ISSN 0288-4534

CODEN: KPPJAD

KONA

Powder andParticle Journal

No.31 (2014)

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

KONA Powder and Particle Journal No. 31 (2014) 

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

About the Cover:Self-reporting materials belong to a subclass of intelligent
materials which exhibit the capability to provide the authentic
signal of structural damage propagating inside. The cover
picture demonstrates a novel concept of self-reporting composite materials built from multifunctional ZnO tetrapods(SEM image) and a polymer matrix. The blue and green luminescent emissions from ZnO tetrapods embedded in thepolymer matrix are altered under stress and by monitoring
the relative change in their intensities the internal damage
can be identified. Please read the full article on pp. 91–109.

http://www.kona.or.jp

Editorial Board
Editor-in-Chief
J. Hidaka(Doshisha Univ., JAPAN)

Asia / Oceania Editorial Board
Y. Fukumori(Kobe Gakuin Univ., JAPAN)
K. Higashitani(Kyoto Univ., JAPAN)
H. Kage(Kyushu Institute of Technology, JAPAN)
Y. Kang(Chungnam National Univ., KOREA)
J. Li(Chinese Academy of Science, CHINA)
H. Masuda(Professor Emeritus of Kyoto Univ., JAPAN)
S. Matsusaka(Kyoto Univ., JAPAN)
M. Naito(Osaka Univ., JAPAN)
K. Nogi(Professor Emeritus of Osaka Univ., JAPAN)
K. Okuyama(Hiroshima Univ., JAPAN)
Pradip(Tata Research Development and Design
Centre, INDIA)
M. Rhodes(Monash Univ., AUSTRALIA)
M. Takahashi(Nagoya Institute of Technology, JAPAN)
H. Takeuchi(Gifu Pharmaceutical Univ., JAPAN)
W. Tanthapanichakoon (Tokyo Institute of Technology, JAPAN)
Y. Tsuji(Professor Emeritus of Osaka Univ., JAPAN)
Secretariat
T. Yokoyama(Hosokawa Powder Technology Foundation,
JAPAN)
L. Cui(Hosokawa Micron Corporation, JAPAN)
Europe / Africa Editorial Board
M. Ghadiri
B. Biscans
L. Gradon
J. Marijnissen
G. Meesters
W. Peukert
S.E. Pratsinis
J. M. Valverde
Secretariat
S. Sander
N. Faerber(Univ. of Leeds, UK) – Chairman(Univ. de Toulouse, FRANCE)(Univ. of Warsaw, POLAND)(Univ. of Delft, NETHERLANDS)(Univ. of Delft, NETHERLANDS)(Univ. Erlangen, GERMANY)(ETH Zurich, SWITZERLAND)(Univ. of Seville, SPAIN)(Hosokawa Alpine AG, GERMANY)(Hosokawa Alpine AG, GERMANY)

American Editorial Board
B.M. Moudgil(Univ. of Florida., USA) – Chairman
D.W. Fuerstenau(Univ. of California, USA)
F. Concha(Univ. of Concepció, CHILE)
A.I. Hickey(Univ. of North Carolina, USA)R. Hogg(Pennsylvania State Univ., USA)
V.A. Marple(Univ. of Minnesota, USA)R. K. Rajamani(Univ. of Utah, USA)
A. Rosato(New Jersey Institute of Technology, USA)
Secretariat
C.C. Huang(Hosokawa Micron International INC., USA)

■ Publication Office

Headquarters of Hosokawa Micron Corporation

Hosokawa Powder Technology Foundation (http://www.kona.or.jp)(in the headquarters building of Hosokawa Micron Corporation)
Shodai- Tajika 1-9, Hirakata, Osaka, 573-1132 Japane-mail : info@kona.or.jp

KONA Powder and Particle Journal No. 31 (2014) 

http://www.kona.or.jp

Contents<Editorial>
Editorʼs Preface 1<Review Papers>
A PM1.0/2.5/10 Trichotomous Virtual Impactor Based
Sampler: Design and Applied to Arid Southwest Aerosols
Part II: Application to Arid Southwest Aerosols

Virgil Marple, Dale Lundgren and Bernard Olson
   

2

The Relationships among Structure, Activity, and Toxicity
of Engineered Nanoparticles

Christie M. Sayes 
10

Nanophosphor Coatings: Technology and Applications,
Opportunities and Challenges

Roman Kubrin 
22

A Review of the Fire and Explosion Hazards of Particulates

Saul M. Lemkowitz and Hans J. Pasman 
53

Design of Optimum Sampling Plans for Dry Powders
and Slurries

Hassan El-Shall and Brij M. Moudgil 
82

Versatile Fabrication of Complex-Shaped Metal Oxide
Nano-Microstructures and their Interconnected Networks
for Multifunctional Applications

Yogendra Kumar Mishra, Sören Kaps, Arnim Schuchardt,
Ingo Paulowicz, Xin Jin, Dawit Gedamu, Sebastian Wille,
Oleg Lupan and Rainer Adelung 
92

Aerosol Processing of Graphene and Its Application
to Oil Absorbent and Glucose Biosensor

Sun Kyung Kim, Hankwon Chang, Jeong-Woo Choi,
Jiaxing Huang and Hee Dong Jang 
111

Physicochemical Properties and Factors that Induce
Asbestos-Related Respiratory Disease

Hiroto Izumi and Yasuo Morimoto 
126<Original Research Papers>
Transient Flow Induced by the Adsorption of Particles

Naga Musunuri, Bhavin Dalal, Daniel Codjoe,
Ian S. Fischer and Pushpendra Singh 
135Characterization of Oxide-Dispersion-Strengthened (ODS) Longzhou Ma, Bruce S.-J. Kang, Mary A. Alvin andAlloy Powders Processed by Mechano-Chemical-Bonding C. C. Huang 
146(MCB) and Balling Milling (BM)Synthesis of Calcium Carbonate Particles in
Octylamine/Water Bilayer Systems

Jun Wang, William B. White and James H. Adair 
156

Development of a Particulate Solids
Thermal Mass Flowmeter

Mary Kato, John Pugh and Don McGlinchey 
163

The Use of Highly Ionized Pulsed Plasmas for the
Synthesis of Advanced Thin Films and Nanoparticles

Iris Pilch, Daniel Söderström, Daniel Lundin and
Ulf Helmersson 
171

Photophoresis – a Forgotten Force ??

Helmuth Horvath 
181

Population Balance Model for Crushed Ore
Agglomeration for Heap Leach Operations

Nikhil Dhawan, Samira Rashidi and Raj K Rajamani
    

200

Morphology and Nanostructure of Granular Materials
Built from Nanoparticles

Jose L. Castillo, Santiago Martin, Daniel Rodriguez-Perez,
Alvaro Perea and Pedro L. Garcia-Ybarra 
214

Scalable Production of Nanostructured Particles
using Atomic Layer Deposition

Aristeidis Goulas and J. Ruud van Ommen 
234

Recycling-Oriented Investigation of Local Porosity
Changes in Microwave Heated-Concrete

Nicholas R. Lippiatt and Florent S. Bourgeois 
247

Numerical Prediction of the Bulk Density of GranularParticles of Different Geometries

Kasra Samiei, Girma Berhe and Bernhard Peters 
265<Information Articles>
The 47th Symposium on Powder Technology and the Ceremony for the 20th Anniversary of Establishment of
Hosokawa Powder Technology Foundation 271
The 20th KONA Award 273
General Infomation 274

KONA Powder and Particle Journal No. 31 (2014) 01/Doi:10.14356/kona.2014022

Editorial

Editorʼs Preface
Jusuke Hidaka, Editor-in-Chief
Doshisha University, JAPANI am pleased to announce the issue of KONA Powder and Particle Journal No. 31. The issue contains outstanding review papers pertaining to a wide range of fields in powder technology—extending from very usefulparticle production technologies that provide excellent control of particle characteristics including shape andimportant subjects encountered in actual powder industrial processes such as dust explosion and powder sampling method for quality control, to nanoparticle toxicity and risk assessment—topics that have attracted agreat deal of interest in recent years. These review papers will provide the readers with detailed knowledge on
the continuing rapid progress of powder technology involving powder processing technologies and the development of advanced functional materials related to powders.
KONA Powder and Particle Journal aims to publish comprehensive review papers authored by researchers
who have made remarkable achievements on powder technology. It should make significant contribution to theadvancement of powder technology.
This year sees the start of this journal’s publication through the Japan Science and Technology Information
Aggregator, Electronic (J-STAGE), the online publication platform provided by Japan Science and Technology
Agency (JST), a Japanese government agency. J-STAGE is a system for international distribution of journals
that are published in Japan. Through its publication via this system, KONA can now be accessed easily,
promptly, and free of charge by researchers worldwide. Moreover, although KONA is an annually printed journal, J-STAGE allows for its early publication. The papers reviewed by the Editorial Boards in Europe, America,and Asia will be distributed globally at an earliest possible time in the form of an online journal.
In the publication of a journal on J-STAGE, its article format must be standardized, and writing guidelines
need to be more strictly adhered to than was previously done. Therefore, I ask you to make use of the template
prepared by the Editorial Boards to meet this requirement.
The development of advanced particles and powder materials is of increasing importance in solving difficult
problems faced by the modern society. This journal will provide powder technology researchers worldwide
with prompt and detailed information on research trends pertaining to new powder materials and process development. By publishing review papers on the different aspects of powder technology, they inform us not only
on advances in each special field but also educate us in other areas where we may find keys to solving futureengineering problems on powder technology.
I sincerely hope that this journal will be a platform for lively discussion by powder technology researchers. I
would like to thank you for your cooperation.

Jusuke Hidaka
Editor-in-Chief
November 22, 2013©2014 Hosokawa Powder Technology Foundation

1

KONA Powder and Particle Journal No. 31 (2014) 2–9/Doi:10.14356/kona.2014001

Review Paper

A PM1.0/2.5/10 Trichotomous Virtual Impactor Based Sampler:
Design and Applied to Arid Southwest Aerosols
Part II: Application to Arid Southwest Aerosols †Virgil Marple 1*, Dale Lundgren 2 and Bernard Olson 1
1
2

Particle Calibration Laboratory, University of Minnesota, USA
University of Florida, USA

Abstract
A PM1.0/2.5/10 Trichotomous sampler has been developed to determine if the particles in the saddle point between
the coarse and fine particle modes (specifically the 1.0 μm to 2.5 μm size range) are primarily coarse or fine modeparticles. The sampler consists of a standard high volume sampler with two high volume virtual impactors (onewith a cut size of 2.5 μm and the other with a cut size of 1.0 μm) inserted between the PM10 inlet and the 8 × 10
inch after filter. Filters in this sampler were analyzed with ion chromatography (IC) to determine SO4 –2
concentrations, representing a specie primarily found in the fine mode aerosol and proton-induced X-ray emission(PIXE) for determining concentrations of Si, S, Ca and Fe, representing species normally found in coarse mode
aerosols. Application of this sampler to Phoenix, AZ, representing an arid region, showed that particles in thesaddle point consisted of about 75% of particles from the coarse mode and about 25% from the fine mode.
Keywords: atmospheric aerosols, virtual impactors, PM10, PM2.5, PM1

Introduction
In the mid-1990s the United States Environmental Protection Agency (EPA) was reviewing the National Ambient
Air Quality Standards (NAAQS) for particulate matter(PM). The agency was devising a new Federal Reference
Method (FRM) and set a new fine particle standard ateither PM1 or PM2.5 to replace the then current 24-hour
PM10 standard of 150 micrograms per cubic meter (μg/m3).
When the fine particle standard was being established,
there was much discussion amongst experts as to whether
the standard should be set at 1.0 μm or 2.5 μm. The problem arose from the nature of the particle size distributionsin atmospheric aerosols. Whitby (1978) discovered that
atmospheric particle size distributions were trimodal innature, with fresh combustion particles in the smallest
mode, aged combustion particles in the intermediate mode(fine particle mode) and mechanically generated particles
in the largest mode (coarse particle mode). These fine andcoarse particles have different chemical and physical

†
1

*

2

Accepted: January 23, 2013
111 Church Street S. E Minnneapolis, MN 55455, USA
Corresponding author:
E-mail: marple@me.umn.edu
TEL: +1-612-625-3441 FAX: +1-612-625-6069

characteristics and come from different sources (John,
2011). Dr. J.P. Lodge stated in 1995 in the Journal of the
AWMA in a “Critical Review Discussion: Measurement
Methods to Determine Compliance with Ambient Air
Quality Standards for Suspended Particles” (Watson et. al.,1995) that:“I had a lengthy discussion with the late K.T. Whitby
over the optimum upper boundary for fine particles,
which he held to be “... 1.8 μm, or, if you want a purer
sample of fine particles, 1 μm.” If fine particles are thecause of health effects, and if routine monitoring data
are used in epidemiological studies, as Dr. Chow anticipates, we must advocate the use of PM1.0 to clarify thecomposition of the population of the fine particle
modes.”
This statement would indicate that an ideal particle cut
size would be one below which almost all the fine particles are contained, but very few coarse particles are present. Particles in this size range consist of particles fromthe lower tail of the coarse particle mode and particles
from the upper tail of the fine particle mode (see Fig. 1).
Of specific interest in this study was the atmosphericparticulate matter of the arid southwest USA. The city chosen to study was Phoenix, Arizona from May to October,©2014 Hosokawa Powder Technology Foundation

Virgil Marple et al. / KONA Powder and Particle Journal No. 31 (2014) 2–9

1995. In this area of the country the coarse particle modecan be much larger than the fine particle mode and, thus,
may dominate the particulate matter in the saddle region
between the fine and coarse particle modes.
The concern was that the large particle mode lower tail,consisting of fugitive and windblown dust, could dominate the particles in the 1 to 2.5 μm size range, a test program was initiated to collect particulate matter in this size
range and determine the fraction of the particulate matterthat may be coarse mode aerosol.
In part I of this paper, published in the 2012 issue of
KONA (Marple et.al., 2012), a PM1.0/2.5/10 trichotomous
sampler (see Fig. 2) was developed to specifically answer
the question of what fraction of particles in the 1.0 μm to
2.5 μm size range are part of the fine particle mode andwhat fraction are from the coarse particle mode, isdescribed.

