he received his Ph.D. from Department of Chemical Engineering, Kyoto University in 2005, he worked as an AssistantProfessor, Hiroshima University from 2005 to 2014. He was also a guest researcher in
Max Planck Institute for Polymer Research in 2012.
His research is in the field of synthesis of polymer particle and surface control engineering. He received awards for outstanding young researchers from The Society ofChemical Engineering, Japan, from The Society of Powder Technology, Japan, and fromThe Nagai Foundation for Science and Technology.

Ko Higashitani
Ko Higashitani graduated from Department of Chemical Engineering, Kyoto University, Japan in 1968. He worked on Viscoelastic Fluids as a Ph.D. student under the supervision of Prof. A.S. Lodge in Department of Chemical Engineering, University of
Wisconsin-Madison, USA. After he received a Ph.D. degree in 1973, he joined Department of Applied Chemistry, Kyushu Institute of Technology, Japan, as a lecturer, andthen became a professor in 1983. He moved to Department of Chemical Engineering,
Kyoto University in 1992. He is now an Emeritus Professor, Kyoto University.
His major research interests are the correlations between macroscopic behaviours of
colloidal particles in solutions, such as particle formation, particle stability, suspension
rheology etc. with the molecular-scale characteristics of particles which can be evaluatedby the Atomic Force Microscope, and so on

79

KONA Powder and Particle Journal No. 35 (2018) 80–88/Doi:10.14356/kona.2018013

Review Paper

Review; Risk Assessment of Aerosolized SWCNTs,
MWCNTs, Fullerenes and Carbon Black †Toshihiko Myojo 1* and Mariko Ono-Ogasawara 2
1
2

Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, JapanWork Environment Research Group, National Institute of Occupational Safety and Health, Japan

Abstract
In this paper we review the risk assessment of carbonaceous nanomaterials, such as single-wall carbon nanotubes(SWCNTs), multi-walled carbon nanotubes (MWCNTs), fullerenes and carbon black, and summarize elemental
carbon (EC) analyses for the determination of the those nanomaterials, focusing on the inhalation exposure ofairborne nanomaterials. In the reports of hazard assessment, the proposed OELs (Occupational Exposure Limits)of MWCNTs and SWCNTs ranged from 1 to 50 μg/m3. The fullerenes and carbon black seem to be less toxic thanthe CNTs. In the reports of exposure assessment, the aerosol concentrations of MWCNTs and SWCNTs in work
environments were from less than 0.1 to more than 100 μg/m3. The expected minimum concentration of airborne
MWCNTs in the EC analyses was around 1 μg/m3, but the concentrations of EC in ambient particulate matters(APM) were more than 1 μg/m3 in urban environments. The EC analysis introduced in this paper is a convenientmethod to quantify the carbonaceous nanomaterials in the samples, but size-classification of aerosol samples bycascade impactor and observation using electron microscopes are needed to confirm the characteristics of thenanomaterials.
Keywords: nanomaterials, SWCNTs, MWCNTs, fullerenes, carbon black, thermal carbon analysis

1. Introduction
Ten years ago, Maynard (2007) wrote “Nanotechnology
is clearly a concept whose time has come. Yet it is now
being promoted in the scientific and popular press as amajor technological breakthrough, heralding the next industrial revolution.” He also foresaw, “At the same time,
there are increasing concerns that new nanotechnologies
will bring about new risks to human health and the environment.” That is, nanotechnology will have both benefits
and risks. How can we avoid the risks and obtain the benefits? In this paper, we review the risk-management ofcarbonaceous nanomaterials, as shown in Fig. 1.
Carbon black (CB), a representative carbonaceous
nanomaterial, has a long history and is mass-produced
worldwide. Primary CB particles are produced during
partial combustion or thermal decomposition of hydrocarbons by gas-to-particle conversion. The sizes of primary
†
1
2

*

80

Received 24 May 2017; Accepted 7 June 2017
J-STAGE Advance published online 31 Augest 2017
1-1, Iseigaoka, Yahatanishi-ku Kitakyushu-shi, Fukuoka, 807-0804,
Japan
6-21-1, Nagao, Kawasaki, Kanagawa, 214-8585, Japan
Corresponding author: Toshihiko Myojo;
E-mail: tmyojo@med.uoeh-u.ac.jp
TEL: +81-93-691-7459 FAX: +81-93-602-1782

particles range from 10 nm to 100 nm. A few to many tensof primary particles immediately form highly branchedchains of primary particles called aggregates. CB is added
to rubber to reinforce final products and is also used as apigment for printing ink, paints and toners. Other carbonaceous nanomaterials, such as fullerenes and carbon
nanotubes, have been developed recently and supplied tomarkets.
Kroto et al. (1985) determined the atomic structure of
C60 fullerene having the same geometry as soccer ball,and since then there have been many studies about fullerene derivatives in the fields of chemistry and pharmacology. C60 fullerene is soluble in organic solvents, such as
toluene and tetrahydrofuran, but insoluble in water. Purified C60 fullerene forms a dense molecular crystal structure (brown powder), not a random-shaped agglomerateof the single molecule of C60 fullerene.A sensational study
on nano-risk reported that C60 fullerenes induced oxidative stress in the brain of juvenile largemouth bass, butlater the authors admitted that the results were mainly
affected by the tetrahydrofuran used as a dispersant of
C60 fullerene (Oberdörster, 2004; Zhu et al., 2006).
Carbon nanotubes (CNTs) possess unique properties
and have been the focus of extensive research originatedby Japanese scientists (Endo, 1988; Iijima, 1991) during
the last two decades. CNTs are fiber-shaped substances

Copyright © 2018 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/).

Toshihiko Myojo et al. / KONA Powder and Particle Journal No. 35 (2018) 80–88

Fig. 1

Carbonaceous nanomaterial in this review.

that consist of graphite hexagonal-mesh planes (graphenesheets) that present as a single-layer or in multiple layers.
Tubes with single-wall structures are called single-wallcarbon nanotubes (SWCNTs), and those with multi-wallstructures are called multi-walled carbon nanotubes(MWCNTs). The physical properties of SWCNTs and
MWCNTs, including high tensile strength and conductivity, make them increasingly desirable for manufacturingand medical applications (Maynard, 2007). Carbon nanofiber (CNF) is also used as a general term of the products,
such as VGCNF (Vapor Grown Carbon Nanofiber). Carbon nanofibers with graphene layers wrapped into perfectcylinders are called CNTs.
Hazard assessment and exposure assessment are essential elements in the risk-assessment and risk-managementof nanomaterial production. Occupational exposure limits(OELs), key issues in hazard assessment, are determinedby toxicological studies using laboratory animals, such asrats and mice, if epidemiological data are not available
especially for nanomaterials. The Japan Society for Occupational Health (JSOH, 2015) defined “Occupational Exposure Limit-Mean (OEL-M) for mean concentration of achemical substance is defined as the reference value to themean exposure concentration at or below which adverse
health effects caused by the substance do not appear in
most workers working for 8 hours a day, 40 hours a week
under a moderate work-load”. The mean exposure concentration can be determined as the 8-hour time-weighted
average (TWA) concentration of target materials.
For exposure assessment, we need analytical techniques for monitoring the concentrations of target nanomaterials in the ambient contaminants. Frequently, we
have not suitable OELs or the monitoring techniques
ranged from 1/10 level of OELs for the nanomaterials.

2. Health effects of carbonaceous nanomaterials
2.1 Carbon black
CB was the most examined nanomaterial in the past.
Several studies have shown that inhaled CB particles induce lung tumors in rats when they are administered atdoses that cause particle overload in the lungs, as well as
chronic inflammation and epithelial hyperplasia. The In-

ternational Agency for Research on Cancer (IARC) has
classified CB as possibly carcinogenic to humans (Group
2B; IARC, 1996; 2010). Elder et al. (2005) reported that
this evaluation was based on inadequate evidence in humans, but sufficient evidence in experimental animals. In
the case of human epidemiological evidence, U.S. studies
on cancer in carbon black workers showed no excess oflung cancer. Rats, mice, and hamsters were exposed for
13 weeks to inhaled CB, and, based on the results, a subchronic No-observable-adverse-effect-level (NOAEL) of
1 mg/m3 respirable CB (Printex 90) can be assigned tofemale rats, mice, and hamsters.
Sager et al. (2009) reported that pulmonary responses
to the instillation of ultrafine CB (Printex 90) to rats werecomparable to equivalent particle surface area doses ofultrafine titanium dioxide, concluding that ultrafine titanium dioxide appears to be more bioactive than ultrafine
CB on an equivalent surface area of particles on the delivered basis.
A short-term (5 consecutive days) inhalation study using rats (Ma Hock et al., 2013) was conducted to compare
the effects of different carbon-based materials with different structures. No relevant toxicity was observed for
CB (larger size than Printex 90) of 10 mg/m 3, but
MWCNT of 0.5 mg/m3 induced lung toxicity.
At present, the Japan Society of Occupational Healthrecommends that the OEL of CB should be 1mg/m3 as the
respirable fraction (JSOH, 2015).

2.2 Fullerene
The first assessment of the toxicity resulting from inhalation exposures to C60 fullerene nanoparticles andmicroparticles found minimal changes in the toxicological
endpoints examined (Baker et al., 2008).
In a project (P06041, Risk assessment of manufactured
nanomaterials) of Japanese New Energy and Industrial
Technology Development Organization (NEDO), intratracheal instillation (IT) and inhalation (IH) studies on rats
exposed to C60 suggested that well-dispersed fullerenes
do not have a strong potential of neutrophil inflammation(Morimoto et al., 2010), and the pulmonary inflammation
pattern after exposure to C60 was slight and transient in
the pathological features of rat lungs. (Ogami et al., 2011)
The half-life of intratracheally instilled C60 (0.1 to 1 mg/rat)
was 15–28 days; a short period compared with othernanomaterials (Shinohara et al., 2010). An OEL of
0.39 mg/m3 was adopted for fullerenes in a report by the
NEDO project (Nakanishi, 2011).

2.3 Carbon nanotubes
The continuing increase in CNT production will leadto heightened risks of occupational exposure, raising con-81

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cern that CNT exposure via inhalation, ingestion or dermal contact will lead to harmful effects (Donaldson et al.,2006). Many in vivo experimental studies have been conducted to assess the potential effects of MWCNTs.
In the NEDO project, MWCNTs and SWCNTs were
evaluated in IH tests and/or IT tests using rats (Nakanishi,
2011), and the biological results from the project were
published by Kobayashi et al. (2010) and Morimoto et al.
(2012). In one specific result of the project, Lee et al.
(2013) analyzed the data of rat lungs administered two
samples of MWCNTs (Nikkiso) with different average
lengths derived from one bulk sample (44 nm in diameter)
by IT and found that, based on histopathological changes,
the pulmonary surfactants and inflammation scores of thelungs were significantly higher by MWCNT-Long (3.4 μm
in mean length) than by MWCNT-Short (0.94 μm in mean
length) exposure. Nakanishi et al. (2015) analyzed the relationship between the specific surface area of CNTs andthe rate of increase of Polymorphonuclea leucocytes(PMNs) in Bronchoalveolar-lavage-fluid (BALF) and reported that the larger the specific surface area, the larger
the rate of increase. The authors concluded that there wasonly a common relationship between the specific surface
area and the increased rate of PMNs, regardless of
SWCNTs or MWCNTs. The surface energy or surface
activity of the CNTs was assumed to be the real reason
for this difference, and the surface area reflects this indirectly. Generally, a larger specific surface area of CNTs
means a smaller fiber diameter. An OEL of 0.03 mg/m3
was adopted for SWCNTs, DWCNTs, and MWCNTs as
a common criterion in a report by the NEDO project(Nakanishi, 2011), based on the integration of IT and IH
tests. Considering the uncertainties in the data processing, they proposed limiting the period of application of
the OEL to 15 years on the assumption that the values
will be reviewed whenever new data are obtained.
One of the earliest OELs for CNTs was proposed by the
British Standards Institution (2007); they proposed a“benchmark exposure limit” of 0.1 fiber/cm3. Other OELs,
however, were based on mass concentrations of CNT particles as a metric.
The U.S. NIOSH reviewed animal and other toxicological data relevant to assessing the potential non-malignant
adverse respiratory effects of CNTs and CNFs, provided aquantitative risk assessment based on animal dose-­response
data, and proposed a recommended exposure limit (REL)of 0.001 mg/m3 (1 μg/m3) for elemental carbon (EC) as a
respirable mass 8-hour time-weighted average (TWA)
concentration in the NIOSH Current Intelligence Bulletin
65 (2013). Irrespective of many reports on MWCNT toxicity studies from the US NIOSH, the recommended OEL
for CNTs was based on the limit of quantification of
Method 5040 (NIOSH, 2003), a thermal-optical carbon
analysis method for determining airborne exposure to re-82

spirable CNTs.
Pauluhn (2010) selected 0.1 mg/m3 as the NOAEL in a
rat 13-week inhalation study to derive a human-equivalentconcentration, and proposed 0.05 mg/m3 (8-h TWA) as
the OEL for a specific MWCNT (Baytubes).
Ma-Hock et al. (2009) conducted a MWCNT inhalation
test in which rats were head-nose exposed for 13 weeks toconcentrations of 0.1, 0.5, or 2.5 mg/m3. At 0.1 mg/m3,
there was still minimal granulomatous inflammation in
the lung and in lung-associated lymph nodes, while there
was no substance-related systemic toxicity at 2.5 mg/m3.
They did not select a NOAEL for MWCNT (Nanocyl NC7000) from their study.
The Japan Bioassay Research Center conducted a rat
2-year inhalation study of MWCNT (MWNT-7) at concentrations of 0.02, 0.2, and 2 mg/m3. Adenoma and adenocarcinoma in rat lungs were observed dose-dependently
in male rats. Inflammatory responses were observed from0.02 mg/m3 (Kasai et al., 2016). Before publication of thestudy, IARC (Kuempel et al., 2017) classified MWCNT-7
as possibly carcinogenic to humans (Group 2B); andSWCNTs and MWCNTs excluding MWCNT-7 were categorized as not classifiable as to their carcinogenicity tohumans (Group 3). These categories of CNTs may bechanged in the future along with the progress of toxicological studies.

3. Workplace handling of carbonaceous
nanomaterials
Aerosol concentrations of carbonaceous nanomaterials
in work environments are usually measured by online instruments, such as a scanning mobility particle sizer(SMPS), and offline measurement, such as Transmission
Electron Microscopy (TEM), Scanning Electron Microscopy (SEM) and carbon analysis. Online measurement ofparticle size, number, and surface area is convenient, but
the instruments used for these measurements respond to
all particles, not just carbonaceous nanomaterials, and do
not show information on shape/morphology and chemicalcomposition.
Carbon is a common element on the earth and it is noteasy to distinguish the sources of EC in ambient particles,
such as carbonaceous nanomaterials and ambient particulate matter (APM) (see Fig. 2), but it has the merit thatcarbon analysis for the mass concentration of EC is a relatively sensitive and quick procedure from sampling toanalysis.
Kuhlbusch et al. (2006) studied the particle characteristics in reactor and pelletizing areas of CB production. Filters that collected PM2.5 and PM10 at worksites andoutdoor sites within the same production facilities wereanalyzed for EC and organic carbon (OC) to assess andToshihiko Myojo et al. / KONA Powder and Particle Journal No. 35 (2018) 80–88

Fig. 2 Many sources of elemental carbon in work environment
atmosphere.

quantify the magnitude and proportion of the carbon fractions in the total particulate matter in the work areas. The
particle number and mass concentrations in the reactor
and pelletizing areas of the CB production plants appeared to fall within the range of ambient air values, but
the pelletizing areas for CB showed high ratios of EC to
PM10: 60–74 %, compared with 9–16 % for APM.
Fujitani et al. (2008) reported on a work environment
in a C60 production facility in Japan. They used SMPS
and optical particle counter (OPC) for online measurement, and filter sampling and SEM observation for offline
analysis. The particle volume concentration in the coarse
size range (> 2 μm) was higher during the removal offullerenes from the storage tank and/or weighing. The
presence of fullerenes in the filter samples was confirmed
by SEM observation of the morphology of microparticles
collected during the bagging operation.
Takaya et al. (2010) carried out aerosol monitoring in
two types of packing facilities of MWCNTs, where one ofthe packing facilities was manually operated and the otherwas automated, and found that the personal exposures
were 2.39/0.39 (total/respirable) mg/m 3 and 0.29/0.08(total/respirable) mg/m3, respectively. The task, however,
was related to nanoscale particle release and was not observed by real-time aerosol monitors. In further research
by Takaya et al. (2012), micron-size particles containing
MWCNTs were released into the air in a weaving processof MWCNT-coated yarn. The mass concentrations of
total/respirable dust collected by personal sampling were0.159/0.093 mg/m3 (total/respirable). The concentrationsof EC in the respirable mass ranged from 1 to 5 μg C/m3.
Hedmer et al. (2014) quantified the occupational exposures and emissions during arc discharge production,
purification, and functionalization of MWCNTs in alaboratory-scale worksite. In the personal exposure meas­
urements, respirable dust ranged between detection limit
and 93 μg/m3, and EC ranged between detection limit
and 7.4 μg C/m3.
Dahm et al. (2015) assessed exposures to CNT (13sites) and CNF (1 site). Personal breathing zone (PBZ)
and area samples were collected for both the inhalable

and respirable mass concentration of EC, using the
NIOSH Method 5040. The respirable EC PBZ concentrations ranged from 0.02 to 2.94 μg/m3, with a geometricmean of 0.34 μg/m3 and an 8-h TWA of 0.16 μg/m3.
Kuijpers et al. (2016) assessed personal exposure to
MWCNTs during the synthesis and handling of MWCNTs
in a commercial production facility and linked these
exposure levels to specific activities. The exposure levelsof the MWCNTs observed in the production area during
the full scale synthesis of MWCNTs (N = 23) were comparable to levels observed during further handling of
MWCNTs (N = 19); 41 μg/m3 and 43 μg/m3, respectively.
Carbon analysis has also been used to determine the massconcentration of SWCNT aerosols generated (Maynard etal., 2004), the concentration of MWCNT aerosols in alaboratory (Han et al., 2008), and the concentration ofcarbon nanofibers and MWCNTs in factories (Methner etal., 2010; Birch et al., 2002).
There have been other studies to determine the number
concentration of CNTs as asbestos fibers. We think thatmorphological observation by SEM and/or TEM can yield
important data to confirm the presence of CNTs, but thatthe counting of CNT fibers is not a good way to determine
the exposure assessment because the toxicological studies
mentioned above were based on mass concentration anddid not observe any clear toxicological similarity between
CNTs and asbestos fibers. In addition, most CNT particles
observed in work environments are large (micron size)
agglomerates, which should be omitted according to therules of asbestos counting.

4. Analysis of airborne carbonaceous
nanomaterials
In the case of carbonaceous nanomaterials, carbon
analysis has been used to determine the aerosol concentrations mentioned above. The U.S. NIOSH recommended
applying Method 5040, a thermal-optical carbon analysis
method, to determine airborne exposure to respirable
CNT (Birch and Cary, 1996). Method 5040 was originallydeveloped to measure EC concentration to estimate diesel
particulates in work-environments. A similar carbon analysis method that determines the EC concentration in APM
was also published by Chow et al. (1993). Both methods
were originally intended to determine the EC mass generated by combustion processes and focused on the separation of organic carbon and elemental carbon in theparticulates. The concentrations of EC in APM measured
in urban areas of Japan were usually more than 1 μg/m3(Ono-Ogasawara et al., 2009; Kim et al., 2011; Kudo etal., 2011), which value is similar to the level proposed by
the US NIOSH as the OEL for CNT: 1 μg/m3 as EC.
In our pilot study, we obtained samples from quartz fi-

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ber filters at a factory for CNT production. The color of
the obtained samples was almost black, and the automaticfunction of thermal optical split of OC and EC by the carbon analyzer did not work. The samples were also resistant to high temperatures (850 degree C) and remained
after the carbon analysis because the CNT had a graphite
structure and annealed in the inert gas atmosphere. We
decided to stop using the Method 5040, based on the
optical split of OC and EC, and adopted a modified
IMPROVE protocol by Chow et al. (1993). We used themodified IMPROVE protocol at each temperature stage,
defined as OC1–OC4 and EC1–EC3, as shown in Table 1(Ono-Ogasawara and Myojo, 2013). This protocol was adopted for the analysis of CNTs in the reports by Takaya etal. (2010, 2012).
Airborne particle samples on the quartz fiber filters in
the impaction stages of a Sioutas cascade impactor (SCI;SKC Inc., Eighty Four, PA, USA) were observed by SEM.
Fig. 3 shows particles collected on the filter fibers of thestage (> 2.5 μm). The fine and tangled fibers in the debris
must be carbon nanotubes. We assumed that CNTs, inparticular MWCNTs, decomposed at a higher temperature than APM and behaved as micron-size agglomerates
irrespective of the nano-size diameter. In our method, at
first, size-segregated particles are collected using an impactor, and then the EC concentrations of the collectedparticles of each size fraction are measured by carbon
analysis without optical correction. The presence of
MWCNTs is evaluated using factors of both size and theoxidation temperature in the measured data. Airborne
particles were collected using a SCI, and the EC in theparticles was analyzed using a carbon monitor. A schematic diagram of this procedure is shown in Fig. 4(Ono-Ogasawara and Myojo, 2011). The SCI is designed
to collect size-segregated particles in six stages of> 6.6 μm, > 2.5 μm, > 1.0 μm, > 0.5 μm, > 0.25 μm, andsmaller than 0.25 μm at a flow rate of 9 L/min. The middle four stages are called stages A to D, and the final stage
is a back-up filter. A quartz fiber filter (2500QAT-UP,
PALL, Port Washington, NY, USA) was used to collectparticles, as shown in Fig. 4.
Typical cases of simulated MWCNT aerosols and APM
are shown in Fig. 5. The EC of the MWCNTs is localized
at stage A as EC3, and the EC of APM is localized at
backup filter F as EC2. We analyzed several samples fromthe maintenance work of instruments for heat treatmentof MWCNTs: automated packing during and not during
work; and outside of the factory at 5 m from the air inlet
to the factory. These real airborne particle samples at
CNT production facilities showed tendencies somewhere
between the MW1 and APM shown in Fig. 5. The details
were shown in our previous paper (Ono-Ogasawara andMyojo, 2013).
Based on our data, a schematic diagram of the size and84

Table 1 IMPROVE protocol for carbon aerosol analyzer.

Fig. 3

Scanning electron microscopy of MWCNTs suspended
in a workplace air. The bold fibers in the image arefibers of quartz filter. The white bar in the photo shows
10 μm.

EC amounts that evolved at different oven temperatures
could be depicted as shown in Fig. 6 (Ono-Ogasawara
and Myojo, 2013). Fullerene (C60) decomposed easily at a
low temperature (Myojo et al., 2011). SWCNTs and thin
MWCNTs also oxidized at 700 degree C, and the main
proportion was EC2. The MWCNTs oxidized as EC2, as
indicated by the presence of thinner MWCNTs, then EC3
must be an indication of the presence of thick MWCNTs.
Well-produced carbon black (CB) is stable at high temperatures, and EC3 was a main constituent. Fig. 6 showsToshihiko Myojo et al. / KONA Powder and Particle Journal No. 35 (2018) 80–88

Fig. 4 Schematic diagram of sampling and analysis of ambient MWCNT particles.
* Determined by measured data (Ono-Ogasawara and Myojo, 2011). Nominally 75 % (= 15 mm/20 mm).

Fig. 5

Typical size effects on EC2 and EC3 of carbon analysis for typical samples of APM and MW1 (a sample of
MWCNTs). Agglomerates of MWCNTs were detected at large fractions (> 2.5 μm and EC3). EC in a sample ofambient particulate matters were detected at small fractions (< 0.25 μm and EC2). Real samples were mixtures ofthe both graphs. (Ono-Ogasawara and Myojo, 2013)

a general tendency of the appearance of different types ofcarbon from carbonaceous nanomaterials in a carbon
analysis. This tendency depends not only on the graphitization but also on the impurities in each sample, such as
catalytic metals. To apply this method to the workplace, it
is important to know the properties of the target materials
used in each workplace. For measurements using a carbon
monitor, the limit of quantitation is around 1 μg EC on apunched filter. This means stages A to D need to be morethan 1.5 μg EC at each stage. The quantitation limit forthe backup filter is expected to be 5.3 μg on the filter, andthe expected minimum concentration of 2 hours sampling
by SCI should be 1 μg EC/m3.

5. Conclusion
The lifecycle of carbonaceous nanomaterials can be
categorized into the following six stages: manufacturing
or synthesizing; manufacturing of interim products (master batches and dispersed solutions); manufacturing ofproducts (composite, papers or fibers); processing of the
products (cutting or sanding); use of the products; anddisposal/recycling (Ono-Ogasawara et al. 2015). In thesephases of the life cycle, the isolated nanoparticles ornanofibers discussed above may exist only in the first twophases and the last phase. The binding strength between
nanomaterials and base materials of the composite ranges
from weak surface adhesion to chemical bonding. The

85

Toshihiko Myojo et al. / KONA Powder and Particle Journal No. 35 (2018) 80–88

Fig. 6

Estimated 2 dimensional map of size and EC1 to EC3 by
our carbon analysis for MWCNT and other carbonaceous materials. CB: carbon black, APM: ambient particulate matter, df: diameter of MWCNTs. A to D and F
are samples on the stages of SCI. (Ono-Ogasawara andMyojo, 2013)

exposure assessment and risk assessment of nanomaterials should be anticipated at all these stages. The thermal
carbon analysis method with size-segregation of airborne
particles is applicable to the measurement of exposure tocarbonaceous nanomaterials at any stage of the life cycle.
Further validation of the method and examples of its application are needed, however, in order to reach consensus
regarding exposure measurements of carbonaceous nanomaterials.
This review is not a systematic review and mainly focused on reports on the risk assessment of carbonaceous
nanomaterials as conducted by the authors and their coworkers or related work by others.

Acknowledgements
Table 1 and Fig. 5 and 6 in this article are reprinted
from “Characteristics of multi-walled carbon nanotubes
and background aerosols by carbon analysis; particle sizeand oxidation temperature. Advanced Powder Technol.
(2013) 24(1): 263–69 by Ono-Ogasawara, M. and Myojo,
T.” with permission from Elsevier.
Fig. 4 in this article is reprinted from “A proposal of
method for evaluating airborne MWCNT concentration.
Ind Health. (2011) 49(6): 726–34 by Ono-Ogasawara, M.
and Myojo, T.” with permission from Industrial Health.

References
Baker G.L., Gupta A., Clark M.L., Valenzuela B.R., Staska
L.M., Harbo S.J., Pierce J.T., Dill J.A., Inhalation toxicity
and lung toxicokinetics of C60 fullerene nanoparticles and86

microparticles, Toxicological Sciences, 101 (2008) 122–131.
Birch M.E., Cary R.A., Elemental carbon-based method formonitoring occupational exposures to particulate diesel
exhaust, Aerosol Science and Technology, 25 (1996) 221–
241.
Birch M.E., Occupational monitoring of particulate diesel
exhaust by NIOSH method 5040, Applied Occupational
and Environmental Hygiene, 17 (2002) 400–405.
British Standards Institution, Nanotechnologies—Part 2: Guide
to safe handling and disposal of manufactured nanomaterials, (2007) PD 6699-2:2007.
Chow J.C., Watson J.G., Pritchett L.C., Pierson W.R., Frazier
C.A., Purcell R.G., The DRI thermal/optical reflectancecarbon analysis system: description, evaluation and applications in U.S. Air quality studies, Atmospheric Environment Part A General Topics, 27 (1993) 1185–1201.
Dahm M.M., Schubauer-Berigan M.K., Evans D.E., Birch M.E.,
Fernback J.E., Deddens J.A., Carbon nanotube and nanofiber exposure assessments: an analysis of 14 site visits, The
Annals of Occupational Hygiene, 59 (2015) 705–723.
Donaldson K., Aitken R., Tran L., Stone V., Duffin R., ForrestG., Alexander A., Carbon nanotubes: a review of theirproperties in relation to pulmonary toxicology and workplace safety, Toxicological Sciences, 92 (2006) 5–22.
Elder A., Gelein R., Finkelstein J.N., Driscoll K.E., Harkema J.,
Oberdörster G., Effects of subchronically inhaled carbon
black in three species. I. Retention kinetics, lung inflammation, and histopathology, Toxicological Sciences, 88 (2005)
614–629.
Endo M., Grow carbon fibers in the vapor phase, CHEMTECH,
18 (1988) 568–576.
Fujitani Y., Kobayashi T., Arashidani K., Kunugita N., Suemura
K., Measurement of the physical properties of aerosols in a
fullerene factory for inhalation exposure assessment, Journal of Occupational and Environmental Hygiene, 5 (2008)
380–389.
Han J.H., Lee E.J., Lee J.H., So K.P., Lee Y.H., Bae G.N., Lee
S.-B., Ji J.H., Cho M.H., Yu I.J., Monitoring multiwalledcarbon nanotube exposure in carbon nanotube researchfacility, Inhalation Toxicology, 20 (2008) 741–749.
Hedmer M., Isaxon C., Nilsson P.T., Ludvigsson L., Messing
M.E., Genberg J., Skaug V., Bohgard M., Tinnerberg H.,
Pagels J.H., Exposure and emission measurements during
production, purification, and functionalization of arc-­
discharge-produced multi-walled carbon nanotubes, The
Annals of Occupational Hygiene, 58 (2014) 355–379.
IARC Monographs on the Evaluation of Carcinogenic Risks to
Humans, Eds., volume 65, Printing processes and printing
inks, carbon black and some nitro compounds, Lyon,
France, 1996, pp. 149–262.
IARC Monographs on the Evaluation of Carcinogenic Risks to
Humans, Eds., volume 93, Carbon Black, Titanium Dioxide, and Talc, Lyon, France, 2010, pp. 1–413.
Iijima S., Helical microtubules of graphitic carbon, Nature, 354(1991) 56–58.
JSOH (the Japan Society for Occupational Health), Recommendation of occupational exposure limits (2015–2016), Journalof Occupational Health, 57 (2015) 394–417.

Toshihiko Myojo et al. / KONA Powder and Particle Journal No. 35 (2018) 80–88

Kasai T., Umeda Y., Ohnishi M., Mine T., Kondo H., TakeuchiT., Matsumoto M., Fukushima S., Lung carcinogenicity of
inhaled multi-walled carbon nanotube in rats, Particle andFibre Toxicology, 13 (2016) 53.
Kim K.H., Sekiguchi K., Kudo S., Sakamoto K., Characteristics
of atmospheric elemental carbon (char and soot) in ultrafine
and fine particles in a roadside environment, Japan, Aerosol
and Air Quality Research, 11 (2011) 1–12.
Kobayashi N., Naya M., Ema M., Endoh S., Maru J., Mizuno K.,
Nakanishi J., Biological response and morphologicalassessment of individually dispersed multi-wall carbon
nanotubes in the lung after intratracheal instillation in rats,
Toxicology, 276 (2010) 143–153.
Kroto H.W., Heath J.R., O’Brien S.C., Curl R.F., Smalley R.E.,
C60: Buckminsterfullerene, Nature, 318 (1985) 162–163.
Kudo S., Sekiguchi K., Kim K.H., Sakamoto K., Spatial distributions of ultrafine particles and their behavior and chemicalcomposition in relation to roadside sources, Atmospheric
Environment, 45 (2011) 6403–6413.
Kuempel E.D., Jaurand M.-C., Møller P., Morimoto Y.,
Kobayashi N., Pinkerton K.E., Sargent L.M., Vermeulen
R.C.H., Fubini B., Kane A.B., Evaluating the mechanistic
evidence and key data gaps in assessing the potential carcinogenicity of carbon nanotubes and nanofibers inhumans, Critical Reviews in Toxicology, 47 (2017) 1–58.
Kuhlbusch T.A.J., Fissan H., Particle characteristics in the reactor and pelletizing areas of carbon black production, Journal of Occupational and Environmental Hygiene, 3 (2006)
558–567.
Kuijpers E., Bekker C., Fransman W., Brouwer D., Tromp P.,
Vlaanderen J., Godderis L., Hoet P., Lan Q., Silverman D.,
Vermeulen R., Pronk A., Occupational exposure to multiwalled carbon nanotubes during commercial production
synthesis and handling, The Annals of Occupational
Hygiene, 60 (2016) 305–317.
Lee B.-W., Kadoya C., Horie M., Mizuguchi Y., Hashiba M.,
Kambara T., Okada T., Myojo T., Oyabu T., Ogami A.,
Morimoto Y., Tanaka I., Uchida K., Endoh S., Nakanishi J.,
Analysis of pulmonary surfactant in rat lungs after intratracheal instillation of short and long multi-walled carbon
nanotubes, Inhalation Toxicology, 25 (2013) 609–620.
Ma-Hock L., Strauss V., Treumann S., Küttler K., Wohlleben
W., Hofmann T., Gröters S., Wiench K., van Ravenzwaay
B., Landsiedel R., Comparative inhalation toxicity of multiwall carbon nanotubes, graphene, graphite nanoplatelets
and low surface carbon black, Particle and Fibre Toxicology, 10 (2013) 23.
Ma-Hock L., Treumann S., Strauss V., Brill S., Luizi F., Mertler
M., Wiench K., Gamer A.O., van Ravenzwaay B., Landsiedel
R., Inhalation toxicity of multiwall carbon nanotubes in rats
exposed for 3 months, Toxicological Sciences, 112 (2009)
468–481.
Maynard A.D., Baron P.A., Foley M., Shvedova A.A., Kisin
E.R., Castranova V., Exposure to carbon nanotube material:aerosol release during the handling of unrefined single-­
walled carbon nanotube material, Journal of Toxicology
and Environmental Health, Part A, 67 (2004) 87–107.
Maynard A.D., Nanotechnology: The next big thing, or muchado about nothing?, The Annals of Occupational Hygiene,
51 (2007) 1–12.
Methner M., Hodson L., Geraci C., Nanoparticle emission
assessment technique (NEAT) for the identification andmeasurement of potential inhalation exposure to engineered
nanomaterials—Part A, Journal of Occupational and Environmental Hygiene, 7 (2010) 127–132.
Morimoto Y., Hirohashi M., Ogami A., Oyabu T., Myojo T.,
Nishi K.-i., Kadoya C., Todoroki M., Yamamoto M.,
Murakami M., Shimada M., Wang W.-N., Yamamoto K.,
Fujita K., Endoh S., Uchida K., Shinohara N., Nakanishi J.,
Tanaka I., Inflammogenic effect of well-characterized
fullerenes in inhalation and intratracheal instillation studies, Particle and Fibre Toxicology, 7 (2010) 4. DOI:
10.1186/1743-8977-7-4
Morimoto Y., Hirohashi M., Ogami A., Oyabu T., Myojo T.,
Todoroki M., Yamamoto M., Hashiba M., Mizuguchi Y.,
Lee B.W., Kuroda E., Shimada M., Wang W.-N., YamamotoK., Fujita K., Endoh S., Uchida K., Kobayashi N., Mizuno
K., Inada M., Tao H., Nakazato T., Nakanishi J., Tanaka I.,
Pulmonary toxicity of well-dispersed multi-wall carbon
nanotubes following inhalation and intratracheal instillation, Nanotoxicology, 6 (2012) 587–599.
Myojo T., Oyabu T., Nishi K., Kadoya C., Tanaka I., Ono-­
Ogasawara M., Sakae H., Shirai T., Aerosol generation andmeasurement of multi-wall carbon nanotubes, Journal of
Nanoparticle Research, 11 (2009) 91–99.
Myojo T., Oyabu T., Ogami A., Hirohashi M., Murakami M.,
Yamamoto M., Todoroki M., Kadoya C., Nishi K., YamasakiS., Morimoto Y., Tanaka I., Shimada M., Endoh S., Monitoring of C60 aerosol concentrations during 4-week inhalation study using a carbon aerosol analyzer with adjusted
analytical protocol, Journal of Nanoparticle Research, 13(2011) 2063–2071.
Nakanishi J, Risk Assessment of Manufactured Nanomaterials:“Approaches”—Overview of Approaches and Results—
Final Report Issued on August 17, 2011. NEDO Project(P06041) Research and development of Nanoparticle characterization method, Tokyo, 2011, <www.aist-riss.jp/projects/
nedo-nanorisk/index_e.html> accessed 08.06.2017.
Nakanishi J., Morimoto Y., Ogura I., Kobayashi N., Naya M.,
Ema M., Endoh S., Shimada M., Ogami A., Myojyo T.,
Oyabu T., Gamo M., Kishimoto A., Igarashi T., Hanai S.,
Risk assessment of the carbon nanotube group, Risk Analysis, 35 (2015) 1940–1956.
NIOSH (National Institute for Occupational Safety and Health),
Current Intelligence Bulletin 65, Occupational Exposure to
Carbon Nanotubes and Nanofibers, Ohio, 2013, <www.cdc.
gov/niosh/docs/2013-145/pdfs/2013-145.pdf> accessed 08.06.
2017.
NIOSH Manual of Analytical Methods (NMAM), in: PC.
Schlecht, PF. O’Connor (Eds.), Method 5040 update DHHS
(NIOSH) Publication No. 2003-154, Third Supplement to
NMAM, fourth ed., National Institute for Occupational
Safety and Health, Cincinnati, OH, USA, 2003.
Oberdörster E., Manufactured nanomaterials (fullerenes, C(60))
induce oxidative stress in the brain of juvenile largemouth
bass, Environmental health perspectives, 112 (2004) 1058–

87Toshihiko Myojo et al. / KONA Powder and Particle Journal No. 35 (2018) 80–88

1062.
Ogami A., Yamamoto K., Morimoto Y., Fujita K., Hirohashi M.,
Oyabu T., Myojo T., Nishi K., Kadoya C., Todoroki M.,
Yamamoto M., Murakami M., Shimada M., Wang W.-N.,
Shinohara N., Endoh S., Uchida K., Nakanishi J., Tanaka I.,
Pathological features of rat lung following inhalation andintratracheal instillation of C60 fullerene, Inhalation Toxicology, 23 (2011) 407–416.
Ono-Ogasawara M., Myojo T., Kobayashi S., A nanoparticle
sampler incorporating differential mobility analyzers andits application at a road-side near heavy traffic in Kawasaki,
Japan, Aerosol and Air Quality Research, 9 (2009) 290–
304.
Ono-Ogasawara M., Myojo T., A proposal of method for evaluating airborne MWCNT concentration, Industrial Health,49 (2011) 726–734.
Ono-Ogasawara M., Myojo T., Characteristics of multi-walledcarbon nanotubes and background aerosols by carbon analysis; particle size and oxidation temperature, Advanced
Powder Technology, 24 (2013) 263–269.
Ono-Ogasawara M., Takaya M., Yamada M., Exposure assessment of MWCNTs in their life cycle, Journal of Physics:
Conference Series, 617 (2015) 012009.
Pauluhn J., Subchronic 13-week inhalation exposure of rats tomultiwalled carbon nanotubes: toxic effects are determinedby density of agglomerate structures, not fibrillar struc-tures, Toxicological Sciences, 113 (2010) 226–242.
Sager T.M., Castranova V., Surface area of particle administered versus mass in determining the pulmonary toxicity ofultrafine and fine carbon black: comparison to ultrafine
titanium dioxide, Particle and Fibre Toxicology, 6 (2009)15.
Shinohara N., Nakazato T., Tamura M., Endoh S., Fukui H.,
Morimoto Y., Myojo T., Shimada M., Yamamoto K., Tao H.,
Yoshida Y., Nakanishi J., Clearance kinetics of fullerene
C60 nanoparticles from rat lungs after intratracheal C60
instillation and inhalation C60 exposure, Toxicological Sciences, 118 (2010) 564–573.
Takaya M., Ono-Ogasawara M., Shinohara Y., Kubota H.,
Tsuruoka S., Koda S., Evaluation of exposure risk in theweaving process of MWCNT-coated yarn with real-time
particle concentration measurements and characterizationof dust particles, Industrial Health, 50 (2012) 147–155.
Takaya M., Serita F., Ono-Ogasawara M., Shinohara Y., Saito
H., Koda S., Airborne particles in a multi-wall carbon
nanotube production plant: observation of particle emission
and personal exposure 1: Measurement in the packing process, Sangyo Eiseigaku Zasshi, 52 (2010) 182–188.
Zhu S., Oberdörster E., Haasch M.L., Toxicity of an engineered
nanoparticle (fullerene, C60) in two aquatic species, Daphnia and fathead minnow, Marine Environmental Research,
62 (2006) S5–S9.

Author’s short biography
Toshihiko Myojo
His research interests are the sampling and analysis of airborne particles at workplaces
and biological effects after inhalation of the particles based on in vivo studies.
He was educated at Kanazawa University, B.S. and M.S. in Chemical Engineering. He
got Ph.D. degree (1991) from Kanazawa University. He worked as a researcher at National
Institute of Industrial Health, Ministry of Labour, Japan (1979–2006). He was appointed
to Associate Professor, University of Occupational and Environmental Health, Japan(2006–2010) and then promoted Professor in 2010.

Mariko Ono-Ogasawara
Her research interest is the exposure assessment of hazardous vapors and particles,
especially carbon nanotubes and carbonaceous nanomaterials, in workplaces.
She was educated at Saitama University, B.S. and M.S. in Environmental Chemistry.
She got the Ph.D. degree (2011) from Saitama University. She has been working for
National Institute of Occupational Safety and Health, Japan (JNIOSH), former National
Institute of Industrial Health, Ministry of Labour, as a researcher since 1987. She wasappointed to Director of Work Environment Research group, JNIOSH in 2015.

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KONA Powder and Particle Journal No. 35 (2018) 89–111/Doi:10.14356/kona.2018015

Review Paper

Nanoparticles Carrying Biological Molecules:
Recent Advances and Applications †Suryani Saallah 1,2 and I. Wuled Lenggoro 1,3*
1

Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology, Japan
Biotechnology Research Institute, Universiti Malaysia Sabah, Malaysia
3
Department of Chemical Engineering, Tokyo University of Agriculture and Technology, Japan
2

Abstract
In the past few decades, enormous advances have been achieved in the field of particle technology and the trend
has been shifted from macro to micro and recently to the nanoscale. Integration of nanotechnology andbiotechnology has paved the way to the development of biological nanoparticles, derived from biomolecules, andbiomolecule-nanoparticle conjugates for numerous applications. This review provides an overview of various
types of biological nanoparticles and the methods of their fabrication with primary emphasis on the drying
methods, particularly on the newly emerging technique, the electrospraying. Recent advances in the integration of
biomolecules with nanoparticles in the past five years to present are also discussed. Finally, the application of thebiomolecule-nanoparticle conjugates in various fields including medicals and pharmaceuticals, biosensors andbioelectronics, foods, and agricultures are also highlighted.
Keywords: powder, particle, electrospray, biomaterial, enzyme

1. Introduction
Nanotechnology is a rapidly growing field that deals
with the processing of materials with size less than
1000 nm, from the production to its applications (Jaworek
A. and Sobczyk A.T., 2008). Owing to its large surface
area to volume ratio, the reduction of particle size to nanoscale offers remarkable improvement in the physical,
mechanical, electrical, and optical properties, that is notseen in the bulk materials (Yurteri C.U. et al., 2010).
Breakthroughs in nanomaterial synthesis increased diverse nanomaterials production and subsequently theirapplications.
Nature had provided various types of biomolecules
such as proteins, nucleic acids, lipids, and polysaccharides, which have their own unique properties that can beutilised for the development of nanoparticles (Sperling
R.A. and Parak W.J., 2010). These organic based nanoparticles received little attention in the past; in comparison
with inorganic based such as metals, metal oxides, ceram†
1
2
3

*

Received 12 April 2017; Accepted 4 August 2017
J-STAGE Advance published online 30 September 20172-24-16 Nakacho, Koganei, Tokyo 184-8588, Japan
88400, Kota Kinabalu, Sabah, Malaysia
2-24-16 Nakacho, Koganei, Tokyo 184-8588, Japan
Corresponding author: I. Wuled Lenggoro
E-mail: wuled@cc.tuat.ac.jp
TEL/FAX: +81-42-388-7987

ics and quantum dots where enormous researches andtechnological advancements have been made (Kumar R.
and Lal S., 2014). However, in recent years, considerable
interest has been shown in the utilisation of biological
nanoparticles, derived from biomolecules as an alternative
to the chemically synthesised nanoparticles. This is dueto the need for developing biocompatible and biodegradable nanoparticles in addition to the other advantages offered including ease of availability and non-immunogenic(Sundar S. et al., 2010).
Biomolecules can also be engineered to possess uniquecompositions and functionalities and can be conjugatedwith various types of nanoparticles such as metals andmetal oxides, to complement the unique properties ofnanoparticles with intrinsic features of biomolecules, toyield novel biomolecule-nanoparticle hybrid. To date,many review papers are available in the literature thathighlights the development and application of nanoparticles in various sectors (De M. et al., 2008, Salata O.V.,
2004, Wang E.C. and Wang A.Z., 2014). However, limited
reviews are available for biological nanoparticles and theintegration of nanoparticles with biomolecules. Therefore,
up to date information on the technology and current
trend in the field is required. The present review details
the types of biological nanoparticles, their methods ofsynthesis, the recent advances in the integration of biomolecules with nanoparticles, and the application of
biomolecule-nanoparticle conjugates in medicals and

Copyright © 2018 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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pharmaceuticals, biosensors and bioelectronics, foods,
and agricultures. For the context of this review, only
nanoparticles derived or conjugated with biomolecules
were discussed.

2. Types of biological nanoparticles
Biological nanoparticles are particles with size ranging
from 10 nm to 1 μm, derived from biomolecules or organic compounds. They can be divided into four major
categories which are proteins, nucleic acids, lipids andpolysaccharides based (Kumar R. and Lal S., 2014).
Protein is the predecessor of the naturally occurring
material used for the preparation of nanoparticle, attributed to their unique functionalities and defined primary structure. These features enable various possibilities
for surface modifications and attachment of other compounds such as drugs and therapeutics (Bhunchu S. andRojsitthisak P., 2014; Jahanshahi M. and Babaei Z., 2008).
Additionally, they can be processed in the form of gels,emulsions and dried particles, have greater stability invivo and during storage, and relatively easy to synthesisewith controllable size distribution (Sundar S. et al., 2010),
which allows them to be an ideal material for nanoparticles preparations. To date, wide varieties of proteins havebeen used for nanoparticle formulations including albumin, gelatine, elastin, collagen, gliadin, zein, ferritin(Nitta S.K. and Numata K., 2013) and silk proteins suchas sericin and fibroin (Hazeri N. et al., 2012; Zhao Z. etal., 2015).
Nanoparticles can also be formulated from nucleic acids strands of DNA and RNA. These biomolecules can beengineered to form 3-dimensional nano-scaffolds due tothe simplicity of their primary structure. Furthermore,
nucleic acids have a unique ability to self-assemble into
compact and stable structures with precise control overthe nanoparticle size, geometry, and composition (Panigaj
M. and Reiser J., 2016). The current research in the development of bio-based nanoparticles have shown that the
DNA and RNA nanoparticles can be utilised as scaffolds
and can be tagged with various types of biological andtherapeutic compounds such as aptamers, fluorophores, andoligonucleotides to carry its desired function (Friedman
A.D. et al., 2013; Panigaj M. and Reiser J., 2016).
Lipid based nanoparticles which include liposomes,
nanoemulsions, solid lipid nanoparticles (SLN) and nanostructured lipid carriers (NLC) have emerged as apotential nanoparticulate system and have been recog­
nised among the most promising encapsulant in the nanobiotechnology field (Tamjidi F. et al., 2013). In addition totheir high encapsulation efficiency, lipid nanoparticles
demonstrated longer shelf life and storage stability, hassle-free scaling up from lab to industrial scale, and ability90

to target and entrap compound with different solubility(Weiss J. et al., 2008).
Polysaccharides are naturally occurring carbohydrate
polymers that are linked together by glycosidic bonds.
They can be obtained from plants (e.g. pectin, insulin), animals (e.g. chitosan), and algae (alginates) and also from a
microorganism such as a dextran. Among various typesof polysaccharides, chitosan is one of the most valued
polysaccharides probably due to its permeability enhancing properties. Chitosan, a cationic polyaminosaccharide,
have high-density amino groups and mucoadhesive properties, allowing facile chemical modification and complexation with negatively charged molecules (Sahdev P. etal., 2014). By exploiting the charge mediated ionic interactions, a wide variety of biomolecules such as proteins(Mattu C. et al., 2013), plasmid DNA and antigens as wellas bioflavonoids (Ha H.-K. et al., 2013; Hosseini S.F. etal., 2013) have been successfully incorporated into chitosan nanoparticles. The nanoparticles are commonly
fabricated through ionotropic gelation and self-assemblyof polyelectrolytes, a relatively simple procedure that does
not require the use of organic solvents and operated inmild temperature and pressure condition (Rampino A. etal., 2013; Sahdev P. et al., 2014).

3. Methods to synthesise biological nanoparticles
Synthesis of nanoparticles derived from inorganic compounds such as metal, metal oxides and polymeric materials have been discussed deeply in a number of review
papers. However, only a few reviews are available forthe synthesis of biological nanoparticles. Design and synthesis of biological nanoparticles with desired properties
is an important field of research in nanotechnology to allow applications of such materials in various fields whichconsequently give a positive impact to nature and humanbeing. Recently, different strategies for production ofnanosized materials exist and new techniques are constantly developed (Table 1). In biotechnology context,
several criteria have to be taken into account for the selection of techniques to produce particles with controlledcharacteristics such as uniform size distribution, morphology, high purity, and composition. Additionally, themethod should be simple, inexpensive, and have highthroughput (Peltonen L. et al., 2010). In this section, general overviews of the methods to synthesise biological
nanoparticles which include two steps procedures basedon emulsification, a one-step procedure involving nano-­precipitation, desolvation, and gelation, and through drying methods are presented, with primary emphasis on the
preparation by drying process.

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Table 1 Summary of various types and methods to synthesise biological nanoparticles.
Material

Fabrication method

BSA

Application

Reference

Dynamic aggregation, 20–40 nm
radiation-induced
cross-linking

Drug carrier

Achilli E. etal. (2015)

Cruciferin

Cold gelation~200 nm spherical,
polydispersity index(PDI) of 0.2–0.3

Delivery of bioactive foodcomponents

Akbari A. and
Wu J. (2016)

Chimeric
polypeptide

Genetically encodedsynthesis in E. Coli

60 nm, nearlymonodisperse

Treatment of cancer Conjugateddrug: paclitaxel

Bhattacharyya
J. et al. (2015)

FibronectinElectrospraying

28.2–31.52 nm

Functionally active protein fortissue engineering

Fornari E. etal. (2015)

Zein

Electrospraying

175–900 nm

Encapsulant for food coloring and Gomez-Estaca
ingredientsJ. et al. (2012)

Fluorescentproteins

Liquid nanodispensing (NADIS)

50 nm–microns

Nanodevice (Scanning probe
lithography)

Fabie L. et al.
(2015)

FibroinElectrospraying

80 nm

Wound dressing and tissue
engineering

Gholami A. et
al. (2010)

Whey protein
isolate (WPI)

Homogenisationevaporation

90 nm

Delivery vehicle for beta-­carotene Yi J. et al.
to intestine(2015)

Soybean protein
isolate (SPI)

Homogenisationevaporation

370 nmDelivery vehicle for beta-­carotene Yi J. et al.
to intestine(2015)

Chitosanoligosaccharide/
β-lactoglobulin

Ionic gelation

150–30 nm,
spherical

Delivery of hydrophobic bioactive compounds into aqueousfoods

Ha H.-K. et al.
(2013)

Bioactive
Ionic gelation
peptides/chitosan

150 ± 4.3 nm,
PDI = 0.05 to 0.14

Encapsulant of epigallocatechin-3-gallate (EGCG) for
nanochemoprevention

Hu B. et al.
(2012)

Chitosan550–850 nm, spherical Protein carriers in tissue engiwith some irregularneering
shape particles

Ionic gelation

Particle size andcharacteristics

3.1 Two steps procedure based on emulsifications
Methods for the preparation of biological nanoparticles
based on emulsification strategies have been evolved in
the past decades due to the advancement in the technology and emulsification devices (Kumar R. and Lal S.,
2014). The emulsion system can be in the form of oil inwater (o/w), water in oil (w/o) and oil in oil (o/o), depending on the type of the dispersed phase and dispersion medium. A more complex system based on a combination ofmultiple emulsions has also been synthesised such as water in oil in water (w/o/w), oil in water in oil (o/w/o) andwater in oil in oil (w/o/o). After generation of the emulsion
nanodroplets, nanoparticles can be produced through precipitation induced by various solvent extractions mechanisms such as solvent evaporation, solvent diffusion or
salting-out. Other techniques such as gelation and polymerisation can also be used for converting the emulsions to nanoparticles (Bilati U. et al., 2005; Kumar R.

Mattu C. et al.
(2013)and Lal S., 2014).
Emulsification method offers high encapsulation efficiency and high batch-to-batch reproducibility. Furthermore, nanoparticles obtained through this method usually
have narrow size distribution (Chaturvedi S.P. and Kumar
V., 2012; Pal S.L. et al., 2011). The avoidance of heat
treatment during the preparation step has made thismethod as a useful strategy for encapsulation of highly
thermolabile compounds. However, the presence of residual solvent in the final dispersion is undesirable due toregulatory concern. Therefore, intensive washing procedures are required to eliminate the solvent residue(Chaturvedi S.P. and Kumar V., 2012). Moreover, the application of this method is mainly limited to lipophilicmolecules. Compounds which have limited solubility inorganic solvent require a subsequent addition of excesswater, resulted in dilute dispersion that needs to be concentrated by means of another operation such as filtrationand evaporation (Das S. and Chaudhury A., 2011). The

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particles generation through emulsification have been reviewed extensively by Anton and co-workers (2008) andwill not be discussed in details.

3.2 One step procedures
Nano-precipitation is a method to synthesise nanoparticles based on the interfacial deposition of polymer after
displacement of a semi polar solvent (miscible with water)from a lipophilic solution. Therefore, nano-precipitationis also termed as interfacial deposition or solvent displacement methods. This method was developed by Fessiet al. in the late 1980s (Kumar R. and Lal S., 2014).
Nanoparticles are formed through a quick diffusion of thepolymer solvent such as acetone in the non-solvent or
aqueous phase. The reduction in the interfacial tension
between the two phases resulted in the increase of thesurface area and momentary precipitation of nanoparticles. The process can occur in the absence or presence of
mechanical stirring. This method provides a simple andrapid route for the fabrication of biological nanoparticles
from natural polymers and peptides with high reproducibility, even at low concentration. However, the use of
nanoprecipitation approach is often hampered by the low
nanoparticle recovery yields due to the low concentrationof polymer required and low entrapment efficiency forwater-soluble molecules such as drugs (Bilati U. et al.,2005; Kumar R. and Lal S., 2014).
Desolvation or also known as coacervation, a techniquedesigned by Marty et al. in 1978 is a thermodynamicallydriven self-assembly of proteins that occur based on the
addition of desolvating agents such as salts, alcohol orsolvents (e.g. acetone) in a solution of biomolecules, which
separates and coacervates the molecules in the aqueous
phase. In this process, electrostatic interaction plays a vital role to promote self-assembly of protein (Sundar S. etal., 2010). Variety types of proteins such as albumins (human serum albumin and bovine serum albumin), gliadin
and gelatine, polysaccharide particles such as chitosan,
DNA and oligonucleotides have been fabricated throughthis method (Allouche J., 2013). To improve the stabilityof the nanoparticles and prevent dissolution in water,crosslinking reaction with glutaraldehyde and carbodiimide was usually performed (Sundar S. et al., 2010).
Many proteins have gel forming properties at particularconditions of pH and temperature. These properties enable the proteins to form heat-induced gels through thermal gelation process, attributed to the protein structures(primary, secondary, tertiary and quaternary) and thesurrounding conditions. Under suitable conditions, theprotein molecules will denature and unfold followed by
the rearrangement and aggregation into a 3-dimensional
structure that finds numerous applications in food industry. For charged biomolecules such as chitosan and algi-

92nate, gelation can occur through interactions with small
ions of opposite charges to form nanoclusters that can bestabilised further with the addition of oppositely charged
polyelectrolytes (Allouche J., 2013; Nitta S.K. and NumataK., 2013).

3.3 Preparation by drying process
Environmental considerations have motivated researchers to find alternative methods for synthesis of nanoparticles with the elimination of the use of organic solvents(Allouche J., 2013). To achieve this goal, preparation of
biological nanoparticles through drying method has been
seen as a promising alternative to the conventional methods discussed above. Furthermore, dry formulation of biological nanoparticles offers further stabilisation against
degradation, improves shelf life and ease of handling that
often difficult to achieve in liquid formulation due to thecomplexity of the biological molecules (Haggag Y.A. and
Faheem A.M., 2015).
Besides, nanosuspensions often need to be dried forfurther processing and formulation for example in theform of tablets or capsules. In this regard, drying based
techniques provide a convenient and straightforward
method, as dried nanoparticles can be produced directly
in a single step without the need for further drying steps,
and the dried particles still preserved the unique properties of the original suspension (Peltonen L. et al., 2010).
There are three main strategies to produce biological
nanoparticles through drying methods which are supercritical drying, spray drying and the newly emerging
technique, the electrospraying method which will be discussed in details.

3.3.1 Supercritical drying

Supercritical drying involves utilisation of supercriticalfluid (SCF) as a drying medium (antisolvent) which offers
unique property of having the density and solvating
power of a liquid but with gas-like transport properties(with respect to its viscosity and diffusivity). In most supercritical fluid processing, carbon dioxide (CO2) is used,attributed to its low critical temperature and pressure,nontoxic, non-flammable and environmentally friendly
characteristics as well as availability at low prices (Sellers
S.P. et al., 2001). A number of supercritical techniques are
currently available for production of submicrometer-sized
and nano-sized particles.
The rapid expansion of a supercritical solution (RESS)
typically uses supercritical CO2 to form finely divided dry
thermolabile drugs and pharmaceutical powders. In thistechnique, biological constituents are solubilised in supercritical CO2 which subsequently decompress through a
nozzle into an ambient air. This process created highsupersaturation conditions that promote homogeneousSuryani Saallah et al. / KONA Powder and Particle Journal No. 35 (2018) 89–111

nucleation and precipitation of the biological solutes into
well-dispersed particles. Despite the ability to generate
nano-sized particles, the coalescence mechanism involvedin the free jet promotes particle aggregation into micro-­sized. Besides that, although the process can be conductedin a solvent free environment, the solubility of many
pharmaceutical constituents in supercritical CO2 is verylow (Allouche J., 2013). Therefore, another supercriticaltechnology such as solution enhanced dispersion by supercritical solution (SEDS) has been developed. In thissystem, co-solvents have been used to improve the solubility of the pharmaceutical compounds in CO2 (Zhao Z.
et al., 2015). This method has been used for precipitationof protein nanoparticles such as lysozyme, insulin, andrhDNase from their aqueous solution with the use of ethanol as co-solvent, yielding nanoparticles with size ranging
from 100–500 nm (Chan H.K. and Kwok P.C.L., 2011;
Sellers S.P. et al., 2001). Alternatively, supercritical fluid
antisolvent (SAS) strategy can be applied to exploit thelow solubilities of the solute compounds in supercritical
CO2 by mixing the solution with compressed CO2 to promote crystallisation or by spraying into the compressed
CO2. Organic non-aqueous solvents such as dimethylsulfoxide that have been normally used in the SAS techniqueto enhance miscibility of solute with CO2 at its recrystallisation temperature and pressure, however, compromised
the environmental friendly nature of the CO2. Thus, thismethod may not be favourable for biomolecules processing as it may cause conformational changes to their native
structure (Tabernero A. et al., 2012; Zhao Z. et al., 2015).

3.3.2 Spray drying

Spray drying has been used since the 1980s as an alternative means of fine particles or powders production. The
utilisation of this method for drying of biological compounds was started in the early 1990s when the potentialof therapeutic proteins or drugs delivery through pulmonary route was discovered (Chan H.K. and Kwok P.C.L.,2011). In spray drying, a solution containing biomolecules
is atomised into a plume of fine droplets which subsequently dried in a hot air to form solid particles. The driedparticles are finally collected via a cyclone. The spraydrying technology has been evolved in the past years andmany types of biological solution have been processed
into nanoparticles or nanopowder through this technology
particularly for food and pharmaceutical application.
However, the collection yield of particles generated
through the conventional spray drying method is very
low, resulted from the very small size of the nanoparticles. Recently, a nano-spray dryer has been developed byBÜCHI Labortechnik AG to increase the particle recovery. In this system, tiny droplets with size much smaller
than the conventional spray dryer were generated by using
piezoelectric actuator. The actuator is driven at an ultra-

sonic frequency to provide vibrating energy to a membrane, which causes ejection of millions of nanodroplets
per second. The size of the particles collected depends on
various factors such as the solution properties (e.g. concentration), operating conditions (e.g. feed rate, drying
temperature) and the presence or absence of surfactant(Haggag Y.A. and Faheem A.M., 2015; Lee S.H. et al.,2011). By using this innovative approach, spherical shape
BSA nanoparticles with smooth surface have been successfully produced by Lee S.H. et al. (2011) from BSA
solution in the presence of surfactant (Tween-80). Despite
the technological advancement in the spray drying system, the applicability of such system to produce biologically active particles remains a hot debate. This is mainly
due to the fragile nature of biomolecules when subjected
to hot drying air during the process which may lead toaggregation and loss of biological activity (Mehta P. et al.,2016). The inclusion of surfactant or disaccharide to theheat-sensitive materials such as proteins, peptides and enzymes can help to minimise these effects (Lee S.H. et al.,2011).

3.3.3 Electrospraying

Electrospraying is an electrohydrodynamic atomisationof liquid into uniform sized droplets under the influencedof electrical forces. The phenomenon of the interaction ofliquid with electric field was first reported by William
Gilbert in the sixteenth century who discovered that awater droplet transformed into conical shape when a pieceof amber was held close to it (Yurteri C.U. et al., 2010).
The first attempt to use electrospraying for the productionof protein nanoparticles was demonstrated by Gomez A.
et al. (1998). Insulin was used as a model protein to study
the feasibility of electrospraying to produce monodispersed protein particles with preserved biological activity.
In their work, the electrospraying was conducted in Taylor
cone jet mode with controlled current and flowrate of 64–
100 nA and 0.17–0.38 μL/min, respectively. The size ofthe produced insulin particles was in the range of 98–
117 nm with a doughnut shape. The analysis of receptor
binding properties of the electrosprayed insulin and thecontrol insulin showed identical results, which proved that
biological activity of insulin is preserved upon electrospraying. With these findings, researches involving thegeneration of active particles of biomolecules using theelectrospraying method have emerged rapidly, especiallyfor drug delivery application.
Besides the ability to preserve the bioactive propertiesof the biomolecules, the emerging utilisation of the electrospraying method is also attributed to the other uniqueadvantages offered; the production of monodisperse particles in cone-jet mode which is often difficult to beachieved by the other particle synthesis methods, a reduction in the number of molecular aggregates due to the co-93Suryani Saallah et al. / KONA Powder and Particle Journal No. 35 (2018) 89–111

alescences of droplets with the same polarity, a reductionin the risk of product contamination, can be operated inambient conditions, cost effectiveness and simple operation. In view of these advantages, a few types of biologically active substances including DNA (Lee Y.-H. et al.,2011), proteins such as sericin (Hazeri N. et al., 2012),
fibroin (Gholami A. et al., 2010), cytochrome c (Mortensen
D.N. and Williams E.R., 2015), and α-lactalbumin (α-LA)(Uematsu I. et al., 2004), enzymes such as alkaline phosphatase (ALP) (Avseenko N.V. et al., 2001) and peptide
such as α-cyano-4-hydroxycinnamic acid (Wei H. et al.,2004) have been successfully electrosprayed with preserved biological activity.
Basic electrospraying setup, which consists of a highvoltage supply, metal capillary, and grounded collector,
and the mechanism of particle generation, is shown in
Fig. 1. The four major processes involved in electrospraying are; 1) generation of charged droplets, 2) shrinkage ofthe droplets due to removal or evaporation of solvent, 3)
continual disintegration of the droplets to form dry particles, and finally, 4) collection or deposition of the particles(Lenggoro I.W. et al., 2002; Naim M.N. et al., 2010).
In electrospraying, the particle size and shape can becontrolled by controlling the solution properties such as
conductivity and surface tension and also the electrospraying parameters which include spraying voltage,
flowrate and distance of the needle tip to the collector. In
our group, the electrospraying technique was used to produce cyclodextrin glucanotransferase (CGTase) nanoparticles from its aqueous suspension. It was found that byconducting the electrospraying in cone jet mode andchanging the needle tip to collector distance from 10 to
25 cm, nanoparticles with narrow size distribution can be

Fig. 1

94

obtained and the average particle size was reduced significantly from 201 to 75 nm. The reduction in the particle
size has been shown to improve the CGTase catalytic performance (Saallah S. et al., 2014).

4. Integrated biomolecule-nanoparticle
systems
Biomolecules exhibit nanoscale dimensions comparable
to the dimensions of nanoparticles (Fig. 2). Revolutionaryof nanotechnology and biotechnology have paved the way
to complement these size similarities and intrinsic features of biomolecules with unique properties of nanoparticles to yield novel biomolecule-nanoparticle hybrid ofsynergistic characteristics and functions (Sperling R.A.
and Parak W.J., 2010). Biomolecules also display several
fundamental features that can be utilised as future building blocks for nanoparticle architecture. For example, thenature-evolved multiple binding sites of biomolecules in
addition with its catalytic properties could facilitate thedevelopment of multifunctional nanoparticles (Katz E.
and Willner I., 2004). Recently, substantial research efforts were directed towards developing and extending theapplications of biomolecules by integrating the biomolecules with biological nanoparticles such as polysaccharides and lipids (Liao W. et al., 2016; Rassu G. et al.,2015) and other types of nanoparticles including metals(Chinen A.B. et al., 2015; Politi J. et al., 2015), metal oxides (Cao Y. et al., 2016; Shahrestani H. et al., 2016) andpolymers (Cavalli R. et al., 2011; Lin T.-T. et al., 2016)
through various conjugation strategies (Table 2).

(a) Basic electrospraying setup and (b) Electrospraying mechanism.

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Fig. 2

Nanoscale integration of nanoparticles and biomolecules.

4.1 Strategies for the development of biomoleculenanoparticle conjugates
4.1.1 Functionalisation of nanoparticles withbiomolecules through non-covalentinteractions

Non-covalent biofunctionalisation is a physical conjugation strategy that can be realised through electrostatic,hydrophobic and affinity interactions (Fig. 3) (Yu M.K. etal., 2012). Electrostatic adsorption is useful for the assembly of biomolecules to nanoparticles that are stabilised byanionic ligands such as lipoic acid and citrate in which theinteraction of nanoparticles and the biomolecules rely on
the opposite charged of both materials (Niemeyer C.M.,
2001). Biological nanoparticles can be engineered to havea specific charge to enable interaction with biomolecules.
The recent example is the utilisation of cationic lipid
nanoparticles modified with a supercharged coiled-coilprotein having positively charged arginine residues to facilitate interaction with the negatively charged SiRNA(Rabbani P.S. et al., 2017). Another example is the development of a self-assembled nanocomplex based on fucoidan, a sulphated marine polysaccharide and protamine,a strongly basic protein by utilising the electrostatic interaction between the oppositely charged polysaccharide andprotein (Lu K.Y. et al., 2017). The non-covalent electrostatic complexes between proteins and polysaccharides
can potentially enhance the functional properties by thesynergistic combination of functional properties of bothmaterials, compared to the single biological nanoparticle
system (Hosseini S.M.H. et al., 2015).
In some cases, the strong electrostatic interaction between the charged biomolecules and its host is not always
preferred. As observed by Lebre F. et al. (2016), the strong
binding between positively charged chitosan and negatively charged DNA resulted in low transfection efficiency

in vivo. To encounter this issue, the electrostatic interactions between the cationic chitosan nanoparticles with theanionic DNA were modified by attaching anionic humanserum albumin onto the chitosan nanoparticles surface.
This system enabled the intracellular release of DNA,
thus enhancing the transfection efficiency.
The role of electrostatic interactions in adsorption ofprotein onto inorganic nanoparticles such as silica andmetal oxides has been well described in many studies(Meissner J. et al., 2015). For instance, immobilisation oflysozyme and β-lactoglobulin, a globular protein onto
negatively charged silica nanoparticles and binding of bovine serum albumin and β-lactoglobulin to cationic gold
nanoparticle functionalised with 3,6,9,12-tetraoxatricosan1-1-aminium, 23-mercapto-N,N,N-trimethyl, under
different pH and ionic conditions (Chen K. et al., 2011;
Meissner J. et al., 2015). Generally, the maximum adsorption occurs at the protein isoelectric point. This is due tothe minimum repulsion between the adsorbed protein
molecules at its isoelectric point which allow them tomake a closer packing at the particle surface.
Although extensive investigation on the interactions of
biomolecules such as amino acids, proteins, and peptides
with silica nanoparticles have shown that binding of
biomolecules to silica nanoparticle is mainly driven byelectrostatic interaction, Puddu V. and Perry C.C. (2012)
found that hydrophobic interactions were responsible forthe recognition and adsorption of peptide sequence of different charge on silica at various pH conditions. They also
showed that it is possible to modulate the uptake of biomolecules on nanoparticles by tuning the surface properties and binding environments such as the biomoleculesbulk concentration and pH. Bioconjugation of silica withpeptide sequence having hydrophobic character is favoured
when the surface charge of silica is close to its point ofzero charge (more hydrophobic) (Puddu V. and Perry C.C.,

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Table 2 Summary of integrated biomolecule-nanoparticle systems.
Biomolecule

Nanoparticle

Fabrication
methodConjugation strategy

Application

References(i) Organic-organic nanoparticle conjugates
BSA

Tripolyphosphate-­ Ionic gelation
crosslinked chitosan

Electrostatic interaction, encapsulation

Sustained release ofprotein

Mattu C. et al.
(2013)

Propolis

LipidHigh shear
homogenisation

Entrapment

Nasal drug delivery

Rassu G. et al.
(2015)

D. indusiata
polysaccharide

SeleniumRedox reaction

Encapsulation

Anticancer treatment

Liao W. et al. (2016)

Curcumin

O-carboxymethyl
chitosan/fucoidan

Ionic gelation

Crosslinking

Oral delivery system

Huang Y.C. and
Kuo T.H. (2014)

Quercetin

Chitosan oligosaccharide/
β-lactoglobulin

Ionic gelation

Covalent

Encapsulation of
bioactives

Ha H.-K. et al.
(2013)

CurcuminZein–pectin/
alginate

Electrostatic
deposition

Electrostatic interaction, encapsulation

Functional foods andbeverages

Hu K. et al. (2015)

Beta-carotene

Whey protein
concentrate

Electrospraying

Encapsulation

Encapsulation of
bioactives

López-Rubio A. and
Lagaron J.M. (2012)

Anthocyanin-rich
extract

Whey protein
isolate/beet pectin

Thermal processing

Electrostatic complex- Encapsulation ofation
natural colorants andfood nutraceuticals

Arroyo-Maya I.J.
and McClements
D.J. (2015)(–)-epigallocatechin-3-gallate

Peptide/chitosan

Ionic interaction, hydrophobic association

Encapsulation

Nano-­
chemoprevention

Hu B. et al. (2012)(ii) Biomolecule-polymeric nanoparticle conjugates
BSA

PLGA

Co-axial electrospraying

Encapsulation

Drug delivery

Zamani M. et al.
(2014)

BSA

HPMA/Ac-DAPBoc

One-pot synthesis

Encapsulation

Delivery of platinum
drugs into cancerous
cells

Dag A. et al. (2015)

Cholestrol

Polyamidoamines

Electrospraying

Covalent

Tamoxifen delivery

Cavalli R. et al.
(2011)

ChitosanPolylactic acid/
nifedipine

Emulsion

Encapsulation

Treatment of angina
pectorice and hypertension

Chinh N.T. et al.
(2016)

Serum albumin

PCL/PLGAElectrospraying

Encapsulation

Delivery of therapeutics

Bock N. et al. (2014)

Sorafenib

PEG-PLGA/PLGA
co-polymer

O/W emulsion

Encapsulation

Systemic treatment of Huang X. et al.
liver fibrosis(2016)

Cisplatin

PCL-block-PEGdiblock copolymer

Dialysis, lyophi- Encapsulation
lisation

Treatment of glutaSurnar B. et al.
thione over-expressed (2015)
breast cancer cells(iii) Organic-inorganic nanoparticle conjugates
Lysozyme andβ-lactoglobulin

Silica—Electrostatic interaction

Not specificallymentioned

Meissner J. et al.
(2015)

Hydrophobin
Vmh2

AuNP

One pot synthesis

Covalent

Biomedical

Politi J. et al. (2015)96

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Table 2 Summary of integrated biomolecule-nanoparticle systems (contd.).
Biomolecule

Nanoparticle

Fabrication
methodConjugation strategy

Application

References

Chitosan/Collagen Bioactive glass

Sol-gel/freeze
dryingNon-covalent

Injectable scaffolds
in bone and cartilage
repairMoreira C.D.F. etal. (2016)

Spherical nucleic
acid

AuNP

—

Covalent

Cellular uptake

Chinen A.B. et al.
(2015)DNA

Magnesium phosphate

Water-in-oil
emulsion

Entrapment

DNA vaccine formulation

Bhakta G. et al.
(2014)

Mussel adhesive
proteins

Iron(III)–3,4-dihydroxyphenylalanine(DOPA)

Electrospraying

Crosslinking

pH-responsive drugdelivery Model drug:
Doxorubicin

Kim B.J. et al.
(2015)

Plasmid DNA

Calcium phosphate

Precipitation

Encapsulation

Stem cell uptake andgene transfer

Cao X. et al. (2011)

PepsinAuNP

Chemicalreduction

Covalent-amide
coupling

Analytical sample
preparation

Höldrich M. et al.
(2016)

α-amylase, pectinase, cellulose

Fe3O4

Co-precipitation GA crosslinking

Clarification of fruit
juicesSojitra U.V. et al.
(2016)(iv) Biomolecule-hybrid nanoparticle conjugates
BSA

Ampiphilic polymer Chemical
coated hydrophobic precipitation
silver nanoparticle

Physisorption

To study protein-­
nanoparticle interaction

Guo J. et al. (2015)

LipaseHydroxyapatite-encapsulated-c-Fe2O3

Chemicalprecipitation

EncapsulationCovalentInteresterification ofsoybean oil

Xie W. and Zang X.
(2016)

CurcuminAlbumin–polycaprolactone

Ring opening
polymerisation

Covalent

Drug delivery system Jiang Y. et al. (2016)
for prostate carcinoma therapeutics

Xylanase

Fe3O4/SiO2

Co-precipitation Covalent

Enzymatic clarification of fruit juices

Shahrestani H. et al.
(2016)

Organic fluorescent dye

PVP/SiO2/Fe3O4

Co-precipitation, Encapsulation Elecpolymerization, trostatic interaction
sol–gelBiomedical, analytical and catalytic
application

Viswanathan K.
(2011)

Glucose oxidase

Fe3O4/Polypyrrol

Co-precipitation Encapsulation

Potentiomeric glucose biosensor

Yang Z. et al. (2014)

Trypsin

AuNP/Fe3O4

Solvothermal
reaction

Covalent

Enzymatic digestionof proteins to peptides

Cao Y. et al. (2016)

Aptamers

AgNP/Fe3O4

Redox reaction

Streptavidin-biotin
affinity binding

Detection of Staphylococcus aureus

Abbaspour A. et al.
(2015)v) Self-assembled biomolecule-nanoparticle hybrid
BSA

Copper(II) phosphate

Self-assembly—

Decomposition oforganic dyes inwastewater treatment

Huang Y. et al.
(2015)

α-lactalbumin,
laccase, carbonic
anhydrase andlipaseCopper(II) phosphate

Self-assembly—

Bionsensors

Ge J. et al. (2012)

SericinCopper(II) phosphate

Self-assembly—

Adsorption of heavy
metal ions

Koley P. et al.
(2016)

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bound onto streptavidin functionalised nanoparticles suchas silver and gold (Tauran Y. et al., 2013). By utilising anelectric-field-directed self-assembly method, Hsiao A.P.
and Heller M.J. (2012) have successfully developed a multilayer structures glucose sensor composed of glucose oxidase, horseradish peroxidase and alkaline phosphatase
enzymes conjugated with streptavidin/avidin-biotin
nanoparticles through affinity interaction. The catalytic
activity of the enzymes was preserved after the assembly,
suggesting that the process employed did not have an adverse effect on the enzyme. Affinity interactions can also
be achieved through antibody-antigen binding to allow
assembly of NP-antibody conjugate with its respective
antigen which is beneficial to increase the NP-­antibodyantigen association constant, with respect to the free antibody (Katz E. and Willner I., 2004).
Fig. 3

Non-covalent functionalisation of nanoparticles withbiomolecules.

2012). Hydrophobic interaction can also be utilised toallow binding of biomolecules with protein nanoparticles
having hydrophobic properties such as gliadin as reported
by Joye I.J. et al. (2015). Through fluorescence quenching
and thermodynamic analysis, they found that binding of
gliadin nanoparticles and resveratrol, a polyphenol extracted from a grape skin is predominantly mediated byhydrophobic interactions rather than hydrogen bonding.
Both of the electrostatic and hydrophobic interactions
requires fewer modification steps, thus provide a simple
and rapid route for Biofunctionalisation of nanoparticles.
However, molecular orientations of the physically boundbiomolecules are difficult to control. By introducing specific functional groups on the nanoparticles such as avidin, biomolecules can bound onto the nanoparticles more
effectively through affinity interactions (Zhang Y. et al.,2012). Avidin is a glycoprotein composed of four identicalsubunits which have high specificity and affinity towards
biotin, resulted in a strong affinity interaction. Despite
these advantages, avidin possesses several drawbacks including a high degree of non-specific binding in vivo attributed to its basic isoelectric point and glycosylation,and the high possibility of immunogenicity. Moreover, thestrong avidin-biotin interaction might hinder the releaseof tagged biomolecules from the biotin or avidin. To overcome these issues, extensive research effort has been devoted to develop new variants of avidin from different
sources or through genetic modification (Jain A. andCheng K., 2017).
Streptavidin, a non-glycosylated tetrameric protein, isthe most widely used avidin analogue. Biotinylated proteins such as immunoglobulins and bovine serum albumin, oligonucleotides and single strand DNA have been98

4.1.2 Functionalisation of nanoparticles withbiomolecules through covalent interactions

Conjugation of biomolecules with nanoparticles via covalent interactions can be achieved by means of chemisorption of the biomolecules on the particle surface or throughthe use of a bifunctional linker (De M. et al., 2008).
Chemisorption is a simple chemical reaction that occurs
between thiol group of biomolecules and the nanoparticles through cysteine residues that are present on the surface of the biomolecules (Fig. 4a). If no thiolated residues
available in the native biomolecules, the thiol group canbe introduced chemically onto the outer part of biomolecules using Traut`s reagent (2-aminothiolane) to allow
biomolecules-NP interaction (Fig. 4b) (De M. et al., 2008;
Zhang Y. et al., 2012). The noble metal nanoparticle, particularly gold (Au) nanoparticle is highly reactive toward
thiol group, thus forming a superior Au-S bond. The
strong binding affinity of Au towards thiols has been exploited for conjugation of biomolecules such as DNA,
peptides, antibodies, and proteins onto the nanoparticle
surface (Katz E. and Willner I., 2004; Spampinato V. etal., 2016; Yu M.K. et al., 2012). Conjugation of maltose
binding protein (MBP) to gold nanoparticles funtionalisedwith thiol-modified glucose (TG) self-assembled monolayers has been studied by Spampinato V. et al. (2016).

Fig. 4

Covalent functionalisation of nanoparticles through a)
Cysteine residue; b) Addition of Traut’s reagent.

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Surface chemistry analysis of the gold nanoparticles before and after functionalisation and interaction with TG
and MBP revealed that the reaction of the thiolated gold
nanoparticles with MBP occurred with specific aminoacid residues exist in the protein binding pocket. In another study, Mejias S.H. et al. (2016) have demonstrated
the successful assembly of an idealised protein building
block, the consensus tetratricopeptide repeat (CTPR) into
the nanoparticle surface through thiol chemisorption of
the protein cysteine residues. As a comparison, adsorption of CTPR without cysteine residues on the gold surface was also carried out. They found that direct
adsorption of CTPR having cysteine residues occurs
through a single-point interaction of the thiol-derivative
protein on the gold surface while the adsorption of CTPR
with no cysteine residues proceeds through unspecificmultipoint attachment of the protein.
Covalent binding through bifunctional linkers provide
a versatile means for biomolecules conjugation. Low molecular weight bifunctional linkers which have anchor
groups such as thiols, disulfides and phosphine ligands
containing terminal carboxy, amino or maleimide groups
are commonly used to bind biomolecules to the nanoparticles such as Au, CdS, ZnS, CdSe/ZnS and Ag. Theseanchor groups can be utilised to replace weakly adsorbed
molecules for the nanoparticles stabilisation. Besides,
during the synthesis stage of the nanoparticles, the anchor
groups can be introduced to functionalise the nanoparticles surface for further reactions. Coupling of biologicalcomponents to the ligands occur via carbodiimide-mediatedamidation and esterification, or through reaction withthiol groups (De M. et al., 2008; Niemeyer C.M., 2001).
For the oxide nanoparticles such as SiO2, alkoxy- or halo­silane groups are commonly used to covalently bind thelinkers to the nanoparticles (Katz E. and Willner I., 2004).
In other research done by Mejias S.H. et al. (2016), gold
nanoparticles were attached to the immobilised CTPR
having cysteine residues via the formation of a covalentamide linkage between the terminal amine of the protein
and the carboxylate groups of the gold nanoparticles, resulting in the formation of an ordered monolayer of CTRP
that can be applied in the controlled patterning of gold
nanoparticles.

4.1.3 Encapsulation of biomolecules in polymericmaterials

Polymeric nanoparticles are solid particles that havebeen used extensively as carriers for biomolecules attributed to their unique properties such as can be co-­polymerised, easy to synthesise and the polymer surface
can be modified for biomolecules conjugation (Menon J.U.
et al., 2014).. They can be fabricated in the form of nanospheres and nanocapsules (Fig. 5). The entire mass of thenanospheres composed of a solid polymer and the biomol-Fig. 5Different modes of interaction of biomolecules withpolymeric nanosphere and nanocapsule.

ecules can be attached to the surface or encapsulated
within the particle while the nanocapsules are designed insuch a way that the biomolecules are confined inside a
core-shell structure (Rao J.P. and Geckeler K.E., 2011;
Wang E.C. and Wang A.Z., 2014). In some cases, the bioactive substances can also be adsorbed on the surface ofthe capsule (Jawahar N. and Meyyanathan S., 2012).
Encapsulation is a rapidly growing technology with diverse potential applications particularly in pharmaceuticaland food industries. The major advantage of the encapsulation strategy is the protection of biomolecules against
denaturing environment which might cause undesirable
conformational changes to the biomolecules native structure and function. Moreover, encapsulation allows controlled release of biomolecules at the targeted sites.
Techniques for nanoencapsulation of food and bioactive
compounds have been reviewed comprehensively by
Ezhilarasi P.N. et al. (2013).

4.2 Recent advances in the integration of
biomolecules with nanoparticles
4.2.1 Organic-organic nanoparticle conjugates

Biological nanoparticles form part of many industrial
products, particularly in food, pharmaceutical, and cosmetic industries. One of the most important features of
biological nanoparticles is that they offer relatively simple
means for encapsulation of biomolecules, resulting in theformation of organic-organic nanoparticle complexes. For
instance, encapsulation of β-carotene into whey protein
concentrate (WPC) was achieved by means of electrospraying from aqueous solutions of β-carotene/WPC
mixture at various pH conditions, resulting in a formation99

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of nanocapsule with high encapsulation efficiency andstability against photo-oxidation (López-Rubio A. and
Lagaron J.M., 2012).
Biological nanoparticles derived from a single component of biomolecule have been widely used as cancer chemo-preventive and therapeutic agents. However, thesingle component biological nanoparticle system might
possess a lack of stability and potential toxicity in a cellular system. These challenges can be potentially solved by
conjugation of biomolecules with biological nanoparticle
through strategic functionalisation. Liao W. et al. (2016)
reported that selenium nanoparticles functionalised witha Dictyophora indusiata polysaccharide formed monodispersed nanoparticles with high stability attributed to thehigh electrostatic repulsion between hydrophilic moietieson the surface of the polysaccharide in comparison withthe bare selenium. Moreover, the nanoparticle conjugate
exhibited enhanced selectivity and antiproliferative activity by inducing cell apoptosis.
Strategies of mixing of two or more biological components to yield hybrid biological nanoparticles have also
been reported by several researchers for encapsulation of
biomolecules and bioactives such as curcumin (Huang
Y.C. and Kuo T.H., 2014), quercetin (Ha H.-K. et al., 2013)
and (–)-epigallocatechin-3-gallate (Hu B. et al., 2012) into
chitosan based nanoparticles. This is due to the fact that
nanoparticles formulated from bare chitosan are unstable
and can be easily dissociated at low pH which potentiallyleads to the release of the encapsulated biomolecules. By
mixing the chitosan with other biological compounds
such as fucoidan, β-lactoglobulin, and peptide, hybrid
nanoparticles with remarkable improvement in stability,
encapsulation efficiency and functional properties wereobtained (Ha H.-K. et al., 2013; Hu B. et al., 2012; Huang
Y.C. and Kuo T.H., 2014).
Recently, considerable interests have been shown toutilise hydrophobic protein nanoparticles such as zein for
encapsulation of lipophilic compounds such as curcumin.
However, zein nanoparticles have poor stability against
the changes in environmental conditions such as pH andtemperature. Coating the protein nanoparticle with polysaccharide molecules allow the modulation of an electrostatic interaction and steric repulsion between theparticles, thus improving the nanoparticle stability. The
recent example is the development of zein-pectin/alginate
nanoparticle for encapsulation of curcumin as reported by
Huang X. et al. (2016). The curcumin loaded core-shell
nanoparticles show enhanced water dispersibility and antioxidant activity.