Review of the PM1.0/2.5/10 trichotomous sampler
In the PM1.0/2.5/10 trichotomous sampler two High Volume
Virtual Impactors (HVVIs), with cutsizes of 2.5 μm and1.0 μm were inserted between the PM10 size selective
inlet and the 8×10 inch (20×25 cm) filter of a standard
high volume 40 cfm (1.13 m3/min) flowrate PM10 sampler(Marple and Olson, 1995). Fig. 2a shows the assembled
trichotomous sampler, while Figs. 2b and 2c shows the
sampler opened to provide access to the 2.5 μm and the
1.0 μm HVVIs, respectively.
By using nine 47 mm filters at various locations in thetrichotomous sampler, concentration and composition ofparticles could be obtained for particulate matter in theranges of PM10, PM2.5–10, PM2.5, PM1–2.5, and PM1. Fromdata analysis of these filters, the fraction of the particulatematter in the 1.0 μm to 2.5 μm size range that are fine andcoarse mode particles can be determined. See Part I for
further details of this sampler.

Mass and specie analysis techniquesFig. 1Fine and Coarse Particle Modes. From U.S. Environmental Protection Agency (1982)

Fig. 2The net mass gains on the filters were determined gravimetrically by weighing them before and after sampling.
The weighings were conducted in a controlled environment
where the temperature was maintained at 24 ± 3°C and therelative humidity at 30 ± 10% to minimize loss of soluble
and volatile compounds. As a quality control measure,approximately one out of ten filters was later reweighed.
Several methods were available to determine elemental compositions of the PM collected on the filters.
For this study, proton-induced X-ray emission (PIXE)

Photos of PM1.0/2.5/10 Trichotomous Sampler. a) Assembled sampler; b) 2.5 μm HVVI; c) 1.0 μm HVVI
A-PM10 inlet; B-Intermediate chamber; C-Base; D-2.5 μm HVVI; E-1.0 μm HVVI; F-After filter

3Virgil Marple et al. / KONA Powder and Particle Journal No. 31 (2014) 2–9

and photon-induced x-ray fluorescence (XRF) methods
were used. Both of these methods are commonly used dueto their nondestructive multi-element capabilities and relatively good sensitivities.
Aerosol ions (i.e., the water-soluble portion of the suspended particles in the atmosphere) were quantified using
ion chromatography (IC). Using the IC method, theextracted sample passes through an ion-exchange column
and the separated ions are individually analyzed by anelectroconductivity detector.
Volatile aerosol materials such as organics and nitrates
were not included in this study. Although a large portionof the fine aerosol often consists of volatile organics ornitrates, little of the remaining (weighable) PM collectedon the filters was expected to be volatile, since the filters
were exposed to the high summer temperatures of Phoenix(often exceeding 40°C during the day).

Mass concentrations
PM mass concentrations (μg/m3) were determined by
dividing the net weight gain (μg) on a filter by the total air
volume (m3) that passed through it during the 24-hour
sampling period. Although a small decrease in flowrate
can be expected at the end of sampling period due to aslightly higher pressure drop caused by particle loadingon the filters, no flowrate correction was deemed necessary for the purposes of this study. Mass concentrations
were, however, divided by an appropriate “flow factor” toaccount for the fact that the samplers did not run forexactly 24 hours in most cases. The general equation used
for mass calculations is as follows:

PM X =

Δm
V× f

(1)

Where PM X = PM mass concentration for size fraction
× (μg/m3), Δm = mass gain on filter (μg), V = flow volume
through filter in 24 hours (m3) and f = flow factor (fractionof 24-hour day that sampler was operated). Thus, the following equations were then used to calculate mass concentrations for various PM size fractions:Δm (PM10 )PM10 =
81.6× f(2)

Δm (PM2.5 )81.6× f(3)

∑ Δm (PM1)81.6× f

(4)

PM 2.5 =PM1 =4

PM 2.5−10 =PM1−2.5 =Δm (PM2.5)
10163× f(5)∑Δm ( PM1−2.5 ) − ∑Δm (PM1)1469× f(6)Δm ( PM2.5−10 ) −In equations (5) and (6), the terms {Δm(PM2.5–10)} and{ΣΔm(PM1–2.5)} are the masses collected on the minor
flow filters of the 2.5 μm and 1.0 μm HVVIs, respectively.
The Σ sign in equation (6) indicates summing the masscollected on both filters being used to collect minor flow
particles in the 1.0 μm HVVI. As described in Part I of
this paper, particles collected in the minor flow of the
HVVIs contain background particles (particles of a size
less than the cutsize of the HVVI) and the mass of thesebackground particles must be subtracted from the mass ofthe particles in the minor flow to determine the true massof particles in the minor flow that are larger than the cutsize of the HVVI. In equations (5) and (6), this background mass is represented by the terms {Δm(PM2.5)/10}and {ΣΔm(PM1)} in the 2.5 μm and 1.0 μm HVVIs,
respectively. The factor of 10 in the denominator of equation (5) is due to the flowrate of the filter collecting the
major flow particulate matter of the 2.5 μm HVVI is
2 cfm and the flowrate of the filter collecting particulatematter in the minor flow is 0.2 cfm.
Using equations (2) to (6), results of the 6-month sampling program in Phoenix are summarized as mass concentrations in Table 1 and as percent of PM10 in Table 2.
Average PM1, PM 2.5 and PM10 concentrations for the
Phoenix area are 5.9, 8.6, and 32.8 μg/m3, respectively. In
terms of percentages, PM10 was made of 69% PM2.5–10,
26% PM2.5 (< 2.5 μm), 8% PM1–2.5, and 18% PM1 (< 1 μm).
It is also interesting to note that average % PM1–2.5 appears
to be nearly constant (at about 8%) for all six months. A
comparison of measured PM10 and summed PM10 (PM2.5–10+ PM1–2.5 + PM1) can also be seen in Tables 1 and 2. In
general, summed PM10 is slightly less than measured
PM10, most likely due to particle loss in the HVVIs.

Intermodal size range (PM1–2.5) calculations
Atmospheric aerosol is formed by two basic processes:
the dispersion process, which is the breakup of solid andliquid particles; and the condensation/reaction process,which represents particle formation by coming together ofgases and smaller particles (including surface reactions).
Aerosol formed by the dispersion mechanism is generallyof larger size (normally > 1 μm in diameter) and will bereferred to as “coarse” mode aerosol (and the particles ascoarse particles) (ref). On the other hand, aerosol formedby the condensation/reaction mechanism is usually ofVirgil Marple et al. / KONA Powder and Particle Journal No. 31 (2014) 2–9

Table 1 Summary of PM concentrations (μg/m3), Phoenix, AZ
Month(1995)

PM10

PM2.5

PM1

PM2.5–10

PM1–2.5

PM10(PM2.5–10+PM1–2.5+PM1)

May

25.8

6.6

4.4

18.4

2.2

25.0

June

34.0

8.8

5.7

26.8

3.3

35.7

July

35.0

8.6

5.8

26.3

2.9

35.0

August

25.9

7.9

5.7

15.3

2.0

23.0

September

26.9

7.8

5.8

16.1

2.0

23.9

October

57.8

14.2

9.9

35.7

4.2

49.8

Average

32.8

8.6

5.9

22.6

2.7

31.3

Table 2

Phoenix PM data expressed as percentages of PM10

Month(1995)

PM10

PM2.5

PM1

PM2.5–10

PM1–2.5

PM10(PM2.5–10+PM1–2.5+PM1)

May

100%

26%

17%

72%

8%

97%

June

100%

26%

17%

79%

10%

105%

July

100%

25%

17%

75%

8%

100%

August

100%

30%

22%

59%

8%

89%

September

100%

29%

21%

60%

8%

89%

October

100%

25%

17%

62%

7%

86%

Average

100%

26%

18%

69%

8%

95%

ucts). The following algorithms were developed:
smaller size (normally < 2.5 μm in diameter) and will bereferred to as “fine” mode aerosol (and the particles as(7)
X +Y =
I
fine particles). All diameters are of aerodynamic particle
size (i.e., a unit density spherical particle with equivalent
I % SI( X %SC ) + (Y %SF ) =(8)
aerodynamic properties).
Intermodal size range (PM1–2.5) calculations in thiswhere X = mass contribution from coarse mode (μg/m3),
study were made using chemical composition data
Y = mass contribution from fine mode (µg/m3), I = PM1-2.5
obtained from the PM1, PM1–2.5, and PM2.5–10 filter samples.
mass (μg/m3), %SC = percent of species in PM2.5–10 (usedThe following assumptions were made for the calculations:
to represent the coarse mode), %SF = percent of species in
1) Intermodal aerosol is composed of coarse and fine mode
PM1 (used to represent the fine mode), %SI = percent ofaerosol with the two modes overlapping in the intermodal
species in PM1–2.5 (considered as the intermediate range).
size range; 2) Both coarse and fine modes are chemicallyEquations (7) and (8) can easily be solved for X and Y,
homogeneous over their respective particle size ranges; 3)
since X and Y are the only two unknowns. The percent ofCoarse mode aerosol is contained within the 1 to > 10 μm
any specie “i ” in the intermediate range that is contributed
size range, and the chemical composition of the coarse
by the coarse, (%X)i, and fine, (%Y)i, modes can then bemode aerosol is fairly represented by that of PM2.5–10; andcalculated. For the coarse mode contribution:4) Fine mode aerosol is contained within the 0 to 2.5 μm( %SI )i − ( %SF )isize range, and the chemical composition of fine mode
(9)
=
× 100
( % X )i( %SC )i − ( %SF )iaerosol in fairly represented by that of PM1 (i.e., < 1 μm).
Based upon these assumptions, it is possible to calculate
And for the fine mode contribution:
how much of the intermodal particle mass was contributed( %SI )i − ( %SF )iby the coarse mode PM (wind-blown dust) and how much
(10)
=
× 100
( %Y )i( %SC )i − ( %SF )iby the fine mode PM (gas reaction or condensation prod-5

Virgil Marple et al. / KONA Powder and Particle Journal No. 31 (2014) 2–9

Sample Calculation
Example calculations are based on data from two Trichotomous samplers for July 19.1995:
Mass Conc. (μg/m3)

SO4 –2 Data

Unit 1 Unit 2 Average (μg/m3) %PM2.5–10 (coarse)

14.06 12.23

13.15

0.27

2.1

PM1–2.5 (intermediate)

1.75

1.62

1.68

0.13

7.7

PM1 (fine)