4.2.2 Biomolecule-polymer nanoparticle conjugates

A great deal of effort has now been focused on designing biomolecule-polymer nanoparticle conjugates with
unprecedented properties, driven by the vast development

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of novel bio-conjugation and polymerisation techniques.
Various type of polymeric materials have been investigated either as support or carrier matrix for biologicalcompounds which include poly (ethylene glycol) (PEG),
poly (lactic acid) (PLA), polyglycolides (PGA), poly(lactide-co-glycolides) (PLGA), polycaprolactone (PCL)
and poly(hydroxy butyrate) (PHB) (Panta P. et al., 2014;
Sapsford K.E. et al., 2013). These polymers are mostly
biocompatible and biodegradable and may have other useful properties such as stimulus-responsive function andgood mechanical strength that can be utilised for fabrication of various types of biomolecule-polymer conjugates(Wang E.C. and Wang A.Z., 2014).
Conjugation of polymer with protein such as albuminhas been widely explored for drug delivery applications.
The resulting nanoparticles usually have a biocompatible
and bioactive albumin shell while the core is rich in a hydrophobic polymer that can entrap drugs. This strategy
can aid the delivery of drugs and targeting the cancer
cells. Protein-polymer nanoparticles conjugate consistedof FDA approved thermoplastic hydrophobic polymer ofpoly-methyl methacrylate (PMMA) and bovine serum albumin (BSA) have been successfully synthesised by Ge J.
et al. (2011) for application in drug delivery. This hybrid
nanoparticle with spherical structure and an average sizeof 100 nm was fabricated by using nanoprecipitation
method. The size and surface charge can be tuned by controlling the weight ratio and concentration of both the
BSA and PMMA. Encapsulation of hydrophobic drug, acamptothecin in the BSA-PMMA nanoparticles showed
efficient cell uptake and enhanced antitumor activity.
Since PMMA is a nondegradable polymer, Jiang Y. et al.
(2016) prepared a curcumin loaded albumin-polymer
nanoparticle from a biodegradable polymer of polycaprolactone (PCL) and the performance of this nanoparticle
was compared with PMMA for prostate carcinoma therapy. The fully degradable PCL-based nanoparticles candeliver the drug more efficiently in comparison with the
PMMA-based nanoparticles and effectively limits the tumor growth.
Other work on the synthesis of a protein-polymer hybrid was done by Dag A. et al. (2015) to enhance the delivery of macromolecular platinum drugs into cancer
cells. The polymer was prepared by copolymerization of
N-(2-hydroxypropyl) methacrylamide (HPMA) and Boc
protected 1,3-diaminopropan-2-yl acrylate (Ac-DAP-Boc),
yielded a P(HPMA 14-co-(Ac-DAP-Boc), which was used
as a macromolecular ligand for the conjugation of theplatinum drug. After activation, the polymer-drug was
further conjugated with albumin by exploiting the Cys34
functionality. This albumin-coated nanoparticle shows
superior toxicity to the cancer cell in comparison with thepolymer nanoparticles without protein coating.
A special form of polymeric nanomaterial, a dendrimer,

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is a cationic polymer with well-defined molecular shapeand unique architecture. This type of polymer has highwater solubility and a large number of surface groups
which make them as a versatile nanostructure. Conjugationof protein to dendrimer has been reported by Chanphai P.
et al. (2016). Polyamidoamines (PAMAM) dendrimers
were conjugated with trypsin from bovine pancreas andtrypsin inhibitor from glycine. Stable bindings of the
PAMAM dendrimers with both proteins occur throughhydrophilic and hydrogen bonding as well as Van der
Waals interaction, suggesting that this hybrid system
could be used further enzymatic catalysis study. Besides
that, the PAMAM dendrimers have been studied previously by Menjoge A.R. et al. (2011) for the delivery of
drug to pregnant women, without affecting the fetus byintercepting the drug so that it cannot pass through thefetal membrane.

4.2.3 Organic-inorganic nanoparticle conjugates

Considering the versatile physicochemical properties ofinorganic nanoparticles including wide availability andrich functionality, in combination with their unique op­tical, electronic, and catalytic properties, conjugation of
biological molecules and inorganic nanoparticles haveopened a new route in the development of advanced functional materials with significantly enhanced features andbroad applications. Various inorganic nanoparticles including metals, metal oxides, and quantum dots have been
prepared by various synthetic procedures and hybridised
or immobilised with biomolecules such as DNA, enzymes, and antibodies either through covalent or non-­covalent interactions that have been discussed previously.
Gold nanoparticles (AuNPs) represent one type ofmetal nanoparticles that found numerous applications inimaging, sensing, and nanomedicine. The utilisation of
biomolecules to tune the surface chemistry and theassembly of AuNPs is a very attractive approach for thedevelopment of next generation nanometric complexes.
Politi J. et al. (2015) have shown that hybridisation of afungal protein, namely hyrophobin (HFB) Vmh2 with
AuNPs can be achieved via a simple one step chemical
reduction process, yielding a highly stable HFB-AuNPs
that can interact well with a model protein of BSA andimmunoglobulins. The addition of dicarboxylic acid-­terminated polyethylene-glycol (PEG) during the synthesis process produced hybrid complexes with outer surface
rich in functional chemical groups that can be tailored for
attachments of various compounds.
Integration of enzymes with inorganic nanoparticles
has shown to have a remarkable effect on the enzyme catalytic performance. This is attributed to the extremely
small size of the nano scale material and their unique surface chemistry (Ding S. et al., 2015). For example, covalently bound pepsin on gold nanoparticles via amide

coupling has produced efficient biocatalyst with sufficiently high stability for application in analysis of therapeutic proteins and peptides (Höldrich M. et al., 2016).
Recently, multi-enzyme catalysis was developed by
Sojitra U.V. et al. (2016) by covalently bind three types of
enzymes (alpha-amylase, pectinase and cellulase) on
amino functionalised magnetic nanoparticles for clarification of fruit juices. The tri-enzyme magnetic nanobiocatalyst allows rapid reduction of the fruit juices turbidity, incomparison with the individual enzyme system. Anothermultienzyme-nanoparticle complex was constructed by
Honda T. et al. (2015) by using magnetosome display system to prepare a system that can mimick natural cellulosomes on magnetic nanoparticle. As a proof of concept,
two types of fluorescent proteins which are the green fluorescent and mCherry were initially immobilised on the
MNPs. These proteins showed a close proximity on themagnetic nanoparticles. Later, endoglucanase (EG) and
β-glucosidase (BG) were immobilised on the magnetic
nanoparticles to promote rapid hydrolysis of carboxymethyl cellulose.

4.2.4 Biomolecule-hybrid nanoparticle conjugatesHybrid nanocarrier can be prepared by mixing two or
more components such as magnetic and metal nanoparticles. By using this strategy, properties of both materials
can be merged and enhanced. As recently being reported
by Cao Y. et al. (2016), a magnetic iron oxide nanoparticles were coated with a layer of gold nanoparticles andused for trypsin immobilisation. This system provides arobust carrier for the enzyme. Moreover, the magnetic
feature facilitated separation from the reaction media
and enabled repeated usage of the enzyme. Magnetic nano­particles can also be designed in a form of core-shellstructure by conjugation with other materials such ashydroxyapatite (Xie W. and Zang X., 2016), silica(Shahrestani H. et al., 2016) and polypyrrol (Yang Z. etal., 2014) for the development of novel composites support
for enzyme immobilisation.
A sandwich hybrid nanoparticle has been designed by
Abbaspour A. et al. (2015) by immobilising a biotinylated
primary aptamer on capture probe of a streptavidin coatedmagnetic nanoparticle. A secondary aptamer was coupled
to a silver nanoparticle (AgNP) for the target detection. In
the presence of target bacterium (S. aureus), a sandwich
complex of Apt/S.aureus/Apt-AgNP is formed on themagnetic nanoparticle surface, giving an electrochemicalsignal. This sandwich system combined the unique features of magnetic nanoparticles as a carrier of affinity
ligands for solution-phase recognition, a hassle free magnetic separation and highly sensitive signal amplification
by AgNP.
Hybrid nanoparticles based on polymeric materials
conjugated with protein have also been reported. In the101

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study done by Jiang Y. et al. (2016), bovine serum albumin (BSA) was utilised as a hydrophilic moiety of thehydrophobic maleimide-terminated polycaprolactone
nanoparticles to improve the biodegradability and biocompatibility of the polymer nanoparticle for encapsulation of curcumin.

4.2.5 Self-assembled biomolecule-nanoparticle
conjugatesSelf-assembly is an advanced technology that is capable of integrating different components together spontaneously for the fabrication of the desired hybrid materials.
Proteins can be incorporated into nanostructures during
the growth phase of the inorganic material and a uniqueflower-like structure was obtained as shown in the study
done by Ge J. et al. (2012). The formation of hybrid nanoflowers is believed due to the protein-induced nucleationof copper phosphate crystal during the self-assembly process, which binds the nanocrystal petals together. Incorporation of laccase into the protein-inorganic nanoflowers
resulted in enhanced laccase activity and stability, incomparison with the free enzyme.
Huang Y. et al. (2015) extended this work to explore thepotential applications of the inorganic copper-phosphate
framework of the hybrid nanoflowers by introducing BSA
as the model protein. This copper-phosphate framework
has an intrinsic peroxidise-like activity that promotes thedevelopment of a hybrid material with superior durability
and stability. Moreover, the nanostructure morphology
can be preserved during catalytic reaction, even at hightemperature. The system also has been tested by using
glucose oxidase (GOx) to replace BSA as the protein
component to study the communication between artificial
and natural enzyme. Interestingly, they found that aself-activated cascade reaction could be achieved throughin one integrated system whereby the artificial enzymaticcascade could mimic the natural ones. Through this
newly developed technology, deep understanding of thecomplex enzymatic reactions could be achieved. They
also proposed that this hybrid nanoflowers have potential
to be applied in the decomposition of organic dyes andwaste water treatment.
Most recently, the fabrication of hybrid nanoflowers
with abundant surface porosity has been reported by
Koley P. et al. (2016). Sericin, a silk protein, was used as
the organic component and copper-phosphate as the inorganic counterpart. By tuning the protein concentration,
various morphological structures of the nanoflowers wereobserved. Similar with the BSA-copper phosphate nanoflowers synthesized by Huang Y. et al. (2015), this sericin
hybrid nanoflowers exhibited excellent thermal stability
even after calcination. The calcination process resulted in
the complete evaporation of the sericin molecules which
eventually increase the nanoflowers porosity, thus signifi-

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cantly increased their surface area for adsorption of heavy
metal ions from wastewater.

5. Applications of biomolecule-nanoparticle
conjugates
5.1 Medical and pharmaceutical
The recent development in the field of nanomedicine
particularly in the drug delivery application has led to thediscovery of nanoparticle-based therapeutics for diagnosis
and treatment of diseases such as cancer, diabetes, and allergy. The fundamental characteristics of nanoscale materials such as greater solubility and diffusivity have beenshown to improve drug release characteristic and blood
circulation half-life (Valo H., 2012). Furthermore, thenanoparticle-based drug delivery system allows better
control of drug release to the targeted area which consequently lowers the administration frequency and minimises the possibilities of systemic side effects (Mahapatro
A. and Singh D.K., 2011).
Several studies have been attempted to develop
biomolecule-­nanoparticle conjugates for cancer therapies.
By mimicking the ability of Salmonella enterica serotype
Typhimurium pathogen to reverse multidrug resistance, asemi-synthetic ‘Salmonella nanoparticle mimic’ based ongold nanoparticle packaged with effector protein (SipA)
has been constructed by Mercado-Lubo R. et al. (2016).
The system could suppress the growth of tumour by reducing the P-glycoprotein, a multidrug resistance transporter, at a SipA dose significantly lower than the free
SipA and increases tumour sensitivity to conventional
chemotherapeutics. In another study, conjugation of
prostate-­specific antigen (PSA) to gold nanoparticles hasenhanced the efficacy and sensitivity of the PSA for diagnosis of prostate cancer based on localised surface plasmon resonance (Jazayeri M.H. et al., 2016). Enzyme
prodrug therapy based on horseradish peroxidase (HRP)
immobilised onto mesoporous silica nanoparticles converts
a prodrug (indole-3-acetic acid (IAA)) into cytotoxic radicals, which caused apoptotic tumor cell death in humancolon carcinoma cells as reported by Hung B.-Y. et al.
(2015).
Integration of nanoparticle with biomolecule also
allows the development of three-dimensional scaffolds
based on gelatin-hydroxyapatite hybrid nanoparticles withuniformly distributed nano-topologies for application in
osteogenesis (Yang G. et al., 2017). Interestingly, the particle morphology has shown to have a remarkable effecton bone formation in which the spherical nanoparticles
show the strongest bone formation capacity in comparison
to the nanoparticles with a different shape.
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nanoparticle which are derived from proteins and polysaccharides are promising vehicles in nanoparticle-­
mediated delivery systems (Gan Q. et al., 2005; Hu B. etal., 2012; Nitta S.K. and Numata K., 2013). Encapsulationof dietary phytochemicals, (–) epigallocatechin-3-gallate(EGCG) with highly biocompatible nanoparticles derived
from bioactive peptide/chitosan is able to enhance bioavailability of the EGCG (Hu B. et al., 2012). The EGCG
loaded-­peptide/chitosan nanoparticle could serve as an effective nanochemoprevention in cancer management andprevention.The use of protein nanoparticles as a carrierfor various types of drugs allows the drugs to be transported across the blood-brain barrier (Sundar S. et al.,2010). Binding of drugs to polysaccharide nanoparticles
such as albumin and gelatine could enhance the antitumour function of the drugs (Huang Y.C. and Kuo T.H.,
2014; Jiang Y. et al., 2016; Kobayashi K. et al., 2014). In
an advanced drug delivery system, more types of drugs
could be delivered simultaneously to generate synergistic
therapies of diseases.
One of the major challenges in the intracellular delivery of anti-cancer drugs to a cancer cell is the rapidchanges in pH due to the acidification that occurs in theendosomal compartments. In this viewpoint, a novel strategy has been designed by Kim B.J. et al. (2015) for thesynthesis of pH-responsive drug delivery system by usingmussel adhesive proteins (MAPs)-based iron(III)–3,4-­
dihydroxyphenylalanine (DOPA) nanoparticles. The pH-­
responsive release of drugs was achieved by exploiting
the pH-dependent changes in the coordination stoichiometry of the DOPA complexes. This newly developed system has shown effective cytotoxicity towards cancer cells
and therefore, can be applied further for the diverse controlled-drug delivery application.
With the significant advantages of the nanoscale materials and the advancement made in the drug delivery, several types of the drug-bound biological nanoparticles are
currently under clinical trial and a few are already commercialised such as albumin-bound paclitaxel, which ismarketed as Abraxane, for use in metatstatic breast cancer
treatment. Most recently, Bhattacharyya J. et al. (2015)
have successfully designed a new drug delivery systemfor paclitaxel that outperforms the readily commercialised
Abraxane with 2 times greater systemic exposure and tumor uptake. The system was prepared with a chimeric
polypeptide that could self-assemble spontaneously, producing monodispersed nanoparticle of 60 nm in size. The
chimeric polypeptide-­paclitaxel conjugate has shown nearcomplete tumor regression in breast and prostate cancer
tumor models after single dose injection. These outstanding performances are attributed to the improvement of theaqueous solubility, plasma-half life, tumor uptake andtherapeutic potential of the self-assembled chimeric polypeptide nanoparticle.

5.2 Biosensors and bioelectronics
Nanotechnology has broadened the opportunities andadded a new dimension in designing powerful biosensor
and bioelectronic devices for diagnostic of diseases anddetection of contaminants in medical, food and agricultural
sector. Substantial research efforts are currently being
directed towards the utilisation of biological molecules
hybridised with nanoparticles for the development ofnovel biosensor and bioelectronic system (Willner I. et al.,2007).
Ulltrasensitive biosensor for detection of epithelial tumor marker has been developed by Hu R. et al. (2014)
through the immobilisation of hairpin oligonucleotide(HO) and horseradish peroxidase (HRP) on AuNPs. The
HO-AuNP-HRP conjugate provides multiple signal amplification strategy that could enable rapid detection andenhanced the detection sensitivity in a wide linear range.
This strategy was achieved by modification of the biosensor surface by carbon nanotubes for accelerating the electron transfer while the HO-AuNPs-HRP enzyme acts as a
tracing tag for the electrochemical detection. This newly
developed electrochemical method can be applied for diagnostic and detection of diseases.
Besides for cancer detection, a biosensor based on immobilised enzyme-nanoparticles has also been applied forneurobiology for detection of glutamate, important excitatory signaling molecules that are responsible for carrying out various brain functions. Özel R.E. et al. (2014)
used nanocomposite based on ceria and titania nanoparticles, dispersed in a semi-permeable membrane made up
from chitosan, that was co-immobilised with glutamate
oxidase (GmOX) on the platinum electrode for fabricationof glutamate biosensor. Conjugation of the ceria and titania nanoparticles provide ‘oxygen rich’ environment forthe biosensor to detect glutamate in hypoxic conditions
while the immobilisation of this nanoparticle conjugate ina biocompatible chitosan membrane facilitate the enzyme
stabilisation.
Enzymes-based biosensors are now gaining more popularity for a rapid detection and on-line and in situ monitoring of specific compounds in medical, environmental
and food industries. For example, a novel potentiometricglucose biosensor has been fabricated by Yang Z. et al.
(2014) by immobilising core-shell hybrid nanoparticles ofiron oxide, glucose oxidase (GOx) and polypyrrole to thesurface of magnetic glassy carbon electrode. This biosensor enabled fast detection and highly-selective glucose
monitoring with low detection limit and wider linear
range. Enzymes-based biosensors have also been used for
detection of phenolic compounds by using various typesof enzymes such as tyrosinase, horseradish peroxidise
and laccase (Rodríguez-Delgado M.M. et al., 2015).
Recently, many researchers discovered the unique and103

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programmable molecular recognition of DNA for the development of artificial, machine-like devices. DNAzymes,
an important functional nucleotide acid have been recognised as important building blocks for the constructionof nanodevices. The development of a walking system
based on DNAzymes that are moving along a DNA track
has been reported. The motion is driven by the chemicalenergy that has been supplied by the DNAzyme substrate.
This concept was used by Liu and co-workers (2013) todesign DNA hemin-G-quadruplex-DNAzyme-based
walkers which allow the chemiluminescence, chemiluminescence resonance energy transfer (CRET), electrochemical, or photoelectrochemical transduction of theswitchable states of the different DNA machines. Besides
that, the DNA exhibited a unique feature of being easy tocode which enables them to be used in the computational
operation and logic gates (Gong L. et al., 2015).
Development of nanoscale memory devices is anotherinteresting application of biomolecule-nanoparticle conjugates. Hybrid nanoparticle composed of recombinantazurin, a well-characterised redox protein and a quantum
dot (CdSe-ZnS) have been developed by Yagati A.K. et al.
(2017). By introducing a site specific amino acid sequences in azurin, the CdSe-ZnS nanoparticle can bindwith the protein, thus forming resistive random accessmemory (ReRAM) device with reversible voltage driven-switching function and repeatable writing-reading
processes.

5.3 Foods
Despite the explosion of nanotechnology in diverse
fields, particularly in medical and pharmaceutical, the application of nanotechnology in the food sector is considered still in infancy stage due to the public perception andpreference on the so called ‘natural’ food products, which
limit the development of new food technologies (Duncan
T.V., 2011). However, as the nanotechnology has been revolutionised in the past few years, the potential uses ofnanotechnology in food industries have already been recognised in every chain of food products development,
ranging from the processing to packaging and storage(Berekaa M.M., 2015).
Nanoparticles have been used as nanocarrier which is
known as ‘nutrition delivery system’. The nanoscale delivery system plays an important role in improving foodor nutrients absorption in the human body, particularly
for those who suffer from the gastroinstestinal disease.
Nanoparticles are also useful for enhancing bioavailability of poorly soluble bioactive compounds and improving
food properties such as stability and texture.
The main criterion for the application of nanoparticles
in food products is the particles which must be developed
from food grade materials. In this regard, nanoparticles

104

from biomolecules origin are the most suited for that purpose (Ha H.-K. et al., 2013). Chitosan and whey protein
have been widely used as encapsulant of neutraceuticals,
food ingredients, probiotics and enzymes due to their easeof availability in large quantity in combination with their
good physical and mechanical properties. Ha andco-workers (2013) used linoleic acid modified chitosan/
β-lactoglobulin for encapsulation of quercetin, a hydrophobic bioactive compound with good anticancer, antiviral and antioxidant properties. Findings by Yi J. et al.
(2015) have shown that whey protein isolate was more effective for encapsulating beta-carotene than other type ofprotein such as soybean protein with great improvementin radical scavenging and cellular antioxidant activities.
Recently, calcium induced cruciferin nanoparticles from
canola protein prepared by cold gelation method havebeen utilised as a protecting agent for β-carotene to increase its bioavailability (Akbari A. and Wu J., 2016). The
main driving forces for the formation of the nanoparticles
were hydrophobic interaction and electrostatic forces.
Another study done by Marelli B. et al. (2016) shows thatcoating of food ingredients with protein nanoparticles
such as silk fibroin has a positive effect on improving
food shelf-life.
Besides used in the development of food products, nano­technology also plays a crucial role in food packaging
sector. Incorporation of nanoparticles in food packaging
materials could provide efficient food preservation systemby improving barrier protection by scavenging oxygenand other spoilage causing constituents and improve antimicrobial properties. For example, packaging film madeup from whey protein-montmorillonite nanoparticle activated with lycopene could improve the film barrier property against water vapour and at the same time provide
antioxidant activity and UV-light protection (Pereira R.C.
et al., 2016).

5.4 Agricultures
The role of nanotechnology in agricultural sectors covers the conversion of agricultural waste into energy orother useful byproducts, detection and prevention of crops
diseases, treatment of plants using various types of nanocides and delivery of agrochemicals such as pesticides,
fertilizers, genetic materials and growth hormone (Nair R.
et al., 2010; Nuruzzaman M. et al., 2016). With respects tothe delivery of agrochemicals, nanoscale materials havenovel characteristics that can improve bioactivity andagrochemicals efficiency through the development of asmart delivery system. In the smart delivery system, nano­scale carriers are utilised with the aim to enhance controlled-release properties of the agrochemicals, increase
the active ingredients solubility, and improve the stabilityof pesticides as well as for preventing premature degrada-

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tion of crops.
Silica nanoparticles have been explored as a control
agent for agricultural pesticides. Conjugation of terpenes(α-pinene and linalool) onto the silica nanoparticles surface resulted in enhanced bioavailability of the compounds and improved the antifeedant potential of theindividual terpenes against insects which consequently
prolonged shelf-life of the terpenes (Usha Rani P. et al.,2014).
Nowadays, growing interest has been shown in the utilisation of biodegradable and biocompatible materials derived from natural materials particularly chitosan-based
for the development of the agriculture nanocarriers. Chitosan is a versatile polymer which is well known to serve
two major functions in agriculture; preventing the spreadof pathogens with its wide-spectrum of antimicrobial
properties and enhancing immunity defenses of the plant(Xing K. et al., 2016).
The presence of phytopathogenic fungi and viruses has
resulted in severe damages to many crops around theglobe. The control of diseases caused by these microorganisms is a problem that remains unsolved (Cota-Arriola
O. et al., 2013). To protect crops from fungal pathogens,
the growth of the fungi can be inhibited by using protein-­chitosan nanoparticle conjugate as demonstrated by
Sathiyabama M. and Parthasarathy R. (2016). The chitosan nanoparticle was prepared through the biologicalmethod by the addition of anionic proteins to the chitosan
solution. They found that this protein-chitosan nanoparticle conjugate has high antifungal activities which inhibit
the growth of the phytopathogenic fungi tested. Additionally, treatment of the chitosan nanoparticle with chickpea
seeds allows the nanoparticle to be used as a growth promoter. Chitosan-based nanoparticles have also been prepared by Xing K. et al. (2016) for controlling pathogenic
fungi in agriculture. The antifungal nanoparticle was prepared by grafting oleoyl onto the chitosan molecules,
yielding an oleoyl-chitosan nanoparticle hybrid with sizearound 297 nm. Improvement in the antifungal index was
observed as the concentration of the nanoparticle increased.

6. Conclusions and future prospects
In this review, various types of biological nanoparticles
and the synthesis methods have been discussed. Fabrication of biological nanoparticles through drying methods,
particularly electrospraying is highlighted mainly due tothe ability of the method to generate nanoparticles with anarrow size distribution that often could not be achievedby the other nanoparticulate fabrication techniques. In order to broaden the application of biological nanoparticles,
integration of biomolecules with other types of nanoparti-

cles such as inorganic and polymeric through numerous
biofunctionalisation strategies have been established.
However, much remains to be discovered in this newly
emerging field. With the recent technological advancements and innovations, next generation of biological
nanoparticles that has multiple functionalities will be
developed which could improve the characteristics of thebiological nanoparticles and extend its application to diverse fields.

References
Abbaspour A., Norouz-Sarvestani F., Noori A., Soltani N.,
Aptamer-conjugated silver nanoparticles for electrochemical dual-aptamer-based sandwich detection of staphylococcus aureus, Biosensors and Bioelectronics, 68 (2015) 149–
155.
Achilli E., Casajus G., Siri M., Flores C., Kadlubowski S.,
Alonso S.d.V., Grasselli M., Preparation of protein nanoparticle by dynamic aggregation and ionizing-induced crosslinking, Colloids and Surfaces A: Physicochemical andEngineering Aspects, 486 (2015) 161–171.
Akbari A., Wu J., Cruciferin nanoparticles: Preparation, characterization and their potential application in delivery of bioactive compounds, Food Hydrocolloids, 54 (2016) 107–118.
Allouche J., Synthesis of Organic and Bioorganic Nanoparticles: An overview of the preparation methods, in: Brayner
R. (Ed.), Springer-Verlag, London, 2013, pp. 27–74.
Anton N., Benoit J.-P., Saulnier P., Design and production of
nanoparticles formulated from nano-emulsion templates—
A review, 128 (2008) 185–199.
Arroyo-Maya I.J., McClements D.J., Biopolymer nanoparticles
as potential delivery systems for anthocyanins: Fabricationand properties, Food Research International, 69 (2015) 1–8.
Avseenko N.V., Morozova T.Y., Ataullakhanov F.I., Morozov
V.N., Immobilization of proteins in immunochemical
microarrays fabricated by electrospray deposition, Analytical chemistry, 73 (2001) 6047–6052.
Berekaa M.M., Nanotechnology in food industry; Advances infood processing, packaging and food safety, International
Journal of Current Microbiology and Applied Sciences, 4(2015) 345–357.
Bhakta G., Nurcombe V., Maitra A., Shrivastava A., DNA-­
encapsulated magnesium phosphate nanoparticles elicit
both humoral and cellular immune responses in mice,
Results in Immunology, 4 (2014) 46–53.
Bhattacharyya J., Bellucci J.J., Weitzhandler I., McDaniel J.R.,
Spasojevic I., Li X., Lin C.-C., Chi J.-T.A., Chilkoti A., A
paclitaxel-loaded recombinant polypeptide nanoparticle
outperforms Abraxane in multiple murine cancer models,Nature Communications, 6 (2015) 7939 (12pp). http://doi.
org/10.1038/ncomms8939
Bhunchu S., Rojsitthisak P., Biopolymeric alginate-chitosan
nanoparticles as drug delivery carriers for cancer therapy,
Pharmazie, 69 (2014) 563–570.
Bilati U., Allémann E., Doelker E., Nanoprecipitation versus

105Suryani Saallah et al. / KONA Powder and Particle Journal No. 35 (2018) 89–111

emulsion-based techniques for the encapsulation of proteins
into biodegradable nanoparticles and process-related stability issues, AAPS PharmSciTech, 6 (2005) E594–E604.
Bock N., Dargaville T.R., Woodruff M.A., Controlling microencapsulation and release of micronized proteins using
poly(ethylene glycol) and electrospraying, European Journal of Pharmaceutics and Biopharmaceutics, 87 (2014)366–377.
Cao X., Deng W., Wei Y., Su W., Yang Y., Wei Y., Yu J., Xu X.,
Encapsulation of plasmid DNA in calcium phosphate
nanoparticles: stem cell uptake and gene transfer efficiency,
International Journal of Nanomedicine, 6 (2011) 3335–3349.
Cao Y., Wen L., Svec F., Tan T., Lv Y., Magnetic AuNP@Fe3O4
nanoparticles as reusable carriers for reversible enzyme
immobilization, Chemical Engineering Journal, 286 (2016)
272–281.
Cavalli R., Bisazza A., Bussano R., Trotta M., Civra A., Lembo
D., Ranucci E., Ferruti P., Poly(amidoamine)-cholesterol
conjugate nanoparticles obtained by electrospraying as
novel tamoxifen delivery system, Journal of Drug Delivery,
2011 (2011) 587604 (9pp). http://doi.org/10.1155/2011/587604
Chan H.K., Kwok P.C.L., Production methods for nanodrug
particles using the bottom-up approach, Advanced Drug
Delivery Reviews, 63 (2011) 406–416.
Chanphai P., Thomas T.J., Tajmir-Riahi H.A., Conjugation ofbiogenic and synthetic polyamines with trypsin and trypsin
inhibitor, RSC Advances, 6 (2016) 53690–53697.
Chaturvedi S.P., Kumar V., Production techniques of lipid
nanoparticles: A review, Research Journal of Pharmaceutical, Biological and Chemical Sciences, 3 (2012) 525–541.
Chen K., Xu Y., Rana S., Miranda O.R., Dubin P.L., Rotello
V.M., Sun L., Guo X., Electrostatic selectivity in protein-­
nanoparticle interactions, Biomacromolecules, 12 (2011)
2552–2561.
Chinen A.B., Guan C.M., Mirkin C.A., Spherical nucleic acid
nanoparticle conjugates enhance G-quadruplex formationand increase serum protein interactions, Angewandte Chemie International Edition, 54 (2015) 527–531.
Chinh N.T., Trang N.T.T., Giang N.V., Thanh D.T.M., Hang T.
T.X., Tung N.Q., Truyen C.Q., Quan P.M., Long P.Q., Hoang
T., In vitro nifedipine release from poly(lactic acid)/chitosan nanoparticles loaded with nifedipine, Journal ofApplied Polymer Science, 43330 (2016) 1–8.
Cota-Arriola O., Onofre Cortez-Rocha M., Burgos-HernandezA., Marina Ezquerra-Brauer J., Plascencia-Jatomea M.,
Controlled release matrices and micro/nanoparticles of chitosan with antimicrobial potential: Development of new
strategies for microbial control in agriculture, Journal of
the Science of Food and Agriculture, 93 (2013) 1525–1536.
Dag A., Jiang Y., Karim K.J.A., Hart-Smith G., Scarano W.,
Stenzel M.H., Polymer-albumin conjugate for the facilitateddelivery of macromolecular platinum drugs, Macromolecular Rapid Communications, 36 (2015) 890–897.
Das S., Chaudhury A., Recent advances in lipid nanoparticle
formulations with solid matrix for oral drug delivery,
AAPS PharmSciTech, 12 (2011) 62–76.
De M., Ghosh P.S., Rotello V.M., Applications of nanoparticles
in biology, Advanced Materials, 01003 (2008) 4225–4241.

106

Ding S., Cargill A.A., Medintz I.L., Claussen J.C., Increasing
the activity of immobilized enzymes with nanoparticle
conjugation, Current Opinion in Biotechnology, 34 (2015)
242–250.
Duncan T.V., Applications of nanotechnology in food packaging
and food safety: Barrier materials, antimicrobials and sensors, Journal of Colloid and Interface Science, 363 (2011)
1–24.
Ezhilarasi P.N., Karthik P., Chhanwal N., Anandharamakrishnan C., Nanoencapsulation techniques for food bioactive
components: A review, Food and Bioprocess Technology, 6(2013) 628–647.
Fabie L., Agostini P., Stopel M., Blum C., Lassagne B., Subramaniam V., Ondarcuhu T., Direct patterning of nanoparticles and biomolecules by liquid nanodispensing, Nanoscale,
7 (2015) 4497–4504.
Fessi H., Puisieux F., Devissaguet J.P., Ammoury N., Benita S.,
Nanocapsule formation by interfacial polymer deposition
following solvent displacement, International Journal of
Pharmaceutics, 55 (1989) 1–4.
Fornari E., Roberts C.J., Temperton R.H., O’Shea J.N., Electrospray deposition in vacuum as method to create functionally active protein immobilization on polymeric substrates,
Journal of Colloid and Interface Science, 453 (2015) 252–
259.
Friedman A.D., Claypool S.E., Liu R., The smart targeting of
nanoparticles, Current Pharmaceutical Design, 19 (2013)
6315–6329.
Gan Q., Wang T., Cochrane C., McCarron P., Modulation of
surface charge, particle size and morphological propertiesof chitosan-TPP nanoparticles intended for gene delivery,
Colloids and Surfaces B: Biointerfaces, 44 (2005) 65–73.
Ge J., Lei J., Zare R.N., Bovine serum albumin–poly(methyl
methacrylate) nanoparticles: An example of frustrated
phase separation, Nano Letters, 11 (2011) 2551–2554.
Ge J., Lei J., Zare R.N., Protein–inorganic hybrid nanoflowers,
Nature Nanotechnology, 7 (2012) 428–432.
Gholami A., Tavanai H., Moradi A.R., Production of fibroin
nanopowder through electrospraying, Journal of Nanoparticle Research, 13 (2010) 2089–2098.
Gilbert W., De Magnete, Anno MDC, Londini, Anno MDC,
1600.
Gomez-Estaca J., Balaguer M.P., Gavara R., Hernandez-Munoz
P., Formation of zein nanoparticles by electrohydrodynamic
atomization: Effect of the main processing variables andsuitability for encapsulating the food coloring and active
ingredient curcumin, Food Hydrocolloids, 28 (2012) 82–91.
Gomez A., Bingham D., De Juan L., Tang K., Production ofprotein nanoparticles by electrospray drying, Journal of
Aerosol Science, 29 (1998) 561–574.
Gong L., Zhao Z., Lv Y.-F., Huan S.-Y., Fu T., Zhang X.-b., Shen
G.-L., Yu R.-Q., DNAzyme-based biosensors and nanodevices, Chemical Communications, 51 (2015) 979–995.
Guo J., Zhong R., Li W., Liu Y., Bai Z., Yin J., Liu J., Gong P.,
Zhao X., Zhang F., Interaction study on bovine serum albumin physically binding to silver nanoparticles: Evolution
from discrete conjugates to protein coronas, Applied Surface Science, 359 (2015) 82–88.

Suryani Saallah et al. / KONA Powder and Particle Journal No. 35 (2018) 89–111

Ha H.-K., Wook J., Lee M.-R., Lee W.-J., Formation and characterization of quercetin-loaded chitosan oligosaccharide/
β-lactoglobulin nanoparticle, Food Research International,
52 (2013) 82–90.
Haggag Y.A., Faheem A.M., Evaluation of nano spray drying asa method for drying and formulation of therapeutic peptides
and proteins, Frontiers in Pharmacology, 6 (2015) 1–5.
Hazeri N., Tavanai H., Moradi A.R., Production and properties
of electrosprayed sericin nanopowder, Science and Technology of Advanced Materials, 13 (2012) 035010 (7pp).
http://dx.doi.org/10.1088/1468-6996/13/3/035010
Höldrich M., Sievers-Engler A., Lämmerhofer M., Goldnanoparticle-conjugated pepsin for efficient solution-likeheterogeneous biocatalysis in analytical sample preparation
protocols, Analytical and Bioanalytical Chemistry, 408(2016) 5415–5427.
Honda T., Tanaka T., Yoshino T., Stoichiometrically controlled
immobilization of multiple enzymes on magnetic nanoparticles by the magnetosome display system for efficient cellulose hydrolysis, Biomacromolecules, 16 (2015) 3863–
3868.
Hosseini S.F., Zandi M., Rezaei M., Farahmandghavi F., Twostep method for encapsulation of oregano essential oil inchitosan nanoparticles: Preparation, characterization and invitro release study, Carbohydrate Polymers, 95 (2013)
50–56.
Hosseini S.M.H., Emam-Djomeh Z., Sabatino P., Van der MeerenP., Nanocomplexes arising from protein-polysaccharide
electrostatic interaction as a promising carrier for nutraceutical compounds, Food Hydrocolloids, 50 (2015) 16–26.
Hsiao A.P., Heller M.J., Electric-field-directed self-assembly ofactive enzyme-nanoparticle structures, Journal of Biomedicine & Biotechnology, 2012 (2012) 178487 (9pp). http://dx.
doi.org/10.1155/2012/178487
Hu B., Ting Y., Yang X., Tang W., Zeng X., Huang Q., Nanochemoprevention by encapsulation of (–)-epigallocatechin-­
3-gallate with bioactive peptides/chitosan nanoparticles forenhancement of its bioavailability, Chemical Communications, 48 (2012) 2421 (4pp). http://www.rsc.org/suppdata/cc/
c2/c2cc17295j/c2cc17295j.pdf.
Hu K., Huang X., Gao Y., Huang X., Xiao H., McClements
D.J., Core-shell biopolymer nanoparticle delivery systems:
Synthesis and characterization of curcumin fortified zein-­pectin nanoparticles, Food Chemistry, 182 (2015) 275–281.
Hu R., Wen W., Wang Q., Xiong H., Zhang X., Gu H., Wang S.,
Novel electrochemical aptamer biosensor based on an
enzyme–gold nanoparticle dual label for the ultrasensitive
detection of epithelial tumour marker MUC1, Biosensors
and Bioelectronics, 53 (2014) 384–389.
Huang X., Huang X., Gong Y., Xiao H., McClements D.J., Hu
K., Enhancement of curcumin water dispersibility and antioxidant activity using core-shell protein-polysaccharide
nanoparticles, Food Research International, 87 (2016) 1–9.
Huang Y., Ran X., Lin Y., Ren J., Qu X., Self-assembly of anorganic–inorganic hybrid nanoflower as an efficient biomimetic catalyst for self-activated tandem reactions, Chemical
Communications, 51 (2015) 4386–4389.
Huang Y.C., Kuo T.H., O-carboxymethyl chitosan/fucoidan

nanoparticles increase cellular curcumin uptake, Food
Hydrocolloids, 53 (2014) 261–269.
Hung B.-Y., Kuthati Y., Kankala R., Kankala S., Deng J.-P.,
Liu C.-L., Lee C.-H., Utilization of enzyme-immobilized
mesoporous silica nanocontainers (IBN-4) in prodrug-­
activated cancer theranostics, Nanomaterials, 5 (2015)
2169–2191.
Jahanshahi M., Babaei Z., Protein nanoparticle : A unique system as drug delivery vehicles, Journal of Biotechnology, 7(2008) 4926–4934.
Jain A., Cheng K., The principles and applications of avidin-­based nanoparticles in drug delivery and diagnosis, Journalof Controlled Release, 245 (2017) 27–40.
Jawahar N., Meyyanathan S., Polymeric nanoparticles for drugdelivery and targeting: A comprehensive review, International Journal of Health & Allied Sciences, 1 (2012) 217–
223.
Jaworek A., Sobczyk A.T., Electrospraying route to nanotechnology: An overview, Journal of Electrostatics, 66 (2008)
197–219.
Jazayeri M.H., Amani H., Pourfatollah A.A., Avan A., Ferns
G.A., Pazoki-Toroudi H., Enhanced detection sensitivityof prostate-specific antigen via PSA-conjugated gold
nanoparticles based on localized surface plasmon resonance: GNP-coated anti-PSA/LSPR as a novel approach forthe identification of prostate anomalies, Cancer Gene Therapy, 23 (2016) 365–369.
Jiang Y., Lu H., Dag A., Hart-Smith G., Stenzel M.H., Albumin–polymer conjugate nanoparticles and their interactions
with prostate cancer cells in 2D and 3D culture: comparison
between PMMA and PCL, Journal of Materials ChemistryB, 4 (2016) 2017–2027.
Joye I.J., Davidov-Pardo G., Ludescher R.D., McClements D.J.,
Fluorescence quenching study of resveratrol binding to zein
and gliadin: Towards a more rational approach to resveratrol encapsulation using water-insoluble proteins, Food
Chemistry, 185 (2015) 261–267.
Katz E., Willner I., Integrated nanoparticle-biomolecule hybrid
systems: Synthesis, properties, and applications, Angewandte Chemie International Edition, 43 (2004) 6042–
6108.
Kim B.J., Cheong H., Hwang B.H., Cha H.J., Mussel-inspired
protein nanoparticles containing iron(III)-DOPA complexes
for ph-responsive drug delivery, Angewandte ChemieInternational Edition, 54 (2015) 7318–7322.
Kobayashi K., Wei J., Iida R., Ijiro K., Niikura K., Surface
engineering of nanoparticles for therapeutic applications,
Polymer Journal, 46 (2014) 460–468.
Koley P., Sakurai M., Aono M., Controlled fabrication of silk
protein sericin mediated hierarchical hybrid flowers andtheir excellent adsorption capability of heavy metal ions ofPb(II), Cd(II) and Hg(II), ACS Applied Materials andInterfaces, 8 (2016) 2380–2392.
Kumar R., Lal S., Synthesis of organic nanoparticles and theirapplications in drug delivery and food nanotechnology: A
Review, Journal of Nanomaterials & Molecular Nanotechnology, 03 (2014).
Lebre F., Borchard G., Faneca H., Pedroso de Lima M.C.,

107

Suryani Saallah et al. / KONA Powder and Particle Journal No. 35 (2018) 89–111

Borges O., Intranasal administration of novel chitosan
nanoparticle/DNA complexes induces antibody response to
hepatitis B surface antigen in mice, Molecular Pharmaceutics, 13 (2016) 472–482.
Lee S.H., Heng D., Ng W.K., Chan H.K., Tan R.B.H., Nano
spray drying: A novel method for preparing protein
nanoparticles for protein therapy, International Journal of
Pharmaceutics, 403 (2011) 192–200.
Lee Y.-H., Wu B., Zhuang W.-Q., Chen D.-R., Tang Y.J.,
Nanoparticles facilitate gene delivery to microorganisms
via an electrospray process, Journal of Microbiologicalmethods, 84 (2011) 228–233.
Lenggoro I.W., Xia B., Okuyama K., de la Mora J.F., Sizing of
colloidal nanoparticles by electrospray and differential
mobility analyzer methods, Langmuir, 18 (2002) 4584–
4591.
Liao W., Yu Z., Lin Z., Lei Z., Ning Z., Regenstein J.M., Yang J.,
Ren J., Biofunctionalization of selenium nanoparticle withdictyophora indusiata polysaccharide and its antiproliferative activity through death-receptor and mitochondria-mediated apoptotic pathways, Scientific Reports, 5 (2016)
18629 (13pp). http://doi.org/10.1038/srep18629
Lin T.-T., Gao D.-Y., Liu Y.-C., Sung Y.-C., Wan D., Liu J.-Y.,
Chiang T., Wang L., Chen Y., Development and characterization of sorafenib-loaded PLGA nanoparticles for the systemic treatment of liver fibrosis, Journal of Controlled
Release, 221 (2016) 62–70.
Liu X., Niazov-Elkan A., Wang F., Willner I., Switching photonic and electrochemical functions of a DNAzyme by
DNA machines, Nano Letters, 13 (2013) 219–225.
López-Rubio A., Lagaron J.M., Whey protein capsules obtained
through electrospraying for the encapsulation of bioactives,
Innovative Food Science and Emerging Technologies, 13(2012) 200–206.
Lu K.Y., Li R., Hsu C.H., Lin C.W., Chou S.C., Tsai M.L.,
Mi F.L., Development of a new type of multifunctional
fucoidan-­based nanoparticles for anticancer drug delivery,
Carbohydrate Polymers, 165 (2017) 410–420.
Mahapatro A., Singh D.K., Biodegradable nanoparticles are
excellent vehicle for site directed in-vivo delivery of drugs
and vaccines, Journal of Nanobiotechnology, 9 (2011) 55(11pp). https://doi.org/10.1186/1477-3155-9-55
Marelli B., Brenckle M.A., Kaplan D.L., Omenetto F.G., Silk
fibroin as edible coating for perishable food preservation,
Scientific Reports, 6 (2016) 25263 (11pp). http://doi.org/10.
1038/srep25263
Marty J.J., Oppenheim R.C., Speiser P., Nanoparticles—a new
colloidal drug delivery system, Pharmaceutica acta Helvetiae, 53 (1978) 17–23.
Mattu C., Li R., Ciardelli G., Chitosan nanoparticles as therapeutic protein nanocarriers : the effect of ph on particle formation and encapsulation efficiency, Polymer Composites,(2013) 1538–1545.
Mehta P., Haj-Ahmad R., Rasekh M., Arshad M.S., Smith A.,
van der Merwe S.M., Li X., Chang M.-W., Ahmad Z., Pharmaceutical and biomaterial engineering via electrohydrodynamic atomization technologies, Drug Discovery Today,
00 (2016) 1–9.

108

Meissner J., Prause A., Bharti B., Findenegg G.H., Characterization of protein adsorption onto silica nanoparticles: influence of pH and ionic strength, Colloid and Polymer Science, 293 (2015) 3381–3391.
Mejias S.H., Couleaud P., Casado S., Granados D., Garcia M.A.,
Abad J.M., Cortajarena A.L., Assembly of designed protein
scaffolds into monolayers for nanoparticle patterning, Colloids and Surfaces B: Biointerfaces, 141 (2016) 93–101.
Menjoge A.R., Rinderknecht A.L., Navath R.S., Faridnia M.,
Kim C.J., Romero R., Miller R.K., Kannan R.M., Transfer
of PAMAM dendrimers across human placenta: Prospectsof its use as drug carrier during pregnancy, Journal of Controlled Release, 150 (2011) 326–338.
Menon J.U., Ravikumar P., Pise A., Gyawali D., Hsia C.C.W.,
Nguyen K.T., Polymeric nanoparticles for pulmonary protein and DNA delivery, Acta Biomaterialia, 10 (2014)
2643–2652.
Mercado-Lubo R., Zhang Y., Zhao L., Rossi K., Wu X., Zou Y.,
Castillo A., Leonard J., Bortell R., Greiner D.L., Shultz
L.D., Han G., McCormick B.A., A Salmonella nanoparticle
mimic overcomes multidrug resistance in tumours, Nature
Communications, 7 (2016) 12225 (13pp). http://doi.org/10.
1038/ncomms12225
Moreira C.D.F., Carvalho S.M., Mansur H.S., Pereira M.M.,
Thermogelling chitosan-collagen-bioactive glass nanoparticle hybrids as potential injectable systems for tissue engineering, Materials Science and Engineering C, 58 (2016)
1207–1216.
Mortensen D.N., Williams E.R., Investigating protein folding
and unfolding in electrospray nanodrops upon rapid mixing
using theta-glass emitters, Analytical Chemistry, 87 (2015)
1281–1287.
Naim M.N., Abu Bakar N.F., Iijima M., Kamiya H., Lenggoro
I.W., Electrostatic deposition of aerosol particles generated
from an aqueous nanopowder suspension on a chemicallytreated substrate, Japanese Journal of Applied Physics, 49(2010) 06GH17 (6pp). http://stacks.iop.org/1347-4065/49/
i= 6S/a= 06GH17
Nair R., Varghese S.H., Nair B.G., Maekawa T., Yoshida Y.,
Kumar D.S., Nanoparticulate material delivery to plants,
Plant Science, 179 (2010) 154–163.
Niemeyer C.M., Biotechnology meets materials science, Angewandte Chemie International Edition, 40 (2001) 4128–4158.
Nitta S.K., Numata K., Biopolymer-based nanoparticles for
drug/gene delivery and tissue engineering, International
Journal of Molecular Sciences, 14 (2013) 1629–1654.
Nuruzzaman M., Rahman M.M., Liu Y., Naidu R., Nanoencapsulation, nano-guard for pesticides: A new window for safe
application, Journal of Agricultural and Food Chemistry,
64 (2016) 1447–1483.
Özel R.E., Ispas C., Ganesana M., Leiter J.C., Andreescu S.,
Glutamate oxidase biosensor based on mixed ceria and titania nanoparticles for the detection of glutamate in hypoxic
environments, Biosensors & Bioelectronics, 52 (2014) 397–
402.
Pal S.L., Jana U., Manna P.K., Mohanta G.P., Manavalan R.,
Nanoparticles–an overview of preparation and characterization, Journal of Applied Pharmaceutical Science, 1 (2011)

Suryani Saallah et al. / KONA Powder and Particle Journal No. 35 (2018) 89–111

228–234.
Panigaj M., Reiser J., Aptamer guided delivery of nucleic acidbased nanoparticles, DNA and RNA Nanotechnology, 2(2016) 42–52.
Panta P., Kim D.Y., Kwon J.S., Son A.R., Lee K.W., Kim S.,
Protein drug-loaded polymeric nanoparticles, Journal of
Biomedical Science and Engineering, 7 (2014) 825–832.
Peltonen L., Valo H., Kolakovic R., Laaksonen T., Hirvonen J.,
Electrospraying, spray drying and related techniques for
production and formulation of drug nanoparticles, Expert
Opinion on Drug Delivery, 7 (2010) 705–719.
Pereira R.C., de Deus Souza Carneiro J., Borges S.V., Assis
O.B.G., Alvarenga G.L., Preparation and characterizationof nanocomposites from whey protein concentrate activatedwith lycopene, Journal of Food Science, 81 (2016) E637–
E642.
Politi J., De Stefano L., Longobardi S., Giardina P., Rea I.,
Methivier C., Pradier C.M., Casale S., Spadavecchia J., Theamphiphilic hydrophobin Vmh2 plays a key role in one step
synthesis of hybrid protein-gold nanoparticles, Colloids andSurfaces B: Biointerfaces, 136 (2015) 214–221.
Puddu V., Perry C.C., Peptide adsorption on silica nanoparticles: Evidence of hydrophobic interactions, ACS Nano, 6(2012) 6356–6363.
Rabbani P.S., Zhou A., Borab Z.M., Frezzo J.A., Srivastava N.,
More H.T., Rifkin W.J., David J.A., Berens S.J., Chen R.,
Hameedi S., Junejo M.H., Kim C., Sartor R.A., Liu C.F.,
Saadeh P.B., Montclare J.K., Ceradini D.J., Novel lipoproteoplex delivers Keap1 siRNA based gene therapy to accelerate diabetic wound healing, Biomaterials, 132 (2017)
1–15.
Rampino A., Borgogna M., Blasi P., Bellich B., Cesàro A., Chitosan nanoparticles: Preparation, size evolution and stability, International Journal of Pharmaceutics, 455 (2013) 219–
228.
Rao J.P., Geckeler K.E., Progress in Polymer Science Polymer
nanoparticles : Preparation techniques and size-control
parameters, Progress in Polymer Science, 36 (2011) 887–
913.
Rassu G., Cossu M., Langasco R., Carta A., Cavalli R.,
Giunchedi P., Gavini E., Propolis as lipid bioactive
nano-carrier for topical nasal drug delivery, Colloids andSurfaces B: Biointerfaces, 136 (2015) 908–917.
Rodríguez-Delgado M.M., Alemán-Nava G.S., Rodríguez-­
Delgado J.M., Dieck-Assad G., Martínez-Chapa S.O.,
Barceló D., Parra R., Laccase-based biosensors for detection of phenolic compounds, TrAC Trends in Analytical
Chemistry, 74 (2015) 21–45.
Saallah S., Naim N.N., Mokhtar M.N., Abu Bakar N.F., Gen M.,
Lenggoro W.W., Transformation of cyclodextrin glucanotransferase (CGTase) from aqueous suspension to fine solid
particles via electrospraying, Enzyme and Microbial Technology, 64–65 (2014) 52–59.
Sahdev P., Ochyl L.J., Moon J.J., Biomaterials for nanoparticle
vaccine delivery systems, Pharmaceutical Research, 31(2014) 2563–2582.
Salata O.V., Applications of nanoparticles in biology and medicine, Journal of Nanobiotechnology, 2 (2004) 3 (6pp).

https://doi.org/10.1186/1477-3155-2-3
Sapsford K.E., Algar W.R., Berti L., Gemmill K.B., Casey B.J.,
Oh E., Stewart M.H., Medintz I.L., Functionalizing
nanoparticles with biological molecules: Developing chemistries that facilitate nanotechnology, Chemical Reviews,
113 (2013) 1904–2074.
Sathiyabama M., Parthasarathy R., Biological preparation of
chitosan nanoparticles and its in vitro antifungal efficacy
against some phytopathogenic fungi, Carbohydrate Polymers, 151 (2016) 321–325.
Sellers S.P., Clark G.S., Sievers R.E., Carpenter J.F., Dry powders of stable protein formulations from aqueous solutions
prepared using supercritical CO2-assisted aerosolization,
Journal of Pharmaceutical Sciences, 90 (2001) 785–797.
Shahrestani H., Taheri-Kafrani A., Soozanipour A., Tavakoli O.,
Enzymatic clarification of fruit juices using xylanase
immobilized on 1,3,5-triazine-functionalized silica-encapsulated magnetic nanoparticles, Biochemical Engineering
Journal, 109 (2016) 51–58.
Sojitra U.V., Nadar S.S., Rathod V.K., A magnetic tri-enzyme
nanobiocatalyst for fruit juice clarification, Food Chemistry, 213 (2016) 296–305.
Spampinato V., Parracino M.A., La Spina R., Rossi F., Ceccone
G., Surface analysis of gold nanoparticles functionalizedwith thiol-modified glucose SAMs for biosensor applications, Frontiers in Chemistry, 4 (2016) 1–12.
Sperling R.A., Parak W.J., Surface modification, functionalization and bioconjugation of colloidal inorganic nanoparticles, Philosophical transactions Series A, Mathematical,
physical, and engineering sciences, 368 (2010) 1333–1383.
Sundar S., Kundu J., Kundu S.C., Biopolymeric nanoparticles,
Science and Technology of Advanced Materials, 11 (2010)
014104 (13pp). http://dx.doi.org/10.1088/1468-6996/11/1/
014104
Surnar B., Sharma K., Jayakannan M., Core–shell polymer
nanoparticles for prevention of GSH drug detoxificationand cisplatin delivery to breast cancer cells, Nanoscale, 7(2015) 17964–17979.
Tabernero A., Martín Del Valle E.M., Galán M.A., Supercriticalfluids for pharmaceutical particle engineering: Methods,
basic fundamentals and modelling, Chemical Engineering& Processing: Process Intensification, 60 (2012) 9–25.
Tamjidi F., Shahedi M., Varshosaz J., Nasirpour A., Nanostructured lipid carriers (NLC): A potential delivery system forbioactive food molecules, Innovative Food Science andEmerging Technologies, 19 (2013) 29–43.
Tauran Y., Brioude A., Coleman A.W., Rhimi M., Kim B.,
Molecular recognition by gold, silver and copper nanoparticles, World Journal of Biological Chemistry, 4 (2013) 35–63.
Uematsu I., Matsumoto H., Morota K., Minagawa M., Tanioka
A., Yamagata Y., Inoue K., Surface morphology and biological activity of protein thin films produced by electrospraydeposition, Journal of Colloid and Interface Science, 269(2004) 336–340.
Usha Rani P., Madhusudhanamurthy J., Sreedhar B., Dynamic
adsorption of α-pinene and linalool on silica nanoparticles
for enhanced antifeedant activity against agricultural pests,
Journal of Pest Science, 87 (2014) 191–200.

109

Suryani Saallah et al. / KONA Powder and Particle Journal No. 35 (2018) 89–111

Valo H., Biopolymer-Based Nanoparticles for Drug Delivery,
Helsinki University Printing House, Helsinki, 2012.
Viswanathan K., Preparation and characterization of fluorescentsilica coated magnetic hybrid nanoparticles, Colloids andSurfaces A: Physicochemical and Engineering Aspects, 386(2011) 11–15.
Wang E.C., Wang A.Z., Nanoparticles and their applications incell and molecular biology, Integrative Biology, 6 (2014)
9–26.
Wei H., Nolkrantz K., Powell D.H., Woods J.H., Ko M.-C.,
Kennedy R.T., Electrospray sample deposition for
matrix-assisted laser desorption/ionization (MALDI) andatmospheric pressure MALDI mass spectrometry withattomole detection limits, Rapid Communications in Mass
Spectrometry: RCM, 18 (2004) 1193–1200.
Weiss J., Decker E.A., McClements D.J., Kristbergsson K., Helgason T., Awad T., Solid lipid nanoparticles as delivery systems for bioactive food components, Food Biophysics, 3(2008) 146–154.
Willner I., Willner B., Katz E., Biomolecule–nanoparticle
hybrid systems for bioelectronic applications, Bioelectrochemistry, 70 (2007) 2–11.
Xie W., Zang X., Covalent immobilization of lipase ontoaminopropyl-­f unctionalized hydroxyapatite-encapsulated-­γ-Fe2O3 nanoparticles: A magnetic biocatalyst for interesterification of soybean oil, Food Chemistry, 194 (2016) 1283–
1292.
Xing K., Shen X., Zhu X., Ju X., Miao X., Tian J., Feng Z., Peng
X., Jiang J., Qin S., Synthesis and in vitro antifungal efficacy of oleoyl-chitosan nanoparticles against plant pathogenic fungi, International Journal of Biological Macromolecules, 82 (2016) 830–836.
Yagati A.K., Kim S.U., Lee T., Min J., Choi J.W., Recombinantazurin-CdSe/ZnS hybrid structures for nanoscale resistive110

random access memory device, Biosensors & Bioelectronics, 90 (2017) 23–30.
Yang G., Liu H., Hu X., Chen Z., Friis T.E., Wang J., Xiao Y.,
Zhang S., Bio-inspired hybrid nanoparticles promote vascularized bone regeneration in a morphology-dependent
manner, Nanoscale, 9 (2017) 5794–5805.
Yang Z., Zhang C., Zhang J., Bai W., Potentiometric glucose
biosensor based on core-shell Fe3O4 -enzyme-polypyrrole
nanoparticles, Biosensors and Bioelectronics, 51 (2014)
268–273.
Yi J., Lam T.I., Yokoyama W., Cheng L.W., Zhong F., Beta-­
carotene encapsulated in food protein nanoparticles reduces
peroxyl radical oxidation in Caco-2 cells, Food Hydrocolloids, 43 (2015) 31–40.
Yu M.K., Park J., Jon S., Targeting strategies for multifunctional
nanoparticles in cancer imaging and therapy, Theranostics,
2 (2012) 3–44.
Yurteri C.U., Hartman R.P.A., Marijnissen J.C.M., Producing
pharmaceutical particles via electrospraying with anemphasis on nano and nano structured particles—A review,
KONA Powder and Particle Journal, 28 (2010) 91–115.
Zamani M., Prabhakaran M.P., Thian E.S., Ramakrishna S.,
Protein encapsulated core-shell structured particles prepared by coaxial electrospraying: Investigation on material
and processing variables, International Journal of Pharmaceutics, 473 (2014) 134–143.
Zhang Y., Huang R., Zhu X., Wang L., Wu C., Synthesis, properties, and optical applications of noble metal nanoparticle-­biomolecule conjugates, Chinese Science Bulletin, 57(2012) 238–246.
Zhao Z., Li Y., Xie M.B., Silk fibroin-based nanoparticles for
drug delivery, International Journal of Molecular Sciences,
16 (2015) 4880–4903.

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Author’s short biography
Suryani Saallah
Suryani Saallah is currently a PhD student at Graduate School of Bio-Application and
Systems Engineering, Tokyo University of Agriculture and Technology (TUAT). She
also served as a Lecturer at Biotechnology Research Institute, Universiti Malaysia Sabah(UMS) with a specialization in Bioprocess Engineering. She earned her B. Eng (Chemical-­
Bioprocess) from Universiti Teknologi Malaysia (UTM) and Master Degree from Universiti Putra Malaysia. Her research is mainly focused on synthesis of nanomaterials
including nanoparticles and nanofibers and its application in bioprocessing.

I. Wuled Lenggoro
Dr. Wuled Lenggoro is a faculty member at TUAT. He holds a doctoral degree andfaculty position at Hiroshima Univ., followed by visiting positions in RIKEN (Instituteof Physical and Chemical Research) and Yale Univ. In 2007, he established a researchgroup under JST/TUAT “Tenure-track” program. At TUAT, he has supervised more than
10 doctoral-, 20 master’s degree students, and more than 30 undergraduates. He was a
Regional Editor of Journal of Nanoparticle Research (Springer). He was awarded “AsianYoung Aerosol Scientist Award” (2007), “Chemical Engineering Science’s Most Cited
Paper 2003–2006 Award” (Elsevier), “Iinoya Award” (2005), “Takahashi Award” (2013),
and “Measurement Award” (2016) from Japan Association of Aerosol Science and Technology.

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KONA Powder and Particle Journal No. 35 (2018) 112–121/Doi:10.14356/kona.2018018

Review Paper

Leading Edge of Coal Utilization Technologies
for Gasification and Cokemaking †Kenji Kato 1* and Keiji Matsueda 2
1
2

Engineering R&D Institute, Nippon Steel & Sumikin Engineering Co., Ltd., Japan
Head Office, Nippon Steel & Sumitomo Metal Corp., Japan

Abstract
Coal is a very important resource for power generation and cokemaking. Moreover, coal is a very useful resourcefor producing city gas and chemical materials by gasification technology. Low grade coals are suitable for the coalgasification resources because they are easily decomposed and converted to generate gas in the gasifier. On theother hand, high quality coals such as good quality bituminous coals are required for producing metallurgicalcoke. Recently, the amount of high quality coals has been decreasing. The expansion of raw coal brands for
producing metallurgical coke is very important. In this paper, the development of high energy efficiency
gasification technology, ECORO®, and new cokemaking technologies such as the DAPS and the SCOPE21
enabling the expansion of coal resources are introduced. These technologies are contributed to the expansion ofcoal resources and energy savings.
Keywords: coal, low rank coal, gasification, cokemaking, SCOPE21

1. Introduction
Coal is a very important resource for power generationand cokemaking. Moreover, coal is a very useful resourcefor producing city gas and chemical materials by gasification technology. Low grade coal is suitable as coal gasification resources because they are easily decomposed andconverted to generate gas in the gasifier.
On the other hand, high quality coals such as goodquality bituminous coals are required for producing metallurgical coke. Fig. 1 shows the coal band and the expansion target of coal resources for producing metallurgicalcoke (Kato, 2008). In the conventional cokemaking process, only high quality bituminous coals can be used as
raw coals. Recently, the amount of high quality coals has
been decreasing. The expansion of raw coal brands for
producing metallurgical coke is very important. In Japan,
improvement of coke quality is strongly demanded tosmoothly operate large inner volume blast furnaces.
Therefore, the effective coal utilization technologies involving the dry coal charging process and the new coke†
1
2*

Received 27 June 2017; Accepted 21 August 2017
J-STAGE Advance published online 30 September 201710-12, Koyocho, Wakamatsu-ku, Kitakyushu-city, Fukuoka
808-0002, Japan
2-6-1, Marunouchi, Chiyoda-ku, Tokyo 100-8071, Japan
Corresponding author: Kenji Kato
E-mail: katoh.kenji.e2q@eng.nssmc.com
TEL: +81-93-751-0780 FAX: +81-93-752-3159

112

making process were developed.
In this paper, the trend of gasification technologies andnew cokemaking processes enabling the expansion of coalresources are introduced.

2. Coal gasification technology
2.1 Trend of coal gasification technology
Coal gasification is the technology to convert coal into
gas such as hydrogen (H2), carbon monoxide (CO) andmethane (CH4) at high temperature using air or oxygenand steam as the gasifying agent. The main coal gasification reactions are shown in equation (1) to (8). The generated gas is used as the clean gas for raw materials to
produce city gas, chemical products etc.
1) Pyrolysis;
Coal to gas component, tar, heavy oil, char(C)2) Reaction with oxygen;
C + O2 = CO2 + 393 kJ/mol

(1)

C + 1/2O2 = CO + 111 kJ/mol(2)

C + CO2 = 2CO – 171 kJ/mol

(3)3) Reaction with steam
C + H2O = CO2 + H2 – 131 kJ/mol(4)

C + 2H2O = CO2 + 2H2 – 76 kJ/mol(5)

Copyright © 2018 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/).

Kenji Kato et al. / KONA Powder and Particle Journal No. 35 (2018) 112–121

Fig. 1

Coal band.

CO + H2O = CO2 + H2 + 41 kJ/mol

(6)4) Reaction with hydrogenC + 2H2 = CH4 + 75 kJ/mol(7)

CO + 3H2 = CH4 + H2O + 206 kJ/mol

(8)Fig. 2 shows the history of the coal gasification technology (Gräbner M., 2014). The history of coal gasification is divided into three generations. The first generationof industrial gasification arose from the idea of supplying
a chemical synthesis produced from coal. A typical example is the Winkler fluidized bed gasifier, which found its
first commercial application in 1926 in Germany. Amongthe first generation of gasification technologies, the Lurgi
fixed bed dry bottom technology was developed.
Besides minor industrial factors, the oil crises relaunched interest in coal gasification again leading to thedevelopment of a second generation of coal gasification
processes from 1970s until the early 1990s.
For fluidized bed and entrained bed processes, the gas-

Fig. 2

ification pressure should be raised from atmospheric to
2–6 MPa. For fluidized bed and fixed bed processes, theperformance was enhanced in the points of high carbon
conversion rate and high energy efficiency. Another focus
was on the integration of heat recovery from syngas bysteam generation if gasification is employed for power
generation.
However, after a decade of relative silence surrounding
coal gasification, beginning around 2000s, the following
general trends have renewed interest in the technology.
(1) Substitution of crude oil by other energy carriers,
such as biomass or coal targeting supply security andlocal energy price stabilization(2) Increasing interest in the use of low grade coals withhigh ash or moisture contents in emerging nations
The Lurgi process uses the pressurized fixed bed gasifier. The Winkler process uses the fluidized bed typegasifier developed in German, and the Koppers-Totzek
process uses the entrained bed gasifier developed inGermany in 1952.
After the first oil crisis of the 1970s, coal was reviewed
as the industrial raw materials. Various types of gasification process were developed and the energy efficiency
was improved. The feature of the Texaco and the GE
process is a coal-water slurry type, and the Shell furnace
is a dry process.
One of the coal gasification technologies developed inJapan is the ECOPRO®. This technology has the featureof two stage coal gasification.

2.2 ECOPRO® gasification technology
ECOPRO® is the gasification technology with an entrained bed type gasifier with two stages (Kosuge et al.,2014). Generally, an entrained bed type gasifier can takehigh carbon conversion and high energy efficiency. Furthermore, the energy efficiency of the ECOPRO® process
is higher than that of a conventional entrained bed gasifier

Trend of coal gasification technologies.

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Fig. 3Fig. 4

Process flow of the ECOPRO®.

Comparison of energy efficiency involving the ECOPRO® and conventional gasification process.

because it has two stage reactors. Fig. 3 shows the outlineof the ECOPRO® process. First, coal is crushed and dried
to prepare pulverized coal for gasification. Pulverizedcoal is introduced into both of the chambers of the gasifier
with the career gas, and quickly converted to the syngas.
In the lower chamber, coal is reacted with oxygen andsteam. Partial oxidation reaction occurs, and syngas is
generated from 1300 °C to 1400 °C. The generated syngas
is introduced into the upper part of the reactor. In the upper chamber, the coal pyrolysis reaction is occurred by
the sensible heat of the high temperature syngas introduced from the lower chamber. Syngas including methaneand char is generated at 1100 °C in the upper chamber.
Fig. 4 shows the unique feature of the ECOPRO® process. In the ECOPRO® process, the sensible heat generated during coal partial combustion at the lower chamber
can be used for coal pyrolysis at the upper chamber.
Therefore, total energy efficiency of the process increases
by 5 % compared with other conventional gasification
processes.
In other gasification processes, the sensible heat fromthe high temperature syngas obtained by coal gasificationis recovered as steam by the boiler. Therefore, the maximum energy efficiency of these processes is 80 % (DOE/

114

Fig. 5Experimental apparatuses of the ECOPRO®.

NETL, 2011). In the ECOPRO® process, part of the sensible heat from the high temperature syngas generated at
the lower chamber is used for coal pyrolysis in the upper
part of gasifier. As a result, the ECOPRO® provides 85 %energy efficiency (Kosuge et al., 2014).
Fig. 5 shows the experimental apparatuses of ECOPRO®. Since the early 1990s, Nippon Steel & Sumikin
Engineering has been developing coal gasification technologies and has developed the ECOPRO® process. Basedon the basic research with 1 kg/d-scale experimental
apparatus (1992–1996) and bench scale tests with 1 t/d

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Fig. 6Development schedule of the ECOPRO® process.

scale unit, pilot plant scale tests with 20 t/d started in2003 (Fig. 6) (Kosuge et al., 2014).
The pilot plant operation with three different types ofcoal samples of brown coals and sub-bituminous coals
had been conducted for 3101 h in total. Fig. 7 shows thecoal characteristics used for the pilot plant operation. It
was clarified that the ECOPRO® process is suitable for awide range of coal resources such as sub-bituminous
coals and brown coals.

3. Cokemaking technology
3.1 Conventional cokemaking technology

Fig. 7

Coal map suitable for gasification technology.

Fig. 8

Coke is mainly used for producing pig iron using theblast furnace method. More than 90 % of coke produced
in Japan is used for blast furnace (Fig. 8). The role ofcoke is mainly as follows, iron ore reducing agent, heating
material and permeability maintaining spacer that sustains the flow passes in the blast furnace (Fig. 9). Coke is

Schematic diagram of ironmaking process flow.

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very important because no alternative of coke is available
in the blast furnace process.
Fig. 10 shows the conventional cokemaking process
flow. First, several brands of raw coals are blended andcrushed by a coal crusher. Blended raw coals are charged
into coke ovens for producing metallurgical coke. Fig. 11
shows the appearance of a coke oven battery. The carbonization time is from 19 to 24 h and the raw coals are carbonized in the coke oven. The carbonization temperatureis around 1,000 °C.

constant.
To increase the blending ratio of non- or slightly-caking
coals in coal charges, the new pretreating technology forthe coal charge, DAPS was developed and came on streamat Nippon Steel & Sumitomo Metal Oita works in 1992
(Kato, 2004).
At first, to evaluate the dust occurrence during the coaltransportation from a coal dryer to coke oven, the rela-

3.2 Dry coal charging process for improving coke
qualityDry coal charging processes such as coal moisture control (CMC) process and dry-cleaned and agglomerated
precompaction system (DAPS) were successfully developed by Nippon Steel & Sumitomo Metal Corp (Kato,
2004; Kato et al., 2006).
The first CMC process using indirect heating in a rotary dryer was operated in 1983. Coal moisture of raw
coal charged into a coke oven is reduced from 10 mass%
to 5–6 mass% with the CMC process. The use of the
CMC process has been spreading because this technology
saves energy, permits the increased use of non- or slightly-caking coals, stabilizes the operation of cokemaking
process by keeping the moisture content of coal charges

Fig. 9

Role of coke on blast furnace operation.

Fig. 11 Appearance of coke oven battery.

Fig. 12 Experimental apparatus for dust occurrence measurement. Reprinted with permission from Ref. (Kato,
2004). Copyright: (2004) The Iron and Steel Instituteof Japan.

Fig. 10 Conventional cokemaking process flow.

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Fig. 13 Relationship between dust occurrence index and coalmoisture. Reprinted with permission from Ref. (Kato,
2004). Copyright: (2004) The Iron and Steel Instituteof Japan.

Fig. 15

Relation between dust occurrence and the content ofunder 74 μm of coal charge. Reprinted with permission from Ref. (Kato, 2004). Copyright: (2004) The
Iron and Steel Institute of Japan.

Fig. 14 Coal particles in charging coal (SEM). Reprinted withpermission from Ref. (Kato, 2004). Copyright: (2004)
The Iron and Steel Institute of Japan.

tionship between the coal moisture and dust occurrence
was investigated using a dust occurrence tester. Fig. 12schematically illustrates the experimental apparatus(Kato, 2004).
Sample coal 1 kg in weight was put into the experimental apparatus from the top; the coal particles floating inside the tube were sucked by a blower until the tube inside
became visually clear of the particles, and the quantity ofthe particles collected was measured.
Fig. 13 shows the results (Kato, 2004). The dust occurrence increased as the moisture of coal decreased. Fig. 14
shows the photomicrographs of coal grains with different
moisture contents (Kato, 2004). With the high moisture
content, fine particles either adhere to coarse grains or
cohere with each other to form pseudo-particles withwater serving as a binder and the dust occurrence is low.
On the other hand, when the coal is dried for pretreatment, the pseudo-particles disintegrate into fine particles
and the dust occurrence increases.
Fig. 15 shows the relation between the fractions offines that are 74 μm or less in size in the feedstock coaland dust occurrence (Kato, 2004). As a result, it was presumed that the coal particles that are 74 μm or less in size
were mainly responsible for the dust occurrence.
From the above, it was clarified that agglomeration offine coals was important to reduce the dust occurrence
and stabilize the dry coal charging process.

Fig. 16 Outline of fluidized bed dryer. Reprinted with permission from Ref. (Kato, 2004). Copyright: (2004) The
Iron and Steel Institute of Japan.

Fig. 17 Process flow of DAPS. Reprinted with permission
from Ref. (Kato, 2004). Copyright: (2004) The Iron
and Steel Institute of Japan.

The application of the fluidized bed method for drying
and classification of fine coal in the cokemaking process
was studied as the first case in the world. Moreover, a fluidized bed coal dryer was developed that is capable of efficiently drying and classifying roughly 6,800 t/d of coal(Fig. 16) (Kato, 2004).
Fig. 17 shows the process flow of DAPS (Kato, 2004).
In the process, the coal is dried in the fluidized bed dryer117

Kenji Kato et al. / KONA Powder and Particle Journal No. 35 (2018) 112–121

Fig. 19 Comparison of non- or slightly caking coal ratio incoal charge. Reprinted with permission from Ref.
(Kato, 2004). Copyright: (2004) The Iron and SteelInstitute of Japan.
Fig. 18 Relation between bulk density and total dilatation coefficient of fine coal. Reprinted with permission from
Ref. (Kato, 2004). Copyright: (2004) The Iron andSteel Institute of Japan.

and fine coal is separated from coarser grains by the gas
flow, collected by a cyclone separator, and formed into
agglomerated by a roll compactor. The ratio of fine coal isabout 30 mass% of the coal charge. The agglomerated
fine coal is added to the coarse coal and charged into cokeovens.
The relation between the bulk density of coal charge
and total dilatation coefficient of fine coal was investigated. The result is shown in Fig. 18 (Kato, 2004). The
dilatation of fine coal increases when the bulk density is
increased. From the result, it is apparent that the agglomeration of fine coal not only suppresses the generation ofdust but also improves the dilatation of fine coal.
The coke strength from the DAPS process was compared the one from the CMC process under the same coal
blending conditions. As a result, the coke quality in the
DAPS was improved. The coke quality is thought to be
improved in the DAPS process owing to the increase in
the bulk density of coal charge, which is caused by a decrease in the moisture of coal charge (Nomura et al.,2004), and the improvement in coal dilatation, which is
caused by the agglomeration of fine coal.
Fig. 19 shows the comparison of non- or slightly-­
caking coal ratio in each process without deterioratingcoke strength (Kato, 2004). By the application of the
DAPS process to the cokemaking plant, it was found thatthe ratio of non- or slightly-caking coal in coal charge isincreased by 20 mass% compared with the CMC process
without deteriorating coke strength.
As a result, it was found that coke strength was improved in the DAPS process owing to increase in the bulk
density of coal charge, due to decrease in the moisture ofcoal charge. So, it was clarified that the DAPS process
was suitable for expansion of coal resources.

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3.3 SCOPE21 process
Research and development of a new cokemaking process —super coke oven for productivity and environmental enhancement toward the 21st century (SCOPE21)—
was conducted in Japan from 1994 to 2003 by the Japan
Iron and Steel Federation (JISF) (Nishioka et al., 2004).
Fig. 20 shows the SCOPE21 process flow (Kato, 2010).
The SCOPE21 process mainly consists of three units.
First is coal rapid preheating unit, second is coal carbonization unit and third is coke quality upgrading andquenching unit by coke dry quenching equipment. The
aim for dividing the whole process into three is to makefull use of the function of each process in order to maximize the total process efficiency.
Preheating the charging coal heated up from 330 °C–
400 °C in the coal pretreatment facility has the effect of
reducing carbonization time (Fig. 21) (Kato, 2010).
The pilot plant had a coal pretreatment facility, which
was the scale-up version of the bench scale plant and acoke oven (Fig. 22) (Kato, 2010). The coal pretreatment
facility was designed to have a 6 t/h coal throughput, andthe basic specifications were determined from the benchscale plant data. One coke oven was constructed. The
coke oven chamber was 8 m in length, which was almost
half of the length of the commercial plant, 7.5 m in height,
and 450 mm in width.
In the coal rapid preheating test, the coal was heatedslowly to 300 °C in a fluidized bed dryer, and then heated
rapidly to 380 °C in a pneumatic preheater, and carbonized in the coke oven (Matsuura et al, 2004; Kato et al.,2004, Matsuura et al., 2005). The quality of the obtainedcoke was measured by the JIS drum strength index(DI15015) ( DI: Drum Index). (Kubota et al., 2004). Non- or
slightly-caking coal was blended 50 mass% in the coalcharge. As a result, coke strength (DI15015) became about
2.5points higher than the conventional level by virtue ofthe rapid preheating effect and the increased bulk density(Fig. 23) (Kato, 2010). Pilot plant scale test of the SCOPE21

Kenji Kato et al. / KONA Powder and Particle Journal No. 35 (2018) 112–121

Fig. 20 Schematic diagram of the SCOPE21 process flow. Reprinted with permission from Ref. (Kato, 2010).
Copyright: (2010) The Iron and Steel Institute of Japan.

Fig. 21 Comparison of carbonization time between SCOPE21and conventional process. Reprinted with permission
from Ref. (Kato, 2010). Copyright: (2010) The Iron
and Steel Institute of Japan.

Fig. 23

Technologies for improving coke quality. Reprinted
with permission from Ref. (Kato, 2010). Copyright:(2010) The Iron and Steel Institute of Japan.

Fig. 22 Process flow of SCOPE21 pilot plant. Reprinted with permission from Ref. (Kato, 2010). Copyright:(2010) The Iron and Steel Institute of Japan.

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Fig. 24 Process flow of Oita No. 5 coke oven battery. Reprinted with permission from Ref. (Kato, 2010). Copyright: (2010) The Iron and Steel Institute of Japan.

Table 1 Specification of Oita No. 5 coke oven battery.
Reprinted with permission from Ref. (Kato, 2010).
Copyright: (2010) The Iron and Steel Institute ofJapan.
Equipment
Coal
pre-treating

Coke oven
CDQ

Fluidized bed dryer

Specification(Capacity)
155 dry-t/hPneumatic pre-heater 106 dry-t/h
Agglomerater

34 dry-t/h ~2

Coke oven chamber

64 ovens, 6.7 mH *0.45 mW * 16.6 mL
120 t/hprocess was conducted successfully and targets of the
project were confirmed by the pilot plant test (Sugiyama
et al., 2005) .
The SCOPE21-type new coke oven battery was constructed at Nippon Steel & Sumitomo Metal Oita works
from 2006 to 2008 and the operation of the new coke
plant was started in 2008. The coke production capacity
is 1 million ton per year. Fig. 24 shows the process flowof the new coke plant and Table 1 shows the main specification of Oita No. 5 coke oven battery (Kato, 2010). The
coal is dried in a fluidized bed dryer and fine coal is separated, and then agglomerated by an agglomerater. Next,
the agglomerated fine coal is added to the coarse coal, andcharged into coke ovens. The coal is pre-heated rapidly to
350 °C in a pneumatic pre-heater, and carbonized in thecoke oven.
The 2nd SCOPE21-type new coke plant was constructedat Nippon Steel & Sumitomo Metal Nagoya works and theoperation of the plant started in 2013 (Kato et al., 2013).
These two plants have been operated very smoothlywith high productivity and high non- or slightly-caking
coal ratio in coal charge.

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4. Conclusion
Coal is a very important resource for power generation,
cokemaking, gasification, etc. R & D of effective coal utilization technologies has been conducted. In this paper,
the trend of the coal gasification technology and new coalgasification technology, ECOPRO®, are introduced. Furthermore, new cokemaking technologies are discussed.
They are summarized as follows.
(1) New gasification technology the ECOPRO® has beendeveloping. ECOPRO® is a suitable process for low
rank coals gasification with high energy efficiency.
(2) To expand the coal resources for metallurgical cokemaking process, dry coal charging process DAPS wasdeveloped. Coke strength was improved in the DAPS
process owing to increase in the bulk density of coalcharge, due to decrease in the moisture of coal charge.
So, it was clarified that the DAPS process was suitablefor expansion of coal resources.
(3) Furthermore, new cokemaking technology SCOPE21
for improving coke quality was developed. New coke
plants of the SCOPE21-type were constructed at Nippon
Steel & Sumitomo Metal Oita and Nagoya works. The
new coke plants have been operated very smoothly.

References
DOE/NETL (Department of Energy / National Energy Technology Laboratory), Cost and Performance Baseline for Fossil
Energy Plants; Volume 3a: Low Rank Coal to Electricity:
IGCC Cases, (2011) 99–101.
Gräbner M., Ed., Coal gasification in a global context, in:Industrial Coal Gasification Technologies Covering Baseline and High-Ash Coal, Wiley-VCH Verlag GmbH & Co.
KGaA, Weinheim, Germany, 2014, pp. 3–9. doi: 10.1002/
9783527336913.ch02
Kato K., Development of dry-cleaned and agglomerated pre-

Kenji Kato et al. / KONA Powder and Particle Journal No. 35 (2018) 112–121

compaction system (DAPS) for metallurgical coke-­making,Ferrum, 9 (11) (2004) 810–815.
Kato K., Matsuura M., Sasaki M., Sakawa M., Komaki I., Effectof rapid preheating treatment on coal thermoplasticity andits evaluation method, Journal of the Japan Institute ofEnergy, 83 (2004) 868–874.
Kato K., Nakashima Y., Yamamura Y., Development of drycleaned and agglomerated precompaction system (DAPS)
for metallurgical cokemaking, SHINNITTETSU GIHO, 94(2006) 42–46. http://www.nssmc.com/en/tech/report/nsc/
pdf/n9407.pdf
Kato K., Expansion of coal resources for cokemaking, Journalof the Japan Institute of Energy, 87 (2008) 344–352.
Kato K., Development of new cokemaking technology(SCOPE21), Tetsu-to-Hagane, 96 (2010) 196–200.
Kato K., Suzuki Y., Development of coal utilization technologies and future tasks in cokemaking process, Journal of theJapan Institute of Energy, 92 (2013) 985–993.
Kosuge K., Takeda S., Mizuno M. and Kato K., Development ofcoal gasification technology (ECOPRO® process) for browncoals, Journal of the Japan Institute of Energy, 93 (2014)

1106–1114.
Kubota Y., Arima T., Kato K., Matsuura M., Nakai H., Sasaki
M., Sugiyama I., Evaluation of coke strength and coke sizein the SCOPE21 process, Tetsu-to-Hagane, 90 (2004) 686–
693.
Matsuura M., Sasaki M., Kato K., Nakashima Y., Effects ofCoal Blend Type and Preheating Temperature in Coal
Rapid Preheating Process on Coke Strength, Tetsu-to-­Hagane, 90 (2004) 656–660.
Matsuura M., Kato K., The structural analysis of rapid preheated coal using ESR spectroscopy, Journal of the Japan
Institute of Energy, 84 (2005) 426–430.
Nishioka K., Oshima H., Sugiyama I., Fujikawa H., Development of the Innovative Cokemaking Process (SCOPE21) for
the 21st Century, Tetsu-to-Hagane, 90 (2004) 614–619.
Nomura S., Arima T., Kato K., Coal blending theory for dry
coal charging process, Fuel, 83 (2004) 1771–1776.
Sugiyama I., Kato K., Nishioka K., Oshima H., Fujikawa H.,
Development of innovative cokemaking process SCOPE21,
The 5th European Coke and Ironmaking Congress(5thECIC), 2005, Stockholm, We 6:4.1.

Author’s short biography
Kenji Kato
Kenji Kato is a general manager of R & D institute, Nippon Steel & Sumikin Engineering Co. Ltd. since 2013. He graduated Chiba University and entered Nippon SteelCorporation in 1981. He was a general manger (2009-2012) of Nippon Steel Corporation,a general manager (2012–2013) of Nippon Steel & Sumitomo Metal Corporation. He
received his doctoral degree from Tohoku University (Environmental Science) in 2005.
His research area ranges over cokemaking, low rank coal utilization technologies andenvironmental technologies.

Keiji Matsueda
Keiji Matsueda is a general manager of head office, Nippon Steel & Sumitomo Metal
Corporation. He received his master degree from Nagaoka Universiyty of Technology
and entered Nippon Steel Corporation in 1991. His research covers metallurgical cokemaking technology.

121

KONA Powder and Particle Journal No. 35 (2018) 122–138/Doi:10.14356/kona.2018020

Review Paper

Powder Particles and Technologies for Medicine Delivery to
the Respiratory System: Challenges and Opportunities †Tomasz R. Sosnowski
1

Faculty of Chemical and Process Engineering, Warsaw University of Technology, Poland

Abstract
The paper discusses essential engineering challenges related to the application of powder medicines for
pulmonary delivery as inhaled aerosol. Starting from a physically based description of the complexity of aerosol
dynamics inside the respiratory system, the paper discusses several technical factors responsible for efficient drugdelivery to the lungs: (i) interparticle interactions—which can be tuned by selection and control of powder
manufacturing methods, (ii) inhaler design—as a determinant of flow dynamics through the inhaling device anddegree of powder dispersion, (iii) the dynamics of inhalation in a given inhaler—which is related to patient-device
interaction. Basic information on the standard (compendial) methods of the quantitative evaluation of dry powder
inhalers (DPIs) are presented with a special focus on the correct data interpretation and the consequences for invivo-in vitro correlation (IVIVC) problems. Some issues regarding the development of inhalation products(including generics) are also briefly highlighted. Finally, possible strategies of powder particle functionalization
to obtain the required bioavailability are outlined on the basis of knowledge on the physicochemical interactionsof inhaled particles with the lung fluids.
Keywords: inhalation, lung deposition, DPI, flow dynamics, mucus, pulmonary surfactant

1. Introduction
The idea of using aerosol particles as drug carriers
comes from the ancient times when the inhalation ofsmoke and fumes from burned plants appeared to induce
favorable health effects (Sanders M., 2011; Stein S.W. andThiel C.G., 2017). In modern times, it has been realizedthat the atomization of medicinal liquids to very small
droplets helps to transfer them to the respiratory systembeyond the upper airways (mouth and throat). Such a possibility of drug targeting to specific lung regions provided
the opportunity to treat pulmonary diseases locally withlow overall drug mass and minimized side effects. It also
became clear that aerosolized drugs need not necessarily
be a liquid, but can also be in the form of fine particles ofsolids.
The technical possibility of using dry powders as vehicles of drugs carried into the respiratory system is the
topic of this paper. This apparently simple idea of drugdelivery covers non-trivial challenges and many physicallimitations which need to be overcome if a reproducible

drug dose is to be delivered from a portable and inexpensive inhaling device.
This analysis starts with the overall characteristics ofphysical phenomena related to aerosol inhalation and particle deposition in the lungs. Next, the major challenges ofaerosol formation in inhaling devices are discussed withthe main focus on the proper design of dry powder inhalers (DPIs) and on the properties of powders as precursors
of inhalable aerosols. The dynamic aspects of theabove-mentioned problems are highlighted because very
often they are ignored in the analysis of particle deposition in the lungs and powder inhaler performance. Someessential information on aerosol evaluation using thecompendial (pharmacopeial) methods is also presented,
indicating their limitations which can lead to the inaccurate interpretation of data. Finally, some facts regarding
physical aspects of interactions between deposited particles
and the lung surface are discussed to show the relationships between particle properties and drug bioavailability.
All presented data make it possible to highlight potential
new opportunities of inhalation therapy with the use of
powder particles.

† Received 7 June 2017; Accepted 9 August 2017
J-STAGE Advance published online 30 September 20171Waryńskiego 1, 00-645 Warsaw, Poland
E-mail: tomasz.sosnowski@pw.edu.pl
TEL: +48-22-234-6278 FAX: +48-22-825-1440

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Copyright © 2018 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/).

Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

Table 1 Main benefits and drawbacks of drug delivery byaerosol inhalation.
Benefits

Drawbacks/limitations

1. Uncertainty of dose
1. Drug delivered directly to thedelivered locally to the
expected site of action in thetarget area
respiratory system: the dose canbe minimized, low side effects
2. Low enzymatic drug deactivation in the lungs: the dose canbe minimized

2. Technical challenges
related to drug formulation, dosing andaerosolization

3. Non-invasive, pain-free andeasy-to-use method of drugdelivery

3. Patient-dependent
efficiency of drugdeliveryFig. 1

General relationship between the nominal (metered)dose–MD, aerosolized dose–AD, emitted dose–ED,
fine particles dose–FPD and dose deposited at the target–DDT.

2. Basic concepts and the physics of inhalation
drug delivery
2.1 Drug inhalation as a unique method ofpharmacotherapy
Drug delivery by the inhalation of aerosolized medicines is a therapeutic method which has several advantages but also some essential drawbacks (Table 1).
The main benefit is related to minimization of the dose
which needs to be introduced to the organism to produce
the expected concentration in the target site (i.e. on thesurface of the respiratory system). For inhalation devices(inhalers), it is often enough to deliver only several micrograms of the active pharmaceutical ingredient (API)to result in the local lung dose comparable to almost
one hundred milligrams delivered by injection or tablets(Alangari A.A., 2014). With a natural and painless application mode, inhalation therefore presents a safe and convenient method of pharmacotherapy. On the other hand,unlike other drug delivery systems (tablets, pills, injections), the inhalation of aerosolized medicine does notguarantee precise dosing. The reason is that none of thesequential processes of aerosol generation, aerosol evacuation from the inhaler and regional deposition in the respiratory system is 100 % efficient, which means that
only a fraction of the drug initially loaded to the inhaler
can be transferred to the target area, Fig. 1. Moreover,this number is noticeably variable since it depends bothon the performance of the inhaling device and on the patient’s individual capabilities to use it correctly, Fig. 2. Asstated earlier, there is a long list of technical problems
which need to be solved to achieve a reliable and reproducible drug delivery system based on powder inhalation,and they will be addressed herein.
It is obvious that not all aerosol particles can be used as
effective drug carriers. To play that role, particles must be
inhalable, i.e. small enough to be drawn with air into theFig. 2

Schematic path from the drug to target deposition.

mouth or nose. Moreover, they must be capable of penetrating beyond the naso-oro-pharynx and the upper bronchial tree so they can reach the lower respiratory systemand settle there.
Interestingly, the preferred deposition region may bedifferent for various types of inhaled drug, since the occurrence and surface density of cellular receptors for drug
binding/stimulation differs along the walls of the bronchial and pulmonary airways (Howarth P.H., 2001;
Barnes P.J., 2004; Usmani O.S. et al., 2005; Pirożyński M.
and Sosnowski T.R., 2016). For instance, muscarinic receptors (e.g. M3) are located mainly in the central airways, so the relevant drugs (bronchodilating cholinergic
antagonists) should be preferentially delivered to theselung regions. The distribution of the receptors for beta2-mimetics requires the deposition of such drugs bothin the central and distal respiratory tract, although the alveolar region can be omitted since no bronchodilating effect is expected there. Glucocorticoid receptors (GRs) aredistributed all over the lower respiratory system, but steroids should not penetrate in large amounts into the lung
periphery since we want to avoid their undesired absorption into the circulation from alveoli. It is therefore clearthat different aerosol drugs can be formulated differently
to obtain the most desired therapeutic effects.

2.2 Physics of aerosol particle flow and depositionin the respiratory tract
The whole respiratory tract acts as a filter for inhaledaerosols where particle flow, penetration and deposition in
the respiratory system are governed by general physical123Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

Fig. 3

Basic deposition mechanism of airborne particles in the
respiratory airways: 1 - diffusion, 2 - inertial impaction, 3 - sedimentation, 4 - interception.
Fig. 4laws (Heyder J. and Svartengren M.U., 2002; DarquenneC., 2012; Tsuda A. et al., 2013; Cheng Y.S, 2014). Obviously, particle ‘filtration’ in the respiratory system issequential, i.e. only those particles which have avoided
elimination in the previous generations of the bronchial
tree can penetrate and deposit in the next ones. This factor must be considered if we try to target any specificregion with inhaled aerosol medicine (Zanen P., 2003;
Kleinstreuer C. et al., 2008). Fig. 3 shows all particle
deposition mechanisms which are believed to predominate in respiratory airways.
Particles with a high momentum (mass × velocity) hit
the walls of the air ducts due to inertial impaction, mostly
when the airflow rapidly turns. It takes place, e.g. in themouth (hard and soft palate), throat and at bifurcations oflarge bronchi (Moskal A. and Gradoń L., 2002; Sosnowski
T.R. et al., 2007). Particles which are able to penetratethese regions but have a relatively high mass can still fall
gravitationally at an appreciable rate. Therefore, thechance of their penetration beyond the small bronchi,
where aerosol residence time is extended due to a decrease of the average flow velocity, is minute. Moreover,the diameter of the airways in this region is reduced so
the gravitational settling becomes effective. Submicronparticles, which have a low inertia and also a negligible
sedimentation rate, penetrate to the lung periphery to agreater extent. They can reach the airway walls of that
region by Brownian diffusion.
Presented facts allow the development of quantitative
methods for predicting particle deposition in various lungregions (Longest P.W. and Holbrook L.T., 2012; Tu J. etal., 2013). Different approaches to that problem are presented in the next section.

2.3 Quantitative models of deposition of inhaledparticles
The deposition of inhaled drug particles can be quantitatively predicted by adaptation of the models which havebeen originally elaborated in the field of inhalation toxicology. Such semi-empirical models are often based on

124

Regional and total particle deposition in the respiratory
system as a function of particle size—calculations
based on the ICRP model and Multi-Path Particle
Dosimetry software (MPPD, 2015) for deep and slow
oral inhalation (TV = 1500 ml, breathing cycle
time = 12 s). Lung regions: Pulm = pulmonary (alveolar), T-B = tracheobronchial, E-T = extra-thoracic (airways of head and neck). The particle size range withthe lowest deposition is highlighted.

the experimental data fitted by relatively simple mathematical formulae which can estimate the deposition ofparticles with different sizes and for variable breathing
regimes. Such models (e.g. ICRP (Annals of the ICRP,
1994)) calculate only the regional deposition efficiencies(in the upper airways, tracheo-bronchial region, small
bronchi or alveolar zone) which, by summing up, givealso the total deposition in the whole respiratory system(Fig. 4).
Regional deposition can be derived also from othermodels which consider more precisely the predominating
deposition mechanisms in various regions of the respiratory system. For instance, Finlay W.H. and Martin A.R.
(2008) proposed mathematical formulae for the oro-­pharyngeal region and the lower respiratory tract deposition, taking into account the residence time and the average
local particle aerodynamics. In this model, the average
Reynolds (Re) and Stokes (Stk) numbers are used to generalize air and particle flow in the respiratory system.
A more detailed approach to the quantitative description of particle deposition is based on particle tracking
during their flight through the respiratory airways. Reliable quantitative data regarding bronchial tree geometry(airway lengths, diameters and branching angles) areneeded to predict the average airflow rates and particle
behavior in each generation. Symmetrical or asymmetrical lung geometry can be used (Yeh H.C. and SchumG.M., 1980) where the first leads to a single path while
the second leads to multipath trajectories of aerosol particle transport (Asgharian B. et al., 2001). In the multipathtransport, a random choice of geometry is assumed resulting in a so-called stochastic lung deposition model(Koblinger L. and Hofmann W., 1990).

Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

In these models, the fractional deposition in each generation of the bronchial tree can be calculated which gives
more detailed information on drug distribution in the lungs.
It may be mentioned that some of the above-discussed
models are accessible in the user-friendly calculators
which are freely available on the Internet (MPPD, 2015;
ARLA, 2008).
The most precise predictions of local particle dynamics
and deposition can be obtained from detailed calculationsof the particle trajectory within the numerically reconstructed geometry of the selected fragments of the respiratory system. It can be conveniently done applying
computational fluid dynamics (CFD) methodology (Tu J.
et al., 2013). Commercial packages help to predict the actual three-dimensional airflow field in the defined airway
geometry by numerically solving the Navier-Stokes equation within the domain decomposed into finite volume
elements. Even with the use of a commercial computational
package, the task itself is not trivial and requires correct
construction and optimized resolution of the numericalmesh followed by the application of a suitable solver withappropriate boundary conditions. Tracking of each particle in the airflow field is done by the Lagrangian approach, i.e. solving the mass balance of a single particle.
The most general description combines both deterministic
and stochastic forces acting on particles, the latter being
associated with Brownian diffusion, i.e. particle motion
caused by random collisions with air molecules. The
Langevin equation which describes particle acceleration
under such conditions takes the form (Moskal A., 2011):
du p
18 μ
6
6


Fext 
FB
u p  u 23
ρp d pdt
πρpd pπρ p d p 3(1)

where up and u denote the velocity of particle and air, respectively, dp – particle diameter, ρp – particle density, μ –air viscosity, Fext – external forces affecting the particle
trajectory (gravity, electrostatic or magnetic interactions,etc.) and FB – the Brownian force which plays a role
mainly for submicrometer-size particles. For a sphericalaerosol particle suspended in the air, the Brownian force
is given by:
FB  mpα B Z(2)where αB is the characteristic magnitude of acceleration
due to thermal excitation, and can be expressed as:
αB 

2πS 0
Δt

(3)

S0 is a spectral intensity of a white noise which can be conveniently used to model the stochastic Brownian effects:
S0 

216 μf k BT
π 2d p5 ρp2Cs(4)

where T is the absolute temperature, k B is the Boltzmann

constant, and Cs the Cunningham slip correction factor. Z
in eq. (2) is the dimensionless vector with random direction and ∆t denotes the time step of numerical integrationof the trajectory equation. It can be noted that the Brownian force acts on aerosol particles all the time but its direction and magnitude are randomly changed (through therandom updating of value of Z) at the end of every time
step ∆t. The presented method of numerical computations
can be used to analyse particle motion in a human breathing system also at realistic non-steady-state flow conditions (Moskal A. and Gradoń L., 2002). Numericalsolutions allow finding the trajectory of any particle of thedefined size and properties, and eventually finding theplace of particle deposition on the airway wall. If thecomputations are repeated many times for thousands ofparticles with various sizes, the results of particle deposition probability (i.e. deposition efficiency) in the analysed
region is obtained as a function of the particle size.
As in any type of particle separation process (e.g. conventional air filtration), a certain particle size range exists
where none of the previously mentioned mechanisms issufficiently effective. Such particles (typically 0.3–
0.8 µm) can be exhaled without significant previous deposition in the respiratory system. In the example of therelationships of regional deposition efficiency vs. particle
size shown in Fig. 4, the minimum of total deposition in
the size range referred to above is clearly seen. Interestingly, some systems dedicated to aerosol delivery to thelungs may take advantage of a non-optimal deposition.
For instance, e-cigarettes are designed in a way whichallow a visible mist (typically composed of fine dropletsof glycerine and propylene glycol) to be exhaled since thismimics the use of classic (i.e. tobacco) products. All droplets released from e-cigarettes are smaller than 2 µm
(mass median diameter ~0.4 µm), for which the predicted
deposition in the respiratory system is less than 50 %,independent of the breathing maneuver (Sosnowski T.R.
and Kramek-Romanowska K., 2016).

2.4 Aerosol dynamics and other factors influencing
particle deposition during inhalation
It is commonly agreed that the aerodynamic particle
diameter da is the most suitable measure of the particle
ability to penetrate and deposit within the respiratory system. The aerodynamic diameter is defined as: 1 ρp da  dp  χ ρw 

0.5(5)

where ρw denotes density of water, and χ the dynamic
shape factor of the particle. Only particles with da < 5 µm
are expected to be inhaled deeply to the bronchial tree
where they eventually settle. Aerosol particle size distribution based on the aerodynamic diameter is typically125

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assessed by standard compendial methodology using
multi-stage (cascade) impaction separators: NGI (NextGeneration Impactor), Andersen, Marple-Miller or impinging jet impactors (USP, 2008; European Pharmacopoeia, 2013). This type of determination of the aerosol
particle size distribution is an indispensable step in thepharmaceutical development and validation of orally inhaled medical products (CHMP, 2009), and some detailsof such characterizations of aerosol drug particles will be
discussed in section 3.3.
The aerodynamic diameter is a disputable criterion ofparticle behavior in the lungs if the particles are non-­compact in shape, e.g. plate-like or needle-like, when interception can become the predominant deposition
mechanism (Fig. 3). Moreover, the aerodynamic size
properly describes the particle settling time under gravity
or inertial forces, assuming that a particle is carried with
air at constant velocity. In reality, it is obviously not true.
Inhalation is a dynamic (time-dependent) process inwhich a certain volume of air is pumped through the airways at variable acceleration and deceleration. Therefore,
the aerodynamic size has a different influence on particle
behavior depending on the time-instant during inhalation.
This complicates analysis of the processes of aerosol penetration and deposition in the respiratory system. In many
theoretical and experimental analyses of aerosol inhalation and deposition, the constant flow rate is assumed(such as the mean flow of the inspiration, e.g. Matida
E.Z. et al., 2004; Zhang Z. et al., 2005; Farkas A. andBalazhazy I., 2008; Ma B. and Lutchen K.R., 2009),
which is an inaccurate simplification. Some studies showthat particles in the realistic non-steady inhalation flow
show dissimilar dynamics as compared to the constantflow conditions, and this leads to a different spatial distribution of particle deposition (Moskal A. and Gradoń L.,
2002; Sosnowski T.R. et al., 2007). The influence of flow
dynamics on particle deposition can be demonstrated by asimple example. Fig. 5 schematically shows the dynamics
of the inhalation phase and the relationship between thetemporal volumetric flow rate Q(t) and two characteristic
values—the mean flow:
t

1 inh
Qˆ 
Q t dttinh 0(6)

and the maximum flow value, Qmax = PIFR (peak inspiratory flow rate). It is important to note that the flow value
equal to Q̂ occurs in reality only at two instants of time (t1and t2) during the whole inspiration.
The temporal dimensionless Stokes number, being an
indicator of inertial deposition (impaction), is defined as:
Stk 

ρpud p 2
μL0(7)

where—in addition to already defined variables—L0 de-

126

Fig. 5

Relationships between real flow dynamics Q(t), average
flow rate Q̂ and the peak inspiratory flow rate (PIFR).

notes the characteristic local dimension of the airways. It
can be easily seen that the same local value of the Stokes
number is obtained if:
ud p 2  const.

(8)

Consequently, for a variable airflow rate during inhalation, a particle with dp = 10 µm which moves at a velocity
equal to the air velocity u1 will be locally (L0 = const) deposited by impaction with the similar efficiency as a 5-µm
particle at the velocity 4u1. The analogous analyses can bedone also for other deposition mechanisms and they willshow that at variable airflow, one cannot unambiguously
link the regional deposition efficiency with the aerodynamic (or geometric) particle size.
The complexity of the description of dynamic behavior
of inhaled powder particles in the lungs is additionallycaused by other issues:– in general, particles of medical aerosols are polydisperse;– quite often powder particles are hygroscopic, so theiractual size in the respiratory system will increase andtheir density will also be changed (Schum G.M. andPhalen R.F., 1997; Asgharian B., 2004; Winkler-Heil R.
et al., 2014).
– particles at high concentrations may coagulate or movecollectively in a so-called ‘cloud motion’ (Broday D.M.
and Robinson R., 2003);– bronchi and bronchioles are short-tubes, so inlet effects
have an influence on the flow pattern—e.g. the secondary flows are formed (Zhang Z. and Kleinstreuer C.,
2002; Fresconi F.E. and Prasad A.K., 2007);– due to flow periodicity, the analysis based on the local
f low regime (laminar/turbulent) according to the
Reynolds number as a basic criterion is inadequate;– in DPIs, particles can appear in different phases of inhalation which has an influence on their transport in
the respiratory system (see section 3.2).
Flow dynamics influences not only the behavior of particles in the respiratory system but also the performanceof inhaling devices (aerosol formation and emission). This
problem will be discussed in section 3.

Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

3. Technical problems of effective powder
drug delivery by inhalation
Several books, book chapters and review papers arefocused on a variety of technical solutions required for
drug delivery of aerosolized powders via inhalation(e.g. Dunbar C.A. et al., 1998; Zeng X.M. et al., 2000;
Borgström L. et al., 2002; Vanbever R., 2003; Newman S.
and Peart J., 2009; Hoppentocht M. et al., 2014; Berkenfeld
K. et al., 2015; Carvalho S.R. et al., 2015; de Boer A.H. etal., 2017). Here we will highlight the critical issues. Assuming that aerosol particles within a certain size-range
are required for effective lung treatment by inhalation, thefollowing technical problems must be identified:– raw powders with the required particle size and surface
properties must be prepared. Fine aerosol particles cannot be obtained from a powder composed of large
grains;– in addition, the surface properties of powders must assure that particles are not too cohesive so that theirflow, fluidization and de-agglomeration are easily obtainable in a given inhaling device (Zeng X.M. et al.,2000);– such powders must allow the formation of reproducible
inhalable API doses in the range of several to some
hundreds of micrograms. This frequently requires
blending the API grains with additional powder. Anhydrous lactose or lactose monohydrate particles are typically used as the excipient, and it must have an
optimized particle size and surface properties to ensure
flowability and the required de-agglomeration of theblend upon aerosolization (Pilcer G. et al., 2012);– optionally, the suitable API powder can be preparedwithout the excipient (Healy A.M. et al., 2014). In thatcase, the powder should possess special properties
which can be obtained by particle engineering methods(Kaialy W. and Nokhodchi A., 2015)—see section 3.1;
– powder properties must be stable during the typicalshelf lifetime of pharmaceutical products (typically 3
years);– the medical powder must be packed in capsules or
blisters with suitable properties to guarantee their efficient emptying during inhalation (Martinelli F. et al.,2015). Another choice is the use of reservoir-type inhaling devices, when the powder dose is metered immediately prior to the inhalation (Islam N. and GladkiE., 2008);– the inhaling device itself must be optimized in a way toensure reproducible powder metering and aerosolization (emitted dose: ED, fine particle dose: FPD). At thesame time, the device should be easy to use, ergonomic,
mechanically resistant and inexpensive in production.
Certain conditions must be met regarding the internal
aerodynamic resistance of the inhaler (the airflow

through the device must match the inhaling force of thepatients) (Hoppentocht M. et al., 2014)—see section 3.2.

3.1 Essential properties of powders used in drugdelivery by inhalation
To be effective vehicles for inhaled drugs, powder particles must be de-agglomerated in the airflow to form micrometer-size particles as schematically shown in Fig. 6
The outcome of this process depends on inhaler design,
applied flow rate and powder properties. This is why thepharmaceutical powder has to be properly prepared before
it can be used as a drug carrier. The main cohesive interactions which act against powder redispersion are caused
by van der Waals forces, electrostatic and capillary forces,by hydrogen bonds and mechanical interlocking due tosurface roughness (Zeng X.M. et al., 2000; RamachandranV. et al., 2015). These interactions depend not only on theparticle properties and their preparation method, but also
on the ambient conditions such as air humidity.
Strategies which are used to prepare powder particles
with the properties that facilitate their de-agglomeration
include: (i) controlling the surface smoothness of the particles (Chew N.Y.K. and Chan H.-K., 2001; Geller D.E. etal., 2011), (ii) increasing interparticle distance, e.g. byadding nanoparticles (Begat P. et al., 2005), (iii) changing
the properties of the particle surface, e.g. by coating with,e.g. leucine, magnesium stearate or surfactants asforce-control agents (Begat P. et al., 2009; Sosnowski T.R.
and Gradoń L., 2010). It can be also be beneficial to use
micrometer-size nanostructured (partly porous) particles
instead of compact ones with the same size (Tsapis N. etal., 2002; Jabłczyńska K. et al., 2015). All these strategies
can be used both for drugs prepared as interactive mixtures (API-excipient) and for excipient-free formulations.
Inhalable particles can also be developed with API embedded in a polymer matrix with PLGA (poly(lactic-co-glycolide) acid) being the most common matrix
builder (Liang Z. et al., 2014). This drug delivery system
has the additional advantage of sustained drug release in
the target area. We should also mention a novel concept of
inhalation powders based on the application of solid lipid
nanoparticles (SLN) and nanostructured lipid carriers(NLC) forming a dry lipid matrix which can be loadedwith the API and transferred to the lungs from DPIs without additional excipients (Weber S. et al., 2014; Li Y.Z. etal., 2010).

Fig. 6De-agglomeration of powder drug in the airflow.

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Fig. 7

Examples of different shape and structure of powder particles obtained by the controlled spray-drying of various
precursors (unpublished SEM images from author’s laboratory).

Spray drying, spray-freeze drying and enhanced crystallization/precipitation (ultrasonic-assisted or utilizing thesupercritical fluid technology) are applied to obtain engineered powder particles. We will skip the detailed characteristics of these methods as their thorough description
can be found elsewhere (Gradoń L. and Sosnowski T.R.,
2014; Kaialy W. and Nokhodchi A., 2015). Due to thetechnological feasibility and easy scale-up, spray drying
is probably the most convenient method of producing
inhalable powders. It also allows control of the particle
structure, size and aerosolization properties (Vehring R.,
2008; Weers J.G. and Miller D.P., 2015). Correct selectionof the composition and concentration of the precursor (i.e.
liquid solution or suspension), as well as of the drying
parameters are decisive in obtaining powders with thedesired particle size and shape (Nandiyanto A.B.D. andOkuyama K., 2011; Kramek-Romanowska K. et al., 2011).
Fig. 7 shows some examples of different powder structures which can be obtained by tuning the parameters of
the spray-drying process into a conventional laboratory-­
scale device with pneumatic atomization of liquid precursors.

3.2 Inhaler design and performance
In all powder inhaler devices, aerodynamic stresses areused to fluidize the powder and de-agglomerate particle
clusters to maximize the number of individual fine particles. The majority of DPIs currently available in the market belong to so-called ‘passive’ devices (Islam N. and
Gladki E., 2008), where the aerosol is formed solely due
to powder interaction with the flow generated by the patient’s inhalation. In all such devices it is necessary to
maximize the transfer of airflow energy to the powder,possibly without useless dissipation. This can be effectively done by the creation—in a logical way—of local
turbulence or other effects such as flow focusing or fluctuations (Gac J. et al., 2008; Sosnowski T.R. et al., 2014).
However, flow arrangements of this type always increase
the aerodynamic resistance (the pressure drop) in the inhaler, so the final design of a DPI must be optimized. It is
important to note that erroneous concepts of aerosolization chambers can result in completely inefficient powder

128

Fig. 8Comparison of two hypothetical aerosolization systems
with the same aerodynamic resistance but disparate
dispersion efficiencies due to a different location of thepowder layer (grey rectangle).

redispersion. This obvious rule is shown schematically in
Fig. 8 by presenting two hypothetical inhaler chambers ofidentical design and aerodynamic resistance, but with totally different performance regarding the aerosol emission.
Aerodynamic resistance of the inhaler is a very important issue which needs to be well understood since it often
leads to ambiguities. The intrinsic inhaler resistance isdefined by the equation (Clark A.R. and Hollingworth
A.M., 1993):
RD 

ΔP
Q

(9)

where ΔP denotes the pressure drop (typically in hPa) andQ the volumetric airflow rate (typically in liters per minute, L/min).
Eq. (9) can be derived from the well-known relationship describing the local pressure drop:

ΔP  γ

ρu 2
2

(10)

where γ denotes the local resistance coefficient, which canbe assumed independent of the airflow rate in the range
relevant to inhalation (30–120 L/min). This equation canbe rewritten as:
ΔP γρ  Q  2 
2  A

(11)

where A denotes the cross-sectional area for the airflow.
After substituting:RD 2 

γρ
2 A2

(12)

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Eq. (9) is obtained directly.
Passive DPIs have different degrees of aerodynamic resistance, typically in the range of 0.05–0.2 hPa0.5min/L(or: 30–120 Pa0.5s/L). At the given inspiratory effort,
low-resistant (L-R) DPIs allow high flow rates to be obtained at which good aerosolization is achieved. In thecase of high-resistant (H-R) DPIs, similar efforts will produce lower flow rates, however, the flow restriction obtained in such inhalers should cause strong aerodynamic
effects and a similar powder deaggreation as in the
low-resistant devices at higher flows. This is why DPIs
need to be tested at the fixed pressure drop (the standard
value is 4 kPa (USP, 2008; European Pharmacopoeia,2013) not at a fixed flow rate.
A frequent mistake is the comparison of different DPIs
based on the criterion of the optimum volumetric flowrate (Qopt needed to get aerosol with maximized FPD). It
is often believed that a low Qopt is always equivalent to abetter performance of the DPI. But a low Qopt actuallymeans a high resistance of the inhaler, which may limit
correct operation by all groups of patients due to the demands of high inspiratory efforts. It is easier to obtainhigh flow rates in L-R DPIs, so even if they work sub-­optimally at Q < Qopt, they can be used with some successby patients who may be not able to use H-R DPIs. The
problem of L-R inhalers is that they are typically flow-­dependent, i.e. the mass and particle size distribution of
the aerosol they release are significantly improved when
flow increases (Weuthen T. et al., 2002; Azouz W. et al.,2015). Powder de-agglomeration is better at high airflow
rates but at the same time the aerosol velocity at the inlet
to the mouth becomes higher, which increases undesired
drug deposition in the oro-pharynx. For H-R DPIs, theairflow through the device is limited, and dependence of
their performance on the flow rate is lower. Concluding
this analysis, it may be stated that there should be an optimum of flow resistance in DPIs. The flow must be restricted to produce the high aerodynamic stresses
required for good aerosolization of the powder, however,if the overall resistance of the device is too high, it can
exclude a large group of patients from proper use of suchdevice. Elimination of the problem of DPIs f low-­dependence is achieved in ‘active’ DPIs which utilize, forinstance, the compressed gas to facilitate powder de-­agglomeration to fine particles. More than a decade ago,
Exubera® was developed as an active DPI for insulin delivery, however—due to various reasons—it was withdrawn from the market in 2007 (Heinemann L., 2008).
Another active DPI—Spiromax® —has emerged recently
for the delivery of drugs for asthma and COPD patients(Canonica G.W. et al., 2015).
Similarly to particle deposition in the lungs, drug inhalation from passive DPIs is a dynamic process. The aerosol is formed and released from the device during the

given (rather short) period of the inhalation. Let us recall
the flow curve already shown in Fig. 5 to analyse thisprocess. Two different situations are depicted in Fig. 9.
Assuming that the two DPIs denoted as 1 and 2 have asimilar aerodynamic resistance but a different principle ofpowder release, we can see that the aerosol is emitted
from inhaler 1 during time period t1 ÷ t1’, but from inhaler
2 during time period t2 ÷ t2’. Fig. 9a shows the corresponding flow rate, i.e. inhalation curve, while Fig. 9bshows the corresponding volume of air aspirated to thelungs.
Let us note that aerosol is emitted from inhaler 1during a short period which is finished at t1’, i.e. before
the maximum flow rate Qmax is achieved. In contrast, inhaler 2 is activated later (at t2) by the flow rate close to
Qmax and the release time is longer, so the aerosol is introduced to the air stream until t2’, which is not far from theend of inhalation, tinh. It can be expected that the quality(size distribution) of aerosol produced at higher flow rates,
i.e. in case 2, will be more favorable than in case 1.
The graph of inhaled volume (Fig. 9b) shows that when
the aerosol is totally emitted from inhaler 1, the remaining volume of air to be inhaled is still large (Vr1), whichmeans that the released particles can be carried even to
the lung periphery. In contrast, after the entire dose ofaerosol is released from inhaler 2 (at t2’), a small volume
of air Vr2 remained for inhalation, so probably these particles can penetrate only the very first generations of thebronchial tree before the exhalation will begin.
The presented example shows another, often overlooked, factor which should be considered for the rational

Fig. 9(a) Inhalation curve Q(t) and periods of aerosol release(gray fields) for two DPIs; (b) the corresponding inhaled volume curve V(t) = ∫Q(t)dt and indicated remaining volumes of air inhaled after complete releaseof aerosol from both DPIs (Vr1 or Vr2).

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design of inhalation systems based on powder redispersion.

3.3 Understanding the compendial methods ofaerosol characterization
Aerosol particles of medicines intended for inhalationmust be evaluated by specialized methods to confirm thatthey have the proper size characteristics and reproducibility (USP, 2008; European Pharmacopoeia, 2013). Use of
impactors instead of other measuring techniques is necessary because the majority of formulations contain particles with different chemical composition, e.g. in DPIs
based on API-lactose blends or in combined products (twoor more drugs delivered in one inhalation). In such cases,
optical methods which are typically used for aerosol assessment (e.g. time-of-flight or light scattering/light diffraction) cannot be used because they do not distinguishparticles that carry different chemicals. Since only themass of API is of interest from the therapeutic perspective, all other particles should be ignored in such analyses.
Cascade impactors can sort particles into several (typically 5–8) size classes based on their inertial deposition
which is caused by flow acceleration at the consecutive
separation stages. In the testing of DPIs, the aerosolized
drug is drawn to the impactor via the inlet and the additional vessel (preseparator) capable of capturing large
grains of the excipient which usually also contains some
API is attached. Impactor inlet and preseparator are believed to mimic the upper airways (mouth and throat),
however, the particle separation efficiency of these impactor elements is not strictly defined. Material collected ateach stage of the impactor is then quantified by sensitive
chemical assays – typically high-performance liquid
chromatography (HPLC) – against the pharmacopeial
standard of the API under test. Chromatographic analysis
ensures that the API concentration is evaluated selectively
and assigned to the given size class of particles captured
at each separation stage. Thanks to this technique, thesize distribution based on drug mass is obtained, whichallows finding the most important indicators of the qualityof medical aerosol: fine particle dose (FPD), fine particle
fraction (FPF) and mass median aerodynamic diameter(MMAD). Due to their principle of operation, all impactors classify particles based on their aerodynamic size dadefined by equation (5). Assuming a quasi-spherical particle shape and density in the range of 800–1200 kg/m3, theaerodynamic particle diameter is almost the same(± 10 %) as the geometric diameter, dp. However, thesetwo diameters can be very different in the case of, e.g.
porous particles with an effective density in the range ofhundreds of kg/m3. In such cases, large particles (larger
than 10 μm) may still be effective as drug carriers for inhalation since their aerodynamic behavior and inertial

130

deposition is equivalent to smaller particles with a typicaldensity.
There are two major drawbacks to impactor particle
size analysis:– the size resolution is limited to only 8 classes which arevariable if the flow imposed during different assays is
not the same;– the measurements are time-consuming, expensive andsensitive to human factors. Errors can easily be madedue to an extensive number of manual operations (assembly/disassembly of the impactor, pipetting, labware
handling, impactor cleaning, etc.)
Until the Next Generation Impactor (NGI) was developed, inhalers could be tested only at several standard
airflow rates (e.g. 28.3, 60 and 90 L/min in the Andresen
cascade impactor) due to a lack of certified calibration forother flows. The NGI allows characterization of the aerosol
particle size at any flow rate in the range of 30–100 L/min,but also at lower values (down to 15 L/min). The aerodynamic cut-off size, dci, at each stage i depends on the applied f low rate and for 30–100 L/min, they can becalculated from the equation:
Qd ci at Q  d ci at 60LPM   60 

xi(13)

where xi is the unique exponent for the given separation
stage (MSP Corporation, 2008). A slightly modified correlation is valid for flow rates in the range 15–30 L/min.
Cut-off sizes for selected airflow rates are listed in Table 2.
As seen from Table 2, the NGI cannot determine thesize of particles larger than those captured at stage no. 1,
and this maximum diameter depends on the flow rate applied during DPI testing. According to the standard, themass median aerodynamic diameter (MMAD), which isoften considered the important parameter in comparing
different inhalation products, is calculated only taking
into account the drug particles within the range of cut-off
sizes specified for the numbered stages, thus ignoring the
API mass collected inside the inlet port and preseparator.
This leads to a risk of misinterpretation of the experimenTable 2 Nominal cut-off sizes [µm] for NGI impactor atselected airflow rates [L/min].
Stage no.

15 L/min

30 L/min

60 L/min90 L/min

1

14.1

11.7

8.06

6.12

2

8.61

6.40

4.46

3.42

3

5.39

3.99

2.82

2.18

4

3.30

2.30

1.66

1.31

5

2.08

1.36

0.94

0.72

6

1.36

0.83

0.55

0.40

7

0.98

0.54

0.34

0.24

Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

tal data. Since the range of particle sizes used for calculation of the MMAD depends on the applied flow (Table 2),
it will be incorrect to compare the MMAD obtained for
DPIs characterized by different resistance, RD. According
to the standard, they must be compared at the same pressure drop (4 kPa), hence at different flow rates. As particles eliminated before stage no. 1 are not considered in
the mass balance, then it is possible to achieve a low
MMAD (apparently a good value) even if a large amountof aerosol drug is contained in big particles deposited in
the impactor inlet port and preseparator, as shown in
Fig. 10. Therefore, the MMAD should be consideredrather as a quality parameter which allows verification if
different batches of a given inhalation product (i.e. with agiven DPI) deliver—at the fixed airflow rate—the aerosolwith a similar particle size distribution. According to thepresented discussion, it is incorrect to use MMAD as acriterion of comparison of different DPIs and drugs.
The troublesome aerosol particle sizing by cascade impactors can sometimes be replaced by fast and accurate
optical on-line measuring techniques such as laser diffraction, however, only under certain conditions. Thesemethods can be used, e.g. in carrier-free DPIs which aerosolize only a single API. It is also reasonable to apply
optical methods for pMDIs (pressurized metered dose inhalers), SMIs (soft mist inhalers) and nebulizers, assuming that all particles/droplets have a statistically identicalcomposition. In such cases, they contain the API mass
which is proportional to the cube of the particle diameter.
For aqueous droplets ρp ≈ ρw, according to eq. (5), we will
directly obtain the aerodynamic diameter. For other materials, the geometric diameters dp can be easily recalculated to da if the material density is known. Although
optical methods are not compendial, for some inhalers (e.g.
nebulizers), they have been demonstrated to be equivalent
to pharmacopeial impactors (Kwong W.T.J et al., 2000;
Ziegler J. and Wachtel H., 2005; Mao L. et al., 2010).

3.4 In vitro-in vivo correlation (IVIVC) problem
in aerosol inhalation
The aerodynamic size of drug particles is needed not
only to verify the reproducibility of the inhalation product(quality assurance) but also to confirm that the drug canbe expected to effectively penetrate to the target region in
the respiratory system. FPD (da < 5 µm) informs about thedose which has the best chance to reach the lower airways(USP, 2008; European Pharmacopeia, 2013). However, theapplicability of this criterion is still discussed within theissue of IVIVC, i.e. in vitro-in vivo correlation (Clark A.R.
and Borgström L., 2002; Newman S.P. and Chan H.-K.,
2008). This problem tries to find a possibly precise link
between the particle size of inhaled drugs and the expected health benefit and must, in fact, acknowledge thecomplexity of particle deposition discussed in section 2.
Some researchers claim that the mass of extra-fine particles (1–3 μm) is more relevant to the real deposition andhealth effects (de Boer A.H. et al., 2015). However, as
shown in Fig. 4, it is difficult to unequivocally indicate
the optimum particle size, in particular considering inter-­subject variability in inhalation flow dynamics and airway
geometry where both can be additionally altered in lungdisease. Mitchell J. et al. (2007) additionally pointed outthat the clinical response (the real in-vivo effect) will
depend not only on the actual deposition of drug particles
but also on the drug potency and the severity of lung disorder. These authors also discussed other limitations ofapplication of the results of aerodynamic particle sizing topredict the regional aerosol deposition in the respiratory
system. Cascade impactors are the technical devices
which operate at ambient temperature and at a constantflow rate, which is a completely different situation compared to real aerosol inhalation. Laboratory testing conditions may influence the particle size distribution, e.g. due
to evaporation of nebulized droplets (Zhou Y. et al., 2005)
or additional deagglomeration of powders (Sosnowski
T.R., 2008), which make such aerosols incomparable withthe ones entering the lungs during drug inhalation. Although some additional technical improvements of cascade impactors have been proposed such as a more
realistic mouth-throat model instead of the standard inlet(Copley M. et al., 2011), the problem of a direct conversion of the measured particle size to the real in-vivo drugdelivery and efficacy still remains unsolved (Clark A.R.
and Borgström L., 2002; Mitchell J. et al., 2007).

3.5 Innovative and generic drugs development
Fig. 10 Comparison of the real MMAD (A) of the aerosol andthe MMAD calculated only on the basis of particles in
the range limited to 0–11.70 µm, i.e. the sizes classified inside the NGI at 60 L/min (B).

At the end of the discussion of challenges and opportunities in using inhalable powders for drug delivery, we
should take a short look at the problems of developmentof inhalable medical products. Completely new inhalation

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concepts (i.e. the new molecules with new inhalers) require strictly defined, demanding and expensive procedures to become a candidate for the medial product. In
addition to precisely documented development steps,
clinical studies to confirm the efficacy and safety are always required. Since many patents for therapeutic molecules are expiring, there is a trend to develop the genericproducts as cheaper substitutes of drugs originally developed some years ago. The procedure required to introduce
a generic inhalation product to the market is simplified,
and—according to some regulations (e.g. in Europe)—
clinical studies are not required if therapeutic equivalence
is convincingly demonstrated (CHMP, 2009). Accordingly, the whole procedure is cheaper and faster, although
there is concern whether such an approach is fully justified. It should also be noted that the legislation regarding generic inhalation products is different worldwide(Pirożyński M., and Sosnowski T.R., 2016). In any case,an important issue is the quality of the powder drug andthe inhaling device, and both have to match the original
product closely regarding the aerodynamic performance(e.g. DPI resistance) and the API aerosol size distribution
obtained at different flow rates through the inhaler(CHMP, 2009).
Consequently, all key problems highlighted in the previous sections should be taken into account when thedevelopment of innovative or generic powder inhalation
products is considered.

4. Interactions of inhaled powders with lungsurface—towards functional particles
Powder properties should also be optimized regarding
the bioavailability of the drug they carry into the lungs.
Inhaled particles land on the wet surface of bronchi, bronchioles or alveoli, so they directly interact with the fluidlayers of the lungs. In conducting airways, particles comeinto contact with mucus and the drug molecules eventually reach the epithelium after penetrating across the layerof this complex viscoelastic liquid. Deposited particles
can be simultaneously transported along the airways dueto the action of ‘mucociliary escalator’, i.e. the longitudinal flow propelled by beating cellular cilia (Smith D.J. etal., 2007). Since the underlying epithelium is the main
target for inhaled bronchodilating and anti-inflammatory
drugs, it is important to prepare the aerosol drug carriers
in a way which facilitates API penetration through the
mucus blanket. In diseased lungs, the mucus is abundantand more viscous (Cone R.A., 2009), so less permeable
for inhaled drugs. In such a situation, inhalable powders
with a specific composition and properties can be useful.
According to a recent idea (Odziomek M. et al., 2012), theexcipient particles might contain a mucolytic agent such132

as N-acetylcysteine together with the stabilizing additive(e.g. dextran). Deposited particles of the drug bonded tosuch a carrier (in a similar way as in typical API-lactose
blends) are capable of rheologically thinning the mucus
due to interactions with the mucolytic agent which is released locally. This allows the drug to penetrate fasterthrough the mucus layer (Odziomek M. et al., 2015).
In the alternative concept, multicomponent powders combining both the mucolytic agent and the drug in a single
particle were proposed (Gradoń L. et al., 2009). The
described functional particles can be effectively preparedby spray-drying through the adjustment of process conditions to obtain powders with good aerosolization properties. Mucus rheology and mass transfer phenomena in raw
or modified mucus can be analysed by selected physicochemical methods (Schuster B.S. et al., 2013; Odziomek
M. et al., 2017).
Particles deposited in the respiratory (alveolar) region
interact not with the mucus but with the pulmonary surfactant (PS). The PS produced by type II alveolar cells
contains lipids (mainly lecithins) and some unique proteins (Parra E. and Perez-Gil J., 2015). True to its name,the PS demonstrates strong surface-active properties.
They have important consequences for lung physiology,
due to:– reduction of the work of breathing, i.e. the energy input
required to expand during inspiration a large surface ofthe lungs (~100 m2),
– several functions related to the lung clearance and improvement of other mass transfer processes in the pulmonary region (Sosnowski T.R., 2016).
It is important to note that PS is highly surface-active
under the dynamic conditions of breathing, i.e. during oscillatory variations of the air/liquid interfacial area. Bothtemporal and spatial fluctuations of the surface tension
along the interface take place due to surfactant mass exchange between the bulk liquid and the free interface, butalso due to flow and diffusion at the interfacial boundary.
Marangoni effects are generated due to the surface tension gradients providing the driving force for the hydrodynamic clearance of deposited particulates from thealveolar zone (Gradoń L. and Podgórski A., 1989; Gradoń
L. et al., 1996) - Fig. 11.
Such behavior of the air-liquid interface can be reproduced in the laboratory using specialized measuring devices, e.g. Langmuir-Wilhelmy balance, oscillating bubble
or oscillating drop tensiometers (e.g. Sosnowski T.R. etal., 2017; Kondej D. and Sosnowski T.R., 2013; Kondej D.
and Sosnowski T.R., 2016; Wüstneck R. et al., 2002).
These experimental systems allow determination of the
dynamic surface tension variations during the breathing-like compression and expansion of the interface with
the PS. Experimental measurements can also directly
demonstrate the occurrence of the Marangoni flows in-Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

Fig. 11 Dynamic surface tension in alveolar region. Marangoni flows and particle transport are due to dynamic
surface tension gradients σ (t).
∆duced by the variations of interfacial area. For some typesof inhaled medicinal aerosols (e.g. drugs with the desired
systemic absorption), it may be beneficial to extend theirresidence time in the alveolar region, so this kind of fasttransport would be undesired. Tuning the surface properties of particles (e.g. total surface area, porosity, wettability) may influence their interactions with the surfactant
which can extend the residence time and improve thelocal bioavailability of inhaled drugs (Sosnowski T.R. etal., 2003).
The results shown in Fig. 12 confirm that local disturbance of the air/liquid interface with a model PS generates
the surface tension gradient σ and, as a consequence, thesuperficial flows. In Fig. 12, the surface tension gradientis produced by the unidirectional compression of the interface, and the superficial flow is illustrated by a lateraldisplacement of tracer particles.
Similar flows can contribute to alveolar clearance invivo, i.e. to the effective removal of deposited particles (orparticles already captured by alveolar macrophages) fromalveoli as shown in Fig. 11.
Surface tension hysteresis measured in vitro for PS
shown in Fig. 13 is another characteristic dynamic feature of the pulmonary surfactant, and it can be used to
trace alterations in the dynamic surface tension of the PS
caused by deposited particles (Kondej D. and Sosnowski
T.R., 2013). In this way, physicochemical methods help toassess potential disturbance of the alveolar mass transfer
caused by inhaled particles, including powder drugs(Kramek-Romanowska K. et al., 2015). The results may
indicate which properties of the inhaled powders are required for the best drug bioavailability. These specificpowder properties can be obtained during their production by particle engineering methods highlighted in section 3.1.

Fig. 12 Experimental results (top view of the Langmuir-­
Wilhelmy balance) showing the flow of tracer particles at the air-water surface with the phospholipid
monolayer (as the model of PS) during unidirectionalsurface compression.

∆

5. Conclusions
The main intention of this paper was to indicate important technical issues of the use of aerosolized powder
particles as vehicles of drugs delivered to the lungs. Starting from the overall physical overview of the aerody-

Fig. 13 Example of surface tension hysteresis recorded in the
PS during oscillation of the air/liquid surface at aphysiological rate and temperature (results obtainedwith PAT-1M device, Sinterface, Germany).

namic particle transport in the respiratory system, theimportance of dynamic effects related to the non-steady
airflow during breathing was pointed out. Other difficulties and uncertainties in predicting particle flow anddeposition in the respiratory tract are related to the specific phenomena (e.g. particle coagulation, hygroscopic
growth) which can influence the dynamic behavior ofparticles in the lungs. The properties of powders and theselected issues related to their preparation for inhalation
purposes were briefly presented to indicate the key factors
in optimizing the inhalation product. The proper design

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of powder inhaling devices, i.e. DPIs, is another vital condition of successful drug delivery. Again, special attention was given here to the dynamic processes of aerosol
formation and entrance into the organism. This allowed
demonstration of the fact that for particles which are notdrawn in sufficiently early during the inhalation phase of
the breathing cycle, their deep penetration to distal lungregions will not be possible. Discussion of the uniquemethods of the characterization of aerosols produced in
the inhalers (including DPIs) was used to indicate common misinterpretations of certain experimental data. Finally, the possibility of designing powder particles with abetter pharmaceutical outcome was highlighted on thebasis of a brief description of physicochemical interactions between deposited particles and lung fluids (mucus
and pulmonary surfactant).
It should be realized that the physics of all processes ofpowder aerosolization, penetration through the respiratory system, deposition and interaction with the lung surface are so complex that we are still lacking theircomplete quantitative description. Classic considerations
which are often based on strong simplifications overlook
some key features of these processes and can lead to erroneous conclusions. It may have certain consequences inchoosing the appropriate steps in product development by
the pharmaceuticals industry, but also in non-optimal
therapeutic decisions made by physicians. It is therefore
always important to take into account the latest achievements in understanding aerosol generation from powders
and their deposition in the lungs.

FPD

Fine Particle Dose

H-R

High-Resistant (inhaler)

ICRP

International Committee for Radiological Protection

L-R

Low-Resistant (inhaler)

MD

Metered Dose

MMAD Mass Median Aerodynamic Diameter
MPPD

Multi-Path Particle Deposition (model)

NGI

Next Generation Impactor

PIFR

Peak Inspiratory Flow RatepMDI

Pressurized Metered Dose Inhaler

PS

Pulmonary Surfactant

SMI

Soft Mist Inhaler

T-B

Tracheo-Bronchial

TV

Tidal Volume

Across-sectional area (m 2)Cs

Cunningham slip correction factor (–)

daparticle aerodynamic diameter (μm)

dci

cut-off diameter of stage i (μm)

dpparticle diameter (μm)

FB

Brownian force (N)Fextexternal forces (N)kB

Boltzmann constant (J K–1)

L0

characteristic length (m)mmass (kg)Acknowledgements

ΔP

pressure drop (Pa)Q

airflow rate (m3s –1)

This scientific work was partly supported by the budget
for sciences in the years 2015–2018 as Research ProjectNo. 2014/13/B/ST8/00808. The author thanks Katarzyna
Jabłczyńska, M.Sc., for preparation of the spray-dried
powders and their SEM images used in this paper.

Qmax

maximum airflow rate (m3s –1)

Qopt

optimum airflow rate (m3s –1)

Q̂mean airflow rate (m3s –1)

RD

intrinsic aerodynamic resistance of a DPI(hPa0.5min L –1)

Re

Reynolds number (–)

S0

spectral intensity of fluctuations (m 2s –3)

Stk

Stokes number (–)

ttime (s)tinhtime of inhalation (s)Δttime step of numerical integration (s)Ttemperature (K)uair velocity (m s –1)

upparticle velocity (m s –1)

Vinhaled volume (L)Nomenclature
AD

Aerosolized DoseAPI

Active Pharmaceutical Ingredient

CFD

Computational Fluid Dynamics

COPD

Chronic Obstructive Pulmonary Disease

DDT

Dose Delivered to Target

DPI

Dry Powder Inhaler

ED

Emitted Dose

E-T

Extra-Thoracic (deposition)

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xi

exponent of the correlation in NGI (–)

Z

dimensionless vector (–)αBmagnitude of the acceleration of thermal excitations(m s –2)

γlocal resistance coefficient (–)μ

air viscosity (Pa s)ρpair density (kg m–3)

ρwwater density (kg m–3)

σsurface tension (N m–1)

σeq

equilibrium surface tension (N m –1)

χdynamic shape factor (–)

References
Asgharian B., A model of deposition of hygroscopic particles in
the human lung, Aerosol Science and Technology, 38 (2004)
938–947.
Asgharian B., Hofmann W., Bergmann R., Particle deposition
in a multiple-path model of the human lung, Aerosol Science and Technology, 34 (2001) 332–339.
Alangari A.A., Corticosteroids in the treatment of acute asthma.
Annals of Thoracic Medicine 9 (2014) 187–192.
Annals of the ICRP 24. International Commission on Radiological Protection (ICRP) Publication 66, Human respiratory
tract model for radiological protection. Oxford: Elsevier
Science; 1994.
ARLA. The Aerosol Research Lab of Alberta Respiratory
Deposition Calculator (2008) <www.mece.ualberta.ca/arla/
deposition_ calculator.html> accessed 10.05.2017.
Azouz W., Chetcuti P., Hosker H.S., Saralaya D., Stephenson J.,
Crystyn H., The inhalation characteristics of patients when
they use different dry powder inhalers. Journal of Aerosol
Medicine and Pulmonary Drug Delivery, 28 (2015) 35–42.
Barnes P.J., Distribution of receptor targets in the lung, Proceedings of American Thoracic Society, 1 (2004) 345–351.
Begat P., Morton D.A., Shur J., Kippax P., Staniforth J.N., Price
R., The role of force control agents in high-dose dry powder
inhaler formulations, Journal of Pharmaceutical Sciences,
98 (2009) 2770–2783.
Begat P., Price R., Harris H., Morton D.A.V., Staniforth J.N.,
The influence of force control agents on the cohesive-­adhesive balance in dry powder inhaler formulations,
KONA Powder and Particle Journal, 23 (2005)109–121.
Berkenfeld K., Lamprecht A., McConville J.T., Devices for dry
powder drug delivery to the lung, AAPS Pharmaceutical
Science and Technology, 16 (2015) 479–490.
Borgström L., Bisgaard H., O’Callaghan C, Pedersen S.,
Dry-powder inhalers, in: Bisgaard H., O’Callaghan C.,
Smaldone G.C. (Eds.), Drug Delivery to the Lung (Lung
Biology in Health and Disease), Marcel Dekker, Inc., New
York-Basel, 2002, pp. 421–448.
Broday D.M., Robinson R., Application of cloud dynamics to

dosimetry of cigarette smoke particles in the lungs. Aerosol
Science and Technology, 37 (2003) 510–527.
Canonica G.W., Arp J., Keegstra J.R., Chrystyn H., Spiromax, a
new dry powder inhaler: dose consistency under simulated
real-world conditions. Journal of Aerosol Medicine andPulmonary Drug Delivery, 28 (2015) 309–319.
Carvalho S.R., Watts A.B., Peters J.I., Williams III R.O., Dry
powder inhalation for pulmonary delivery: recent advancesand continuing challenges, in: Nokhodhi A., Martin G.P.
(Eds.), Pulmonary Drug Delivery. Advances and Challenges (Advances in Pharmaceutical Technology), John
Wiley & Sons, Chichester, UK, 2015, pp. 35–62.
Cheng Y.S., Mechanisms of pharmaceutical aerosol depositionin the respiratory tract, AAPS Pharmaceutical Science andTechnology, 15 (2014) 630–640.
Chew N.Y.K., Chan H.-K., Use of solid corrugated particles toenhance powder aerosol performance, Pharmaceutical
Research, 18 (2001) 1570–1577.
CHMP (Committee for Human Medical Products), Guideline on
the requirements for clinical documentation for orally
inhaled products (OIP) including the requirements fordemonstration of therapeutic equivalence between two
inhaled products for use in the treatment of asthma andchronic obstructive pulmonary disease (COPD) in adults
and for use in the treatment of asthma in children and adolescents, London: European Medicinal Agency, 2009.
Clark A.R., Borgström L., In vitro testing of pharmaceuticalaerosols and predicting lung deposition from in vitro measurements, in: Bisgaard K., O’Callaghan C., Smaldone G.C.
(Eds.), Drug Delivery to the Lung, Marcel Dekker, New
York, 2002, pp. 105–142.
Clark A.R., Hollingworth A.M, The relationship between powder inhaler resistance and peak inspiratory conditions inhealthy volunteers-implications for in vitro testing, Journalof Aerosol Medicine, 6 (1993) 99–110.
Cone R.A., Barrier properties of mucus, Advanced Drug Delivery Reviews, 61 (2009) 75–85.
Copley M., Mitchell J., Solomon D., Evaluating of the Alberta
throat: an innovation to support the acquisition of moreclinically applicable aerosol aerodynamic particle sized
distribution (ASPD) data in oral inhaled product (OIP)
development, Inhalation, 5 (2011), 12–16.
Darquenne C., Aerosol deposition in health and disease, Journalof Aerosol Medicine and Pulmonary Drug Delivery, 25(2012) 140–147.
de Boer A.H., Gjaltema D., Hagedoorn P., Frijlink H.W., Can‘extrafine’ dry powder aerosols improve lung deposition?,
European Journal of Pharmaceutics and Biopharmaceutics,
96 (2015) 143–151.
de Boer A.H., Hagedoorn P., Hoppentocht M., Buttini F.,
Grasmeijer F., Frijlink H.W., Dry powder inhalation: past,present and future, Expert Opinion on Drug Delivery, 14(2017) 499–512.
Dunbar C.A., Hickey A.J., Holzner P., Dispersion and characterization of pharmaceutical dry powder aerosols, KONA
Powder and Particle Journal, 16 (1998) 7–45.
European Pharmacopoeia, 8th ed., Council of Europe, Strassbourg, 2013.

135

Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

Farkas A., Balashazy I., Quantification of particle deposition inasymmetrical tracheobronchial model geometry, Computers in Biology and Medicine, 38 (2008) 508–518.
Finlay W.H., Martin A.R., Recent advances in predictive understanding of respiratory tract deposition, Journal of Aerosol
Medicine and Pulmonary Drug Delivery, 21 (2008) 189–
206.
Fresconi F.E., Prasad A.K., Secondary velocity fields in the
conducting airways of the human lung, Journal of Biomechanical Engineering, 129 (2007) 722–732.
Gac J., Sosnowski T.R., Gradoń L., Turbulent flow energy foraerosolization of powder particles, Journal of Aerosol Science, 39 (2008) 113–126.
Geller D.E., Weers J., Heuerding S., Development of an Inhaled
Dry-Powder Formulation of Tobramycin Using PulmoSphere™ Technology, Journal of Aerosol Medicine andPulmonary Drug Delivery, 24 (2011) 175–182.
Gradoń L., Podgórski A., Hydrodynamical model of pulmonary
clearance, Chemical Engineering Science, 44 (1989) 741–
749.
Gradoń L., Podgórski A., Sosnowski T.R., Experimental andtheoretical investigations of transport properties of DPPC
monolayer, Journal of Aerosol Medicine, 9 (1996) 357–367.
Gradoń L., Sosnowski T.R., Formation of particles for dry powder inhalers, Advanced Powder Technology 25 (2014)
43–55.
Gradoń L., Sosnowski TR, Pirożyński M, Han S., European
Patent Application, (2009) EP 2340817A1Stein S.W., Thiel
C.G., The history of therapeutic aerosols: a chronologicalreview, Journal of Aerosol Medicine and Pulmonary Drug
Delivery, 30 (2017) 20–41.
Healy A.M., Amaro M.I., Paluch K.J., Tajber L., Dry powders
for oral inhalation free of lactose carrier particles.
Advanced Drug Delivery Review 75 (2014) 32–52.
Heinemann L., The failure of Exubera: are we beating a deadhorse?, Journal of Diabetes Science and Technology, 2(2008) 518–529.
Heyder J., Svartengren M.U., Basic principles of particle behavior
in the human respiratory tract, in: Bisgaard H., O’CallaghanC., Smaldone G.C. (Eds.), Drug Delivery to the Lung (Lung
Biology in Health and Disease), Marcel Dekker, Inc., New
York-Basel, 2002, pp. 21–45.
Hoppentocht, M., Hagedoorn, P., Frijlink, H.W., de Boer, A.H.,
Technological and practical challenges of dry powder inhalers and formulations, Advanced Drug Delivery Review, 75(2014) 18–31.
Howarth P.H., Why particle size should affect clinical response
to inhaled therapy, Journal of Aerosol Medicine, 14S1
(2001) S27–S34.
Islam N., Gladki E., Dry powder inhalers (DPIs)—a review ofdevice reliability and innovation, International Journal of
Pharmaceutics, 360 (2008) 1–11.
Jabłczyńska K., Janczewska M., Kulikowska A., Sosnowski
T.R., Preparation and characterization of biocompatible
polymer particles as potential nanocarriers for inhalation
therapy, International Journal of Polymer Science, 2015
(2015) 763020 (8 pages), DOI:10.1155/2015/763020
Kaialy W., Nokhodchi A., Particle engineering for improved

136

pulmonary drug delivery through dry powder inhalers, in:Nokhodhi A., Martin G.P. (Eds.), Pulmonary Drug Delivery. Advances and Challenges (Advances in Pharmaceutical
Technology), John Wiley & Sons, Chichester, UK, 2015,
pp. 171–197.
Kleinstreuer C., Zhang Z., Donohue J.F., Targeted drug-aerosoldelivery in the human respiratory system, Annual Reviewsin Biomedical Engineering 10 (2008) 195–220.
Koblinger L., Hofmann W., Monte Carlo modeling of aerosol
deposition in human lungs: Part I: Simulation of particle
transport in a stochastic lung structure, Journal of Aerosol
Science, 21 (1990) 661–674.
Kondej D., Sosnowski T.R., Alteration of biophysical activity of
pulmonary surfactant by aluminosilicate nanoparticles.
Inhalation Toxicology 25 (2013) 77–83.
Kondej D., Sosnowski T.R., Effect of clay nanoparticles onmodel lung surfactant: a potential marker of hazard fromnanoaerosol inhalation. Environmental Science and Pollution Research, 23 (2016) 4660–4669.
Kramek-Romanowska K., Odziomek M., Sosnowski T.R.,
Dynamic tensiometry studies on interactions of novel therapeutic inhalable powders with model pulmonary surfactant
at the air–water interface, Colloids Surfaces A: Physicochemical and Engineering Aspects, 480 (2015) 149–158.
Kramek-Romanowska K., Odziomek M., Sosnowski T.R.,
Gradoń L., Effects of process variables on the properties ofspray-dried mannitol and mannitol/disodium cromoglycate
powders suitable for drug delivery by inhalation, Industrial
and Engineering Chemistry Research, 50 (2011) 13922–
13931.
Kwong W.T.J., Ho S.L., Coates A.L., Comparison of nebulized
particle size distribution with Malvern diffraction analyzer
versus Andersen Cascade Impactor and Marple Personal
Cascade Impactor, Journal of Aerosol Medicine, 13 (2000)
303–314.
Li Y.Z., Sun X., Gong T., Liu J., Zuo J., Zhang Z.R., Inhalable
microparticles as carriers for pulmonary delivery ofthymopentin-­loaded solid lipid nanoparticles, Pharmaceutical Research, 27 (2010) 1977–1986.
Liang Z., Ni R., Zhou J., Mao S., Recent advances in controlled
pulmonary drug delivery, Drug Discovery Today, 20 (2014)
380–389.
Longest P.W., Holbrook L.T., In silico models of aerosol delivery to the respiratory tract - development and applications,
Advanced Drug Delivery Review, 64 (2012) 296–311.
Ma B., Lutchen K.R, CFD Simulation of aerosol deposition inan anatomically based human large–medium airway model.
Annals of Biomedical Engineering, 37 (2009) 271–285.
Mao L., Wilcox D., Kippax P., Laser diffraction particle size
analysis: a powerful tool for rapidly screening nebulizer
formulations, Drug Delivery Technology, 10 (2010) 64–67.
Martinelli F., Balducci A.G., Rossi A., Sonvico F., Colombo P.,
Buttini F., “Pierce and inhale” design in capsule based dry
powder inhalers: Effect of capsule piercing and motion on
aerodynamic performance of drugs, International Journalof Pharmaceutics, 487 (2015), 197–204.
Matida E.A., Finlay W.H., Lange C.F., Grgic B., Improved
numerical simulation of aerosol deposition in an idealizedTomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

mouth–throat. Journal of Aerosol Science, 35 (2004) 1–19.
Mitchell J., Newman S., Chan H.-K., In vitro and in vivo
aspects of cascade impactor tests and inhaler performance:a review, AAPS Pharmaceutical Science and Technology, 8(2007) 237–248.
Moskal A., On Transport and Deposition of Aerosol Particles inthe Human Breathing System—Selected Problems, Publishing House of Warsaw University of Technology, Poland,
2011.
Moskal A., Gradoń L., Temporary and spatial deposition ofaerosol particles in the upper human airways during breathing cycle. Journal of Aerosol Science, 33 (2002) 1525–1539.
MPPD, Multiple-Path Particle Dosimetry Model v.3.04 (2015).
<www.ara.com/products/multiple-path-particle-dosimetry-model-mppd-v-304> accessed 10.05.2017
MSP Corporation, The Next Generation Pharmaceutical Impactor (NGI) User Guide, Shoreview, MN, USA (2008).
Nandiyanto A.B.D., Okuyama K., Progress in developing
spray-drying methods for the production of controlled morphology particles: from the nanometer to submicrometersize ranges, Advanced Powder Technology, 22 (2011) 1–19.
Newman S.P., Chan H.-K., In vitro/in vivo comparisons in pulmonary drug delivery. Journal of Aerosol Medicine andPulmonary Drug Delivery 21 (2008) 77–84.
Newman S., Peart J., Dry powder inhalers, in: Newman S. (Ed.),
Respiratory Drug Delivery. Essential Theory and Practice,
RDD Online/VCU, Richmond, VA, USA, 2009, pp. 257–
307.
Odziomek M., Kalinowska M., Płuzińska, A., Rożeń A., Sosnowski T.R., Bronchial mucus as a complex fluid: molecular interactions and influence of nanostructured particles onrheological and transport properties. Chemical and Process
Engineering 38 (2017) 217–229.
Odziomek M., Sosnowski T.R., Gradoń L., Conception, preparation and properties of functional carrier particles for pulmonary drug delivery, International Journal of Pharmaceutics,
433 (2012) 51–59.
Odziomek M., Sosnowski T.R., Gradoń L., The influence ofFunctional Carrier Particles (FCPs) on the molecular transport rate through the reconstructed bronchial mucus - invitro studies, Transport in Porous Media, 106 (2015) 439–
454.
Parra E., Pérez-Gil J., Composition, structure and mechanicalproperties define performance of pulmonary surfactant
membranes and films, Chemistry and Physics of Lipids, 185(2015) 153–175.
Pilcer G., Wauthoz N., Amighi K., Lactose characteristics andthe generation of the aerosol, Advanced Drug Delivery
Reviews, 64 (2012) 233–256.
Pirożyński M., Sosnowski T.R., Inhalation devices: from basic
science to practical use, innovative vs generic products,
Expert Opinion on Drug Delivery, 13 (2016) 1559–1571.
Ramachandran V., Murnane D., Hammond R.B., Pickering J.,
Roberts K.J., Soufian M., Forbes B., Jaffari S., Martin G.P.,
Collins E., Pencheva K., Formulation pre-screening of
inhalation powders using computational atom–atom systematic search method, Molecular Pharmaceutics, 12 (2015)
18–33.

Sanders M., Pulmonary drug delivery: an historical overview,in: Smyth H.D.C., Hickey A.J. (Eds.), Controlled Pulmonary Drug Delivery (Advances in Delivery Science andTechnology), Springer, NY-Dordrecht-Heildeberg-London,
2011, pp. 51–73.
Schuster B.S., Suk J.S., Woodworth G.F., Hanes J., Nanoparticle
diffusion in respiratory mucus from humans without lungdisease, Biomaterials, 34 (2013) 3439–3446.
Schum G.M., Phalen R.F., Modelling hygroscopic particle
growth in human lung airways, Annals of Occupational
Hygiene, 41 (1997) 60–64.
Smith D.J., Gaffney E.A., Blake J.R., A viscoelastic traction
layer model of mucociliary transport, Bulletin of Mathematical Biology, 69 (2007) 289–327.
Sosnowski T.R., Powder de-aggregation in the cascade impactor, Abstracts of European Aerosol Conference, Thessaloniki, 24–29.08.2008, paper T09A035P.
Sosnowski T.R., Selected engineering and physicochemical
aspects of systemic drug delivery by inhalation, Current
Pharmaceutical Design, 22 (2016) 2453–2462.
Sosnowski T.R., Giżyńska K., Żywczyk Ł., Fluidization andbreak-up of powder particle aggregates during constant andpulsating flow in converging nozzles, Colloids Surfaces A:
Physicochemical and Engineering Aspects, 441 (2014)
905–911.
Sosnowski T.R., Gradoń L., Modification of inhalable powders
by pulmonary surfactant components adsorbed on droplets
during spray-drying process, Colloids Surfaces A: Physicochemical and Engineering Aspects, 365 (2010) 56–61.
Sosnowski T.R., Gradoń L., Iskandar, F., Okuyama K., Interaction of deposited aerosol particles with the alveolar liquid
layer, in: Gradoń L., Marijnissen J. (Eds.), Optimizationof Aerosol Drug Delivery, Kluwer Academic Publishers,
Dordrecht, 2003, pp. 205–216.
Sosnowski T.R., Kramek-Romanowska K., Predicted depositionof e-cigarette aerosol in the human lungs, Journal of Aerosol Medicine and Pulmonary Drug Delivery, 29 (2016)
299–309.
Sosnowski T.R., Kubski P., Wojciechowski K., New experimental model of pulmonary surfactant for biophysical studies,
Colloids and Surfaces A: Physicochemical and Engineering
Aspects, 519 (2017) 27–33.
Sosnowski T.R., Moskal A., Gradoń L., Mechanisms of aerosol
particle deposition in the oro-pharynx under non-steady
airflow, Annals of Occupational Hygiene, 51 (2007) 19–25.
Stein S.W, Thiel C.G., The history of therapeutic aerosols: achronological review, Journal of Aerosol Medicine andPulmonary Drug Delivery, 30 (2017) 20–41.
Tsapis N., Bennett D., Jackson B., Weitz D.A., Edwards D.A.,
Trojan particles: large porous carriers of nanoparticles for
drug delivery, Proceedings of the National Academy of Sciences of the USA 99 (2002) 12001–12005.
Tsuda A., Henry F.S., Butler J.P., Particle transport and deposition: basic physics of particle kinetics, Comprehensive
Physiology, 3 (2013), 1437–1471.
Tu J., Inthavong K., Ahmadi G.S., Computational Fluid andParticle Dynamics in The Human Respiratory System,
Springer, Dordrecht, 2013.

137

Tomasz R. Sosnowski / KONA Powder and Particle Journal No. 35 (2018) 122–138

Usmani O.S., Biddiscombe M.F., Barnes P.J., Regional lungdeposition and bronchodilator response as a function ofbeta2-agonist particle size, American Journal of Respiratory and Critical Care Medicine 172 (2005) 1497–1504.
USP (United States Pharmacopeia). Aerosols, nasal sprays,
metered dose inhalers and dry powder inhalers, US Pharmacopeial Convention, Rockville, 2008.
Vanbever R., Optimization of dry powder aersosols for systemic
drug delivery, in: Gradoń L., Marijnissen J. (Eds.), Optimization of Aerosol Drug Delivery, Kluwer Academic Publishers, Dordrecht, 2003, pp. 91–103.
Vehring R., Expert review: pharmaceutical particle engineering
via spray drying, Pharmaceutical Research, 25 (2008) 999–
1022.
Weber S., Zimmer A., Pardeike J., Solid Lipid Nanoparticles(SLN) and Nanostructured Lipid Carriers (NLC) for pulmonary application: A review of the state of the art, European Journal of Pharmaceutics and Biopharmaceutics, 86(2014) 7–22.
Weers J.G., Miller D.P., Formulation design of dry powders forinhalation, Journal of Pharmaceutical Sciences, 104 (2015)
3259–3288.
Weuthen T., Roeder S., Brand P., Mullinger B., Scheuch G., In
vitro testing of two formoterol dry powder inhalers at different flow rates, Journal of Aerosol Medicine, 15 (2002)
297–303.
Winkler-Heil R., Ferron G., Hofmann W., Calculation of hygroscopic particle deposition in the human lung, Inhalation
Toxicology, 26 (2014) 193–206.

Wüstneck R., Wüstneck N., Moser B., Karageorgieva V., Pison
U., Surface dilatational behavior of pulmonary surfactant
components spread on the surface of a pendant drop. 1.
Dipalmitoyl phosphatidylcholine and surfactant protein C,
Langmuir, 18 (2002) 1119–1124.
Yeh H.C., Schum G.M., Models of human lung airways andtheir application to inhaled particle deposition, Bulletin of
Mathematical Biology 42 (1980) 461–480.
Zanen P., Targetting aerosols to disease area, in: Gradoń L.,
Marijnissen J. (Eds.), Optimization of Aerosol Drug Delivery, Kluwer Academic Publishers, Dordrecht, 2003, pp.
243–276.
Zeng X.M., Martin G.P., Marriott C., Particulate Interactions
in Dry Powder Formulations for Inhalation, CRC Press,
London, 2000.
Zhang Z., Kleinstreuer C., Transient airflow structures and particle transport in a sequentially branching lung airway
model, Physics of Fluids, 14 (2002) 862–880.
Zhang Z., Kleinstreuer C., Donohue J.F., Kim C.S., Comparisonof micro- and nano-size particle depositions in a humanupper airway model. Journal of Aerosol Science, 36 (2005)
211–233.
Zhou Y., Ahuja A., Irvin C.M., Kracko D.A., McDonald J.D.,
Cheng Y.S., Medical nebulizer performance: effects of cascade impactor temperature, Respiratory Care, 50 (2005)
1077–1082.
Ziegler J., Wachtel H., Comparison of cascade impaction andlaser diffraction for particle size distribution measurements, Journal of Aerosol Medicine, 18 (2005) 311–324.

Author’s short biography
Tomasz R. Sosnowski
Tomasz R. Sosnowski received his PhD (1997) and DSc (habilitation - 2006) in chemical engineering from Warsaw University of Technology (WUT), Poland. In 1999–2000
he was a post-doc fellow at Lovelace Respiratory Research Institute in Albuquerque,
USA. Currently he is a full professor at the Faculty of Chemical and Process Engineering WUT. His main scientific interests are: (i) interfacial phenomena in human lungs,
including the role of the pulmonary surfactant, (ii) technical aspects of aerosol systems
used in drug delivery by inhalation. He is a co-author of more than 70 scientific papers,
several books and chapters, 2 granted patents and 6 patent applications.

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KONA Powder and Particle Journal No. 35 (2018) 139–149/Doi:10.14356/kona.2018021

Review Paper

Development Tendency and Prospect ofHigh Performance Coal Utilization Power
Generation System for Low Carbon Society †Kenji Tanno * and Hisao Makino
1

Energy Engineering Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Japan

Abstract
Coal is an important energy resource for meeting future demands for electricity, as coal reserves are much moreabundant than those of other fossil fuels. However, coal utilization technologies exhaust carbon dioxide more thanother fossil fuels, because of the higher carbon content of coal. To control of global warming, development of newtechnologies for the reduction of carbon dioxide emission from a coal-utilized power station are thus required. For
reduction of carbon dioxide emission, it is very important to utilize low carbon content fuel such as subbituminous coal and lignite, as well as carbon neutral biomass, and develop new technologies needed for a highefficiency power generation system. For the further reduction of carbon dioxide, effective removal and storage
technologies are also necessary. In this paper, the utilization technology of low carbonized sub-bituminous coaland carbon neutral biomass in pulverized coal combustion is at first introduced. The development situation of ahigh efficiency coal-fired power generation technique including an integrated coal gasification combined cycle
system (IGCC) and an integrated coal gasification fuel cell combined cycle system (IGFC) are overviewed, andcarbon dioxide removal technologies in a thermal power station are investigated. Finally, the high efficiency
power generation oxy-fuel IGCC system with CO2 removal is presented, and the characteristics of this system areexamined.
Keywords: coal utilization, carbon dioxide, biomass, low rank coal, high efficiency power generation

1. Introduction
Coal is an important energy resource for meeting thefuture demands for electricity. Coal reserves are much
more abundant than those of other fossil fuels. However,
the higher carbon content of coal exhausts carbon dioxidein the coal utilization process more than in other fossil
fuel utilization processes. To prevent global warming, it isrequired to develop new technologies for the reduction ofcarbon dioxide emission from coal-fired power stations.
To reduce carbon dioxide emission, it is essential to develop a high efficiency power generation system, with thetechnology for utilization of low carbonized coal or carbon neutral biomass. Carbon dioxide removal technology
is one option but it involves high power consumption andcost.
In this paper, the utilization technology of low rankcoal, characterized by a low carbon content, and the utili†
1*

Received 14 June 2017; Accepted 28 August 2017
J-STAGE Advance published online 30 September 2017
2-6-1 Nagasaka, Yokosuka, Kanagawa 240-0196, Japan
Corresponding author: Kenji Tanno
E-mail: k-tanno@criepi.denken.or.jp
TEL: +81-46-856-2121

zation technology of biomass based fuels in pulverizedcoal power plants are firstly presented. Furthermore, thedevelopment situation of a high efficiency power generation system including an Integrated Coal Gasification
Combined Cycle and an Integrated Coal Gasification Fuel
Cell Combined Cycle, as well as power generation systems combined with carbon dioxide removal technology
are introduced. Finally, a new high-efficiency power generation system for CO2 removal using an O2-CO2 blown
gasifier is introduced.

2. Overview of reduction technology of CO2
emission
2.1 Reduction of CO2 emission by utilization of
low carbon fuelAs low carbonized coal such as sub-bituminous coal or
lignite is lower in carbon content than bituminous coal,
the utilization of low carbonized coal has the possibilityof reducing CO2 emission. Especially, the mineable reserves of sub-bituminous coal are more than 30 % that ofbituminous coal, so the utilization of sub-bituminous coal

Copyright © 2018 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/).

139

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in a coal fired power plant has progressed in Japan. In a
coal-fired power plant, coal is pulverized to particles of
40 μm median diameter size and then the pulverized coalis fired in a boiler. The properties of sub-bituminous coal
are different from those of bituminous coal. For the reduction of CO2 emission by using sub-bituminous coal, it
is important to retain the same power generation efficiency as produced with bituminous coal.
Fig. 1 indicates the difference in the oxygen concentration distribution in the test furnace (Ikeda, et al., 2002).
Fig. 1(a) shows the oxygen concentration distribution on
bituminous coal combustion and Fig. 1(b) shows that on
sub-bituminous coal combustion. Oxygen consumption in
the furnace is affected by the combustion situation, so
this contour indicates the profile of the combustion flame.
The oxygen consumption rate near the burner exit insub-bituminous coal combustion is lower than that on
bituminous coal combustion, as an evaporation period formoisture is necessary in sub-bituminous coal before combustion. So, the ignition of sub-bituminous coal takes
place later as compared with bituminous coal. Also, after
ignition, sub-bituminous coal combustion flame is diffused rapidly to the outer side of the furnace. This phenomenon is caused by the diffusion of pulverized coalparticles. As sub-bituminous coal contains a high mois-

ture content, the particles of sub-bituminous coal become
porous or burst into fine particles by the rapid evaporationof moisture from the pore. Small coal particles or porouscoal particles possess weak inertia, so these particles canbe easily diffused by the swirl force of combustion air.
As a solution to this problem, it is effective to reduce
the flow rate of primary air and the swirl force of secondary air. The reduction of primary air velocity can movethe ignition point closer to the burner exit and the reduction of swirl force can reduce the diffusion of coal particles to the outer side of the furnace. Fig. 2 indicates theoxygen concentration of the flame on sub-bituminous coal
combustion after this modification. The flame shape inthis condition is similar to the flame shape for bituminous
coal combustion, as shown in Fig. 1(a). The power generation efficiency using sub-bituminous coal in a pulverizedcoal combustion plant can maintain almost the same as
the power generation efficiency using bituminous coal by
optimizing the burner operation condition.
Biomass is defined as carbon neutral since biomass isrenewable. However, as there are many kinds of biomass,
such as woodchips, wood pellets, and sewage sludge, thepulverizing and combustion characteristics of these species are different from each other. For utilization of biomass, the main problem is the high moisture content andthe difficulty in pulverizing. Although many kinds oftechnology for biomass upgrading have been developed,
the drying and carbonizing technologies are the mostimportant. For high performance removal of moisture, themethods using evaporation are effective. However, thesemethods require higher power consumption because ofincrease in coal temperature. In CRIEPI, the extraction
method using DME (di-methyl-ether) has been investigated. Fig. 3 shows the concept of the method (Kanda, etal., 2008). Although DME is in the gas phase in ambientpressure and temperature, it becomes liquid after pressurization in ambient temperature. The liquefied DME can
include moisture. In this system, the liquefied DME isFig. 1

Fig. 2

140

Comparison of oxygen concentration distribution in the
furnace. Reprinted with permission from Ikeda et al.
2002. Copyright: (2002) The Japan Society of Mechanical Engineers.

Oxygen concentration distribution for sub-bituminous
coal under the modified condition. Reprinted with permission from Ikeda et al. 2002. Copyright: (2002) The
Japan Society of Mechanical Engineers.

Kenji Tanno et al. / KONA Powder and Particle Journal No. 35 (2018) 139–149

Fig. 3

Concept of the moisture extraction method using DME.

Fig. 5
Fig. 4

Schematic of a typical carbonizing system.

mixed with the biomass, and DME extracts the moisture.
After separation of the liquefied DME including moistureextracted from the law biomass, DME is converted to gas
phase by decompression. The gaseous DME is then separated with liquid water. The gaseous DME can be converted to liquid phase by pressurization, and the DME isused again by recycling. This method can reduce thepower consumption required for the drying of biomass
and be applied to biomass drying.
For utilization of biomass (especially woody biomass),
mixing with coal, as a blended fuel, in pulverized coal
combustion power plants is a major technique. The pulverizing characteristics of biomass are important topic in
blend combustion. The power consumption of a typicalmill for coal is increased in the case of mixing biomass.
To control the pulverizing characteristics of woody biomass, the carbonization of biomass is an effective technology. A typical carbonizing system is shown in Fig. 4.
The woody biomass is carbonized in high temperature
condition (600 K–1,000 K). The grindability and heatvalue of the carbonized biomass is increased which consequently enables the utilization of the biomass in ahigher blend ratio. Tar produced in a carbonizing process

Improvement of power generation efficiency in Japan.

is combusted and the generated heat is used as a heatsource of carbonization.

2.2 High efficiency power generation system
A high efficiency power generation system can reduce
CO2 emission while producing the required electric
power. In Japan, the ultra-super critical (USC) boiler has
been introduced into operation and the steam condition
has been gradually improved (Fig. 5). For the greater improvement of power generation efficiency, the development of the integrated coal gasification combined cycle(IGCC) and the integrated coal gasification and fuel cellcombined cycle (IGFC) are being promoted.
Fig. 6 indicates the system flow of the IGCC process.
In Japan, the demonstration plant of IGCC has been operated since 2007. This plant has succeeded in a continuous
run of 5,000 hours and is now used commercially. In the
IGCC system, coal is pulverized to particles of about
40 μm median diameter size and the pulverized coal isthen converted to gaseous phase fuel. The coal derived
gas is purified by gas cleaning equipment and fired in agas turbine combustor. Usually, IGCC plants use a wet
gas cleaning system. For more power generation efficiency, the development of hot gas cleaning system and141

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Fig. 6

Fig. 7

System flow of IGCC process.

System flow of IGFC using MCFC.

utilization of a high temperature gas turbine are important. In the future, the power generation efficiency of
IGCC may be improved by the application of a hot gas
cleaning system and high temperature gas turbine system.
The high temperature fuel cell can maintain high power
generation efficiency. IGFC can reduce CO2 emission
more than IGCC. As a high temperature fuel cell, themolten carbonate fuel cell (MCFC) and the solid oxide
fuel cell (SOFC) have been investigated.
Fig. 7 shows the system flow of IGFC. Pulverized coal
is converted to gaseous fuel as in a usual IGCC system.
Part of the gaseous fuel is introduced into a fuel cell andinjected into a gas turbine combustor after generating
electricity in the fuel cell, whereas in usual IGCC all of
the gaseous fuel is introduced into a gas turbine combustor. Consequently, thermal power generation efficiency of
IGFC surpasses that of IGCC. The major issues in the utilization of fuel cell are improvement in the durability of

142

Fig. 8Comparisons of power generation efficiency and CO2
emission rate.

cell performance and the cost.
Fig. 8 shows the power generation efficiency and CO2
emission rate of these high efficiency power generation

Kenji Tanno et al. / KONA Powder and Particle Journal No. 35 (2018) 139–149

Fig. 9System flow of thermal power plant with CO2 removal.

systems. Consistent with the improvement in power generation efficiency, the CO2 emission rate is reduced.

2.3 CO2 removal technology
To reduce CO2 emission to a great extent, the CO2 capture and storage (CCS) system is one of the foremost
techniques. However, emission of CO2 from a thermal
power plant is of a large amount, therefore the CO2 removal method requires a high consumption of power andthus a reduction in power generation efficiency. As a consequence, this method causes an extreme increase inpower generation cost. Fig. 9 shows some examples of apower generation system with CO2 removal (Minchener
et al., 2007). Post combustion and oxy-fuel combustion
processes are for conventional coal-fired boilers, and pre-­combustion process is for IGCC. The post combustion
process captures CO2 in the exhaust gases after the coalhas been fully burned out. The oxy-fuel process consistsof oxygen combustion with recycled exhaust gases, where
the exhaust gasses are mainly composed of CO2 andmoisture. The generated as particles are collected in anelectrostatic precipitator in the post combustion and oxyfuel combustion system. The pre-combustion processcaptures CO2 in a synthesis gas after conversion of CO
into CO2 by using the shift reactor. Generated ash particles are collected by a ceramic filter in the pre combustion
system.
There are some ways of capturing CO2 from flue gas
such as separation with chemical/physical solvents (absorption), adsorption, separation with membranes andcryogenic separation. At any rate, capturing CO2 fromflue gas needs a huge amount of energy and decreases
power generation efficiency. Fig. 10 indicates the comparison of estimation result of power generation efficiency
with and without CO2 removal (Makino and Noda, 2011).

Fig. 10 Power generation efficiency with and without CO2 removal. (Makino and Noda, 2011)

In general, the power generation efficiency of a thermal
power plant with CO2 removal is about 30 % lower ascompared to that of a power generation plant without CO2
removal. In these CO2 removal systems, the CO2 removal
technology in the IGCC system is better than the CO2 removal technology in the pulverized coal combustion
power plant. For greater improvement of power generation
efficiency of IGCC system with CO2 removal, the development of high performance CO2 separation technology
is important.

3. Development of the oxy-fuel IGCC system
3.1 Outline of the system
As mentioned in a previous chapter, the consumptionof a huge amount of energy has been a severe problem ininstalling the CO2 capturing system in thermal power
plants.

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The pre-combustion system (Fig. 9(c)) converts syngas
to a mixed gas of CO2 and H2 using a shift reactor andthen separates CO2 using a capture unit. The remaining
H2 is injected into gas turbine combustors as fuel. However, a shift reactor requires large amount of steam whichis extracted from the steam turbine system; as a result,thermal efficiency becomes lower than in a conventional
IGCC without CO2 capturing.
Recently, a new concept of IGCC, namely the oxy-fuel
IGCC system, which retains high efficiency while capturing CO2, has been proposed. The system applies the concept of the oxy-fuel combustion system (Fig. 9(b)) to
IGCC. Fig. 11 shows the system flow of the oxy-fuel
IGCC system. Pulverized coal is fed into a gasifier withrecirculated exhaust gas (mostly composed of CO2) andadded oxygen, and converted to syngas in a gasifier. Syngas is injected into gas turbine combustors as fuel in thedownstream of dry type gas clean-up unit. The exhaustgas from the gas turbine is supplied to a regenerative heatexchanger and the heat exchanger heats up the gas at the
combustor inlet using the heat of GT exhaust gas. As specific heat of CO2 is 1.6 times larger than that of N2, it ishard to utilize the heat in the gas turbine. Therefore, theregenerative heat exchanger plays an important role in thesystem. In contrast to a pre-combustion system, this system does not require a shift converter and a CO2 capture
unit because of the high CO2 concentration in the flue gas.
Therefore, the system can retain high efficiency (morethan 42 % HHV) while capturing CO2.
The other merit of the system is derived from the recycled CO2 injection into a gasifier. A conventional gasifier
works with a mixed gas of O2 and N2. Although N2 isneutral in a coal gasification reaction, CO2 can work as a
gasifying agent in coal gasification. Therefore, the performance of a coal gasifier is expected to increase under theoxy-fuel IGCC condition.
From 2008, the authors have developed the proposedsystem with the support of New Energy and Industrial
Technology Development Organization (NEDO) in Japan.

Fig. 11 System flow of the oxy-fuel IGCC system.

144

3.2 Development status of O2-CO2 blown coalgasifier
The O2-CO2 blown coal gasifier is a key component of
the oxy-fuel IGCC system; hence it is of importance inevaluating the effect of CO2 concentration on coalgasification reaction. The CO2 effect in a coal gasifier andvalidity of the O2-CO2 blown coal gasifier have been experimentally investigated (Hamada et al., 2016). Fig. 12shows the schematic of coal gasifier used in their work.
The lower chamber is called a “combustor” and the upper
one is called a “reductor”. Two coal burner and two charburners were installed in the combustor, and two coalburners were installed in the reductor. The coal gasifier
was a two-stage entrained flow type. The operating pressure was 2.0 MPa and the coal feeding rate was about
100 kg/h. Char discharged from the gasifier was collectedby cyclone separator installed in the downstream of gasifier and recycled into the combustor as fuel. The coal ash
was melted in the combustor and the melted ash, called“slag”, was dropped into an ash hopper installed under
the gasifier. Coal gasification experiments were performed under the CO2 enriched condition. Fig. 13 shows
the relationship between CO2 concentration and gasifiercarbon conversion efficiency (CCE) (Oki et al., 2014).
Here, CCE is defined as (carbon in product gas)/(carbon incoal and char fed into gasifier). For almost all types ofcoal, CCE increases with CO2 enrichment. The results
show that CO2 enrichment promotes the char gasification
reaction and increases the coal gasifier performance.
Present results were under the condition where CO2 concentration was less than 30 % on account of the restrictionsof the gas supplying system. However, CO2 concentrationin the actual oxy-fuel IGCC condition is expected to be

Fig. 12 Schematic of coal gasifier.

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Table 1 Numerical condition of 100 kg/h scale coal gasifier.
Items

Case 1Case 2

Case 3

Coal feeding rate

kg/h

100

100

100

Oxygen ratio

—

0.52

0.55

0.54

Composition of gasifying agent
O2

vol%

25

25

25

CO2

vol%

0

15

25

N2

vol%

75

60

50

Fig. 13 Relationship between CO2 concentration and coal gasifier performance. (Oki et al., 2014)

much higher. For our next step, it is planned to modify thegas supplying system to increase CO2 concentration to ashigh as in the actual oxy-fuel IGCC condition.

4. Numerical analysis of O2-CO2 blown coalgasifier
In a previous chapter, current experimental results obtained in an O2-CO2 blown condition were introduced. As
mentioned, CO2 concentration was much higher than in
the current experimental condition. Also, the size of thecoal gasifier was much larger. In the early stages of system development, experimental studies using actual size
equipment are quite difficult. Therefore, the authors havebeen developing numerical tools by which to estimate thevalidity of the system and performance of the O2-CO2
blown coal gasifier. The numerical method is based on
CFD code coupled with chemical reactions such as thecoal gasification reaction. The details of the numericalmethod are addressed in the author’s previous paper(Watanabe et al., 2015).
The char particle reaction is the most important pointin the modeling of the coal gasifier. Therefore, an appropriate particle reaction model was employed in the study(Umemoto et al., 2013).
The numerical simulation for the 100 kg/h class coalgasifier that Hamada et al. used was first validated comparing with experimental results. Table 1 shows the calculation condition of the 100 kg/h class coal gasifier. Case
1 is the typical condition for air-blown IGCC system
whereas in cases 2 and 3, 15 % and 25 % N2 have been replaced by CO2, respectively.

Fig. 14 Comparison of gaseous temperature distribution. Reprinted with permission from Tanno et al. 2015.
Copyright: (2015) The Japan Institute of Energy.

Fig. 14 shows the comparisons of gaseous temperature
distribution (Tanno et al., 2015). Axial location is normalized by gasifier diameter. Numerical results are in quite
good agreement with experimental data for all cases. The
burner in the combustor is located around z/D = 0.5 andthe burner in the reductor is located z/D = 3.0. Gaseous
temperature has a peak around the coal burner and rapidly decreases when getting closer to the reductor by reason of the endothermic coal gasification reaction. Gaseous
temperature gradually decreases as a result of the heat release form the wall in the downstream of the reductor
burner. Fig. 15 shows the comparisons of product gas
composition (Tanno et al., 2015). The major product gases
are H2, CO, CO2 and H2O. CO and CO2 concentrations
increase and H2 decreases with increasing injected CO2
concentration. This is due to the coal gasification reaction
and water gas shift reaction. Numerical results also reflect
the change in product gas composition.
From these results, the accuracy of the numerical results was validated. Subsequently, the numerical simulation for an actual size coal gasifier was performed. Fig. 16
shows the schematic of the actual scale coal gasifier. The
gasifier is two-stage entrained flow type. Four coal burners and four char burners are installed in the combustor
and four coal burners are installed in the reductor. The
operating and the coal feeding rate is 70 ton/h. Table 2
shows the numerical conditions. A-25 case shows the typ-145

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ical conditions in an air-blown IGCC system whereas
C25, C35 and C45 are the oxy-fuel IGCC conditions. 25,
35, and 45 denote oxygen concentration.
Fig. 17 shows the comparison of velocity vectors on
horizontal planes. A25, the air-blown condition, shows analmost axisymmetric distribution and the strong swirling
flow is formed by the jet from the four burners. Almost
the same flow behavior is found in C25. The magnitude of
the swirling flow decreases with increasing O2 concentration (C35 and C45). This is due to the fact that the flowrate is reduced to maintain the same oxygen amount withincreasing O2 concentration. Fig. 18 shows the gaseous

temperature distribution around the combustor. For allcases, the high temperature region is located near the coalburners, and gaseous temperature rapidly decreases as thegases pass through the throat section to the reductor. Thisis due to the fact that the exothermic reaction (combustion) dominant in the combustor changes to the endothermic reaction (gasification) in the reductor, namely, achemical quenching. The same tendency is also observedin C25, C35 and C45. It is also seen that gaseous temperature significantly decreases when N2 in the gasifying
agents is replaced by CO2 with the same O2 concentration(A25 to C25).
This is due to the difference in specific heat between
N2 and CO2. On the other hand, gaseous temperature recovers with increasing O2 concentration in the gasifying
agent and almost the same level and distribution of tem-

Table 2 Numerical condition of actual scale coal gasifier.
Items

A25

C25

C35

C45

Coal feeding rate

t/h

70

70

70

70

Oxygen ratio

—

0.45

0.45

0.45

0.45

Composition of gasifying agent
O2

vol%

25

25

35

45

CO2

vol%

0

75

65

55

N2

vol%

75

0

0

0

Fig. 15 Comparison of product gas composition. Reprinted
with permission from Tanno et al. 2015. Copyright:(2015) The Japan Institute of Energy.

Fig. 16 Schematic of the actual scale coal gasifier.

146

Fig. 17 Velocity vector on horizontal plane. Reprinted withpermission from Tanno et al. 2015. Copyright: (2015)
The Japan Institute of Energy.

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perature as with A25 is observed, when the O2 concentration is 35 % (C35). For a much higher O2 concentration
condition (C45), the gaseous temperature increases to that

Fig. 18 Gaseous temperature distributions.

of A25. The temperature trend can be clearly seen in
Fig. 19 which shows the axial distributions of gaseous
temperature. From the results, it is seen that even thoughgaseous temperature decreases as a result of replacing N2
by CO2 on account of the difference in specific heat, it
can be recovered by optimizing the oxygen concentration.
Fig. 20 shows the axial distributions of the concentration of the major product gas. Just by replacing N2 by CO2(A25 to C25) does not increase CO concentration very
much, although the CO2 concentration is very high. Thisis due to decrease in gaseous temperature in C25 sup-Fig. 19 Axial distributions of gaseous temperature. Reprinted
with permission from Tanno et al. 2015. Copyright:(2015) The Japan Institute of Energy.

Fig. 20 Axial distributions of major product gas. Reprinted with permission from Tanno et al. 2015. Copyright:(2015) The Japan Institute of Energy.

147

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Fig. 21 Comparisons of carbon conversion efficiency. Reprinted with permission from Tanno et al. 2015.
Copyright: (2015) The Japan Institute of Energy.

pressing CO production in the coal gasification. When O2
concentration increases and consequently gaseous temperature increases for C35 and C45, CO concentration
significantly increases. From these results, maintaining ahigh temperature in the combustor is found to be important in order to take advantage of the oxy-fuel IGCC condition.
Fig. 21 shows the comparisons of carbon conversion
efficiency (CCE). Here, combustor CCE is the carbon
conversion efficiency of the coal fed into the combustor,
reductor CCE is that fed into the reductor and total CCE
is that introduced into the gasifier. Combustor CCE
reaches almost 100 % in all cases; the difference in total
CCE is thus due to the reductor CCE. Replacing N2 with
CO2 (between A25 and C25) slightly suppresses total
CCE. This is due to the decrease in gaseous temperature
seen in Figs. 18 and 19. However, total CCE for C35 exceeds that for A25 in spite of the same level of gaseous
temperature. This is due to the high CO2 concentration;
the advantages of the oxy-fuel IGCC are therefore numerically indicated.

5. Conclusion
Coal is an important energy resource for meeting thefuture demands for electricity, as coal reserves are much
more abundant than those of other fossil fuels. For futurecoal utilization, it is necessary to reduce CO2 emission. It
is thus very important to utilize low carbonized coal andcarbon neutral biomass and develop new technologies fora high efficiency power generation system. For the further
reduction of CO2 emission, CO2 removal technology isalso effective, but requires high power consumption and148

cost. Recently, a new type of thermal power generation
system which maintains high efficiency while capturing
CO2 has been proposed. The O2-CO2 blown coal gasifier
is a key component of the system, therefore feasibility of
the O2-CO2 blown gasifier and gasification characteristics
were experimentally and numerically investigated in thispaper.
(1) For the utilization of low rank coal and biomass in thepulverized coal combustion power plant, it is important to maintain the combustion profile of the sub-­bituminous coal similar to bituminous coal combustionand develop drying or carbonizing technologies ofbiomass to improve the calorific value and pulverizing
characteristics.
(2) The integrated coal gasification combined cycle system (IGCC) and the integrated coal gasification fuelcell combined cycle system (IGFC) can reduce CO2
emission because of their high efficiency power generation characteristics.
(3) To reduce carbon dioxide emission to an extreme
amount, CO2 removal technology is very effective, but
usual CO2 removal technologies require high power
consumption and cost. As a high performance power
generation system with CO2 removal, the oxy-fuel
IGCC system is promising.
(4) The coal gasifier performance under the oxy-fuel
IGCC condition was numerically investigated and thefeasibility of the gasifier in the system was validated.
Furthermore, the oxy-fuel IGCC condition has thepossibility to increase coal gasifier performance compared with the conventional IGCC.

Acknowledgements
This work was in part supported financially by the New
Energy and Industrial Technology Development Organization (NEDO) program “Innovative Zero-emission Coal
Gasification Power Generation Project”, P08020.

Nomenclature
CCE

Carbon conversion efficiency

D

Diameter of gasifier

Xi

Species mass fractionz

Axial location of gasifier

References
Hamada H., Evaluation of CO2-enriched gasification characteristics using small coal research gasifier, Proceedings ofKenji Tanno et al. / KONA Powder and Particle Journal No. 35 (2018) 139–149

Annual conference of JSME (2016)
Ikeda M., Kozai Y., Makino H., Emission characteristics ofNOx and unburned carbon in fly ash of sub-bituminous
coal combustion, JSME International Journal Series B
Fluids and Thermal Engineering, 45 (2002) 506–511.
Kanda H., Makino H., Miyahara M., Energy-saving drying
technology for porous media using liquefied DME gas,
Adsorption, 14 (2008) 467–473.
Makino H., Noda N., Reduction technology of carbon dioxide
emission from a coal utilized power generation system,
WIT Transactions on Ecology and the Environment, 154(2011) 83–92.
Minchener A.J., McMullan J.T., Sustainable clean coal power
generation within a European context – The view in 2006,
Fuel, 86 (2007) 2124–2133.
Oki Y., Hara S., Umemoto S., Kidoguchi K., Hamada H.,
Kobayashi M., Nakao Y., Development of High-efficiency

Oxy-fuel IGCC System, Energy Procedia, 63 (2014) 471–
475.
Tanno K., Watanabe H., Makino H., Numerical simulation ofcoal gasifier for oxy-fuel IGCC system, Journal of the Japan
Institute of Energy, 94 (2015) 403–412.
Umemoto S., Kajitani S., Hara S., Modeling of coal char gasification in coexistence of CO2 and H2O considering sharingof active sites, Fuel 103 (2013) 14–21.
Watanabe H., Tanno K., Umetsu H., Umemoto S., Modeling andsimulation of coal gasification on an entrained flow coalgasifier with a recycled CO2 injection, Fuel, 142 (2015)
250–259.
Watanabe H., Ahn S., Tanno K., Numerical investigation ofeffects of CO2 recirculation in an oxy-fuel IGCC on gasification characteristics of a two-stage entrained flow coalgasifier, Energy, 118 (2017) 181–189.

Author’s short biography
Kenji Tanno
Dr. Kenji Tanno is a senior research scientist of CRIEPI (Central Research Institute ofElectric Power Industry) in Japan. He received his doctoral degree in 2007 in Mechanical Engineering at Kyoto University. He was employed at CRIEPI in 2007 as a researchscientist in coal combustion group. His research covers numerical simulation of coal
combustion and gasification, flue gas treatment technology and non-contact laser applied
measurement for multiphase combustion.

Hisao Makino
Dr. Hisao Makino is an executive research scientist of CRIEPI (Central Research Institute of Electric Power Industry) in Japan. He graduated from Kyoto University in 1977
and received M.E. degree in Chemical Engineering from Kyoto University in 1979 and a
Ph.D. in Chemical Engineering from Kyoto University in 1995. He was employed at
CRIEPI in 1979 as a Research Associate in combustion research section. His researchinterests are powder technology, coal utilization technology for the energy supply andenvironmental protection. Current main subjects are an advanced combustion technology for pulverized coal, upgrading technology for low rank coal and flue gas treatment
technology.

149

KONA Powder and Particle Journal No. 35 (2018) 150–159/Doi:10.14356/kona.2018010

Special Contribution

Historical Review of Pneumatic Conveying †George E. Klinzing
1

Swanson School of Engineering, University of Pittsburgh, USA

Abstract
This document attempts to cover the development of pneumatic conveying over the past 100 years or so. The
individual researchers who worked in the field are highlighted along with their photograph which is included at
the end of the document. As time progressed in the scientific and engineering developments of these years one seea transition from a purely experimental approach with considerable empiricism to adapt to the development of
numerical procedures in attempt to predict the flow characteristics. The basic physics of the phenomena ofpneumatic still is not completely understood and new and novel experimental techniques are always welcome in
the field.
Keywords: pneumatic conveying, dilute phase, dense phase, measurements, numerical

1. Introduction
Pneumatic conveying appears to have been in existence
for well over 100 years. The literature indicates that grain
was being unloaded from ships from 1856 to 1876 in theports of London, Rotterdam, Hamburg and Leningrad.
Fig. 1 shows this operation of a Russian ship loading ofgrain in 1882. Possibly other applications did exist before
this but this is the only one found to date. The Russian literature most likely exists but is difficult to discover.

Compressors have their early beginning in 1762 withJohn Smeaton followed by a compressor producing about
15 psi. Improvements were made in 1872 with a compound air compressor.
Thus one sees that the vacuum pumps and the air compressors pre-dates the air blowers so pneumatic conveying
could have taken place in very early times. We have norecord or mention of pneumatic conveying previous to theRussian grain unloading citation.

2. Air movers
It is said that pneumatic conveying took off with the invention of the Roots Blower by the Roots brothers, Philander and Francis, in Indiana in 1859, Roll (1931). At thattime the blowers were used in supercharging the internal
combustion engine and first being employed in blast furnaces to help with the melting of iron. Undoubtedly compressors did exist before this so that high pressure air
could be obtained to utilize in the pneumatic conveying
operations. Vacuum conveying was also possible about
the same time frame.
The vacuum pump is attributed to the Romans and laterin the 13th century the Arabs were using suction pumps.
The pumps surfaced in Europe in the 15th century. The firstvacuum pump is attributed to Otto von Guericke in 1654.
†
1

Received 23 February 2017; Accepted 13 June 2017
J-STAGE Advance published online 30 July 2017
Benedum Hall 700 O’Hara Street | Pittsburgh, PA 15261, USA
E-mail : Klinzing@pitt.edu
TEL : +1-412-624-4604 FAX: +1-412-624-4618

150

Fig. 1

Grain Unloading in 1882.

Copyright © 2018 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/).

George E. Klinzing / KONA Powder and Particle Journal No. 35 (2018) 150–159

3. Earlier pneumatic conveying studies
The earliest technical exploration into pneumatic conveying occurred in Germany by Gasterstadt (1924) at theTechnische Hochschule Dresden. The work is reported in
the German Engineering Journal, VDI. The work reported a linear behavior of the pressure drop in a straightsection of pipe with the solids flow rate. The flow was dilute in nature. This concept was used by Cabrejos andKlinzing (1992) to develop a flow meter for measuring thesolids flow rates with a system of transducers and valve to
explore the full range of experimental conditions. Using
the data from a large conveying system the linearity ofthe system pressure drop with the solids flow rate (Fig. 2)
was constructed by Baker (1997).
Following this work the field seemed to be quiet withpublications until after the Second World War when activity at Karlsruhe University began. The Karlsruhe groupflourished under Rumpf, (Students-Leschonski, Molerus,
Schwedes, Sommer, Werther), working in Process Technology. Teamed with Barth, (Students-Reh, Muschelknautz,
Leineweber, Moller, Bohnet, Weber, Rizk), who worked
in Conveying Flow Technology, to address all aspects ofsolids processing. Barth developed a solids friction factor
term, λz which has been used extensively in the literature.
Solids Friction = λz (velocity of the particle)2/2D(1)

Rizk (1973) through his dissertation work with Barthdeveloped the first equation for the saltation velocity ofpolymer particles and explore the material of constructionof the pipe to ascertain the frictional terms developed by
the interaction of the particles with the wall. About thesame time Zenz and Othmer published a book of Fluidization and Fluid-Particle Systems (1960). This work
contained the first known experiments which Zenz performed in pneumatic conveying which according to legend were performed in his garage with a vacuum cleaner

Fig. 2

System Pressure Drop as a function of the solids flow
rate. (With permission of the author.)

Fig. 3Zenz diagram from pressure loss versus the conveying
velocity at various flow rates, Rizk (1973) (With Permission of the author).

as an air source. Zenz was able to develop a phase diagram which is used extensively in the analysis of pneumatic conveying. See Fig. 3. In Japan pneumaticconveying blossomed under the direction of Morikawa
who mentored such noted researchers as Tsuji and Tomita.
Tomita began his contributions to pneumatic in 1971 andhad a long and successful career at Kyushu Institute ofTechnology. His work was mostly experimental but he diddelve into numerical simulation later in his career. He also
addressed the issue of introducing swirl into the initialpart of the pipe in order to enhance the transfer of particulate solids.

4. Germany
As noted above, before the 1950’s Gasterstadt (1924)
did some very basic studies in pneumatic conveying. His
results of the pressure drop linearity with flow rate fordilute solid flow was the first flow meter of its kind. In
addition he performed pneumatic conveying studies on a
100 m long horizontal pipe.
As noted above, in Germany the solids processing
concept and its study began in earnest with Rumpf ofKarlsruhe University along with other senior colleagues
especially Barth who concentrated his studies in pneumatic conveying providing a rich source of students insolid processing. Almost all of the researchers in Germany in this solids processing through 1960’s to 1990’s
came out of Karlsruhe. Many of the existing researchers
can also trace their academic lineage back to Karlsruhe.
Professor Barth’s untimely death did not stop the research machine from going. Some of the notables fromKarlsruhe who populated Europe’s elite of solids processing were Leschonski, de Silva, Schoenert, Loeffler,
Molerus, and Schwedes. The Karlsruhe group spreadthroughout Europe taking professorships or senior re-151

George E. Klinzing / KONA Powder and Particle Journal No. 35 (2018) 150–159

Table 1 Researcher from the Karlsruhe Group.
Last nameAffiliation

Leschonski

Clausthal Technical University

de Silva

Tel-Tek in Porsgrunn, Norway

Molerus

University of Erlangen

Rizk

BASF

Sommer

BASF—Technical University of Munich

Muschelknautz Bayer—University of Stuttgart
Weber

Karlsruhe University

Bohnet

BASF—Technical University of Braunschweig

search positions in industry. Many started in industry andthen moved on to universities.
Krambrock (1979–2004) is another German pneumaticconveying practitioner who has been prolific in the development of patents in pneumatic conveying and solids processing. He worked initially with Bayer collaborated with
Muschelknautz who was also at the same firm at thattime. He then joined Waeschle and from there formed his
own firm eventually cooperating with Zeppelin andWilms. Muschelknautz (1969, 1985) after the Universityof Karlsruhe started his industrial career with Bayer andthen joined the University of Stuttgart.
Sommer (2009, 2011) from the Technical Universityof Munich and his students developed a clever way ofmeasuring the wall stress in dense phase flow as well as
exploring the structure of dense phase flow with two-­
dimensional tomographics. These results showed that thevoidage is not uniform across the pipe cross-section.
Bohnet after working for BASF joined the faculty at
the Technical University of Braunschweig and studied long
distance conveying and cyclone operation in solids processing. He and his colleagues, Gottschalk and Morweiser(1997) produced a work on modern design of cyclones.
Molerus (1993) of the Technical University of Erlangen
who also was Karlsruhe and Rumpf educated concentrated mostly on developing theories for solids processing
operations including pneumatic conveying.

5. Japan
In Japan Iinoya at Nagoya and Kyoto Universities assembled a team of students to begin to address the challenging area of solids processing from all levels. His lab
produced many of the researchers in this field throughout
Japan for the next 20 years or more. In fact it was challenging for other Japanese researcher who did not havethe Nagoya or Kyoto stamp to advance. In pneumatic conveying Morikawa of Osaka University began to research

152

pneumatic conveying and added a well-known student to
his research team; Tsuji. Morikawa (1982) and Tsuji did
many projects together mostly experimental before
branching out to numerical simulations.
Tsuji followed Morikawa as the Principal Professor at
Osaka University and since has retired being followed by
Tanaka, his student. They have produced a large volumeof students who are world renown in the modeling andsimulations area of solid processing and pneumatic conveying. After retirement from Osaka, Tsuji became thetechnical director of the Hosokawa Research Foundation.
He still participates in symposium on numerical simulations although not formally attached in any entity.
In Japan there were a few other hot spots of pneumaticconveying research. Tomita of Kyushu Institute of Technology (1971) contributed extensively to the literature
covering a wide spectrum of solids transport from pneumatic to hydraulic to capsule. As noted above he studied
induced rotational flows to numerical simulations in dense
phase flows. Tashiro was a student of his and he now at
Kurume Technical University. Tashiro has done some fascinating work on the rotational motion of particle in dense
phase flow.
At the large Nihon University Ochi has done pneumaticconveying research mostly in the dilute phase regime although he has also explored some dense phase work
At Kyoto University Masuda (2003) concentrated ontrying to understand the electrostatic phenomena that occurs in pneumatic conveying. He performed some very
basic work and also has explored measurement devices
and flow measurement in pneumatic conveying. These arereally fundamental in all electrostatic interactions.

6. United states
Much of the U.S. pneumatic conveying work did notcome out of one font as was in Germany with Karlsruhe.
With the importance of energy and coal, fluidizations
studies were plentiful and many industrial companies andresearch organization developed extensive expertise inthis field which is ancillary to pneumatic conveying. The
work of Yang of Westinghouse and Knowlton at GRI andlater PSRI are most noteworthy. Novel and creative experiments and devices were developed being placed almost immediately on the industrial scale. Expertisedeveloped in the solids processing and fluidization area at
Exxon, Texaco, Shell and others. Agrawal from Union
Carbide was their resident expert in pneumatic conveying design with a specialty in dilute phase transport.
Dow Chemical developed similar solids processing expertise under the leadership of Jacob and Dhodapkar. They
fostered research in solids processing in the chemical industry making significant contributions to the state-of-George E. Klinzing / KONA Powder and Particle Journal No. 35 (2018) 150–159

the-art. At Dupont Bell spearheaded the pneumaticconveying activities in their solids processing team leadby Reg Davies. Bell explored many relevant industrial
issues including the use of multiple bends in conveying
systems and particle attrition.
The area of consulting engineering cannot be forgotten
when it comes to pneumatic conveying. Solt after many
years with Fuller Company carried out extensive testing
on a wide variety of materials and designs. Presently he isteamed with Hilbert in having webinars through the magazine Bulk Solids Engineering. Solt’s “Point to Ponder”
in the same magazine is classic with series now being soldseparately. Solt did extensive short course offerings with
the Center for Professional Development, AICHE and the
University of Wisconsin. Jenike and Johanson is now alsooffering consulting services in pneumatic conveying. In
Great Britain Bates has been an active contributor to theconsulting field in addition to providing articles on practical guidelines on solids processing.
As mentioned before the field of pneumatic conveying
did not spring from a single source but had a variety ofdifferent researchers at universities approach the topic.
Michaelides (1984) did some interesting work on the solids friction factors. Soo developed unique mathematicalanalyses for pneumatic conveying with a heavy emphasisof electrostatic generation. Sinclair-Curtis (2015) probed
both simulation and modeling proficiencies as well as experimental verification in her work. Sinclair-Curtis contributed heavily to the numerical simulations in solids
processing including pneumatic conveying. Work in thearea of constitutive models for stress/viscosity is noteworthy. She also carried out fundamental studies using Laser
Doppler Velocimetry for both dilute and dense phase conveying. Most recently she is addressing the issue of particle shape which has been a challenge in the field from the
beginning.
Klinzing and his students carried out experimental
work in a wide scope of topics related to pneumatic conveying; electrostatics, drag reduction, meter development,
long distance conveying, dense phase resulting in a number patents and copyrights. In collaboration with Rizk,
Marcus and Leung a comprehensive book on pneumaticconveying was produced and is in its 3rd edition (2010).

7. Great Britain
Early work in Great Britain began with Rose andDuckworth (1969) who did research in pneumatic conveying at Kings College, University of London and City
University London. Later, in the early 1970s, Mason developed a strong pneumatic conveying facility and expertise at Thames Polytechnic in London. He attracted Mills
as a student who later developed into a trusted colleague

in pneumatic conveying Mills and Mason (1985). Mills
has published widely and lectures often. Mills has had aclose collaboration with Agarwal at IIT—Delhi in India
in the transport of fly ash (1999, 2000). Reed also waspart of the Thames group and took a real leadership role
in research and administration later being part of Greenwich University. Mills initiate work with Mason on benderosion started a long and productive career in pneumaticconveying provide a compendium of design procedures in
the field developed from his many studies (1985). He
focused on different feeders exploring the blow tank operation in considerable detail. He began his work at
Thames Polytechnic and then at Glasgow Calendonian
University and then private consultancy. Mills has work
extensive with Agarwal of the Indian Institute of Technology in New Delhi on the transport of flyash. Extensive
studies were performed under this partnership.
Bradley at the University of Greenwich has developeda large consultancy that goes under the name of theWolfson Center (2008). While in Scotland, Mason with
Jones and Mills attracted two researchers who developed
some interesting basic concepts in measurements inpneumatic conveying: McGlinchey (1999), Pugh andMarjaovic. They continued to develop novel flow measurements devices and research in pneumatic conveying.
During a sabbatical stay at Glasgow Calendonian University Levy collaborated strongly with David Mason andMarjanovic to produce three notable works in pneumaticconveying; Mason, Marjanovic (1998), Mason andMarjanovic (1998) and Mason and Levy (2001). In addition his work on a nozzles with Jones is also noteworthy;
Levy, Jones and Das (1996).
At Cambridge University in Great Britain Nedderman
supervised Konrad; Konrad, Harrison, Nedderson, andDavidson (1980), in theoretical and experimental analysis
of dense phase conveying using the basic principles ofsoil mechanics. Their work is classic and the real beginning to the basic understanding of dense phase flow.
Konrad had a brief stint at Virginia Tech to teach and thenmoved to Exxon changing fields somewhat. Lyndon Bates
is a well-known consultant from Great Britain but his expertise is used widely around the world. He published review articles and guidelines often in the field of solids
processing.

8. South Africa
South Africa came into the pneumatic conveying realm
with a great force in moving large quantities of solids
through large pipelines over long distances. Marcus began
this effort through his dissertation work and continued onwith a faculty position in Mechanical Engineering at Witwatersrand University. The mining industry and the coal

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conversion activities of Sasol supplied a rich variety ofchallenging problems in pneumatic conveying. Marcus
supervised about a dozen students who went on to continue in the field making contributions to industry and academia. The most successful ones were Meijer with
Bateman (ELB, CEO) and Sheer (1995) who now is on thefaculty at Witwatersrand (Wits) after working for a gold
mining company. Unusual applications of pneumatic conveying were seen in carrying ice into gold and diamondmines for cooling. Long distance conveying processes
were explored by Marcus and his students having some of
the longest examples of actual commercial systems. Presently there is some work going on at Wits and the University of Johannesburg.

9. Australia and New ZealandAustralia has been a hot bed for solids processing leadby their vast mineral industry. Their ability to design
large scale systems is found by their large scale experimental facilities both at Newcastle and Wollongong.
Roberts started the bulk solids work in Australia before
moving to the University of Newcastle in 1974. Arnold,
Roberts’ first research student, continued the work at
Arnold at University of Wollongong in close communication with Roberts of Newcastle University. Arnold specialized in bin and hopper design as well as mechanicaltransport with belt conveyors. Wypych who studied with
Arnold moved the progress forward in large scale pneumatic conveying. He always obtained data on experimental facilities that were comparable to industry. Wypych
has been able to explore pneumatic conveying with realistic size conveying lines in both distance and pipe diameters. He has modelled dense phase transport with a twolayer flow theory. The minimum transport boundary wasstudied with flyash and cement. He studied dense phasetransport of various materials and probed the frictionalterm in pneumatic conveying as well as scale-up procedures. Wypych is active in his interactions with industry
through consultancies.
Wypych guided a number of very talented students in
his laboratory; Mi and Pan come quickly to mind. Pan has
returned to China and leading a larger effort in China at
this time, (2013, 2014, 2016)
About 15 to 20 years ago Newcastle University wasable to attract Jones to their research group at The University of Newcastle Research Associates (TUNRA).
Jones left the Mason group at Caledonian University in
Glasgow, Scotland. Jones (1987, 1990, 1994), has beensuccessful in leading the pneumatic conveying group at
Newcastle and has grown the group into a well-recognized
team. Jones served as the advisor and mentor to Williams
and Krull both who have become recognized for their in-154

novative studies. The Newcastle team is active in most of
the solids processing conveying conference world-wide.
Jones explored various topics in pneumatic conveying.
He and his colleagues probed the performance of blow
tanks; product classification in relationship to pneumaticconveying; the effect of gas density on pneumatic conveying; bench scale tests for assessment of pneumatic conveying; blending and segregation of coals for pneumaticconveying; suction nozzles; fly ash, sand and cement
properties in conveying; dense phase conveying; Behera,
Das (2000)
In New Zealand Davies and Tallon (2006, 2014, 2015)
collaborative work yielded a number of contributions to
the field in measurements. Many of these resulted in patents for new devices using tracers in the flow and acoustic
pulsations did considerable work on developing flow meters which a variety of sensors mainly based on acoustics.
Davies and Gunabalan (1998) attacked the difficult problem of assessing the effect of back-to-back bends in conveying system. These meters have been proven to work inpneumatic conveying operation and in other solids processing applications. Many of the devices developed
where applied to other solid processing systems.

10. Israel
A little later in the time line researcher in Israel began
to explore the intricacies of pneumatic conveying lead by
Kalman (1998, 1999). There were other researchers in twophase flow system in Israel who approached the topic in afundamental basic analysis such as Hetsroni at the Technion and Taitel at Tel-Aviv University. Kalman spurred
research to attrition, wear and threshold velocities andproduced a number of students who advances these topics. Kalman’s work in pneumatic conveying spans a number of different aspect of the technology. Besides hisleadership in the International Conveying and Handlingof Particulate Solids conferences and procedures he beganwith studies on size reduction and attrition phenomena ispneumatic conveying. He has explored the behavior ofparticles under different shear and impact conditions aswell as multiple impacts. He probed deeper into this phenomena and was able to show the behaviors of stresses inparticles over a wider range of temperatures. He and his
students addressed the pickup and saltation velocities ofparticle in pneumatic conveying systems producing ageneralized approach which is applicable for both pneumatic and hydraulic conveying. Some recent work in particle velocities in conveying both in bends and feeders has
led to some interesting observations.
Kalman also works closely with Levy (2011) expanding
their work to modeling and simulation with wide applications in solids processing; Han, Levy and Kalman (2003).

George E. Klinzing / KONA Powder and Particle Journal No. 35 (2018) 150–159

Kalman has questioned the basic premises on which mostof pneumatic conveying is built and examined previous
data assiduously. Most notable of Kalman’s students havebeen Rabinovich, Goder, Portnikov. Shaul and others.
The research of Levy (2000) concentrated on numericalsimulations of pneumatic conveying and other solids processing operations. The effect of a bend on the particle
cross-section concentration and segregation in pneumaticconveying systems and finite-volume for conservations ofmass and momentum are a few examples.

11. Norway
When de Silva came to Porsgrunn in Norway to headup the solids processing group at Tel-Tek he began to construct a laborator he termed an insulated tent housing
the pneumatic conveying facilities. De Silva organized aseries of conferences on reliability of solids flow terms
REPOWFLO. Some fundamentals studies were carriedout as well as testing of powders and bins and hopper design. He worked closely with Enstad on particle characterization and behaviors. De Silva was able to attract
Datta to his group to concentrate on pneumatic conveying
and then followed by Ratnayake who is active today.

12. Chile
In Chile Francisco Cabrejos has been a force in pneumatic conveying working for Jenike-Johanson and alsoteaching at the Universidad Tecnica Federico Santa Mariain Valparaiso, Chile. His work has been mainly in themining industry often carrying out transport at high altitudes where the mines are located. He has written a bookon pneumatic conveying in Spanish entitled “Transport
Neumatico” by Editorial USM (2013).

13. Interaction of pneumatic conveying withother solids processing operations anddesigns
Pneumatic conveying developed initially quite separately from other operations in solids processing althoughdetermination of the properties of the materials conveyed
were always recognized as being an important parameter.
The size, shape, distribution of both, true densities andbulk densities were essential in the analysis and experimentation. With the classification of Geldart (1973) into
his A, B, C, and D type powders interest began in earnest
to utilize this classification in reference to the ability andmodes of conveying. It was quickly recognized as it wasin the fluidization field that A type powders were one of

the easiest to be conveyed. The C—cohesive powder werea challenge with such materials as coal, flyash and cement
being representative of these powders. The stresses thatseen in dense phase conveying are similar to the analysisof bins and hoppers and Konrad (1980) under the direction of Nedderman recognized this and formulated thefirst attempt to understand dense phase conveying using
first mechanistic principles. The feeder for pneumaticconveying systems vary from the simple to the very complex and their inter-relationship with bins and hoppers isimperative to understand. The same principles used inbins and hoppers and especially with outlet sizing is important to pneumatic conveying. In addition collection of
the product at the end of the conveying lines requires
knowledge of cyclone operation, filters and electrostatic
separators depending on the size and characteristics of thesolids being conveyed.

14. Modeling and simulation
Tsuji and Morikawa were the first to apply numerical
techniques to the simulation of pneumatic conveying(1982). Since this beginning there has been a strong addition of more studies in the numerical simulation area
which continues until today. Each investigator has refined
the models that they employ and relaxed assumptions. In
2006 Tsuji gave a good summary of the status of modeling in pneumatic conveying and other solids processing
operations. Theuerkauf in 2012 also presented a comprehensive survey of simulations and modeling in solids processing. Modelers have attempted to find experimental
data with which to compare their findings with the workof Tsuji and Morikawa using LDV to measure the motionof particles in pneumatic conveying. Other researchers
who explored the modeling and simulation from the sueof discrete element methods to numerical fluid dynamics
modeling have been Yu (2008), Tomita, Sinclair-Curtis(2012, 2013a, 2013b), Sommerfeld, Levy and others.
Tsuji (2006) has given an excellent summary of computational activities related to solids processing including
pneumatic conveying. He noted that these computations
can be separated into four groups; 1. gas-particle multiphase flows, classification according to numerical analysis,
2. collision-dominated flow and Direct Simulation Monte
Carlo methods (DSMC) and 3. the contact-dominatedflow and 4. the Discrete Element Method (DEM).
Theuerkauf in his talk at Conveying, Handling of Particulate Solids-7 conference gave a good summary ofmodeling granular flows using the DEM. He also considered the DEM to be part of the modeling toolkit for design
over the coming 10 years.

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14.1 The need for further work
The reliable design of bulk solids storage systems wasgiven a significant boost when Andrew Jenike and Jerry
Johanson were able to develop a systematic design procedure based on bench scale bulk property testing. From areasonable sized representative bulk sample of the material to be stored, material testing provides key parametersthat can be used directly in an analytical design procedure. At present this is not possible in pneumatic conveying. Although many workers have attempted to classify
bulk materials according to their pneumatic conveying
mode of flow capability, none of the classifications canpredict with certainty particularly around boundaries
between categories of behavior. Neither can these classifications be used to establish the critical relationship between air flow rate, material flow rate and pressure
gradient. This is an area of work that needs further development.
Many of the theoretical approaches that have been developed are empirically based. While this approach often
yields good quality correlations for specific sets of circumstances it does little to further the real understandingof the mechanisms. The significant developments and reduction in cost of high quality instrumentation opens up
many avenues for further investigation. An example ofthis is the miniaturization of technology which will allow
the investigation of a much wider range of parameters inreal time. An example of this is the work of Klinzing and
Clarke (2012) in the development of the smart particle
which will allow the direct measurement of particle acceleration. This will provide useful data to improve modelling and understanding of the mechanisms involved inpneumatic conveying.

15. Technical conferences related to pneumaticconveying
As noted previously, the literature in pneumatic conveying mostly like began in Germany with VDI and followed in the U.S. with the book on Fluidization and
Fluid-Particle Systems by Zenz and Othmer (1960). Regular technical meetings began with Pneumotransport in1972 lasting for about twelve years followed with Pneumatech lead by Stan Mason. Now-a-days the topic isregularly treated in most chemical and mechanical engineering journals along with specialized journals such as
Powder Technology, Granular Matter, Multiphase Flow,
Chemical Engineering Science and the American Instituteof Chemical Engineers. The series of technical meetings
lead by Kalman called Conveying and Handling of Particulate Solids (CHoPS) has provided a wide venue forresearchers throughout the world. These conferences are156

held every three years and CHoPS now beginning its 9th
conference in 2018.

16. Future
Predicting the future is always dangerous because unforeseen development can surface which can upset thewhole apple cart. At the present time there will undoubted
more and more simulations and modeling approaches
which can handle more and more particles that are not
only spherical in nature. We have to address thenon-spherical systems and multi-distributions and cohesive behaviors which occur in nature. In order to obtain
the proper information to input into the models more basic physics must be explored experimentally. The ultimate
goal is to be able to model a new system with new properties and guarantee that the behavior is realistic. When thisoccurs, we will have programs that can operate in a reasonable amount of time to give designs that are true to thenature of the material and the system. In many respects
pneumatic conveying has the same future that all solids
processing systems will have. To set a time frame for thiswill be a wild estimation but in 30 to 40 years we should
be on our way to achieve our objective.

References (Selected)
Agarwal V.K., Bharathi M.D., Mills D., The influence of particle size range on the pneumatic conveying of fly-ash,
Powder Handling & Processing, 11 (1999) 197.
Agarwal V.K., Bharathi M.D., Mills D., The influence of material grade on pneumatic conveying system performance,
Powder Handling & Processing, 12 (2000) 239–246.
Baker J.D., Performance analysis and control of dilute phase
gas-solid systems employing neural networks and optimization techniques, Ph.D Dissertation, University of Pittsburgh, 1997.
Behera S., Das S., Desirable conveying characteristics for pneumatic transportation of flyash, sand, cement and crushedbath, Powder Handling & Processing, 12 (2000) 23–25.
Bohnet M., Gottschalk O., Morweiser M., Modern design ofaerocyclones, Advanced Powder Technology, 8 (1997) 127–
161.
Bunchatheeravate P., Fujii Y., Matsusaka S., Curtis J., Prediction of particle charging in a dilute pneumatic conveying
system, AIChE Journal, 59 (2013) 2308–2316.
Cabrejos F.M., Transporte Neumatico, Editorial USM (2013).
Cabrejos F.M., Klinzing G.E., Solids mass flow rate measurements in pneumatic conveying, ASME Winter Annual
Meeting, 92-WA/FE-3, Anaheim, CA. (1992).
Davies C., Gunabalan G., Effect of back to back bends on pressure loss in dilute phase pneumatic conveying, WCPT 3.
(1998)
Davies C., Tallon S., X-ray measurement of voidage in aGeorge E. Klinzing / KONA Powder and Particle Journal No. 35 (2018) 150–159

flat-bottom 2-D silo with central discharge, AIChE Meeting(ISBN: 978-0-8169-1086-1) (2014).
Davies C., Tallon S., Measurement of Flowrate of Particulate
Solids, AIChE Meeting (ISBN: 978-0-8169-1094-6) (2015).
Deng T., Farnish R.J., Bradley M.S.A., Evaluation of particle
degradation due to high-speed impacts in a pneumatic handling system, Particulate Science and Technology, 26 (2008)
438–450.
Fargette C., Jones M.G., Nussbaum G., Bench scale tests for theassessment of pneumatic conveying behaviour of powders,
Powder Handling & Processing, 9 (1997) 103.
Gasterstadt J., Die experimentalle Untersuchung des pneumatischsen Fordervorganges, VDI, 68 (1924) 617–624.
Geldart D., Types of gas fluidization, Powder Tech, 7 (1973)
285–292.
Guo Y., Curtis, J., Discrete element method simulations forcomplex granular flows, Annual Review of Fluid Mechanics (2015) 21–46.
Guo Y., Wassgren C., Ketterhagen W., Hancock B., James B.,
Curtis J., A numerical study of granular shear flows of rodlike particles using the discrete element method, Journal of
Fluid Mechanics, 713 (2012) 1–26.
Han T., Levy A., Kalman H., DEM simulation for attrition ofsalt during dilute-phase pneumatic conveying, Powder
Tech, 129 (2003) 92–100.
Johnson P.A., Jones M.G., Mills D., Investigation into the influence of gas density on pneumatic conveying performance,
Powder Handling & Processing, 6 (1994) 157.
Jones M.G., Mills D., Product classification for pneumatic conveying, Powder Handling & Processing, 2 (1990) 117.
Kalman H., Attrition Control by Pneumatic Conveying, Powder
Technology, 104 (1999) 214–220.
Kalman H., Goder D., Design criteria for particle attrition,
Advanced Powder Technology, 9 (1998) 153–167.
Kalman H., Levy A., Brosch T., DEM simulation of particle
attrition in dilute phase pneumatic conveying, Granular
Matter, 13 (2011) 175–181.
Klinzing G.E., Clark W.W., Zhang M., Pahk J.B., Exploratory
development of a microprobe for pneumatic conveying
measurements and analysis, ChoPS 7, Friedrichshafen,
Germany (2012).
Klinzing G.E., Rizk F., Marcus R.D., Leung S.L., Pneumaticconveying of solids, 3rd edition, Springer (2010).
Konrad K., Harrison D., Nedderman R.M., Davidson J.F., Proc.
of Pneumotransport 5. Paper D1, BHRA Fluid Engineering,
Cranfield, Bedford, UK (1980) 225.
Krambrock W., Pneumatic conveying system, US Patent (1979)
US4171925A.
Krambrock W., Paul Lubbehusen P., Method and apparatus for
mixing loose material, US Patent (1980) US4194845A.
Krambrock W., Eberhard N., Device for pneumatic charging
container-type balance, US Patent (1981) US4301880A.
Krambrock W., Device for closing a pipe branch, US Patent(1989) US4836250A.
Krambrock W., Rotary slide valve, US Patent (1991)
US5072758A.
Krambrock W., Device for setting a prescribed gas quantity, US
Patent (1995) US5397062A.

Krambrock W., Wilms H., Brar G.S., Loading apparatus forbulk materials, US Patent (1997) US5660215A.
Krambrock W., Elbow/countercurrent classifier, US Patent(1998) US5788083A.
Krambrock W., Wilms H., Method of blowing conveying conduits free of material after conveyance, US Patent (1998)
US5704990A.
Krambrock W., Method for conveying a solid substance, US
Patent (2005) US6971786B2.
Kuang S.B., Chu K.W., Yu A.B., Z. Zou S., Feng Y.Q., Computational investigation of horizontal slug flow in pneumaticconveying, Industrial & Engineering Chemistry Research,
47 (2008) 470–480.
Kuang S.B., LaMarche C.Q., Curtis J., Yu A.B., Discrete particle simulation of jet induced cratering of a granular bed,
Powder Technology, 239 (2013) 319–336.
Lecreps I., Sommer K., Wolz K., Stress states and porosity
within horizontal slug by dense-phase pneumatic conveying, Particulate Science and Tech, 27 (2009) 297–313.
Levy A., Two-fluid approach for plug flow simulations in horizontal pneumatic conveying, Powder Tech., 112 (2000)
263–272.
Levy A., Jones M.G., Das S., An investigation into the performance of a suction nozzle, Powder Handling & Processing,
8 (1996) 337.
Mallick S.S., Wypych P.W., Pan R., Modeling dense-phasepneumatic conveying of powders using suspension density,
Particulate Science and Technology, 31 (2013) 340–347.
Mason D.J., Levy A., A model for non-suspension gas-solids
flow of fine powders in pipes, Int. J. Multiphase Flow, 27(2001) 415–435.
Mason D.J., Marjanovic P., Levy A., A simulation system forpneumatic conveying systems, Powder Technology, 95(1998) 7–14.
Mason D.J., Marjanovic P., Levy A., The influence of bends on
the performance of conveying systems, Advanced Powder
Technology, 9 (1998) 197–206.
Matsusaka S., Masuda H., Electrostatics of particles, Advanced
Powder Technology, 14 (2003) 143–166. DOI: 10.1163/
156855203763593958
McGlinchey D., Jones M.G., Marjanovic P., Blending and segregation of coal for the U.K. industrial market, Bulk Solids
Handling, 19 (1999–2001) 345.
Michaelides E.E., A model for the flow of solid particles ingases, Int. J. of Multiphase Flow, 10 (1984) 61.
Mills D., Mason J.S., Some aspects of bend erosion in pneumatic conveying system, Bulk Solids Handling, 5 (1985)
1085.
Mittal A., Mallick S.S., Wypych P.W., An Investigation into thetransition of flow Mechanism during fluidized dense-phasepneumatic conveying of fine powders, Particulate Scienceand Technology, 34 (2016) 23–32.
Molerus O., Principles of flow in disperse systems, ISBN-13
9780412406300, CRC Monograph (1993).
Muschelknautz E., Werkstoffforschung und Verfahrenstechnik
unter Weltraumbegingungen, Bundesministerium fur Forschung und Technologie, Vorhaben: SN/A-QV-543 (Reibungsverluste FPL 304/a) (1985).

157

George E. Klinzing / KONA Powder and Particle Journal No. 35 (2018) 150–159

Muschelknautz E., Krambrock W., Vereinfachte Berechnung
horizontaler pneumatischer Forderleitungen bei hoher Gutbeladung mit feinkornigen Produkten, Chemie-Ing.-Techn,41 (1969) 1164.
Nied C., Hauth D., Sommer K., Stress states and pressure loss
in pneumatically conveyed spatially confined single plugs,
ICBM, Newcastle, Australia DOI: 10.3850/978-981-072518-1_150. (2011).
Rizk F., Pneumatische Förderung von Kunststoffgranulaten inhorizontalen Rohrleitungen unter Berücksichtigung desGewichtseinflusses in Zusammenhang mit Guteigenschaften und Rohrwerkstoffeigenschaften, insbesondere im
optimalen Förderbereich Ph.D. Dissertation, University ofKarlsruhe, 1973.
Roll C., Indiana One Hundred and fifty years of American
development, Vol. 3, The Lewis Publishing Company, 1931.
Rose H.E., Duckworth R.A., Transport of solid particles in liquids and gases, The Engineer, 227 (1969) 392–396.
Setia G., Mallick S.S., Wypych P.W., On improving solid friction factor modeling for fluidized dense-phase pneumaticconveying systems, Powder Tech., 257 (2014) 88–103.

Sheer T.J., Pneumatic conveying of ice particles through mineshaft pipelines, Powder Tech., 5 (1995) 203.
Theuerkauf J., Application of discrete element method simulations industry, 7th International CHoPS, Friedrichshaven,
Germany (2012).
Tomita Y., Solids velocities and pressure drops in a horizontal
pneumatic conveying system, Proc. 1st Intl. Conference on
Pneumatic Transport of Solids in Pipe, BHRA, B3 (1971)
99–108.
Tsuji Y., Proceedings of the 5th World Congress on Particle Technology, Orlando, FL, USA, World Congress of Particle Technology—AIChE—Plenary Lecture—Paper 109 (2006).
Tsuji Y., Morikawa Y., LDV measurements in an air-solid twophase flow in a horizontal pipe, J. Fluid Mech, 120 (1982)
385–409.
Wilson R.W., Sheer T.J., Erosion prediction in rotary regenerative boiler air preheaters. Proceedings of 2nd S. A Conference on Applied Mechanics, Cape Town, 1998.
Zenz F.A., Othmer D.F., Fluidization and Fluid Particle Systems, Reinhold (1960).

Author’s short biography
George Klinzing
Dr. George Klinzing is a professor of Chemical Engineering and served as the Vice
Provost for Research at the University of Pittsburgh. He has directed 50 MS and 25 PhD
dissertations in chemical engineering over a 53-year period with a focus on solids transport, handling, processing, and mass transfer.
He has been a consultant to DOE, Goodyear, Mountain State Energy, Allen-­ShermanHoff, Kimberly-Clark, Dow Chemical, Certain Teed, U.S. Steel, Falconbridge, and Sarnoff.
His experience includes co-inventing the LICADO coal-cleaning process and two gassolid flow meters; developing four software packages for pneumatic design; solid-liquid
separation processing, particularly coal filtration and dewatering with an emphasis on
solids characterization and analysis; research into fundamentals of coal-liquid and coalgas transport as related to flow behaviors and energy requirements; coal-water slurrystability studies; and mineral filtration and dewatering process research into fundamentals of cake structure.
George Klinzing was the Chair of the Organizing Committee for the World Congressof Powder Technology-2006, has developed several patents, authored more than 254 publications, and has authored/co-authored two books on pneumatic transport.
He received a BS in Chemical Engineering from the University of Pittsburgh and a
M.S. and Ph.D. degree in Chemical Engineering from Carnegie-Mellon University.

158George E. Klinzing / KONA Powder and Particle Journal No. 35 (2018) 150–159

Walter Barth—Courtesy of Lothar
Reh former of ETH Zurich; www.
thhz.chEdgar Muschelknautz—Website of
University of Stuttgart; www.
uni-stuttgart.de/en/Karl Sommer—Website of Technical
University of Munich; www.tum.de/en/homepage

Otto Molerus—Courtesy of the staffof the University of Erlangen

Farid Rizk—Photo by ReinhardWőhlblier from Bulk-online; https://www.bulk-online.com/faq

Yoshinobu Morikawa—Website of
Osaka University; www.osaka-u.ac.jp

Yukata Tsuji—Website of Osaka
University; www.osaka-u.ac.jp

S. L. Soo—Website of the University
of Illinois; http://illinois.edu/

Paul Solt—Courtesy of Paul Solt

Peter Arnold—Website of Universityof Wollongong; www.uow.edu.au

Clive Davies—Website of Massey
University; www.massey.ac.nz

Roy Marcus—Website of the University of Johannesburg; www.uj.ac.za

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Original Research Paper

Analysis of the Periodic Motion in a Powder Rheometerand Development of a New Flowability Testing Method †Ming Li, Mikel Leturia and Khashayar Saleh *1

Chemical Engineering Department, Compiègne University of Technology, Sorbonne Universities, France

Abstract
This study focuses on the periodic motion observed in the FT4 Powder Rheometer and aims to develop a new
testing method to evaluate powder flowability. This new method is based on the autocorrelation analysis of thetorque measurements. The test results of powders belonging to different Geldart’s groups show that the torquemeasurements are periodic and that the cycle time (period) depends on the flowability. When the powder
cohesiveness increases, the oscillations’ amplitude and the cycle time increase. Conversely, a free-flowing powder
exhibits a liquid-like behavior and shows almost no periodic motion.
Keywords: powder rheometer, flowability, periodic motion, autocorrelation

1. Introduction
Powders or bulk solids are widely used in the industries.
A good powder flowability is of crucial importance sincepoor powder flow can lead to many problems during manufacturing such as inaccurate dosing and off-­specification
products (Valverde J.M., 2012). Especially during a number of processes such as filling small bags or tablet press
dies, the powder materials are under very low stress conditions and their flow behavior is more difficult to predict(Zafar et al., 2015).
To replicate and characterize the powder flow at low
stress conditions, a number of characterization techniques
have been developed over the last 50 years (Jenike A.W.,
1980; Prescott J.J. and Barnum R.A., 2000; Schwedes J.,
2003; Zafar et al., 2015).
The shear cell test is most commonly used for the characterization of powder flowability. It gives the relationshipbetween the shear stress (which leads to flow of the material) and the normal stress (Bek et al., 2016). The yield locus in the low stress region and the tensile strength are
obtained indirectly by extrapolating to zero of the measured yield locus. However, the yield locus tends to curve
downwards at low stresses for cohesive powders so thatthe results can be overestimated (Vasilenko et al., 2013).
Other techniques that allow powder flow characteriza†
1*

Received 15 May 2016; Accepted 19 September 2016
J-STAGE Advance published online 18 March 2017
Lab. TIMR-EA 4297, 60200 Compiègne, France
Corresponding author: Khashayar Saleh
E-mail: khashayar.saleh@utc.fr
TEL: +33 (0)3-4423-5274 FAX: +33 (0)3-4423-1980

160

tion under low stress conditions are reported in the literature. The Sevilla Powder Tester (SPT) and the Raining
Bed Method (RBM) are two similar test methods that candirectly measure the tensile yield stress at low stress levels. Both methods use a controlled gas flow to introduce
small stresses in the powder bed. The tensile yield stressis then calculated by measuring the pressure drop acrossthe powder bed at failure (Formisani et al., 2002; Valverde
et al., 2000).
Another recently developed test method, the ball indentation method (BIM), measures the resistance to plastic
deformation of powder materials at very low stress to assess the flowability (Hassanpour and Ghadiri, 2007).
However, this method was originally designed for continuum solids and the extension to the testing of cohesive
powder beds has only recently been analyzed (Pasha etal., 2013).
Zafar et al. (2015) proposed a comparison of these four
techniques (shear cell, SPT, RBM and BIM), and showedthat:– The powder flow characterization under low stressconditions is greatly influenced by the stress history.
Consequently, the initialization procedure has to bewell controlled in order to obtain reproducible data;– Since the distribution of stresses in granular materials
is highly heterogeneous, it is important to ensure thefailure plane occurs at the proper location and in a reproducible way.
Quintanilla et al. (2006) studied the behavior of a seriesof granular materials of different cohesiveness in a halffilled and slowly rotating horizontal drum. The authors
used a CCD camera and digital image processing to de-

Copyright © 2018 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/).

Ming Li et al. / KONA Powder and Particle Journal No. 35 (2018) 160–171

tect and characterize the avalanches. By statistical analysis, they studied the periodicity of the signals as well as
the probability distributions of the avalanche size and the
maximum angle of stability. The results showed that thesystem cohesiveness was correlated to these probability
distributions: the larger the cohesion, the larger the average size and maximum angle of stability of the avalanches.
More in-depth studies and new testing methods stillneed to be developed to better characterize powder flow
properties under low stress conditions. This work aims todevelop a new dynamic testing method to evaluate powder flowability under unconfined flow conditions. Thisnew method is based on the autocorrelation analysis of
the torque measurements obtained with the FT4 Powder
Rheometer.

2. Materials
Six powders belonging to Geldart’s groups A, B and C
were used in this study. The properties of these six powders are summarized in Table 1. The particle size distributions were measured using a laser diffraction size
analyzer (Mastersizer 2000, Malvern Instruments) and

Fig. 1the particle density by a helium pycnometer Accupyc1330 (Micromeritics). In addition, a liquid honey wasused in this study as a reference material to simulate an“ideal” flow behavior. As it will be shown later in this paper, the liquid honey is viscous enough to obtain significant torque measurements. At the same time, these torquemeasurements are close to those corresponding to a “perfectly flowing” granular material. As a consequence, itwill be considered as a “reference material” and will be
used to simulate an “ideal” flow behavior.

3. Periodic motion during dynamic
measurements
3.1 Standard dynamic test on the FT4 powder
rheometer
Tests on the FT4 powder rheometer are based on a sophisticated twisted blade which passes through the powder bed along a predetermined helical path (Fig. 1). Whenthe blade moves clockwise (conditioning cycle), the powder is lifted up and conditioned to obtain a uniform andreproducible state. When the blade moves anticlockwise(test cycle), it creates a compaction zone which is a local-

Test cycle (left) and conditioning cycle (right) with the FT4 Powder Rheometer.

Table 1 Physical properties of the powders.
powderd[3, 2] (μm)

d[4, 3] (μm)

d[10] (μm)

d[50] (μm)

d[90] (μm)

span

ρ (kg/m3)

shape

Geldart’s
classification

CaCO3 (a)3.4 ± 0.5

11.7 ± 1.7

1.2 ± 0.2

8.6 ± 1.4

26.1 ± 3.9

2.9

2750

angularC

CaCO3 (b)4.0 ± 0.3

15.9 ± 1.4

1.5 ± 0.2

12.3 ± 1.1

35.2 ± 2.9

2.8

2750

angularC

CaCO3 (c)8.4 ± 0.2

51.5 ± 1.2

4.9 ± 0.4

35.2 ± 0.3

104.6 ± 2.1

2.8

2750

angularC

ZrO2

23.7 ± 0.5

60.1 ± 0.5

12.8 ± 0.2

55.1 ± 0.4

113.0 ± 1.2

1.7

5790

angularA

SiC

79.1 ± 0.7

66.0 ± 3.6

43.4 ± 0.9

73.7 ± 0.5

122.7 ± 0.4

1.1

3056

angularA

sand

342.2 ± 15.7

287.1 ± 8.1

186.3 ± 6.6

306.3 ± 11.4

517.6 ± 20.6

1.1

2546

angularB

Values after “±” indicate the 95 % confidence intervals;
span = (d90 – d10)/d50

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ized high-stress region in front of the blade and forces thepowder to flow (Leturia M. et al., 2014).
The FT4 standard “dynamic test” measures the evolution of the torque and force for a downward flow pattern
in a conditioned controlled volume of powder. The energy
required to induce this movement is then calculated (byintegration of the force and torque measurements) to evaluate the flow properties of the powder (Conesa C. et al.,2004). This test is divided into two main parts.
The first part, called “stability test”, corresponds toseven identical complete cycles (conditioning + test cycles) at a constant blade tip speed of 100 mm/s. The objective is to detect any possible change in the powder flow
properties after repeated tests (attrition, agglomeration,etc.). The stability test also allows a stable energy level tobe achieved. The basic flow energy (BFE), as defined byFreeman Technology, corresponds to the stabilized flowenergy. It represents the energy required to force a conditioned powder sample to flow during a downwards test:

BFE (mJ)  Flowenergy of test 7(1)

Usually, fine powders have relatively high interparticulate forces compared to gravitational forces. As a consequence, they behave in a cohesive way: Agglomerates areformed and a large amount of air is trapped inside thebulk powder (Freeman R., 2007). In this case, particles
forced to flow at the blade face can be accommodated by
the voids that exist between the agglomerates (high compressibility). The resulting flow or stress transmission
zone is relatively localized. Thus the displaced volume of
powder is small and the measured BFE value is particularly low. Powders made of larger particles often behave
in a non-cohesive manner due to the minimal effect of cohesive forces compared to gravitational forces. Less air istrapped in the bulk powder resulting in a relatively lower
compressibility. The flow zone is transmitted far ahead of
the blade (Freeman R., 2007). In this case, the displaced
volume of powder is large and the measured flow energy
is high.
The second part, called “variable flow rate test”, corresponds to 4 complete cycles at decreasing blade tip speeds(100, 70, 40 and 10 mm/s). The objective is to evaluate thepowder sensitivity to the flow rate. The flow rate index(FRI) corresponds to the ratio of the flow energy at
10 mm/s blade tip speed to the flow energy at 100 mm/s
blade tip speed:
FRI 

Flowenergy of test 11 (10 mm /s )Flowenergy of test 8 (100 mm /s )(2)

Many factors can affect the value of the FRI index, e.g.:
Cohesive powders are more sensitive to the flow rate
and present a high FRI value (Freeman R., 2007);– Angular particles generally have a high FRI value.
Although the combination of the values of the BFE and–

162

Fig. 2

Results of the FT4 standard dynamic test.

Table 2 Results of the FT4 standard dynamic test.
powderBFE (mJ)FRI

CaCO3 (a)

715.4

2.0

CaCO3 (b)

816.6

2.2

CaCO3 (c)1696.21.9

ZrO22426.1

2.0

FRI helps to identify the powder flow properties, the standard dynamic test has many limitations for the classification of powder flowability.
Fig. 2 and Table 2 present the standard dynamic test
results and the corresponding BFE and FRI values of four
powder samples:–	CaCO3 (a) has a slightly smaller BFE value than
CaCO3 (b), which generally means a lower flowability.
On the other hand, CaCO3 (a) has a smaller FRI value
than CaCO3 (b), which is generally associated with abetter flowability;–	ZrO2 has a much higher BFE value than CaCO3 (c)and seems to have a better flowability. But ZrO2 has amuch higher bulk density, making it difficult to knowwhether the higher value of BFE is caused by the better flowability or the higher density. Meanwhile, ZrO2
has a higher FRI value, which in contrast may indicate
a poorer flowability.
In both cases, it is difficult to make a conclusion about
which powder has better flowability. Therefore, the standard dynamic test on the FT4 cannot be used to compare
two different powders and it can be difficult to distinguishbetween very similar materials.

3.2 Observation of a periodic motion
In order to optimize the FT4 standard procedures, thepowder flow behavior during testing was closely observed(Fig. 3) and the resulting raw data were analyzed (normal
force and torque measurements before integration for theMing Li et al. / KONA Powder and Particle Journal No. 35 (2018) 160–171

Fig. 3

Flow behavior of non-cohesive powders (sand, left) andcohesive powders (CaCO3 (a), right).

stayed at the same height, there was no significant normal
force. Under these conditions, the total energy needed tomove the blade through the powder is proportional to thetorque acting on the blade. The torque oscillations were
evaluated through an autocorrelation analysis, which is amathematics tool commonly used in signal processing
and time-series analysis to investigate repeating patterns(Dunn and Patrick F., 2005)
In statistics, the autocorrelation function for a continuous-­time process, Xt, is the correlation of the process with itself at a later time. It represents the similarity between
observations as a function of the time lag (Box G.E.P. etal., 1994):
ACF τ  Fig. 4Torque variation during a standard dynamic test (blade
tip speed = 70 mm/s).

energy calculation). For cohesive powders, the blade
leaves an empty space behind it when passing through thepowder bed. This empty space grows in size as the blade
moves forward and collapses when it reaches a maximum
volume. It then grows in size and collapses again, following a cyclic pattern. It was also observed that this empty
zone had a smaller maximum volume at a lower blade tip
speed. For non-cohesive powders, the blade does not leave
any significant empty space behind it and particles flow
around the blade, almost like a liquid. The cyclic patternis also reflected in the torque measurements where oscillations can be observed (Fig. 4). These oscillations aremuch more significant in a cohesive sample compared toa free-flowing powder.
A “verification test” was performed to reveal the causesof this cyclic pattern. In this test, only the surface of thepowder bed was forced to flow so that the flow behavior
could easily be observed. A 160-ml conditioned sample of
CaCO3 (a) was placed in the 50-mm ID cylinder vessel.
The blade was moved just below the powder surface(70 mm from the bottom) and rotated for 60 seconds at 4
different blade tip speeds (100 mm/s, 70 mm/s, 40 mm/s
and 10 mm/s). At the same time, a video camera recorded
the powder motion around the blade. Since the blade

E [( X t  μ)( X t  τ  μ)]σ2(3)where “E” is the expected value operator. For a stationary
process, the mean μ and the variance σ 2 are time-­
independent and the autocorrelation depends only on thetime lag τ. In other words, the correlation depends only on
the time distance between the two chosen values but noton their position on the time axis. Particularly, the autocorrelation function of a periodic function has the same
period as the original function, which is the key to investigating the repeating patterns. The values of the autocorrelation function (ACF) should be in the range [–1, 1],with 1 indicating a perfect correlation (the signals exactly
overlap when time is shifted by τ) and –1 indicating a perfect anti-­correlation (Priestley M.B., 1982). For a discrete
process with n observations such as the measured torqueseries in this test, an estimate of the autocorrelation may
be obtained as (Chatfield C., 2004):

A
CF k nk1
( X t  μ)( X t k  μ)(n  k )σ 2 t 1

(4)

3.3 Analysis of the periodic motion
Fig. 5 presents the time evolution of the torque measurements and the corresponding autocorrelation functions (ACF) for the “verification test”. On the one hand, aseries of oscillations in the torque measurements are observed and the autocorrelation function brings to light theexistence of a cyclic pattern. At high blade tip speeds, theCaCO3 (a) material has a period corresponding to one rotation of the blade. It should be noted that small peaks(small “events”) can be found at each half-rotation of theblade. As the blade tip speed decreases, it can be observedthat:– These small events become more significant and eventually reach the same value as the main peak. Thismeans that the cycle time is halved;– The maximum autocorrelation level decreases.
The test video was analyzed frame by frame. The im-163

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Fig. 5

Fig. 6Torque measurements and autocorrelation function (ACF) of CaCO3 (a) for the verification test.

Image of the verification test (the blade rotates in anticlockwise direction).

ages clearly show (Fig. 6) that a “block” of powder moves
in front of the blade while a large empty space is left behind it.
During the “verification test”, the “powder block” infront of the blade was observed in the form of several agglomerates (Fig. 7). Whenever some agglomerates fall off
the blade (as the big one in the red frame in Fig. 7-A), a
sudden drop is observed in the torque measurements

164(Fig. 7-B). The torque goes up again when this agglomerate is picked up by the other side of the blade in Fig. 7-C,
D. Since the agglomerates are not exactly of the same
size, the oscillations do not have the same amplitude. In
Fig. 7-E, F, G, H, torque oscillations can also be observed as several small agglomerates fall off the blade
one after another.
Indeed, while the blade pushes the powder to flow, an
unstable “compacted powder zone” builds up in front ofeach side of the blade, forming two “powder blocks” andtwo empty spaces behind them. Since these powder
blocks are unstable, they may eventually collapse to fill
the empty spaces. The fallen agglomerates stay in theempty space for a short time and are picked up by theother side of the blade. The second powder block then increases in volume and becomes less stable. It will finallycollapse like the first powder block and this flow patternis repeated continuously.
The flow speed has an important impact on this periodic motion:– When the blade moves slowly, this process is quitesmooth and the flow pattern has a period corresponding to a 1/2 rotation of the blade;– When the blade moves fast, the cycle time of the flow
pattern becomes one rotation of the blade.

Ming Li et al. / KONA Powder and Particle Journal No. 35 (2018) 160–171

Fig. 7Torque variation and agglomerates behavior (blade tip speed = 70 mm/s).

This behavior could be explained by the fact that thecollapsing process is not immediate as a given powder hasa certain response time to plastic flow deformation. As aconsequence, there may be a critical flow speed above
which the response time is longer than a 1/2 rotation, resulting in a cycle time of one complete rotation of theblade.

4. New powder rheometer testing method
A specific testing procedure was developed on the FT4
Powder Rheometer. First, a 160-ml conditioned sample
was placed in the 50-mm ID cylinder vessel. Then thetwisted blade was set to rotate in the powder bed at aheight of 30 mm from the bottom with a blade tip speedof 100 mm/s for 200 seconds. The blade tip speed wasthen gradually decreased from 100 mm/s to 10 mm/s (by10 mm/s steps for each speed reduction), and the rotation
was repeated for 200 seconds at each step. A conditioning
cycle was performed between each step.
The torque needed to induce flow was measured continuously. To ensure a stable powder flow (steady state),
only the data measured during the last 50 seconds wereanalyzed for each step. The autocorrelation function wasthen used to determine the cycle time and correlationlevel. By this means, the periodic motion was characterized and the powders could then be classified dependingon their behavior.

4.1 Results obtained with the proposed testing
methodThe liquid honey was first used to simulate a regularflow behavior (reference material). Indeed, it was viscousenough to obtain significant torque measurements while
behaving like an ideal material under the testing conditions. Fig. 8 (top) presents the variations of the required
torque to force the liquid honey to flow at different flow
rates. The measured torque is very stable (small oscillations) and the corresponding ACF values (Fig. 8 bottom)
are always close to 0. This means that the torque needed
to force a viscous liquid to flow at a given speed is a constant and no periodic motion can be detected with the
FT4. From this point of view, the liquid honey can be regarded as an “ideal” material (in this flow rate range). On
the other hand, it can also be noted that the average torque(Fig. 8, center) is proportional to the flow speed. This
corresponds to the flow behavior of a Newtonian fluid.
The CaCO3 (a), SiC and sand powders were first char-165

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Fig. 9Relative torque evolution ( (T  T ) / T ) at the blade tip
speed = 100 mm/s.

– For all three specimens, the materials below the blade
seemed to remain static.
Fig. 9 presents the relative torque measurements of the
3 powder specimens (+ honey) as a function of the number of rotations of the blade (at a blade tip speed of
100 mm/s). The relative torque is defined as:
Relativetorque (T  T ) / T

Fig. 8Torque variation as a function of the blade tip speed forthe liquid honey and autocorrelation analysis.

acterized by this method, since each of them belongs to adifferent Geldart’s group. Visual observations during thetests showed that:– For the CaCO3 (a) powder (group C), the rotating
blade left a large empty space behind it by passing
through the powder bed and only a small part of thepowder moved in front of the blade;– In the SiC powder bed (group A), the particles flowed
around the blade, a small empty space was left behindand the flowing zone extended above and in front of
the blade;– For the sand powder (group B), the particles flowed
freely, almost like a liquid. No empty space was left
behind the blade and the flowing zone extended evenfurther above the blade up until the surface of thepowder bed.

166

(5)

where T is the mean torque value calculated within the
50-second measurements.
The results show that the torque measurements can becorrelated to the system cohesiveness:– A cohesive granular material like CaCO3 (a) (group C)
is characterized by large and slow torque oscillations.
Because of the powder cohesiveness, the powder
blocks formed in front of the blade can become large
before they become unstable and collapse. The“build-up/collapse” process is repeated regularly as
the blade rotates in the powder bed. This leads to aperiodic behavior with large events (large oscillations)and a low frequency (slow oscillations). It can be said
that the “response time” is slow when the powder bed
is disturbed by the blade;– For a less cohesive powder like SiC (group A), thepowder blocks become unstable and collapse earlier
compared to a group C powder. This still leads to aperiodic “build-up/collapse” process, but with smallerand faster events;– For a free-flowing powder (sand, group B), the gravitational forces are preponderant compared to cohesion
forces. As a consequence, no stable powder block can
be formed and the “build-up/collapse” process is almost instantaneous. This leads to a continuous flow ofparticles around the blade. The “response time” of afree-flowing powder is fast when the powder bed isdisturbed by the blade. The corresponding torquesignal is quite stable and there is no periodic pattern(relatively close to the honey torque signal).
These results can be related to those obtained by

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Fig. 10 Autocorrelation function at different blade tip speeds. a) blade tip speed = 100 mm/s; b) blade tip
speed = 70 mm/s; c) blade tip speed = 40 mm/s; d) blade tip speed = 10 mm/s.

Fig. 11 Cycle time at different blade tip speeds.

Quintanilla et al. (2006), who used a half-filled and slowly
rotating horizontal drum. Indeed, the collapse of the powder blocks can be assimilated to the avalanches in therotating drum. In both cases, a periodic behavior is observed and the periodicity of the signals can be correlated
to the system cohesiveness. Also, in both studies, it isshown that a higher cohesion leads to larger events (collapses or avalanches).

4.2 Periodic motion analysis and powder
flowability classification
During the tests, the torque was recorded every 0.04

seconds and the 50-second measurements could then betreated as a discrete process with 1250 observations forthe autocorrelation analysis. The autocorrelation functions of the three powders are presented in Fig. 10. Thesegraphs indicate that the flow within the powder bed exhibits the same cyclic pattern as the flow on the surface(Fig. 5). However, the periodic motion on the surface
shows a lower correlation level, which might be caused by
the surface effects.
These ACF curves show that:– At high flow speeds, the CaCO3 (a) powder (group C)
has a cycle time corresponding to one blade rotationand it is close to an “ideal” correlation (the maximum
correlation level is close to 1). When the flow speed
decreases, the cycle time of the CaCO3 specimen ishalved and the correlation level of the cyclic patterndecreases;– The SiC powder (group A) always has a cycle time of
1/2 a rotation of the blade and a relatively lower correlation level.
– The sand powder (group B) has a low correlation level(ACF < 0.2), which means that no significant periodic
motion can be detected in this case.
The cycle times (expressed in the number of rotationsof the blade) of the three samples at different flow speeds
are summarized in Fig. 11. Based on previous results, athreshold value of 0.2 was used to differentiate periodic

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Fig. 12 Transition speeds and powder flow behaviors in the FT4 Powder Rheometer.

Fig. 13 Test results of the new testing method: autocorrelation function at 100 mm/s (left); cycle time at different blade tip speeds (right).

from non-periodic flow patterns. All the processes with acorrelation level lower than 0.2 were ignored and considered as non-periodic flow patterns. For convenience, thecycle time of such processes was then considered as 0.
The results of the autocorrelation analysis indicate that:– The cycle time of a powder material increases as its
cohesiveness increases;– The cycle time doubles at a certain blade tip speed,which can be regarded as a “transition speed”;– Free-flowing powders have a very low correlationlevel (ACF < 0.2) and present almost no periodic flow
pattern. These powders behave almost like the liquid
honey (“ideal” flow)
These results suggest that for any powder material,
there are three flow behaviors:– Flow type 1 (Fig. 12-left): It is observed when the response time of the powder is significantly smaller than
the time required for a 1/2 rotation of the blade. As a

168

–

–

consequence, the particles flow freely and smoothly
around the blade. The corresponding torque signal isquite stable and there are no periodic patterns. For thistype of flow, the correlation level is less than 0.2 (thecycle time is set to 0);
Flow type 2 (Fig. 12-middle): The response time ofthe powder is smaller but close to the time corresponding to a 1/2 rotation of the blade. In this case,the blade leaves a small unstable empty space behind
it when passing through the powder bed. This empty
space expands to a maximum volume and collapses
before being reached by the other side of the blade.
This type of flow corresponds to a cycle time of a 1/2
rotation of the blade and a moderate correlation levelin the autocorrelation analysis (0.2 < ACF < 0.8);
Flow type 3 (Fig. 12-right): The response time of thepowder is larger than the time required for a 1/2 rotation of the blade. Thus the blade leaves a large empty

Ming Li et al. / KONA Powder and Particle Journal No. 35 (2018) 160–171

space behind it when passing through the powder bed.
The other side of the blade reaches the empty space
before it collapses. This type of powder flow corresponds to a cycle time of one complete rotation of theblade and a high correlation level (ACF > 0.8).
These results suggest the existence of two flow transition speeds (Fig. 12): TS[1, 2] is the transition speed fromflow type 1 to flow type 2 and TS[2, 3] is the transition
speed from flow type 2 to flow type 3. For a given powder, the values of TS[1, 2] and TS[2, 3] depend on its response time to plastic flow deformation. Therefore, thevalues of the two transition speeds can be used to identify
the powder flow properties:– Free-flowing powders such as the sand powder flow
almost like a liquid and have a very short response
time. The corresponding TS[1, 2] and TS[2, 3] values
are very high. As a result, these powders exhibit theflow type 1 at any accessible flow speed with the FT4
Powder Rheometer;– Cohesive powders such as the CaCO3 powder on thecontrary have a very long response time, which resultsin low TS[1, 2] and TS[2, 3] values. These powders
then present all three flow types within the flow
speeds accessible with the FT4 Powder Rheometer;– The powders with moderate flowability such as the
SiC powder have an intermediate response time,
which means that they have intermediate TS[1, 2] values (accessible with the FT4 Powder Rheometer) andhigh TS[2, 3] values. As a consequence, these powders can exhibit flow type 1 or 2 depending on theflow speed.
Other tests were also performed to verify these conclusions. As explained in section 3.1, the standard dynamic
test cannot discriminate the flowabilities between CaCO3(a), CaCO3 (b), CaCO3 (c) and ZrO2. The results of the
new testing method clearly show these differences(Fig. 13):
– CaCO3 (a) has a poorer flowability than CaCO3 (b)since it has a lower TS[2,3] and a higher correlationlevel;– CaCO3 (c) and ZrO2 present similar flowabilities as
they have similar cycle time variations. Still, CaCO3(c) flows a little more easily than ZrO2, as it has ahigher TS[1,2] and a lower correlation level.

5. Conclusion
In this study, a new flowability testing method is presented. This method is based on the FT4 standard dynamic test and quantifies the powder periodic motion
under forced flow conditions. The test results prove thatthe dependence of the torque cycle time on the flow rate
can be linked to the powder flow properties: when the

powder cohesiveness increases, the autocorrelation level
and cycle time increase; conversely, a free-flowing powder tends to act like a liquid and shows no periodic motion.
This work shows that this new method has a good capability to identify and classify powder flow properties.
The flowabilities of different powders which cannot be
discriminated with the standard dynamic method of the
FT4 Powder Rheometer are easily identified with this new
methodFurther studies still need to be done to optimize thismethod such as the influence of the blade height (30 mm
in this study), the variation of the periodic motion in a
wider flow speed range, as well as the influence of theblade shape.

Nomenclature
BFE

Basic Flow Energy, [mJ]d[10]10 % of the population lies below the d[10], [m]d[3, 2]

Mean surface-volume diameter (Sauter mean diameter), [m]d[4, 3]

Volume or mass moment mean (De Brouckere mean
diameter), [m]d[50]Mass median diameter, [m]d[90]90 % of the population lies below the d[90], [m]E

Expected value operator

FRI

Flow Rate Index, [–]kObservation number in the discrete time process, [–]nTotal observations of the discrete process

ACF

Autocorrelation function, [–]
ACF

Autocorrelation function of a discrete process, [–]span(d[90]-d[10])/d[50], [–]tTime, [s]T

Torque, [mN m]

T

Average torque, [mN m]

TS[1, 2] Transition speed between flow type 1 and flow type 2,[mm/s]
TS[2, 3] Transition speed between flow type 2 and flow type 3,[mm/s]
X

Signal of a continuous-time process

μ

Mean

ρ

Particle density, [kg/m3]

σStandard deviation

τTime lag, [s]169Ming Li et al. / KONA Powder and Particle Journal No. 35 (2018) 160–171

References
Bek M., Gonzalez-Gutierrez J., Moreno Lopez J.A., Bregant D.
and Emri I., Apparatus for measuring friction inside granular materials—Granular friction analyzer, Powder Technology, 288 (2016) 255–265.
Box G.E.P., Jenkin G.M. and Reinsel G.C., Time Series Analysis: Forecasting and Control, 3rd ed, Upper Saddle River,
NJ: Prentice-Hall, 1994.
Chatfield C., The Analysis of Time Series: An Introduction.
sixth ed., CRC Press Company, New York, 2004.
Conesa C., Saleh K., Thomas A., Guigon P. and Guillot N.,
Characterization of Flow Properties of Powder Coatings
Used in the Automotive Industry, KONA Powder and Particle Journal, 22 (2004) 94–106.
Dunn and Patrick F., Measurement and Data Analysis for Engineering and Science, New York: McGraw-Hill, 2005.
Formisani B., Bernardo P., Girimonte R. and Minnicelli A., The
bed support experiment in the analysis of the fluidization
properties of fine solids. Paper presented at the Proceedingsof the conference 4th World Congress on Particle Technology, 2002.
Freeman R., Measuring the flow properties of consolidated,conditioned and aerated powders. A comparative study
using a powder rheometer and a rotational shear cell, Powder Technology, 174 (2007) 25–33.
Hassanpour A. and Ghadiri M., Characterisation of Flowabilityof Loosely Compacted Cohesive Powders by Indentation,
Particle & Particle Systems Characterization, 24 (2007)
117–123.

170

Jenike A.W., Storage and flow of solids. Bull. No. 123, 20thPrinting, 1980.
Leturia M., Benali M., Lagarde S., Ronga I. and Saleh K.,
Characterization of flow properties of cohesive powders: A
comparative study of traditional and new testing methods,
Powder Technology, 253 (2014) 406–423.
Pasha M., Hare C., Hassanpour A. and Ghadiri M., Analysis ofball indentation on cohesive powder beds using distinct element modelling, Powder Technology, 233 (2013) 80–90.
Prescott J.J. and Barnum R.A., On powder flowability, Pharm.
Technol., 24 (2000) 60–84.
Priestley M.B., Spectral analysis and time series, Academic
Press, London; New York, 1982.
Schwedes J., Review on testers for measuring flow properties ofbulk solids, Granul. Matter, 5 (2003) 1–43.
Valverde J.M., Castellanos A., Ramos A., Pérez A.T., Morgan
M.A. and Watson P., An automated apparatus for measuring the tensile strength and compressibility of fine cohesive
powders, Rev. Sci. Instrum., 71 (2000) 2791.
Valverde J.M., Fluidization of Fine Powders: Cohesive Versus
Dynamical Aggregation, Springer, 2012.
Vasilenko A., Koynov S., Glasser B.J. and Muzzio F.J., Role ofconsolidation state in the measurement of bulk density andcohesion, Powder Technology, 71 (2013) 2791.
Zafar U., Hare C., Calvert G., Ghadiri M., Girimonte R.,
Formisani B., Quintanilla M.A.S. and Valverde J.M.,
Comparison of cohesive powder flowability measured by
Schulze Shear Cell, Raining Bed Method, Sevilla Powder
Tester and new Ball Indentation Method, Powder Technology, 286 (2015) 807–816.

Ming Li et al. / KONA Powder and Particle Journal No. 35 (2018) 160–171

Author’s short biography
Ming Li
Ming Li is a Ph.D. student in the Chemical Engineering Department at Compiègne
University of Technology (Sorbonne Universities). His research is focused on the comparison of powder characterization methods and the improvement of testing protocols fora better evaluation of powder flow properties.

Mikel Leturia
Mikel Leturia is a chemical engineer from Compiègne University of Technology(2009). He prepared a Ph.D. thesis in the Chemical Engineering Department at Compiègne University of Technology on the experimental study and modeling of fluidized-bed reactors using cohesive powders (2013). He is currently associate professor in
the same university and his research focuses on powder technology including fluidization, caking and flowability testing methods.

Khashayar Saleh
Khashayar Saleh prepared a Ph.D. thesis on the coating of fine powders in theChemical Engineering Laboratory of Toulouse and obtained his Ph.D. degree in 1998
from the Institute National Poly-technique de Toulouse (France). Professor Khashayar
Saleh is currently the director of the Chemical Engineering Department at Compiègne
University of Technology (Sorbonne Universities). His work is focused on powder technology including size enlargement technology, powder electrification and powder characterisation methods.

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KONA Powder and Particle Journal No. 35 (2018) 172–185/Doi:10.14356/kona.2018003

Original Research Paper

Separation Characteristics of a Deflector Wheel Classifierin Stationary Conditions and at High Loadings:
New Insights by Flow Visualization †Christian Spötter *, Kurt Legenhausen and Alfred P. Weber
1

Institute for Particle Technology, Clausthal University of Technology, Germany

Abstract
Although the deflector wheel classifier is the dominant separation device in the industrial separation of finegrained particle fractions, the classifying mechanisms at high particle loadings are still not described andunderstood sufficiently. The existing models for the calculation of the separation efficiency, which are mostly
based on a single particle’s fate, fail to capture the behavior at high particle loading where particle-particle andparticle-wall collisions are encountered. To overcome this knowledge gap, a high-speed camera was used toanalyze the particle movement in the separation process of a deflector wheel classifier representing real physicalconditions. It is shown that particle-particle and particle-wall collisions must be included in a consistenttheoretical model to represent the effective particle behavior in the separation process. In addition, the influenceof process parameters such as revolution rate and mass loading on the separation efficiency of a deflector wheel
classifier at high loadings is presented here.
Keywords: particle size, deflector wheel classifier, cut point, separation efficiency, separation sharpness

1. Introduction
Air classification is an important step in the productionof many industrial powders. According to Rumpf (Rumpf
H. and Raasch J., 1962; Rumpf H. and Leschonski K.,
1967; Rumpf H. et al., 1974), the basic task of this process
is to classify a mixture of particles of different sizes intoa fine and a coarse particle fraction. Since product characteristics and quality are closely related to the particle
size, products with a narrow particle size distribution aredesired, e.g. for color pigments and abrasive powders(Leschonski K., 1988, 1996). In contrast to classifierswith unrestricted flow such as the spiral air classifier
with a free vortex, the deflector wheel classifier produces a forced vortex due to the rotating paddles; this has
been stated as being less dependent on the mass loading(Leschonski K., 1988, 1996; Rumpf H. and Raasch J.,
1962; Rumpf H. and Leschonski K., 1967; Rumpf H. etal., 1974).
The underlying conception is that the particles experi-†
1*

Received 17 May 2016; Accepted 16 September 2016
J-STAGE Advance published online 25 February 2017
Leibnizstrasse 19, 38678 Clausthal – Zellerfeld, Germany
Corresponding author: Christian Spötter
E-mail : Christian.Spoetter@tu-clausthal.de
TEL : +49-5323-72-2576 FAX: +49-05323-72-2830

172

ence a centrifugal force in the rotational flow field whichis counteracted by the drag of the air flowing inwards between the paddles (cf. Fig. 1) (Rumpf H. and Raasch J.,
1962). Coarse particles are deflected on the outer edge ofthe deflector wheel, while fine particles follow the air flow
through the deflector wheel and are separated later fromthe air flow by an aero-cyclone (Leschonski K., 1988, 1996;
Rumpf H. and Raasch J., 1962; Rumpf H. and Leschonski
K., 1967; Rumpf H. et al., 1974).
In the last century, Rumpf (Rumpf H. and Raasch J.,
1962; Rumpf H. and Leschonski K., 1967; Rumpf H. etal., 1974), Molerus (Molerus O., 1967; Molerus O. and
Hoffmann H., 1968), Sender, Schubert (Schubert H.,
1968) and Husemann (Husemann K., 1998) developed
separation models which describe the particle behavior
and the separation efficiency of a deflector wheel classifier
only on the basis of geometrical and equilibrium considerations. These models, which consider the behavior of asingle particle under the influence of the centrifugal force
and drag, are applicable for calculation of the cut point
using several empirical coefficients, which can only beobtained from experiments. However, they suffer fromseveral drawbacks. First, the dependency of the empiricalparameters on the operating conditions cannot be attributed to a physically sound picture of the separation
process. Second, the particle-paddle and particle-particle
collisions which become significant at higher loadings are

Copyright © 2018 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/).

Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

not taken into account. To overcome this knowledge gap
Galk (Galk J., 1995) and Füchsel (Füchsel S., 2005) examined the influence of the particle loading on the separation characteristics of a deflector wheel classifier.
During these experiments, Galk found a decrease in theratio of the measured to the theoretical cut point at an increasing mass loading accompanied by a decrease of theseparation sharpness. He explained this phenomenon witha retroactive effect of the feed over impulse exchange
onto the fluid flow between the separating paddles. According to Galk, this momentum exchange leads to a deceleration of the drag flow near the feed inlet (Galk J.,
1995).
Bauer (Bauer U., 2002) extended the studies into thesubmicron particle range and observed that in this regime
also, the material mass flow has an influence on the position and slope of the calculated separation curves underotherwise constant experimental conditions. Based on his
experimental results, he hypothesized that different sections of the separation efficiency curve are directly related
to the geometry of different parts of the classifier (Stender
M. et al., 2015). This interesting approach may explain
our observations—which will be treated in future work
but are out of the scope of the present contribution.
While for quite a while, little attention has been paid tothe flow field through the paddles of the deflector wheel,
Legenhausen (Legenhausen K., 1991) analyzed the flow
behavior between the separation paddles using a Laser
Doppler Anemometer (LDA) based on a water model. He
found that the flow between two separation paddles detaches forming a flow vortex. Later, Toneva (Toneva P. etal., 2011) determined the gas flow behavior in a deflector
wheel classifier using Particle Image Velocimetry (PIV)and Computational Fluid Dynamic (CFD) simulations. In
agreement with Legenhausen they found a detachment of
the gas flow from the paddles accompanied by a gas
vortex between the separation paddles. Further, Toneva
demonstrated that the vortex formation leads to a constriction of the particle flow and an increase in the inward
radial gas velocity. Although they neglected the influenceof particle-particle collisions on the separation behavior,
their numerical calculations indicated that the particles
frequently collide with the separation paddles wherecoarse particles leave the separation zone faster than fineparticles. The calculations of Tenova have also shown thatthe coarse particles rebound in both inside and outside direction, which leads to a deterioration of the separation
sharpness. Deduced from the calculated trajectories, a large
proportion of the particle stream is not transported into theinside of the separation wheel. On the contrary, their calculations have shown that a particle accumulation in theflow stream near the outside edge of the separation wheel
is possible. According to Toneva, this accumulation willlead to a deterioration of the separation sharpness due tolong residence times and particle-particle interactions(Spötter C. et al., 2015; Stender M. et al., 2015; Toneva P.
et al., 2011).
In order to transfer the simulation results of Toneva et
al. to studies at high loadings, Stender et al. (Stender M.
et al., 2015) reconstructed a deflector wheel classifier type
Hosokawa Alpine ATP 50. By replacing the two-sided
mounting of the wheel axis by a one-sided high-speed ballbearing, they achieved direct optical access to the front
side of the separator wheel. With this optical access andusing a high-speed camera, initial studies of the gas flow
and particle movement in a real separation process of adeflector wheel classifier were carried out. During theirexperiments, Stender et al. found that at a revolution rateof the deflector wheel of 6000 rpm, a vortex forms near
the leading separation paddles. This vortex moves into aseparation area between the two separation paddles at anincreasing revolution rate and finally reaches the area near
the pursuing paddle at a revolution rate of 15,000 rpm.
With increasing revolution rate, the vortex increasingly
constricts the particle flow stream. Through this study,
Stender et al. were able to confirm the model from Legenhausen for the first time under real process conditions.
They pointed out that particle-particle and particle-wallcollisions affect the separation process (Spötter C. et al.,2015; Stender M. et al., 2015).
To incorporate the real behavior of the gas flow and theparticle motion during the separation process into the existing models, it is necessary to extend the considerationsof Legenhausen and Toneva et al. to higher particle concentrations. Based on these studies, a better interpretationof feedback effects at higher material loadings and of theparticle interactions under real process conditions may beachieved.
While performing separation studies on fly ash, Eswaraiah and Narayanan (Eswarajah C. and Narayanan
S.S., 2005) also noticed that the separation process at highloadings is not sufficiently understood to enable development of reliable physically sound models. For this reason,
this work aims at the presentation of systematic studies ofthe separation characteristics of a deflector wheel classifier by varying the revolution rate between 3000 and
15,000 rpm and the material loadings between 1 to 5 %,which may form the basis for an improved model taking
into account particle-particle and particle-wall collisions.