5.53

4.07

4.80

1.71

35.6

Using equations (9) and (10),%X = (7.7 − 35.6)/(2.1 − 35.6)= 83% contribution from coarse modeand%Y = (7.7 − 2.1)/(35.6 − 2.1)
= 17% contribution from fine modeThus, this example indicates that 83% of the SO4 –2 particles in the intermediate region (sizes from 1.0 to
2.5 μm) are from the lower tail of the coarse mode and
17% are from the upper tail of the fine mode.
The data gathered from the trichotomous samplers
from May to October, 1995, was analyzed using themethod laid out in the above sample calculation. Two setsof data were chosen for analysis; 1) data from six days in
July, 1995, was analyzed by ion chromatography (IC) and2) data from five days in May, 1995, was analyzed byproton-induced X-ray emission (PIXE).
IC analyses were used to determine concentrations forthe anions SO4−2, NO3−, and Cl−. Table 3 presents the cal-Table 3Day

Data quality assessment
As with any field project, some sampling and analyticalproblems were encountered in this study. To ascertain thatthe data presented here is statistically valid, certain data
reduction procedures were carefully followed in addition
to the standard laboratory quality control measures. For
example, no apparently-out-of-line data (i.e., does not fallwithin the 95% confidence limits) was invalidated, unlessthe cause was known or obvious (e.g., power failure).
When two samplers were run, mass concentrations wereaveraged between both samplers as well as between two
filters of the same particle size, so that the data are statis-

Sulfate and mass data for six July days (μg/m3)
PM2.5–10 (Coarse)

PM1–2.5 (Intermediate)PM1 (Fine)

%X*

Mass

Sulfates

Mass

Sulfates

Mass

Sulfates

7/15/95

12.94

0.19 (1.5%)

1.40

0.09 (6.4%)

5.70

1.20 (21.1%)

75%

7/19/95

13.15

0.27 (2.1%)

1.68

0.13 (7.7%)

4.80

1.71 (35.7%)83%

7/23/95

20.92

0.30 (1.4%)

2.79

0.10 (3.6%)

5.87

0.78 (13.3%)

82%

7/26/95

29.98

0.36 (1.2%)

3.15

0.13 (4.1%)

3.54

1.12 (31.6%)

90%

7/28/9562.39

0.26 (0.4%)

5.38

0.16 (3.0%)

11.26

1.41 (12.5%)

79%

7/30/95

74.02

0.64 (0.9%)

7.68

0.20 (2.6%)

6.86

1.34 (19.5%)

91%

Average

35.57

0.34 (1.0%)

3.21

0.14 (4.4%)

6.34

1.26 (19.9%)

83%

X* is the calculated coarse mode contribution to PM1–2.5 (See text).

6

culated percent contributions of coarse and fine mode PM
to the intermediate size PM (PM1–2.5), based upon SO4 –2
concentration data for six July days of high, medium, andlow mass concentrations. The results indicate that thecoarse mode contribution to the intermodal size varies
from 75% to 91% (with an average of 83%), and therefore,
the fine mode contributions ranges from 9% to 25% (withan average of 17%). Due to their instability and associatedanalytical problems, the contribution analysis of NO3– andCl– were found to be inconclusive, and are not shown.
The PIXE results indicated that Si, S, Ca, Fe, K, and Al
were among the most abundant species in the samples
analyzed. Therefore, they were chosen for the elemental
contribution analysis in this study. The K and Al contribution results were questionable and thus excluded. Elemental
concentrations for the five days in May are shown in
Table 4. Table 5 shows the contribution results fromanalysis of the data in Table 4.
The results in Table 5 clearly indicate that most of the
PM in the intermediate region is associated with coarse
mode particulate.

Virgil Marple et al. / KONA Powder and Particle Journal No. 31 (2014) 2–9

Table 4

Elemental data for five May days (μg/m3)

5/2/95

5/6/95

5/18/95

5/19/95

5/26/95

Average

Total Mass

Si

S

Ca

Fe

K

Al

PM2.5–10

15.67

1.82

0.06

0.69

0.64

0.27

0.61

PM1–2.5

2.03

0.20

0.03

0.03

0.07

0.03

0.08

PM1

3.04

0.05

0.18

0.01

0.03

0.02

0.03

PM2.5–10

11.77

1.37

0.05

0.42

0.48

0.20

0.48

PM1–2.5

1.66

0.21

0.03

0.05

0.06

0.03

0.08

PM1

3.88

0.04

0.21

0.01

0.01

0.02

0.02

PM2.5–10

32.38

3.93

0.11

1.34

1.50

0.58

1.29

PM1–2.5

2.70

0.20

0.03

0.07

0.11

0.03

0.07

PM1

8.84

0.03

0.20

0.01

0.03

0.02

0.01

PM2.5–10

20.55

1.95

0.07

0.68

0.69

0.29

0.65

PM1–2.5

2.08

0.16

0.03

0.06

0.07

0.03

0.06

PM1

5.76

0.03

0.15

0.01

0.02

0.03

0.01

PM2.5–10

24.73

2.25

0.08

0.80

0.89

0.34

0.76

PM1–2.5

2.18

0.19

0.03

0.06

0.08

0.03

0.07

PM1

5.54

0.03

0.23

0.01

0.02

0.03

0.02

PM2.5–10

21.02

2.26

0.07

0.79

0.84

0.34

0.76

PM1–2.5

2.03

0.19

0.03

0.06

0.08

0.03

0.07

PM1

5.41

0.03

0.19

0.01

0.02

0.02

0.02

Si = Silicon, S = Sulfur, Ca = Calcium, Fe = Iron, K = Potassium, Al = Aluminum

Table 5Contribution to the intermodal (PM1–2.5) aerosol
from coarse and fine particle modes
Average for the five days in May, 1995

Specie

%X

%Y

Si

79

21

S

67

33

Ca

76

24

Fe

85

15

Average78

22

tically more representative.
Table 6 shows precision data for the two co-located trichotomous samplers. The EPA performance specifications
call for precision in the range of ± 5 μg/m3 for PM10 concentrations less than 80 μg/m3 and ± 7% for concentrations
over 80 μg/m3.

Conclusions

lows: First, it can be shown that most of the PM10 in thisarea is made up of coarse mode aerosol (PM2.5–10). Secondly, most of the intermediate size aerosol (PM1–2.5) was
due to the coarse mode (dispersion) aerosol. Therefore,
crustal materials from sources such as windblown dust are
the most significant contributor to the PM concentration inthis area, far more so than the combustion related sources.
Based up on the calculations presented, it appears that PM
measurement using a cutpoint of 1 μm would capture
about 90% as much fine mode mass as those made using a
cutpoint of 2.5 μm, and would minimize any interference
from natural sources (e.g., windblown dust). The reader
should bear in mind that these results and conclusions are
only valid for conditions similar to those at the Phoenix
site, namely the dry, arid Southwest.

Acknowledgements
Development and calibration of the PM1.0/2.5/10 Trichotomous sampler has been supported by the National Mining
Association.

Results of the Phoenix PM10/PM2.5/PM1 study using thetrichotomous sampler technique can be summarized as fol-7

Virgil Marple et al. / KONA Powder and Particle Journal No. 31 (2014) 2–9

Table 6

Precision data for the two trichotomous samplers
May

June

July

AugustAverage

Unit 1

26.9

34.4

34.9

25.8

30.5

Unit 2

24.7

33.5

35.1

25.9

29.8

S.D. (μg/m )

5.5

2.6

2.6

1.8

3.1

S.D. (%)

20.3

7.0

7.9

6.8

10.5

6.6

9.5

8.9

7.9

8.2

6.6

8.1

8.3

7.9

7.7

S.D. (μg/m )

1.0

1.0

2.9

0.9

1.5

S.D. (%)

16.7

11.3

27.6

11.5

16.8

4.4

5.9

6.0

5.9

5.6

4.4

5.5

5.6

5.6

5.3

PM10

3

PM2.5
Unit 1
Unit 2
3

PM1
Unit 1
Unit 2
3

S.D. (μg/m )

0.9

2.3

2.9

1.8

2.0

S.D. (%)

22.1

54.5

45.4

32.9

38.7

Unit 1

17.8

25.3

26.1

15.3

21.1

PM2.5–10
Unit 2

19.0

28.3

26.5

15.3

22.3

S.D. (μg/m3)

1.4

6.3

2.9

1.4

3.0

S.D. (%)

7.0

28.1

11.3

13.6

15.0

PM1–2.5
Unit 1

2.2

3.6

3.0

2.0

2.7

Unit 2

2.2

2.9

2.9

1.9

2.5

S.D. (μg/m3)

0.1

0.3

0.5

0.2

0.3

S.D. (%)

5.5

7.5

29.6

13.4

14.0

24.4

34.8

35.0

23.1

29.3

25.6

36.7

35.0

22.8

30.0

S.D. (μg/m )

1.7

5.9

3.7

2.1

3.4

S.D. (%)

5.9

18.3

10.0

9.1

10.8

PM10 (sum)Unit 1
Unit 2
3

S.D.= Standard Deviation of the differences between Unit 1 and Unit 2.
For PM10 samplers, EPA specifies precision of 5 μg/m3 for conc. less than 80 μg/m3, and 7% for conc. greater than 80 μg/m3.

References
John W., Size distribution characteristics of aerosols, in:Kulkarni P., Baron P.A., Willeke K. (Eds.), Aerosol Measurement: Principles, Techniques, and Applications, 3rd
Edition, Wiley, New Jersey, 2011, pp. 41–54.
Marple V.A., Lundgren D.A., Olson B.A., A PM1.0/2.5/10 trichotomous virtual impactor based sampler: Design and applied
to arid southwest aerosols—Part I: Design, KONA Powder
and Particle Journal, 30 (2012) 15–21.
Marple V.A., Olson B.A., A high volume PM10/2.5/1.0 trichotomous
sampler, in: Particulate Matter: Health and Regulatory
Issues, VIP-49, Air and Waste Management Assoc. International Specialty Conference, Pittsburg, PA, 1995, pp. 237–261.

8

U.S. Environmental Protection Agency, Air quality criteria forparticulate matter and sulfur, EPA-600/882-029b, December, 1982.
Watson J.G., Thurston G., Frank N., Lodge J.P., Wiener R.W.,
McElroy F.F., Kleinman M.T., Mueller P.K., Schmidt A.C.,
Lipfert F.W., Thompson R.J., Dasgupta P.K., Marrack D.,
Michaels R.A., Moore T., Penkala S., Tombach I., Vestman
L., Hauser T., Chow J.C., Measurement Methods to Determine Compliance with Ambient Air Quality Standards for
Suspended Particles, Journal of the air & Waste Management Association, 45 (1995) 666–684.
Whitby K.T., The physical characteristics of sulfur aerosols,
Atmospheric Environment, 12 (1978) 135–159.

Virgil Marple et al. / KONA Powder and Particle Journal No. 31 (2014) 2–9

Author’s short biography
Virgil A. Marple
Virgil A. Marple is a Professor in the Mechanical Engineering Department at the University of Minnesota. He received his Ph.D. from the University of Minnesota in 1970.
He is Director of the Particle Calibration Laboratory, and his research interest includes
development of inertial classifiers, measurement of mining related aerosol in both thecoal and taconite industries and measurement of pharmaceutical aerosols.

Dale A. Lundgren
Dale A. Lundgren is Professor Emeritus—Environmental Engineering Department, University of Florida. He received his Ph.D. from the University of Minnesota in 1973. His
recent research interest has been as a consultant to the National Resource Research Institute (University of Minnesota Duluth campus) studying particulate concentrations in cities and taconite mines on the Minnesota Iron range.

Bernard A. Olson
Bernard A. Olson is a Research Associate and Manager of the Particle Calibration Laboratory in the Mechanical Engineering Department at the University of Minnesota. He
received his BSME, MSME, and Ph.D. from the University of Minnesota. For the past
22 years his research has been in the design, testing and numerical modeling of aerosol
sampling instruments, characterization of mining aerosols related to the coal mine andtaconite industries and effluents generated by cooking appliances in the commercial
kitchen industry.