2. Theoretical basics
2.1 The operation principle of a deflector wheel
classifier
In 1939, Rumpf (Rumpf H. and Raasch J., 1962) described for the first time the extension of a spiral air clas-

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Fig. 1

Schematic diagram of a deflector wheel classifier.

sifier with a forced eddy sink flow, which is today known
as a deflector wheel classifier (cf. Fig. 1). In this type ofcentrifugal counterflow air classifier, the flow field isformed by superposition of a sink flow and a vorticity
flow induced by rotating paddles. The paddles are usually
made out of thin plates, which are arranged vertically orobliquely to the separation wheel tangent (Rumpf H. and
Raasch J.; 1962, Rumpf H. and Leschonski K., 1967;
Rumpf H. et al., 1974).
The feed and the classifying air may be added separately or at the same time into the classifying zone of thedeflector wheel classifier. The particles are then carriedby the air flow towards the deflector wheel where the separation takes place. In the traditional approach, the particle movement between the paddles is determined by the
opposing centrifugal force outwards and drag force inwards. For coarse particles, the centrifugal forces FC
dominate the drag forces so that the particles are rejectedby the rotating wheel. For smaller particles, the centrifugal forces become less important compared to the dragforces Fd, and the particles are carried inwards where they
are sucked into the fine particle outlet. In the following
section, a simple model will be outlined which takes into
account particle properties such as size and density andoperation parameters such as air flow rate, material loading, revolution speed and wheel geometry

2.2 Classic model for cut point
For the following model, spherical particles with agiven density are considered which neither interact nor
influence each other, i.e. single particles in a uniform flow
field, which is not affected by any walls. The flow field
consists of a tangential velocity vφ (circumferential direction) and a radial velocity vr (inward direction). It is assumed that the particles initially have the same tangential
uφ and radial velocity components ur as the classifying air(uφ = vφ & ur = vr).

174

Due to the rotational movement, the particles experience the outwardly directed centrifugal force FC
FC = ρP·VP·(uφ2/r)(1)

where r is the distance to the rotation axis and uφ is theparticle tangential velocity which is assumed to be equal
to vφ (Bauer U., 2002; Legenhausen K., 1991; Spötter C.
et al., 2015).
The drag force depends on the projection area of theparticles, the drag coefficient and the relative velocity
vrel = vr – ur(2)

and can be written in the following way (Richardson J. F.
and Zaki W.N., 1954; Rumpf H. and Raasch J., 1962):
Fd = cw(Re)·Ap∙(ρFl/2)∙|vrel|·vrel(3)

For a certain particle size xt,th, the radial velocity outwards induced by the superposition of centrifugal force
and drag is equal to the radial gas velocity inwards so thatparticles of this size will describe circular trajectories
without being classified to neither the fine nor the coarse
fraction (idealized equilibrium). By assuming particle
motion in the Stokes range, the cut point can be determinedby equation (1) and (3) (Bauer U., 2002; Legenhausen K.,
1991; Spötter C. et al., 2015):

xt,th 18  η  vr 0  r02
ρp  vφ0(4)

where r0 is the radial position where the equilibrium occurs. The calculated cut point xt,th at the radius r0 is inversely proportional to the fluid circumferential velocity
vφ and proportional to the square root of the product vrr0.
For a given deflector wheel geometry, a small cut point
can only be achieved by a high peripheral speed and low
radial velocities of the air flow. However, the separation
grain size is distributed due to stochastic processes withidentical shares into the fine and coarse material fractions(Bauer U., 2002; Legenhausen K., 1991).

Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

2.3 Determination of separation curve andsharpness from experimental data
The separation efficiency T(x) describes the fraction ofa feed material, which is contained in the coarse material
fraction after classification.
q ( x)mC
T  x 
 3,C
100%
mFeed q3, Feed ( x)(5)Here, feed and coarse materials were analyzed by laser
diffraction in discrete size classes as a histogram or cumulative distribution. From the separation efficiency
curve, the cut size is obtained for a separation efficiencyof 50 % (T(xt) = 50 %). The corresponding sharpness of
cut is defined as (Stieß M., 2009):
κ = (x25/x75)·100 %(6)

3. Material and method
3.1 Basic constriction and separation method of adeflector wheel classifier
In order to determine the separation characteristics, themodified deflector wheel classifier type Turboplex ATP
50 from Hosokawa Alpine with an aero cyclone and a bag
filter system was used, as illustrated in Fig. 2.
As a feed material, limestone (CaCO3) is introduced
into the deflector wheel classifier (2) below the rotor via afeed screw attached to the side of the deflector wheel classifier (1). The cumulative particle size distribution of thefeed material has an x10,3 value of 5.86 μm, an x50,3 valueof 59.86 μm and an x90,3 of 179,54 μm. From the bottom of
the housing, the classifying air is supplied into the deflec-

tor wheel classifier tangentially via a classifying air pipe(3) equipped with an air filter. The aspirator produces aconstant air flow of 75 m3/h. The classifying wheel of theTurboplex ATP 50 has a wheel diameter of 50 mm and is
powered by a horizontally positioned shaft. The peripheral speed of the separating wheel was varied using a frequency converter from 7.86 (3000 rpm) to 39.27 m/s(15000 rpm). The rejected coarse material leaves the separator downwards through the central particle lock systemoutlet (4). The fine material leaves the classifier wheel together with the classifying air stream via a fixed pipe
(Spötter C. et al., 2015; Stender M. et al., 2015).
The fine particle fraction is separated from the classifying air by an aero cyclone (6). The fine particles leave thecyclone through a particle lock system into the fines outlet
1 (7). The very fine particles of the fine fraction leave theaero cyclone via the vortex finder and are finally separated in a bag filter system (5). The bag filters are periodically cleaned with compressed air and the particles arecollected in a fines outlet 2 (8). By using the particle locksystems (4) and (7) for the separation of the coarse andfine particle fraction, it was possible to take samples
while the separation wheel was still running. Therefore, it
is possible to take and analyze samples from the starting
point of the separation process and at different intervals
until the separation process reaches stationary conditions(Spötter C. et al., 2015; Stender M. et al., 2015).
In the present study, an experimental protocol was used
to recover the coarse and fine particle fractions. In different runs, the peripheral speed varied between 7.86 and39.27 m/s, and the mass loading ranged from 1 to 5 %.
The sampling procedure consisted of taking subsequent
samples for 5 min each with a total collection time of
60 min using a particle lock system shown in Fig. 2 ((4)
and (7)). With this time-resolved system, it was possible
to determine the time the deflector wheel classifier needs
to reach stationary separation behavior.

3.2 Reconstruction of the deflector wheel classifierto permit optical accessibility

Fig. 2

Schematic of the Hosokawa Alpine ATP 50: (1) Feedscrew, (2) deflector wheel classifier ATP, (3) separating
air pipe, (4) particle lock system 1: coarse material outlet, (5) bag filter system, (6) aero cyclone (7) particle
lock system 2: fine material outlet 1, (8) fine material
outlet 2.

In order to determine the separation characteristics of adeflector wheel classifier, Stender et al. (Stender M., et al.,2015) reconstructed the ATP 50 so that an optical accessonto the deflector wheel was achieved. In order to maintain the classification conditions and the flow of the separation air, Stender et al. did not change the geometry of
the classifying wheel or the neighboring components. In
order to realize this, the motor of the wheel and the outlet
pipe of the fine particle fraction had to be moved to thesame side of the deflector wheel. The outlet pipe of thefine particles was realized using a hollow shaft supported
by two high-speed spindle bearings (A), driven by a flat
belt (B) which is sealed with an oil-soaked gasket. The

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Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

Fig. 3Remodeled Turboplex ATP 50 deflector wheel: a) One-sided bearing for optical access on the opposite
side, b) Installations to permit optical access and purge air for keeping the view of the deflector wheel
free. (A = high-speed spindle bearings, B = flat belt, C = classifier chamber, D = three-phase asynchronous motor, E = top viewing window, F = light source, G = classifying wheel, H = side viewing window,
I = transparent front wall, J = high-speed camera). Reprinted with permission from Ref. (Stender M. etal., 2015). Copyright: (2015) John Wiley & Sons Ltd.

drive of the hollow shaft takes place via a 1:3 gearing
which is powered by a frequency-controlled three-phaseasynchronous motor (D) (see Fig. 3) (Stender M. et al.,2015).
For the optical access to the classifying wheel, speciallydesigned viewing windows were installed on the top (E)and on the side (H). The windows were placed in the sidewall and the ceiling of the housing. Special glass discs ofthe type Mirogard were used for the windows which exhibit anti-reflective properties on both sides thus leading
to a high transparency. A high-speed Keyence VW-600M
camera was placed in front of the window (cf. Fig. 3 (J))
to visualize the motions of the particles during the separation process. In order to prevent light reflections, thecamera was aligned in a 90° angle to the illumination realized with a tripod lamp across the ceiling window(Spötter C. et al., 2015; Stender M. et al., 2015).

Table 1 Mass loading of the experiments at stationary
conditions from 1 to 5 %.
Massloading(ML)

Feed mass flow

Separation
air mass
flow[%][kg/h][g/min][kg/h]

1

0.903

15.05

90.31

2

1.806

30.10

90.31

3

2.709

45.15

90.31

4

3.612

60.20

90.31

5

4.515

75.25

90.31

3.3 Calculation of the material loading
Besides the circumferential speed, also the mass loading (ML) was varied in this study. According to equation(7), the mass loading was calculated by dividing the feedmass flow rate by the separation air mass flow rate (StießM., 2009):

kg
feed mass flow  
h 
ML 
kg
separationair mass flow  
 h 

(7)

The aspirator of the deflector wheel classifier provided
a constant air flow rate of 75 m3/h, corresponding to an
air mass flow rate of 90.13 kg/h. The mass loading wasvaried between 1 and 5 % (Table 1).

3.4 Construction of a particle cannon
In section 5 of this study, a new model approach for the176

Fig. 4Illustration of a particle cannon. (1) impaction plate, (2)metal tube, (3) particle, (4) relaxed ribbon, (5) tensioned ribbon and (6) high-speed camera.

separation of a deflector wheel classifier will be presented.
This model includes as a new parameter the thickness Hof the particle layer which is formed by the impacting andrebounding particles close to the pursuing paddle. In order to determine this parameter, a particle cannon (cf.
Fig. 4) was constructed which is able to image particles
with sizes from 500 to 2000 μm at a velocity up to 80 m/s
where the lower particle size is given by the camera resolution which also depends on the particle material. Since
the limestone particles exhibited a mediocre contrast, theChristian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

dependence of H on impact velocity and mass loading
was investigated for quartz particles. During each experiment, particles were accelerated by means of an elastic
ribbon under tension to different velocities (finger of arubber glove). The particles leave the metal tube and collide with an impaction plate. While at very low loadings,
the coefficient of restitution for single particles can be determined from the initial and rebounding velocity(en = vr ⁄vi), at higher loadings, where significant particle-particle collisions occur, the particle layer thickness H
is measured from images of the bulk behavior obtainedwith the high-speed camera.
Since the boundaries of the particle layer were notsharp but rather diffuse, the thickness was determinedfrom the distribution of the gray scale values evaluatedwith the software ImageJ. As a criterion for the extensionof the layer, the position was recorded where the grayscale value had dropped to 80 % of the maximum value.

4. Experimental results
4.1 Visualization and parametrization of gas andparticle flow in the separation zone
The following results present the gas flow and the particle motion in the area between two separation paddles(separation zone). While for the visualization of the gas
flow very fine limestone particles were used, the motionof coarser particles was visualized with coarser limestone
particles (x50,3 of 59.86 μm). As tracers, fine limestone
particles with an x50.3 of 2.15 μm were used which follow
the gas flow without lag and without classification. To
catch the gas flow behavior, due to some inhomogeneous
distribution of the fine particles, the discernible contrast
points were tracked on subsequent images. Using the software Motion analyzer VW 9000, the motion of these fineparticle accumulations was represented by lines of arrows.
In Fig. 5a), it is shown that at a revolution rate of3000 rpm, the limestone tracer particles pass the wholeseparation area in an arc-like flow. The gas flow starts to
be deflected slightly in the left/middle section of the classifying zone, while near the pursuing paddle, the gas
flows in straight lines. Nevertheless, the gas flow of thevery fine limestone particles passes the entire classification area at a revolution rate of 3000 rpm. At the beginning, the coarse limestone particles (Fig. 6a)) follow thegas flow into the separation zone, but later they continue
their motion towards the pursuing paddle deviating fromthe gas flow due to their higher inertia. Only at this low
revolution rate is the spatial distribution of the particles
relatively homogeneous over the classification area as aconsequence of the less deviated incoming particles anddeflected larger particles (cf. Fig. 6a)).

Fig. 5Visualization of the gas flow (indicated by fine particles) between the separating paddles for increasing
revolution rates from a) to e). View onto the separation
area between two deflection paddles (The separation
wheel moves in anticlockwise direction). Reprinted
with permission from Ref. (Stender M. et al., 2015).
Copyright: (2015) John Wiley & Sons Ltd.

From subsequent images, the particle velocity relative
to the pursuing paddle was measured using the Motion
analyzer VW 9000 software. Interestingly, the particle

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Fig. 7

Fig. 6Visualization of the coarse particle motion between theseparating paddles for increasing revolution rates froma) to e). View onto the separation area between two deflection paddles (The separation wheel moves in anticlockwise direction) [Reprinted with permission from
Ref. (Stender M. et al., 2015). Copyright: (2015) John
Wiley & Sons Ltd.

velocity, initially close to the peripheral speed of the paddle, decreased as the paddle approached. This deceleration effect could be caused either by bouncing particles

178

2D model of the vortex formation and the particle flowin the separation zone of a deflector wheel classifier(paddle depth is D): Leff = effective separation distance(Aeff = Leff·D = effective separation area), Limp = Impaction length (Aimp = Limp·D = impaction area), dv = vortex diameter, vi = relative velocity between particle andpursuing paddle, Rimp = mean impaction radius (related
to the axis of rotation) and Reff = distance between thecenter of the vortex and the center of the deflector
wheel.

colliding with the approaching particles or by peripheral
air flow created by the paddle motion, or a combination of
both. In any case, the deceleration of the approaching particles was observed at all revolution rates, as indicated by
the relative velocities given in Fig. 6.
For higher revolution rates, a vortex is formed (cf.
Fig. 5b–e) which leads to a constriction of the particle
flow, thereby focusing especially the coarse particles to hit
the pursuing paddle on a smaller area (Fig. 6b–e) (Stender
M. et al., 2015).
At an increased revolution rate of 6000 rpm, the tracer
particle flow (Fig. 5b) begins to form a vortex on the left
side of the separation area. This vortex leads to a constriction of the particle flow, thereby focusing it onto asmaller area of the impaction paddle (Fig. 6b) (Stender M.
et al., 2015).
The vortex begins to move away from the leading separation paddle into the middle of the separation area if therevolution rate is increased further to 9000 rpm (Fig. 5c).
With increasing revolution rate (Fig. 5d–e), the vortex
moves closer and closer to the pursuing paddle. Fig. 7 illustrates the model of the vortex formation and the particle motion in the separation zone.
Using the parametrization shown in Fig. 7, the flow
field between the separation paddles was determined as afunction of the revolution rate. The results illustrate themovement of the vortex leading to a constriction of thegas flow which depends on the revolution rate. Regarding
the separation process, the constriction of the flow results
in an increased inwards radial gas velocity. This should
facilitate the entrainment of coarser particles according to
the classic model outlined in chapter 2.2. However, thiseffect was not observed in the separation curves as discussed in chapter 4.3.

Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

Legenhausen (Legenhausen K., 1991).
For the classifier geometry used, it was observed thatthe particles were initially nearly at rest so that the relative velocity was mainly determined by the motion of thepaddles as shown in Fig. 8c). As a consequence of thevortex behavior, the incoming particles are increasingly
focused onto an impaction area Aimp of the pursuing paddle with increasing peripheral speed (cf. Figs. 6 (b–e) &8b). The impaction area is reduced in size and moves, on
average, to the outer edge with increasing peripheral
speed as indicated by the parameter Rimp (cf. Fig. 8c).
After the impaction, the coarse particles are reflected at
a reduced speed relative to the pursuing paddle in random
directions. However, in an absolute coordinate system,
the particles experience much higher velocities after therebound which is important for the centrifugal force. At
low material charge, it is possible that a single particle
bounces from the pursuing paddle almost unimpeded tothe opposite leading paddle. With an increasing material
charge and constriction of the particle flow (cf. Figs. 6
and 8), the rebounding particles collide with subsequent
feed particles in a zone near the pursuing paddle. This interaction decelerates the approaching particles as well as
the rebounding particles. With an increase in particle
concentration, the frequency of particle-particle collisions
also increases which reduces the extension of the collisionzone as indicated by a particle layer in the vicinity of the
pursuing paddle (cf. Fig. 16).

4.2 Transition from instationary to stationary
separation behavior

Fig. 8a) Separation diameter Leff and effective separation radius Reff plotted against the peripheral speed of the deflector wheel; b) Impaction area Aimp and vortex
diameter dv plotted against the peripheral speed of thedeflector wheel; c) Relative velocity between feed particle and pursuing paddle vi and mean impact radius
Rimp plotted against the peripheral speed of the deflector wheel.

While the lateral position of the vortex between thepaddles depends on the peripheral speed, the radial position does not change (cf. Fig. 8a). At the same time, thesize of the vortex dv increases linearly with peripheral
speed up to about 32 m/s, at which point it approaches aconstant value given by the geometric constrictions of thepaddles (cf. Fig. 8b). In all experiments performed here,
the peripheral speed vs of the separating wheel was higher
than the circumferential component of the classifying airvφ (vφ ⁄vs < 1), leading to a clockwise rotating gas vortex
for an anticlockwise rotating wheel in agreement with theresults of the LDA measurements on a water model by

In the following sections, the particle separation behavior will be discussed. Since the separation process between the paddles is very fast (in the ms range), it may be
hypothesized that the overall separation process quickly
reaches a steady state. However, in the following text it
will be shown that, depending on the revolution rate andmaterial loading, it may take several minutes up to over
50 min to reach a stationary separation behavior.
In Fig. 9, the mass fractions of fine and coarse material
are shown as a function of the separation time for different mass loadings. For a revolution rate of 9000 rpm, thestationary separation is achieved faster with increasing
mass loading and at a higher fraction of coarse material.
The same behavior, however, in a mirror symmetricalway, applies for the fine material.
A similar observation was made for the separation
curve as shown in Fig. 10. For a revolution rate of
9000 rpm and a mass loading of 3 %, a stationary separation behavior is not achieved before about 25 min.
In the following text, the time to reach stationary separation curves which are parametrized by the cut point andthe sharpness of cut will be summarized for various revo-179

Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

Fig. 9Coarse and fine mass fraction plotted against the separation time for a material loading of 1 to 5 % and constant revolution rate of 9000 min–1.

Fig. 11 a) Arrival of a stationary cut point & b) Arrival of astationary separation sharpness plotted against therevolution rate for material loadings of 1 to 5 %.

Fig. 10 Separation efficiency plotted against the separation
time for a mass loading of 3 % and revolution rate of
9000 rpm.

lution rates and mass loadings. As shown in Fig. 11a) andb), the cut point and sharpness reaches steady state fasterwith an increasing revolution rate and/or increasing massloading. These results indicate that the particles accumulate in a hold-up ring around the deflector wheel which
was in fact seen with the high-speed camera (Fig. 12).
This hold-up ring consists of deflected and approachingparticles with a concentration which increases significantly near the outer edge of the deflector wheel. Whenassuming that the capacity of this hold-up ring is constant, the dependence of the characteristic time to reachthe steady state on the revolution rate and mass loading
becomes obvious. The time to fill the hold-up ring scales
inversely with the mass flow rate which in turn is determined by the particle velocity (peripheral speed) and theparticle concentration (mass loading).

4.3 Separation behavior in stationary conditions
As shown in the last chapter, the deflector wheel classi-

180

Fig. 12 Image of the hold-up ring around the deflector wheelwith high concentrations close to the outer edge of thewheel surrounded by a more diffuse zone.

fier needs a certain time to reach stationary separation behavior, which may take up to 50 min in the worst case(3000 rpm). In the following text, the separation behavior
at steady state conditions is outlined.
In Fig. 13, the fractions of fine and coarse material are
shown as a function of revolution rate and mass loading.
With increasing revolution rate and mass loading, thefraction of the coarse material increases where, however,
the influence of the revolution rate is dominating the effect of the mass loading. It is clear that the behavior of thefine material fraction is mirror-symmetrical to the coarse
material. While the profile of the mass fraction curve remains unchanged, the absolute values of the mass fractions depend on the powder properties such as initial size
distribution.
The dominating influence of the revolution rate is also

Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

Fig. 13

Coarse and fine mass fraction plotted against the revolution rate in stationary conditions.

reflected in the separation curves shown in Fig. 14a).
While an increase of the revolution rate by a factor of 3
leads to an 83 % decrease of the cut point, an increase of
the mass loading of the factor 3 results only in a reductionof 24 % (starting at 1 % and 3000 rpm). The evolution of
the cut point for all investigated conditions is shown in
Fig. 14b).
In contrast to the cut point, the sharpness of cut isnearly independent of the revolution rate and mass loading. For the limestone particles with a median size of
70 μm, the values varied between 54 and 62 % (cf.
Fig. 14c)). This uniformity of the sharpness was deemed
to be a consequence of the hold-up ring around the deflector wheel which could act similarly to a pre-filter for theincoming particles. In addition, the particle layer formedat the pursuing paddle may also contribute to a constant
sharpness, as further outlined in the discussion. Some experiments with finer limestone particles (median particle
size of 40 μm) indicate a similar independence of the
sharpness of cut on the revolution rate and mass loading,however, reaching higher average values in the range of65 %.

5. Discussion
In industrial applications of deflector wheel classifiers,
the operation time is usually so long that the time needed
to reach the steady state separation may be considered as
negligible. However, the reason for this induction time, i.e.
the hold-up ring which needs to be filled for stationary
operation, can also influence the feed delivery to the classifying wheel with respect to size distribution and initial
particle velocity. While the detailed investigation of thecharacteristics of the hold-up ring is beyond the scope of
this contribution, the motion of the particles in the deflector wheel will be treated in the following text. From thehigh-speed camera images presented in chapter 4.1, it isFig. 14 a) Separation efficiency plotted against the particle
size, b) Cut point & c) Separation sharpness against
the revolution rate in stationary conditions.

concluded that the particles are nearly at rest in an absolute coordinate system, i.e. the deflection paddles approach the particles which start to be drawn into theinter-paddle space by the radial gas flow. Therefore, in theapproach phase, the particles have no peripheral speed sothat they do not experience a centrifugal force. This result
may be different for separators where the particles are accelerated to a certain circumferential speed before entering the classification zone. However, the deflector wheel
classifier used here is representative for a significant classof separators. In the case of particles initially at rest, theclassic model comparing centrifugal force and drag is notapplicable and a physical sound cut size cannot be estimated. In fact, the particles would experience centrifugal
forces only after being hit by the paddle. This phase will
be discussed in more detail below. During the approachphase, however, the particles are accelerated in radial direction due to the constriction of the free flow area as a181

Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

d u r 18  ηeff vr r  u r rdt
ρp  x 2

Fig. 15 Comparison of calculated limestone particle trajectories (black lines) for three revolution rates (6000,
9000, 15000 rpm) during the approach phase using asimple model with the measured cut sizes (43 μm,
27 μm, 15 μm) (white arrows). For each revolution
rate, the calculated trajectories for particles with 10,
20, 40, 80 and 160 μm, respectively, are shown. The
dashed line indicates the motion of the outer edge ofthe paddles, moving in anticlockwise direction.

Fig. 16 Layer thickness of quartz particles plotted against approach velocity.

consequence of the vortex. Based on the geometricparametrization of the vortex (cf. chapter 4.1), the particle
trajectories relative to the paddles were calculated by numerically integrating the equation of motion. To do so, it
was assumed that the paddle approaches the particles at
the given peripheral speed while the particles are accelerated in radial direction by the radial inwards gas flow.
Since the revolution speed of the vortex and the gas flowat the initial zone between the paddles are not known, it
was simply assumed that radial particle motion starts atthe vortex in the presence of an accelerating radial gas
flow. The radial component of the gas flow was approximated by the total gas flow divided by the cross-sectional
area A given by:
1
2

A r D·L r D·[Rv  Leff   r ·2Rv  r ]where RV is the vortex radius (=dV/2).
The radial particle motion is then determined by:

182

(8)

(9)

where Stokes’ regime was assumed and the radial gas velocity was calculated by vr r  V A r.
The calculated trajectories obtained from this simple
model are shown in Fig. 15 for three revolution speeds(6000, 9000, 15000 rpm), corresponding to peripheral
speeds of 15.71, 23.56 and 39.27 m/s, respectively. In
Fig. 15, the calculated particle motion is shown in the coordinate system where the origin is fixed on the outermost
point of the leading paddle for limestone particles withsizes of 10, 20, 40, 80 and 160 μm.
From Fig. 15 it is obvious that the particle trajectory in
the approach phase depends on the particle Stokes’ number (determined by the particle size and density and radial
gas flow velocity) and the peripheral speed of the deflector
wheel. However, the radial dispersion of the particles depends also on the effective viscosity ηeff, i.e. the drag coefficient encountered by the particle due to friction withthe gas and to particle-particle collisions. Beside the gas
properties, this effective viscosity is also a function of
the peripheral speed and mass loading and can be approximated following the model of Richardson and Zaki
(Richardson J. F. and Zaki W.N., 1954). Although the exact value of ηeff is not known for the particle system observed here, the particle trajectories calculated with thepure gas viscosity are in qualitative agreement with theexperimental observations (cf. Fig. 6).
In addition to the calculated particle trajectories, themeasured cut sizes (43 μm, 27 μm, 15 μm) for the three
revolution rates (6000, 9000, 15000 rpm) are also indicated in Fig. 15. The white arrows indicate the locationsof these cut sizes on the pursuing paddle in relation to thecalculated trajectories. In this simple model for a given
operating condition, the white arrow indicates the position where the feed is distributed in equal parts into thefine and coarse fraction. However, this size-dependent
partitioning of the feed between the fine and coarse fraction could not be recorded with the high-speed camera
used due to the limited size resolution which was further
exacerbated by superposition effects at elevated concentrations.
In the rebound phase, the situation near the paddle ismuch more complicated. The particles bouncing from thepaddle collide with the particles just approaching, leading
to a very dense particle layer. Due to the limited resolution for the limestone particles, the thickness of this layer
could not be determined directly at the paddle from thehigh-speed camera images. Therefore, off-line experiments with quartz particles which gave a better contrast
were performed with the particle cannon (cf. chapter 3.4)
to investigate the principal dependencies of the particle
layer thickness on the mass loading and approach velocity.

Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

6. SummaryFig. 17 High-speed camera picture of a particle streak at theouter edge of the deflector wheel.

As indicated in Fig. 16, the layer thickness depends
more strongly on the mass loading than on the approaching velocity which corresponds to the peripheral speed ofthe paddle. In this particle layer, the concentration is extremely high so that the particles are prevented from freemotion due to frequent particle-particle collisions. Therefore, we hypothesize that depending on the radial position, the different parts of the particle layer experience
different centrifugal forces. It is then assumed that at a
certain radial position, the centrifugal forces overcome
the inwards directed drag on the particle layer. As especially well observed at low peripheral speed, the outerpart of the particle layer discharges toward the hold-up
ring while the inner part is drawn into the fine fraction. In
Fig. 15, the measured cut sizes for the different revolution
rates are indicated by white arrows. For each revolution
rate, the arrow would indicate the separation of the feedmaterial into a coarser fraction discharged to the outside
in the form of streaks and a fine fraction reporting to theinside.
The formation of streaks on the periphery of the deflector wheel was already deduced by Toneva et al. (Toneva P.
et al., 2011), who analyzed the gas flow field in a deflector
wheel separator. They concluded that particles which arerejected from the pursuing paddle could build particle
streaks in the periphery of the deflector wheel, exactly as
observed in the high-speed camera images (cf. Fig. 17).
Surprisingly, the occurrence of streaks is periodicalwith a frequency which depends on peripheral speed andmass loading. So far, however, a detailed analysis of thestreak characteristics has not been completed.
Since the detailed investigation of many open issues
such as fine particle trajectories and motion, the thicknessof the particle layer at the pursuing paddle and the circumferential speed of the vortex is currently restricted by
the resolution of the high-speed camera, it is planned forthe future to use a microscope objective and a Laser
Doppler Anemometer to quantitatively evaluate these
phenomena. These measurements, combined with ongoing CFD and DEM calculations, should provide a solidbase for the development of a more quantitative separation model.

The performance of a deflector wheel classifier atsteady state condition was studied experimentally with alimestone feed material. It was found that the time toreach stationary separation behavior may amount to several tens of minutes depending on mass loading and peripheral speed. In steady state, the separation efficiency
curve, separation sharpness and cut point also depend on
mass loading and peripheral speed.
The visualization of the separation zone between thepaddles of the deflector wheel revealed that the classic
separation models do not represent the physics of the separation process adequately. First, the formation and evolution of a vortex forming inside the separation zone asproposed by Legenhausen, Toneva et al. and Stender et al.
has to be taken into account. This vortex causes a constriction of the radial fluid flow in the separation zone.
Secondly, in an absolute coordinate system, the particles
have nearly no peripheral speed in the approach phase towards the pursuing paddle and therefore they do not experience centrifugal forces in this phase. Third, theparticles bouncing from the paddle collide with the incoming particles and form a dense layer close to the pursuing paddle. We hypothesize that the particles spreadradially in the approach phase while the separation into
coarse and fine fraction occurs in the dense layer close topursuing paddle. In this model, the separation occurs at a
special radial position on the pursuing paddle. Combining
these considerations with the measured cut points may
provide the base for more quantitative separation models
taking into account operational and particle parameters.
As confirmed by high-speed camera images, the coarse
fraction discharges as streaks to the periphery of the deflector wheel, probably contributing to the hold-up ringwhich forms around the deflector wheel. This hold-up
ring which, to the best of our knowledge, is describedhere for the first time seems to be responsible for the induction time to reach stationary separation conditions.
Finally, the sharpness of cut was observed to be virtually constant, only marginally influenced by mass loadingand peripheral speed. While this fact may facilitate thedevelopment of a separation model significantly, i.e. reducing the task to the determination of the cut point, thereason for the constant sharpness of cut is unclear so far.
This phenomenon indicates that the interplay between
particle approach, layer formation, streaks and hold-up
ring is far from being understood and needs much morein-depth investigations.

Acknowledgements
The German research foundation is gratefully acknowl-

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Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

edged for their financial support of this work in context ofthe priority program SPP 1679 (“Dyn. Simulation ofcross-linked solid processes”) under the grand sign WE
2331/16-1.
In addition, special thanks go to B.Sc. Leonard Hansen
for his work on the model approach and the particle cannon.

Abbreviations
CFD Computational Fluid Dynamics
LDA Laser Doppler anemometry
PIV

Particle image velocimetry

Greek letters
ρFl

Fluid density

ρP

Particle density

ηDynamic viscosity

Equation letters
Ap

[m 2]

Particle surface

cw(Re) [–]Coefficient of resistance

Fc

[N]

Centrifugal force

FW

[N]

Drag forceg[m/s²]

GravityɡC[–]

Coarse material proportionk[%]

Separation sharpness

mC

[kg]

Coarse material mass

mFeed [kg]Feed material mass
–1

qFeed

[μm ]

Particle density distribution of the feedqC

[μm–1]

Particle density distribution of the coarse
particle fraction

Q3

[–]

Particle size distribution

r0

[m]

Separation radius

Re

[–]

Particle-Reynolds-number

T(x)

[%]

Separation efficiency

up

[m/s]

Particle circumferential velocity

VP

3

[m ]

Particle volume

vrel

[m/s]

Relative velocity

vr0

[m/s]

Radial fluid velocity at the radius r0,

vφ

[m/s]

Fluid circumferential velocity at radius r0

x

[μm]

Particle size

184

x25

[μm]

Particle size at 25 % of the separation efficiency curve

x75

[μm]

Particle size at 75 % of the separation efficiency curve

xc

[μm]

Median cut point

References
Bauer U., Zur trennscharfen Feinstsichtung in Fliehkraft-­
Abweiseradsichtern, Dissertation, TU Clausthal (2002).
Eswaraiah C. and Narayanan S.S., Studies on a rotating wheel
air classifier for size classification of fly ash, Mineral process technology, Trichy India (2005) 465–472.
Füchsel S., Trockene Desagglomeration von Nanopartikelflocken in einer Gegenstrahlmühle mit kombinierter
Onlineüberwachung, Dissertation, Clausthal (2012).
Galk J., Feinsttrennung in Abweiseradsichtern, Dissertation,
TU Clausthal (1995).
Husemann K., Modelling of Dry Countercurrent Classification,
Aufbereitungs-Technik 39, Freiberg (1998) 279–286.
Legenhausen K., Untersuchung der Strömungsverhältnisse ineinem Abweiseradsichter, Dissertation, TU Clausthal(1991).
Leschonski K., Windsichter, verfahrenstechnische Maschinen
zur Herstellung definierter pulverförmiger Produkte, Jahrbuch 1988 der Braunschweigischen Wissenschaftlichen
Gesellschaft, Braunschweig (1988).
Leschonski K., Classification of particles in the submicron
range in an impeller wheel air classifier, KONA Powder andParticle Journal, 14 (1996) 52–60.
Molerus O., Stochastisches modell der gleichgewichtssichtung,Chemie Ingenieur Technik, 39 (1967) 792–796.
Molerus O., Hoffmann H., Darstellung von windsichtertrennkurven durch ein stochastisches modell, Chemie Ingenieur
Technik, 41 (1969) 340–344.
Richardson J.F., Zaki W.N., The sedimentation of a suspensionof uniform spheres under conditions of viscous flow, Chemical Engineering Science, 3 (1954) 65–73.
Rumpf H. and Raasch J., Desagglomeration in Strömungen,Karlsruhe (1962).
Rumpf, H., Leschonski K., Prinzipien und neuere Verfahren derWindsichtung, Chemie Ingenieur Technik, 39 (1967) 1231–
1241.
Rumpf H., Sommer K. and Stieß M., Berechnung von Trennkurven für Gleichgewichtsichter, Verfahrenstechnik (8),Karlsruhe (1974).
Schubert H., Aufbereitung fester mineralscher Rohstoffe—
Band 1, Leipzig (1968).
Stender M., Legenhausen K. und Weber A.P., Visualisierung
der Partikelbewegung in einem Abweiseradsichter, Chemie
Ingenieur Technik, 87 (2015) 1392–1401..
Stieß M., Mechanische Vefahrenstechnik—Partikeltech-nologie
1, Springerverlag Konstanz (2009).
Spötter C., Stender M., Legenhausen K. und Weber A.P., Dynamische Trenncharakteristik von Abweiseradsichtern,Christian Spötter et al. / KONA Powder and Particle Journal No. 35 (2018) 172–185

Produktgestaltung in der Partikeltechnologie Band 7,
Faunhofer Verlag (2015).
Toneva P., Epple P., Breuer M., Peukert W., Wirth K.-E., Grinding in an air classifier mill Part I: Characterisation of the

one-phase flow, Powder Technology, 211 (2011) 19–27.
Toneva P., Wirth K.-E., Peukert W., Grinding in an air classifiermill—Part II: Characterisation of the two-phase flow, Powder Technology, 211 (2011) 28–37.

Author’s short biography
Christian Spötter
Christian Spötter obtained his M.Sc. degree in 2014 from Clausthal University ofTechnology, Clausthal-Zellerfeld, with the study of environmental process engineering.
For his master’s thesis he researched the optimization of an ilmenite froth flotation byusing new technologies. He graduated from the Institute of Mineral and Waste Processing, Clausthal University of Technology in 2014 headed by Prof. Dr.-Ing. D. Goldmann.
His PhD work focuses on the characterization of the separation behaviour of a deflector
wheel classifier by means of visualization of the separation of air and the particle flow.

Kurt Legenhausen
Dr.-Ing. Kurt Legenhausen studied mechanical engineering at Clausthal University ofTechnology and received his Dipl.-Ing. in 1981. In 1983, he joined the Institute of Particle
Technology at Clausthal University of Technology (Head: Prof. Kurt Leschonski). He
obtained his PhD in 1991 on the investigation of the flow field in a deflector wheel classifier. Afterwards he was chief engineer at the institute, which has been headed by Prof.
Dr. Alfred Weber since 2005. He is managing editor of the Journal of Aerosol Scienceand assists Prof. Weber at the annual Clausthal course on “Particle Measuring Technologies”.

Alfred P. WeberProf. Dr. Alfred Weber studied physics and obtained his PhD in aerosol physics at
ETH Zurich in 1993. After a stay in the group of Prof. Sheldon Friedlander at UC Los
Angeles (UCLA), he joined the group of Prof. Gerhard Kasper at the Karlsruhe Instituteof Technology (KIT) in 1996. He received the Smoluchowski Award in 2001 for his workon aerosol nanoparticles. Since 2005, he is a full professor for Particle Technology at theClausthal University of Technology. He is the editor-in-chief of the Journal of Aerosol
Science. His research focuses on the gas-phase synthesis and applications of nanoparticles.

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KONA Powder and Particle Journal No. 35 (2018) 186–199/Doi:10.14356/kona.2018001

Original Research Paper

Experimental Investigations of the Effect ofChemical Additives on the Rheological Properties
of Highly Concentrated Iron Ore Slurries †Assefa Kebede Melorie and Deo Raj Kaushal *1

Department of Civil Engineering, Indian Institute of Technology Delhi, India

Abstract
Chemical additives are widely used in iron ore industry in various processing steps such as classification,
crushing, grinding, and pelletization. These additives are also used in transportation of iron ore through highly
concentrated slurry pipelines which are currently operating and coming up in large number across the world.
These additives are usually categorized by their functions rather than chemical composition. In this study, theeffect of quick lime (QL), hydrated lime (HL), Sodium hexametaphosphate (SHMP) and Acti-Gel on therheological behaviors of iron ore slurries at volumetric concentrations (Cv) of 18.8 %, 22.1 % and 25.8 % anddosages of additives ranging from 0.05–2 % were investigated. The rheological parameters were measured using
computerized rotational rheometer. All the sample data were best represented by Herschel-Bulkley model.
Minimum shear stress and viscosity were obtained at 2 % dosage of QL for 18.8 % and minimum flow behaviour
index was obtained at 25.8 % with 2 % additive dosage. The addition of HL markedly increases all the rheologicalparameters. When SHMP is used, minimum shear stress and viscosity were obtained at dosage of 1.5 %, 2 % and
2 % for Cv of 18.8 %, 22.1 % and 25.8 % respectively. Acti-Gel resulted higher values of yield stress and flow
behaviour indices at all solid concentrations.
Keywords: iron ore slurry, highly concentrated slurry, chemical additive, rheological property, Herschel-Bulkley
fluid

1. Introduction
The demand of transporting a large quantities of ironore fines, which are generated during mining and washing, through pipeline is increased very rapidly in the last
decades. To mention one, recently in India the Essar SteelCompany completed 253 km-long slurry pipeline thatconnects its ore washery plant at Dabuna, in Keonjhar
district with its pelletization unit at Paradip. The designof this slurry pipeline entails predicting the power requirement per unit of solids delivered over a unit distance.
This pump power demand is mainly a function of pressure drop. For establishing the pressure drop requirements
the rheology of slurry has been identified as a critical parameter. Therefore, it would be useful to study the rheological behaviours of the slurry to estimate pressure dropand hence pumping capacity.
A number of factors influence the rheological be†
1*

Received 23 September 2016; Accepted 27 December 2016
J-STAGE Advance published online 4 February 2017
Hauz Khas, New Delhi - 110016, India
Corresponding author: Deo Raj Kaushal;
E-mail: kaushal@civil.iitd.ac.in
TEL: +91-98-1828-0867 FAX: +91-11-2658-1117

186

haviours namely the parent solid materials, the solid content, the particle size and its size distribution, slurry
temperature, the pH and the presence of electrolytes andchemical additives (He et al., 2004). As stated by Jonesand Harsley (2000) certain chemical additives enhance
the fluidity of the slurries and hence enable the slurries tobe pumped at much higher concentrations thus reducing
the water requirements. So, the selection of appropriate
additives should be recognized as one of the most essential factors in the preparation of slurries for transportation. It is, therefore, relevant to investigate the effects ofchemical additives on the rheological behaviours of slurries. According to Schick and Villa (1983), the chemical
additives must be chosen such that they should provide
sufficient viscosity, electro-kinetic potential and the desired stability. A wide range of chemical additives havebeen used at various processing stages of iron ore mining
industries in order to improve the rheological behaviours.
These chemical agents might have been acted as a dispersants, coagulants, surfactants, or anti-settling agents.
Qiu G. et al. (2003) investigated the functions and molecular structure of ideal organic binders for iron ore pelletization based on the molecular design, interface
chemistry, polymer science as well as failure model of a

Copyright © 2018 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/).

Assefa Kebede Melorie et al. / KONA Powder and Particle Journal No. 35 (2018) 186–199

binding system. Their investigations proved that -COO
and -OH are ideal polar and hydrophilic groups of organic
binders, respectively. They concluded that good organic
binders for iron ore pelletization should contain structurally sufficient polar groups and hydrophilic groups.
He et al. (2004) reviewed the slurry rheology in ultrafine grinding, methods for the characterization of theslurry rheology, empirical equations for modelling therheological behaviours and use of dispersants which affect the slurry rheology. They concluded that the effect ofdispersant is crucial since the solids content of a groundmaterial with an appropriate dispersant in a stirred media
mill increases by about 30 wt.% and the fineness of the final product significantly enhances. They also concluded
that for the slurry rheology control polyacrylic acid or its
salts is the mostly used dispersant as a grinding aid.
Pearse (2005) reviewed in detail the predominant reagentsused and their mode of action in the mineral processing
industry. According to this revision, lime and sulphuricacid are the highest volume bulk inorganic reagents usedin mineral processing. Lime is being used for pH adjustment, coagulation, heavy metal precipitation, causticizationand depression of pyrite in flotation whereas Sulphuricacid is used for pH adjustment as well as for leaching. He
concluded that polyDADMAC (diallyldimethyl ammonium chloride) and quaternized polyamines are the main
coagulants used in the minerals industry and low molecular mass polymers of sodium polyacrylate are used as thedispersing reagents.
Marcos and Antonio (2012, 2013) investigated the effects of the slurry’s rheological behavior and the state ofaggregation and dispersion on wet ultrafine grinding of aniron ore concentrate. They observed that the addition oflime caused an increase in specific energy consumption,with significant increase in yield stress and consistency
index of the fluid. According to the review of Assefa andKaushal (2015a) on the effects of various chemical additives on the flow behaviours of coal ash and iron ore slurries, all the chemical studied are capable of changing theflow behaviours of the slurries under considerations. They

also concluded that the function of these chemical additives
is almost always very specific in nature in which some additives are proprietary products with highly specific functions that work well in some systems but cannot be usedin others. Hence, correct additive selection is important to
get the intended results. Many other chemical additives
are being used in the mineral processing industries suchas in iron ore transportations (Mahiuddin et al., 1989;
Sandra et al., 2013). A summary of some of the chemical
additives and their functions are given in Table 1.
Generally speaking, the use of chemical additives in
the iron ore processing varies from simple to the use ofcomplex combinations of additives in classification, concentration, crushing, grinding, and pelletization. Many
additional studies related to these have been published but
there is still little understanding of the influence of chemicals on the flow behaviours of highly concentrated ironore slurries. In the present study, the influence of fourchemical agents, which have different nature, namely
lime (quick lime and hydrated lime), Sodium hexametaphosphate (SHMP), and Acti-Gel®, on the rheological behaviours of high concentrate iron ore slurries were
investigated.

2. Materials used
2.1 Parental solid material
The material used for this particular study was iron ore
obtained from mine situated at the outskirt of Bangalore
city, Karnataka state, India. The measured pH values are
between 7.52–7.24 for slurry concentration of 18.8–25.8 %by volume without the addition of chemicals agents.

2.2 Chemical additives usedi) Lime
The two types of lime used for this study are quick
lime (CaO) and hydrated lime (Ca(OH)2). Usually both

Table 1 Some of the chemical additives and their functions on the iron ore slurries.
Name of the chemicals

Functions/effects

Parental solids

References

Tapioca, Potato and corn starch;
Sodium Silicate & SHMP

Flocculants; DispersantsIron ore tailings

Hanumantha andNarasimhan, 1985

Magnafloc and Rishfloc; Sodium
petroleum and CTAB

Flocculants; Surfactants

Iron ore fines

Singh & Besra, 1997

Calcium lignosulphonate

Surfactants

Ferrosilicon and magnetite

Mabuza et al., 2005

Magnafloc-1011-anionic andMagnafloc-333- non-ionic

Flocculants

Iron ore tailings

Dash et al., 2011

limestone

Increased reducibilityacid iron ore pellets

Iljana et al., 2015187

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Table 2 Typical physical properties of the chemical agents.

Table 3 Technical Specifications of RheoLabQC.

Properties

QL

HL

SHMP

Acti-Gel

Property

Range

Specific gravity

3.2–3.4

2.0–2.4

2.18

2.62

Speed

0.01 to 1200 L/min

pH

~12.8

~12.4

5.5–7.7

7–9.5

Torque0.20 to 75 mNm

Shear stress

0.5 to 30000 Pa

Shear rate

0.01 to 4000 L/s

Temperature–20°C to 180°C

Angular resolution

2 μradlime act as a coagulants or flocculants and often added tothe iron ore mixture to assist in binding the material to
improve productivity and give a stronger sinter. The maindifference between the two are their reactivity and chemical composition. Quick lime has a heavy density and ismore reactive than hydrated lime. The pH values aremuch more alkaline (Table 2).
ii) Sodium Hexametaphosphate (SHMP)
It is mainly used as a deflocculant or as a dispersing
agent. The dispersant reduces the particle-particle interaction by altering the surface charge, which prevents theparticles from aggregating and effectively reduces theyield stress of the suspension. Several examples of viscosity modification in industrial slurries have been described
although the cost of modifiers limits their general application. SHMP is more commonly used in laboratory procedures to sustain suspensions in the determination ofparticle size distribution.
iii) Acti-Gel
According to the Active Minerals International, LLC
website (ActiveMinerals, 2016), Acti-Gel® 208 is a highly
purified Magnesium Alumino-Silicate and used in a wide
variety of water based industrial applications. It is chemically inert and stable between pH 2 and pH 13. It is a lowdose (–0.05 % to –0.20 % total dry weight material basis)rheology modifier and anti-settling agent that provides
superior particle suspension, stabilizes mixtures, anddramatically improves the workability, flowability, pumpability and performance of slurries and pastes.

2.3 Water
In the real transportation of iron ore as slurries throughpipelines, ordinary water is commonly used as a medium.
Hence, ordinary tap water was chosen for the preparationof iron ore slurry for this particular investigation.

3. Measurement set up and range of parameters
3.1 Measuring device and sample preparations
The experiments were carried out in the Water Resources Simulation Laboratory of Civil Engineering Department, Indian Institute of Technology Delhi. The
rheological data measurements were obtained with thehelp of an advanced computerized rotational rheometer,

188

RheolabQC, manufactured by Anton Paar Company Ltd.,
Germany. It works according to the Searle principle inwhich the viscosity is proportional to the motor torquethat is required for turning the measuring bob (rotor)
against the fluid’s viscous forces. It determines the required force for rotating a bob in a fluid at known speed
and works by defining the exact volume of sample whichis to be sheared within a test cell, the torque required toachieve a certain rotational speed is measured.
The components of the rheometer and how the data canbe read is explained in Assefa and Kaushal (2015b). Two
setting options are available for test: controlled shear rate(CSR) and controlled shear stress (CSS). These options,
together with the wide speed and torque ranges and very
short motor response times, bring innumerable benefits
for the application to investigate the conventional flow
and viscosity behaviours of slurries and others. Details of
the specifications of the rheometer geometry are shown in
Table 3.
For the tests, around 80 to 100 g of the slurry was prepared by mixing the required quantity of solid materials
with tap water to obtain the desired concentration byweight (Cw). The samples were weighed by an electronicbalance with a deviation of ±10 –4 g. Then, the volumetricsolid concentration (Cv) is computed as:

Cv 

100 C w
C w  S g (100  C w )(1)

Where Sg is the specific gravity of the sample.
CSR between 30 to 300 s–1 at 10 equal intervals wasapplied for about 2 minutes to measure the corresponding
shear stress and viscosity. All the measurements were repeated several times to minimize errors occur during
tests. The repeated sets of sample data on shear stress andviscosity agreed within ±2 %. The pH were recorded ateach measurements.
Once the sample is prepared and the measurement isdone, different analysis method can be added in the analysis window interface. And hence, the measured data will
be approximated using the chosen equations and the pa-

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rameters are estimated by weighting of relative error.
From the various equations inbuilt in the Rheoplus Software, Herschel-Bulkley and Bingham models have beenchosen.
Using the given input data points of shear rate, in thisparticular study ranges from 30 to 300 s–1, the parameterssuch as shear stress and apparent viscosity are estimated.
After running the analysis, the model results are obtained
together with the statistical results of correlation ratio, R
and R2, as well as standard deviations relation to yieldstress. For a single data the model selection can be doneusing this value. But in this case, since for each samples
data at least five replications have been made, the averageof the series data were considered. Then, the rheological
data obtained was fit to the Herschel-Bulkley and Bingham models and the best fit model was chosen using R2.

3.2 Range of Parameters
The investigations were carried out at Cv of 18.8, 22.1
and 25.8 %. For all chemicals except Acti-Gel, the additive proportions of 0.05, 0.1, 0.5, 1, 1.5 and 2 % were used.
But for Acti-Gel, proportions of 0.05, 0.1 and 0.2 % wereused.

around 89 % of the particle sizes are below 75 μm. Hence,the sample can be categorized as finer particles. The specific gravity of iron ore fine was measured by sedimentation technique and found to be 4.32 and static settledconcentration is 53.04 % by volume.

4.2 pH values
Fig. 2 shows the effects of concentration of chemical
agents on pH values of iron ore slurries at different concentrations. From the figure, it is seen that pH values werehighly affected by the addition of QL and HL.
Abrupt increase in the pH values was observed whenthese chemicals were added even in small proportions(0.05 %). But then onwards, the rate of increment was decreased as the amount of chemical agents increased. The
minimum and the maximum values registered for bothlime were 9.83 and 12.57 at 0.05 % on Cv of 25.8 % and at
2 % additives on Cv of 18.8 % respectively. When SHMP
was used, the pH values were decreased as the additive
proportion was increased for all slurry concentrations and4. Results and discussions
Analysing the chemical reactions or change in thechemical properties of the slurry is not the intention ofthis particular study. It merely focuses on the influence ofchemicals on the rheological properties of the iron ore
slurries .

4.1 Physical properties of the sample
As shown in Fig. 1, the median particle diameter (d50)
is 12 μm. The maximum particle size is 300 μm andFig. 1

Particle size distribution of the iron ore sample.

Fig. 2pH values of the iron ore slurries at different solid concentration and chemical dosages.

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a minimum and a maximum values of 7.72 and 6.37 were
measured on Cv of 18.8 % at 0.05 % additive and on Cv of
25.8 % at 2 % additive respectively. In contrary, additionof Acti-Gel showed insignificant change in the pH values
at all solid concentrations due to its inert properties.

4.3 Slurries rheological properties and model
representation
The shear stress data were fitted to the models of
Herschel-Bulkley and Bingham, which are expressed as:τ τ y  Kγ n
Herschel-Bulkley model: (2)τ τ y  ηpγBingham model: (3)Where, τy is the yield stress, K is a measure of the average viscosity of the fluid (or the flow consistency index)
and n is a measure of the deviation of the fluid from Newtonian (or the flow behaviour index), ηp is the plastic viscosity and γ is the shear rate.
The average rheological data obtained from exact shear
stress- shear rate data using the rotational rheometer andthose obtained from the two models for Cv of 18.8, 22.1,
and 25.8 % without chemical additives and Cv of 18.8 %with the addition of QL are shown in Fig. 3(a–i). The
same trends were followed for the rest of the data. For all
the samples data, the range of R2 were from 0.8993–
0.9998 and from 0.4253–0.9997 for Herschel-Bulkley andBingham model respectively. Hence, it is concluded thatthe variation of the shear stress with shear rate at all solidFig. 3 (a–i). Selection of best fit model to the measured data of QL at different Cv and chemical proportions.

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concentrations with and without the addition of chemicals
follow a power law with yield stress and best represented
by Herschel-Bulkley model.
The values of K and n were determined by regression
analysis of the logarithmic form of Eqn. (2) using sets ofshear stress and shear rate data read from the flow curves.
For all data sets, the values of n are greater than one
which indicate that the samples exhibit yield shear thickening behaviours (Tables 4–7). Furthermore, it shows anincreasing degree of shear thickening with increase insolid contents. It may also be mentioned that the increase
in apparent viscosity with iron ore content is almost proportional to the value of K.

4.4 The Effects of chemical additives
The Effects of different concentrations of chemical
agents on the rheological behaviours of iron ore slurries
are shown in Figs. 4–15. Figs. 4–6 show the effects of
QL on the shear stress and viscosity of iron ore slurries at
Cv of 18.8 %, 22.1 % and 25.8 % and at additives concentrations of 0, 0.05, 0.1, 0.5, 1, 1.5 and 2 %.
It is showed that for all additives dosages the values ofshear stress and viscosity registered were higher than thevalues without the chemical additives at Cv of 22.1 % and25.8 %. Similarly, the increased in rheogram values wereobserved with increasing the solid concentrations andhigher rate of increments were also shown in all additives
dosages. But in the case of Cv of 18.8 %, the shear stressand viscosity were increased up to 0.5 % of additives andthen deceased as the additives proportions increased andthe minimum rheogram data were registered at the maximum additive concentration (2 %). The rate of decrementin viscosity at the lower shear rate ranges was higher thanat higher shear rate ranges for all the solid concentrations
and chemical additives proportions. Table 4 displayed theresults of the rheological parameters yield stress, flow behaviour index and consistency index as a function of proportions of QL. It is shown that the values of n weredecreased as the solid concentrations increased for thesame additives concentrations and minimum n values
were registered at Cv of 25.8 %. Furthermore, for all solid
concentrations, the additions of QL increased the yieldstresses.
Figs. 7–9 present the shear stress and viscosity at Cv of
18.8, 22.1, and 25.8 % as a function of dosages of HL.
Both the shear stresses and viscosities with the additionsof this chemical agent were markedly higher compared

Table 4 Rheological parameters data at various concentrations and chemical additives of QL.
Cv = 18.8 %Cv = 22.1 %Cv = 25.8 %

QL
(%)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

0

0.086

1.7

5034

0.164

1.4

3361

0.307

1.21

11830

0.05

0.934

1.63

723

0.82

1.45

2548

0.856

1.25

9632

0.1

0.836

1.7

504

0.273

1.25

7851

1.28

1.42

3762

0.5

0.766

1.45

2119

0.521

1.4

3399

0.991

1.27

8760

1

0.369

1.39

3133

0.564

1.28

6794

0.759

1.17

16703

1.5

0.403

1.47

2031

0.783

1.32

5183

1.401

1.2

13265

2

0.329

1.47

1948

0.932

1.52

1724

1.25

1.19

13861

Table 5 Rheological parameters data at various concentrations and chemical additives of HL.
Cv = 18.8 %Cv = 22.1 %Cv = 25.8 %

HL
(%)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

0

0

1.26

6625

0

1.2

11197

0.134

1.11

22459

0.05

0

1.35

4482

0.143

1.26

8449

1.367

1.27

9605

0.1

0.755

1.57

1125

0.186

1.21

10965

1.8

1.48

2928

0.5

0.399

1.39

3330

0.108

1.21

10730

2.017

1.41

4217

1

0.604

1.36

3858

0.073

1.17

14197

1.264

1.32

7176

1.5

0.541

1.4

3185

0.413

1.2

11410

1.227

1.33

7068

2

0.548

1.42

2807

0.047

1.14

16711

1.57

1.32

7537

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with the reference rheogram data (without the addition ofchemical agents) at all solid concentrations and additive
ranges. The same trends as that of QL were observed at

low and high shear rates. Unlike the QL, the lower valuesof n were registered at Cv of 22.1 % for all additive dosages (Table 5).

Table 6 Rheological parameters data at various concentrations and chemical additives of SHMP.
Cv = 18.8 %Cv = 22.1 %Cv = 25.8 %

SHMP
(%)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

0

0

1.39

3760

0

1.31

6111

0.441

1.26

8736

0.05

0

1.64

940

0.559

1.53

5282

0.39

1.34

5546

0.1

0.087

1.44

2623

1.807

1.93

157

3.82

2.65

262

0.5

1.567

2.12

48.5

2.003

2.15

43.6

2.71

2.41

11.9

1

1.367

2.03

82.7

1.49

2.06

75.3

1.75

1.96

156

1.5

0.818

1.97

122

1.407

1.43

2207

1.92

2.02

116

2

1.297

1.85

219

1.321

2.76

2187

1.17

1.83

359

Table 7 Rheological parameters data at various concentrations and chemical additives of Acti-Gel.
Cv = 18.8 %Cv = 25.8 %Acti-Gel
(%)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

τy
(Pa)

n
(–)

K
(μPa.sn)

0

0.106

1.43

2493

0.468

1.79

371.4

2.343

1.4

3424

0.05

0.72

1.81

277.2

0.7

1.79

350.2

0.514

1.38

4620

0.1

0.88

1.69

509.3

0.64

1.72

510.3

1.065

1.58

1454

0.2

0.668

1.84

231.5

1.013

1.67

678.6

1.54

1.69

757

Fig. 4

192

Cv = 22.1 %Rheogram of iron ore slurries at QL dosages of 0 to 2 % and Cv of 18.8 %.

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Fig. 5

Rheogram of iron ore slurries at QL dosages of 0 to 2 % and Cv of 22.1 %.

Fig. 6

Rheogram of iron ore slurries at QL dosages of 0 to 2 % and Cv of 25.8 %.

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194

Fig. 7

Rheogram of iron ore slurries at HL concentrations of 0 to 2 % and Cv of 18.8 %.

Fig. 8

Rheogram of iron ore slurries at HL concentrations of 0 to 2 % and Cv of 22.1 %.

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Fig. 9Rheogram of iron ore slurries at HL concentrations of 0 to 2 % and Cv of 25.8 %.

Fig. 10 Rheogram of iron ore slurries at SHMP concentrations of 0 to 2 % and Cv of 18.8 %.

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Fig. 11 Rheogram of iron ore slurries at SHMP concentrations of 0 to 2 % and Cv of 22.1 %.

Fig. 12 Rheogram of iron ore slurries at SHMP concentrations of 0 to 2 % and Cv of 25.8 %.

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Fig. 13 Rheogram of iron ore slurries at Acti-Gel concentrations of 0 to 0.2 % and Cv of 18.8 %.

Fig. 14 Rheogram of iron ore slurries at Acti-Gel concentrations of 0 to 0.2 % and Cv of 22.8 %.

Fig. 15

Rheogram of iron ore slurries at Acti-Gel concentrations of 0 to 0.2 % and Cv of 25.8 %.

Figs. 10–12 illustrate the relationship between shear
stress versus shear rate and viscosity versus shear rate forthe iron ore slurries at Cv of 18.8 %, 22.1 % and 25.8 %using different dosages of SHMP as a dispersing agents.
It can be seen that low shear stress and viscosity were obtained at additive dosage of 1.5 % for Cv of 18.8 % and at
2 % for Cv of 22.1 and 25.8 %. The same trends also observed as that of lime (QL and HL) at low shear, particularly less than 60 s-1, the rheogram values increased at all
solid concentrations and additives dosages but the rate ofincrement is higher than lime. Furthermore, the values ofn were decreased as the solid concentrations increased for
additives concentrations 0.05 % and then increased forthe remaining dosages of additives for all concentrations(Table 6).
The effects of Acti-Gel dosages on the shear stress andviscosity of iron ore slurries at Cv of 18.8, 22.1 and 25.8 %are presented in Figs. 13–15. From these figures it can beobserved that minimum shear stress was registered at
0.2 % of Acti-Gel for Cv of 18.8 % and at 0.1 % for 22.1 %197

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and 25.8 % of solid concentrations. It can also be seenthat viscosity was increased drastically at the lower shear
rate (usually less than 90 s-1) for all additives and solid
concentrations. A minimum yield stress was obtained atadditive concentrations of 0.2 %, 0.1 % and 0.05 % for Cv
of 18.8, 22.1 and 25.8 % respectively. But these minimum
values were higher than the yield stress at 0 % additive(Table 7). Furthermore, it is also shown that the values ofn were higher when this chemical was added for all rangeof solid concentrations which indicate that the slurryshows more yield thickening behaviours.

Nomenclature
Cw

Concentration by weight (%)

Cv

Volumetric solid concentration (%)

D

Pipe diameter (m)fFanning friction factor (–)

f0

Reference fanning friction factor (–)

f’

Normalized friction factor (–)

HL

Hydrated lime

K

Flow consistency index (Pa sn)

5. ConclusionsnFlow behaviour index (–)

QL

Quick lime

The iron ore slurries, with and without the additions ofchemical agents, considered in this particular study exhibit shear thickening properties and best represented by
Herschel-Bulkley model. The shear stress and viscosity
were decreased beyond 0.5 % of QL and minimum results
were registered at the maximum additive dosage (2 %) on
18.8 % solid concentration. Furthermore, the addition of
QL increased the yield stress and minimum flow behaviour index was obtained at 25.8 % solid concentration
with 2 % additive dosage. In contrary to the above, theaddition of HL increased markedly the values of shear
stress, viscosity, flow consistency and flow behavior indices. When SHMP is used, minimum shear stress and viscosity were obtained at a dosage of 1.5 % for Cv of 18.8 %and at 2 % for Cv of 22.1 % and 25.8 %. Acti-Gel resulted
higher values of τy and n for all ranges of solid concentrations.
The pH values of the slurries were remarkably increased when QL and HL were used in all solid concentrations and additive dosages. On the other hand Acti-Gel
showed negligible effect on pH due to its inert property
and the friction factors increased at all solid concentration
and Acti-Gel dosages.
Further investigation is needed on how these most effective chemical agents change the chemical compositionand properties of the iron ore slurries for the intended
purposes.

Re

Reynolds number (–)

Sg

Specific gravity (–)

Acknowledgements
This scientific work was financed by the Ministry of
Education, Ethiopia with the coordination of Indian Institute of Technology Delhi, India.

198

SHMP Sodium hexametaphosphateU

Flow velocity (m/s)ρmDensity of mixture (kg/m3)

τyYield stress (Pa)ηp

Plastic viscosity (Pa s)γ

Shear rate (s –1)

References
ActiveMinerals (Active Minerals International, LLC) <activeminerals.com/products/high-purity-magnesium-alumino-­
silicate/> accessed 20.02.2016.
Assefa K.M., Kaushal D.R., The influence of chemical additives
on the flow behaviours of solid-liquid suspensions: areview, Conference Proceedings of RACEE-2015, International Journal of Engineering Research & Technology, 4.3(2015a) 180–185.
Assefa K.M., Kaushal D.R., Experimental study on the rheological behaviour of coal ash slurries, Journal of Hydrology
and Hydromechanics, 63.4 (2015b) 303–310.
Dash M., Dwari R.K., Biswal S.K., Reddy P.S.R., Chattopadhyay P., Mishra B.K., Studies on the effect of flocculant
adsorption on the dewatering of iron ore tailings, Chemical
Engineering Journal, 173 (2011) 318–325.
Qiu G., Jiang T., Li H., Wang D., Functions and molecular
structure of organic binders for iron ore pelletization, Colloids and Surfaces A: Physicochemical and Engineering
Aspects, 224 (2003) 11–22.
Hanumantha R.K., Narasimhan K.S., Selective flocculation
applied to barsuan iron ore tailings, Inter. Journal of Mineral Processing, 14 (1985) 67–75.
He M., Wang Y., Forssberg E., Slurry rheology in wet ultrafine
grinding of industrial minerals: A review, Powder technology, 147 (2004) 94–112.
Iljana M., Kemppainen A., Paananen T., Mattila O., Pisilä E.,

Assefa Kebede Melorie et al. / KONA Powder and Particle Journal No. 35 (2018) 186–199

Kondrakov M., Fabritius T., Effect of adding limestone on
the metallurgical properties of iron ore pellets, Inter. Journal of Mineral Processing, 141 (2015) 34–43.
Jones R.L., Horsley R.R., Viscosity modifiers in the mining
industry, mineral processing and extractive, Metallurgy
Review: An International Journal, 20.1 (2000) 215–223.
Mabuza N.T., Pocock J., Loveday B.K., The use of surface
active chemicals in heavy medium viscosity reduction,
Minerals Engineering, 18 (2005) 25–31.
Mahiuddin S., Bondyopadhyay S., Baruah J.N., A study on thebeneficiation of Indian iron-ore fines and slime using chemical additives, International Journal of Mineral Processing,26 (1989) 285–296.
Marcos G.V., Antonio E.C.P., Effect of reagents on the rheological behavior of an iron ore concentrate slurry, International
Journal of Mining Engineering and Mineral Processing, 1.2(2012) 38–42.

Marcos G.V., Antonio E.C.P., Effect of rheology and dispersion
degree on the regrinding of an iron ore concentrate, Journalof Material Research and Technology, 2.4 (2013) 332–339.
Pearse M.J., An overview of the use of chemical reagents inmineral processing, Minerals Engineering, 18 (2005) 139–149.
Sandra Lúcia de Moraesa, José Renato Baptista de Limaa, JoãoBatista Ferreira Netob, Influence of dispersants on the rheological and colloidal properties of iron ore ultrafine particles and their effect on the pelletizing process—A review,
Journal of Material Research and Technology, 2.4 (2013)
386–391.
Schick M.J., Villa J.L., Surfactants in coal technology, American Oil Chemical Society, (1983) 1349–1359.
Singh B.P., Besra L., The effect of flocculants and surfactantson the filtration dewatering of iron ore fines, Separation
Science and Technology, 32.13 (1997) 2201–2219.

Author’s short biography
Assefa Kebede Melorie
Mr Assefa received his BSc degree from Hawassa University (then Debub University),
Ethiopia in 2004. In 2009, he obtained his MSc degree from Haramaya University, Ethiopia. Currently, he is a Ph.D. Scholar in the Department of Civil Engineering at Indian
Institute of Technology (IIT) Delhi. His main research interests are in Rheology, Slurry/
Sediment Transport, Multiphase Flows, Computational Fluid Dynamics and Hydraulics.

Deo Raj Kaushal
Dr. D. R. Kaushal was trained to be a slurry pipeline designer during his Ph.D. at IIT
Delhi and Postdoctoral Research at KIT Japan. He has been an Associate Professor of
Hydraulics in Water Resources Engineering Section of Civil Engineering Department at
IIT Delhi since 2004. He has visited KIT Japan and KCT Japan as visiting Professor.
During his teaching and Postdoctoral research, he has been carried out several researches and consultancy projects. He has worked with several mining, mineral-processing and production companies, either through direct consultation or throughcollaboration with other companies or research organizations.

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Original Research Paper

Compression and Relaxation Properties of Municipal
Solid Waste Refuse-Derived Fuel Fluff †Charley Sprenger, Lope G. Tabil * and Majid Soleimani
1

Department of Chemical and Biological Engineering, University of Saskatchewan, Canada

Abstract
The compression and relaxation characteristics of municipal solid waste (MSW) refuse-derived-fuel (RDF) fluff
were investigated with respect to biodegradable fraction, grind size, moisture content, applied load, and pelleting
temperature. Experimental trials were performed by using a single pelleting unit mounted on an Instron universal
testing machine. Two grind sizes of each sample were prepared, 3.18 mm and 6.35 mm, and moisture contents
were increased to 8 %, 12 %, and 16 % w.b. The applied loads were set at 2 kN, 3 kN, and 4 kN at two
temperature settings, 50 °C and 90 °C. The experimental data for these trials was collected and multiple
compression and relaxation models were fitted to the applied pressure, compact density or volume data. The
results indicated that the compact density of RDF improved by increasing the grind size, while the compact
density of biodegradable pellets increased with increasing pelleting load and temperature. The compact density ofpellets produced from RDF ranged from 880–1020 kg/m3; the compact density of the biodegradable pellets ranged
from 1120–1290 kg/m3. The Walker and Jones models both indicated that the biodegradable material fraction has
a higher compressibility than the RDF material, where neither moisture content nor grind size at all levels had asignificant effect on the compressibility of either material. The Kawakita-Lüdde model estimated the porosity ofthe pelleted samples, while the Cooper-Eaton model indicated that the primary mechanism of densification wasparticle rearrangement. Application of the Peleg and Moreyra model for analysis of relaxation properties of thecompressed materials determined the asymptotic modulus of the residual stress to be between 89 and 117 MPa forall experimental parameters; however, the RDF material produced more rigid pellets than the biodegradable
material.
Keywords: densification, asymptotic modulus, visco-elastic properties, municipal solid waste, bio-processing,biofuels

1. Introduction
In an age of societal dependence on fossil-based resources, paired with concerns over environmental sustainability, researchers and policy makers are avidly
looking towards biofuels as an alternative means to meetthe demand for energy in future generations. In particular, ‘advanced’ biofuels—those that are made with materials that do not compete with food or land resources—
are of high research and development interest as a means
to achieve the energy goal in the most sustainable means
possible (BioFuelNet, 2015). Biofuels are recognized withbeing carbon-neutral, slowing the exponentially risingconsequences of greenhouse gas emissions, and are developed from renewable resources.
†
1*

Received 13 January 2017; Accepted 30 January 2017
J-STAGE Advance published online 31 March 201757 Campus Drive, Saskatoon, Saskatchewan, S7N 5A9, Canada,
Corresponding author: Lope G. Tabil;
E-mail: lope.tabil@usask.ca
TEL: +1-306-966-5317 FAX: +1-306-966-4777

200

Municipal solid waste (MSW) consists of both organicand inorganic fractions and may include paper, plastic,
glass, metal, food waste, wood, and other composite materials (Mor et al., 2006). There is potential for the utilizationof MSW in the form of refuse derived fuel (RDF) as afeedstock for thermochemical conversion in this advanced
biofuels industry. Typically, MSW is disposed of in landfills as garbage, as such the conversion to RDF would
provide a more sustainable alternative disposal method
for the waste. The City of Edmonton in collaboration with
Enerkem Alberta Biofuels currently operates a Waste-to-­Biofuels facility in which processed MSW (RDF-fluff) isconverted into methanol through patented, low-severity
gasification technology (EWMC, 2015). Densification ofthis RDF-fluff would produce a higher quality feedstockthat is more durable, improving storage and handling aswell as providing a more uniform product for conversion.
Literature indicates that there are numerous variables
that influence biomass densification; these include bothprocess conditions and material characteristics. The process variables imposed on the densification procedure

Copyright © 2018 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/).

Charley Sprenger et al. / KONA Powder and Particle Journal No. 35 (2018) 200–208

include temperature, applied pressure, hold time, diegeometry, and application rate. The addition of heat results in a reduced resistance to applied load by biomaterials (Sokhansanj et al., 2005). Increased applied pressure
will indeed result in higher densities, however there is an
optimal pressure that should be utilized at which the mechanical strength of the material due to plastic deformation is reached (Yaman et al., 2000). Hold times are mostsignificant in reducing the effect of ‘spring-back’ fromelastic deformation during compression. Die geometry
influences the amount of material that can be pelleted;smaller diameters will increase the restriction and therefore the energy required to produce a pellet. Material variables such as moisture content, particle size distribution,
biochemical composition, and pretreatment are characteristic of particular biomass feedstocks. Several sources indicate that moisture contents between 8–12 % result in
denser and higher quality pellets from cellulosic materials(Sokhansanj et al., 2005). Water acts as a binder in which
the contact area of the particles is increased, allowing forthe formation of bonds by van der Waal’s forces (Mani etal., 2003). Particle size distribution in addition to geometric mean diameter has an effect on the quality and densityof pellets (Payne, 1978). The biochemical composition ofa feedstock (i.e. the fraction of starch, cellulose, protein,
etc ...) will also affect the densification process and may
indicate the necessity for pretreatment such as the case of
lignocellulosic materials which are very resistant to deformation. Knowledge of the effects of these characteristics will assist in designing energy efficient compaction
methods to produce high quality pellets for thermochemical conversion and provide understanding for the implementation of feasible waste management strategies.
Various models have been adapted in previous studies
to examine the compression and relaxation characteristics
of biomass feedstocks. The Jones, Walker, Kawakita-­
Lüdde, and Cooper-Eaton models are fitted to experimental compression data, while the Peleg and Moreyra model
is fitted to relaxation data to determine a material’s asymptotic modulus (Adapa, et al., 2010). Relationship between compression pressure and compact density, fromboth Walker and Jones models, indicates the compressibility of a material and points to an optimal pelletingpressure to be used for energy-efficient compaction ofdifferent samples (Mani, et al., 2006). Porosity of compacted samples estimated using the Kawakita-Lüdde
model allows comparison to the solid density of the loosematerial; the solid density is the maximum value that canbe achieved during compression where there is zero porosity. The Cooper-Eaton model hypothesizes the mechanisms of densification as particle rearrangement anddeformation and that if the sum of these two parameters
do not result in unity, then there must be another mechanism involved in the compaction process; thus, analysis ofthese parameters can assist in determining the ratio of themechanisms involved in the densification of new materials (Adapa, et al., 2010). A material’s asymptotic modulus,
estimated by the Peleg and Moreyra model, implies its
ability to sustain unrelaxed stresses or its rigidity (Talebi,
et al., 2011). A material with a high compressibility resulting in a highly compact, rigid pellet is the desired outcome of a densification process, thus analysis of theseparameters can result in optimizing the conditions forpelletization.
The objective of this study is to investigate how composition, grind size, moisture content, applied load, andprocessing temperature affect the compression and relaxation characteristics of MSW RDF-fluff.

2. Materials and Methods
2.1 Materials
Municipal solid waste (MSW) refuse-derived fuel (RDF)
fluff was supplied by the Edmonton Waste Management
Centre (EWMC), Edmonton, AB, Canada. The fluff uponreceipt had a moisture content of 5.5 % wet basis (w.b.)
and an average bulk density of 54.6 kg/m3. It is to be
noted that the EWMC facility experiences RDF-fluff
moisture contents of upwards of 20–30 % w.b.
Pelleting characteristics were examined for two different fractions of the RDF-fluff material. The first material
utilized the RDF in its raw composition; this consisted ofapproximately 35 % paper, 22 % plastics, 14 % textiles,
6 % wood/organics, and the remainder fines and inerts,
determined by a composition sort. The second material
consisted of only biodegradable components, wood andpaper, after undergoing sorting to remove plastics andtextiles.
Each material was ground in two screen sizes, 3.18 mm
and 6.35 mm, of the knife mill (Retsch GmbH, Haan,
West-Germany). The moisture content of each of the 4material/grind size samples was determined according to
ASABE Standard S358.3 (ASABE, 2008), then adjusted
to 8 %, 12 %, and 16 %, w.b. Samples were allowed toequilibrate in air-tight containers for a minimum of 3days prior to the start of the experiment.

2.2 Compression and relaxation tests
The compression tests were performed using a single
pelleting unit (SPU) apparatus mounted on an Instron
Universal Testing Machine (Model No. 3366, InstronCorp., Norwood, MA). This SPU consisted of a cylindrical die fixed to the base of the machine with a plunger attached to the moving crosshead of the Instron machine(Shaw, 2008). A heating element was attached to the pel-201

Charley Sprenger et al. / KONA Powder and Particle Journal No. 35 (2018) 200–208

leting die in order to control the temperature of the process; temperatures were compared at 50 °C and 90 °C,
with the pelleting protocol allowing time for the material
to preheat in the die before being compressed. Approximately 0.55 ± 0.05 g of biomass was fed into the die toproduce each pellet. The Instron was then used to apply
the load to compress the charged material at a rate of
50 mm/min until the desired compressive force (2, 3, and4 kN) was achieved, at which point the plunger was heldfor 60 s as a retention time to avoid “spring-back” typicalof densified biomass. A gate in the platform of the SPU
apparatus was then opened manually to allow the plunger
to eject the newly formed pellet from the die. The software programmed to control the Instron and complete
the densification process recorded the time and force-­
displacement data for each pellet. Twelve pellets (replicates) were produced for each treatment combination; thedimensions and mass of each pellet was measured after
each pellet was stored at room conditions for subsequent
analyses.

2.3 Data analysis
The experimental data collected was analyzed using
several compression and relaxation models for powders.
All of the models were fitted to the experimental data using Microsoft Excel (Microsoft Corp., Redmond, WA)with the exception of the Cooper-Eaton model, in which
SAS (Statistical Analysis System, Cary, NC) was employed. The Microsoft Excel analysis incorporated thesolver tool and non-linear regression techniques, in whichconstants for the appropriate models were determined foreach set of experimental data by the method of leastsquares. Acceptability of the correlation between themodel constants and the experimental data was determined by the mean square error and the coefficient of determination (R2) of the respective models.
The purpose of fitting the compression and relaxation
data of the densification experiments was to determine
the relationship between compression pressure and compact density in order to determine the most energy-­
efficient means of producing quality pellets for different
material conditions.
Models proposed for analyzing the compressibility of
powders have also been successfully applied to the compression of biomaterials such as timothy hay. Compression of non-metallic powders were modelled by Walker
according to the volume ratio to applied pressure (Equation 1) (Walker, 1923).

Vm  ln P  b

Vs

(1)

Where, V = volume of compacted hay, m3; Vs = void-freesolid volume, m3; P = applied pressure, MPa; m, b = con-202

stants.
Jones (1960) described the compression of industrial
metal powders through the linear relationship of the natural logarithm of both pressure and density (Equation 2).
ln ρ m  ln P  b

(2)

Where, ρ = compact density, kg/m3; m', b' = constants.
Kawakita and Lüdde (1971) related pressure to the volume reduction of metallic powders (Equation 3).
P
1
P


C a1b1 a1(3)

V0  V
V0(4)

C

Where, C = volume ratio; V0 = initial volume at zero pressure, m3; a1, b1 = constants.
Cooper and Eaton (1962) attributed the compression ofceramic powders to two independent processes; the fillingof large voids through material sliding past one anotherand slight fractures followed by the filling of small voids
through plastic flow and fragmentation (Equation 5).
 k1
k 2
V0  V a 2 e P  a3 e P
V0  Vs(5)

Where, a2, a3, k1, k 2 = constants.
The relaxation characteristics of solid foods are modelled by Peleg and Moreyra and can be used to compare
different materials (Equation 6).

F0  t k3  k 4  t
F0  F (t )(6)Where, F0 = initial relaxation force, kN; F(t) = relaxation
force at time t, kN; t = time, s; k 3, k4 = constants.
A modified model by Peleg and Moreyra (1980) gives aslope index that describes the solidity of compressed materials; this can be used to determine the asymptotic modulus of solid foods and powders. The asymptotic modulus
is defined as the ability of the compressed material to sustain un-relaxed stress, represented by the residual stressin the Peleg and Moreyra model (Equation 7).

EA

F0 
1 
1
Aa ε  k 4 

(7)Where, EA = asymptotic modulus, MPa; ε = strain; Aa =cross-sectional area, m 2.
The percent average relaxation was calculated by using
the initial force at the beginning of the relaxation phase andthe final force after an elapsed time of 60 s (Equation 8).
Percent average relaxation 

100  F0  Fe 
F0

Where, Fe = final relaxation force, kN.

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3. Results and discussion
The SPU trials resulted in data for 12 replicates of eachmaterial property and pelleting condition combinations.
The aforementioned models were fitted to the data fromthese trials to evaluate the compression and relaxation
characteristics for each sample. Fig. 1 displays a typicalcompression curve for the biodegradable material fractionof RDF.

The moisture content of the unprepared samples wasdetermined to be 5.45 % w.b. for the RDF material and7.15 % w.b. for the biodegradable fraction of the RDF material. These values were used to condition the samples,using the standard ASABE S358.3, to experimental moisture contents of 8, 12, and 16 %.
Prior to the experiments, the particle density of eachmaterial was determined for each moisture content andgrind size combination using a pycnometer (Multipycnometer, Quantachrome Corp., Boynton Beach, FL); particle density is the maximum compact density that can beachieved during compression. Moisture content had little
significance over the particle density; however, the densities for RDF ground by 3.18 and 6.35 mm screens wereapproximately 1350 and 1280 kg/m3 (Table 1), respectively, while the densities for biodegradable material
ground by 3.18 and 6.35 mm screens were approximately
1230 and 1140 kg/m3, respectively.

3.1 Density

Fig. 1

Typical compression curve as a function of compression and relaxation time at preset loadings for 3.18 mm
grind, 16 % m.c. (moisture content) biodegradable material at 50 °C.

Table 1

Table 1 shows the effects of material grind size, moisture content, pelleting load and temperature of the RDF
and biodegradable materials, respectively. Densificationof the RDF pellets was only affected by the material grindsize, in which the material ground in a 6.35 mm screen in

Effects of pelleting parameters on compact density (kg/m3) of refuse derived fuel fluff and biodegradable material fraction.
Applied Load (kN)

Grind Size(mm)

Moisture
Content(% w.b.)2

3

4

Die Temperature (°C)
50

90

50

90

50

90

Refuse Derived Fuel Fluff
3.18

6.35

8

938 (34)12a

885 (28)887 (32)887 (34)918 (47)926 (37)898 (40)870 (33)896 (20)913 (17)937 (24)929 (19)16

905 (20)923 (40)915 (23)938 (19)926 (13)930 (45)8950 (36)972 (36)993 (47)

1000 (41)1010 (29)1010 (48)12988 (44)979 (40)989 (49)998 (42)1007 (58)990 (35)16

982 (36)1014 (40)991 (39)1018 (34)993 (59)

1010 (28)Biodegradable material
3.18

6.35
a

8

1126 (15)1134 (21)1194 (27)1218 (18)1206 (28)1237 (22)121179 (19)1190 (19)1199 (12)1232 (24)1235 (22)1250 (34)161154 (15)1175 (13)1194 (29)1217 (16)1219 (17)1254 (29)81122 (15)1155 (38)1181 (27)1199 (14)1253 (25)1285 (18)121135 (25)1184 (33)1189 (29)1227 (19)1233 (23)1255 (14)161161 (30)1182 (20)1204 (36)1217 (21)1227 (18)1242 (21)Value in parentheses indicates the sample standard deviation where n = 12.

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the knife mill resulted in greater compaction. Compact
density of the biodegradable pellets increased with increasing pelleting load and temperature, while there wasno significant effect of moisture content or grind size ofthe material. There were significant differences in thecompact density of the two materials; the biodegradable
material produced high density pellets; 1100–1250 kg/m3,
at all applied pressure and temperature combinations,while the RDF material produced pellets with densities of
850–1000 kg/m3. Bulk density of the pellets produced
during the single-pelleting trial was unable to be measured due to the small sample size, however a bulk density of pellets produced in a subsequent pilot-scale trial
was determined to be approximately 590 kg/m 3 and660 kg/m3 for RDF and biodegradable materials, respectively. The bulk density of the raw RDF-fluff was 55 kg/m3,
therefore both the RDF and the sorted biodegradable materials produced a feedstock that was at least 10 times
denser than the original product following pelletization.

3.2 Compression models
The relationship between pressure, volume, and densityof the RDF and biodegradable material during the compression portion of the tests (i.e. until maximum loading
was achieved) were fitted to models that have been developed for powders. The Walker model describes the relationship of volume ratio to pressure, which decreases
linearly as the pressure increases. All test combinations
resulted in a fitted Walker model that yielded an averagecoefficient of determination value (R2) of greater than
0.90. Fig. 2 shows a sample relationship between the volume ratio and the natural logarithm of applied pressure.
The slope, m, of the fitted Walker model is referred to as
the compressibility constant and it remained fairly constant for all parameter tests for each material type. For

Fig. 2204

Fitted Walker model relationship to compression datafor 3.18 mm, 16 % m.c. biodegradable material underpelleting conditions of 4 kN applied force and 50 °C
die temperature.

RDF samples, the slope had an average value of −0.3197
with a standard deviation of 0.0194; while the biodegradable fraction of RDF had an average slope value of–0.3410 with a standard deviation of 0.0235. The biodegradable samples showed a higher slope (absolute value)indicating higher compressibility than the RDF material.
This variation could probably be attributed to the different compression properties of the additional plastic fraction in the RDF material. The value of ‘b’ was greater atlower grind size and for the RDF material.
The Jones model describes the relationship of compact
density to pressure, which increases linearly as the pressure increases. All test combinations resulted in a well-­fitted Jones model, yielding an average R 2 value ofgreater than 0.97. The values of the slope, m’, for themodel indicates the compressibility of the material. For
RDF samples, the slope had an average value of 0.1644
with a standard deviation of 0.0084; while the biodegradable samples had an average slope value of 0.1906 with astandard deviation of 0.0079. Similar to the results of theWalker model, the biodegradable samples showed ahigher slope (m’) indicating higher compressibility thanthe RDF material. For all moisture content/grind size
combinations, the value of the slope appeared to decrease
with an increase in either pelleting conditions, temperature or applied load. There was no significant differencein compressibility between trials with different material
conditions, moisture content or grind size. The value of b’of the Jones model was relatively constant for all tests forboth RDF and biodegradable materials at an average(standard deviation) of 7.2331 (0.1611) and 7.5622 (0.1509),
respectively.
The Kawakita and Lüdde model indicated a good fit to
the data, resulting in mean square error (MSE) values ofless than 5 × 10 –4. However, there was no correlation
found between the model constants and any of the experimental variables for either material. Established by
Kawakita and Lüdde (1971), the model constant a1 represents the initial porosity of the sample, while the parameter 1/b1 indicates the yield strength or failure stress ofthe compaction process (MPa). As such, the model indicates a higher average initial porosity for RDF material ata grind size of 6.35 mm, 0.899 compared to 0.753 at the3.18 mm grind size. This is reasonable as the smaller particles would exhibit greater mechanical interlocking andthus, a lower initial porosity. The opposite observation ismade for that of the biodegradable material, in whichmodel determined initial porosities of 0.801 and 0.772
were for grind sizes of 3.18 mm and 6.35 mm, respectively. This contradiction may be attributed to the fact thatwhile the materials were ground using a particular screen
size, not all of the particles were exactly the same size; aparticle size analysis indicated that the biodegradable material, once ground, consisted of a higher fraction of fineCharley Sprenger et al. / KONA Powder and Particle Journal No. 35 (2018) 200–208

particles than the equivalent RDF ground material. Decrease in grind size resulted in a decrease in the yieldstress (1/b1) for both the RDF and biodegradable material,
however the actual values (standard deviation) were similar at 2.59 (0.61) kPa and 2.65 (0.60) kPa, respectively.
Cooper-Eaton model speculates the two mechanisms
involved in densification; particle rearrangement and deformation. The constants a2 and a3 in the Cooper-Eatonmodel, respectively represent the two mechanisms. Fitting
the model to the experimental data yielded values for a2
ranging from 0.66 to 0.97 and values for a3 ranging from0.00 to 0.23; this indicates that the majority of the compaction mechanism is resultant of particle rearrangementby the filling of large pores. The R2 values for each sample were above 0.86 with most being at least 0.95, indicating a good fit of the model to the experimental data.

3.3 Relaxation characteristics
After the desired compression pressure was reachedthrough the applied loading, the relaxation characteristics
were observed for all trials. Noticeable relaxation was observed during the 60 s holding period; this indicates thatcomplete plastic deformation was not fully achieved upon
the applied loading.
The Peleg and Moreyra model was fitted to the linearized data of compressive pressure in relation to relaxation
time. The slope of the model, k4, is referred to as the solidity index and was used to calculate the asymptotic
modulus, Ea, for the material. The asymptotic modulus
indicates a material’s ability to sustain unrelaxed stresses,
such that a higher Ea leads to a more rigid restraint of apellet’s compact density (Table 2). Pellets produced fromRDF material resulted in an asymptotic modulus of between 94 and 117 MPa, while the biodegradable pellets
had an Ea value of 89 to 103 MPa. This indicates that theRDF material produces a more rigid pellet than the biodegradable material. The combined effects of pelleting tem-

perature and initial moisture content have a positive
correlation with the asymptotic modulus value for eachmaterial. Pellets produced at 90 °C had Ea values 3 to 17
percent larger than those produced at 50 °C; the highest
percent difference was observed at 16 % m.c. (w.b.) for
each grind size. The asymptotic modulus values calculated for the RDF-fluff samples were comparable to otherbiological materials according to literature; for example
corn stover, barley straw, and wheat straw display Ea values between 20 and 160 MPa (Mani et al., 2006).
As previously noted, relaxation was observed during
the experiment and was quantified as the percent averagerelaxation (PAR) (Table 3). Values ranging from 21 to
35 % and from 29 to 37 % were determined for the RDF
and biodegradable pellets, respectively. These values are
consistent with literature values for timothy hay, wherein
PAR values of 27 to 53 % were published (Talebi, et al.,2011). As with the asymptotic modulus, die temperature
has the highest positive correlation to PAR.

4. Conclusions
The compression and relaxation characteristics of RDFfluff samples were investigated and the following conclusions were made:1. The compact density of RDF pellets was only affectedby grind size, in which it was greatest with material
that was ground with a 6.35 mm screen in the knife
mill; compact density of biodegradable pellets increased with increasing pelleting load and temperature, while there was no significant effect of moisture
content or grind size of the material.
2. Both Walker and Jones model resulted in good fits tothe experimental data and indicated that the biodegradable material had a higher compressibility thanthe RDF material for all conditions.
3. Fitting of the Kawakita-Lüdde model to the compres-

Table 2 Effects of experimental variables on asymptotic modulus, Ea (MPa).
Grind Size
(mm)

3.18

6.35
a

Moisture
Content(% w.b.)Refuse Derived Fuel Fluff

Biodegradable Material

Die Temperature (°C)
50
a

90

50

90

105.91 (0.98)

96.23 (0.39)

99.23 (12.10)

8102.31 (2.06)

12

94.33 (1.45)

99.76 (1.57)

98.06 (0.16)

102.07 (0.76)

16100.28 (9.40)

117.99 (3.92)

91.07 (0.87)

95.56 (0.49)

8

102.92 (1.06)

108.68 (1.55)

96.88 (0.49)

102.43 (2.17)

12100.24 (4.68)

104.10 (1.58)

93.82 (1.91)

99.88 (1.94)

16

102.26 (8.68)

116.65 (2.04)

89.11 (3.56)

98.45 (3.89)

Value in parentheses indicates the sample standard deviation where n = 6.

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Table 3 Effects of experimental variables on percent average relaxation, PAR (%).
Grind Size
(mm)

3.18

6.35
a

Moisture
Content(% w.b.)Refuse Derived Fuel Fluff

Biodegradable Material

Die Temperature (°C)
50
a

90

50

90

28.00 (0.52)

33.47 (0.28)

34.58 (1.16)

8

31.41 (1.15)

12

35.46 (0.71)

31.90 (1.20)

32.02 (0.19)

29.11 (0.51)

16

31.86 (5.15)

21.65 (1.18)

36.52 (0.71)

33.40 (0.39)

831.53 (0.38)

27.44 (0.76)

32.29 (1.44)

29.16 (1.07)

12

32.23 (2.65)

29.43 (0.39)

34.71 (1.30)

30.25 (1.34)

16

31.17 (4.84)

22.62 (1.07)

37.68 (1.78)

31.52 (2.16)

Value in parentheses indicates the sample standard deviation where n = 6.

sion data resulted in no significant correlation(P = 0.05) between the model parameters and the experimental variables.
4. The Cooper-Eaton model indicates that the primarymechanism in the densification of RDF derived biomass is attributed to particle rearrangement, withsome secondary influence from plastic deformation or
particle fragmentation.
5. Peleg and Moreyra’s model, fit to the data, estimatedthe asymptotic modulus (Ea) for each sample and indicated that pellets formed from the RDF material had ahigher E a value than the biodegradable pellets;
RDF-derived materials are determined to have comparable Ea values to literature values for other biological residues.

Acknowledgements
This research has been in collaboration with the Edmonton Waste Management Centre. Significant funding
was provided by BioFuelNet Canada under the waste as
feedstocks project.

Nomenclature

SPU

Single Pelleting Unit

Aacross-sectional area (m 2)

a1

Kawakita-Lüdde model constanta2

Cooper-Eaton model constanta3

Cooper-Eaton model constantb1

Kawakita-Lüdde model constantb

Walker model constantb'

Jones model constantCvolume ratioEa

asymptotic modulus, (MPa)Fe

final relaxation force (kN)F0

initial relaxation force (kN)F(t)

relaxation for at time t (kN)

k1

Cooper-Eaton model constantk2

Cooper-Eaton model constantk3

Peleg-Moreyra model constantk4

Peleg-Moreyra model constantm

Walker model constantm'

Jones model constantP

pressure (MPa)ttime (s)Ttemperature (K)ASABE

American Society of Agricultural and BiologicalEngineers

BFN

BioFuelNet

Vvolume of compacted material (m3)

EWMC

Edmonton Waste Management Centre

V0

initial volume at zero pressure (m3)MSW

Municipal Solid Waste

Vsvoid-free solid volume (m3)PAR

Percent Average RelaxationεstrainRDF

Refuse Derived Fuelρ

compact density (kg/m3)

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References
Adapa P., Tabil L. Schoenau G., Compression characteristics of
non-treated and steam-exploded barley, canola, oat, andwheat straw grinds. Applied Engineering in Agriculture, 26(2010) 617–632.
ASABE (American Society of Agricultural and BiologicalEngineers Standards), ASAE S358.3 Moisture measurement—forages, ASABE, St. Joseph, Michigan, 2008.
BioFuelNet (BioFuelNet Canada), 2015, What are biofuels?
<http://www.biofuelnet.ca/wp-content/uploads/2015/01/
Infographics11.png> accessed 15.02.2017.
Cooper A., Eaton L., Compaction behavior of several ceramic
powders, Journal of the American Ceramic Society, 45(1962) 97–101.
EWMC (Edmonton Waste Management Centre), 2015, Waste-­to-biofuels and chemicals facility: turning garbage into fuel<www.edmonton.ca/programs_services/garbage_waste/biofuels-facility.aspx> accessed 15.02.2017.
Jones W.D., Fundamental principles of powder metallurgy,
Edward Arnold Publishers Ltd., London, 1960, pp. 242–
370.
Kawakita K, Lüdde K., Some considerations on powder compression equations, Powder Technology, 4(1971) 61–68.
Mani S., Tabil L., Sokhansanj S., An overview of compaction of
biomass grinds, Powder Handling & Processing, 15 (2003)
160–168.
Mani S., Tabil L., Sokhansanj S., Effects of compressive force,
particle size, and moisture content on mechanical proper-

ties of biomass pellets from grasses, Biomass and Bioenergy, 30 (2006) 648–654.
Mor S., Ravindra K., Visscher A. De, Dahiya R., Chandra A.,
Municipal solid waste characterization and its assessment
for potential methane generation: A case study, Science of
the Total Environment, 371 (2006) 1–10.
Moreyra R., Peleg M., Compressive deformation patterns of
selected food powders, Journal of Food Science, 45 (1980)
866–868.
Payne J.D., Improving quality of pellet feeds, Milling Feed andFertilizer, 161 (1978) 3441.
Shaw M, Feedstock and process variables influencing biomass
densification, M.Sc. Thesis, 2008.
Sokhansanj S., Mani S., Bi X., Zaini P., Tabil L., Binderless pelletization of biomass, Presented at the ASAE Annual International Meeting, July 17–20, 2005, Tampa, Florida. ASAE
Paper No. 056061. ASAE, 2950 Niles Road, St. Joseph, MI
49085-9659 USA.
Talebi S., Tabil L., Opoku A., Shaw M., Compression and relaxation properties of timothy hay, International Journal of
Agricultural and Biological Engineering, 4 (2011) 69–78.
Walker E., The properties of powders—Part VI: The compressibility of powders, Transactions of the Faraday Society, 19(1923) 73–82.
Yaman S., Şahan M., Haykiri-açma H., Şeşen K., Küçükbayrak
S., Production of fuel briquettes from olive refuse andpaper mill waste, Fuel Processing Technology, 68 (2000)
23–31.

207

Charley Sprenger et al. / KONA Powder and Particle Journal No. 35 (2018) 200–208

Author’s short biography
Charley Sprenger
Charley Sprenger is a MSc candidate in the Department of Chemical and BiologicalEngineering, University of Saskatchewan. Her thesis research is in the area of pre-­processing of municipal solid waste for biofuels applications.

Lope G. Tabil
Lope G. Tabil, is a Professor of Biological Engineering in the Department of Chemical
and Biological Engineering, University of Saskatchewan. The areas of research in which
he works and maintains interest include bioprocess engineering, value-added engineering, biomass energy and postharvest handling of crops. He has also conducted researchand development projects related to value-added processing of agricultural products including storage, drying and cooling, and physical properties of agricultural and biological materials.

Majid Soleimani
Majid Soleimani is a PDF Research Associate at the Department of Chemical and Biological Engineering, University of Saskatchewan. His research interests are in bioproducts, biofuels, and biomaterials. He did his PhD in Industrial Biotechnology-Bioprocess
Engineering. The title of his thesis was “Xylitol production in free- and immobilized-cellbioconversions from lignocellulosic biomass”. The major focus of the thesis was on the
kinetic study of xylitol production in homogeneous and heterogeneous bioreactors. In
the last few years, he has been working on biomass densification (granulation and pelletization) and some thermochemical processes such as torrefaction for solid biofuelapplications. Also, he has been involved in a few projects on biocomposites, including
fully- and partially-degradable composites for structural applications or as cell support
in biocatalysis.

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KONA Powder and Particle Journal No. 35 (2018) 209–215/Doi:10.14356/kona.2018008

Original Research Paper

Photostability of Risperidone in Tablets †Yuki Fujisawa 1*, Yoshiteru Takahashi 1, Reiko Teraoka 2 and Shuji Kitagawa 2
1
2

Pharmaceutical Technology Center, Sawai Pharmaceutical Co., Ltd., Japan
Laboratory of Pharmaceutical Technology, Kobe Pharmaceutical University, Japan

Abstract
The purpose of this study is to evaluate the photostabilization mechanism of risperidone tablets. Risperidone is
widely used for sensory integration disorder. It is formulated as tablets, orally disintegrating tablets, fine granules,
oral solutions, and intramuscular injections. We found that risperidone was unstable in tablets and generated
oxidized products. Formation of the oxidized product R5 was promoted in the presence of hydroxypropylcellulose
by photoirradiation. On the other hand, photostability improved greatly when carmellose (CMC) or carmellose
calcium (CMC-Ca) was used as a disintegrant. Since CMC and CMC-Ca are acidic substances, the photostabilityof tablets may have been affected by pH. Therefore, the effects of different pHs were examined. Risperidone wasdissolved in methanol and the buffer (in the presence or absence of hydroxypropylcellulose) at different pHs (1.2,
3.0, 4.0, 5.0, and 6.8) was added. The photodegradation of risperidone was not observed at less than pH 3.0 in thepresence of hydroxypropylcellulose, and low pHs improved the photostability of risperidone. On the other hand,risperidone solution without hydroxypropylcellulose was stable at all pH values. Therefore, risperidone wasphotochemically oxidized in the presence of hydroxypropylcellulose at high pHs.
Keywords: photostability, risperidone, carmellose, pH, hydroxypropylcellulose, tablet

1. Introduction
Risperidone (3-{2-[4-(6-fluoro-1,2-benzisoxazol-3-yl)-1-­
piperidinyl]ethyl}-6,7,8,9-tetrahydro-2-methyl-4H-pyrido[1,2-α] pyrimidin-4-one) is a benzisoxazol derivative thatis widely used for sensory integration disorder (Janssen
P.A.J., 1987); it has both serotonin 5-HT2 and dopamine D2
antagonistic activities (Janssen P.A.J. et al., 1988; Leysen
J.E. et al., 1988; Grant S. and Fitton A., 1994).
Risperidone was developed by Janssen Pharmaceutica
Inc. and won FDA approval in the US on December 29,
1993 (where it is marketed as RISPERDALTM), and subsequently achieved worldwide acceptance (Germann D. etal., 2012).
9-Hydroxylation of risperidone is mainly generated by
two cytochrome P-450 enzymes, CYP2D6 and CYP3A4.
9-Hydroxyrisperidone is the major metabolite of risperidone in plasma. 9-Hydroxyrisperidone has pharmacological activity as well as risperidone (Yasui-Furukori N. etal., 2001).
†

Received 30 July 2015; Accepted 26 April 2017
J-STAGE Advance published online 24 June 20171
3-8, Akagawa 1-chome, Asahi-ku, Osaka 535-0005, Japan2
19-1 Motoyamakita-machi 4-chome, Higashinada-ku, Kobe
658-8558, Japan* Corresponding author: Yuki Fujisawa
E-mail: y.fujisawa@sawai.co.jp
TEL: +81-6-6926-2650 FAX: +81-6-6922-5952

Risperidone is formulated as tablets, orally disintegrating (OD) tablets, fine granules, oral solutions (Berus P. etal., 2005), and intramuscular injections. It is practicallyinsoluble in water, freely soluble in methylene chloride,and sparingly soluble in ethanol. It dissolves in dilute acidsolutions (Merck Index, 14th ed., 2006).
This active pharmaceutical ingredient (API) is hydrolyzed into the R2 form in the presence of water, and isalso oxidized into the R5 form during preservation(Tomar R.S. et al., 2004; Bharathi Ch. et al., 2008). R5 is
an N-oxide product of risperidone and one of the majordegraded substances that is generated by photoirradiation.
The chemical structures of risperidone, R2, and R5 areshown in Fig. 1.
OD tablets are a new type of solid dosage form that areeasily dispersed or dissolved in the oral cavity and areswallowed without water. The compliance and acceptability of patients are improved by OD tablets (Rahman Z. etal., 2010). The EP (European pharmacopoeia) describes
OD tablets as uncoated tablets intended to be placed in
the mouth where they disperse rapidly before being swallowed and as tablets which should disintegrate within
3 min. FDA defines OD tablet as a solid dosage form
which contains a medicinal substance or active ingredient
which disintegrates rapidly within a matter of seconds
when placed upon a tongue (Bhatu P.B. et al., 2011).
In the case of tablets that are unstable to light, film
coating technology may be performed to improve the sta-

Copyright © 2018 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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Yuki Fujisawa et al. / KONA Powder and Particle Journal No. 35 (2018) 209–215

Table 1 Formulation of risperidone OD tablets.
IngredientFig. 1

Structural formulas of risperidone, R2, and R5.

bility. For example, titanium oxide, which is often formulated in the film has light shielding properties. However,film coating technology is not applicable to OD tablets
because the film does not dissolve promptly with saliva.
Also, the surface of the OD tablet is often brittle, the surface may collapse during film coating.
To develop the optimal formulation for risperidone OD
tablets, the effects of excipients on the stability of risperidone were investigated.
When the risperidone OD tablets were previously formulated, the stability of risperidone against heat and photoirradiation was improved by adding carmellose (CMC)(Iwakura Y. et al., JP Patent, P2013-60392A).
It is well established that photochemical reactions of
API are often affected by the excipients. Testing of thephotostability of a drug substance and of the final dosage
form is important to ensure the life span of the product(Tønnesen H.H., 2001).
The purpose of this study is to evaluate the stabilization mechanism of risperidone and other additives inrisperidone OD tablets against photoirradiation.

2. Materials and methods
2.1 Formulation and manufacturing methods ofrisperidone orally disintegrating tablets
The formulation of risperidone OD tablets is shown in
Table 1.
Risperidone was obtained from Assia Chemical Indus-

210

Weight(mg/tab)1

Risperidone

0.5

2

D-Mannitol

q.s.

3

Corn Starch

3.0

4

Anhydrous Dibasic Calcium Phosphate

10.0

5

Carmellose (CMC)

5.0

6Carmellose Calcium (CMC-Ca)

5.0

7

Hydroxypropylcellulose (HPC)

0.5

8Light Anhydrous Silicic Acid

0.75

9

Magnesium Stearate

0.5

10

Aspartame

2.0

11

Flavor

0.15

Total

50.0

tries Ltd. (Israel) for JP grade. Aspartame was JPE grade.
Other materials were JP grade.
HPC was obtained for L grade of NISSO HPC (Nippon-­Soda, Japan).
The OD tables were prepared by three different manufacturing methods as follows.
Method A: From No. 1 to No. 6 in Table 1 were mixed
in a fluidized bed granulator and then granulated by 1 %(w/w) HPC aqueous solution. The granules were sieved
using a 710 μm screen and excipients from No. 8 to No.
11 were mixed. The mixture was compressed using a tablet press.
Method B: From No. 1 to No. 7 in Table 1 were mixed
in a fluidized bed granulator and then granulated using
purified water. The granules were sieved using a 710 μm
screen and excipients from No. 8 to No. 11 were mixed.
The mixture was compressed using a tablet press.
Method C: From No. 1 to No. 6 in Table 1 were mixed
in a fluidized bed granulator and then granulated by purified water. Additionally, 1 % (w/w) HPC aqueous solution
was sprayed for granulation. The granule was sieved using a 710 μm screen and excipients from No. 8 to No. 11
were mixed. The mixture was compressed using a tablet
press.
Fluidized bed granulator: Multiplex Coater (MP-01,
Powrex, Japan). Tablet press: PICCOLA (RIVA S.A., Argentina).

2.2 Irradiation test of risperidone OD tablets
Sample tablets of methods A, B, and C were stored in alight-irradiation tester with a D65 lamp (LT-120, Nagano
Science, Japan), as previously demonstrated (Teraoka R.

Yuki Fujisawa et al. / KONA Powder and Particle Journal No. 35 (2018) 209–215

et al., 2001).
Irradiation was carried at 1000 lx for 25 days. The temperature in the light-irradiation tester was kept at 298 K.

Table 2 Preparation of sample powders.
Samplea)2.3 High-performance liquid chromatography(HPLC)
The analysis of risperidone and its degradation forms
by an HPLC system in tablets has been reported (Suthar
A.P. et al., 2009). The R5 formation rate was analyzed
with an HPLC system (Prominence UFLC, Shimadzu,
Japan) equipped with a UV detector (SPD-20AV, Shimadzu, Japan) operated at 275 nm. The packaged column
was a reverse-phase C18 column (Zorbax SB-C18, 3.5 μm,
3.0×150 mm, Agilent, USA) operated at 298 K. The flowrate was kept at 1.1 mL/min. The mobile phase consistedof purified water:acetonitrile:trifluoroacetic acid (1600:
400:3) and the pH value was adjusted to 3.0 by adding NH3
solution. After photoirradiation, 5 risperidone OD tablets
were added into 25 mL of 0.1 mol/L hydrochloric acid/methanol mixture (3:2). After shaking, this solution
was filtered using a polyolefin disposable syringe filter(Chromatdisk 25A, 0.45 μm, GL Science, Japan). A totalof 10 μL of sample solution was subjected to HPLC analysis.

2.4 Colorimetric measurement
The color of a sample tablet was measured with a chromameter (Spectrophotometer SE6000, Nippon Denshoku,
Japan) with the L*a*b* colorimetric system.
The average of 5 tablet measurements of ΔE*, before
and after photoirradiation in the 3-dimensional L*a*b*
color space, was calculated as follows.
ΔE* = [(ΔL*)2 + (Δa*)2 + (Δb*)2]1/2
ΔL*: the lightness differenceΔa*: the red/green differenceΔb*: the yellow/blue difference

2.5 Preparation of sample powders

UV-VIS solid-state absorption spectra of samples froma) to d) were measured on a UV-2450 system (Shimadzu,
Japan) equipped with an integrating sphere unit (Shimadzu ISR-2200) at room temperature. A cell was filledwith sample powder and the spectra were acquired with
0.2 nm sampling pitch in the wavelength range from 300
to 400 nm.

RIS/CMC 7.5 g of risperidone and 7.5 g of CMC were(powder) mixed using a pestle in a mortar for 2 min.

7.5 g of risperidone and 7.5 g of CMC weremixed and granulated in a mortar with 3 mL
RIS/CMC of purified water. The granules were dried atb)(pellet) 343 K for 2 h by a hot air circulation-type
constant-temperature oven (MO-921, Toyama
Sangyo, Japan).
c)

RIS/HPC 7.5 g of risperidone and 7.5 g of HPC were(powder) mixed using a pestle in a mortar for 2 min.

d)

7.5 g of risperidone and 7.5 g of HPC weremixed and granulated in a mortar with 3 mL
RIS/HPC of purified water. The granules were dried at(pellet) 343 K for 2 h by a hot air circulation-type
constant-temperature oven (MO-921, Toyama
Sangyo, Japan).

Table 3 Formulation of different amounts of CMC in risperidone OD tablets.
Ingredient

Weight (mg/tab)(Amount of CMC)

0

2.5

5.0

1

Risperidone

0.5

0.5

0.5

2

D-Mannitol

q.s.

q.s.

q.s.

3

Corn Starch

3.0

3.0

3.0

4

Anhydrous Dibasic
Calcium Phosphate

10.0

10.0

10.0

5

CMC

0

2.5

5.0

6

CMC-Ca

5.0

5.0

5.0

7

HPC

0.5

0.5

0.5

8

Light Anhydrous
Silicic Acid

0.75

0.75

0.75

9

Magnesium Stearate

0.5

0.5

0.5

10

Aspartame

2.0

2.0

2.0

11

Flavor

0.15

0.15

0.15

Total

50.0

50.0

50.0

The sample powders of risperidone and other additives
were prepared as described in Table 2.

2.6 Solid-state UV-VIS spectra

Preparation Method

2.7 Solid-state NMR
13

C CP/MAS NMR spectra of samples a)~d) were measured on a Varian NMR System 500 with a zirconia sample tube (outer diameter: 5 mm, scanning speed: 20 kHz).
2.8 Formulation of sample tablets to examine the effectof CMC amount on stability
To examine the effect of CMC in tablets on photostability, three different amounts of CMC in tablets wereprepared, as shown in Table 3. All formulations were
manufactured by method C described in 2.1. Sample tab-211

Yuki Fujisawa et al. / KONA Powder and Particle Journal No. 35 (2018) 209–215

lets were stored at 1000 lx for 14 days and R5 was measured by HPLC.

2.9 Formulation of sample solutions to examine
the effect of pH on stability
A total of 1 mL of 0.5 mg/mL risperidone in methanol
was mixed with 2 mL of 1 % (w/w) HPC buffer solution
with various pHs (1.2, 3.0, 4.0, 5.0, 6.8). Sample solution
was injected in a quartz cell and stored in a light-irradiation
tester with a D65 lamp (3500 lx) for 14 days. The R5 formation rate was analyzed by HPLC. Each pH of buffer
solution is shown as follows.
pH 1.2: 1st fluid for dissolution test (JP)pH 3.0: Dilute McIlvaine buffer solution, pH 3.0
pH 4.0: Dilute McIlvaine buffer solution, pH 4.0
pH 5.0: Dilute McIlvaine buffer solution, pH 5.0
pH 6.8: 2nd fluid for dissolution test (JP)2.10 Formulation of sample solutions to examine
the effect of HPC concentration
A total of 1 mL of 0.5 mg/mL risperidone in methanol
was mixed with 2 mL of each concentration (0 %, 0.01 %,0.1 %, 1 %) of HPC buffer solution at pH 6.8. Sample
solution was injected in a quartz cell and stored in alight-irradiation tester with a D65 lamp (3500 lx) for 14
days. The R5 generation rate was analyzed by HPLC.

3. Results and discussion
3.1 Photostability of risperidone OD tablets bydifferent manufacturing methods
Tablets produced by methods A, B, and C were subjected to accelerated stability testing at 1000 lx for 25days using a D65 lamp. The R5 formation rate was measured by HPLC and color differences were measured using a chromameter.
The results of photostability testing are shown in
Table 4. Comparing these three manufacturing methods
in terms of stability, method A was most unstable andmethod C was most stable. Similarly, the most color

change was observed in method A. The color difference
in method C was very limited.
It was considered that method C is the most stable manufacturing method among these three methods.

3.2 Measurement of solid-state UV-VIS spectraand solid-state NMR
There was a possibility that the change of photostability
was due to a shift of the absorption wavelength (Kojima T.
et al., 2007). Spectrum from 300 nm to 400 nm in a solidstate was measured and the relative absorbance spectrum
was plotted with the absorbance of 300 nm set as 1.0.
Sample d) was not measured because rubber-like pellets were obtained and these pellets were not suitable forthe measurement because they were not solidified by thepress.
As shown in Fig. 2, a shift of spectrum was not observed in any sample. Therefore, there was no change in
the absorption wavelength.
Solid-state NMR has developed as an important technique for the characterization of pharmaceutical solids aswell as DSC, FT-IR, and PXRD. Physicochemical information about both API and the formulated product wasprovided by the measurement (Berendt R.T. et al., 2006).
It has been reported that risperidone has three polymorphs (Karabas I. et al., 2007; Krochmal B. et al., 2004).
There was a possibility that the crystal form of risperidone was changed and a difference in the stability wasobserved. Measurements of samples a)~d) and risperidone
were performed using solid-state NMR to determine
whether the crystal form had changed or not and theirspectra were compared. As shown in Fig. 3, changes inthe spectra were not observed and it was suggested that
there were no changes in the crystal forms.

Table 4 R5 formation rate and color difference of risperidone
OD tablets after photoirradiation.

212

MethodR5 formation(%)

Color difference
(ΔE*)

A

2.7

1.74

B

1.1

0.76

C

0.5

0.40

Fig. 2

Solid-state UV-VIS spectra of risperidone and samplesa)~c).

Yuki Fujisawa et al. / KONA Powder and Particle Journal No. 35 (2018) 209–215

Fig. 3

Solid-state NMR spectra of risperidone and samplesa)~d).

3.3 Effect of CMC in tablets on the photostability
CMC is widely used as a relatively acidic disintegrant.
A total of 1.0 g of CMC was dispersed in 100 mL of purified water and the suspension showed about pH 3.5 to 5.0(European Pharmacopoeia 8th Edition, 2014).
To examine the effect of CMC on the photostability,
three different amounts of CMC (0, 2.5, 5 mg) in OD tablets were formulated and stored at 1000 lx for 25 days.
The pH of the tablet was also measured by dispersing thetablet in 20 mL of purified water for 20 min.
As the amount of CMC in the tablet increased, the pH
value was lowered.
As shown in Table 5, No R5 was detected in any sample before photoirradiation by HPLC analysis. After photoirradiation, R5 was detected and its amount varied in a
CMC-dependent manner.

Fig. 4R5 formation rate in different pH solutions (HPC concentration: 1 %).

Table 5 R5 formation rate at different amounts of CMC in OD
tablets.
CMC(mg/tab)pH0

R5 formation rate (%)
Initial1000 lx
25 days

7.6

N.D.

4.14

2.5

6.0

N.D.

1.31

5.0

5.1

N.D.

0.87

Table 6 R5 formation rate at different pH solutions (HPC
concentration: 1 %).
pH

R5 formation rate (%)
Initial

3500 lx 14 daysLightshieldingExposure
to light

3.4 R5 formation rate in different pH solutions

1.2

N.D.

N.D.

N.D.

3.0

N.D.

N.D.

0.02

The R5 formation rate of risperidone/HPC solution at
different pHs was investigated. The results of photostability testing are shown in Table 6 and Fig. 4. In lightshielding conditions, all samples were stable. When samples were exposed to light, R5 was generated at high-pH
conditions. It is considered that the photostability ofrisperidone was affected by the pH of the solution.

4.0

N.D.

N.D.

0.13

5.0

N.D.

N.D.

0.63

6.8

N.D.

N.D.

1.14

3.5 R5 formation rate at different hydroxylpropylcellulose concentrations
To evaluate the effect of HPC on the stability of API,risperidone was dissolved in different concentrations of
HPC aqueous solution. As shown in Table 7, R5 formation was not observed at any sample in light shielding
conditions. On the other hand, R5 formation was increased with increasing HPC concentration when samples
were exposed to light.

Table 7 R5 formation rate at different HPC concentrations(pH 6.8).
HPC (%)

R5 formation rate (%)
Initial

3500 lx 14 daysLightshieldingExposure
to light

0

N.D.

N.D.

N.D.

0.01

N.D.

N.D.

0.07

0.1

N.D.

N.D.

0.15

1

N.D.

N.D.

0.86

213

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4. Conclusions

References

By the difference of manufacturing method, the photostability of risperidone in OD tablets was changed.
The photostability was significantly improved by adding purified water before granulation. These differencesin stability suggested that risperidone and HPC reacted
upon photoirradiation and formed degradation substances.
From the analysis of solid-state UV-VIS spectrum andsolid-state NMR, no physical change was observed.
At low pH, risperidone in HPC solution was stable
upon photoirradiation. On the other hand, risperidone in
HPC solution was stable at any pH under light shielding
conditions. It is suggested that this photo-reaction is suppressed at low pH because risperidone has mono- anddi-protonated forms (pK1 = 8.1–8.6, pK 2 = 3.1) (Alparone
A., 2011).
The photostability of risperidone in HPC solution depended on the concentration of HPC.
To improve the photostability of risperidone OD tablets, it is important to use acidic excipients and a small
amount of HPC.

Alparone A., Spectroscopic properties of neuroleptics: IR and
Raman spectra of Risperidone (Risperdal) and of its monoand di-protonated forms, Spectrochimica Acta Part A:
Molecular and Biomolecular Spectroscopy, 81 (2011) 631–
639.
Berendt R.T., Sperger D.M., Isbester P.K., Munson E.J., Solid-­state NMR spectroscopy in pharmaceutical research andanalysis, TrAC Trends in Analytical Chemistry, 25 (2006)
977–984.
Berus P., Gartner A., Mlakar A., Puncuh K.A., Vrecer F., Preparation of a stable oral solution with risperidone, European
Journal of Pharmaceutical Sciences, 25S1 (2005) S57–S58.
Bharathi Ch., Chary D.K., Kumar M.S., Shankar R., Handa
V.K., Dandala R., Naidu A., Identification, isolation andcharacterization of potential degradation product in risperidone tablets, Journal of Pharmaceutical and Biomedical
Analysis, 46 (2008) 165–169.
Bhatu P.B., Atish S.M, The technologies used for developing
orally disintegrating tablets: A review, Acta Pharmaceutica,
61 (2011) 117–139.
European Pharmacopoeia 8th Edition, Carmellose, Carmellose
calcium, The European Directorate for the Quality of Medicines & HealthCare, 2014, pp. 1773–1774.
Germann D., Kurylo N., Han F., Risperidone, Chapter 8 in:
Brittain H. (Eds.), Risperidone, Profiles of drug substances,
excipients, and related methodology, Academic Press, 37,
2012, pp. 313–361.
Grant S., Fitton A., Risperidone: A Review of its pharmacology
and therapeutic potential in the treatment of schizophrenia,
drugs, 48 (1994) 253–273.
Iwakura Y., Fujisawa Y., Toyonaga N., Oral disintegrant tablet
containing risperidone and method for producing the same,
JP Patent, (2013) JP2013060392A.
Janssen P.A.J., The development of new antipsychotic drugs:
Towards a new strategy in the management of chronic psychoses, Journal for Drugtherapy and Research, 12 (1987)
324–328
Janssen P.A.J., Niemegeers C.J.E., Awouters F., Schellekens
K.H.L., Megens A.A.H.P. and Meert T.F., Pharmacology ofrisperidone (R 64 766), a new antipsychotic with serotoninS2 and dopamine-D2 antagonistic properties, Journal ofpharmacology and experimental therapeutics, 244-2 (1988)
685–693.
Karabas I., Orkoula M.G., Kontoyannis C.G., Analysis and stability of polymorphs in tablets: The case of Risperidone,
Talanta, 71 (2007) 1382–1386.
Kojima T., Onoue S., Katoh F., Teraoka R., Matsuda Y.,
Kitagawa S., Tsuhako M., Effect of spectroscopic properties of tamoxifen citrate polymorphs, International Journalof Pharmaceutics, 336 (2007) 346–351.
Krochmal B., Diller D., Dolitzky B., Aronhime J., Preparationof risperidone, US Patent (2004) US6,750,341B2.
Leysen J.E., Gommeren W., Eens A., de Chaffoy de Courcelles
D., Stoof J.C., Janssen P.A., Biochemical profile of risperidone, a new antipsychotic, The Journal of Pharmacology
and Experimental Therapeutics, 247 (1988) 661–670.
Merck Index, 14th ed., Merck Research Laboratories, division of
Merck & Co., Whitehouse Station, N.J., , 2006, entry 8316,
1478.
Rahman Z., Zidan A.S., Khan M.A., Risperidone solid dispersion for orally disintegrating tablet: Its formulation design
and non-destructive methods of evaluation, International
Journal of Pharmaceutics, 400 (2010) 49–58.
Suthar A.P., Dubey S.A., Patel S.R., Shah A.M., Determination

NomenclatureAPI

active pharmaceutical ingredient

CMC

carmellose (carboxymethylcellulose)

CMC-Cacarmellose calcium

DSC

differential scanning calorimetry

EP

European pharmacopoeia

FDA

Food and drug administration

FT-IR

Fourier transform infrared spectroscopy

h

hour

HPC

hydroxypropylcellulose

JP

Japanese pharmacopoeia

lx

lux

min

minuteN.D.

not detected

NMR

nuclear magnetic resonance

OD

orally disintegrating

PXRD

powder X-ray diffraction

q.s.

quantum sufficiat

tabtabletw

weight214

Yuki Fujisawa et al. / KONA Powder and Particle Journal No. 35 (2018) 209–215

of Risperidone and forced degradation behaviour by HPLC
in tablet dosage form, International Journal of PharmTech
Research, 1 (2009) 568–574.
Teraoka R., Konishi Y., Matsuda Y., Photochemical and oxidative degradation of the solid-state tretinoin tocoferil, Chemical & pharmaceutical bulletin, 49 (2001) 368–372.
Tomar R.S., Joseph T.J., Murthy A.S.R., Yadav D.V., SubbaiahG., Krishna Reddy K.V.S.R., Identification and characterization of major degradation products of risperidone in bulk
drug and pharmaceutical dosage forms, Journal of Pharma-

ceutical and Biomedical Analysis, 36 (2004) 231–235.
Tønnesen H.H., Formulation and stability testing of photolabile
drugs, International Journal of Pharmaceutics, 225 (2001)
1–14.
Yasui-Furukori N., Hidestrand M., Spina E., Facciolá G., Scordo
M.G., Tybring G., Different enantioselective 9-hydroxylation of risperidone by the two human CYP2D6 andCYP3A4 enzymes, Drug Metabolism and Disposition, 29(2001) 1263–1268.

Author’s short biography
Yuki Fujisawa
Yuki Fujisawa graduated from Nagoya City University in 2002 and the Graduate
School of the same university in 2004. He received a degree in organic and medicinal
chemistry from the Graduate School. He has worked for Sawai Pharmaceutical Co., Ltd.,
since 2007. He is responsible for formulation development and scale-up study as a pharmaceutical researcher.

Yoshiteru Takahashi
Yoshiteru Takahashi is an executive corporate officer of Sawai Pharmaceutical Co.,
Ltd. He received BS degree (1975), Master degree (1977) and Ph.D. (1985) in pharmaceutical science from Kyoto University. He joined Sawai Pharmaceutical Co., Ltd. in
2003. His research interests include formulation development, scaling-up and improvement of the manufacturing technologies in a manner that allows for production on themarket and enables registration.

Reiko Teraoka
Reiko Teraoka, Ph.D. is currently associate professor of laboratory of pharmaceuticaltechnology in Kobe Pharmaceutical University.
Her research interests focus on:• Stability evaluation and stabilization design of pharmaceutical drugs
Photostability of solid pharmaceutical drugs and cocrystals in particular• Proper use of transdermal fentanyl for palliative care and anti-AIDS agent

Shuji Kitagawa
Shuji Kitagawa is a Professor in Department of Pharmaceutical Technology at Kobe
Pharmaceutical University. Since April, 2013 he has also been a President of the same
university. He holds a Ph.D. degree from Kyoto University in 1981. His research interests
include percutaneous permeation of polyphenols and rheological study on ointments andcreams. He has published more than 100 research papers during his research career.

215

KONA Powder and Particle Journal No. 35 (2018) 216–225/Doi:10.14356/kona.2018009

Original Research Paper

Simulation of Mechanical Degradation of Iron
Ore Pellets in a Direct Reduction Furnace †Fernando O. Boechat*, Rodrigo M. de Carvalho and Luís Marcelo Tavares
1

Department of Metallurgical and Materials Engineering, Universidade Federal do Rio de Janeiro – COPPE/UFRJ, Brazil

Abstract
The increase in production of steel in electric arc furnaces in recent years influenced directly the world productionof direct reduction iron (DRI). Amongst the most widely used technologies for DRI production is the MIDREX®
process. The behavior of the metallic charge used in these furnaces, mainly made up of iron ore pellets, influences
directly their productivity. Fines contained in the feed are typically removed by screening, in order to prevent
them from impacting negatively the productivity of the furnace. However, fines still may be generated inside thefurnace as a result of the collisions amongst pellets and between them and internals of the furnace as they move
downwards from the feed to the discharge of the shaft furnace. Predicting and preventing such mechanicaldegradation is critical in the furnace operation. The present work deals with the prediction of degradation of ironore pellets during reduction in a MIDREX furnace. Collision energies involved in the vertical flow of pellets
along a MINIMOD® MIDREX direct reduction furnace were estimated using the discrete element method. Using
this technique along with a model of degradation that considered assumptions based on information from theliterature it was possible to estimate the proportion of fines generated inside the reactor, which was consistent
with plant practice. Finally, it was predicted that the generation of fines in the reduction zone of the furnace would
vary from 3.4 % to 4.6 % as the throughput of the furnace increased in 50 %.
Keywords: discrete element method, simulation, iron ore pellets, direct reduction, degradation

1. Introduction
Because of the reduced supply of good quality lumpiron ore in the world market and the growing environmental constraints to sintering, iron ore pellets began tooccupy an important role as raw material for primary ironproduction. Their participation in the production of pig
iron and direct reduction iron (DRI) has increased year
after year due to their advantages in comparison to lumpore. Some of the advantages are their higher uniformity insize, greater control of chemical composition, besides
their reduced amenability to mechanical degradation
during handling and under reduction.
The increase in production of steel using electric arc
furnace impacted directly the production of DRI, raising
it from 40 Mt in the beginning of this century to 74 Mt in2014 (MIDREX, 2015). Several processes are used in the
production of sponge iron, however the most widely usedis the MIDREX (Midland Ross Experimental) process,†1*

Received 7 October 2016; Accepted 25 April 2017
J-STAGE Advance published online 24 June 2017
Cx. Postal 68505, CEP 21941-972, Rio de Janeiro, Brazil
Corresponding author: Fernando O. Boechat
E-mail: fboechat@globo.com
TEL: +55-21-2290-1544 Ext. 246

216

which responds for more than half of the world’s DRI production (MIDREX, 2014). In this process lump ore and/or
iron ore pellets as used to compose the metallic charge,
with iron ore pellets contributing to improve operational
stability and increase productivity and/or metallization of
charge, making this raw material the most attractive
charge for producers of sponge iron in MIDREX furnaces(MIDREX, 2014).
In spite of their greater resistance to degradation, ironore pellets still suffer from this problem, although to amore limited extent when compared to lump ore. Suchdegradation can take place either during handling fromthe pellet producer until loading the furnace, or under reduction, generating either coarse fragments or fines. Fines
that are generated by handling prior to loading the furnace can be removed by screening. However, mechanicaldegradation can also occur inside the direct reduction
furnace, as the result of the combined effect of weakeningof the pellet structure due to reduction (Huang et al.,2012) and to the stresses which pellets withstand until
they are discharged at the bottom of the furnace. Whensuch mechanical degradation occurs inside the furnace,either coarse pellet pieces or fines may be produced. Indeed, such fines have been estimated to represent between
2 and 4 % in weight of the product, based on measurements

Copyright © 2018 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/).

Fernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

in plants that screen the furnace discharge (MIDREX,
2011). Such fragments can cause loss of furnace productivity because they affect negatively the permeability ofthe pellet bed, thus resulting in lower metallization of thecharge. In addition to that, these fines can contribute to
the pellets sticking to each other resulting in the formation of clusters, which besides contributing negatively tothe permeation of reduction gasses, also create a disturbance in the flow of the charge (Wong et al., 1999; Basdag
and Arol, 2002). Therefore, prediction of the amount offines that are generated inside the reactor owing to the useof a particular type of iron ore pellet would be useful.
This information could be used to assist in selecting the
optimal feed blend to the direct reduction reactor, besides
enabling the choice of the operational parameters that can
reduce the impact of the formation of fines. However, no
study in the published literature has been found that addressed simulating such mechanical degradation of ironore pellets in direct reduction furnaces.
The present work uses a combination of the discrete element method (DEM) (Weerasekara et al., 2013) andmodels that describe pellet breakage and attrition to predict iron ore pellet degradation and fines generation in a
vertical shaft direct reduction furnace in a one-way coupling strategy.

2. DEM simulation approach
The overview of the simulated direct reduction furnace

Fig. 1is presented in Fig. 1. The furnace consists of a feeding
system, containing 16 conduits (called legs), a first section, named reduction zone, on the bottom of which thereformed gases are introduced. The charge then travels
downwards and encounters the upper burden feeders,which are axles that are meant to oscillate at predetermined angles at a speed that is adjusted to promote uniform transverse movement of the load and to limit thesize of clusters formed. The identification of the sections
and the corresponding numbers of pellets involved in thesimulations can also be found in Fig. 1. The charge thenencounters the region where the cooling gases are injected, to then find the sets of middle and lower burden
feeders, until it is discharged from the bottom of the furnace.
The furnace simulated is designated MINIMOD®, andit has the smallest production capacity among the industrial furnaces that use the MIDREX technology (Atsushi,
2010). With 4.25 m in diameter, it can produce about halfa million tons of sponge iron per year. The selection ofthis scale in the present work was due to challenges associated to the number of pellets that are present in this furnace at any time, which is in the order of several millions,which is only a fraction of the billions that occupy the
2-million ton-per-year Super Megamod® furnace measuring 7.15 m in diameter (Atsushi, 2010).
In spite of being the smallest industrial scale furnace, theMINIMOD® still contains an exceedingly large numberof particles for a computationally cost-effective simulation using DEM. In order to reduce the number of parti-

Overview of the MINIMOD® MIDREX shaft furnace (left) and view of the simulated sections (middle
and right). The number of particles corresponded to the 25 mm spheres simulated in each section.

217

Fernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

cles within the simulation, the furnace was first split from
top to bottom into four sections for simulation in separate,
which were numbered 1 to 4 (Fig. 1). In order to further
reduce the number of particles, only a fraction of the volume, with periodic boundaries, was simulated in sections#1 to #3. The region around the lower burden feeders (#4),
on the other hand, was simulated with the full particle
population.
Still with the aim of reducing the computation effort in
the simulations pellets were assumed to present sphericalgeometry, which is a reasonable assumption in the case ofiron ore pellets. In addition to that, pellets with nearly
twice the average diameter of the actual pellets usuallyused industrially (9–19 mm), that is, 25 mm, were simulated. In spite of their uniform shape and size, no crystallization structures were identified in simulating thedifferent sections of the furnace.
The software used in the DEM simulations was
EDEM® by DEM Solutions (Edinburgh, UK), version 2.7.
In all simulations the Hertz-Mindlin contact model available in EDEM® was adopted, and only gravity was considered as external force. The material parameters used in
the simulations were those estimated on the basis of detailed testing by Barrios et al. (2013) with unreduced fired
iron ore pellets. It is assumed that the contact properties
would not change as pellets undergo reduction in the furnace. These and other material properties (density andshear modulus) are summarized in Table 1.
The speed of descent of metallic charge for each section was determined based on the simulated reactor withproduction of 58 t/h, which would correspond to an annual production in the order of half of a million tons. In
addition to that, simulations were also conducted considering an increase in 50 and 100 % in the throughput of thesystem, resulting in simulated production of 86.8 and116 t/h. These scenarios would correspond to cases when
the residence time of the pellets in the furnace would be
reduced significantly. The three systems of burden feeders
were inserted in the model and the dimensions and modesof operation of these parts that turn were programmed on
the basis of the parameters listed in Table 2.
For instance, the computational effort was such that inorder to simulate 25 seconds of operation of the charge insection #1, approximately 240 hours of processing in astate-of-the-art workstation were required. Indeed, simulations were conducted until steady-state conditions werereached. Upon completion of the simulations, data fromeach collision, discriminated between the normal and thetangential component, were collected and processed using
a post-processing routine developed in the authors’ laboratory (Carvalho, 2013). Energies in the collisions werefirst equally split between each pair of pellets involved
and then divided by the simulated particle weight, resulting in the specific collision energy. Fig. 2 shows that the218

Table 1 Hertz-Mindlin contact and material parameters ofiron ore pellets (Barrios et al., 2013).
Steel

Pellet

0.3

0.25

7000

16

7800

3948

Steel-pellet

Pellet-pellet

Coefficient of restitution

0.48

0.39

Coefficient of static friction

0.49

0.50

Coefficient of rolling friction

0.21

0.25

Poisson’s ratio
Shear modulus (MPa)3

Density (kg/m )Table 2 Operating parameters used for the burden feeders.
PositionAngle ofrotation (°)

Period ofrotation (s)Frequency(rad/s)

Upper

45

180

0.0044

Middle90300.0524

Lower

60

10

0.1047

Position

Shaft radius(m)

Burdenfeeders
radius (m)

Upper

0.228

0.487

Middle

0.080

0.175

Lower

0.069

0.160

Fig. 2

Cumulative distribution of specific energy dissipationin the lower burden feeder section from simulations
considering pellets of different diameters (12.5 and25.0 mm).

magnitudes of the specific collision energies are very
similar for the 25 mm pellets simulated throughout thework and the 12.5 mm here analyzed in the lower burden
feeder region of the furnace, thus demonstrating the validity of considering the larger pellet sizes in the remainder of the simulations.

Fernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

Fig. 3

Simulation of the reduction zone (section #1), showing detail in the bottom layer of the column with theprofile of the compressive forces.

Fig. 4

Simulation showing the compression forces in section #2, influenced by the presence of the upper burden
feeder.

3. DEM simulation results
From the DEM simulations it was possible to analyze
the profile of the compressive forces in the sections studied. Fig. 3 shows the influence of the depth in the pellet
column inside the reduction zone (section #1) on the magnitude of compressive forces. In the following section(#2), shown in Fig. 4, the force applied was transferredfrom the previous section in order to allow simulating theentire column of pellets to which that section was subjected. In the figure it is observed that the magnitudes ofthe forces are similar to those presented on the basis of
the column of reduction zone and the burden feeders work
as a support to the column of pellets, withdrawing fromthe regions beneath it the effect of load from the columnof pellets above. In sections #3 and #4, on the other hand,
this method was not used, given the ability of the burden
feeders of supporting the charge, reducing the magnitudeof the contact forces (Fig. 5).
The energy dissipations in the collisions were analyzed
in each section, with the larger frequency of higher energy collisions found closer to the bottom of the reduction
column (Fig. 3), showing that there is a relative effect of
depth of the pellets column. This effect becomes evident
in Fig. 6, where the variation of the average normal energy dissipated in the collisions as a function of heightand radius of furnace becomes evident.
A summary of the energy dissipation spectra in the dif-219

Fernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

Fig. 5

Simulation showing the compressive forces in section#4 influenced by the presence of the lower burden
feeder.

Fig. 6

Normal average energy transferred to particles as afunction of normalized depth (0: bottom of reduction
zone; 1: top) and radius of the section #1 of the reactor.

Table 3 Summary of the total energy dissipation distributions (in J/kg) of collisions by furnace section for a throughput
of 58 t/h.
Furnace section
Statistic (J/kg)#1—Reduction
Zone#2—UpperBurdenfeeder#3—Middle
Burdenfeeder#4—Lower
Burdenfeeder

Mean

0.214

0.00130.00180.0023

Median0.0035

6.82E-05

1.85E-04

2.99E-04

95th percentile

0.294

0.00420.089

0.0103Standard deviation

2.032

0.00940.00590.0093

ferent sections of the furnace is presented in Table 3 forcomparison. It becomes evident that the highest energy
dissipation occurs in the reduction zone (section #1),
whereas the sections around the burden feeders (sections#2–4) exhibit very low energy dissipations (Fig. 7).
An approach often used to increase the productivity indirect reduction furnaces is to increase the flow of reforming gases coupled to the throughput of the furnace.
However, an adverse effect of this is the increase in the
degradation of the pellets inside the furnace (MIDREX,
2011). Table 4 compares predictions of the collision energy spectrum of the base case to two hypothetical cases inwhich the throughput was raised, showing that important
increases in the average collision energies would result.

4. Modeling of pellet breakage
Depending on the magnitude of the collisions that happen amongst the pellets and between the pellets and thewalls and furnace internals as the charge moves downwards from the feed to the discharge, breakage of pellets

220

may occur. Breakage of pellets can occur catastrophically,
which is called body breakage, every time a pellet loses
more than 10 % of its original weight in any event (Tavares
et al., 2015). On the other hand, pellets may suffer only
surface breakage or attrition, also called breakage byabrasion or chipping, which results in generation of fines,
besides leaving the core of the original pellet nearly undisturbed, since it contains no less than 90 % of the massof the original pellet prior to the collision event. In thislater case, it is possible that the pellet becomes moreamenable to breakage in a future stressing event. A model
framework that has been developed to describe this in thecontext of degradation of ores during handling is described elsewhere (Tavares and Carvalho, 2011) and elements of it are here used to predict breakage in the
MINIMOD MIDREX furnace.
The threshold between these two modes of breakage
efined above is given by the mass-specific particle fracture energy of the pellets (Tavares et al., 2015). Fig. 8
presents the distributions of specific fracture energies for
fired pellets contained in different size classes under slow
compression conditions. A comparison between these andFernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

Fig. 7

Cumulative distribution of total energy dissipated in the four sections of the furnace simulated. Also
shown for comparison are the fracture energy distributions of unreduced and estimated values after
complete reduction.

Fig. 9Fig. 8Distribution of specific fracture energies of fired ironore pellets.

Table 4 Summary of the energy dissipation spectra (in J/kg)
of collisions for section #1 of the furnace as a function of throughput.
Estimated throughput

Statistic(J/kg)

58 t/h87 t/h116 t/h

Mean

0.214

0.238

0.251

Median0.00350.00390.003895th percentile

0.294

0.318

0.321

Std. dev.

2.032

2.536

2.539

the distributions presented in Fig. 7 suggests that no pellets would suffer catastrophic breakage inside the furnace,since the energy required to break the weakest fired pellet
is higher than the collision energy of highest magnitude

Effect of degree of reduction on the compressive
strength and surface hardness of iron ore pellets (datafrom Huang et al., 2012). Copyright: (2012) Powder
Technology.

inside the furnace. However, as pellets move downwards
in the furnace, they undergo reduction, having theirstrength reduced. Work by Huang et al. (2012) demonstrated that the compressive strength—and therefore thefracture energy—of iron ore pellets drops significantly as
reduction occurs (Fig. 9). As such, considering such estimate that particles loose in the order of 75 % of theircompressive strength upon reduction (Huang et al., 2012)
and assuming that the mass-specific fracture energies
would be reduced in the same magnitude, it would be
more likely that breakage of pellets might occur in the reduction section of the furnace (section #1). However, evenconsidering that reduced pellets would further lose theirfracture energies upon undergoing repeated stresses in
the furnace, this effect may be considered negligible under the conditions simulated (Fig. 7).
It is important to recognize, however, that the presence

221Fernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

Fig. 10 Experimental results and model fit for fines generation
due to attrition of fired pellets as a function of effective collision energy (Cavalcanti, 2015). Model coefficient of correlation (R2) of 0.97. Copyright: (2015)
Universidade Federal do Rio de Janeiro.

of coarse fragments, generated during handling prior tofeeding the furnace, may be responsible for the appearance of lower fracture energies particles than well-formedpellets, which could still undergo body breakage inside
the furnace.
Although unlikely to suffer body breakage, pellets inside the furnace will be subjected to stresses that will certainly be responsible for surface breakage or attrition. A
model that describes the relationship between the stressing energy and the generation of fines as the result of surface breakage is (Cavalcanti, 2015) E k  a
 Eo 

λ(1)

where k is the proportion of fines generated in each collision event, Eo is a reference specific collision energy,
taken as 10 J/kg, and a and λ are dimensionless fitting parameters to be calibrated from experimental data. It is
worth noting that in the case where the constant λ is equal
to 1, this model becomes equivalent to the one proposedby Ghadiri and Zhang (2002). E is the effective mass-­
specific energy in each collision, obtained from a combination of the normal component of the energy dissipatedin the normal direction of the collision added to 57 % of
the contribution from the shear component. This composition of the collision energy was estimated on the basisof impacts of pellets against angled targets (Cavalcanti,2015). Fig. 10 presents data for an unreduced iron orepellet, comparing it to the model fit, resulting in the values of a and λ equal to 0.00029 and 1.16, respectively. The
fitted model parameters, however, are only valid for unreduced pellets. Huang et al. (2012) demonstrated that thehardness of an outer layer of the pellet reduces as pellets
undergo reduction (Fig. 9). Recent work in the authors’laboratory (Cavalcanti, 2015) proposed a relationship between the Vickers hardness of the region close to the surface of unreduced iron ore pellets to their amenability to222

Fig. 11 Relationship between parameter a from Eqn. 1 andVickers hardness in the periphery of unreduced ironore pellets (Cavalcanti, 2015). Copyright: (2015) Universidade Federal do Rio de Janeiro.

Fig. 12 Predicted percentage of fines generated in pellets withdifferent levels of reduction as a function of effective
collision energy.

surface breakage (Fig. 11).
Combining now the results from Huang et al. (2012)
and Fig. 11, it is possible to estimate the change in abrasion response as a function of degree of reduction. This is
illustrated in Fig. 12, which shows predictions on the effect of effective collision energy on the mass loss in a single collision of a pellet inside the furnace with different
levels of reduction.
A comparison of Fig. 7 and Fig. 10 demonstrates thatthe collision energies found in the furnace are still comparatively low, so that significant extrapolation in themodel became necessary.

5. Simulation of pellet degradation in the
MINIMOD furnace
Degradation in the furnace, assuming stresses are insufficient to cause body breakage, only surface breakage(attrition), can then be predicted considering that pellets
will undergo collisions from the feed to the discharge ofFernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

Fig. 13 Variation of the degree of reduction (based on Parisi
and Laborde model) and the surface breakage parameter a in Eqn. 1 as a function of depth in the reduction
section of the furnace.

the furnace flowing like a piston, so that1 wi,out wi,in   pi E, h 1  ki (E, h) dEdh, for i  n (2)Fig. 14 Prediction of the evolution of fines generation relative
to the depth of the furnace in reduction zone with theeffect of loss of mechanical strength caused by the reduction.
Table 5 Summary of the predictions of fines generation forthe different sections of the furnace for the feedrateof 58 t/h.

0 0

n 1

wn,out  1  wi,out

Section(3)

i 1

where wi is the fraction of pellets in size class i, n is thenumber of size classes, E is the effective specific energy
applied to each pellet in each collision and h is the fractional depth in the furnace.
The proportion of material contained in the finer size
range (fines) generated is then calculated byFines generated = wn,out − wn,in(4)

The challenge in applying the equations above lies in
the fact that kj, the proportion of degraded material by
surface breakage, not only varies with collision energy,
but also with the degree of reduction and, therefore, thevertical normalized position in the furnace h. Fortunately,work by Parisi and Laborde (2004) made it possible to estimate the degree of reduction of the pellets along the vertical axis of the furnace, from the feed to the end of the
reduction section, that is, the entrance of the point of entry of the reforming gases. Parisi and Laborde (2004) proposed this model on the basis of data from two industrial
MIDREX plants. Fig. 13 shows outputs of their simulations, which were used as the basis for the present work.
The figure also presents predictions of the surface breakage parameter a from Eqn. 1, now considering the model
described in Fig. 11, which nearly doubled in magnitude
from the feed to the end of the reduction section.
The assumptions considered in the present work were:• The variability of the fracture energies as well as thestiffness of iron ore pellets do not change with the degree of reduction

Estimated fines
generation (%)#01—Reduction zone

3.42

#02—Upper Burdenfeeder

0.07#03—Middle Burdenfeeder

0.01#04—Lower Burdenfeeder

0.03

Total

3.53

All characteristics of the pellets remain unchanged after the charge passes the zone of introduction of reforming (reducing) gases
Simulations were carried out considering the base case
(Table 4), which resulted in Fig. 14. It shows that the fines
generation in the reduction zone is 3.4 %. Considering
this, as well as the additional contribution of fines generation in the other sections (#2 to #3, of the burden feeders),
the final predicted value for the amount of fines generated
inside the reactor is estimated as 3.5 % (Table 5). This
result shows good agreement with those seen in industrial
plants that produce cold DRI and perform screening ofdischarge (2 to 4 %) (MIDREX, 2011). With this value
considered for fines generation, the resulting production
loss would be 17600 t/year approximately.
It is important to remember that the reference value
mentioned only corresponds to discharge and other fines
generated inside the reactor, e.g. in take-off, for correctcomparison with the value found by the model, must also
be computed. As such, the predictions by the model may
still be conservative. If the change in the amenability ofthe pellets to surface breakage resulting from reduction is
not accounted for, then predictions would be of only
2.64 % of fines, which very likely underestimates the pro•223

Fernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

portion of fines generated in the furnace.
Simulations have also considered the case when thethroughput of the furnace is increased (Table 4). The increase in throughput by 25 and 50 % would increase thefines production to 4.26 and 4.63 % in the reduction zone,
demonstrating the increased importance of this problem.

6. Conclusions
Based on simulations of motion of iron ore pellets in a
MIDREX MINIMOD furnace using the discrete element
method and to the application of a simple degradation
model, it was possible to conclude that:• Body breakage is unlikely to occur with well-formedpellets, but surface breakage has a significant role indegradation inside the furnace studied in the reduction zone.
• The reduction zone, especially the region closest to
the injection of reducing gases, is the greatest responsible for the most severe collisions, with magnitudes
capable of generating fines due to attrition. Indeed,
the dissipation of energy of the collisions was found tohave direct influence of the height of the column ofpellets. Simulation of the increase of production, corresponding to the increase of descent of the charge
demonstrated an increase in severity of the collisions.
• In the region around the burden feeders, the dissipation of energy in collisions of the pellets showed wasvery low. Because of this, little additional fragmentation due to collisions takes in these regions. Such degradation, however, can increase with the use of higher
speeds of rotation of the burden feeders.
• Simulations demonstrated that about 3.4 % fines fornormal operation and up to 4.6 % at higher throughputs would be generated in the reduction zone of the
MINIMOD furnace.

Acknowledgements
The authors would like to thank Vale S.A. for sponsoring the research and for permission to publish the workand for CNPq for partially sponsoring the work. The authors also thank DEM Solutions for the use of the software EDEM under the Academic Program.

224

References
Atsushi M., Uemura H., Sakaguchi T., MIDREX Processes,
KOBELCO TECHNOLOGY REVIEW, 29 (2010) 50–57.
Barrios G.K.P., Carvalho R.M., Kwade A., Tavares L.M., Contact parameter estimation for DEM simulation of iron orepellet handling, Powder Technology, 248 (2013) 84–93.
Basdag A., Arol A.I., Coating of iron oxide pellets for direct
reduction, Scandinavian Journal of Metallurgy, 31 (2002)
229–233.
Cavalcanti P.P.S., Calibration and validation of a mathematicalmodel of degradation of fired pellets during transportationand handling, M.Sc. thesis, Universidade Federal do Rio deJaneiro, 2015 (in Portuguese).
Carvalho R.M., Mechanistic modeling of semi-autogenous
grinding, Ph.D thesis, Universidade Federal do Rio deJaneiro, 2013.
Ghadiri M., Zhang Z., Impact attrition of particulate solids. Part
1: A theoretical model of chipping, Chemical Engineering
Science, 57 (2002) 3659–3669.
Huang Z., Yi L., Jiang T., Mechanisms of strength decrease in
the initial reduction of iron ore oxide pellets, Powder Technology, 221 (2012) 284–291.
MIDREX, Direct from Midrex–3rd/4th Quarter 2011, Midrex
Technologies, Inc., p. 9, 2011, <www.midrex.com/assets/
user/media/DFM2011Q3-4.pdf> accessed 15.08.2013.
MIDREX, World direct reduction statistics, Midrex Technologies, Inc., p. 14, 2015, <http://www.midrex.com/assets/user/
news/MidrexStatsbook201411.pdf> accessed 10.05.2016.
MIDREX, Shaft Furnace Technologies—Solutions for Steelmakers, Midrex Technologies, Inc., p. 10, 2014, <www.midrex.
com/assets/user/media/MIDREX_Process-Brochure.pdf>
accessed 10.05.2016.
Parisi D.R., Laborde M.A., Modeling of counter current moving
bed gas-solid reactor used in direct reduction of iron ore,
Chemical Engineering Journal, 104 (2004) 35–43.
Tavares L.M., Carvalho R.M., Modeling ore degradation during
handling using continuum damage mechanics, International
Journal of Mineral Processing, 101 (2011) 21–27.
Tavares L.M., Carvalho R.M., Pereira H.C., Bianchi M.R.,
Otaviano M.M., Predicting iron ore pellet degradation due
to handling from pellet plant to steel mill, Proc. 2nd European Steel Technology and Application Days, Düsseldorf,
2015.
Weerasekara N.S., Powell M.S., Cleary P.S., Tavares L.M.,
Evertsson M., Morrison R.D., Quist J., Carvalho R.M., The
contribution of DEM to the science of comminution, Powder Technology, 248 (2013) 3–24.
Wong P.L.M., Kim M.J., Kim H.S., Choi C.H., Sticking
behaviour in direct reduction of iron ore, Ironmaking &Steelmaking, 26 (1999) 53–57.

Fernando O. Boechat et al. / KONA Powder and Particle Journal No. 35 (2018) 216–225

Author’s short biography
Fernando Oliveira Boechat
Fernando Oliveira Boechat is PhD student at Universidade Federal do Rio de Janeiro.
He completed his bachelor’s degree in Industrial Engineering from Faculdade Integradas
Espirito Santense and his master’s degree in Metallurgical and Materials Engineeringfrom Universidade Federal do Rio de Janeiro. He is currently a lecturer at Centro Universitário Católico de Vitória, teaching courses in Industrial Engineering. His researchinterests include modeling of industrial, mainly metallurgical processes.

Rodrigo Magalhães de Carvalho
Rodrigo Magalhães de Carvalho is an Associate Professor at Universidade Federal do
Rio de Janeiro. He holds a bachelor’s degree in Chemical Engineering and Metallurgicaland Materials Engineering master’s and D.Sc. degrees at Universidade Federal do Rio deJaneiro, under Prof. Luís Marcelo M. Tavares supervision. He joined the faculty of the
Department of Metallurgical and Materials Engineering at Universidade Federal do Rio
de Janeiro in 2014, where he is the deputy-head of the Laboratório de Tecnologia Mineral. His research interests include discrete element method in mineral processing andsteelmaking applications, mathematical modeling and simulation of comminution processes. He received Minerals Engineering International Young Person’s award and International Mineral Processing Congress Young Authors Award in 2014 and has received anumber of awards from Brazilian Association of Metallurgy, Materials and Mining(ABM) as a co-author with Prof. Luís Marcelo Tavares.

Luís Marcelo Tavares
Luís Marcelo Tavares is a Professor at Universidade Federal do Rio de Janeiro. He received his bachelor’s degree in Mining Engineering (honours) and his master’s degreefrom Universidade Federal do Rio Grande do Sul. He was awarded a Ph.D. degree in Extractive Metallurgy at the University of Utah under the supervision of the late Professor
R.P. King. He has been a member of the faculty of the Universidade Federal do Rio deJaneiro (Brazil) since 1998, where he is head of the Laboratório de Tecnologia Mineraland has been Department chairman. His research interests include advanced models ofcomminution, particle breakage, physical concentration, classification, iron ore processing and development of pozzolanic materials. He is a founding member of the Global
Comminution Collaborative (GCC) and has received a number of awards from the Brazilian Association of Metallurgy, Materials and Mining (ABM).

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KONA Powder and Particle Journal No. 35 (2018) 226–250/Doi:10.14356/kona.2018014

Original Research Paper

Effect of Particle Size and Cohesion
on Powder Yielding and Flow †Hao Shi 1*, Rahul Mohanty 2,4, Somik Chakravarty 3, Ramon Cabiscol 2, Martin Morgeneyer 3,
Harald Zetzener 2, Jin Y. Ooi 4, Arno Kwade 2, Stefan Luding 1 and Vanessa Magnanimo 1
1

Multi-Scale Mechanics (MSM), Faculty of Engineering Technology (ET), MESA+, University of Twente, The Netherlands
Institute for Particle Technology (iPAT), TU Braunschweig, Germany
3
Laboratoire Transformations Intégrées de la Matière Renouvelable (TIMR),
Université de Technologie de Compiègne (UTC) Sorbonne Universités, France
4
Institute of Infrastructure and Environment, School of Engineering, University of Edinburgh, UK
2

Abstract
The bulk properties of powders depend on material characteristics and size of the primary particles. Duringstorage and transportation processes in the powder processing industry, the material undergoes various modes ofdeformation and stress conditions, e.g., due to compression or shear. In many applications, it is important to know
when powders are yielding, i.e. when they start to flow under shear; in other cases it is necessary to know how
much stress is needed to keep them flowing. The measurement of powder yield and flow properties is still achallenge and will be addressed in this study.
In the framework of the collaborative project T-MAPPP, a large set of shear experiments using different shear
devices, namely the Jenike shear tester, the ELE direct shear tester, the Schulze ring shear tester and the FT4
powder rheometer, have been carried out on eight chemically-identical limestone powders of different particle
sizes in a wide range of confining stresses. These experiments serve two goals: i) to test the reproducibility/
consistency among different shear devices and testing protocols; ii) to relate the bulk behaviour to microscopic
particle properties, focusing on the effect of particle size and thus inter-particle cohesion.
The experiments show high repeatability for all shear devices, though some of them show more fluctuations thanothers. All devices provide consistent results, where the FT4 powder rheometer gives lower yield/steady state
stress values, due to a different pre-shearing protocol. As expected, the bulk cohesion decreases with increasing
particle size (up to 150 μm), due to the decrease of inter-particle cohesion. The bulk friction, characterized indifferent ways, is following a similar decreasing trend, whereas the bulk density increases with particle size inthis range. Interestingly, for samples with particle sizes larger than 150 μm, the bulk cohesion increases slightly,
while the bulk friction increases considerably—presumably due to particle interlocking effects—up tomagnitudes comparable to those of the finest powders. Furthermore, removing the fines from the coarse powder
samples reduces the bulk cohesion and bulk density, but has a negligible effect on the bulk friction.
In addition to providing useful insights into the role of microscopically attractive, van der Waals, gravitational
and/or compressive forces for the macroscopic bulk powder flow behaviour, the experimental data provide arobust database of cohesive and frictional fine powders for industrially relevant designs such as silos, as well as
for calibration and validation of models and computer simulations.
Keywords: cohesive powders, shear testers, yield locus, bulk friction, bulk cohesion, particle size effect,
T-MAPPP, database

1. Introduction
Granular materials are omnipresent in our daily life
†
1
2
3
4

*

Received 10 May 2017; Accepted 27 June 2017
J-STAGE Advance published online 23 September 2017
P.O. Box 217, 7500 AE Enschede, The Netherlands
Volkmaroder Str. 4-5, 38104 Braunschweig, Germany
Rue Roger Couttolenc, CS 60319, 60203 Compiègne Cedex, France
Edinburgh EH9 3JY, Scotland, UK
Corresponding author: Hao Shi
E-mail: h.shi-1@utwente.nl
TEL: +31(0)53-489-6445

226

and widely used in various industries such as food, pharmaceutical, agriculture and mining. Interesting granular
phenomena like yielding and jamming (Liu and Nagel,
1998; Bi et al., 2011; Luding, 2016; Kumar and Luding,2016), dilatancy (Cates et al., 2005; Van Hecke, 2009;
Yang et al., 2015), shear-band localization (Alshibi andSture, 2000; Singh et al., 2014), history-dependence(Thakur et al., 2014), and anisotropy (Radjai et al., 1996;
Majmudar and Behringer, 2005) have attracted significant
scientific interest over the past decades (Savage and Hutter,
1989; Cundall, 1989; Radjai et al., 1999; Wolf et al., 2000;

Copyright © 2018 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/).

Hao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

GDR-MiDi, 2004; Tomas, 2005; Alonso-Marroquin andHerrmann, 2004; Luding 2005a, b, 2008). Various laboratory element tests can be performed to study the bulk behaviour of granular materials (Schwedes, 2003). Element
tests are also a valuable tool to understand the influenceof particle properties, e.g. density, size-distribution andshape, on the macroscopic bulk response. Moreover, suchelement tests are commonly used for the industrial designs of silos (Jenike, 1967; Schwedes and Schulze, 1990;
Schulze, 2003a).
Element tests are (ideally homogeneous) macroscopic
tests in which the force (stress) and/or displacement(strain) path are controlled. The most widely performed
element test in both industry and academia is the shear
test, where a granular sample is sheared until failure isreached and the material starts to flow. Shear testers areusually classified into two groups: direct and indirect
methods (Schwedes, 2003; Schwedes and Schulze, 1990).
In direct shear testers, the shear zone is pre-defined by thedevice design, and the shear failure is forced in a specificphysical location. On the contrary, in the indirect devices,
the shear zone develops according to the applied state ofstress. The most common indirect devices are the uni-­
axial compression tester (Russell et al., 2014; Thakur etal., 2014; Imole et al., 2016) and bi-axial shear box(Morgeneyer et al., 2003; Morgeneyer and Schwedes,
2003; Feise and Schwedes, 1995). Direct devices can befurther categorised into two sub-groups: translational androtational. Typical translational shear testers include thedirect shear tester (Casagrande, 1936; Schwedes, 1979;
Shibuya et al., 1997) and the Jenike shear tester (Jenike,1964), while torsional or rotational shear testers include
the FT4 powder rheometer (Freeman, 2007), the Schulze
ring shear tester (Schulze, 1994) and the Brookfield powder flow tester (Berry et al., 2015). Detailed reviews oftesters have been presented by several authors (Schwedes,
2003; Tsunakawa and Aoki, 1982; Schulze, 2008), andmore (non-commercial) shear testers with higher complexity can be found in literature (Harder and Schwedes,
1985; Janssen and Zetzener, 2003; Bardet, 1997).
Quality and reproducibility of results are key aspects
for proper material characterization. Although shear testing technologies have been developed and studied extensively, significant scatter in measurements is still common
when testing powder flowability using different devices indifferent labs/environments (Freeman, 2007; Schulze,
1994; Berry et al., 2015; Schulze, 2001; Kamath et al.,
1993; Kamath et al., 1994). Previous studies have been
focusing on this problem by performing round-robin experimental studies on the Jenike tester (Akers, 1992), theSchulze ring shear tester (Schulze, 2001) and the Brookfield powder flow tester (Berry et al., 2015) as well ascomparing different devices (Koynov et al., 2015). The
earliest round-robin study (Akers, 1992) resulted in a

certified material (CRM-116 limestone powder) and acommon standard experimental testing procedure fordetermining the yield locus. Schulze (Schulze, 2011) has
collected 60 yield loci obtained using the small Schulze
shear tester RST-XS (21 labs) and 19 yield loci using thelarge Schulze shear tester RST-01 (10 labs) on one limestone powder (CRM-116). Results have been comparedamong them as well as with the results from reference
Jenike tester. While results from RST-01 and RST-XS are
in good agreement, a considerable deviation (up to 20 %)was observed when comparing results from the Schulze
ring shear tester to the Jenike shear tester. Similar outputs
are found by other researchers (Berry et al., 2015; Koynov
et al., 2015; Salehi et al., 2017), where yield loci from the
Brookfield powder flow tester, the Schulze ring shear tester, the FT4 powder rheometer and the Jenike shear tester
are compared. The Brookfield powder flow tester and theFT4 powder rheometer show systematically lower shear
responses in comparison to the other two shear testers.
Other studies have compared different industrially relevant powders but only in a single device (Teunou et al.,
1999; Fitzpatrick et al., 2004). Moreover, these comparative studies have been limited to relatively low stresses.
A deeper understanding of the flow behaviour of powders
in several shear devices over a wide stress range is still
missing.
Our collaborative network, EU/ITN T-MAPPP (www.
t-mappp.eu), offers the unique possibility to shed light on
the complex topic of powder yielding and flow, extending
beyond the boundaries of previous projects. The network
involves 16 partners in both academia and industry acrossEurope. The present study has multiple goals. Firstly, wewant to investigate the consistency and repeatability ofyield loci measurements between commonly used shear
testers. This can provide a robust platform to establish thereliability of the testing methodology and procedures.
Secondly, we aim to study the influence of cohesion on
powder flowability by testing powders that have samechemical composition but different particle size, leading
to different degrees of bulk cohesion. Finally, once theagreement between the shear devices is established, measurements can be combined to characterise the powders
over a wider stress range, which is not achievable with asingle device. To achieve this goal, a systematic study has
been carried out by testing 8 powders (Eskal limestone
with median particle diameter from 2.2 to 938 μm) in 5
shear testers (the Jenike Shear Tester, the Direct Shear
Tester, the Schulze Ring Shear Tester with two shear cell
sizes, and the FT4 Powder Rheometer) at 4 partner locations by different operators. Limestone powder has beenchosen due to its negligible sensitivity towards humidity
and temperature changes.
The work is structured as follows: In section 2, we provide information on the limestone samples/materials, in

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section 3 the description of the experimental devices andin section 4 the test procedures. Sections 5 and 6 are devoted to the discussion of experimental results with focus
on shear devices and materials, respectively, while conclusions and outlook are presented in section 7.

2. Material description and characterization
In this section, a brief description of the limestone samples along with their material properties is provided. Eightsize grades with the same chemical composition, i.e. Eskal
limestone (calcium carbonate), are used, with median particle sizes that almost span three orders of magnitude
from μm to mm.
The Eskal series (KSL Staubtechnik GmbH, Germany)is extensively used in many fields including construction
and automotive industries. Eskal is also used as a reference powder for standard testing and calibration of equipment in powder technology, for instance, shear testers(Feise, 1998; Zetzener and Schwedes, 2002) and opticalsizing systems due to the favourable physical properties:
high roundness, low porosity and an almost negligible
sensitivity towards humidity and temperature changes,
which allows to avoid sample pretreatment.
Table 1 summarizes the physical properties of the Eskal
samples. Median particle size d50 ranges from 2.22 μm(cohesive, sticky primary particles that form clumps) to
938 μm (free-flowing primary particles). In this study, allpowders are named with their original commercial name(e.g. Eskal150, Eskal300), except for Eskal K0.1–0.5 andK0.5–0.8 (original product names are Eskal Körnung 0.1–
0.5 and Körnung 0.5–0.8), which for sake of brevity, isreferred to as “K”. The particle size distributions were
determined by laser diffraction (HELOS + RODOS,
Sympatec GmbH) with the dry dispersion unit. The spanof the particle size distribution decreases with increasing
particle size from 1.52 to 0.7, whereas the initial bulk den-sity (bulk density measured directly after filling) increases from 540 to 1400 kg/m3. Primary particle density
ρp is measured using a helium pycnometer at 0.9 % moisture content and is found to be independent of size. Particle roundness, which is the ratio of the perimeter of theequivalent circle to the real perimeter of the projected primary particle, was measured with the Sympatec-QICPIC
imaging system. The working principle of this techniqueconsists of a high-speed image analysis sensor capable ofcapturing 500 frames per second with low exposure time
below 1 ns; this set-up allows to capture and measurewith a high detail size and shape information of an extremely large number of particles in the size range of
1 μm to 30 mm (Witt et al., 2006). Values are the averageover approximately the range between 20000 and
8000000 particles, depending on the median size of primary particles in the powders. The median particle size,
d50, is used in the following as reference to the different
Eskal samples.
Figs. 1 and 2 show the scanning electron microscopy
images of Eskal30 and Eskal K0.1–0.5, in two different
length scales. The topography of the surfaces are createdusing secondary electron imaging (SEI) method. In Fig. 1,
we see that all the Eskal30 primary particles have similar
shapes (left) and rough surfaces (right). But for Eskal
K0.1–0.5, in Fig. 2, we observe more fines between thecoarse particles (left) as well as on the surface (right). The
other Eskal samples have mostly similar shapes (difference

Fig. 1 SEM topography images of Eskal30 (d50 = 30 μm) in
two different length scales as shown in the scale bars.

Table 1 Material parameters of the experimental samples. The initial bulk density represents bulk density from raw materials.
Here, K0.1–0.5 means Körnung 0.1–0.5, which follows the commercial product naming. The initial bulk density values are provided by the manufacturer.
Property (Eskal)
Particle size
Span

Unit

300

500

15

30

80

150

K0.1–0.5

K0.5–0.8

d10

μm

0.78

1.64

12

21

39

97

4.5

738

d50

μm

2.22

4.42

19

30

71

138

223

938

d90

μm

4.15

8.25

28

43

106

194

292

1148

(d90 –d10)/d50

[–]

1.52

1.50

0.84

0.73

0.94

0.70

1.29

0.44

2737

2737

2737

2737

2737

2737

2737

2737

3

Particle density

ρp

kg/m

Moisture content

w

%

0.9

0.9

0.9

0.9

0.9

0.9

0.9

0.9

Roundness

Ψ

[–]

0.75

0.55

0.48

0.66

0.84

0.88

0.74

0.85

Initial bulk density

ρ0

kg/m3

540

730

1110

1230

1330

1370

1400

1276

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tional” devices, namely the ELE direct shear tester and
the Jenike shear cell, and three “rotational” devices (The
Schulze ring shear testers and the FT4 powder rheometer).
A detailed comparison between the main features of alltesters is shown in Table 2 and a comparison of resultsfrom all these testers is presented in section 5. Two main
characteristics of these devices are the degree of automation and the normal stress regime. The Schulze ring shear
tester and the FT4 powder rheometer are in most of theoperational stages completely automated, which strongly
reduces the operator influences. The ELE direct shear tester can reach the highest normal stress among all the devices we investigated.

Fig. 2 SEM topography images of Eskal K0.1–0.5 (d50 = 223 μm)
in two different length scales as shown in the scalebars.

in the range of 20 %, considering the mean values ofroundness) irrespective of median particle size of thesamples.

3.1 Jenike shear tester

3. Experimental set-up

The Jenike tester is a direct translational shear tester, developed in the 1960s (Jenike, 1964) and it is recognized as
one of the industrial standards for designing reliable bulk
solids handling equipment such as storage bins, silos andhoppers. The tester consists of a shear cell (D = 93 mm)
which includes a closed-bottom hollow base fitted to a
fixed bearing plate. A shear ring capable of moving horizontally is placed over the base with a top lid, used toclose the cell, see Fig. 3(a). The shear cell is filled with

Many testers have been devised for measuring theyielding and flow properties of bulk solids in the last 70
years, ranging from the Jenike Shear Tester to thesemi-automated or fully automated testers that are being
developed in the present days (Carr and Walker, 1968).
Here we present a comparison between measurements infive direct shear devices, specifically the two “transla-

Table 2 Specification comparison of the Schulze ring shear tester (RST-1), ELE direct shear tester (DST), FT4 powder rheometer(FT4) and Jenike shear cell (Jenike). The actual shear velocities used are indicated in parentheses, stars refer to the default value fromcontrol softwares.
Property

JenikeDST

RST-01

RST-XS

FT4Cell volume (cm )

189

126

204

31.4

86.4

Cell geometry

cylinder

box

ring

ring

cylinderWall material

aluminium

stainless steel

aluminium

aluminiumborosilicate glass

Diameter (D) or Length (L) (cm)9.3

6

6 (inner)
12 (outer)

3.2 (inner)
6.4 (outer)5

Height (H) (cm)

2.8

3.5

2.4

1.3

4.4

Aspect ratio H/D or H/L

0.30

0.58

0.27

0.27

0.88

Shear displacement limit (mm)810unlimited

unlimited

unlimited

Test control

ManualManualComputerComputerComputerSample weighingofflineofflineofflineofflineon-board

Compression device

top lid

top lid

top ring

top ring

vented piston

Driving velocity

1–3 (2)(mm/min)0.001–2 (2)(mm/min)0.0038–22.9 (*)(°/min)0.0038–22.9 (*)(°/min)

6–18 (6)(°/min)Max. normal stress (kPa)

10–30

2778

50

20

22

Sample conditioning
before pre-shear

pluviation(manual)pluviation(manual)pluviation(manual)pluviation(manual)rotated blade(automatic)

Yield locus test duration

2 hours

2 hours

20 mins

20 mins

30 mins

Stress measure direction

horizontal

horizontal
and verticalrotationaland verticalrotationaland verticalrotational

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the test sample, which rests within the base and the shear
ring, as shown in Fig. 3(b). A normal force is applied tothe shear lid by loading weight on a hanger. A shear force
is then applied using a bracket and a pin on the shear ring.
The bulk solid undergoes shear deformation due to thesimultaneous displacement of the upper ring and the lid
against the stationary bottom ring. The stem is moved bya motor at a constant speed of around 1–3 mm/minute andthe shear force is measured by a force transducer and isrecorded on a computer.
For conducting a shear test, a sample of powder is uni-

formly filled into the shear cell using a spatula and/or asieve. The sample is initially pre-consolidated by twistinga special lid covering the powder bed under a certain normal load. Then the lid and the filling ring are replacedwith a shear lid and the pre-consolidated sample is presheared until a steady state flow is reached, which is defined as a state of constant shear force and bulk density
for a given normal stress. After retracting the shear stem
and reducing the normal load, the shearing process is
re-initiated under a reduced normal load until a maximum
shear stress is recorded. This peak value represents a single point on the yield locus. The pre-shear and shear process is repeated for lower normal loads in order to get thecomplete yield locus. A more detailed description of thestandard testing procedure is reported in the ASTM standard D-6128 (ASTM-D6128, 2006). The laborious workof filling and sample conditioning as well as a potential
influence of the operator are the major drawbacks of thistechnique.

3.2 ELE direct shear tester (DST)

Fig. 3(a) Jenike direct shear tester and (b) the schematic representation of the Jenike shear cell. For technical details see Table 2. Fig. 3(b), reprinted with permission
from author (Schulze, 2002). Copyright: (2002) Dietmar Schulze.

Fig. 4230

The second direct shear tester (ELE International,
United Kingdom), is illustrated in Fig. 4(a). It operates withspecimens with a square cross-section of 60 mm × 60 mm
and a height of 30 mm. The apparatus is enclosed in arobustly constructed case. It is designed for and can reachshear stress up to 1250 kPa and normal stress up to2778 kPa. The speed range is between 0.0001 to 2 mm/min.
The ELE direct shear tester is designed for much higher
load in soil testing, employs a simple shear principle as
the Jenike shear cell, has a larger shear displacement
range (up to 12 mm in horizontal direction) and the possibility of reverse box movement.
The shear test sequence starts with the filling of theshear box by dry pluviation of the powder into the box
until a height of approximately 40 mm is reached; then(a) The ELE direct shear tester and (b) the schematic representation of the ELE direct shear cell set-up.
For technical details see Table 2.

Hao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

the top excess powder is removed by a scraper to ensurethat the top surface of the sample is flat. Finally the top
lid is mounted and the powder sticking to the sides of thebox is removed carefully using a small paint brush. In addition to the typical direct shear testers as listed in Sec.
3.1, the main drawback for this tester is the possible ejection of powder through the inter-quadrate opening. In order to compare results in DST with other devices properly,
shear tests in this study are performed following the same
ASTM standard D-6128 (ASTM-D6128, 2006) as in Jenike shear tester. For the steady state test, in analogy to
the normal wall friction procedure, the sample is firstsheared to steady state at the highest normal load chosen.
Then step by step the normal load is decreased and shear
is continued until steady state is reached.

3.3 Schulze ring shear tester—RST-01 and RSTXS
Among the shear devices for powder characterization,
the Schulze rotational ring shear tester (1994) is one of themost widely used testers. The Schulze ring shear tester(RST-01) operates connected to a personal computer running a control software that allows the user to obtain,
among other things, yield loci and wall yield loci. A
smaller version of the ring shear tester with exactly thesame working principle is the so-called RST-XS, developed for smaller specimen volumes (3.5 ml to 70 ml,
rather than 204 ml for the RST-01). For both testers, ringshaped (annular) bottom ring of the shear cell contains thebulk solid specimen. An annular-shaped lid is placed on
top of the bulk solid specimen and it is fixed at a crossbeam (Fig. 5).
A normal force, F N, is exerted on the cross-beam in therotational axis of the shear cell and transmitted throughthe lid onto the specimen. Thus a normal stress is applied
to the bulk solid. In order to allow small confining stress,
the counterbalance force, FA, acts in the centre of the crossbeam, created by counterweights and directed upwards,
counteracting the gravity forces of the lid, the hanger andthe cross-beam. Shearing of the sample is achieved by rotating the bottom ring with an angular velocity ω, whereas
the lid and the cross-beam are prevented from rotation by
two tie-rods connected to the cross-beam. Each of the tierods is fixed at a load beam, so that the forces, F1 and F2,
acting on the tie-rods can be measured. The bottom of theshear cell and the lower side of the lid are rough in orderto prevent sliding of the bulk solid on these two surfaces.
Therefore, rotation of the bottom ring relative to the lid creates a shear deformation within the bulk solid. Throughthis shearing the bulk solid is deformed, and thus a shear
stress τ develops, proportional to the forces on the tie-rods(F1 + F2). All the tests performed here follow the ASTM
standard (ASTM-D6773-16, 2008).