9

KONA Powder and Particle Journal No. 31 (2014) 10–21/Doi:10.14356/kona.2014002

Review Paper

The Relationships among Structure, Activity, andToxicity of Engineered Nanoparticles †Christie M. Sayes
1

Center for Aerosol and Nanomaterials Engineering, RTI International, USA

Abstract
Particles within the nanometer size regime (1–100 nm) exhibit properties across quantum and classical mechanics.
An example of the quantum mechanical nature of some particles includes their ability to bend light and change
color appearance in suspension. An example of the classical mechanical nature of some particles includes theirtendency to agglomerate in suspension. Both of these phenomenons are extensively studied in the literature andare the subject of many research projects that examine the utility of nanoparticles in biomedical andenvironmental applications. However, these unique properties have also been shown to induce unintentional
toxicological effects in various biological and ecological systems. In this paper, the applications and implicationsof engineered nanoparticles in aqueous suspensions will be reviewed and discussed relevant to the particle’s
structure on the nanometer size scale and its subsequent biological activity at the cellular level.
Keywords: nanoparticles, nanotoxicology, physicochemical, SARs, safety

1. Introduction
Engineered nanostructures are ubiquitous in the world
around us. Personal interactions with these materials areinevitable, most notably through worker exposure in thechemical industry or consumer exposure through biomedical products. Therefore, assessments of potential risks
associated with contact, including toxicological evaluations, are of paramount importance in the safe development of engineered nanostructures. One important factor
within the regulatory discussion is the need for accurate
and relevant nanomaterial characterization of the physicochemical properties for toxicological evaluations. The
toxicity of nanomaterials can be ranked according
induced toxicities and inflammation at different concentrations over different time points. Chemical compositionand surface coating of the nanomaterial can be related to
toxicological responses. Data suggest that users of certain
nanomaterials may rely on ex vivo measures of concentration, composition, agglomeration, leached metal ions,and reactive species production, as well as other features
such as crystallite phase, surface chemistry, and particle
surface charge as indicators for safety assessment.

†
1

10

Accepted: May 31, 2013
3040 Cornwallis Road, Durham, NC 27709, USA
E-mail: csayes@rti.org
TEL: +1-919-541-6414 FAX: +1-919-541-6936

2. Structure-activity relationships and theirrelevance to particle science
The model engineered-nanoparticle has three distinct
structural features that strongly contribute to its potential
biological activity. These common features of a nanoparticle include highly crystalline, monodisperse, and large
surface area materials. These features are exploited togain a unique material-type for a particular application;
however, this exploitation comes at a cost in that highly
crystalline particles often produce reactive oxygen species
when suspended in aqueous solutions, small monodisperse
particles distribute within an in vivo model rapidly and distally, and particles with large surface area interact withnative biomolecules which in turn disrupt normal biological processes.
Traditionally, structure-activity relationships (SARs)
relate the chemical structure of a compound to qualitative
biological activity. Toxicologists worldwide face a daunting task in screening hundreds of chemicals suspended indifferent media for innumerable toxicological endpoints.
While in vivo (animal) and in vitro (cell culture) testing
are still considered the backbones of obtaining a comprehensive toxicological and risk assessment framework,
these traditional methods are both time consuming andexpensive. A systematic and organized approach such as
computer-based modeling methods that relates experimental data to measurable biological responses is theneed of the hour. These resulting “models” will hence bea quick and effective tool in predicting and characterizing©2014 Hosokawa Powder Technology Foundation

Christie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

a chemical’s toxicity mechanism and consequently integrating physicochemical and biological properties into astrong risk assessment framework for regulatory considerations. Thus, SARs is a multidisciplinary concept and is
a powerful link that ties three major fields, namely chemistry, biology and statistics together.
The application of SARs to the field of nanotoxicology
in particular seems promising. A host of engineered-­nanomaterials is already being incorporated in several consumer products, resulting in large-scale production of thesenew, innovative classes of materials. Given the complex
life cycle of these nano-enabled products, it is essential topredict toxicological effects in a fast and inexpensive manner in order to reduce the risk and improve the benefits ofthis new technology. Mathematical models can, therefore,
be employed to rank, relate, and predict toxicities based on
physicochemical nanomaterial properties. This approachhas the potential to reduce the need for, or extent of animal
testing. Furthermore, these models generate a common
conceptual framework for all stakeholders affected by toxicological regulations. Consequently, scientifically rational
and informed decisions can be made which leads to a better
environmental health protection.

3. Structure, activity, and toxicity of engineered
nanoparticles
When designing a nanotoxicology study, a three-stepprocess must be utilized to determine the interaction ofan engineered-nanoparticle with tissue or cell. First, thestructure of nanoparticle must be determined. Second, thechemical reactivity of the nanoparticle must be understood. Third, the particles’ route of exposure, reaction
with the biological target, and resultant cellular dysfunction must be reported. These experiments should be conducted over a range of increasing concentrations as wellover a well-defined time period. Table 1 summarizes
some of the most common techniques to measure thisthree-step process.

3.1  Structure
3.1.1 Surface area

Brunauer, Emmett, and Teller (BET)—the original
authors of the 1938 article describing this technique-­physisorption is a method of measuring surface area andporosity of a material by physically adsorbing moleculesof nitrogen gas (N2) onto the surface of a solid. BET is oneof the most widely used methods of determining surface
area. It is accomplished by designating particular points at
which relative pressure measurements are to be taken—pressure of a tube containing sample measured against
saturation pressure tube. BET Surface Area measurements

are used in the pharmaceutical, ceramics, carbon black,fuel, and electronics industry, as well as being a key physical characterization method for nanoparticles. The BET
Surface Area of various building materials were measured by passing Nitrogen gas over a “degassed” solid atthe boiling temperature of liquid nitrogen. The building
materials were kept as close to their native state as possible however “coupons” had to be made in order to fit themthrough a 1/4 inch diameter opening on the sample tube.
The instrument should be installed on a stable tabletop
and gas tanks should be secured. Also do not kink the gaslines or damage the integrity of the lines lead to themachine. The operator is responsible for proper cleaningof the sample tubes for each use. The operator shouldreport mass values to a level as precise as possible. The
operator is responsible for identifying a degas procedure.
The operator should ensure that no test sample is sucked
up into the degas or analysis ports when removing sample
tubes after degassing and analysis. Unused gas ports
should be covered or plugged when not in use. Liquid
Nitrogen can cause cryoburns, wear proper PPE whenfilling up liquid nitrogen Dewar for use in analysis. Allow
sample tubes to warm to room temp after completion of
the analysis run. Degas temperature can get quit high(upwards of 350°C), allow sample tubes to cool down
before touching and removal of the heating jackets.
There are thermodynamic consequences of high surface
areas. Difference in free energy between bulk material andnanoparticle contribute to the difficulty in predicting
unknown effects of a nanoparticle based on known effectsof larger micrometer sized materials. Specific to nanocrystals, reduced melting points, large surface areas, andincreased lattice contraction give nanoparticles the heightened ability to produce reactive oxygen and nitrogen species on the particle’s surface. While crystals on the larger
size scale are also known to produce reactive species, somenanocrystals have different crystallographic structures
when compared to their bulk phase counterparts.

3.1.2 Dynamic light scattering

Dynamic light scattering (DLS) is also referred to as
Photon Correlation Spectroscopy (PCS). The technique isused for measuring particle size and size distribution
when in liquid suspension. DLS measures the Brownian
motion of the particles. Brownian motion is the random
movement of suspended particles due to bombardment
between the particle and the solvent molecules. As thesolvent molecules collide with the particles, they exert aforce, which is capable of moving the particles in a random
direction. This random movement is more exaggerated in asmall particle than for a large particle of the same composition in the same time period. This movement is known
as the translational diffusion and is captured in the Einstein-Stokes equation as D along with the hydrodynamic

11Christie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

Table 1

Commonly Studied Physicochemical Properties of Engineered Nanomaterials

Nanomaterial
Property

Description

Common Instrument or Measurement TechniqueParticle
structure•	Size and size distribution• Surface area
• Topology•	Aggregation/agglomerationstate• Shape•	Crystal structure andallotropy•	Brunauer, Emmett, and Teller (BET) physisorption for surface area analyses• Nanoparticle Tracking Analysis (NTA) for size and size distribution•	Dynamic light scattering (DLS) for agglomeration and aggregation analyses•	Transmission and scanning electron microscopy (TEM & SEM) for primaryparticle size determination•	High resolution transmission and scanning electron microscopy (HR-TEM &HR-SEM) for nano clusters• Atomic force microscopy (AFM) for topology•	X-ray diffraction (XRD) and electron diffraction (ED) for crystallinity
information

Chemical
activity• Stability• Sample purity•	Surface characterization•	Chemical composition(includes both compositionof the particle’s core and its
surface)• Therapeutic• Imaging• Functionality• Photo luminescence• Surface charge• Solubility• UV-Visible spectroscopy (UV-Vis)• Ion selective electrodes (ISE) to measure leaked ions•	X-ray photoemission spectroscopy (XPS) to measure electronic state of theelements that exist within a material•	Inductively coupled plasma mass spectroscopy (ICP-MS) for trace metal analysis•	Fourier-transform infrared spectroscopy (FTIR) to analyze chemical bonding• Differential thermal analysis (DTA)•	Energy Dispersive X-Ray spectroscopy (EDS) for elemental analysis andchemical characterization•	Zeta potential and isoelectric point for surface charge and stability
measurements•	Electron spin resonance (ESR) for studying materials with unpaired electrons•	Spectrofluorometer for photoluminiscence and quantum yield measurements forfluorescent particles

Cytotoxicity• Decrease in viability•	Alterations in metabolism•	Oxidative stress due toreactive species• Trigger apoptosis•	Membrane damage (nuclear,cytoplasmic, other)• Glutathione and oxidation detection• Colorimetric indicators for decrease in metabolism (XTT, MTT)
• Live and dead cell counts via fluorescent dyes
• Leaky membrane LDH release•	Protein, cytokine, and chemokine expressions (ELISAs, western blotting)• Damage and repair to DNA (TUNEL)

radius of the particle.
d(H) = kT/3pnD

(1)where D is the translational diffusion coefficient, k is
Boltzmann’s constant, T is temperature, and n is the viscosity of the solvent. The Stokes equation is only applicablefor spherical or spheroidal particle-types.
Measuring the size of particles when suspended inaqueous solvent is an important characterization metricfor nanotoxicology studies. It provides the researcher witha rapid means of generating a size profile (or hydrodynamic radius) of nanoparticles. DLS is also used to measure proteins in a biological buffer. The technique does
have some limitations. For example, in a polydisperse
sample, the larger particles will scatter more light, thus
skewing the intensity of the size profile. The intensity of
scattered light is proportional to the diameter of the particle to the 6th power. This phenomenon is called Rayleigh
Scattering. It is difficult to determine the size of individual particles using light scattering when aggregates or
agglomerates are present i n the suspension — a12polydisperse sample mixture may read as if it were voidof the smaller fraction of nanoparticles. It is important touse control samples without the nanoparticle to determine
the sizing profile of components in the suspension
medium.

3.1.3 Transmission electron microscopy and energy
dispersive spectroscopy

The use of transmission electron microscopy (TEM) isa necessary characterization tool in nanotoxicology. TEM
takes advantage of the extremely small wavelength ofelectrons (0.2 nm) to increase the resolution and magnification of nanometer sized particles as well as cellularorganelles. In transmission electron microscopy, the sample, generally referred to as the specimen, is exposed toan electron beam. The transmitted electrons are viewed
on a phosphorescent screen, camera, or film. Dependingon the specimen characteristics, the TEM can provide
information such as size, shape, aggregation, and crystalline structure. This technique may be used post-exposurefor both in vitro and in vivo tissue samples to determineChristie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

Table 2Comparison of Microscopy Methods used in Nanotoxicology
Molecular
structure

Sizing limits

Aggregation State(in liquids)

Composition
determination

Generation of
artifacts

Special features

OpticalNo> 250 nm

No

SEM

No

> 30 nmNo

Staining

Low

Real time imaging

EDX

High

Topography ofcomplex shapes

TEM, driedYes> 0.5 nm

No

EELS

High

Cross-sectional
details

TEM, cryoNo

1.5 nmYes

None

MediumPreserves the native
state of the sample

the intracellular localization of particles and cell structurechanges (Reynolds, 1963). Table 2 summarises the comparisons of microscopy methods used in nanotoxicology.
TEM provides information about a nanomaterial in its
native state or in a complex mixture. However, there aresome limitations to this technique. Biological specimens
are immediately damaged upon exposure due to the highenergy of the electron beam. Proper biological specimen
preparation determines the quality of the specimen.
Preparation is a multiple step process consisting of fixation,
dehydration, embedding, and sectioning. Post-staining thespecimen with a combination of uranyl acetate and leadcitrate will enhance contrast and allow better visualizationof cell structure. The combination of TEM with composition determination is an even more powerful technique.
Complementary methodologies such as energy dispersive
spectroscopy (EDS), electron diffraction (ED), and highresolution transmission electron microscopy (HRTEM) areuseful. Energy dispersive spectroscopy as a micro-analytical
tool can yield both quantitative and qualitative results.
When emitted electrons strike the atoms of interest in thesample, inelastic reactions generate emitted electrons and
X-rays that are then detected via spectroscopy. The technique is very sensitive and, therefore, special attention
must be placed on sterility during specimen preparation
as to not add artifacts to the sample.