Fig. 5(a) The Schulze ring shear tester RST-01 and (b) the
working principle of the Ring shear cell set-up. The
difference between RST-XS and RST-XS is the shear
cell size. For technical details see Table 2. Fig. 5(b),reprinted with permission from author (Schulz, 2003b).
Copyright: (2003) Dietmar Schulze.

3.4 FT4 powder rheometer
The last experimental equipment used in this work is
the FT4 Powder Rheometer (Freeman technology Ltd.,UK), depicted in Fig. 6(a). Standard accessories for the
shear test include the 50-mm-diameter blade for sample
conditioning, the vented piston for compression, the shear
head for the shearing process and the 50-mm-high with
50 mm diameter borosilicate test vessel. One advantage ofthe commercial FT4 Powder Rheometer is the automatednature of the test procedure requiring minimal operator
intervention.
The shear test sequence under the ASTM standard
D7891 (ASTM-D7891-15, 2015) can be summarized asfollows: the test vessel is carefully filled with the powderof interest using a spatula after obtaining the tare weight.
The conditioning procedure involves the movement of theconditioning blade into the test sample to gently disturb
the powder bed for a user-defined number of cycles before
it is removed slowly. A cycle consists of the inward and231

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outward movement of the conditioning blade into thepowder bed with a constant rotation movement all thetime. In order to prevent the conditioning blade fromtouching the base of the vessel, the direction of the blade
movement is reversed as soon as it is within 1 mm of thevessel base. It is believed that this creates a uniform,
loosely packed test sample that can be readily reproduced(Freeman, 2007).
In this study, we perform three pre-conditioning cycles
before the shear tests are carried out (pre-conditioning
does not involve a confining stress like in the other 3 testers). The portion of the base insert of the test vessel are
excluded from the calculation of the vessel height, leading
to a maximum vessel height of 44 mm instead of 50 mm
and an aspect ratio α of 0.88. Subsequent to pre-­conditioning, the blade is replaced with a vented piston,which incorporates a stainless steel mesh to allow theenclosed air in the powder to escape uniformly across thesurface of the powder bed. The vessel assembly is thensplit (and thus levelled) after the vented piston executes
the compression until the pre-shear normal stress level isreached. Then the powder mass is recorded after splitting
to compute the bulk density before the shear tests start. A
detailed description of the vessel split-and-levelling procedure is reported by Freeman et al. (2009).
A shear test begins after changing the vented piston to
the shear head as shown in Fig. 6(b). The shear headmoves downwards inserting the blades into the powder
and induces a normal stress as the shear head bottom surface is in contact with the top of the powder. The shear
head continues to move downwards until the required
pre-shear normal stress is reached. At this point slow rotation of the shear head begins, inducing an increasing
shear stress. As the powder bed resists the rotation of theshear head, the shear stress increases until failure, at the
point a maximum shear stress is observed. As a consequence, a shear plane is formed just below the ends of theFig. 6232(a) The FT4 Powder Rheometer and (b) the working
principle of the FT4 shear cell set-up. For technical details see Table 2.

blades. The shear head is kept moving until the shear
stress does not change anymore for the pre-shear step andis stopped immediately after the maximum is reached
for each shear step. A constant normal stress is maintained throughout each pre-shear or shear step. Note thatpre-shear in FT4 is a multi-stage process and will be discussed in the next section. All the tests performed with
the FT4 powder rheometer follow ASTM standard(ASTM-D7891-15, 2015).

4. Test procedures
In this section, an overview of the testing procedures aswell as all the details of the tests performed using shear
devices for different limestone specimens are presented.
The diagram in Fig. 7 illustrates the common testingprocedures used for measuring the yield locus. The
Schulze ring shear tester RST-01 only requires one single
pre-shear cycle before the first shear point and the steadystate is reached (Fig. 7 top). And this pre-shear determination is also similar in the DST and Jenike. However, theFT4 powder rheometer involves multiple pre-shear cycles
before the first shear is initiated, and it determines thesteady state only when the difference between the end
point shear stress values from two consecutive pre-shear
cycles is within 1 % (Fig. 7 bottom). The number of multiple pre-shear cycles in the FT4 usually varies from 4 forcohesive powders to 6 for free-flowing powders. And theinfluence of this difference on powder flow properties
will be further elaborated in Sec. 5.3.
The main quantities referred to in this study (linearised
effective yield locus, yield locus and steady state/termination locus) are explained in Fig. 8, where the pre-shear
and shear points are the measured values as indicated inFig. 7. According to these three loci, three different angles can be determined: effective angle of internal friction,

Fig. 7

Schematic drawing of typical yield locus measurement
steps for RST-01 (top) and FT4 (bottom).

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Fig. 8

Schematic drawing of effective yield locus, yield locus
and steady state locus.

the limit of the force sensor. The actual normal stresses
used for this study are also highlighted with black dots on
the solid lines and summarized in Table A1. In Fig. 9, we
divide the whole normal stress range into three regimes: i)low normal stress, where Jenike, RST-01/RST-XS andFT4 can be used; ii) moderate normal stress, where RST01 and FT4 are available; iii) high normal stress that DST
and RST-01 can be relied on.
The Schulze RST-01 was chosen as a reference device
and used to test all 7 Eskal samples at 3 different preshear normal stress levels since it covers the widest stressrange. A limited number of cases were tested with theother devices depending on the accuracy and material
availability. However, for each pre-shear normal stress,
tests on one powder have been performed using at least
two devices in order to check the reproducibility of theresults between the testers. Each test was repeated threetimes (3 fresh samples) to investigate the repeatability
within a single device. Details on the pre-shear and shear
normal stress levels used are given in Table A1. In addition, we have also performed steady state locus study using 4 powders in DST. We have chosen a pre-shear normal
stress values between 1.4 and 36.1 kPa. The test details
are summarized in Table A2.

5. Comparison of shear devices
Fig. 9

Schematic drawing of typical yield locus. Black arrows
at the bottom: typical normal stress ranges used foreach device; dashed lines are extended normal stresslimits. Black points indicate the actual normal stresslevels used for different shear testers.

ϕe, angle of internal friction, ϕ, and steady state angle ofinternal friction, ϕss as depicted in Fig. 8 and the details
are given by Schulze (2008). The intercept of yield locus
for normal stress equals to zero is named as cohesivestrength, and it qualitatively indicates the bulk cohesionof a given sample under a given normal stress. Note that
all the quantities measured from different testers are using the same definition here.
Since all the devices investigated here have been designed for different purposes, they are adapted to test thematerials in preferable normal stress ranges. In Fig. 9, weshow schematically the range of normal stress that eachdevice can cover with acceptable accuracy. In the sameplot, we indicate the extended normal stress ranges of
Jenike and DST (dashed lines). For Jeinke in higher normal stress range, the data are highly difficult to acquireand less reliable due to insufficient shear path available inshearing direction. On the other hand, low/intermediate
normal stress results from DST are less accurate due toIn this section, we compare the measurement from different shear devices and a general overview of the repeatability and reproducibility of the test results is given. In
order to compare the yield loci from different testers, twolimestone powders were chosen as reference powders (seeTable 3), namely cohesive Eskal300 (2.22 μm) and freeflowing Eskal150 (138 μm).

Table 3 Summary of the tests performed. The numbering in
the table are the number of powders tested with a certain device
under a certain pre-shear stress level. For more details, see
Table A1. Note that the values in the parentheses refer to thepre-shear normal stress values used for a specific device.
Stress in kPa
DeviceLow stress
5 (4.3)Moderatestress 20

High stress35 (36.1)

Jenike2 (4.3)

[–]

[–]

DST

[–]

[–]

4 (36.1)

RST-01

7

8

7

RST-XS

4 (4.3)

[–]

[–]

FT4

[–]

4

[–]

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Fig. 10 Yield locus (shear stress versus normal stress) of Eskal150 (138 μm) and Eskal300 (2.22 μm) using RST01 and Jenike. The pre-shear normal stress is kept at
5 kPa for both devices. Points with and without lines
are shear and pre-shear points, respectively. Lines are
guides to the eye.

5.1 Low normal stress: Schulze ring shear tester(RST-01) vs Jenike tester
In the low normal stress regime, we first compare the
RST-01 with the standard Jenike tester at pre-shear normal stress of 5 kPa. Each shear point is measured with 3
fresh samples to acquire the standard deviations. The
yield loci for Eskal150 (138 μm) and 300 (2.22 μm) are
shown in Fig. 10. Both testers show quite good repeatability with a higher standard deviation from the Jeniketester. When we look at the individual powders, the agreement between the two shear testers for Eskal150 is good,with the difference increasing slightly with increasing
normal stress. The pre-shear stress values are also close
within the deviation range. For the finer Eskal300, thediscrepancy between the two devices becomes higher, but
still within the standard deviation. A big discrepancy isobserved for the pre-shear points, where the Jenike shows
lower values and higher standard deviations compared to
RST-01. This may be related to the manual control procedure of the Jenike shear cell. Often the pre-shear must be
stopped to prevent the risk of running out the shear displacement.

5.2 Low normal stress: Schulze ring shear tester(RST-01) vs (RST-XS)
In the same low normal stress range, we have also
tested the two reference powders using the smaller
RST-XS, and the data are compared to RST-01 as shownin Fig. 11. For both devices, the repeatability is very high,with the standard deviations within the symbol size. For
the free flowing Eskal150, the yield loci measured by the234

Fig. 11 Yield locus (shear stress versus normal stress) of Eskal150 (138 μm) and Eskal300 (2.22 μm) using RST01 and RST-XS. The pre-shear normal stresses are set
to 5 and 4.3 kPa for RST-01 and RST-XS, respectively(Eskal300 has one extra 5 kPa pre-shear using
RST-XS). Points with and without lines are shear andpre-shear points, respectively. Lines are guides to theeye. Note that here the data for RST-01 are the sameas in Fig. 10.

two devices demonstrate a very good agreement althougha slightly different pre-shear normal stresses are used. For
the cohesive Eskal300, data from RST-XS are consistently
lower than data from RST-01. However, both devices
show a non-linear behaviour with the slope (decreasing
with increasing normal stress).
To further investigate RST-XS, we have tested Eskal300
in the RST-XS using the same pre-shear and shear stresslevels as in RST-01, and results are also plotted in Fig. 11.
We observe that, also in this case of same pre-shear normal stress, the RST-XS values are systematically lower
than the RST-01 values (around 5 %). As the only known
difference between RST-XS and RST-01 is the shear cellsize, our results indicate that the powder response may be
influenced by the system size in the case of cohesive material.

5.3 Moderate normal stress: Schulze ring shear
tester (RST-01) vs FT4 powder rheometerIn the moderate normal stress regime, we compare themost commonly used rotational shear testers, the RST-01
and the FT4 rheometer. Both testers are automated and allow selection of a pre-shear normal stress value, σpre,which was set to 20 kPa for our comparison.
The yield loci for Eskal300 and Eskal150 are shown in
Fig. 12. Both the RST-01 and the FT4 show good repeatability for each measurement point, with the standard deviations within the symbol size. For the free-flowing
Eskal150, the yield loci measured by the two devices arein very good agreement except for the pre-shear points,

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fairly uniformly over the solid shearing surface; whilst
the FT4 rheometer has a circular cross-section where theshearing displacement is highly non-uniform with values
decreasing towards zero at the centre of the cross-section.
It is thus probable that critical shearing state may not be
fully achieved particularly near the central zone of thecross-section, thereby producing a smaller overall critical
shear stress.

5.4 High normal stress: Schulze ring shear tester(RST-01) vs direct shear tester (DST)

Fig. 12 Yield locus (shear stress versus normal stress) of Eskal150 (138 μm) and Eskal300 (2.22 μm) using RST01 and FT4. The pre-shear normal stress is kept at
20 kPa for both devices. Points with and without lines
are shear and pre-shear points, respectively. Lines are
guides to the eye.

where the FT4 gives a much lower value than the RST-01.
However, for the cohesive Eskal300, we see a pronounced
difference between results obtained by the two devices(around 10–20 %), although the angle of internal friction(slope) between the two devices stays almost the same. A
similar trend is observed with the other two cohesive
samples: Eskal500 and Eskal15, with the values measured
by FT4 systematically lower than the ones from RST-01(data not shown here, for details see Tables B1 and B2).
We associate the difference in the behaviour between
the two devices to the test protocols as explained in Sec. 4.
The Schulze ring shear tester, based on the ASTM standard D-6773 (ASTM-D6773-16, 2008), uses the conventional pre-shear determination criterion: the steady state
shear stress plateau is determined in one pre-shear stage
and the following pre-shear stages after incipient flow follows this one pre-shear state value. On the other hand, for
the FT4 powder rheometer, based on the ASTM standard
D7891 (ASTM-D7891-15, 2015), several pre-shear cycles
are performed until the steady state reaches a constantshear stress value (within 1 % difference). This value isthe assumed as pre-shear steady state and the shear stage
starts. In the case of cohesive powders, the samples need
3–10 repetitions for the pre-shear to fulfil the steady state
criterion in the FT4. This may lead to formation of apre-defined shear failure plane in the sample that reduces
its shearing resistance along the shear direction. We pointout here that both shear devices are automated using theirown test software where the test protocols are in-built andtherefore impossible to change by the users. In addition,
there is another significant difference between the twotesters in that the Schulze ring shear tester has an annularcross-section where the shear displacement is applied

In the high normal stress regime, we compare the reference Schulze ring shear tester (RST-01) with the direct
shear tester (DST) as shown in Fig. 13. The pre-shear
stress σpre is set to 35 kPa for the RST-01 and 36.1 kPa for
the DST. This small difference in the pre-shear normal
stress applied is due to the design limitation of DST,
where one can only change the normal stress discontinuously.
As we can see clearly from the figure, the results from
DST and RST-01 are in good agreement for both powders.
The standard deviation of DST data is higher than the
RST-01, and becomes more prominent for low stress levels as well as for the free-flowing sample Eskal150. In thecase of pre-shear points, the DST shows a slightly lower
value compared to the RST-01, but the difference is negligible. For the yield locus of Eskal150, data from the two
devices overlap within the error bars. When we focus on
Eskal300, DST underestimates the shear stress values on
the yield locus with respect to the RST-01, especially for
low normal stresses. We want to point out that the low
stress data from DST may be less reliable that the shear

Fig. 13 Yield locus (shear stress versus normal stress) of Eskal150 (138 μm) and Eskal300 (2.22 μm) using RST01 and DST. The pre-shear normal stresses are kept at
35 and 36.1 kPa for RST-01 and DST, respectively.
Points with and without lines are shear and pre-shear
points, respectively. Lines are guides to the eye.

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force measurement system of DST has a lower limit valueof 1 N (1 kPa).
Finally, in order to confirm the reproducibility between

the two devices, we further test the steady state shear responses for Eskal K0.1–0.5 and Eskal K0.5–0.8, as shownin Fig. 14. Results from the two shear devices show good
agreements for the tested two powders, with the data
points following the two linearised yield loci within thestandard deviations.

5.5 Summary of device comparison

Fig. 14 Steady state locus (shear stress versus normal stress)of Eskal K0.1–0.5 (223 μm) and K0.5–0.8 (938 μm)
using RST-01 and DST. The lines are the least meansquare linear regression to the data with angle
ϕss = 36.2° for Eskal K0.1–0.5 and 41.5° for Eskal
K0.5–0.8.

In order to validate the consistency of the results obtained from different shear devices, we extrapolate thelinearised yield loci and compare both angle of internal
friction as well as cohesive strength (interception of linearised yield locus on y-axis) for the two reference powders (Figs. 15 and 16). The data from different shear
testers are interpreted in different ways. In the case of theyield locus from the Jenike tester and DST, the shear
points are linearised using a least square method, while
the RST-01, RST-XS and FT4 are linearised using the default software with pro-rating method. For a free-flowing
powder, Eskal150 (138 μm), we get a good agreement
among the RST-01, the RST-XS and the FT4 for the cohesive strength, c, but higher values from the Jenike and es-

Fig. 15 (a) Cohesive strength, c and (b) angle of internal friction, ϕ, plotted against normal stress, σn, for Eskal150(138 μm tested using all the devices in this study.

Fig. 16 (a) Cohesive strength, c and (b) angle of internal friction, ϕ, plotted against normal stress, σn, for Eskal300(2.22 μm) tested using all the devices in this study.

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pecially from the DST with also larger standard
deviations (Fig. 15(a)). A similar observation is also
found for the angle of internal friction as shown in
Fig. 15(b), but the ϕ value obtained from the DST is lower
than the other devices. This is caused by the limit of thedirect shear tester in the low stress range (below 1.0 kPa).
The direct shear tester is initially designed for measuring
the strength of soil samples in civil engineering, where
the stresses applied are usually high, whereas our tests
were performed at much lower stress levels, close to theaccuracy limit (around 0.5 kPa) of the force ring on direct
shear tester, resulting in a decrease in measurement accuracy for the direct shear tester using free-flowing powders. In the case of the Jenike shear tester, the ϕ value ishigher than the other devices, but still within the deviation range.
In Fig. 16, we investigate the reproducibility of all thedevices by looking at the most cohesive Eskal300 powder(2.22 μm). DST shows a good agreement with the highest
standard deviation for cohesive strength, c, (Fig. 16(a)).
However, the difference between the DST and the RST-01
is around 20 %. The RST-XS, Jenike and the RST-01 havea good agreement but FT4 shows a relatively lower value
for c, thus underestimating the flowability of very cohesive powders. When we look at the ϕ value as shown in
Fig. 16(b), Jenike unexpectedly gives the lowest value
with the highest standard deviation. The DST showsslightly lower values than the RST-01 and the FT4 has agood agreement with the RST-01 (within deviation range).
Similar behaviour is observed for two other Eskal powders
tested using RST-01, RST-XS, FT4 and DST: cohesive
Eskal500 and easy-flowing Eskal15 (data are not shown
here, see the Tables in Appendix B). Note that the verticalaxes of cohesive strength are different in Fig. 15 andFig. 16.

6.1 Bulk density at steady state
As a first step, we look at the dependence of the bulk
density on the normal stress and particle size for all thepowders. Data are shown in Fig. 17(a). Zero normal stress(arrows on bulk density axis) corresponds to the initialbulk density of the fresh samples before applying any
stresses (provided by the manufacturer). By increasing
normal stress, the bulk density increases for all powders
with different rates, higher for small-particle-size powder
and almost zero for Eskal80 (71 μm) and 150 (138 μm).
However, for Eskal K0.1–0.5 (223 μm), the bulk density
increases with increasing normal stress. We associate thistrend to the wider particle size distribution (large spanvalue 1.29 as shown in Table 1) and the visible hugeamount of fines as shown in Fig. 2. A wider particle size
distribution allows easy rearrangement of the packing
structure when applying external load.
In Fig. 17(b), we plot the bulk density with respect to6. Effects of varying particle size
In this section, we present the comparison of sevenEskal powders tested by the Schulze ring shear tester(RST-01) at different pre-shear stresses as given in Table 3.
For the analysis of RST-01 data, we used the standard
RST-CONTROL 95 software with “N-RHOB-correction”
activated (Schulze, 2011). The powder have sizes ranging
from 2.22 to 938 μm, and identical chemical composition
as explained in Table 1. We characterize the above-­mentioned seven powders in terms of bulk density, angle
of internal friction, cohesive strength, steady state angle
of internal friction, effective angle of internal friction andflow function.

Fig. 17 Bulk density in steady state, ρb, plotted against (a)normal (pre-shear) stress, σn, (b) median particle size,
d50. Arrows represent the initial bulk density of theraw samples before stress and shear are applied. Symbols in the dashed area are sieved Eskal K0.1–0.5(223 μm) sample sheared at σn = 20 kPa. Lines are
guides to the eye.

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the median particle size for different normal stresses. We
observe an increasing trend with increasing particle size
consistent for all normal stresses. This can be explainedby the presence of cohesive forces (van der Waals) between primarily particles other than gravitational forces.
Since Eskal powders are relatively dry, the presence ofliquid bridging and other forces are expected to be small,the dry cohesive interaction will result in forming clusters
and create many voids in the bulk, and therefore decrease
the bulk density. As cohesive forces become smaller withincreasing size, particles will have mainly frictional andgravitational forces without forming clusters and therefore the material can form a denser bulk solid. One extra
powder, Eskal K0.5–0.8 (938 μm), is also tested under
20 kPa normal stress. This powder breaks the trend seen
previously and shows a lower bulk density associated withthe largest median particle size. In order to investigate
further the role of the span in the bulk density behaviour,
we perform sieving on the sample with largest span, Eskal
K0.1–0.5 (223 μm). Two sieving methods are used: standard vibration sieving and high pressure air sieving. The
median particle sizes reduce to 101 μm and 208 μm, inthe case of vibration sieving and air sieving, respectively.
The vibration sieving is only effective in removing thecoarse particle but not the fines and thus leads to an increase of the span from 1.289 to 2.173. While the air sieving is effective enough to remove both coarse and finesand decrease the span to 0.395. The bulk densities for Eskal K0.1–0.5 (223 μm) after sieving are plotted in thedashed area of the same Fig. 17(b). The bulk density ofthe sieved samples both decrease to values that are similar
to the values of the largest median particle size powder,
Eskal K0.5–0.8 (938 μm). This indicates that for a given
median particle size, the span has a dominating effect on
the bulk density of a powder.

6.2 Bulk responses from incipient and steady stateflow
6.2.1 Angle of internal friction from incipient flow

The angle of internal friction describes the bulk friction during incipient flow of a powder, which is determined from the linearised yield locus as shown in Fig. 8.
Although the yield locus for cohesive powder is non-­linear by nature, the linearised yield locus can still be
used to estimate the angle of internal friction in a certain
stress range. This estimated value is one important property that determines the maximum bulk friction of a powder from a given pre-consolidation history. Here, unlessspecified, all angles of internal friction originate from linearised yield loci.
In Fig. 18, we plot the angle of internal friction against
normal stress at three different pre-shear normal stressand particle size for the 7 powders studied (Eskal K0.5–

238

Fig. 18 Angle of internal friction, ϕ, plotted against (a) preshear normal stress, σn, (b) median particle size, d50.
Symbols in the dashed area are sieved Eskal K0.1–0.5(223 μm) sample sheared at σn = 20 kPa. Lines are
guides to the eye.

0.8 is also included here but with only one point). Within
the stresses investigated, there is no apparent dependenceof the angle of internal friction on the normal stress(Fig. 18(a)). However, if we focus on the dependence on
the particle size as shown in Fig. 18(b), we observe thatwhen d50 is lower than approximately 30 μm, ϕ decreases
with increasing particle size. Then, for 30 < d50 < 150 μm,
we observe that the ϕ is almost constant with changing
particle size for the three pre-shear normal stresses chosen. Interestingly, if the particle size keeps rising to
d50 < 150 μm, ϕ follows a parallel rise and achieves similar values to the ones obtained for samples smaller than
30 μm. For Eskal K0.1–0.5 (d50 = 223 μm), the angle ofinternal friction increases back to around 38°.
We have run several tests/checks with the goal of elucidating the non-monotonic behavior that observed inFig. 18(b). First, we further test another sample in therange of d50 > 150 μm, namely Eskal K0.5–0.8 (d50 =938 μm), at 20 kPa pre-shear stress. The ϕ value of Eskal
K0.5–0.8 increases even further to around 42°. This confirms that the increasing trend is not limited only to a

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specific sample. As second step, we have measured theangle of internal friction for the two sieved samples obtained after sieving Eskal K0.1–0.5 (223 μm) via vibration
and air methods that are already introduced in Sec. 6.2.1.
While the bulk density strongly reduces after sieving, theangle of internal friction remains unaffected as shown inthe dashed area of Fig. 18(b), which indicates that the
span of particle size distribution is not the primary factor
influencing the bulk friction. Finally, in order to check theinfluence of the devices, we have further tested Eskal
K0.1–0.5 (223 μm) and K0.5–0.8 (938 μm) in the direct
shear tester (DST), and the results are reported in Fig. 14.
The flow behaviour of both powders are very similar using RST-01 and DST. This agreement clarifies that the behaviour originates from material properties rather thanfrom a specific shear device.
One possible explanation of this interesting behaviouron bulk friction would be that the different size particles
have a similar shape (this is visible by comparing theroundness between Eskal K0.1–0.5 and K0.5–0.8 inTable 1) but different surface roughness/asperity, but thishas to be further investigated and it is far beyond thescope of this study. Another possibility is the competition
between the inter-particle cohesion and inter-particle friction (caused by shape). When the particles are small, theinter-particle cohesion dominates the flow behaviour andenhances the shear resistance. Also when a sample is confined under a given confining stress, if the inter-particle
cohesion is high, the sample bulk density will be low,which gives more free spaces for particles to movearound. Therefore, the geometrical interlocking does notplay an important role here. When the particle size islarge, we have almost no influence from inter-particle cohesion and the whole powder is more densely packed, sothat the inter-particle friction/interlocking (shape/geometry) is the ruling mechanism of the bulk friction behaviour. For an intermediate particle size, these two
effects are both reducing but still competing with eachother, and they cannot be distinguished.

6.2.2 Cohesive strength from incipient flow

As a complement to the angle of internal friction, one
has to also look at the cohesive strength, which is the extrapolated intercept from the linearised yield locus, andgives an indication of the strength of the powder underzero confining stress (σn). In Fig. 19(a), we plot the cohesive strength against the pre-shear normal stress. As expected, the values of cohesive strength at given stresslevels are higher for powders with finer particle size. The
cohesive strength of all powders increases with increasing
normal stress, but with different slopes. The cohesivestrength of the two finest powders, Eskal300 (2.22 μm)
and Eskal500 (4.42 μm), increase conspicuously with normal stress.

Fig. 19 Cohesive strength, c, plotted against (a) pre-shear normal stress, σn, (b) median particle size, d50. Symbols
in the dashed area are sieved Eskal K0.1–0.5 (223 μm)
sample sheared at σn = 20 kPa. Lines are from the fitted function: c(d50) = σpre * dc/d50 with dc = 0.6919,
0.3953 and 0.2809 μm for σpre = 5, 20 and 35 kPa,
repectively.

As we focus on the particle size dependence in
Fig. 19(b), we see a monotonically decreasing bulk cohesion with increasing particle size for all the normal stresslevels investigated. However, the cohesive strength for
raw Eskal K0.1–0.5 (223 μm) increases above this trend(as shown in the dashed area in the figure). This apparent
discrepancy was also observed in the bulk density and theangle of internal friction, as explained earlier. We further
investigated this behaviour by sieving the sample using
different techniques. It seems that our air sieving procedures are effective and reduce the cohesive strength of thepowder by separating the fines from the coarse fractions.
The theory that smaller particles have the strongest cohesive forces, acting most effectively on each other, is consistent with the strongest decrease in cohesion for the airsieved samples in which the fines are most effectively
removed. The observation of removing fines reduces bulk
cohesion but does not affect bulk friction supports the hypothesis that frictional flow behaviour of powders in the239

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range of d50 > 150 μm is governed by particle interlocking.
In Fig. 19(b), we have also given fitted lines based on
the equation as shown in the caption. All our data fitted
well with a power law dependence and this power has its
origin from the adhesive forces between two particles, as
introduced by Rumpf in 1990 (Rumpf 1990, Rabinovich
et al. 2000), where the adhesion force between two particles is linearly proportional to particle diameter: Fad ∝ d.
While for the cohesive strength, it is a bulk property withan unit of stress. Therefore, cohesive strength is proportional to the adhesion force divided by effective contact
area: c ∝ Fad /d2, and finally we get c ∝ d −1, which is therelation used for our fitting.

6.2.3 Bulk friction from steady state flow

Along with the bulk density (volume fraction), angle ofinternal friction and cohesive strength, the steady state
angle of internal friction, ϕss, also plays a major role indetermining the powder flow behaviour. The steady stateflow does not depend on time change or sample history
and one could get a unique bulk friction response toshearing for each normal stress level for a given sample.
We first look at the ϕss with respect to the applied normal
stress in Fig. 20(a). For samples with median particle size
higher than 20 μm (Eskal30, 80, 150 and K0.1–0.5), theϕss behaves similarly as ϕ, no clear dependence on normal
stress is observed. However, for samples smaller than
20 μm (Eskal300, 500 and 15), ϕss decreases with increasing normal stress.
When we look at the size influence on ϕss in Fig. 20(b),we observe a very similar trend to the angle of internal
friction in Fig. 18(b). However, the value of ϕss for largest
size powder is lower than the value of the finest powder,where ϕ of the coarsest powder exceeds the finest. This
indicates that the inter-particle cohesion contributes moreto the shear resistance at steady state flow than at incipient flow. When looking at the behaviour of the two sieved
samples, ϕss stay almost unchanged after sieving, which isconsistent with Fig. 18(b).

6.3 Quantities relevant for silo design
The parameters mentioned in the sections above aredetermined directly from the physical response of powders in the shear tester, e.g., bulk friction values can bedirectly calculated from the measured normal and shear
stresses, and are very useful for understanding the powder’s physical behaviour. However, for designing a silo,
some additional parameters play an important role (Jenike,
1976; Schulze, 2008, 2014b). These will be discussed in
the following sections.

6.3.1 Effective angle of internal friction

Fig. 20 Steady state angle of internal friction, ϕss, plottedagainst (a) pre-shear normal stress, σn, (b) medianparticle size, d50. Symbols in the dashed area aresieved Eskal K0.1–0.5 (223 μm) sample sheared at
σn = 20 kPa. Lines are guides to the eye.

240

The effective angle of internal friction is defined as theangle of the effective yield locus, which is the line starting at the origin of the σn – τ plane and tangent to theMohr circle (see Fig. 8). And this property is crucial for
designing the hopper angle in order to achieve mass flow
in a silo.
In Fig. 21, the effective angle of internal friction isplotted against the normal stress and median particle size.
Within the stress levels investigated, ϕe decreases with increasing normal stress, except for two intermediate size
powders—Eskal30 (30 μm) and 150 (138 μm), whichshows a consistent behaviour with ϕss independent of thenormal stress. Interestingly, for even higher particle size,
Eskal K0.1–0.5 (223 μm), ϕe again decreases with applied
normal stress.
When we focus on the dependence of the effective angle of internal friction on the particle size as shown in
Fig. 21(b), we observe a very similar trend as ϕ and ϕss,
especially with values of ϕe consistently higher than ϕss
for both very fine and very coarse powders. Also in thisHao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

Fig. 22 Flow function: unconfined yield strength, σc, plottedagainst major consolidation stress, σ1 under 3 different pre-shear stresses using RST-01. Different symbols/colours represent different materials. Note thatfor Eskal K0.5–0.8, there is only one point, and wehave error bars with both σc and σ1. Lines are guides
to the eye.

Fig. 21 Effective angle of internal friction, ϕe, plotted against(a) pre-shear normal stress, σn, (b) median particle
size, d50. Symbols in the dashed area are sieved Eskal
K0.1–0.5 (223 μm) sample sheared at σn = 20 kPa.
Lines are guides to the eye.

case, sieving barely affects the behaviour of the powders,see dashed area in Fig. 21(b).

6.3.2 Flow function and powder flowability

Finally, we process the results to look at the powder
flowability in the form of the flow function to evaluate
how a given powder would fail/flow under a given major
consolidation stress (see Fig. 8). This is also of great significance for designing the outlet diameter of a silo
(Schulze, 2014a). When a powder sample is compressed ina confined geometry, e.g. a cylinder in a uni-axial tester,
the major consolidation stress is named as σ1, which indicates the maximum compressive stress achieved in thesample. If the powder is sufficiently cohesive, it will form
an intact bulk/block after the confinement is removed. If
the block is compressed again, the minimum stressneeded to achieve sample failure/breakage is called theunconfined yield strength, σc. Note that the sample stresspaths in uni-axial testers and shear testers are different,
but the stress states could be linked using Mohr’s Circle.
The curve σc = f(σ1) is called flow function in powder engineering, which can be used to characterize material

flowability, ffc = σ1/σc (Schulze, 2008). The flowability isdefined as follows:• ffc < 1
not flowing• 1 < ffc < 2 very cohesive• 2 < ffc < 4 cohesive• 4 < ffc < 10 easy flowing• ffc > 10
free flowing
In Fig. 22, we plot the flow functions for 7 limestone
powders. As we can see, our powders cover almost thewhole range of flowability, from cohesive to free flowing.
In the stress range we investigated, σc increases for all thesamples with increasing σ1. As expected, the slope of theincrease trend becomes higher with decreasing particle
size, with the maximum slope of Eskal300 (minimum
particle size). The flowability of a certain powder depends
not only on the major consolidation stress σ1, but also on
particle size.

7. Conclusion and outlook
In this study, we have systematically examined thepowder flow behaviour of limestone powder samples withvarying median particle sizes in different shear testers at
different confining stress levels. The major goal is to understand the relation between microscopic properties suchas particle size and contact cohesion and macroscopic,
bulk properties such as bulk density, cohesive strengthand shear resistance (characterized by the effective angle
of internal friction, the internal friction at steady state
flow, and the internal friction).
All shear testers investigated show highly repeatable/

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Hao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

reproducible results and good overall, consistent agreement among each other. Direct shear devices (Jenike and
ELE direct shear tester) give the highest standard deviations. The yield loci obtained by the Schulze ring shear
tester (RST-01) are consistently slightly higher than the
results from other testers, which, on the practical side, results in a more conservative but safer silo design. The
shear protocol evidently influences the measurements asshown by comparing the RST-01 and the FT4, where thelatter gives a significantly lower yield locus, which we attribute to a different pre-shear protocol. As a conclusion,
while the automated devices minimize the operator influence, the output should be carefully interpreted, as differences in the protocol can result in considerable deviationsin the measured material response even if the qualitative
trends are found to be consistent among different testers.
In order to study the material behaviour, eight limestone powders with identical chemical composition andmedian particle size ranging from 2.2 μm to 938 μm havebeen tested in a wide range of normal stresses (5, 20 and
35 kPa). Both factors, size and stress, are found to influence the bulk flow significantly. As expected, the bulk
density and cohesive strength increase with increasing
normal stress, the effect being stronger for finer particles.
On the other hand, the angle of internal friction seems to
be unaffected by the normal stress (at least in the range
investigated here), while the effective angle of internal
friction and the steady state angle of internal friction
show a decreasing trend with normal stress.
When we look at the dependence of the macroscopic
flow on particle size, two regimes can be distinguished,
above and below the median particle size of about
150 μm. For the fine particle regime, contact cohesion
dominates the bulk behaviour, the effect getting smallerwith increasing particle size. The bulk density increases
monotonically with particle size, and the bulk cohesion(cohesive strength) decreases to nearly zero. The friction
angles (effective angle of internal friction, angle of internal friction and steady state angle of internal friction),
follow a similar decreasing trend as bulk cohesion.
In the coarse particle regime (150 to 938 μm), the bulk
behaviour is less obvious. The bulk cohesion slightly increases while bulk density increases, then decreases. The
bulk friction angles increase with increasing particle size
up to values comparable to those of the finest powders. In
order to check the effect of small particles in this regime,
fines are removed from the coarse samples via air sieving.
This results in a significant reduction in bulk density andbulk cohesion, while the bulk friction angles are barely
affected. This proves that the fine particles being the main
source of cohesion. The competition between contact cohesion and geometrical effects can explain the transition
between the two regimes. For dry powders consisting oflarge particles, the inter-particle cohesive forces, espe-

242

cially the van der Waals forces, become negligible. Theinterlocking between particles due to the surface roughness and shape dominates the bulk behaviour of coarse
samples, while cohesion is the key contribution that governs the shear strength of fine powders. The geometricalinterlocking effect is further enhanced by the increase of
the bulk density for coarse samples. On the other hand,
low density is associated with small median particle size,due to the presence of clusters and large pores.
For the sake of completeness, we also look at the flow
behaviour of our powders, as relevant for the silo-design
procedure. Overall, the flowability increases when increasing normal stress (powders become more free flowing) for finer samples, with the effect becoming weakerfor coarse samples that are more free flowing anyway.
The present paper is the beginning of a collection ofexperimental data that, in the future, can be enriched withmore data from many more materials of both industrial
and academic interest. Our speculations on the interesting
bulk cohesion and friction behaviour with increasing particle size have to be further investigated. Furthermore,this experimental database can be used as a source for design (e.g. silo) procedures and as a benchmark for further
experimental studies. Last but not least, the development,
calibration and validation of particle models and simulations, especially the DEM contact models, and simulations of element tests (shear tests), require experimental
data as presented here.

Acknowledgement
Helpful discussions with Abhinendra Singh and Bert
Scheper as well as the help from Bruno E. Chávez
Montesareon on experimental set-ups are gratefully acknowledged. This work is financially supported by the
T-MAPPP project of the European-Union-funded Marie
Curie Initial Training Network FP7 (ITN607453); see
http://www.t-mappp.eu/ for more information.

NomenclatureρpParticle density (kg/m3)

ρ0

Initial bulk density (kg/m3)

ρbBulk density (kg/m3)

w

Moisture content (%)

d10

Particle diameter where 10 % of distribution is below
this value (μm)

d50Particle median size where 50 % of distribution is
below this value (μm)

Hao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

d90

Particle diameter where 90 % of distribution is below
this value (μm)Ψ

Roundness ([–])τ

Shear stress (kPa)τss

Steady state shear stress (kPa)τpPeak failure shear stress (kPa)σnNormal stress (kPa)σprePre-shear normal stress (kPa)cCohesive strength of yield locus or bulk cohesion (kPa)css

Cohesive strength of steady state locus (kPa)σcUnconfined yield strength (kPa)σ1

Major consolidation stress (kPa)σ2Minor consolidation stress (kPa)ϕAngle of internal friction (°)ϕeEffective angle of internal friction (°)ϕss

Steady state angle of internal friction (°)

ffc

Flowability ([–])

References
Akers R.J., The certification of a limestone powder for Jenikeshear testing (CRM 116), EUR (Luxembourg), 1992.
Alonso-Marroquin F., Herrmann, H.J., Ratcheting of granularmaterials, Physics Review Letter, 92 (2004) 54301.
Alshibli K.A., Sture, S., Shear band formation in plane strain
experiments of sand, Journal of Geotechnical and Geoenvironmental Engineering, 126 (2000) 495–503.
ASTM-D6128-16, Standard test method for shear testing of bulk
solids using the Jenike shear cell, West Conshohocken, PA:
ASTM International, 2006.
ASTM-D6773-16, Standard shear test method for bulk solids
using the Schulze ring shear tester, West Conshohocken,
PA: ASTM International, 2008.
ASTM-D7891-15, Standard test method for shear testing of
powders using the freeman technology FT4 powder rheometer shear cell, West Conshohocken, PA: ASTM International, 2015.
Bardet J.P., Experimental Soil Mechanics, Prentice-Hall, Upper
Saddle River, New Jersey, 1997.
Berry R.J., Bradley M.S.A., McGregor R.G., Brookfield powder
flow tester-Results of round robin tests with CRM-116
limestone powder, Proceedings of the Institution of
Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 229 (2015) 215–230.
Bi D., Zhang J., Chakraborty B., Behringer R.P., Jamming by
shear, Nature, 480 (2011) 355–358.
Carr J.F., Walker D.M., An annular shear cell for granular materials, Powder Technology, 1 (1968) 369–373.
Casagrande A., The determination of the pre-consolidation load
and its practical significance, Proceedings of the interna-

tional conference on soil mechanics and foundation engineering, 3 (1936) 60–64.
Cates M.E., Haw M.D., Holmes C.B., Dilatancy, jamming, andthe physics of granulation, Journal of Physics: Condensed
Matter, 17 (2005) S2517.
Cundall P.A., Numerical experiments on localization in frictional materials, Ingenieur-Archiv, 59 (1989) 148–159.
Feise H.J., A review of induced anisotropy and steady-state flowin powders, Powder Technology, 98 (1998) 191–200.
Feise H., Schwedes J., Investigation of the Behaviour of Cohesive Powder in the Biaxial Tester, KONA Powder Particle
Journal, 13 (1995) 99–104.
Fitzpatrick J.J., Barringer S.A., Iqbal T., Flow property measurement of food powders and sensitivity of Jenike’s hopper
design methodology to the measured values, Journal of
Food Engineering, 61 (2004) 399–405.
Freeman R., Measuring the flow properties of consolidated,conditioned and aerated powders—A comparative study
using a powder rheometer and a rotational shear cell, Powder Technology, 174 (2007) 25–33.
Freeman R.E., Cooke J.R., Schneider L.C.R., Measuring shear
properties and normal stresses generated within a rotational
shear cell for consolidated and non-consolidated powders,
Powder Technology, 190 (2009) 65–69.
GDR-MiDi, On dense granular flows, European Physical Journal E–Soft Matter, 14 (2004) 341–365.
Harder J., Schwedes J., The development of a true biaxial shear
tester, Particle & Particle Systems Characterization, 2(1985) 149–153.
Imole O.I., Paulick M., Magnanimo V., Morgeneyer M., Montes
B.E., Ramaioli M., Kwade A., Luding S., Slow stress relaxation behavior of cohesive powders, Powder Technology,
293 (2016) 82–93.
Janssen R.J.M., Zetzener H., Measurements on cohesive powder
with two biaxial shear testers, Chemical Engineering &Technology, 26 (2003) 147–151.
Jenike A.W., Storage and Flow of Solids, Bulletin No. 123, Bulletin of the University of Utah, 53 (1964).
Jenike A.W., Quantitative design of mass-flow bins, Powder
Technology, 1 (1967) 237–244.
Jenike A.W., Storage and flow of solids. bulletin no. 123, vol. 53,
no. 26, November 1964, Technical report, Utah University,
Salt Lake City (USA), 1976.
Kamath S., Puri V.M., Manbeck H.B., Flow property measurement using the Jenike cell for wheat flour at various moisture contents and consolidation times, Powder Technology,
81 (1994) 293–297.
Kamath S., Puri V.M., Manbeck H.B., Hogg R., Flow propertiesof powders using four testers-measurement, comparison
and assessment, Powder Technology, 76 (1993) 277–289.
Koynov S., Glasser B., Muzzio F., Comparison of three rotational shear cell testers: Powder flowability and bulk density, Powder Technology, 283 (2015) 103–112.
Kumar N., Luding S., Memory of jamming–multiscale models
for soft and granular matter, Granular Matter, 18 (2016)
1–21.
Liu A.J., Nagel S.R., Nonlinear dynamics: Jamming is not justcool any more, Nature, 396 (1998) 21–22.

243

Hao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

Luding S., Anisotropy in cohesive, frictional granular media,
Journal of Physics: Condensed Matter, 17 (2005a) S2623–
S2640.
Luding S., Shear flow modeling of cohesive and frictional fine
powder, Powder Technology, 158 (2005b) 45–50.
Luding S., Cohesive, frictional powders: contact models for tension, Granular Matter, 10 (2008) 235–246.
Luding S., Granular matter: So much for the jamming point,
Nature, 12 (2016) 531–532.
Majmudar T.S., Behringer R.P., Contact force measurements
and stress-induced anisotropy in granular materials,
Nature, 435 (2005) 1079–1082.
Morgeneyer M., Brendel L., Farkas Z., Kadau D., Wolf D.E.,
Schwedes J., Can one make a powder forget its history?,
Proceedings of the 4th international conference for conveying and handling of particulate solids, Budapest, 2003, pp.
12–118.
Morgeneyer M., Schwedes J., Investigation of powder properties
using alternating strain paths, Task Quarterly, 7 (2003)
571–578.
Rabinovich Y.I., Adler J.J., Ata A., Singh R.K., Moudgil B.M.,
Adhesion between nanoscale rough surfaces: I. Role ofasperity geometry, Journal of Colloid and Interface Science, 232 (2000) 10–16.
Radjai F., Jean M., Moreau J.J., Roux S., Force distribution indense two-dimensional granular systems, Physical Review
Letters, 77 (1996) 274–277.
Radjai F., Roux S., Moreau J.J., Contact forces in a granular
packing, Chaos: An Interdisciplinary Journal of Nonlinear
Science, 9 (1999) 544–550.
Rumpf H., Particle technology, Chapman & Hall, London/New
York, 1990.
Russell A., Müller P., Shi H., Tomas J., Influences of loading
rate and preloading on the mechanical properties of dry
elasto-plastic granules under compression, AIChE Journal,
60 (2014) 4037–4050.
Salehi H., Barletta D., Poletto M., A comparison between powder flow property testers, Particuology, 32 (2017) 10–20.
Savage S.B., Hutter K., The motion of a finite mass of granularmaterial down a rough incline, Journal of Fluid Mechanics,
199 (1989) 177–215.
Schulze D., Entwicklung und Anwendung eines neuartigen
Ringschergerätes, Aufbereitungs-Technik, 35 (1994) 524–
535.
Schulze D., Flow properties of bulk solids (v), Deutsche Keramische Gesellschaft und Nederlandse Keramische Vereniging, Annual Meeting 2002, Eindhoven., 2002, pp. 21–23.10.
Schulze D., Time- and velocity-dependent properties of powders effecting slip-stick oscillations, Chemical Engineering& Technology, 26 (2003a) 1047–1051.
Schulze D., Towards more reliability in powder testing (v), Proceedings of the 4th international conference for conveying

244

and handling of particulate solids (CHoPS), Budapest,
2003b, pp. 5–31.
Schulze D., Powders and bulk solids: behavior, characterization,
storage and flow, Springer, 2008.
Schulze D., Round robin test on ring shear testers, Advanced
Powder Technology, 22 (2011) 197–202.
Schulze D., Beispiele gemessener Fließeigenschaften, in ‘Pulver
und Schüttgüter’, Springer, 2014a, pp. 249–268.
Schulze D., Verfahrenstechnische Siloauslegung, in ‘Pulver undSchüttgüter’, Springer, 2014b, pp. 335–360.
Schwedes J., Vergleichende Betrachtungen zum Einsatz vonSchergeräten zur Messung von Schüttguteigenschaften,
Proceedings of PARTEC, Nürnberg, 1979, pp. 278–300.
Schwedes J., Review on testers for measuring flow properties ofbulk solids, Granular Matter, 5 (2003) 1–43.
Schwedes J., Schulze D., Measurement of flow properties ofbulk solids, Powder Technology, 61 (1990) 59–68.
Shibuya S., Mitachi T., Tamate S., Interpretation of direct shear
box testing of sands as quasi-simple shear, Geotechnique,47 (1997) 769–790.
Singh A., Magnanimo V., Saitoh K., Luding S., Effect of cohesion on shear banding in quasistatic granular materials,
Physical Review E, 90 (2014) 022202.
Teunou E., Fitzpatrick J.J., Synnott E.C., Characterisation offood powder flowability, Journal of Food Engineering, 39(1999) 31–37.
Thakur S.C., Ahmadian H., Sun J., Ooi J.Y., An experimental
and numerical study of packing, compression, and caking
behaviour of detergent powders, Particuology, 12 (2014)
2–12.
Tomas J., Product design of cohesive powders – Mechanicalproperties, compression and flow behavior, Chemical Engineering & Technology, 27(6) (2005) 605–618.
Tsunakawa H., Aoki R., Measurements of the failure propertiesof granular materials and cohesive powders, Powder Technology, 33 (1982) 249–256.
Van Hecke M., Jamming of soft particles: geometry, mechanics,
scaling and isostaticity, Journal of Physics: Condensed
Matter, 22 (2009) 033101.
Witt W., Altrogge D., Rutsch O., High speed image analysis anddispersion for size and shape characterisation on fibres,
Proceedings of 5th World Congress of Particle Technology,
2006.
Wolf B., Scirocco R., Frith W.J., Norton I.T., Shear-induced
anisotropic microstructure in phase-separated biopolymer
mixtures, Food Hydrocolloids, 14 (2000) 217–225.
Yang Y., Fei W., Yu H.-S., Ooi J., Rotter M., Experimental studyof anisotropy and non-coaxiality of granular solids, Granular Matter, 17 (2015) 189–196.
Zetzener, H. Schwedes, J., Relaxation and creep of dry bulk
solids, Particle & Particle Systems Characterization, 19(2002) 144–148.

Hao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

Appendix A. Test details on yield locus and steady state locus
Table A1 Summary of pre-shear/shear normal stress values used in each shear device to measure yield locus.
DeviceSamples

Normal stress applied (kPa)

Eskal 300, 500, 15, 30,
80, 150, K0.1–0.5

Pre-shear at 5
Shear at 0.5, 1, 1.5, 2, 3Eskal 300, 500, 15, 30,
80, 150, K0.1–0.5, K0.5–0.8

Pre-shear at 20
Shear at 2, 5, 8, 12, 16

Eskal 300, 500, 15, 30,
80, 150, K0.1–0.5

Pre-shear at 35
Shear at 2, 5, 10, 15, 20

RST-XS

Eskal 300, 500, 15, 150

Pre-shear at 4.3
Shear at 0.35, 0,85, 1.4, 2.1, 3.6

DST

Eskal 300, 500, 15, 150

Pre-shear at 36.1
Shear at 1.4, 13.9, 19.4, 25, 30.5

FT4

Eskal 300, 500, 15, 150

Pre-shear at 20
Shear at 0.1, 0.5, 1, 2, 5, 8, 16

JenikeEskal 300, 150

Pre-shear at 5
Shear at 0.5, 1.5, 3

RST-01

Table A2 Summary of normal stress values applied using direct shear tester (DST) to measure steady state locus.
Samples

Normal stress applied (kPa)

Eskal 300, 500, 15, 150

1.4, 2.8, 4.2, 5.5, 6.9, 8.2, 9.6, 11, 12.3, 13.9, 19.4, 25, 30.5, 36.1

Eskal K0.1–0.5

13.9, 36.1

Eskal K0.5–0.8

13.9, 19.4, 25, 30.5, 36.1

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Hao Shi et al. / KONA Powder and Particle Journal No. 35 (2018) 226–250

Appendix B. Test results of all the powders and devices shown in this paper
Table B1 Data measured from RST-01 for several Eskal powders and different pre-shear stresses.
DeviceSampleK0.5–0.8

K0.1–0.5

Eskal150

Eskal80d50 (μm)
938

223

138

71

RST-01
Eskal30

Eskal15

Eskal500

Eskal300

30

19

4.42

2.22

σpre (kPa)c (kPa)σ1 (kPa)σc (kPa)ρb (kg/m3)

ϕe (°)ϕ (°)ϕss (°)

5

0.08

11.49

0.33

1288.00

41.37

40.57

38.97

20

0.23

45.77

0.51

1275.67

42.53

42.37

40.30

35

0.06

88.49

0.27

1299.67

42.30

42.23

41.20

5

0.33

9.47

1.33

1463.33

40.37

37.00

35.87

20

0.45

39.23

1.82

1506.00

38.67

37.60

35.90

35

0.58

70.17

2.33

1531.67

38.60

37.87

36.27

5

0.01

8.53

0.06

1386.00

32.93

32.22

31.00

20

0.10

35.34

0.31

1392.33

33.33

33.17

31.37

35

0.21

66.07

0.19

1400.33

33.93

33.87

31.67

5

0.08

8.88

0.31

1319.33

34.43

32.80

31.87

20

0.07

35.02

0.25

1341.67

33.10

32.97

31.10

35

0.19

63.9

0.68

1356.33

32.77

32.50

31.53

5

0.09

8.83

0.31

1309.67

33.03

32.17

31.37

20

0.14

34.84

0.49

1331.00

33.07

32.73

31.00

35

0.20

62.20

0.74

1342.00

32.67

32.40

31.07

5

0.21

9.44

0.82

1247.00

36.73

34.63

34.13

20

0.34

37.08

1.23

1257.67

35.77

34.97

33.77

35

0.42

64.34

1.31

1262.00

35.13

34.67

33.00

5

0.86

10.47

3.25

1011.33

44.43

36.30

39.53

20

1.76

39.45

5.44

1157.67

39.87

35.70

36.60

35

1.97

67.79

6.17

1190.00

39.33

37.20

36.03

5

1.52

11.33

6.21

760.67

51.20

36.97

43.53

20

3.59

43.06

12.97

861.00

43.87

36.37

39.93

35

4.57

72.81

17.82

932.33

43.47

38.43

39.17

Table B2 Data measured from RST-XS, FT4 and DST for several Eskal powders and different pre-shear stresses.
Device

RST-XS

FT4

DST

Jenike246c (kPa)σ1 (kPa)σc (kPa)ρb (kg/m3)

ϕe (°)ϕ (°)ϕss (°)

0.01

7.67

0.13

1447.67

34.13

32.00

29.93

0.07

7.91

0.26

1416.67

34.57

33.80

32.53

0.41

8.70

0.93

1015.00

40.83

38.33

37.50

2.22

1.09

9.39

4.16

767.67

50.90

39.03

42.97

138

0.12

30.88

0.43

1441.45

33.75

33.41

24.91

Sampled50 (μm)

Eskal150

138

Eskal15

19

Eskal500

4.42

Eskal300
Eskal150
Eskal15

19

Eskal500

4.42

Eskal300

σpre (kPa)

4.3

0.20

32.57

0.75

1297.10

33.51

32.95

29.82

0.75

36.68

2.94

1081.57

37.59

35.68

34.16

2.22

1.92

41.06

7.75

782.16

41.82

37.20

38.21

Eskal150

138

0.86

59.83

1.95

1429.09

32.61

31.00

31.22

Eskal15

19

1.30

60.83

3.10

1281.59

35.83

34.08

34.91

Eskal500

4.42

2.13

61.33

7.40

1204.08

37.60

34.61

35.24

Eskal300

2.22

3.67

64.47

10.07

952.30

42.01

37.21

38.27

Eskal150

138

0.22

18.17

0.35

1445.63

35.31

34.13

32.09

Eskal300

2.22

1.71

11.30

7.17

788.91

47.95

33.83

37.95

20

36.08

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Appendix C. The explanation on the graphical abstract

Fig. C1: Steady state bulk friction, μss = tan(ϕss), plotted against median particle size, d50. Solid line is the fitted func-tion, μ, in Eq. (1C). Orange and purple dashed lines represent contributions from inter-particle cohesion and geometrical/inter-locking, respectively.

In Fig. C1, we have plotted the same data as shown in Fig. 20(b), but with a proposed theory which fits the data withσpre = 20 kPa: dd μ  μ0 1  cμ  50   d 50 d gμ 

(1C)where, the fitted values are μ0 = 0.57, dcμ = 1.12 μm and dgμ = 1790 μm with “c” denoting cohesion and “g” geometry.
In Fig. C1, the curve μ1 represents the first contribution inversely proportional to d50 due to inter-particle cohesion, which
decays to zero with increasing particle size and it has the same power law as the cohesive strength, see Fig. 19(b). In contrast, the second term μ2 is an empirical relation due to contributions from particle geometrical/inter-locking, which increases with particle size. The combination of these two contributions gives the total steady state bulk friction of thelimestone powders in Eq. (1C).

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Author’s short biography
Hao ShiHao Shi is a PhD candidate in the MSM (Multi-Scale Mechanics) group at the facultyof engineering technology (ET) chaired by Prof. Stefan Luding at University of Twente,
the Netherlands. He completed his BEng degree in refrigeration and air-conditioning engineering at Nanjing Institute of Technology (2011), China. He received his MSc degree
in chemical and energy engineering at Otto-von-Guericke University (2013), Magdeburg,
Germany, where he worked in the mechanical process engineering group chaired by
Prof. Jürgen Tomas. Later, he joined the MSM group in 2014 for his PhD study which isbased on the Marie Curie training network “T-MAPPP”. His research interests range
from tabletting processes for cohesive powders to discrete element simulations of granular assemblies with the development of calibration and validation protocols as well asother industry-relevant research studies. He collaborates with other researchers in various institutions and industries including TU Braunschweig in Germany, UT Compiegne
in France, P&G in UK and the university of Edinburgh in UK.

Rahul Mohanty
In 2013, Rahul Mohanty completed his master studies in Material Resource Engineering at AcSIR University, India. In the same year, he joined CSIR-IMMT, India, as a
Quick Hire Scientist for a one-year internship. In September 2014, he joined iPAT—research group “Bulk Solids and Granular Matters” as a research associate in TU Braunschweig, Germany. Later in September 2015, he moved to P&G UK, Newcastle,
continuing his research as a research scientist based on the Marie Curie training network“T-MAPPP”. His research interest is to investigate the dry as well as wet contact adhesion for the chosen processes, in order to develop a DEM model for quasi-static and dynamic processes and validation against simple tests, and to develop an upscaling
procedure from a DEM particle model to process a scale compartment model.

Somik Chakravarty
Somik Chakravarty completed his BEng in mechanical engineering at the Universityof Sheffield and MSc in Thermal power and fluids engineering at the University of Manchester, UK. He is presently on an EU FP7 Marie Curie fellowship (T-MAPPP) working
as an early stage researcher at the University of Technology of Compiègne (UTC),
France, in the field of characterization of mechanical properties of bulk solids. His research interests include powder handling and processing, characterization of powders by
their flow properties and dustiness. He collaborates with researchers in academia and industry including TU Braunschweig, BASF, INERIS, and the University of Twente.

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Author’s short biography
Ramon Cabiscol Martinoli
Ramon Cabiscol studied chemical engineering from 2008 to 2013 at the Institut
Químic de Sarrià in Barcelona. He received a DAAD scholarship in 2013 for postgraduate students to perform a research internship at the Technische Universität Braunschweig. His scientific interests include powder handling and flowability, tableting
technology and numerical modelling of compaction. He is currently part of the Marie
Curie training network “T-MAPPP”. He is carrying out his PhD on “Modelling of abrasion of pharmaceutical tablets” at the Institute for Particle Technology and the Center for
Pharmaceutical Engineering (PVZ), both in Braunschweig.

Martin Morgeneyer
Martin Morgeneyer works at Compiègne University of Technology (UTC), France,and his research focuses on powder and particle properties. He studied in Braunschweig,
Compiègne and Zaragoza, received his degree in mechanics and his PhD in powder mechanics from the Technical University of Braunschweig, Schwedes’ group. Prior to joining UTC as VP International Relations, Morgeneyer worked at Unilever in Warrington,
and was responsible for internationalization at the Faculty of Mechanical Engineering at
Braunschweig, of which he became the managing director later on. He now serves aschair of the Working Party on Characterization of Particulate Systems at the EFCE.

Harald Zetzener
Harald Zetzener studied mechanical engineering from 1989 to 1996 at the Technische
Universität Braunschweig. He finished his PhD thesis on “Determination of rate-dependent
deformation behaviour of cohesive powders in a bi-axial test” in 2002. He performed a
post-doc at the Telemarks Technical Research and Development Centre in Porsgrunn,
Norway. Afterwards he worked as Supply Quality Manager for Reckitt Beckinser before
assuming the position of Deputy Director of the Institute for Particle Technology. His
field of expertise is particle technology and design of equipment.

Jin OoiWith a BEng (Hons) degree from the University of Auckland and a PhD from the University of Sydney, Jin Ooi joined the University of Edinburgh in 1990 and has been theprofessor of Particulate Solid Mechanics since 2005. His research covers both computational and experimental studies of of powders and solids, from particle phenomena tobulk characteristics, and applications in industrial processes. Jin enjoys collaboration
with academic and industrial partners. He has published extensively with over 150 journal and conference papers and several book chapters. He is on the editorial board for Canadian Geotechnical Journal and Acta Geotechnica, and has co-founded DEM Solutions
Ltd. and Particle Analytics Ltd.

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Author’s short biography
Arno Kwade
Arno Kwade studied mechanical engineering from 1986 to 1992 at the Technische
Universität Braunschweig and the University of Waterloo. He finished his PhD thesis on“Autogenous Grinding in Stirrred Media Mills” in 1996. Afterwards he worked as general manager and executive director before he started his career as full professor for mechanical process engineering in 2005 at the Institute for Particle Technology. He is thehead of the Centre of Pharmaceutical Engineering (PVZ) and member of the board of theAutomotive Research Centre Niedersachsen (NFF). His main research focuses on experimental and numerical investigations in the fields of grinding and dispersing, flow andcompression of powders as well as preparation of particulate coatings.

Stefan Luding
Stefan Luding studied physics at the University of Bayreuth, Germany, on reactions
on complex and fractal geometries. He continued his research and moved to Freiburg for
his PhD on simulations of dry granular materials in the group of polymer physics withProf. A. Blumen. Then he spent his postdoc time in Paris VI, Jussieu, with E. Clément
and J. Duran before he joined the group of Computational Physics with Prof. Herrmann,
where he did his habilitation. In 2001, he moved to DelftChemTech at the TU Delft in
Netherlands as Associate Professor in Particle Technology. Since 2007 he holds the chairon Multi-Scale Mechanics (MSM) at the Faculty of Engineering Technology, ET, at the
University of Twente, the Netherlands, with ongoing research on fluids and solids, particles and their contacts, granular materials and powders, asphalt, composites, bio- andmicro-fluid systems and self-healing materials. Since 1998 he is managing Editor in
Chief of the journal Granular Matter and since 2005 president of AEMMG, the scientificorganizing committee of the Powders & Grains conference series.

Vanessa Magnanimo
Vanessa Magnanimo is an Assistant Professor (UD1) in the Department of Thermaland Fluid Engineering within the Faculty of Engineering Technology at the University ofTwente. She is part of the Multi-Scale Mechanics group. Vanessa received her MSc degree in construction engineering from the Politecnico of Bari, Italy, and received her
PhD in Continuum Mechanics from the same university. After her PhD and before joining the University of Twente as a postdoc in 2010, she worked as a consultant in a structural engineering firm. She was a visiting scientist at the Levich Institute—CCNY and
at T&AM—Cornell University. Vanessa is currently principal investigator in EU- andindustrially-funded projects. She was part of the editorial board for Géotechnique andPowder Technology and is presently chair of the Female Faculty Network Twente. Vanessa’s broad research interests are primarily in the area of theoretical analysis and modern
simulation techniques applied to constitutive modelling of materials with an internal
micro-structure such as soils and powders.

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KONA Powder and Particle Journal No. 35 (2018) 251–257/Doi:10.14356/kona.2018016

Original Research Paper

Forces on Particles in Time-Varying Magnetic Fields †Jaclyn D. Ray, James R. Nagel, Dave Cohrs and Raj K. Rajamani *1

Department of Metallurgical Engineering, University of Utah, USA

Abstract
Electrodynamic sorting is a process that sorts metals based on conductivity, density, and geometry. The process
works by inducing electrical eddy currents within particles placed in a time-varying magnetic field. For the
special case of a perfect, uniform sphere, an approximate equation can be used to predict the net force under alinear magnetic gradient. This paper explores the accuracy of that model by measuring the net force on sphericalsamples of copper, brass, and aluminum with varying sizes and excitation frequencies. Results consistently show
strong agreement with the approximate models over all conditions. We also explore several non-sphericalgeometries, including cylinders, cubes, and disks. We found that they could be modeled as equivalent spheres,
given an appropriate radius, and had reasonable accuracy over frequency.
Keywords: electrodynamics, eddy current, time-varying magnetic field, scrap metal waste

1. Introduction
Scrap metal recycling is a high-value industry that reduces pollution from primary production. As it can potentially be recycled an infinite number of times, scrap metal
may even eliminate the mining of some metals altogether.
This factor alone is significant since reducing the primary
production of metals is becoming an essential means ofdecreasing man-made pollutants that aggravate the environment (Förstner et al., 2012). In 2016, for example, aluminum recovered from old scrap was equivalent to about
31 % of apparent consumption while copper scrap contributed similar values to the total US supply (USGS,
2017). Such low percentages of recycled material reveal
the importance of investing in scrap metal recycling.
Since the value of scrap metal depends heavily on purity, a key aspect of the recycling process is sorting. Obtaining high-grade metal, however, can be economicallydifficult for many reasons. Alloys, for example, often
have nearly indistinguishable properties and are thus difficult to tell apart. Furthermore, the material feedstock
might vary from day-to-day. Automobiles, for instance,
have changed dramatically in composition since the 1980s
and continue to do so today (Wernick and Themelis,1998). Consequently, there is strong economic incentive
to find efficient new methods for purifying scrap metal.
†
1*

Received 8 May 2017; Accepted 1 August 2017
J-STAGE Advance published online 30 September 2017
135 S 1460 E, ROOM 412, Salt Lake City, UT 84112-0102, USA
Corresponding author: Raj K. Rajamani
E-mail: raj.rajamani@utah.edu
TEL: +01-801-587-8329

To meet this challenge, several technologies exist to recover metals from mixed material streams. Magnetic separators, for example, remove ferrous material through theuse of fixed permanent magnets (Oberteuffer, 1974).
Dense media separation recovers certain nonferrous metals by separating light elements from the heavy (Weiss,1985). Mechanical eddy current separators recover electrically conductive metals from non-conductive materials
by rotating a drum of alternating north/south magnets(Rem et al., 1998). Metallic particles entering the magnetic
field are excited with electrical eddy currents, which inturn accelerate the particle due to magnetic forces against
the moving electrical charge. Even hand sorting by visualinspection can be effective in certain developing countries where the cost of human labor is very low (Wilson etal., 2006).
Despite the many available technologies, material recovery is still very limited. For example, magnetic separators can only recover ferrous materials from nonferrous.
Density separation cannot distinguish between alloys
with similar densities. Mechanical eddy current separators are generally only effective on particles greater thanan inch in size and when the materials that are being separated have significantly different conductivity (Norrgran
and Wernham, 1991). Hand sorters cannot easily distinguish between metals that look alike nor can they effectively process small particles in large quantity.
One emerging technology that addresses many of these
problems is electrodynamic sorting (EDX) (Dholu et al.,2017; Smith et al, 2017). The process is similar to mechanical eddy current separation but, rather than spin an arrayof permanent magnets, it utilizes a fixed electromagnet.

Copyright © 2018 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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F(m  B) .
Unlike mechanical eddy current separators, however,(3)
EDX can reach far higher frequencies of excitation andthus operate on particles well below an inch in size. The
It is important to note that Eqn. 2 is only a first-ordertunability of frequency and intensity also allows for sepaapproximation derived under the assumption of a linear
ration as a function of density, conductivity, and even gemagnetic field gradient. It also shows that a uniform magometry.
netic field will produce no net force since the quantity
Although the basic principle of EDX has been demonm·B becomes constant. We therefore introduce a linear
strated empirically, there does not yet exist a clear mathegradient α to the magnetic field such that B = (B0 + αx)ẑ.
matical framework by which to model the forces on scrap
The gradient α is assumed to introduce only a small permetal particles. The most relevant contributions to dateturbation, meaning that m does not change significantly
appear to stem from Peter Rony (1964) and George
in the applied gradient. Substituting back into Eqn. 2
Lohöfer (1989), both of whom studied the heating effects
therefore revealsof eddy current induction on uniform spheres. More reF[m z B0  αx]
(4)cently, Bidinosti et al. (2007), developed a workablemodel for the eddy current distribution throughout a uni
form metal sphere in a time-varying magnetic field. The F[m z B0  m zαx] xˆ
(5)
x
recent work of Nagel (2017) has also helped to formalize
the theory of eddy current induction in various canonicalF  m zα xˆ .
(6)geometries. To date, however, there still has yet to be any
direct application of this theory to the field of scrap metal
Noting that F is still a phasor quantity in sinusoidal
steady state, we next calculate the time-averaged force
recycling.
using
This paper seeks to validate the theoretical predictionsof forces acting on metal particles in a time-varying mag1
netic field. We begin by reviewing the relevant theory on(7)
Favg  Re{F },2the subject and modeling the net force acting on a uniform
metal sphere. We then test that model by measuring thewhere Re{x} denotes the real part of x. After some lengthy
forces on several spherical particles under excitation byderivation, the time-averaged force finally evaluates to
an EDX magnet. Lastly, we expand on that analysis by fit3πB0αa 3  1 1 sinh q  sin(q) ting the same equations to non-spherical geometries in an(8)
Favg 
 3  q cosh q  cos(q)  xˆ ,μ0effort to quantify the behavior of more realistic particles.
Results show that even non-spherical particles can be reawhere q = 2α/δ and δ  2 / (ωμ0σ ) is the skin depth.
sonably represented by spheres, thus greatly enhancing
our ability to predict the behavior of scrap metal particles
as they travel through an EDX magnet.
3. Method

2. Theory
We consider a sphere with known radius a and conductivity σ situated in a uniform magnetic field B = B 0cos(ωt)ẑ. Since the excitation field is in a sinusoidal steadystate, we can express this using phasor notation as simply
B = B0ẑ. Building on the work done by Rony (1964), themagnetic dipole moment m of the sphere can be shown tosatisfym

2πB0a 3 
ka cosh ka  sinh ka 
1  3 zˆμ0 
ka 2 sinh kam  m z zˆ ,

(1)
(2)

where k  jωμ0σ and μ 0 is the permeability of freespace. Due to the presence of the applied magnetic field
B, there also exists a net force F acting on m, given byJackson (1999)

252

Fig. 1 shows a diagram of the experimental configuration. A signal generator sets a desired frequency and voltage, which is then fed to a high-current amplifier. In orderto negate the high impedance from the magnetic induc-Fig. 1

Schematic representation of the force measurement circuit.

Jaclyn D. Ray et al. / KONA Powder and Particle Journal No. 35 (2018) 251–257

Fig. 2

NiZn magnet and force gauge used for experiment.

tance, a capacitor bank is placed in series with the inductor to create a resonant RLC circuit. A 1.0-Ω resistor isalso placed in series with the capacitors to serve as acurrent-­sense resistor for the entire circuit.
A custom-built 360-mm NiZn toroid magnet and aMark-10 force gauge were used for our measurements.
Depicted in Fig. 2 the magnet is wound with 300 turns,
using 18-gauge Teflon-insulated stranded-copper wire. At
one end of the magnet, a specialized air gap was cut out
so as to channel the magnetic field into a small volume ofspace. Once the system was activated, any test particles
placed inside the gap were accelerated into the force gauge,
thereby producing a force measurement. To negate gravity, the test particles were also glued to non-conductive
string and suspended in the gap.
Because the probe on the force gauge is made out of
metal, it could not be placed near the magnetic gap during
excitation. To address this issue, a 3D-printed plastic extender was attached to the force gauge. The extender wasthen placed directly in front of the test particle, thereby
catching it as soon as it was acted on by the magnetic
field. The force then transferred directly down the rigid
extender and into the gauge, resulting in a reliable force
measurement.
Fig. 3 shows some metal samples used for our measurements. Though the theoretical model is technically
only supposed to apply to spheres, industrial scrap metals
rarely present as such perfect shapes. We were therefore
particularly interested in testing the validity of Eqn. 8 on
non-spherical geometries. The particle sizes used in thisexperiment ranged from 5 to 13 mm to represent typicalsizes of fine scrap material. Each sample was also madefrom different metals and alloys, including copper, brass,
and aluminum, which are commonly found in industrial
scrap. For each metal shape, we likewise printed a uniqueplastic extender to fit the geometry. For example, an extender with a concave end would fit the spheres and cylinders, a flat end would hold the cubes, and a U-shaped end
would steady the disks.
Fig. 4 shows the magnetic field profile that was measured at 10-A DC down the centerline of the gap. The

Fig. 3Fig. 4

Some test particles used in the force experiment.

Magnetic field versus position at DC. The vertical lines
indicate the volume of space where test particles were
measured.

peak of the field at x = 0 indicates the rear of the gap at
the inner radius to the toroid. Measurements at several
frequencies between 0–10 kHz also showed a fairly consistent field profile over the bandwidth of interest. The
vertical bars indicate the region where test particles wereinserted and measured. This specific region was chosen
due to its approximate linearity, high field intensity, andphysical space into which the particles could fit.
Though the field profile was consistent across frequency, we did notice that the magnetic field decreased
when particle samples were placed within the gap. This
problem was caused by the eddy currents induced in thetest sample itself, which tended to oppose the appliedmagnetic field of excitation. As a result, less magnetic
flux would bridge the gap, thereby lowering the total inductance of the circuit. With the inductance lowered, theresonant frequency of the RLC circuit would shift slightly
and thus lower the total drive current across the coils.

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Since the excitation field is directly proportional to drive
current, we compensated for it by simply increasing thedrive voltage until the current reached its pretest amplitude.
Another problem we encountered during our measurements was thermal instability. When excited by a magnetic field, induced eddy currents tended to dissipate agreat deal of heat throughout the particles. Even thoughmeasurements lasted for only a few seconds, the particle’s
temperature would often jump to over 100 °C. Since conductivity tends to somewhat vary with temperature, there
was some worry about thermal consistency over thecourse of several measurements. To alleviate such concerns, all particles were immersed in a cup of ice water toensure stable and reproducible temperatures before eachtest. Measurements were then repeated four times to ensure accuracy.

4. Results and Discussion
The first set of experiments focused solely on thespherical particles, with parameters displayed in Table 1.
The radius r of each sphere was measured using a caliper.
The magnetic field intensity B was measured from thecenter of the sphere using a Gauss probe and fixed to avalue of 49.5 mT peak (or equivalently, 35 mT RMS) over
all experiments. The field gradient α was then obtained by
calculating the central difference around the center of
each sphere. Note that there are small differences in αeven though each measurement had the same magnetic
field intensity. These differences are due to variations in
the particle’s placement in the gap, which was primarily
determined by its size. Lastly, electrical conductivity σ ofeach particle was measured with a Fisher Sigmascope
conductivity probe. Results from the spherical force measurements are summarized in Fig. 5 and strongly agreewith the predictions of Eqn. 8.

Table 1 Test parameters used in the force calculations ofsphere samples.
Materialr [mm]

B [mT]

α [T/m]σ [MS/m]

Al 2017

2.8

49.5

–1.7

16.1

Al 6061

6.1

49.5

–1.8

25.5

Al 2024

6.3

49.5

–1.7

17.3

Al 1100

6.3

49.5

–1.7

24.3

Brass

3.2

49.5

–1.7

13.8

Brass

9.5

49.5

–1.8

12.7

Copper

2.8

49.5

–1.8

46.6

Copper

7.5

49.5

–1.8

49.6

254

Fig. 5

Spherical force measurements compared to analytic
calculations.

While encouraging, it is important to remember that
scrap metal waste is rarely spherical. At the same time
however, due to the strong predictability and convenienceof Eqn. 8, we would still like to try and approximate
non-spherical geometries as spheres. To that end, we notethat for any arbitrary geometry at a given excitation frequency, there exists a hypothetical sphere which will experience the same force under identical conditions. If theradius of such a sphere were to remain consistent over alarge bandwidth, then we can use that sphere as an approximate model for the non-spherical particle. To test
this hypothesis, we measured the force on several non-­spherical geometries and plotted their frequency response
against an ideal sphere with an appropriate radius.
To derive an equivalent spherical radius, we began bycalculating the equivalent volume of some non-sphericalparticle. For example, a cylinder could satisfy
2 h
πrcyl

4 3
πrs ,
3

(9)

where rcy1 is the measured radius of the cylinder, h is thecylinder height, and rs is the radius of some equal-volume
sphere. Solving for rs, we haveJaclyn D. Ray et al. / KONA Powder and Particle Journal No. 35 (2018) 251–257

rs  34 2
rcylh .
3

(10)

We then multiply rs by a correction coefficient ε to findr0  εrs ,(11)

where r0 is the equivalent radius of a sphere that would
produce the same force as the measured particle underidentical conditions. If ε < 1, then it can be understoodthat r 0 < rs, thus implying a lower force density thanwould have been achieved if the particle were compacted
into a sphere of equal volume. Likewise, for ε > 1, theparticle has a higher force density than its equal-volume
sphere. To find ε for a given particle, we simply searchedover increments of 0.01 until the theoretical curve generated by Eqn. 8 reasonably fit the measured data.
Results of this experiment are summarized in Fig. 6–8
with the parameters for each experiment summarized inTables 2–4. For the cylinders, we found that ε was generally between 0.95–1.05. The only exception was a smallbrass cylinder, which may have been an experimental
outlier. Cubes, however, were consistently between 0.92–
0.99. The disks consistently resulted in ε values well
above 1.2, which is most likely the result of their highcross-sectional area relative to their volume. If the disks
were instead oriented along their minimum cross-section,then ε would naturally decrease accordingly. The key
finding here, however, is that once a suitable r0 was derived, Eqn. 8 seemed to produce a very good fit to themeasured data. This seems to strongly indicate that evennon-spherical particles can, in principle, be modeled interms of some equivalent sphere over a large bandwidth.

Fig. 6

Cylinder force measurements compared to analytical
calculations.

In summary, we found that Eqn. 8 very accurately predicts the expected force on conductive spheres in the presence of a time-varying magnetic field. We also found that,given the appropriate equivalent radius, non-spherical geometries could likewise follow curves similar to Eqn. 8.
Such knowledge has tremendous practical application in
the field of magnetic separation of nonferrous metals.
To illustrate, consider the limit as F→∞. Since the net
force found in Eqn. 8 is a function of the product between
conductivity and frequency, all particles of similar geometry must eventually converge to the same value. Density,
however, is a fixed property of the material itself and does
not vary. For example, copper is roughly three times
denser than aluminum, meaning an aluminum particle

Fig. 7

Cube force measurements compared to analytical calculations.

Fig. 8Disk force measurements compared to analytical calculations.

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Table 2 Test parameters used in the force measurements ofcylinder samples with radius r and height h.
Materialr [mm]

h [mm]

B [mT]Al 2017

3.0

6.1

49.5

–1.7

25.1

Al 6061

6.4

13.1

49.5

–1.8

12.8

Brass

3.3

6.2

49.5

–1.8

12.8

Brass

6.3

13.1

49.5

–1.7

12.8

Cu alloy

3.4

6.2

49.5

–1.7

54.1

Cu alloy

6.3

12.4

49.5

–1.7

50.1

α [T/m] σ [MS/m]

Table 3 Test parameters used in the force measurements ofcube samples with side length ℓ.
Materialℓ [mm]

B [mT]

α [T/m]σ [MS/m]

Al 6061

5.5

49.5

–2.3

25.1

Al 6061

11.3

49.5

–2.0

25.0

Brass

5.6

49.5

–2.3

12.8

Brass

11.7

49.5

–2.3

12.8

Copper

5.5

49.5

–2.3

54.0

Copper

11.5

49.5

–2.0

54.1

Table 4 Test parameters used in the force measurements of
disk samples with radius r and height h.
Materialr [mm]

h [mm]

B [mT]

α [T/m] σ [MS/m]

Al 7075

4.5

1.7

49.5

–1.5

18.2

Copper

5.0

1.7

49.5

–1.3

54.1

Brass

4.7

1.9

49.5

–1.9

12.8

will experience three times the acceleration under thesame magnetic field. As was demonstrated by Dholu(2017), this allows us to separate aluminum from copperby simply throwing the aluminum particles a much further distance. Further research will be necessary to explore the practical limits of this concept on real-world
industrial applications.

Acknowledgements
This work was funded by the United States Advanced
Research Project Agency – Energy (ARPA-E) METALSProgram under cooperative agreement grant DE-AR0000411.
We would also like to thank Jake Salgado for 3D printing
many of the necessary equipment and Dawn Sweeney forher insightful edits.

256

References
Bidinosti C.P., Chapple E.M., Hayden M.E., The sphere in a
uniform RF field—Revisited, Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering, 31B (2007)
191–202.
Dholu N., Nagel J.R., Cohrs D., Rajamani R.K., Eddy current
separation of nonferrous metals using a variable-frequency
electromagnet, KONA Powder and Particle Journal, 34(2017) 241–247.
Förstner U., Wittmann G.T.W., Eds., Metal Pollution in the
Aquatic Environment, Springer Science & Business Media,
2012.
Jackson J.D., Ed., Classical Electrodynamics, 3rd Edition,
Wiley, 1999.
Lohöfer G., Theory of an electromagnetically levitated metal
sphere I: absorbed power, SIAM Journal on Applied Mathematics, 49 (1989) 567–581.
Nagel J.R., Induced eddy currents in simple conductive geometries due to a time-varying magnetic field, IEEE Antennas
and Propagation Magazine (accepted, 2017).
Norrgran D.A., Wernham J.A., Recycling and secondary recovery applications using an eddy-current separator, Minerals& Metallurgical Processing, 8 (1991) 184–187.
Oberteuffer J., Magnetic separation: A review of principles,
devices, and applications, IEEE Transactions on Magnetics,
10 (1974) 223–238.
Rem P.C., Beunder E.M., Akker A.J.v.d., Simulation of
eddy-current separators, IEEE Transactions on Magnetics,
34 (1998) 2280–2286.
Rony P.R., The Electromagnetic Levitation of Metals, California.
Univ., Berkeley. Lawrence Radiation Lab. and California.
Univ., Berkeley, Tech. Rep., 1964.
Smith Y.R., Nagel J.R., Rajamani R.K., Electrodynamic eddy
current separation of end-of-life PV materials, in: Zhang L.,
Drelich J.W., Neelameggham N.R. et al. (Eds.), Energy
Technology 2017: Carbon Dioxide Management and Other
Technologies, Springer International Publishing, Cham(2017) pp. 379–386.
USGS (United States Geological Survey), 2017, Mineral Commodity Summaries 2017 <minerals.usgs.gov/minerals/pubs/
mcs/> accessed 03.08.2017.
Weiss N.L., Ed., SME Mineral Processing Handbook, Vol. 2,
Society of Mining Engineers of the American Institute of
Mining, Metallurgical, and Petroleum Engineers, 1985.
Wernick I.K., Themelis N.J., Recycling metals for the environment, Annual Review of Energy and the Environment, 23(1998) 465–497.
Wilson D.C., Velis C., Cheeseman C., Role of informal sector
recycling in waste management in developing countries,
Habitat International, 30 (2006) 797–808.

Jaclyn D. Ray et al. / KONA Powder and Particle Journal No. 35 (2018) 251–257

Author’s short biography
Jaclyn Ray
Jaclyn Ray completed her undergraduate degree in Physics from the University of
Utah in Salt Lake City, in 2015. In 2016, she graduated with MS degree in MetallurgicalEngineering also from the University of Utah. She currently works for Lockheed Martin
Aerospace Skunk Works.

James Nagel
Dr James Nagel completed his undergraduate degree in 2004 and MS degree in 2006,
both in Electrical Engineering, from Brigham Young University in Provo, Utah. He thencompleted his PhD in 2011, also in Electrical Engineering, from the University of Utah
in Salt Lake City, Utah, and was awarded the Stockham Medal of Excellence for conspicuously effective teaching. He now works as a research associate for the University of
Utah, where his research focuses on applied electromagnetics with a specialty in numerical methods.

Dave Cohrs
Dave studied Environmental Science with emphasis on Analytical Chemistry at University of Maryland, Baltimore County in Maryland. He managed water quality laboratories at public aquariums for 16 years and has consulted for aquariums, zoos, andacademia on water chemistry and life support topics. He now works for the University of
Utah as a research associate.

Raj Rajamani
Raj Rajamani has been on the faculty of the Metallurgical Engineering department of
the University of Utah, Salt Lake City, Utah, USA since 1980. Currently he holds the position of professor. His research interest include population balance modeling of tumbling mills, computational fluid dynamics of hydrocyclones, discrete element modelingof semi-autogenous grinding mills, eddy current sorting of metallic particles and modeling of high pressure grinding rolls. He received the Antoine M. Gaudin Award, presented
by the Society of Mining, Metallurgy and Exploration Engineers Inc. in the year 2009.

257

KONA Powder and Particle Journal No. 35 (2018) 258–272/Doi:10.14356/kona.2018017

Original Research Paper

Applicability of Probabilistic Nucleation Modelling
for the Analysis of Microfluidics Data †Florent Bourgeois *, Sébastien Teychené and Béatrice Biscans
1

Laboratoire de Génie Chimique, Université de Toulouse, CNRS, INPT, UPS, Toulouse, France

Abstract
Microfluidics tools have been developing rapidly over the past decade, as they offer unparalleled ability forcontrolling nucleation and tracking crystallisation events inside very large numbers of individual nanolitre-size
droplets. They have demonstrated a significant potential for screening protein crystallization conditions and forthe direct determination of inorganic products solubility curves. The accepted basis for analysing microfluidics
data is the probabilistic nucleation model originally proposed by Pound and La Mer (1952). Given the significanceof this model for the purpose of analysing microfluidics data, the paper conducts a review of its hypotheses, usage
and applicability. A step-by-step derivation of the model equations confirms that the time variation of the
proportion of empty droplets which microfluidics experiments can provide with high accuracy is indeed therecommended method for estimation of nucleation kinetic parameters from microfluidics experiments. The paper
shows that, depending on its implementation, the model predicts different rates of appearance of crystals
inside individual droplets. The paper focuses on two distinct implementation modes, referred to as constantsupersaturation and single nucleation event modes. By confronting model prediction with microfluidics
measurements for eflucimibe in octanol, the paper finds that both modes yield different model predictions,shedding light on the potential and limits of the probabilistic nucleation model for the analysis of microfluidics
data.
Keywords: microfluidics, nucleation, modelling

1. Introduction
Microfluidics devices have become key research tools
in recent years for the screening of the crystallization
conditions of proteins (Selimović et al., 2009), the determination of crystallization kinetics (Laval et al., 2009;
Teychené and Biscans, 2012) and precipitation kinetics(Vitry et al., 2015). The principle of this method is to divide the volume of the studied solution into a large numberof small, independent droplets in an inert oil. These droplets can be produced in specific microfluidics geometries
and their volume and chemical composition can be fixed
in a controlled way. In addition, microfluidics devices allow a rapid mixing of the different compounds, help prevent hydrodynamic dispersion and cross-contamination,and the droplets can be stored in microchannels.
For nucleation studies, this experimental techniquegenerates a great deal of data that permit reliable access†1*

Received 18 May 2017; Accepted 7 July 2017
J-STAGE Advance published online 30 September 2017
4, allée Emile Monso CS84234, 31432 Toulouse, France
Corresponding author: Florent Bourgeois
E-mail: florent.bourgeois@ensiacet.fr
TEL: +33-(0)5-34-32-36-00 FAX: +33-05-34-32-37-00

258

to the kinetics of nucleation. Typically, the frequency of
nucleation events is obtained by counting over time thenumber of drops without crystals (Laval et al., 2009).
When the number of droplets is larger than the number of
impurities initially present in the solution, one can observe homogeneous nucleation in some droplets. Moreover, when all the droplets have the same volume V andfor a small enough V, it is in principle possible to relate
the probability that a droplet contains a crystal to the
nucleation rate (Kashchiev et al., 1994). Measurements ofthe temporal evolution of the fraction of droplets that contain crystals thus permit an estimation of the nucleation
kinetics.
The processing of the data generated by such techniques remains limited, however. Indeed, because of thepresence of a surfactant, an interface as well as some dust
or impurities, the majority of published experimental
studies show that the appearance of crystal nucleation inthese systems is due to two concomitant mechanisms,
namely heterogeneous and homogeneous nucleation. In
general, nucleation data that originate from such experiments are treated either by neglecting the first instance of
nucleation (Dombrowski et al., 2010), by treating thenucleation process in a comprehensive manner without

Copyright © 2018 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/).

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

differentiating between possible nucleation mechanisms(Goh et al., 2010) or by averaging the influence of impurities on the crystallization process (Laval et al., 2009;
Teychené and Biscans, 2011). In addition to the models
developed by Goh et al. (2010) in the case of protein crystallization by evaporation, we propose a probabilistic
model of the nucleation process that allows us to have access to the different nucleation kinetics that are observed
experimentally, to deduce the temporal evolution of thenumber of crystals within the droplets, and also to trace
the influence of “active sites” on nucleation.

2. Probabilistic nucleation model for analysisof microfluidics experiments
2.1 Nucleation model derivation
The nucleation process inside individual droplets canbe analysed using a probabilistic nucleation model. Suchan approach appears in a number of published studies in
the context of microfluidics systems, albeit through different forms and uses. It is revisited here in some detail withthe objective of establishing a sound basis for its applicability and usage in the context of microfluidics nucleation
analysis.
The model first considers two distinct types of droplets,
namely droplets with active nucleation sites and droplets
without any nucleation site. Only homogeneous nucleation
events can occur inside droplets devoid of nucleationsites, whereas both homogeneous and heterogeneous nucleation events can possibly take place inside droplets thatbear active nucleation sites.
The nucleation model that results, whereby the first account of the probabilistic nucleation model is credited toPound and La Mer (1952), uses only 3 macroscopic parameters, all of which have solid theoretical bases.
The first model parameter m is the mean number ofactive nucleation sites inside the system’s droplets. Considering that active nucleation sites are identical in all respects and that they nucleate independently of each otherinside a droplet, the probabilistic model considers that active nucleation sites have the same nucleation kinetic ratek (time –1), the model’s second parameter. The third model
parameter is the homogeneous nucleation kinetic rate k0(time –1), which applies to all droplets devoid of nucleationsites, and also to droplets with active nucleation sites ifthey undergo homogeneous nucleation.
To avoid any ambiguity, the term “homogeneous nucleation” that is used throughout this paper was chosen to
keep consistent with the original definition by Pound and
La Mer (1952). It refers to nucleation that occurs in thevolume of the droplet, as opposed to “heterogeneous nucleation” which is understood to take place on the surfaceof nucleation sites. The nucleation mechanism associatedwith the term k0 is therefore not to be mistaken for the homogeneous nucleation rate defined in Classic Nucleation
Theory (CNT). This point, which has already been
pointed out by several authors (Laval et al., 2009; Akellaet al., 2014) in relation to probabilistic nucleation modelling, will be further discussed in section 3 of the paper.
Since we have no reason to expect interdependence ofthe droplets inside our microfluidics system – the system
is designed so that two droplets have no interaction witheach other – then a Poisson process is a suitable candidatefor describing the statistics of nucleation events that occur
within individual droplets. This simple statement justifies
application of the Poisson statistics, as initially proposedby Pound and La Mer (1952) to model the nucleation process in microfluidics systems.
Considering a system with NT droplets in total, thenumber Np of droplets with p active nucleation sites ispredicted by the Poisson distribution with mean m suchthat:

N p  N T  dpois( p, m) where p  0, (1)where dpois() denotes the probability density function ofm p me , thethe Poisson distribution. Since dpois( p, m) p!
expected fraction of droplets without active nucleationsites is therefore e –m and the number of droplets with active sites is 1 – e –m. Sear (2014) indicates that m should lie
in the range 0.1 to 1. This means that the maximum number of active nucleation sites per droplet that can be expected, with a confidence level of 99 %, is in the range 1
to 4. These values correspond to the 99 % quantiles of the
Poisson distribution with mean m = 0.1 and m = 1, respectively. Given that k0t is the mean number of nucleation
events to occur inside a droplet without active nucleationsites during time period t, the probability that r nucleation
events take place inside such a droplet during time period
t is:dpois(r, k 0t ) where r  0, (2)Such a droplet may produce any number r of nuclei.
Thus, the number of droplets without nucleation sites that
contain r crystals at time t is:
N 0 (r, t ) 
N T  dpois(0, m)  dpois(r, k 0t )where r  0, (3)

The nucleation event that takes place inside a droplet thatcarries p active nucleation sites is a Bernoulli random

 k0 
variable with probability q   for homogeneous
 k 0  pk  pk 
nucleation and 1  q 
 k  pk  for heterogeneous nucle 0ation.

259

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

The probability of homogeneous nucleation is expected
to be significantly lower than that of heterogeneous nucleation, typically one or two orders of magnitude lower.
This explains why Pound and La Mer (1952) neglected thepossibility that a droplet with active nucleation sites may
nucleate homogeneously. Akella et al. (2014) corrected
this assumption and justly accounted for this possibility
in their work. Finally, the probability that r nucleation
events take place inside such a droplet during time periodt is: k0 
 pk  k  pk  dpois(r, k 0t )   k  pk  dpois(r, pkt )
 0

 0

where r  0, (4)The second Poisson density distribution dpois(r, pkt)
could be upper truncated at p, if one assumes that one active nucleation site can produce one nucleus only. The authors chose not to truncate this distribution, assuming thata nucleation site can produce any number of nuclei. The
number of droplets with p nucleation sites that contain r
crystals at time t is therefore:N p (r,t ) N T  dpois( p, m)
 k 0  k  pk  dpois(r, k 0t ) 



 0
  pk dpois(r, pkt )   k 0  pk where r  0, (5)N (r, t ) 
N T  dpois(0, m)  dpois(r, k 0t ) k 0  k  pk  dpois(r, k 0t ) 


 (6)
 N T  dpois( p, m)   0


pk


p 1
dpois(r, pkt )   k 0  pk where r  0, and the number fraction fr(t) of droplets that bear r crystals at time t is:
f r t dpois(0, m)  dpois(r, k 0t )
(7)This equation is the main equation for predicting thestate of the microfluidics system at any time t. For allpractical uses, there is no need to use the analytical expression of the probability density function (PDF) of the
Poisson distribution since it is easily computed by numer-

260

fr 
t e m 

k 0t re k0tr!
 k 0  k 0t r k t 
e 0  m p m  k 0  pk  r !


e 

r


!
p
pk
pkt

    pkt p 1   k  pk  r ! e 

  0


where r  0, (8)

2.2 The case of empty droplets
The time variation of the fraction of empty droplets iswell accepted as a means of estimating nucleation parameters m, k0 and k from microfluidics experimental data.
This section reviews this important practical issue.
From equation (7), the number fraction f0(t) of empty
droplets (r = 0) at time t is:
f 0 t dpois(0, m)  dpois(0, k 0t ) k 0  k  pk  dpois(0, k 0t )  dpois( p, m)   0



pk


p 1
dpois(0, pkt )
 



  k 0  pk Finally, the total number of droplets with r crystals attime t is given by: k 0  k  pk  dpois(r, k 0t )  dpois( p, m)   0



pk


p 1
dpois(r, pkt )
 



  k 0  pk where r  0, 

ical software programs.
However, in order to relate this expression to the analytical expressions that can be found in the literature,some of which are referred to in the following section,
equation (8) gives the analytical equivalent for the number
fraction fr(t) of droplets that bear r crystals at time t.

(9)Or, from equation (8):f 0t e m  e k0t
 k 0  k t  k  pk  e 0 



 
e m   0p!
 pk   pkt 
p 1
 

 e   k 0  pk 



 

mp

(10)

This expression appears different from those publishedby Pound and La Mer (1952), and later by Akella et al.
(2014). The differences are clarified in the following text.
First of all, let us suppose that the droplets are either
without or with active nucleation sites, as was assumed by
Pound and La Mer (1952). Equation (10) becomes:
f 0t e m  e k0t

 m p m e  0  e k0t  1 e  pkt p!
p 1 


(11)

mp



e m  e k0t   e me  pkt p!

p 1 

Besides the case where k >> k0, which hails back to
Pound and La Mer’s assumption, there is no simplification

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

to equations (9) and (10), recalling that they apply to thesituation where droplets with nucleation sites can nucleatehomogeneously or heterogeneously. Akella and Fraden(2014), however, published the following equation underthese assumptions:f 0 t e m  e k0t  exp me kt (12)

It can be shown that this expression is the analyticalexpression for f0(t) that corresponds to the following nucleation model:
f r t dpois(0, m)  dpois(r, k 0t ) dpois( p, m)  dpois(r, k 0  pk  t )
p 1

(13)

where r  0, This equation assigns a nucleation rate (k0 + pk) to theprobability of nucleation of droplets with active sites,
when in actual fact, the probabilities of nucleation are
different depending on whether these droplets nucleatehomogeneously or heterogeneously. This oversight is ofno consequence when predicting the time variation of
fr(t) in the case k >> k0. However, it becomes increasingly
significant when the difference between homogeneousand heterogeneous nucleation rates decreases, leading toincorrect estimates of nucleation parameters from themeasured variation f0(t).
While providing the reader with a step-by-step derivation of the probabilistic nucleation model, this section has
highlighted that one must be careful and use the modelthat precisely matches the assumptions.
This simplifies to the expression derived by Pound and
La Mer (1952):f 0 t e m  e k0t  exp me kt   1

(14)

whose equivalent in terms of Poisson distribution is:
f 0 t dpois(0, m)  dpois(0, k 0t ) dpois( p, m)  dpois(0, pkt )

(15)

p 1

This is particularly critical when using the model to estimate nucleation model parameters from which phenomenological analysis of the nucleation process can be inferred.

2.3 Analysis of probabilistic nucleation modelusage
In addition to differences that may arise from model
assumptions on the final form of the probabilistic nucleation model, differences will also occur depending on
how it is implemented.
Assuming that droplets with active sites can nucleatehomogeneously or heterogeneously, and that nucleation

events can yield any number of nuclei, equations (7) and(8) give the time variation of droplets with r crystals
given nucleation parameters m, k0 and k.
For the sake of clarity, the behaviour and possible usesof this model are discussed below through numerical examples. The mean number of active nucleation sites per
droplet is set to m = –ln(0.5), which corresponds to an
equal proportion of droplets with and droplets without active nucleation sites. The values of the nucleation rates forhomogeneous and heterogeneous nucleation, noted k0 andk, respectively, will be varied in the examples that follow.
For the sake of readability, only predictions of f0(t)through f4(t) are plotted, that is the fractions of dropletsthat bear up to 4 crystals. This is deemed sufficient to reveal the pattern of the models. Fig. 1 shows the nucleation
model behaviour for a decreasing ratio between homogeneous and nucleation kinetic constants k0/k.
What these curves all have in common is that the proportion of droplets with a given number of crystals increases, goes through a maximum (or two), and then drops
back to zero. When the ratio between homogeneous andheterogeneous kinetic constants k0/k is low, the curves exhibit 2 modes. Theses modes relate to the occurrence of
homogeneous and heterogeneous nucleation events, andthe more different their nucleation rates the more separate
and distinct the 2 modes. These curves evolve gradually
towards single mode curves as the ratio k0/k increases;
this is the behaviour that is most often portrayed in theliterature (Dombrowski et al., 2010; Goh et al., 2010). The
limiting case for this ratio corresponds to k = 0, which isthat of purely homogeneous nucleation. Fig. 2 shows theresult of the model for k = 0.
The underlying assumption behind all the model predictions presented above is that droplets which have undergone a nucleation event at time t can sustain othernucleation events at a later time, with the same nucleation
kinetics. This is equivalent to saying that the state ofsupersaturation inside individual droplets remains constant as time advances (i.e. the crystal growth rate iszero). We shall refer to this use of the nucleation model as
constant supersaturation mode.
Another way of using the nucleation model consists ofallowing droplets to undergo only one nucleation event,with the outcome in terms of number of crystals determined by the Poisson statistics of the model. This mode
may offer a better representation of reality in microfluidics experiments where the constant supersaturation mode
does not apply. We shall refer to this mode as the single
nucleation event mode. In this case, model predictions
can no longer be made analytically as they require using aMonte Carlo (MC) simulation scheme that predicts thenucleation of every single droplet in the system. Fig. 3
explains implementation of the nucleation model byMonte Carlo.

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Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

Fig. 2Model prediction with homogeneous nucleation only(m = –ln(0.5), k0 = 10 –6 s –1, k = 0).

the constant supersaturation mode are totally different, as
one would expect. Where the model with constant supersaturation predicts any number of crystals inside thedroplets, the single nucleation event mode rarely predicts
more than 1 crystal per droplet with the nucleation parameters used.
It is important to recognise that f0(t) is the same regardless of the model used, i.e. whether it is used in single nucleation event mode or in constant supersaturation mode.
This can be demonstrated analytically, and comes fromthe fact that the nucleation rate of droplets is independentof the path followed by the nucleation events that follow.
This is confirmed in the previous figures, which show thatthe prediction for f0(t) using analytical equation (9) is indistinguishable from that calculated by the MC simulation
scheme. This result fully endorses using the variation of
empty droplets to estimate the nucleation parametersfrom microfluidics experiments.

Fig. 1Illustration of the probabilistic nucleation model behaviour. Cases a, b and c show the effect of a decreasing ratio between homogeneous and heterogeneous
nucleation kinetic constants k0/k. Inserts are used tozoom on the heterogeneous nucleation period.
Case a: Mixed homogeneous/heterogeneous nucleation
with k0/k = 0.01 (m = –ln(0.5), k0 = 10 –6 s –1, k = 10 –4 s –1)
Case b: Mixed homogeneous/heterogeneous nucleation
with k0/k = 0.1 (m = –ln(0.5), k0 = 10 –5 s –1, k = 10 –4 s –1)
Case c: Mixed homogeneous/heterogeneous nucleation
with k0/k = 1 (m = –ln(0.5), k0 = k = 10 –4 s –1)

Fig. 4 shows the output of the probabilistic nucleation
model, used in single nucleation event mode, for Fig. 1,
Case a (mixed homogeneous/heterogeneous nucleation),and Fig. 2 (homogeneous nucleation only), recalling thatthey were obtained using the model in constant supersaturation mode.
Predictions using the single nucleation event mode or262

3. Application of the probabilistic nucleation
model to the analysis of microfluidics
nucleation data
As discussed in section 2, the probabilistic nucleation
model can be used to estimate nucleation parameters m,
k0 and k, directly from the measured variation of f0(t).
Once the nucleation parameters have been estimated, themodel can then be applied to predict the variation of fr(t)for any value of the number r of crystals. This section reviews application of the model to both endeavours, anddiscusses the behaviour and validity of the probabilistic
nucleation model through the prism of actual microfluidics experimental data sets.

3.1 Experimental data
The applicability of the probabilistic nucleation model,
which includes estimation of nucleation parameters andFlorent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

Fig. 3

Principle of the MC simulation scheme implementing equation (7), for one set of nucleation parameters (m, k0, k).

prediction of nucleation events inside individual droplets,
was tested using 4 data sets from the authors (see Teychené
and Biscans, 2011), and two additional data sets from
Akella et al., Figs. 25 and 29 (Akella et al., 2014). The latter are used in section 5. Table 1 summarises the experimental conditions used to generate the microfluidics data.
The experimental protocol is summarised below, however, the reader is invited to refer to Teychené et al. (2011)
for details. The data were generated using a glass microfluidics platform in the context of a study about the nucleation of eflucimibe crystals in octanol. Undersaturated
droplets of eflucimibe dissolved in octanol were generated
with water as the carrier fluid. These droplets were generated using a flow-focusing geometry that generates highly
monodispersed droplets. In these experiments, the variation of volume between droplets is less than 0.1 nL.
Glass syringes, equipped with patterned filters (Millipores, pore diameter < 0.2 μm), are used to inject the fluids into the devices. The temperature of the syringe andthe tubing that contain the organic solution are controlled
to avoid crystallization by means of a small flexible
heater. Flow rates are controlled by syringe pumps (PhD

2000, Harvard apparatus). The temperature of the microfluidic platform is precisely controlled using Peltier elements. Platinum temperature sensors, which are embeddedin the microfluidics chip, provide precise temperaturemonitoring. Owing to this temperature control, the droplets are generated at a temperature 5 °C above the saturation temperature (denoted as T* in Table 1) for all theexperiments. As soon as the desired amount of droplets is
obtained on the microfluidics chip, typically 600 to 800,
the flow is stopped and the system is rapidly cooled (i.e.
in less than 1 minute) down to the desired temperature inorder to induce supersaturation (denoted as Tnucleation in
Table 1).
Digital images of the whole microfluidics chip were acquired using an inverted light microscope (Zeiss AXIO
observer) equipped with a CCD colour camera (PCO Sensicam QE) at a frame rate ranging from 5 to 30 minutes.
The optical resolution of the system is 1 μm/pixel with the
10´ objective, and the particle detection threshold isaround 5 μm.
As unfrozen droplets can be identified without ambiguity, their number was determined automatically by image

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Table 1 Experimental conditions used to produce the microfluidics experimental data. The average droplet volume is 11.5 ± 0.1 nL.

Fig. 4Model prediction using single nucleation event mode.
The dotted lines represent the analytical prediction off0(t) from model equations (9) or (10).
Case a: Simulation run output for the mixed homogeneous/heterogeneous nucleation case. m = –ln(0.5),
k0 = 10 –6 s –1, k = 10 –4 s –1, NT = 10000 droplets,∆t = 100 s. At t = 106 seconds, the model predicts
18.29 % empty droplets, 81.67 % droplets with 1 crystal, 0.15 % droplets with 2 crystals, 0 % with 3 crystals.
Case b: Simulation run output for the pure homogeneous case. m = –ln(0.5), k0 = 10 –6 s –1, k = 0 s –1,
NT = 10000 droplets, ∆t = 100 s. At t = 106 seconds, themodel predicts 36.1 % empty droplets, 63.9 % dropletswith 1 crystal, 0 % droplets with 2 crystals.

analysis. The number of crystals in frozen droplets, however, was counted by visual inspection. With each experiment, the time at which the first visible crystallization
event occurred was recorded. It varied between 25 and 70
minutes. This value was ultimately used to rescale the experimental time.

3.2 Estimation of nucleation kinetic parameters
Under the assumption of normality of experimental errors, the model parameters m, k0 and k are estimated by
non-linear least squares minimization. Given the large
amount of data points obtained at the end of a microfluidics experiment, the more so for empty droplets, the experimental data can confidently be bootstrapped in order toprovide an estimate of the confidence intervals of nucle-

264

Data
sets

T*
(°C)

Tnucleation(°C)

103 × x°103 × x*

Sx

A

47

20

4.202

1.870

2.25

B

40

5

2.847

1.411

2.02

C

50

5

5.536

1.411

3.92

D

60

5

8.088

1.411

5.73

Fig. 5

Example of a bootstrap estimation of the nucleation
model parameters. The blue symbols are the experimental data points, the red symbols the bootstrap sample, and the solid line is the model regression for thebootstrap sample.

ation model parameters, as well as the model confidence
and prediction intervals. Fig. 5 illustrates one bootstrap
iteration of the parameter estimation scheme applied todata set D. Typically, 1000 bootstrap iterations are carriedout for a data set that comprises over one hundred data
points.
Each bootstrap iteration gives a set of model parameters (m, k0, k), and the combined bootstrap estimations
yield the model confidence and prediction intervals. Fig. 6
gives the estimated 95 % prediction intervals for data sets
A through D, using 1000 bootstrap estimates in each case.
The bootstrap estimations yield the distribution of individual model parameters from which their confidence intervals can also be obtained. Table 2 gives the results thatwere obtained from the 4 selected data sets.
For all data sets, the relative standard deviation (RSD)of the estimated parameter k0, defined by Pound and La
Mer (1954) as the rate of volume nucleation (i.e. k0 = JvV,
cf. Eqn. 15), is small. This means that the experimental
sampling frequency was high enough to capture the essential features of the homogeneous nucleation kinetic
component of the nucleation model.
Parameters m and k relate to the heterogeneous nucleation kinetic component of the nucleation model. Table 2
shows that parameter k is not estimated with the same

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

Fig. 7

Fig. 6

Nucleation model 95 % prediction interval estimatedfor data sets A through D.

Table 2 Estimated nucleation model parameters (m, k0, k) fordata sets A through D, and number fraction Nact. = 1–e –m of droplets with active nucleation sites. The tableindicates the estimated mean and relative standard
deviation (RSD).
Data sets

A

B

C

D

k0 × 106(s –1)

mean

1.26

0.26

7.05

8.78

RSD

0.9 %

5.5 %

1.6 %

3.0 %

k × 104(s –1)

mean

4.55

9.61

2.24

1.71

RSD

17.9 %

91.5 %

16.5 %

14.7 %

mean

0.16

0.01

0.28

0.85

RSD

1.0 %

70.7 %

3.5 %

4.0 %

mean

0.147

0.008

0.248

0.573

RSD

0.9 %

66.7 %

3.1 %

2.5 %

m
Nact.

precision as parameter k0. Heterogeneous nucleation is aprocess that proceeds very fast at the beginning of theexperiment because the energy barrier to form a critical
nucleus is lower with surface nucleation than it is withvolume nucleation. Moreover, the lower the number of
impurities per drop, the rarer the occurrence of nucleation
events. Sampling frequency at the start of an experimentis therefore critical for capturing the salient features ofheterogeneous nucleation. The frame rate used to conduct
the microfluidics experiments was not always sufficientand sometimes yielded only a handful of experimental
points inside the heterogeneous nucleation period. Thisobservation, which can be readily observed in Fig. 6, explains that the lower the mean number of impurities per
droplet, the broader the confidence interval associatedwith estimation of parameter k. The worst case occurred

Illustration of the strong correlation between heterogeneous nucleation rate parameters m and k. The correlation plotted is: log10 k = –3.82 – 0.48log10 m.

with data sets A and B. This result is exacerbated by sampling statistics. Indeed, the fact that data set B contains
Nact. = 0.8 % of droplets with active nucleation sites meansthat in a microfluidics experiment that uses 600 to 800
droplets, the number of droplets with active nucleationsites is on average no more than 7. Such a number isclearly too low to expect precise estimates of heterogeneous nucleation rate parameters k and m. When theamount of impurities is high enough, as with data sets C
and D, the sampling frame rate is sufficient and nucleation
rate parameter k and m are estimated with good precision.
Notwithstanding the difficulty with estimation of k at
low levels of impurities, Fig. 7 shows that the heterogeneous nucleation parameters m and k are negatively correlated. The interpretation of the correlation between theestimated values of k and m, where the latter increases
with supersaturation as one would expect, is unclear. It isemphasised that the variation of k between experiments
does not contradict the model assumption that k is thesame for all active nucleation sites; it just indicates thatthe nature of active nucleation sites differs between experiments.
Although the purpose of this paper was not to venture
into nucleation theory, it seemed justified to give some interpretation of the values of the estimated nucleation
model parameters that were obtained.
In the framework of CNT, the homogeneous nucleation
rate is related to the parameter of the nucleation model by
the following equation (Kashchiev, 2000):16πσ 3vm2  ΔGv* Jv 
A0 exp  

A
exp
0
 k T  3(k BT ) 3 ln 2 S 
B 
k0

V

(16)

According to equation (16), k0 is the product of the volume of the solution V where nucleation occurs and therate of nucleation J (number of particles per unit time andunit volume). So, CNT for homogeneous nucleation implies that nucleation kinetics parameters are related to
the volume of the droplets, and therefore the size, or size
distribution of the droplets. In the context of this study,265

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

droplets are monodisperse and their volume is invariant
during any given microfluidics experiment.
A0 is the nucleation rate prefactor which can be written
as (Kashchiev, 2000):
 ΔF 

A0 ρ
ρ N Z 4πρDr * exp  
N Zj k BT (17)

 ΔF 
Where j 4πρDr * exp   is the rate at which a k BT 
monomer is added to the critical cluster, ρ is the number
density of a monomer in the solution, D the diffusion co ΔF 
efficient, r* the critical radius of the nuclei, exp   k BT 
is the probability of effective collision between a cluster
and a monomer, and ρN is the number density of nucleationsites. As with homogeneous nucleation, every monomer
can be a nucleation site ρ = ρN.
Similarly, the heterogeneous surface nucleation rate is
written as (Kashchiev, 2000):
 ΔGs* J s  A0' exp  k k BT (18)

As the main assumption of CNT is that the properties(shape, surface tension, etc.) of the pre-critical nuclei are
the same as those of the post-critical nuclei and of thecrystal, the pre-exponential factor has the same expression. However, in that case, the number density of nucleation site is directly related to the number density of
impurities and is much smaller than the number densityof monomers.
The evolution of the nucleation rate (k0) as a function oftemperature and supersaturation is given in Fig. 8. As
predicted by CNT, it is found that ln(k0) varies linearlywith the term T –3ln–2S. The crystal solution interfacial
tension is calculated from the slope of the line, giving avalue of 3 mJ·m–2 that is consistent with the data alreadypublished (Teychené and Biscans, 2008). From the intercept, the pre-exponential factor of the nucleation rate wasfound to be in the range of 107, which is very low for apurely homogeneous nucleation rate. Estimation of thisfactor from CNT in the case of a purely homogeneous nucleation yields values in the range 1010 to 1013 s–1. Because
the number of nucleation sites is smaller than the numberof monomers in solution, the discrepancy can be attributed
either to heterogeneous nucleation (with static heterogeneities present in the solution from the start of the experiment, but with a lower activity than the impurities
responsible for the fast nucleation rate), or to the inabilityof CNT to capture the complexity of crystal nucleationfrom solution (i.e. nucleation is catalysed by dynamic heterogeneities, which are formed during the nucleation process, for instance). The limits of CNT have already been
pointed out by a number of authors, including Vekilov(2010) for protein nucleation, Jawor-Baczynska et al. (2015)

266

Fig. 8Evolution of the nucleation rates k and k0 as a functionof supersaturation S and temperature T.

for organic molecules and Gebauer et al. (2014) for salts.
Fig. 8 also displays the variation of the heterogeneous
surface nucleation rate k as a function of T–3ln–2S. Because m and k are strongly correlated, and because of thelarge uncertainty associated with data set B in particular,
it is difficult to interpret the measured trend of the heterogeneous nucleation rate k. Nevertheless, the upward trendof ln(k) vs T–3ln–2S (which is directly related to the energy
barrier of the nucleation process) is lower than the one obtained in the case of volume nucleation. As the nucleation
process is fast, it can be inferred that the energy barrierfor heterogeneous nucleation is very low.
For the same reasons, it is difficult to interpret the evolution of the mean number of impurities m. Based on
Pound and La Mer’s original paper (1954), this number
depends both on temperature and concentration. For data
sets A through D, it appears that m is proportional to theconcentration of solute, which implies that the impurities
come with the solute molecules. They are probably associated with molecules with a molecular structure that resemble the solute molecules and cannot be purified.
This section has confirmed that provided the samplingframe rate is commensurate with the heterogeneous nucleation rate and that the number of observed droplets ishigh enough to eliminate sampling statistics issues, themeasured variation of unfrozen droplets can yield good
estimates of nucleation parameters. Discussion about theparameter estimates led to the assertion that nucleation
microfluidics experiments should be performed at thesame initial concentration but with a different final temperature in order to decorrelate the heterogeneous nucleation parameters m and k, and to study conclusively the
influence of supersaturation and temperature on nucleation kinetics.

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4. Prediction of the appearance of crystals
Model predictions of fr(t) were obtained using the probabilistic model employed in single event nucleation modeand using the MC simulation scheme presented earlier forthe selected experimental data sets. The output of the MC
scheme is dependent on the time step ∆t used as well as
the total number NT of droplets. The MC simulation requires using as small a time step ∆t as possible, which
impacts computation time. The choice of time step ∆t usedin the simulations is such that it is no greater than 1/k, theheterogeneous nucleation giving the fastest kinetics.
Fig. 9 shows the prediction of the fraction of empty
droplets output by the MC simulation against the experimental microfluidics data. The prediction is good, as one
would expect since the nucleation model parameters were
estimated from the measured fraction of empty droplets.
However, the point here is to recognise that the predictions are obtained by the MC simulation scheme, not fromthe analytical expressions for f0(t), which confirms thecorrectness of the Monte-Carlo simulation code developed by the authors to simulate the probabilistic nucleation model.
Fig. 9 also shows the predicted prediction intervals fordata set D for two different total numbers NT of droplets.
The prediction intervals obtained for the simulation performed using 700 droplets (which correspond to the number of the droplets analysed during the experiment)
captures nicely the spread of the experimental data. As
expected, the model predicts that had a lower number ofdroplets been observed, the spread of the experimental
data would have been higher. This expected trend showsthat the model can also be used to guide the experimenta-

Fig. 9Prediction of the fraction of empty droplets as a function of time using MC simulation for two representative experiments and two total numbers of droplets.

tion in terms of setting the number of droplets to be observed. This is an important issue as the spread of thedata controls the precision of the estimates of the nucleation model parameters.
The point was made in section 2.3 that the prediction of
the number of crystals inside a droplet depends on themode chosen to implement the nucleation model. The following text analyses the capacity of the nucleation model
to predict the appearance of crystals. It is worthy of note
that, to the best of the authors’ knowledge, application of
the probabilistic nucleation model to predict the appearance of crystals in microfluidics experiments has not yet
been reported.
Experimentally, it was observed that for experiments
performed at relatively low supersaturation, most of thedroplets contained 1 crystal and very few droplets contained two crystals. This is the case for data set A, which
produced 33 % of droplets with 1 crystal, 2 % with 2
crystals and 65 % without crystals. With experiment B,
droplets that had nucleated contained only 1 crystal. Simulation results of the probabilistic nucleation model usedin single nucleation event mode are given in Fig. 10 for
data sets A and B. It is emphasised here that the predictions use the parameters (k0, k, m) that were estimated in
section 3 from the time variation of empty droplets. The
agreement between simulations and measurements isgood, confirming that the single nucleation event mode
gives a good account of the nucleation events that took
place in experiments A and B. One explanation is that assupersaturation is low, when one crystal appears, it starts
growing and consumes all the supersaturation. The depletion of solute induces a decrease in nucleation probability
such that no new nucleation event can occur inside thedroplet. Such a situation will prevail when crystal growth
kinetics are very fast, or when the ratio between the crystal nucleation rate and the crystal growth rate is small.
It can be noticed in Fig. 10 that the measured fractionof droplets which bear one crystal is mainly inside the upper portion of the model’s prediction interval, and that itis the opposite for the droplets with 2 crystals. One may
recall that crystal number counting was done by visualinspection, and it is believed that the visual counting biased the data by overestimating the number of dropletswith 1 crystal at the expense of those with 2 crystals. Visual counting of the number of crystals inside a droplet isdifficult, and this nucleation-model-based analysis
stressed the importance of this issue for analysis of microfluidics experiments.
When the crystal nucleation rate to crystal growth rate
ratio is high (with the limiting case of no crystal growth),
not all the supersaturation is consumed by a single crystal, and successive nucleation events may occur over time.
Let us consider data set D for which the initial supersaturation was twice that of data sets A and B. Fig. 11 shows267

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

Fig. 10 Predicted and measured temporal evolution of thefraction droplets containing one or two crystals in thedroplets for data set A (upper) and data set B (lower).

the predictions of the probabilistic nucleation model usedin both single nucleation event mode and constant supersaturation mode.
The variation of the number fraction of droplets that
contain one crystal bears no resemblance with data sets A
and B. Indeed, it shows a rapid increase at the beginningof the experiment to a maximum value, then a slow decrease. The measured number fraction of droplets with 2
crystals or more shows a continuous increase over time.
The upper plot in Fig. 11 shows the nucleation model prediction in single nucleation event mode. It is clear that this
implementation mode of the nucleation model does not
capture at all the nucleation events of data set D. The
lower plot in Fig. 11 gives the prediction of the nucleation
model in constant supersaturation mode. Notwithstanding
the counting bias between droplets with one or more crys-

268

Fig. 11 Predicted and measured temporal evolution of thenumber fractions of droplets containing one or more
crystals for data set D. Upper figure: single nucleation
event mode. Lower figure: constant supersaturation
mode.
Table 3 Values of the k0/k ratio for data sets A through D.
Data sets

A

B

C

D

k0/k

0.00280.00030.03140.0515tals, it is clearly apparent that the constant supersaturation
mode gives a much closer match to the measured data.
With data set D, given its higher state of supersaturationand its higher k0/k ratio, which is more than 1 order ofmagnitude higher than that of data sets A and B as seenin Table 3, it is not surprising to find that the hypothesesof the constant supersaturation mode give a better accountof the measured microfluidics data.
Even though the single nucleation event mode can be a

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

close match to microfluidics data, as found with data sets
A and B, both the single nucleation event and the constantsupersaturation modes are limited in their ability to predict nucleation in that they do not account for the crystal
growth that follows nucleation. To further improve ourability to model microfluidics systems and gain even morevalue out of the valuable data produced by such systems,
it is necessary to couple the probabilistic nucleation modelwith a crystal growth model that accounts for the consumption of supersaturation inside individual droplets.
The Monte-Carlo simulation scheme, in which droplets
are individualised, provides just the right environment forsuch a development. This requires both accurate measurements of crystal growth inside droplets, and a valid thermodynamic model of the liquid phase.

Table 4 Estimated nucleation model parameters (m, k0, k) for
Akella et al’s data sets (Akella et al., 2014, Figs. 25
and 29), and number fraction of droplets with active
nucleation sites.
Fig. 25

Fig. 29

mean

6.93

10.2

RSD

1.7 %

1.1 %

mean

0.66

3.55

RSD

5.7 %

38.4 %

mean

0.48

0.20

RSD

3.4 %

2.4 %

mean

0.383

0.181

RSD

2.7 %

2.2 %

Data sets
k0 × 106 (s –1)
k × 104 (s –1)m
Nact.

5. Application to microfluidics data fromliterature
For the sake of rounding off the paper, it was deemed
relevant to apply the probabilistic nucleation model tohigh-quality data published by researchers other than thepresent authors. The data selected was that of Figs. 25 and29 from Akella et al. (2014). The estimated nucleation
parameters, using the non-linear parameter estimation
scheme presented earlier, are given in Table 4. The values
are close to those published by Akella et al., however,they differ due to the difference between equation (10),proposed by the authors and equation (14) used by Akellaet al.
Figs. 12 and 13 show the corresponding 95 % prediction intervals for the number fraction f0 of empty droplets.
The prediction intervals are narrower compared to thoseof data sets A through D. This is due to Akella et al. using
a high number of droplets, typically 1200 to 4000 in eachof their experiments, so that their raw measurements of f0
are extremely smooth.
Figs. 14 and 15 show the predictions made using both
single nucleation event mode (NT = 1000 drops) and constant supersaturation mode for the production of crystals.
The results show that the single nucleation event modepredicts that after 15 hours, most droplets contain 1 crystal, with no more than 0.24 % and 0.62 % of droplets containing 2 crystals for the data from Figs. 25 and 29,
respectively. The constant supersaturation mode predicts
a significant proportion of droplets that bear 2 or more
crystals.
It is anyone’s guess as to the actual number of crystals
observed by Akella and co-workers (2014), as they did notreport this information. The predictions are so distinct
that it should be rather simple for them to decide whether
their system behaves more like one mode or the other. By
examining the images and movie frames provided in theirFig. 12 Nucleation model 95 % prediction interval for thenumber fraction of empty drops using Akella et al.’sdata (Akella et al., 2014, Fig. 25, p. 4500).

Fig. 13 Nucleation model 95 % prediction interval for thenumber fraction of empty drops using Akella et al.’sdata (Akella et al., 2014, Fig. 29, p. 4502).

paper, and considering that their experiment is carried out
at a low level of supersaturation, it is probable that theirsystem follows the single nucleation event mode and produced no more than 1 crystal per droplet.

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Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

Fig. 14 Prediction of crystal formation for Akella et al.’s datafrom Fig. 25. (top: single nucleation event mode; bottom: constant supersaturation mode)

Fig. 15 Prediction of crystal formation for Akella et al.’s datafrom Fig. 29. (top: single nucleation event mode; bottom: constant supersaturation mode)

6. Conclusions
The probabilistic nucleation model originally proposedby Pound and La Mer (1952) was revisited with the objective of clarifying its underlying hypotheses and associatedbehaviour. The nucleation model considers two types ofdroplets, i.e. droplets without nucleation sites which can
only undergo homogeneous nucleation events, and drop-

270

lets with active nucleation sites which can undergo homogeneous and heterogeneous nucleation events. Analyticalexpressions were derived for predicting the variation of
the fraction of droplets that contain a given number ofcrystals, both in terms of Poisson distribution functions
and exponential functions.
The paper emphasises that the same model can be implemented in different ways which yield different outcomes. The model was applied in constant supersaturationand single nucleation event modes. The first mode, which
is often portrayed in the literature, corresponds to thedroplets with no crystal growth, whereas the second one
corresponds to droplets having a supersaturation that is justsufficient for one nucleation event and associated crystal
growth.
Regardless of the implementation mode, the model prediction for the time variation of the fraction of empty or
unfrozen droplets is the same, confirming that nucleation
kinetic parameters m, k0 and k should indeed be estimatedusing the experimental measurements of the fraction of
empty droplets. This is a particularly favourable situation
given that this is the fraction that is most accurately measured in practice. Indeed, identifying droplets that contain
1 or more crystals is obviously more prone to measurement
errors than identifying empty droplets. The estimation of
nucleation model parameters showed the importance offrame rate and number of droplets as they impact the precision of the parameter estimates.
In the context of microfluidics studies, it was confirmedthat both modes of implementation of the nucleation
model are applicable. The probabilistic nucleation model
was used, possibly for the first time, to predict the rate ofappearance of crystals for microfluidics systems. Experimental results with low supersaturation levels were well
predicted by the single nucleation event mode. The single
nucleation event mode was shown to yield droplets withno more than one or two crystals, a desirable situation froman industrial perspective. The constant supersaturation
mode accounted better for the nucleation events observed
for data sets with excess supersaturation. Comparison between predicted and measured number fractions of droplets with one or more crystals indicated the possibility ofbias in the number counting of crystals inside individual
droplets, emphasising the need to develop reliable crystal
counting methods for harvesting the full benefit of microfluidics systems.
The analysis confirmed the value and applicability of theprobabilistic nucleation model for analysis of microfluidics data, particularly for estimation of nucleation parameters. The model showed limitations in its applicability forpredicting the appearance of crystals inside droplets, although it gave reasonable predictions at low supersaturation levels. As the probabilistic nucleation model alone
cannot account for the consumption of the supersaturation

Florent Bourgeois et al. / KONA Powder and Particle Journal No. 35 (2018) 258–272

inside droplets, the nucleation model cannot predict the
number of crystals inside droplets. As the real situation issomewhere between the single nucleation event and theconstant supersaturation modes, it is necessary for prediction of the rate of appearance of crystals inside individual
droplets to merge the probabilistic nucleation model witha crystal growth model.

Nomenclaturedpois(k,λ) Probability density function of the Poisson distribution with mean λDDiffusion coefficient (m 2·s –1)

fr (t)

Number fraction of droplets containing r crystals attime tk

Nucleation rate constant of an active nucleation site(s –1)kB

Boltzmann constant k B = 1.38064852 × 10 –23 m 2kg·s –2·K–1

k0

Homogeneous nucleation rate constant (s –1)

jDroplet index used in Monte-Carlo simulation (s)JsHeterogeneous surface nucleation rate (s –1)

Jv

Homogeneous nucleation rate (s –1·m –3)

m

Mean number of active nucleation sites per droplet

Nact.

Number fraction of droplets that contain active
nucleation sites at the start of a microfluidics
experiment

Np

Number of droplets with p active nucleation sites

NT

Total number of droplets counted in a microfluidics
experimentp

Number of active nucleation sites in a dropletr

Number of nucleation events inside a dropletr*Radius of the critical nuclei (m)SxSupersaturation defined as Sx = x°/x*tTime (s)T

Temperature (K)T*

Saturation temperature (°C)

Tnucleation

Final quench temperature (°C)

V

Droplet volume (m3)x°

Initial molar fraction of eflucimibe in octanol orsolubility molar fraction at T*x*

Solubility molar fraction at Tnucleation

Z

Zeldovich factor

ΔtTime increment used in the Monte-Carlo simulation
(s)

ΔG*

Free energy barrier of nucleation (J)ρ

Number density of monomers per unit of volume
(m–3)

ρN

Number density of nucleation sites (m–3)σ

Crystal solution interfacial tension (mJ·m–2)

References
Akella S.V., Mowitz A., Heymann M., Fraden S., Emulsion-­based technique to measure protein crystal nucleation rates
of lysozyme, Crystal Growth & Design, 14 (2014) 4487–
4509.
Dombrowski R.D., Litster J.D., Wagner N.J., He Y., Modelingthe crystallization of proteins and small organic moleculesin nanoliter drops, AIChE Journal, 56 (2010) 79–91.
Gebauer D., Kellermeier M., Gale J.D., Bergstrom L., Colfen H.,
Pre-nucleation clusters as solute precursors in crystallisation, Chemical Society Reviews, 43 (2014) 2348–2371.
Goh L., Chen K., Bhamidi V., He G., Kee N.C.S., Kenis P.J.A.,
Zukoski C.F., Braatz R.D., A stochastic model for nucleation kinetics determination in droplet-based microfluidic
systems, Crystal Growth & Design, 10 (2010) 2515–2521.
Jawor-Baczynska A., Moore B.D., Sefcik J., Effect of mixing,
concentration and temperature on the formation of mesostructured solutions and their role in the nucleation of
DL-valine crystals, Faraday Discussions, 179 (2015) 141–
154.
Kashchiev D., Clausse D., Jolivet-Dalmazzone C., Crystallization and critical supercooling of disperse liquids, Journal of
Colloid and Interface Science, 165 (1994) 148–153.
Kashchiev D., Ed., Nucleation – Basic Theory with Applications, Butterworth-Heinemann, Oxford (2000).
Laval P., Crombez A., Salmon J.-B., Microfluidic droplet
method for nucleation kinetics measurements, Langmuir,
25 (2009) 1836–1841.
Pound G.M., Lar Mer V.K., Kinetics of crystalline nucleus formation in supercooled liquid tin, Journal of the American
Chemical Society, 74 (1952) 2323–2332.
Sear R.P., Quantitative studies of crystal nucleation at constantsupersaturation: Experimental data and models, CrystEngComm, 16 (2014) 6506–6522.
Selimović Š., Jia Y., Fraden S., Measuring the nucleation rate oflysozyme using microfluidics, Crystal Growth & Design, 9(2009) 1806–1810.
Teychené S., Biscans B., Nucleation kinetics of polymorphs:
induction period and interfacial energy measurements,
Crystal Growth & Design, 8 (2008) 1133–1139.
Teychené S., Biscans B., Microfluidic device for the crystallization of organic molecules in organic solvents, Crystal
Growth & Design, 11 (2011) 4810–4818.
Teychené S., Biscans B., Crystal nucleation in a droplet based
microfluidic crystallizer, Chemical Engineering Science,
77 (2012) 242–248.
Vekilov P.G., The two-step mechanism of nucleation of crystals
in solution, Nanoscale, 2 (2010) 2346–2357.
Vitry Y., Teychené S., Charton S., Lamadie F., Biscans B.,
Investigation of a microfluidic approach to study very highnucleation rates involved in precipitation processes, Chemical Engineering Science, 133 (2015) 54–61.

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Author’s short biography
Florent Bourgeois
Prof. Bourgeois received his PhD in extractive metallurgy from the University of Utahin 1993. He was affiliated to the University of Queensland from 1994 to 2000 with research and teaching activities related to mineral and coal processing, after which hespent 5 years with the French Geological Survey’s processing department. In 2006, hejoined the Laboratoire de Génie Chimique at the University of Toulouse (France). His
field of competence is particulate process design and modelling, with emphasis on solid­liquid separation, comminution, liberation and sampling, as they apply to mineral andwaste beneficiation.

Sébastien Teychené
Dr Sébastien Teychené is assistant professor in chemical engineering at the Laboratoire de Génie Chimique of the University of Toulouse (France). He received his B.
Eng. degree in chemical and environmental engineering from the Institut National de
Sciences Appliquées (INSA, Toulouse) in 2000, and a master’s degree in chemical engineering in 2001. He was awarded his PhD in chemical engineering from the Universityof Toulouse in 2006, after which he joined Dr. Béatrice Biscans’ research team at theLaboratoire de Génie Chimique. His research work focuses on thermodynamics andkinetics aspects of nucleation and phase transitions in the crystallization processes oforganic compounds.

Béatrice Biscans
Dr. Béatrice Biscans obtained her engineering degree in chemical engineering fromthe University of Toulouse in 1982 and was awarded her PhD in chemical and processengineering in 1985. From 1987 onwards, following a post-doctoral position, she worked
for the National Centre for Scientific Research (CNRS) at the Laboratoire de Génie
Chimique (Toulouse, France). Her research focuses on particle technology and processing. She leads a research group working on crystallization, formulation processes andthe production of nanoparticles. Until recently, she was head of the Laboratoire de Génie
Chimique. She is currently president of the Working Party on Crystallization of theEuropean Federation of Chemical Engineering and of the Working Party on Powders andParticles of the French Society of Chemical Engineering. She is also the CNRS’ representative expert in chemical engineering.

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KONA Powder and Particle Journal No. 35 (2018) 273–282/Doi:10.14356/kona.2018019

Original Research Paper

The Friction Stress Distribution of Loose Materials
to Silo Walls in Deep Pyramidal Silos †Xuewen Wang *, Zhaojian Yang and Bo Li
1

Shanxi Key Laboratory of Fully Mechanized Coal Mining Equipment, College of Mechanical Engineering,Taiyuan University of Technology, China

Abstract
Referring to the classification of vertical silos, the classification rules for deep silos and shallow silos on
pyramidal silos and conical silos have been established. Based on the basic assumptions of Janssen Formula, thefriction stress distribution of loose materials to silo walls was discussed in detail on deep pyramidal silos. An
analytic equation was established used the slice method. Finite element model was developed to simulate thefriction stress distribution. The analytic result was almost the same with the simulation result. However, theequation yielded a minor error mainly because there were some differences between the assumptions presented in
the equation and the real state of materials. Based on the simulation results, the analytic equation was revised.
The results showed that the friction stress distribution of loose materials to silo walls in deep pyramidal silos was
related to the material characteristics and design parameters of silo walls, as well as the material powder attribute.
The revised equation precisely indicated the contact friction stress behaviors of loose materials and provided ashortcut method of calculation for related research.
Key words: loose material, pyramidal silos, friction stress, contact, finite element

1. Introduction
As a special industry thin-shell structure, silos have
many advantages, ranging from having a simple structurethat is low cost, space efficient, and stable, having an easyloading and unloading process that can be conveniently
managed. Silos are widely used in many fields to stockpile loose materials, such as mineral, grain, foodstuff,
coal, chemical fertilizer, and concrete. In the state ofstockpiling loose materials, the mechanics behavior of
the silos and the loose materials are all very complex(Jansseune A. et al., 2016a,b; Park H.W. et al., 2016;
Jagtap P. et al., 2015; Colonnello C. et al., 2014). However,with the mature development of the finite element methodand discrete element method, the numerical simulation
method managed to contribute greatly to the silo research(Ding S. et al., 2015; Wang Y. et al., 2014; Gallego E. etal., 2010) and the loose materials or the solid particle behavior, including the powder friction angles, forces,
stresses and so on (Hua X. et al., 2013; 2015). Basing on
relevant literature, many scholars are interested in study†
1*

Received 16 May 2017; Accepted 23 August 2017
J-STAGE Advance published online 30 September 201779 Yingze W St, Wanbailin Qu, Taiyuan, Shanxi 030024, China
Corresponding author: Xuewen Wang
E-mail: wxuew@163.com
TEL: +86-351-6010414

ing the lateral pressure of stored loose material in silos.
Although the famous static deep-silo lateral pressure formula has already been put forward by JANSSEN over 100
years ago (Janssen, H.A. 1895), the JANSSEN formula isstill being widely cited, used and discussed (Matchett A.J.
et al., 2015; LI Z.F. et al., 2014). In the meantime, many
new research results on lateral pressure have been put
forward (Wang Y. et al., 2014; Couto A. et al., 2013;
Nascimento J.W.B.d. et al., 2013).
In general, these research works are mainly concernedwith cylindrical silos (Iwicki P. et al., 2016; Jansseune A.
et al., 2016a,b; Sadowski A.J. et al., 2014), particularly on
the pressure (Wang Y. et al., 2014; Couto A. et al., 2013;
Nascimento J.W.B.d. et al., 2013), stability (Sondej M. etal., 2016; Iwicki P. et al., 2015; Lozano C. et al., 2015),
and fluidity effect or discharge flow (Ding S.et al., 2015;
Gallego E. et al., 2015; Benyamine M. et al., 2014) of theloose material on the silos. The square platform silos havealready been studied by some scholars (Goodey R.J. et al.,2006; Guines D. et al., 2001; Brown C.J. et al., 2000).
However, there are only a few studies so far which analyze the mechanical behavior of loose materials in pyramidal silos. Comparing with the general cylindrical silos,
the structure of the pyramidal silos is special. It has been
applied in some engineering fields because of its simple
structure and easy manufacture. The friction stress distribution of loose materials in these silos is helpful to study

Copyright © 2018 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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Xuewen Wang et al. / KONA Powder and Particle Journal No. 35 (2018) 273–282

the force obtained in storing and unloading, optimize thedesign structure and cut down the manufacturing cost.
In this paper, an analytic equation of loose material
friction stress distribution was established used the slice
method in deep pyramidal silos with reasonable assumptions and simplifications. The friction stress was solved bya finite element contact analytic method, and the contact-­
friction state was discussed in deep pyramidal silos.
Lastly, a more reasonable equation was published after
verification and modifying to provide foundation for the
deep pyramidal silos’ structure design and storage efficiency.

2. The analytic formula of friction stress
distribution
2.1 The silo structure“EN 1991-4. Eurocode 1: actions on structures, Part 4:
silos and tanks” (CEN, 2004) prescribed that a deep cylindrical silo was the one with aspect ratios (the ratio of h toD) greater than or equal to 2.0; a shallow cylindrical silo
was the ratio of h to D greater than or equal to 0.4 andless than 1.0; otherwise, it was a medium deep silo [seeFig. 1(a)]. However, there was no rule for conical silos
and pyramidal silos. Here, such a rule was prescribed forthem with reference to “EN 1991-4. Eurocode 1: actions
on structures, Part 4: silos and tanks” (CEN, 2004), as

Fig. 1

274

shown in Fig. 1.
(1) As far as the conical silo was concerned, it was a
deep conical silo when h/(D/2) ≥ 2.0; it was a shallow
conical silo when h/(D/2) < 2.0 [see Fig. 1(b)]. It was a
deep conical silo when α ≤ 0.462 rad (α was the obliquityof the conical silo, cotangent 0.462 rad ≈ 2.0); otherwise,
it was a shallow conical silo [see Fig. 1(b)].
(2) As far as the pyramidal silo was concerned, it was a
deep pyramidal silo when h/[min(A,B)/2] ≥ 2.0; it was ashallow pyramidal silo when h/[min(A,B)/2] < 2.0 [seeFig. 1(c)]; It was a deep pyramidal silo when min (ϕ1,
ϕ2) ≤ 0.462 rad; otherwise, it was a shallow pyramidal silo[see Fig. 1(c)].
A pyramidal silo has some features as follows: (1) it has
a simple structure (see Fig. 2) and is easy to manufacture;(2) the friction stress of the materials varies with theobliquity of silo walls; (3) the contact friction behaviors ofloose materials in deep silos as presented in this paper isdifferent from those of the shallow silos.
In this paper, the friction stress distribution of loosematerials to silo walls was investigated for the case of the
deep pyramidal silos.

2.2 The friction stress distribution
In 1895, according to two basic assumptions, the German civil engineer JANSSEN gave the famous calculation
formula of the static pressure in a cylindrical silo, namely,
the JANSSEN Formula (Janssen H.A., 1895). The two as-

The diagram of deep silo and shallow silo.

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uities of the four walls to the axis vertical curve were ϕ1,
ϕ2, ϕ3 and ϕ4, respectively, and the bulk density of loosematerials was ρ. Starting at the lowermost peak, a thinlayer unit with vertical thickness dy was the research object. The thin layer unit was approximated as a cuboid.
Let the areas of the four walls of the thin layer unit bedA1, dA2, dA3, and dA4, and the friction forces of the loosematerials in walls be fdA1, fdA2, fdA3 and fdA4. Thus, along
the vertical direction, the force balance of the loose materials in the thin layer unit could be expressed in the following: p  dp  ρgdy   y tan 1  y tan 3 y tan 2  y tan 4p   y tan 1  y tan 3 y tan 2  y tan 4  f dA1  f dA2  f dA3  f dA4 (1)

f dAi μkp d Ai(2)i
1, 2, 3, 4
dA1  y tan 2  y tan 4 dydA2  y tan 1  y tan 3 dydA3  y tan 2  y tan 4 dydA4  y tan 1  y tan 3 dy(3)Upon combining Eq. (1), (2), and (3), a relationship relating dp to dy could be expressed in the form of Eq. (4):Fig. 2dp
The diagram of the vertical pressure
distribution ofdyloose materials in deep pyramidal silo.

sumptions were expressed in the following: (1) the vertical pressures were equally distributed in the same depth;(2) the ratio of horizontal pressure to vertical pressure
was a constant k, which was the lateral pressure coefficient.
Below are some of the assumptions in this paper basedon above:(1) Loose materials are in an ultimate stress state. Before or after the state, the external force on the loose materials approached a limiting value and the loose materials
will suddenly collapse. At this moment, the lateral pressure coefficient k reflects the force exerted from anotherdirection when the force is acted upon by the loose materials either horizontally or vertically.
(2) Particles are minute (the diameter is less than
1 mm), indicating that the loose materials are homogeneous.
(3) The loose materials must have unified physicalproperties and be in a uniformly filling state to assure a
constant internal friction factor.
(4) The vertical pressure is equal on the same plane.
As shown in Fig. 2, we supposed that the horizontal
cross section was rectangular, the height was h, the obliq-

2k tan 1  tan 2  tan 3  tan 4 μ p  ρg (4)ytan 1  tan 3tan 2  tan 4Note that p = p0 if y = h from Fig. 2. By solving thedifferential Eq. (4), the vertical pressure p of the loosematerials in deep pyramidal silos could be determined in
Eq. (5):yh
ρgy  ln    p0
p 
h
 y


λ 1
λ 1
ρgy   y  

 y


p
1
p 




0


λ 1   h  hλ  2k tan 1  tan 2  tan 3  tan 4 μtan 1  tan 3tan 2  tan 4

1
λ 

 λ  1
(5)

In most cases, λ ≠ 1.
If there were no loose materials or other pressures at
the top of the silos, p0 = 0.
In the engineering practice, most pyramidal silos weresymmetrically designed, namely ϕ1 = ϕ3, and ϕ 2 = ϕ4.
Thus, the λ might be simplified in Eq. (6) in the following:λk tan 1  tan 2 μ
1 
3,  2  4 
tan 1  tan 2(6)

In some cases, the design parameters of the pyramidalsilos were the length A and B of silo top opening as Fig. 2

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showed rather than the dip angle of the silo walls. If theThus, the friction stress distribution on plane A could
pyramidal silos were symmetrically designed, namely
be indicated as Eq. (10):ϕ1 = ϕ3 and ϕ2 = ϕ4, the λ might be expressed as Eq. (7) inpf μp sin 2 i  k cos 2 i 
the following:(10)k  A  B μ
1 
3,  2  4 
(7)
A B
2h
The vertical pressure shown in Eq. (5) must be disassembled to study the friction stress between loose materials and silo walls. In the current study, the lateral pressure
coefficient k was an important constant when the verticalforce was changed into the horizontal force. Furthermore,
the lateral pressure coefficient k could be sampled withdifferent methods prescribed by the code for the design ofsilos in different countries (SAG, 2001; ACI, 1997; Jaky J.,
1948; CEN, 1995; DIN 1055, 1987). In this paper, the lateral pressure coefficient k was prescribed in Eq. (8) according to Rankine’s earth pressure theory (SAG, 2001).

λ


 

k tan 2  45  f 

2


(8)

In Eq. (8), ϕf is the internal friction angle of loose materials.
Taking a piece of triangular prism as an object for investigation (Fig. 3). We supposed that plane A was an internal wall, ϕi (i = 1, 2, 3, 4) was the dip angle of plane A
to the vertical plane, p was the vertical pressure, pAi was
the pressure of p to Ai, and pAi sin ϕi was the disassembled
pressure perpendicular to plane A. Similarly, the lateralpressure kp might be disassembled. The disassembled
pressure of the perpendicular pressure to surface A was
kpAj cos ϕi. Therefore, the friction force on plane A was
Eq. (9):f A μ  pAi sin i  kpA j cos i 

 μ  pA sin i sin i  kpA cos i cos i =μpA sin 2 i  k cos 2 i(9)

3. Contact Analysis and Verification
Eq. (10) could be verified numerically using finite element contact analysis.

3.1 Contact conditions and iterative processes
Contact conditions established when two separated
surfaces touched at normal direction while maintaining
tangential relative movement. In general physical meaning, the surfaces in contact status had the following characteristics:(1) No penetration between each other.
(2) The normal pressure and tangent friction force might
be transferred during contact.
(3) Generally the normal pulling force could not be transferred when surface separation occurred.
All the above three characteristics introduced significant physical variations of silo-loose material system interms of normal and tangential stiffness. In fact, thishighly nonlinear contact mechanics between silo andloose materials formed a major concern of silo engineers
or civil engineers. This paper studied the contact friction
stress.
Nonlinear contact problems could be solved through aseries of repetitive iterative processes to accomplish accurate contact analysis. The procedure could be divided into
four steps: (1) a particular contact status type was initiallypresumed; (2) finding out the contact stresses and displacement of contact point based on the presumed contact
status; (3) checking if the contact condition could be met
for all contact points; (4) if the contact condition was notsatisfied, then the contact status was modified and another
iteration started until all contact conditions could be met
at all contacting points.

3.2 Contact analysis

Fig. 3276

The diagram of the vertical pressure disassembling.

Due to the symmetric property of silo structures, simplified two-dimensional contacting simulations were carriedout in this paper, nonlinear finite element software ANSYS
was used and the contacting surfaces between loosematerials and silos were defined with rigid-to-flexible
surface-to-surface contact pair. Target surfaces of silos
were modeled with TARGE169 element and the contact
surfaces of loose materials were modeled with CONTA171
element.
The ANSYS TARGE169 element could be used to rep-

Xuewen Wang et al. / KONA Powder and Particle Journal No. 35 (2018) 273–282

resent various 2-D “target” surfaces together with theassociated contact elements (CONTA171). The contact
elements, CONTA171, were overlaid on top of the relevantsolid elements in order to describe deformable loose material boundary and possible contact silo surface with target
elements, TARGE169. This target surface was discretisedby a set of target segment elements (TARGE169) and waspaired with its associated contact surface via a shared realconstant set. Any translational or rotational displacement
or even temperature could be imposed on the target segment element. Moments and Forces could also be applied
on target elements.
CONTA171 was used to represent contact and sliding
between 2-D “target” surfaces (TARGE169) and a deformable surface, defined by this element. The element
was applicable to 2-D structural and coupled field contact
analyses. This element was located on the surfaces of 2-D
solid, shell, or beam elements without midside nodes (suchas PLANE42). It had the same geometric characteristics
as the attached solid, shell, or beam element. In ANSYS
numerical model, contact occurred when surface elements
penetrated into target segment elements (TARGE169) atallowable normal distance. Coulomb and shear stress friction could be used to simulate the tangential contact behavior.
Although no penetration occurred in real silos, numerical technique only allowed a stiffness-penetration law tosimulate the contacting physics (see Fig. 4). Hence, penetration Δ must be small enough so that high accuracy
could be obtained, which meant larger contact stiffness
must be used. But large contact stiffness added simulation
cost and convergence difficulties. To overcome this, contact stiffness in this paper was defined as the silo element
stiffness multiplied by a normal contact stiffness factor. It
was found that accurate results could be obtained when

the normal contact stiffness factor was set to 1.0. It should
be noted that this factor also indicated the contact stiffness equaled to the silo element stiffness. The maximum
penetration was only δ = 0.001 m (see Table 1) when thenormal contact stiffness factor was set to 1.0. Since only abrief summary of analysis method was given here, moredetailed discussions and method could be found elsewhere(Wang X.W. et al., 2015).
During FE analysis, silos and loose materials were
meshed with 2D solid element, PLANE42. Such element
could be used either in 2D plane model (plane stress orplane strain) or axi-symmetric model. The element was
defined by four corner nodes, each had two degrees of
freedom: translations in the nodal x or y directions. The
element could simulate plasticity, creep, swelling, stressstiffening behavior with large deflection and large strain
capabilities.
The full Newton-Raphson solver was used in thisstudy, due to its improved convergence efficiency forhighly nonlinear problems, especially to the contact between granulate materials and silo surfaces. Moreover,
ANSYS Newton-Raphson solver could automatically improve. Its convergence efficiency by tracing back system
residual errors.
In FE contact analysis, correlation parameters on theloose materials and the silo were indicated in Table 2.
Table 1 The contact parameters.
The item

The parameters

The mesh element

Plane42

The contact elements

Targe169 and conta171

The contact form

Rigid-to-flexible surface-­to-surface contact

The normal contact rigid factor

1

The maximum penetration depth

0.001 mTable 2 Applied parameters of a pyramidal silo.
1)bulk density: ρ = 700 kgm –3, cohesion: Pn = 10000 Pa;

2)gravity acceleration: g = 9.8 ms –2;

3)

the dip angles of the silo walls: ϕ1 = ϕ3 = 0.227 rad;4)

friction factor: μ = 0.5;5)internal friction angle: ϕf = 0.349 rad;6)

silo roof pressure: p0 = 6432 Pa;

7)

vertical height: h = 11.0 m;

8)calculation ranges: y = 0.3–11 m.

Then, k = 0.49;
Fig. 4The penetration tolerance δ and the penetration Δ(a) In non-contact state; (b) In contact state.

λ

2k tan 1  tan 2  tan 3  tan 4 μ= 1.49tan 1  tan 3tan 2  tan 4

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Xuewen Wang et al. / KONA Powder and Particle Journal No. 35 (2018) 273–282

3.3 The results
Taking an engineering silo as an example (Fig. 5), thecontact analysis were carried out. The analysis object isthe narrow-wall of the engineering silo (Fig. 5).
Correlation parameters on the narrow-wall and theloose materials in the engineering silo were indicated inTable 2. The k and λ were determined by these parameters, where k = 0.49, λ = 1.49. The results were shown in
Fig. 6, Fig. 7, and Table 3. In Fig. 6, different width rep-

Fig. 5

Fig. 6

An engineering silo.

resents different friction zone (sliding and sticking). The
curves of Fig. 7 shown the contact friction stress value
and its location.

3.4 Modification
Fig. 6 indicated that the contact friction zone could be
divided into two parts: sliding contact friction zone andsticking contact friction zone. The interval dividing point
between the sliding zone and sticking zone was approximately in the middle. The location varied with different
parameters. In Fig. 6, the location is located in the middleof node 103 and node 104. The contact friction stressreached the minimum (near 0) at the top of the pyramidalsilo, and the stress gradually increased from the sliding
contact friction zone to the interval dividing point(Fig. 7). The contact friction stress was at the max in theinterval dividing point, and it gradually decreased fromthe interval dividing point to the bottom.
Comparing the FEA results value with the analytic
value of the 11 nodes in Table 3 (node location shown in
Fig. 6), it showed that above the interval dividing point,
the FEA results was a little greater than the analytic solution for most of the nodes. The FEA results were about 1.1
times that of the analytic solution. However, the FEA results below the interval dividing point were about 0.95

Fig. 7The contact friction zone and the node location.

The contact friction stress (Pa).

Table 3 Results comparison.
Node number

96

98

100

102

103

104

107

110

114

115

116

Vertical height
coordinate: y (m)

11

9.93

8.86

7.79

7.255

6.72

5.115

3.51

1.37

0.835

0.3

FEA results: m (Pa)1573.43803.65322.86291.96923.76912.46650.96177.63523.92492.1

1822.0Analytic results: n (Pa)1658.83331.24709.75776.06185.46508.26917.66379.93761.82631.51181.7

(m/n)

0.95

1.14

1.13

1.09

1.12

1.06

0.96

0.97

0.94

0.95

1.54

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Xuewen Wang et al. / KONA Powder and Particle Journal No. 35 (2018) 273–282

times or less that of the analytic solution. Near the discharge opening (node No. 116), the FEA results were a little greater because of the dynamic discharge pressure. For
dynamic discharge, more complex phenomena, such as
material sticking or blocking in the form of a rat hole,arching and bridging were likely to happen. This paper
did not discuss the complex phenomena near the discharge opening.
As a whole, the analytic results roughly conformed to
the FE contact calculation results. It had been pointed outthat the analytic method was still reasonable. The error
was in 10 % or less, because there were some differences
between the assumptions and the real state.
Moreover, different states in the sliding contact friction
zone and sticking contact friction zone had not been fully
taken into account in the assumptions. In the sliding contact friction zone, the friction was introduced by external
forces. The energy dissipation by friction was mainly due
to the relative movement between the loose materials andFig. 8The friction stress distribution curve.

the silo at the contact surfaces. In the sticking contact
friction zone, the friction was internal friction. The friction energy dissipation was mainly due to the elastic deformation because of the contact. In general, the impact
of external forces was a little greater than internal friction.
Taking the wide-wall of the engineering silo as analysis
object, and changing attribute parameters of the loosematerials, a similar contact friction stress curve and similar conclusion were obtained (Fig. 9). Thus, Eq. (10)might be modified. Based on Table 3 and Fig. 6, taking
the discharge opening as a starting point, supposing theheight of pyramidal silo was h, the modified formula ofthe combination of Eq. (5) and Eq. (10) were as follows: y  h, i 1, 2, 3, 4
hmax 
 pf 1.1μp sin 2 i  k cos 2 i 

2
2

0 
y  hmax , i 1, 2, 3, 4
 pf 0.95 μp sin i  k cos i 



λ
λ
1
1

ρgy   y  y 1      p0  p λ  1

λ
h
h
1








2k tan 1  tan 2  tan 3  tan 4 μ

(11)
λ 
tan 1  tan 3tan 2  tan 4Here, y = hmax when p is at the max, and ϕi is the obliquity (see Fig. 2 and Fig. 3).
In addition, the force of loose materials in the discharge
opening could not be regarded as the static force. In here,
dynamic pressure would be acted upon during the unloading process of the loose materials. Eq. (11) would not
be applied in the discharge opening where the friction
stress distribution was more complex. Hence, further research would be needed, or the values near the discharge
opening would increase by 1.5–2 times that of the results
obtained by Eq. (11) in the practical engineering calculations.
The modified distribution curve (shown in Fig. 8: after
modifying) was drawn according to Eq. (11). In fact, there
was a mutation near hmax. The curve in Fig. 8 was made asmooth processing.

4. Discussions and prospects

Fig. 9The contact friction stress curve (on wide-wall).

(1) For the purpose of engineering application, thisstudy focused on the pyramidal silos which other researchers paid less attention. The lateral pressure coefficient k and the assumptions based on Janssen formulawere also applied during the calculation to provide a convenient way for structure calculation of pyramidal silos
and improve the design efficiency of field application engineers. Obviously, the stress conditions of pyramidal silos could have been some different from the cylindricalsilo that Janssen formula applied on, and the mechanical279

Xuewen Wang et al. / KONA Powder and Particle Journal No. 35 (2018) 273–282

properties of loose materials were complex at the edge
and corner part. Therefore, this study only did the approximate research on silo walls. More precise behavior andmechanism research of loose materials, and the friction
stress distribution around the edges of the pyramid silos
were beyond the scope of this study.
(2) Pyramidal silos are mainly used on the field of storing industrial bulk material (such as coal, gravel, concrete). According to the data obtained from fieldengineers, the main problems of this kind of silo were thepoor flow during the unloading process and the wear ofwalls. To solve these problems, this study mainly researched on the friction stress distribution and the contact
state between the loose materials and silo walls. For thenormal pressure (or stress) distribution and the behavior
study, the related papers were recommended (Goodey R.J.
et al., 2017; Li Z.F., et al., 2014; Rotter J.M. et al., 2002;
Brown C.J. et al., 2000).
(3) The slice method, based on the limit equilibrium
theory, took the loose materials as the rigid body. Whenestablishing equilibrium equations, some acceptable assumptions were used to increase the known conditions
and transformed the statically indeterminate problem into
the static problem. The complex boundary conditions of
non-continuous, heterogeneity, anisotropy and externalload of loose materials could be conveniently processed
and finally derived the quantitative calculation model forfield applications.
However, the slice method ignored the deformation andstrength of the material itself and the complex behavior
was simplified which would inevitably cause some error.
In addition, the slice method could not provide accurate
friction stress distribution graphics and images. The finite
element analysis and software technology could make up
for this defect and validate and correct the quantitativemodel. The combination of them could correct the calculation error to a certain extent.
(4) The finite element method was used in this study tosimulate the contact and friction between the bulk material and the pyramidal silo. The discrete element method
could be applied combining test researches to study thediscrete characteristic of material, particle behavior andthe influence mechanism of material on the silo in the future.

5. Conclusions(1) The analytic equation of loose material friction
stress distribution was established in deep pyramidal silos
with reference to the basic assumptions of the JANSSEN
Formula.
(2) The friction stress distribution of loose materials indeep pyramidal silos was studied with the finite element

280

contact analysis. We concluded that the friction behaviors
included sliding contact friction and sticking contact friction, and that the friction stress was maximum at the interval dividing point between the sliding zone andsticking zone. The friction stress decreased gradually tothe roof and the bottom separately.
(3) The FEA results and the analytic result were compared and analyzed. The error was 10 % or less. The main
reason was that some differences existed between the assumptions and the real state. Moreover, the different
states in the sliding contact friction zone and sticking
contact friction zone had not been fully taken into account in the assumptions.
(4) The analytic equation had been modified by comparing the results. It showed that the friction stress distribution of loose materials in deep pyramidal silos was
related to the material and design parameters of silos, aswell as the powder attribute of the loose material. The
modified equation reflected precisely the contact-friction
behaviors of loose materials in deep pyramidal silos andprovided a shortcut method for calculation in related research.

Acknowledgements
The project was supported by the Young Scientists
Fund of the National Natural Science Foundation of China(51105266), Program for the Outstanding Innovative
Teams of Higher Learning Institutions of Shanxi (2014)
and the Basic Condition Platform Project of Shanxi(2014091016).

Nomenclature
A, B

internal side length of silo top opening (seeFig. 1)D

internal diameter of silo top opening (see Fig. 1)

ggravity acceleration, g = 9.8 ms –2hvertical height of the conical silo or the pyramidal silo (see Fig. 1 and Fig. 2)

klateral pressure coefficient [see Eq. (2)]pvertical pressure [see Eq. (5)]p0silo roof pressure (see Fig. 2)

pf, p’ffriction stress [see Eq. (10) and Eq. (11)]Pncohesion of loose material

αobliquity of the conical silo (see Fig. 1)

ϕ1, ϕ2, ϕ3, ϕ4

obliquity of the pyramidal silo walls (see Fig. 1
and Fig. 2)

Xuewen Wang et al. / KONA Powder and Particle Journal No. 35 (2018) 273–282

ρbulk density of loose material

μfriction factor

ϕfinternal friction angle

λa coefficientλ

2k tan 1  tan 2  tan 3  tan 4 μtan 1  tan 3tan 2  tan 4[see Eq. (11)]References
ACI (American Concrete Institute), ACI 313-97 & ACI 313R-97,
Standard practice for design and construction of concretesilos and stacking tubes for storing granular materials (ACI
313-97) and Commentary—ACI 313R-97, ACI International, 1997.
Benyamine M., Djermane M., Dallozdubrujeaud B., Aussillous
P., Discharge flow of a bidisperse granular media from asilo, Physical Review E Statistical Nonlinear & Soft Matter
Physics, 90 (2014) 032201(8pp). https://doi.org/10.1103/
PhysRevE.90.032201
Brown C.J., Lahlouh E.H., Rotter J.M., Experiments on a square
planform steel silo, Chemical Engineering Science, 55(2000) 4399–4413.
CEN (the European Committee for Standardization), ENV
1991-2-2: Eurocode 1: Basis of design and actions on structures. Actions on structures exposed to fire (together with
United Kingdom National Application Document), Brussels, Belgium, 1995.
CEN (the European Committee for Standardization), EN 19914: Eurocode 1: actions on structures, Part 4: silos and tanks,
Brussels, Belgium, 2004.
Colonnello C., Reyes L.I., Clément E., Gutiérrez G., Behaviorof grains in contact with the wall of a silo during the initialinstants of a discharge-driven collapse, Physica A: Statistical Mechanics and its Applications, 398 (2014) 35–42.
Couto A., Ruiz A., Herráez L., Moran J., Aguado P.J., Measuring pressures in a slender cylindrical silo for storing maize.
Filling, static state and discharge with different material
flow rates and comparison with Eurocode 1 part 4, Computers & Electronics in Agriculture, 96 (2013) 40–56.
DIN 1055, Design loads for buildings: Loads in silo bins, Beuth
Verlag, Berlin, Part 6, 1987.
Ding S., Li H., Ooi J.Y., Rotter J.M., Prediction of flow patterns
during silo discharges using a finite element approach andits preliminary experimental verification, PARTICUOLOGY, 18 (2015) 42–49.
Gallego E., Rombach G.A., Neumann F., Ayuga F., Simulationsof granular flow in silos with different finite element programs: ANSYS vs. SILO, Transactions of the Asabe, 53(2010) 819–829.
Gallego E., Ruiz A., Aguado P.J., Simulation of silo filling anddischarge using ANSYS and comparison with experimental
data, Computers & Electronics in Agriculture, 118 (2015)
281–289.

Goodey R.J., Brown C.J., Rotter J.M., Predicted patterns of filling pressures in thin-walled square silos, Engineering
Structures, 28 (2006) 109–119.
Goodey R.J., Brown C.J., Rotter J.M., Rectangular steel silos:
Finite element predictions of filling wall pressures, Engineering Structures, 132 (2017) 61–69.
Guines D., Ragneau E., Kerour B., 3D Finite-Element Simulation of a Square Silo with Flexible Walls, Journal of Engineering Mechanics, 127 (2001) 1051–1057.
Hua X., Curtis J., Guo Y., Hancock B., Ketterhagen W., Wassgren
C., The internal loads, moments, and stresses in rod-likeparticles in a low-speed, vertical axis mixer, Chemical
Engineering Science, 134 (2015) 581–598.
Hua X., Curtis J., Hancock B., Ketterhagen W., Wassgren C.,
The kinematics of non-cohesive, sphero-cylindrical particles in a low-speed, vertical axis mixer, Chemical Engineering Science, 101 (2013) 144–164.
Iwicki P., Rejowski K., Tejchman J., Stability of cylindricalsteel silos composed of corrugated sheets and columns
based on FE analyses versus Eurocode 3 approach, Engineering Failure Analysis, 57 (2015) 444–469.
Iwicki P., Sondej M., Tejchman J., Application of linear buckling sensitivity analysis to economic design of cylindricalsteel silos composed of corrugated sheets and columns,
Engineering Failure Analysis, 70 (2016) 105–121.
Jagtap P., Chakraborty T., Matsagar V., Nonlinear dynamic
behavior of granular materials in base excited silos,
Mechanics of Advanced Materials & Structures, 22 (2015)
313–323.
Jaky J., Pressure in silos. In Proc. 2nd International Conference
on Soil Mechanics and Foundation Engineering, Rotterdam, June 21–30 (1948), 1, 103–107.
Janssen H.A., Versuche über getreidedruck in silozellen,Zeitschrdvereines Deutscher Ingenieure, 39 (1895) 1045–
1049.
Jansseune A., Corte W.D., Belis J., Elastic failure of locallysupported silos with U-shaped longitudinal stiffeners,
Engineering Failure Analysis, 70 (2016a) 1041–1049.
Jansseune A., Corte W.D., Belis J., Imperfection sensitivity of
locally supported cylindrical silos subjected to uniform
axial compression, International Journal of Solids & Structures, 96 (2016b) 92–109.
Li Z.F., Peng Z., Jiang Y.M., Measurements of granular pressure
in silo: Janssen behaviour and deviation, Physics, 63 (2014)
104503.
Lozano C., Zuriguel I., Garcimartín A., Stability of clogging
arches in a silo submitted to vertical vibrations, PhysicalReview E Statistical Nonlinear & Soft Matter Physics, 91(2015) 062203.
Matchett A.J., Langston P.A., Mcglinchey D., A model forstresses in a circular silo with an off-centre circular core,using the concept of a principal stress cap: Solution for acompletely filled silo and comparison with Janssen and
DEM data, Chemical Engineering Research & Design, 93(2015) 330–348.
Nascimento J.W.B.d., Lopes Neto J.P., Montross M.D., Horizontal pressures in cylindrical metal silos and comparison withdifferent international standards, Engenharia Agrícola, 33281

Xuewen Wang et al. / KONA Powder and Particle Journal No. 35 (2018) 273–282(2013) 601–611.
Park H.W., Kim S.T., Choung M.G., Han W.Y., Yoon W.B.,
Analysis of grinding kinetics and flow behavior of adzuki
bean (phaseolus angularis) flour for hopper design, Journalof Food Process Engineering, 39 (2016) 366–376.
Rotter J.M., Brown C.J., Lahlouh E.H., Patterns of wall pressure
on filling a square planform steel silo, Engineering Structures, 24 (2002) 135–150.
Sadowski A.J., Rotter J.M., Modelling and behaviour of cylindrical shell structures with helical features, Computers andStructures, 133 (2014) 90–102.
SAG (State Administration of Grain), GB50322-2001, Grainsteel silo design standard, China Planning Press, Beijing,
China (in Chinese), 2001.
Sondej M., Iwicki P., Wójcik M., Tejchman J., Stability analysesof a cylindrical steel silo with corrugated sheets and columns, Steel & Composite Structures, 20 (2016) 147–166.

Wang X., Qin Y., Li J., Tian Y., Yang Z., Static contact statuses
between conical silos and granular materials and its influential factors, Transactions of the Chinese Society of Agricultural Engineering, 31 (2015) 65–70.
Wang Y., Lu Y., Jin Y.O., Finite element modelling of wall pressures in a cylindrical silo with conical hopper using an
Arbitrary Lagrangian–Eulerian formulation, Powder Technol, 257 (2014) 181–190.
Xia H., Wassgren C.R., Curtis J.S., Hancock B.C., Ketterhagen
W.R., Yu G., Sphero-Cylindrical Particle Dynamics andStresses in a Vertical Axis Mixer, AIChE Annual Meeting,Pittsburgh, PA, USA, 2012.
Xia H., Wassgren C.R., Curtis J.S., Hancock B.C., Ketterhagen
W.R., Yu G., Internal Load and Moment Distributions of
Rigid, Sphero-Cylindrical Particles in a Stirred Vessel, 14
Aiche Meeting, Atlanta, GA, USA, 2014.

Author’s short biography
Xuewen Wang
Xuewen Wang received the PhD in mechanical design and theory in 2008. He is a full
professor of mechanical engineering in Taiyuan University of Technology, Taiyuan,
China. His research interests include granular material mechanics, modern mechanicaldesign theory and method and mechanical CAD/CAE.

Zhaojian Yang
Zhaojian Yang received the PhD in mechanical design and theory in 1997. He is a full
professor of mechanical engineering in Taiyuan University of Technology, Taiyuan,
China. His research interests include modern design theory and method, mechanicalequipment status monitor and fault diagnosis and mechanical dynamics.

Bo Li
Bo Li received the PhD in mechanical design and theory in 2016. He is a lecturer of
mechanical engineering in Taiyuan University of Technology, Taiyuan, China. His research interests include granular material mechanics.

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Infomation Article

Symposium Reports
The 51st Symposium on Powder Technology
The 51st Symposium on Powder Technology was held at Senri Hankyu Hotel, Osaka, Japan on Wednesday,
September 13, 2017. It was organized by Hosokawa Powder Technology Foundation with the sponsorship of Hosokawa
Micron Corporation. Over 160 people from the industries and universities attended this symposium. The theme ofthe symposium this year was “Powder Technology Required for Creation of Advanced Materials”. There were six
lectures with questions and answers followed by a get-acquainted party for further free discussions.
The first lecture was given by Prof. Adschiri, who was presented the KONA Award last year, on his lifework
research in the field of production and applications of nanoparticles prepared by the Supercritical Hydrothermal
Synthesis method. The further three lectures were carried out by the professors with the diversity of the fields
including solid-liquid separation of colloids, particle packing of the particles in the coated film during drying andpreparation of materials for all-solid-state batteries via a mechanochemical process.
The other two lectures were from the industries and concerned about the development of engineered smart particles for the functional pharmaceutical products by use of a granulation technology and the introduction of new
machines for the wide range of powder processing including grinding mills, air classifies, driers and so on.
The contents of the symposium are shown in the followings.

The 51st Symposium on Powder Technology
Theme: Powder Technology Required for Creation of Advanced Materials
Opening address Mr. Yoshio Hosokawa (President of Hosokawa Powder Technology Foundation)

Session 1 Chaired by Prof. emeritus Ko Higashitani (Kyoto University)• Lecture 1“Continuous Production of Nanoparticles by Supercritical Hydrothermal Synthesis—Nanoparticles Synthesis, Nanohybrid Materials, and Surface Controlled Nanocatalysts—”
Prof. Tadafumi Adschiri (WPI-AIMR, Tohoku University)• Lecture 2“Developments on Solid-Liquid Separation of Colloids”
Prof. Eiji Iritani (Graduate School of Engineering, Nagoya University)
Session 2 Chaired by Prof. Hirofumi Takeuchi (Gifu Pharmaceutical University)• Lecture 3“Particle Packing Process in the Coated Film of Particle Dispersions during Drying”
Assoc. Prof. Yoshiyuki Komoda (Graduate School of Engineering, Kobe University)• Lecture 4“Smart Particle Design for Advanced Functional Formulations—Creation and Evaluation of Opusgran®—”Mr. Yasushi Ochiai (CMC based Drug Development, Sumitomo Dainippon Pharma Co., Ltd.)

283

Session 3 Chaired by Prof. Satoshi Watano (Osaka Prefecture University)• Lecture 5“Preparation of Materials for All-Solid-State Batteries via a Mechanochemical Process”
Prof. Akitoshi Hayashi (Graduate School of Engineering, Osaka Prefecture University)• Lecture 6“The Latest Trend of Development of Powder Equipment”
Dr. Akira Watanabe (Technology Research Institute, Hosokawa Micron Corporation)
Closing remarks

Prof. emeritus Fumiyoshi Saito (Tohoku University)

Symposium on Powder Technology

Get-acquainted Party

2nd International Hosokawa Powder Technology Symposium
As a part of special events to celebrate the 25th anniversary of the establishment of Hosokawa Powder Technology Foundation, the 2nd Hosokawa Powder Technology Symposium was held at Hosokawa Micron Powder Systems
in Summit, New Jersey, USA on Wednesday, October 4, 2017. This symposium was the second overseas conferenceon powder and particle technology organized by Hosokawa Foundation and supported by Hosokawa Micron Corporation as well as Hosokawa Micron Powder Systems, which is a division of Hosokawa Micron International, Inc.
The number of attendees was nearly 100 including more than 10 people from the universities. Most attendees camefrom various locations in USA and also included some from Mexico as well as Japan.
The main subject of this symposium was “Challenges & Opportunities in Particle Characterization & Processing” and there were four lectures by the speakers from both academic and industrial fields after the welcome address from Mr.Yoshio Hosokawa, the President of Hosokawa Powder Technology Foundation and Hosokawa Micron
Corporation, with the closing remarks from Mr. Rob Voorhees, President of Hosokawa Micron International, Inc.
The symposium consisted of lectures of different aspects from bio and nano particle technology, grinding processing, particle characterization and application to the dry powder inhalation as seen in the program below. Additionally the history and activities of Hosokawa Foundation were introduced using poster panels together with
the KONA Powder and Particle Journal exhibited. During the lunch time, discussions were also made among theattendees in front of the actual powder processing machines and characterization devices.

284

2nd International Hosokawa Powder Technology Symposium
Theme: Challenges & Opportunities in Particle Characterization & Processing
Welcome address Mr. Yoshio Hosokawa (President of Hosokawa Powder Technology Foundation)◆ 1 Leveraging Particle and Nano Bio Technologies for Product and Process Innovations

Dr. Brij M. Moudgil – Center for Particulate and Surfactant Systems (CPaSS), University of Florida◆ 2 Size Reduction Technologies for Efficient Powder Processing Systems

Mr. Bill Brown – Hosokawa Micron Powder Systems◆ 3 Particle Shape Analysis – Sometimes It’s Very Important

Dr. Raymond S. Farinato – Solvay Technology Solutions◆ 4 Particle Technology for Dry Powder Inhalers

Dr. Anthony J. Hickey – RTI International, Research Triangle Park
Closing remarks

Mr. Rob Voorhees (President of Hosokawa Micron International, Inc.)

At a lecture

Speakers and organizers

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Infomation Article

The 24th KONA Award
Prof. Adschiri graduated from The University of Tokyo in 1981, and received his Doctorate in Engineering fromthe same institution in 1986. He worked as a Special Research Fellow at JSPS (Japan Society for the Promotion of
Science), following which he was appointed as an Assistant Professor in The University of Tokyo in 1987. As a visiting scholar, he has had the opportunity to carry out research work at the University of Waterloo (1991, Canada),
University of Hawaii (1996, US), and University of Delaware (1997, US).
Prior to joining Tohoku University, the primary focus of his research was on coal conversion technology. In 1989,
he moved to Tohoku University and began studying reactions in supercritical fluids for biomass conversion, chemical recycling of wastes, new organic reactions, and materials synthesis. He is the inventor of the “supercritical hydrothermal synthesis” method for nanoparticles (NPs). This method enables the in-situ organic modification of thesurface of NPs, as well as the direct synthesis of NPs. He led a major national project (30 million USD) in Japan entitled “Super Hybrid Nanomaterials” for fabricating new composite materials of surface-controlled NPs and polymers that simultaneously show properties of ceramics and polymers, based on his supercritical fluid method. Thismethod enables the control of the morphology of NPs, and allows for the exposure of the most reactive surface foruse as a nano-catalyst. The impact of his research is not just constrained to academia; it also has significant application potential in industry. Some of his proposed processes have been commercialized in Japan and elsewhere. In
particular, the first chemical recycling process of waste polymers and the synthesis of supercritical NPs have attracted significant industrial attention.
He has published more than 250 papers, with more than 9000 citations, and has an h-index of over 50. He has
been invited more than forty times to major international conferences in a variety of research fields as a plenary/
keynote/invited lecture. For his research excellence, he has been awarded many prizes, including awards from the
Chemical Society Japan (Science Award), Society of Chemical Engineering of Japan (Best Research Award, and
SCEJ Society Award), Japan Energy Society (Progress Award), etc. In addition to academic societies, he is the recipient of the honorable Japan Invention Award from the Japanese government and three-time winner of the Minister’s awards of MEXT (Ministry of Education, Culture, Sports,
Science and Technology) as well. Ten years ago, the Japanese
government selected five (now nine) distinguished research teams
as part of the World Premier Research Center Initiative (WPI),
and he had the honor to be selected as a principal researcher for
the Advanced Institute of Materials Research (WPI-AIMR) in
Tohoku University.
Currently, Prof. Adschiri serves as the Vice President of ISHA
(International Solvothermal Hydrothermal Association), Vice
President of IASCF (International Society for Advancement ofSupercritical Fluids), Chairman of the Asian Society of Supercritical Fluids, and Vice President of the Society of Chemical Engineers, Japan. In 2014 he was assigned as a member of Science
Council of Japan (six-year appointment followed by a conjunction
membership for an additional twelve years). In 2016, he became amember of the Engineering Academy of Japan (life time).

286

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Infomation Article

General Information
History of the Journal
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Hosokawa Powder Technology Foundation (Hosokawa Foundation).
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