3.1.4 Crystallinity

X-ray diffraction (XRD) is one of the most commonlyused methods for confirming crystalline product. Limitations of the technique include large sample amount needed(100 mg powder sample). While small grain sizes can be
determined, the technique requires long collection times.
The chemical composition influences the crystalline structure, as does synthesis (and sometimes storage) method.
Two equations are used in this technique: Bragg’s law
and Scherrer equation. Bragg’s law is used to determine
the angles for coherent and incoherent scattering from acrystal lattice.
nl = 2d sin q

(2)

where n is an integer, l is the wavelength of incident
wave, d is the spacing between the planes in the atomic
lattice, and q is the angle between the incident ray and thescattering planes.
Scherrer equation is used to determine the size andshape of the nanocrystalline material, also known as
crystallite.
D(Å) = 0.89l/β cos q B(3)

where D is the crystallite size, l is the X-ray wavelength(1.54 Å for Cu Ka radiation), q B is the Bragg angle, and b= (B2-b2)1/2 where B and b are taken as the FWHM (fullwidth at half max peak) of standard and sample.
Electron diffraction (ED) is the phenomenon that
results in an interference pattern when a beam of electrons bombard a sample. It is a commonly used techniqueto study the crystal structure of solids, especially in material characterization techniques such as transmission andscanning electron microscopy. Based on the diffraction
patterns, the crystallinity of the sample under investigation can be determined. Once this pattern has been
attained, it is compared with that of a standard material.
This technique may come into play when a particle has
multiple crystalline states (Sayes et al., 2006a). HRTEM
is also used to study the crystallographic structure at theatomic scale.
Recent studies have related the crystal structure of amaterial to its photocatalytic and cytotoxicological ac­
tivities (Sayes et al., 2006b). Different crystalline phasesof nanoscale titania (TiO2) particles contribute to theirdifferential cytotoxic responses in cultured cells. The
most inactive catalytic material (TiO2 in the rutile crystal
phase) is less cytotoxic than similarly sized TiO2 particles
in the anatase crystal phase. Anatase TiO2 also exhibitshigh photoactivity. This correlation is a manifesta­tion of afundamental structure-activity relationship in nanoscaletitania—nanoparticle structures optimized to produce reactive species under UV illumination also are more effective at disrupting cellular functioning. Simple ex vivo
tests of nanoscale titania photoactivity could prove usefulas a comparative screen for cytotoxicity in this important class of materials.

13Christie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

3.2 Activity
3.2.1 Zeta potential

The zeta potential of a particle is used as a measure of
the particle’s surface charge. In actuality, the zeta potential is a measure of the electric double layer and is generated from oriented solute molecules and ions surrounding
the nanoparticle surface. The electric double layer isdependent on it environment and will change intensity if
pH or ionic strength is altered. For example, all nanoparticles have an isoelectric point. The particle’s isoelectric
point is the pH of the suspension when the particle’s zeta
potential is zero net charge (Berg et al., 2009).
Zeta potential is also used as a measurement of colloidal stability (Harush-Frenkel et al., 2007; Zhang, 2009).
Values above ±30 mV are considered a stable system
while values below ±30 mV are deemed unstable suspensions and aggregate readily. The benchmark time scale forthis assessment is generally 30 days. This aggregation isdue to the lack of charge-charge repulsion between individual nanoparticles.

3.2.2 Photocatalytic degradation

The surface of a nanoparticle has been identified as asource of leached ions, molecules, and reactive species.
There are a variety of techniques and an array of colorimetric probes that are used to measure the reactivity ofthe surface of a nanoparticle that yields these species into
the surrounding particle matrix. Vitamin C and Congo
Red are probes used to measure the photocatalytic degradation of the particle’s surface. When identifying andquantifying the reactivity of a particle’s surface, it isimportant to recognize that no single technique can beused for all types of nanoparticles. Results in the literature indicate that the mechanism for color change in thesetests is a result of charge transfer complexes between theprobe and the “active sites” on the particle surface (Warheit et al., 2007a).

3.2.3 Spectroscopy

One of the most common analytical techniques in nanoscience is spectroscopy. Spectroscopy is defined as themeasurement and interpretation of changes in the electromagnetic spectra arising from either absorption or emissionof radiant energy by a sample. Spectroscopic techniques
are especially useful for particle analyses. Information
about the chemical composition, structure, surface functionality, and optical/electronic properties of the sample
can be obtained. For example, mass spectroscopy is used todetermine the masses of small electrically charged particles
and can be utilized to measure properties proteins absorbed
onto the particle surface. Raman spectroscopy is used to
study vibrational, rotational, and other low-frequency
modes in a system and can determine the type and degree

14

of functionalization on the particle surface. Absorption
spectroscopy is used to quantify the amount of photons asubstance absorbs and can be utilized to measure the sizeof nanoparticles. Fluorescence spectroscopy is used to analyze the different frequencies of light emitted by a substance which is then used to determine the structure of thevibrational levels of that substance.

3.3 Toxicity
3.3.1 Concentration

Of all the physicochemical properties associated withnanomaterials, the feature that is most easily correlated to
toxicity is concentration or dose. However, to measure theconcentration of a sample is non-trivial. Three techniques
are usually employed to determine concentration of ananoparticle in a suspension. Gravimetric tests can beused, but must assume particle composition. Methods
based on chemical reactant reactions can be utilized, but
can produce erroneous results. Transmission electron
microscopy of cryogenically frozen samples in suspension
is the best measure of particle concentration. There are avariety of factors that influence the accuracy of measurements of concentration, such as the purity of sample andquantity of material available for analyses. Special considerations must be taken when a nanoparticle is surfacefunctionalized with an organic coating. For example, surfactant coatings are not stable, and much like a protein
absorbed onto the particle’s surface, the surfactant will
dissociate and be replaced with other molecules present in
the suspension.

3.3.2 Exposure to nanomaterial samples

Real-world exposure to engineered nanomaterials is very
likely to be a mixture of multiple substances, such as airborne particulate matter. Epidemiological data had suggested that airborne particulate matter (a mixture of manydifferent substances) was more toxic than the sum of its
parts. This was attributed to the “synergistic” effect due tothe mixture of critical components within airborne particulate matter. In the nanotoxicology environment, human
exposure to mixed nanomaterials is likely because multiple
types of nanomaterials are often used simultaneously. For
example, both metal oxide nanoparticles (e.g., Fe2O3) andgraphitic carbon nanoparticles (e.g., carbon black) arelikely to be used in various industrial applications. Therefore, it is imperative to understand the toxicological effectof exposure to mixed nanomaterials as well as the effectsof the individual components alone. Recent publications
have highlighted the importance of studying multiple
nanoparticle exposure scenarios (Berg et al., 2010).

3.3.3 Hemolytic potential

The hemolytic potential of a nanoparticle sample givesChristie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

vital information on the effects of the particle on a biological membrane. The assay has been used in the past century
with a variety of particulates including silicate powders,
asbestos, and more recently a multitude of nanoparticles.
Hemolysis (i.e. rupturing of erythrocytes or red blood cells)
is an ex vivo characterization method that is complementary to assessing cell death. The ability of nanoparticles toreact with a biological membrane is an important indicator
especially for particles incorporated into medicinal devices
for therapy or diagnosis (Warheit et al., 2007a) (Harington
et al., 1971; Nolan et al., 1981; Warheit et al., 2007b).
Particulates, such as nanomaterials, interact with theerythrocyte and exert their cytotoxic effect via a multitude of hypothesized mechanisms depending on the characteristics of the particle such as size, composition, surface functionalization, and zeta potential. The mechanicalinteraction between the particle and the membrane cancause rupture releasing the intracellular hemoglobin into
the ambient solution thus turning the solution pink to redin color. In addition to mechanical interactions, nanoparticles may react with the membrane of the erythrocyte
indirectly via actively oxidizing the membrane molecular
structure thereby increasing the membrane permeability.
The particles may alter the ionic composition of the suspension medium through particle surface degradation,
which could then increase the amount of hemoglobin insurrounding medium, as well.

3.3.4 Oxidative stress indicators

The presence of excessive reactive oxygen species(ROS) can cause cellular oxidative stress, which may leadto sub-cellular damage such as DNA, RNA, protein,
mitochondrial, and membrane or other lipid degradation(Sayes et al., 2004; Fortner et al., 2005; Lyon et al., 2005;
Sayes et al., 2005; Sayes et al., 2006). Exposure tonanoparticles has been shown to produce excess ROS.
Consequently, oxidative stress damage has become a critical assessment tool in characterization the physical,
chemical, and toxicological properties of engineered
nanostructures.
In nanotoxicology, DNA oxidative stress is used as anindicator for potential cytotoxicity (Cattley and Glover,
1993; Hwang and Kim, 2007). Research has shown thatdifferent types of DNA damage and repair after oxidative
damage can provide insights into mechanisms of action(Cooke et al., 2003). DNA damage is a result of a break orchange in the chemical sequence of DNA in the nucleus ofa cell. Each type of DNA lesion has different affects on thecells. For example, some DNA lesions result in mutations
and can affect DNA replication and transcription; othertypes of DNA damage are repairable (Cooke et al., 2003).
There are numerous biomarkers that measure oxidative
stress endpoints in cells, urine, blood, and other tissues.
The assays capable of determining DNA oxidative stress,

damage, or repair after damage usually measure levels of
8-hydroxyguanosine (8-OHG) and 8-hydroxydeoxyguanosine (8-OHdG) nucleosides (Cattley and Glover, 1993;
Hwang and Kim, 2007). The Comet assay measures general DNA damage via gel electrophoresis of cell lysate,
followed by fluorescence signal quantification.
Protein oxidation is the process of oxidative damage topolypeptides and amino acids present in cells. Examples of
assays that measure oxidative protein damage are protein
carbonyl content (PCC) and 3-nitrotyrosine. Techniques
used to evaluate the oxidant-antioxidant biomarkers are
enzyme-linked immunosorbent assays (ELISA), ion
exchange chromatography, immunoblotting, and electron
paramagnetic resonance imaging. Several mechanisms are
known that describe how electophiles and pro-oxidants
cause protein damage. Alterations in protein function canoccur following formation of covalent bonds between electrophiles and nucleophilic amino acids, oxidation of nucleophilic amino acids, or production of reactive nucleophiles.
Oxidative stress can also be caused by the accumulationof nanoparticles within the mitochondria (Nicholls andBudd, 2000) (Oberdorster et al., 2005; Li et al., 2008)(Sayes et al., 2004). It has been demonstrated that nanoparticles of various size and chemical composition are preferentially transferred to and accumulate in the mitochondria(Li et al., 2008) . ROS from the nanoparticle surface at thesite of the mitochondria or ROS produced by the mitochondria because of nanoparticle exposure leads to cell damage
or death. In structurally intact mitochondria, the productionof ROS is balanced by an extensive antioxidant defense
system that works to detoxify the oxygen radical generation(Nicholls and Budd, 2000). This protection is generally
provided via glutathione and superoxide dismutase. Heightened cellular production of ROS occurs after damage to themitochondria; thus, oxidative stress is often detected bymeasuring mitochondrial function.
Lipid peroxidation and membrane damage are used asindicators of oxidative stress and cellular damage. The
major concern in this type of oxidative damage is disruption the ion channel flow. Lipid peroxides are unstable anddegrade to molecules such as reactive carbonyl compounds. Polyunsaturated fatty acid peroxides generatemalondialdehyde (MDA) and 4-hydroxyalkenals (HAE).
MDA and HAE are colorimetric/flourometric indicators
for this type of oxidation. Cytoplasmic and other cellularcomponent membranes are easily targeted due to theamount of lipids found within the membrane.
Fluorescent dyes are very good indicators to detect oxidative stress in cells and tissues (Wang and Joseph, 1999;
Lin et al., 2006). These ROS-sepcific dyes are categorizedaccording to which type of ROS being probed. In general,
there are multiple fluorescence probes for the detection ofsuperoxide radical (O2•-), hydrogen peroxide (H2O2), singlet oxygen (1O2), hydroxyl radical (HO •), or peroxy15Christie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

Table 3

Examples of fluorescent ROS dyes
Fluorescent probe

Excitation/emission wavelengths (nm)ROS species detected

DCFDA(2,7-dichlorodihydrofluorescein)

498/522

H2O2
ROO•
HO•

DHE
(Dihydroethidium)520/610

O2•-

B-TOH
(BOPIDY-a-tocopherol)

514/565

ROO•
RO•
HO•

HPF
(Hydroxyphenyl fluorescein)

485/535

HO•

CM-H2DCFDA(chloro methyl dihydro derivative of fluorescein)

485/538

H2O2
ROO•
HO•

radical (ROO•), as well as others (see Table 3). As withany colorimetric or fluorescent indictors, however, special
attention must be placed on whether or not the nanoparticle
auto fluoresces at the same wavelength or interferes withdye to avoid false positives or false negatives in results.
There is a wide range of applications for these dyes within
the realm of detecting ROS. For example, some probes aremainly used in an indirect approach to probe for antioxidant capacity, while others probe for oxidation in particular
sub-cellular compartments and membranes (Gomes andFernandes, 2005).
In addition to fluorescence spectroscopy, confocal
microscopy can be used as a tool to probe stress (Uggeri,2004). Oxidative stress can induce a dose-related increaseor decrease in the level of fluorescence depending on the
fluorescent probe of choice. In confocal microscopy, fluorescent probes are used to stain cell structures. The fluorescent probes dihydrorhodamine 123, dihydroethidium,
2’,7’ dihydro-dichlorofluorescein (H2DCF), and dichlorodihydrofluorescein diacetate (H2DCFDA) are some of themost commonly used detectors of reactive oxygen species(ROS) in spectroscopy and microscopy (Uggeri, 2004).

3.3.5 In vitro toxicology

The successful development of in vitro assays as predictive screens for assessing particle toxicity is an important goal during early product development. Ideally, thescreen would be utilized prior to more substantive in vivo
toxicity testing. If properly validated, the advantages ofthese early screening tests would be evident. In vitro testing is simpler, faster, and less expensive than in vivo
assays. Successful development of in vitro toxicity models
should reduce the use of animals for hazard identificationof potential toxicants as well as to improve the ability toevaluate new materials in small quantities. Althoughimplementation of in vitro toxicity screens would be beneficial, the accuracy and predictability of these tests with

16

particulates have shown high correlative evidence whencompared to results obtained in vivo models.
An interne national panel of scientists recommended five
grand challenges associated with the safe handling of nanotechnology. The panel has recommended strategic researchstrategies to support sustainable nanotechnologies by maximizing benefits and minimizing environmental and healthrisks (Maynard et al., 2006). One of the five key grandchallenges cited was to develop and validate alternatives toin vivo toxicity testing of engineered nanomaterials, recognizing that there would be several limitations inherent to in
vitro assays and cell culture systems when simulating complex biological effects after exposure to nanoparticles.
These limitations include particle dose, selection of celltype for simulating the organ system of choice, characterization of exposure, effects over time, and appropriatenessof endpoints for hazard evaluation (Sayes et al., 2007).
In recent study, a number of variables which strongly
impact the ability of in vitro screens to accurately reflectin vivo pulmonary toxicity of several particle types in rats
were systematically evaluated (Sayes et al., 2007). The
variables tested included particle dose, time course, duration of treatment exposure, and pulmonary cell types. In
vivo effects in the lungs of rats were utilized as thebarometer for comparison. Under the conditions of thisstudy, the results of in vivo and in vitro cytotoxicity andinflammatory cell measurements demonstrated little correlation when single cell cultures were used, but resulted
in a higher level of correlation when co-cultures of epithelial cells and macrophages were used together. There isa need for better culture systems and for more research todesignate the most relevant biological endpoints to test forin vitro studies (Romoser et al., 2011; Romoser et al.,2012; Berg et al., 2013).

3.3.6 Cellular uptake

Interaction of engineered nanoparticles occurs on a size

Christie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

scale previously seen with the entrance of viral pathogens
across the cytoplasmic membrane (Oberdorster et al., 2004;
Larese et al., 2009). The uptake of nanoparticles provides aunique way of accessing intracellular compartments
through intentional (i.e. drug delivery) or unintentional (i.e.
occupational or consumer exposure). In either scenario,
nanoparticles are capable of intracellular localization
through a variety of endocytic mechanisms ranging fromthe clathrin-mediated endocytosis (CME) to non-specificmacropinocytosis or simple passive diffusion (Qaddoumi
et al., 2003; Geiser et al., 2005; Rothen-Rutishauser et al.,2006; Harush-Frenkel et al., 2007; Harush-Frenkel et al.,2008; Jiang et al., 2008). Many physicochemical characteristics such as nanoparticle size, surface coating, andsurface charge have been postulated as factors influencing
the endocytosis of nanoparticles. Many endocytic mechanisms are structurally size limited by the protein scaffolding lining of the vesicle on the cytoplasmic membrane.
Calculations based on thermodynamic limitations andcell-ligand interactions have calculated the most efficient
receptor-mediated nanoparticle endocytosis occurs when
the particle is a spherical is shape and 30 nm in diameter(Freund and Lin 2004; Gao et al., 2005). When the particles aggregate, however, the resultant agglomerate istreated as larger particle. In these circumstances, phagocytosis by immune-modulator macrophages is responsible
for clearance of agglomerates.
While primary particle size and agglomeration state play
the primary role in directing the specific route in nanoparticle endocytosis, they are not the only factors. Surface
charge also plays a role in the interactions between
nanoparticles and cell membranes (Harush-Frenkel et al.,2008; Zhang, 2009). For example, negatively charged particle surfaces, such as particles coated with hydrophilic
acids, and positively charged particle surfaces, such as particles coated with polymers, are more capable of incorporation into human cells than particles with little to no surface
charge. The charge of a nanoparticle will also dictate thepathway through which the particle is internalized(Harush-Frenkel et al., 2008; Mayor and Pagano, 2007;
Doherty and McMahon, 2009; Gould and Lippincott-Schwartz, 2009; Zhang, 2009). For example, while
uptake of both positively and negatively charged particles
are energy and F-actin polymerization dependent, they
have been shown to undergo different pathways. Positively
charged nanoparticles enter cells through macropinocytosis
and CME (Qaddoumi et al., 2003; Chung et al., 2007).
Negatively charged nanoparticles enter cells throughdynamin-independent mechanisms (Qaddoumi et al., 2003;
Schroeder et al., 2007; Partha et al., 2008; Villanueva et al.,2009). While associations between charge and mechanismsof cellular internalization have been made, further research
into this topic is needed.
In addition to nanoparticle charge, a modified surface

coating influences the uptake by cells. Another factor dictating nanoparticle cellular uptake and potential toxicity
is the adsorption of proteins onto the surface of the particle (Chen et al., 2005; Chen et al., 2006; Huang et al.,2007; Lundqvist et al., 2008; Schellenberger et al., 2008).
Proteins have been shown to coat particles when placed incell culture media, serum, and biological fluids. The
extent of the protein coating is dependent upon physicalfactors such as size and shape and chemical factors suchas charge and other surface functionalization. Antibody
conjugation onto the surface of a particle increases linearlywith respect to the radius. This association between sizeand protein binding is due to the high rate of curvature
exhibited by the surface of a small nanoparticle which sterically hinders the binding of additional antibodies. Protein
adsorption may be dramatically altered as any single
physicochemical property is changed—thus prohibiting
many mathematical models to be used in this field. It is
this protein adsorption theory, which necessitates theimportance of proper characterization of nanomaterials,
as well as puts forth complicating task of linking nanomaterial physicochemical properties with their biological
endpoint.

4. The phases of nanomaterial characterization
within a study design
The most thorough nanotoxicology studies include athoughtful experimental design for the material characterization. The nanoparticle sample should be characterized and re-characterized for physical and chemical
properties throughout the course of the designed study.
When changing the matrix surrounding the material or
simply measuring changes over time, a nanoparticle
sample should be analyzed and labeled, as material
characterization is the primary phase, the secondary
phase, or the tertiary phase (Fig. 1).
Primary phase physical and chemical characteristics
refer to those nanoscale properties immediately after thematerial is synthesized using liquid-phase synthesis or
aerosolized synthesis. Furthermore, the characterization
should be performed on both lab-synthesized and purchased material. Those properties relevant to toxicity testing include a diverse range of particle features, including:chemical composition, surface functionalization, surface
area, size, size distribution, shape, crystallinity, and purity.
Secondary phase characterization relevant to toxicity testing includes aggregation/agglomeration/coagulation, concentration, activity/reactivity, presence of reactive species,
surface modifications, and leached ions or molecules.
Properties in the tertiary phase that are relevant to toxicity testing include cellular uptake and tissue distribution,
adsorption of molecules onto the surface, aggregation,17

Christie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

Fig. 1The Physicochemical Characterization Required for Toxicological Evaluations.

degradation and decomposition, and dissociated ions ormolecules.
There are specific characteristics regarding nanoparticle production that are most relevant to toxicologists.
These issues include quantity of material produced andavailability for exposure, particle composition and amountof impurities, and presence and identity of a surface
coating. When performing toxicological evaluations on
nanoparticles, these properties should be addressed.
One of the most frequently asked questions in nanotoxicology is: to what extent do particles aggregate (Sager etal., 2007; Murdock et al., 2008)? Particles are always
attracted to each other. Forces such as van der Waals interactions, type of solvent, and Hamaker constant are all contributors for particles to aggregate. It is noteworthy, however, that aggregated particles, may not have significantly
different surface areas compared to individual particles.
Nanoaggregates are often referred to as “soft” aggregates.
Chemical changes are needed for aggregates of nanoparticles to become permanently fixed to each other. Factors
such as direct covalent attachment at grain boundaries
require chemical reaction between particles. When nanoaggregates become fixed, they are often are referred to as“hard” aggregates. It is this type of aggregation (or18agglomeration) that leads to much lower surface areas.
Nanoparticles can be stabilized against aggregation. For
example, ionic strength alters repulsion between particles
by several orders of magnitude). In ionic stabilization,strong repulsive electrostatic forces are present and are
dependent on the type of solvent used in the system. The
strength of these electrostatic forces is affected by surface
charge density. If the density of the surface charge is large
in magnitude and equivalent in sign, then the repelling
forces on a particle-to-particle basis can operate in relatively long ranges. Another example of prohibiting aggregation is steric stabilization. In this case, the coatings on
surfaces of the nanoparticles define the extent of stabilization. Understating the interactions of the coatings withthe solvent essential and ultimately can reduce van der
Waals interactions.
These principles apply to nanoparticles. When characterizing a nanoparticle for any type of assessment, it isimportant to consider an engineered nanomaterial as aparticle obeying quantum mechanics (Fig. 2). When theparticle is aggregated into larger agglomerate, then the particle may be obeying classical mechanics. Nonetheless,particles on the nanometer size scale are different fromparticles on the micrometer size scale (Nel et al., 2006).

Christie M. Sayes / KONA Powder and Particle Journal No. 31 (2014) 10–21

Fig. 2The Properties Exploited in Specific Particle Size Ranges.

5. Conclusion on utility of structure-activity
relationships for nanoparticles
The role of engineered nanomaterials in a variety offields in science and engineering requires an adequate
methodology for evaluating their potential impact on safety
and health. Recent publications point to an increase of various biological responses, such as inflammatory or immune
responses, after exposure to nanomaterials. These biological responses have been observed and reported on fromeither in vitro (cell culture based) or in vivo (whole animal)model systems; however, not enough effort has been placedon relating the physicochemical features of each engineered
nanomaterial to the observed biological responses. Developing experimental models and methodologies that not
only establish relationships between different physicalstructures and biological activity but also can reliably predict biological responses to nanomaterials is critical. Thiseffort, however, requires a large and organized effort
within the nanoscience community. Many data sets measuring multiple endpoints are required in order to accurately predict biological responses. The same is true for thephysicochemical characterization.
The structure of a nanoparticle can be used as one ofmany predictors of biological responses. However, it must
be noted that structure is not the only physicochemical feature that contributes to a material’s potential toxicity. For
example, not all nanoparticles are more toxic than theirlarger micrometer sized counterparts. Size, alone, is not ameasure of toxicity. Surface coatings of particles have beenshown to more likely influence toxicity—no matter the sizeor structure of the material. And particle aggregation andsubsequent de-aggregation complicates the structure-activity relationship even more since this process is dynamic
depending on time, suspension matrix, and temperature.
Using both analytical chemistry and biochemistry
approaches, a systematic methodology is under developmentthat will assist researchers and regulators in evaluating
potential responses of a specific biological system to a specific nanomaterial exposure. While the methodology development is well underway, there is still an urgent need for
new tools, standardized practices, and meaningful interpretations that help address the challenges presented bynanomaterials and nano-enabled products. Due to theircomplexity, nanomaterials do not fit into established structure-activity models of chemical behavior. Nonetheless, it
is important to identify the trends among different
nanoparticles with varying measurable physicochemical
characteristics for hazard identification, exposure analyses,
risk assessments, and regulatory and policy decisions. The
result, ideally, would be a framework that would produce
meaningful groupings of particles in an effort to generalize
some of the common features and resultant common
responses that so many particles on the nanometer size
scale seem to induce. For instance, particles less than 10
nm in diameter not only have different optical properties,
they also have different translocation tendencies in cellular
systems. Metal-based nanoparticles, a.k.a. metal colloids,
tend to leach metal ions at different rates and at different
pH’s. Crystalline materials produce more oxidant species
than amorphous materials. While there are always exceptions to generalizations, these types of observations can bemade when considering the literature as a whole.

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Criscitiello M.F., Sayes C.M., Quantum dots trigger immunomodulation of the nfκb pathway in human skin cells,
Molecular Immunology, 48 (2011) 1349–1359.
Romoser A.A., Figueroa D.E., Sooresh A., Scribner K., Chen
P.L., Porter W., Criscitiello M.F., Sayes C.M., Distinct
immunomodulatory effects of a panel of nanomaterials inhuman dermal fibroblasts, Toxicology Letters, 210 (2012)
293–301.
Rothen-Rutishauser B.M., Schurch S., Haenni B., Kapp N.,
Gehr P., Interaction of fine particles and nanoparticles with
red blood cells visualized with advanced microscopic techniques, Environ Sci Technol, 40 (2006) 4353–4359.
Sager T.M., Porter D.W., Robinson V.A., Lindsley W.G., Schwegler-Berry D.E., Castranova V., Improved method todisperse nanoparticles for in vitro and in vivo investigationof toxicity, Nanotoxicology, 1 (2007) 118–129.
Sayes C.M., Fortner J.D., Guo W., Lyon D., Boyd A.M., Ausman
K.D., Tao Y.J., Sitharaman B., Wilson L.J., Hughes J.B.,
West J.L., Colvin V.L., The differential cytotoxicity ofwater-soluble fullerenes, Nano Letters, 4 (2004) 1881–1887.
Sayes C.M., Gobin A.M., Ausman K.D., Mendez J., West J.L.,
Colvin V.L., Nano-c60 cytotoxicity is due to lipid peroxidation, Biomaterials, 26 (2005) 7587–7595.
Sayes C.M., Wahi R., Kurian P.A., Liu Y., West J.L., Ausman
K.D., Warheit D.B., Colvin V.L., Correlating nanoscaletitania structure with toxicity: A cytotoxicity and inflammatory response study with human dermal fibroblasts andhuman lung epithelial cells, Toxicological Sciences, 92(2006a) 174–185.
Sayes C.M., Liang F., Hudson J.L., Mendez J., Guo W., Beach
J.M., Moore V.C., Doyle C.D., West J.L., Billups W.E.,
Ausman K.D., Colvin V.L., Functionalization density

dependence of single-walled carbon nanotubes cytotoxicity
in vitro, Toxicology Letters, 161 (2006b) 135–142.
Sayes C.M., Reed K.L., Warheit D.B., Assessing toxicity of fineand nanoparticles: Comparing in vitro measurements to invivo pulmonary toxicity profiles, Toxicological Sciences,
97 (2007) 163–180.
Schellenberger E., Schnorr J., Reutelingsperger C., Ungethüm
L., Meyer W., Taupitz M., Hamm B., Linking proteins withanionic nanoparticles via protamine: Ultrasmall protein-coupled probes for magnetic resonance imaging of
apoptosis, Small, 4 (2008) 225–230.
Schroeder J.E., Shweky I., Shmeeda H., Banin U., Gabizon A.,
Folate-mediated tumor cell uptake of quantum dots
entrapped in lipid nanoparticles, Journal of Controlled
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Rotoli B., Orlandini G., Calcein-am is a detector of intracellular oxidative activity, Histochemistry and Cell Biology, 122 (2004) 499–505.
Villanueva A., Cañete M., Roca A.G., Calero M., Veintemillas-Verdaguer S., Serna C.J. , Morales M. del Puerto,
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Pulmonary bioassay studies with nanoscale and fine-quartz
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95 (2007a) 270–280.
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Author’s short biography
Christie M. Sayes
Dr. Christie M. Sayes is the Program Manager for Nanotoxicology RTI International.
She was formerly a professor of toxicology at Texas A&M University. She has more thana decade of experience in the fields of nanotechnology and nanotoxicology. She has
authored publications, including original research, invited reviews and book chapters.
She is a member of the Society of Toxicology, the American Chemical Society, and theSociety of Environmental Toxicology and Chemistry. She serves on the Editorial Boardsof Nanotoxicology, Toxicological Sciences, and Toxicology Letters. Recently, she waselected onto the Executive Committee of the North Carolina Chapter Society of Toxicology.

21

KONA Powder and Particle Journal No. 31 (2014) 22–52/Doi:10.14356/kona.2014006

Review Paper

Nanophosphor Coatings: Technology and Applications,
Opportunities and Challenges †Roman Kubrin
1

Institute of Advanced Ceramics, Hamburg University of Technology, Germany

Abstract
The particle size of conventional commercial phosphor powders used in lighting and displays is in the range fromseveral micrometers to tens of micrometers and it is known that submicrometer-sized phosphors can facilitate adecrease in their consumption and improved resolution of phosphor screens. When the particle size becomescomparable to wavelengths of light, the optical properties of phosphor powders undergo remarkable qualitativechanges so that the luminescence performance of nanophosphor screens, along with a very pronounced influenceof the particle size, becomes dependent on several additional parameters such as packing density of nanoparticles,
refractive index and chemical composition of the medium between them. This brings about both advantages anddisadvantages which are discussed in this review of recent literature on the synthesis, deposition, and applicationsof nanophosphors.
Keywords: nanophosphors, lanthanide-doped nanoparticles, particle size effects, phosphor screens, transparent
luminescent coatings, phosphor-converted white LEDs

1. Introduction
The general function of any phosphor is to convert acertain kind of external energy into visible light. This
conversion process can serve different purposes and, fromthis point of view, all practical applications of phosphors
can be classified into several main groups:• Light sources (fluorescent lamps, backlights of liquid
crystal displays (LCDs), light-emitting diodes (LEDs)
including phosphor-converted white LEDs (pc-WLEDs),etc.).
• Information displays (plasma display panels (PDPs),
field emission displays (FEDs), cathode-ray tubes (CRTs),etc.).
• Radiation converters (X-ray intensifying screens andother image intensifiers, spectral converters for solar
cells, down-converters for excimer laser beam profilers
and photolithography mask inspection tools, viewing
screens for electron microscopy, etc.).
• Fluorescent pigments and tracers (non-destructive
testing, biolabeling, security labeling, leisure goods, etc.).
Luminescent substances are very often utilized in theform of a powder coating, i.e. a continuous particulate
film of relatively small thickness extended in the other†1

22

Accepted: June 24, 2013
Denickestr. 15, 21073 Hamburg, Germany
E-mail: roman.kubrin@tuhh.de
TEL:+49-40-42878-3459 FAX: +49-40-42878-2647

two dimensions. Such a coating deposited on a transparent
substrate is usually referred to as a screen, if it is used for
representation of any visual information. Each application
imposes an appropriate set of requirements on the properties of the phosphor coating, e.g. its chemical composition,
homogeneous or patterned structure, and its thickness.
Usually, a trade-off between the maximum light output
for the given excitation conditions, desired transient characteristics, quality of image reproduction, mechanical andenvironmental stability, and costs of the phosphors andtheir processing has to be found.
The size of phosphor particles is one of the main
parameters affecting the performance of phosphor
screens. Phosphors produced by conventional methods
usually consist of particles with the sizes ranging fromseveral micrometers to several tens of micrometers, i.e.
significantly larger than the wavelengths of light theyemit. The reduction of phosphor particle size into thesubwavelength regime could be advantageous in many
applications provided that the luminescent properties of
the chosen material are still appropriate and the technological route is economical.
The purpose of this review is to point out the general
qualitative differences between conventional phosphorsand nanophosphors and to show potential advantages ofthe latter. Nanophosphors can be defined as nanoparticlesof transparent dielectrics (hosts) doped with optically activeions (activators), so that the emission of light happens dueto the electronic transitions between the levels of the©2014 Hosokawa Powder Technology Foundation

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

impurity ions inside the bandgap of the host (characteristic luminescence). They have to be distinguished from theluminescent quantum dots as these emit light upon bandto-band transitions (bandgap luminescence) and are
affected much more strongly by quantum confinement
effects. Semiconductor quantum dots are not dealt withdirectly in this article although certain conclusions could
also be applied to them. Interested readers can be directedto the reviews of physics and applications of quantum
dots, such as Samokhvalov et al. (2013), Geszke-Moritz
and Moritz (2013), Bera et al. (2010), Gaponik et al.
(2010), and Liu et al. (2010). We will also not devote muchattention to phosphor powders with particles of intermediate size between 100 nm and 1–2 mm. Their properties
and synthesis were recently treated in (Kubrin, 2012)
including an extended discussion of modeling methods
and spray-based deposition techniques partially repeated
here. Previous reviews of the physics and technology ofluminescent nanoparticles can be found, e.g. in Ronda(2008), Tissue (2007), Liu and Chen (2007a), Tanner(2005), Chander (2005), and Tissue (1998).

2. Basic optics of phosphor screens
For the given excitation conditions (constant intensityof the incident X-Rays, UV-light, or an electron beam),
the perceived brightness of a phosphor screen is determined by the geometrical configuration of the screen, theexcitation source, and the observer. Generally, one distinguishes two different modes of screen observation. In thetransmission (T-) mode, the screen is placed between the
excitation source and the observer (Fig. 1, Observer A).
In the reflection (R-) mode, the observer and the source of
excitation are situated on the same side of the screen (Fig.
1, Observer B). The intensity of light exiting the screen inboth modes depends on the screen thickness.

2.1 Perfect non-scattering screens
Let us consider the simplest model of the phosphor
screen—an infinite continuous plate with even, perfectly
smooth boundaries. If we assume a uniform excitation by
unpolarized light (from one side of the screen), thetime-averaged spatial distribution of intensity of luminescence from any volume element inside of the phosphor
plate should by fully isotropic. We also assume a perfectmatch between refractive indices of the phosphor andsurrounding medium, so that the light reflection at theboundaries of the phosphor layer can be neglected. Insuch cases, the intensities of light emitted forward(T-mode) and backward (R-mode) should be equal andconstant everywhere outside of the screen
IT = I R ,(1)

where IT and IR stand for the transmission-mode andreflection-mode intensities, respectively, expressed as anumber of photons emitted in a unit of time. Their sum
equals the total intensity of luminescence and it can be
related to the intensity of exciting radiation absorbed in
the phosphor coating I'A by the quantum efficiency q ofthe phosphor (number ratio of emitted and absorbed
photons). From now on, symbols with a prime will be
used for exciting radiation

I=
I=
q
T
R

I ′A
2 .

(2)

Exciting radiation incident on the phosphor screen iseither absorbed or transmitted through the screen. The
sum of corresponding contributions equals the initialintensity of excitation′0 I ′A + I T′ .
I=

(3)

The part of exciting radiation transmitted through thephosphor is given by the Beer-Lambert law=
I T′ I ′0 exp(−′d ) ,(4)where a' is the coefficient of absorption measured in theunits of inverse length and d is the thickness of the screen.
We obtain the following final expression

I=
I=
q
T
R

Fig. 1 Transmission and reflection modes of screen observation(Kubrin, 2012), © Cuvillier Verlag.

I ′0 (1 − exp(−′d ))
.
2

(5)

Obviously, both R- and T-mode brightness increase forthicker phosphor screens and asymptotically approach thevalues corresponding to complete absorption of exciting
radiation (Fig. 2). When considering the brightness of aperfect non-scattering screen, there is no definite optimalvalue of the screen thickness; the phosphor layer theoretically should be as thick as possible.
In most practical cases, the refractive index of theluminescent material is substantially higher than that of23

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

I=
IR < qT

Fig. 2 Theoretical thickness dependence curves for non-scatteringand single scattering models of phosphor screens.

the surrounding medium and the resulting light intensities
should be corrected for the Fresnel reflection at the interface between the media. Eq. 4, which describes transmissionof the exciting radiation (for the normal incidence on thescreen), should now become (Nakazawa et al., 2007)
I T′ =≈(1 − R0 ) 2 (1 +  2 n 2 ) exp(−′d )1 − R02 exp(−2′d )(1 − R0 ) 2 exp(− ′d ),1 − R02 exp(−2 ′d )(6)

where n and k are the real and imaginary part of therefractive index, respectively; and R0 is the normal surface reflectivity
R0 =(n − 1) 2 +  2.
(n + 1) 2 +  2(7)Equation 3 should now include a part of radiation I'R
reflected from the surface of the phosphor plate
I ′0 = I ′A + I T′ + I ′R ,(8)

which equals
I ′R =
R0 (1 + I T′ exp(−′d )) .

(9)

The emitted light undergoes reflection from the layerboundaries and a significant fraction of all light quantacannot escape the phosphor plate due to the total internalreflection because their angle of incidence exceeds thecritical angle
 C = arcsin(n A n P ) ,(10)

where nA and nP are the refractive indices of the ambient
medium and phosphor material, respectively. Such photons experience multiple reflections inside of the phosphor
plate, while propagating towards the lateral edges of thestructure (this phenomenon is often referred to as waveguiding), until they are finally absorbed and transformed
into heat. Eq. 2 does not hold anymore and we obtain

24

I ′A
.
2

(11)

The trapping of light inside of the luminescent layer (orin an adjacent transparent substrate) can have a dramaticeffect on device performance. For example, the light
extraction efficiency of semiconductor light-emitting
diodes (LEDs) (i.e. the ratio between the intensity of lightemitted into the ambience and the total intensity of light
generated by the device) would come to only 2–4% if nospecial design measures were taken (Fujii et al., 2004;
Windisch et al., 2001). Such inefficient light outcoupling
results from high refractive indices of semiconductors(e.g. n[GaN] = 2.5). However, even for organic LEDs
(OLEDs) which employ materials with moderate values ofrefractive index (n~1.5), only about 20–30% of lightwould escape into air (Wei et al., 2006). Refractive indices of dielectrics used as phosphor hosts fall into therange between 1.5 and 2.5 and, therefore, the brightnessof any single-crystalline phosphor screen should also bestrongly affected by the internal reflection. Enhancementof the light extraction can be achieved by optimization of
the device structure, e.g., “flip-chip” LEDs (Krames etal., 2007) or truncated cone patterns in single-crystalline
phosphor screens (Jianbo et al., 2000), and/or intentionalroughening of the emitting surfaces, which is applied inorder to disrupt waveguiding by means of light scattering.
LEDs with extraction efficiencies of 80% have been
demonstrated (Krames et al., 2007). Elimination of theeffect of the total internal reflection led to a remarkable
improvement in performance, so that power efficiencies
of semiconductor LEDs and OLEDs could exceed that ofconventional fluorescent lamps (60–70 lm/W) (Krames etal., 2007; Reineke et al., 2009). This can be considered agreat success because the light extraction efficiency of thefluorescent tubes is close to unity. It has to be mentionedthat the improvement of device architecture and phosphor
materials already allowed the production of LEDs withluminous efficacies approaching the predicted maximum
values of 260–300 lm/W (Tan et al., 2012).

2.2 Single scattering model
The fluorescent lamps and many other devices in which
phosphors are used in a powder form are practically notaffected by waveguiding due to the absence of sufficiently
smooth layer boundaries. Intensive scattering at the surfaceof phosphor particles, pores, and other inhomogeneities
has a drastic influence on propagation of both the exciting
radiation and emitted light. The equations describing therelation between the thickness of a screen and its brightness have to be changed accordingly.
Mathematically, the simplest case of the scattering
phosphor screen is when the entire intensity of scattered

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

light is immediately lost without any further effect on
resulting screen brightness. The Beer-Lambert law for theexciting light (Eq. 4) should now include the scattering
coefficient b':=
I T′ I ′0 exp(−(′ + ′)d ) .

(12)

The scattering coefficient is not a material-specific constant; it is determined by processing-dependent propertiesof the phosphor powder. The absorption coefficient a' in
Eq. 12 also depends on the condition of the phosphor
powder and, therefore, it should be distinguished from a'for the bulk phosphor material in Eq. 4.
The assumption of equality of the T- and R-mode intensities of the emitted light (Eq. 1) does not hold anymore,
especially for thick screens (i.e. when the intensity of
excitation substantially changes with the screen depth)
due to the effects of scattering. The T-mode intensitychanges with the increasing thickness of the phosphor
layer as follows=
dI T aq′I T′ dx −  I T dx ,(13)

where a is a fraction of light emitted in the forward direction, q is the quantum efficiency of the phosphor, b is thescattering coefficient for the light at the wavelength ofemission. When combined with Eq. 12, this results in adifferential equation
IT=+  I T aq′I ′0 exp(−(′ + ′)d ) .

(14)

The solution of Eq. 14 isIT =aq′I ′0[exp(−  d ) − exp(−(′ + ′)d )] .
′ + ′ − (15)This is a pulse function of the general formy =A[1 − exp(−

xx)]exp(− ) ,
t1
t2

(16)

which can be easily reformulated to match with Eq. 15 bysettingA=11aq′I ′0t1 =
t2 = .
′
′
′
′



+
−

,
,
 + −

(17)

For the R-mode,=dI R dI Rx exp(− x) ,(18)

where IR is the intensity of light coming out from the phosphor plate in the backward direction and IRx is the intensityof light emitted in the backward direction at the depth x in
the screen. Eq. 18 results in a differential equation=IR aq′I ′0 exp(−(′ + ′ +  ) x) ,(19)

which is solved with=IR

aq′I ′0
[1 − exp(−(′ + ′ +  )d )].
′ + ′ + (20)

The R-mode curve is a single exponential decay curve.
Fig. 2 shows the curves of the R- and T-mode brightness, which were obtained by the fitting of publishedexperimental data (Fran and Tseng, 1999; Ozawa, 2007).
This is a rather special case of the thickness dependence
curves, which could only be obtained in the extremelyrare conditions when the scattered photons did not reachthe detector.
Even though the single scattering scenario is an oversimplification in most of the practical cases, it allows us
to draw a conclusion which is generally valid. For any
powder phosphor screen with non-negligible scattering
which is observed in the T-mode (the usual way of operation of displays, fluorescent lamps, and phosphor-converted
white LEDs), there always exists an optimal screen thickness corresponding to the maximum emission brightness
at given conditions of excitation. When the exciting radiation is almost completely absorbed inside the phosphor
plaque, each additional infinitesimal phosphor layer inexcess of the optimal thickness introduces a net decrease of
the perceived intensity because losses due to scattering
exceed the intensity of light generated in this layer.

2.3 Multiple scattering of light in the powder
screens
Even though the shape of the T- and R-mode curves inFig. 2 could be predicted by simple mathematical derivations, the obtained equations (Eqs. 15 and 20) do notdescribe the general case of light generation in a powder
phosphor screen because usually, photons are not lost
immediately upon the first scattering event and can still
contribute to the light output of the screen after being
scattered several times. Even for a relatively low concentration of scatterers (e.g. atmospheric aerosols), thiscauses significant deviations from the Beer-Lambert law(Tam and Zardecki, 1982; Wind and Szymanski, 2002). In
the case of densely packed particles, the propagation oflight does not practically obey the Beer-Lambert law(Dick, 1998).
Fig. 3 shows an example of the typical dependence of
the intensity of photoluminescence on the thickness of thestrongly scattering screen. As opposed to the single scattering model, the R-mode intensity neither obeys the exponential law nor reaches saturation when the exciting
radiation is fully absorbed in the screen. Both the T- andR-mode curves have an approximately linear character inthe range of large screen thickness, while the sum of thecorresponding intensities stays approximately constant.
The comprehensive mathematical description of the process of light generation in the layers of packed phosphor
particles is rather complicated. The most frequently
implemented theoretical approaches to this problem arebased on Kubelka-Munk’s theory and the Monte Carlo25

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

Fig. 3Thickness dependence curves of strongly scattering
Y2O3:Eu phosphor coatings (average phosphor particle
size 440 nm, Kubrin, 2012), © Cuvillier Verlag.

method (Yen et al., 2007). In some cases, simple practicaltechniques for optimization of the screen weight could be
developed. For example, for strongly absorbed exciting
radiation, the maximum of the T-mode intensity corresponds to the minimum thickness of the powder screen
fully covering the substrate (i.e. there should be no directtransmission of exciting radiation via the voids between
the particles, Donofrio and Rehkopf, 1979).
In any case, it is expected that the T-mode thickness
dependence curve has a maximum for a certain optimal
screen thickness. Screen brightness in the R-mode
asymptotically approaches a constant value, as for the
non-scattering and single scattering models. However, forthe multiple scattering of light emitted by a semi-infinite
phosphor layer, the ratio between the light intensity
detected in the R-mode and the total intensity of light generated in the screen could reach unity, if self-absorption of
luminescence is negligible:
I R → qI ′(0) ,(21)

whereas for non-scattering screens the limit is half as
small (see Eq. 2, internal reflection is disregarded):IR →1qI ′(0) ,2(22)

and it is even smaller in the single scattering model (seeEq. 20)IR →1
′qI ′(0) .
′ + ′ +  2(23)

The brightness of the non-scattering screen in the T-mode
is equal to that in the R-mode and tends to the same maximum value (Eq. 22). When taking into account any losses,
e.g. due to the unintended waveguiding, one obtains

1
I T < qI ′0 .
226This inequality also holds for both single and multiple
scattering models because the T-mode intensity would
never exceed the R-mode intensity for any given screen
thickness of isotropically emitting phosphor, and theirsum cannot exceed the total intensity of emitted light.
Practical calculations for the phosphor coatings offinite thickness require more rigorous treatment. The
Kubelka-Munk two-flux approach, which is discussed
below based on the derivation in Narita (2007), is commonly applied for various kinds of pigment coatings or
any other optical coatings with non-negligible multiple
scattering. Its theoretical framework can be used inmany fields of application of phosphor screens. Alongwith modeling of the performance of fluorescent tubes(Grossman, 1998; Narita, 2007), it was successfully
adopted for LEDs (Ishida et al., 2008), X-ray and vacuum
UV (VUV)-excitation (Baciero et al., 1999; Jeon et al.,
2000; Kandarakis et al., 1996), and cathodoluminescence(Narita, 2007). Discussion of other modeling approachesof phosphor powder coatings can be found in Yen et al.
(2007) and (Kubrin, 2012).
In the approximation of the infinite screen uniformly
excited from one side, scattered light produces a diffuse
light flux opposite to the initial direction of propagationof the exciting radiation or emitted light. In the standard
Kubelka-Munk theory, the optical properties of a particle
layer (e.g. a pigment coating, Buxbaum, 2005), which isassumed to be a continuous optical medium, are completely determined by two optical constants: the absorption coefficient K and the scattering coefficient S. These
coefficients correspond to the previously introduced coefficients a and b generalized to three dimensions, i.e. whenincident light is diffuse and scattering takes place in all
directions (Narita, 2007).
In order to perform calculations, a value of either theabsorption coefficient K or the scattering coefficient S
must be known. The other constant can be determinedfrom the value of the Kubelka-Munk function F(R∞) by
the equation=
F ( R∞ )

K
,
S

(25)

where R∞ is reflectance of a semi-infinite powder layer
obtained from experiments

R∞ =1−  0.
1+  0(26)

Usually, the scattering coefficient is obtained by measuring the reflectance R0 of a relatively thin layer coated on a
black plate (which has negligible reflectance)

S=
(24)

(1 − R∞ ) 2
=
2R∞

R∞
R (1 − R0 R∞ )ln ∞,d (1 − R∞2 )R∞ − R0

where d is the thickness of the layer (Narita, 2007).

(27)

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

In a one-dimensional case, the light incident on thelayer of non-luminescent particles is scattered in the forward and backward directions with intensities which wewill denote by I'(x) and J'(x) instead of I'T and I'R, respectively. For the forward direction, the light absorbed in an
infinitesimal layer of thickness dx is a'I'(x)dx, and thescattered light is b'I'(x)dx. A part of J'(x) is scattered backand has to be added to I'(x). One obtains

dI ′( x)=−(′ + ′)I ′( x) + ′J ′( x) .
dx

(28)

For the backward direction, a similar equation can be
writtendJ ′( x)=(′ + ′) J ′( x) − ′I ′( x) .
dx

(29)

The general solutions to this set of differential equations,known as Schuster-Kubelka-Munk equations, areI ′( x) = A′(1 − ′0 ) exp(′0 x) + B′(1 + ′0 ) exp(−′0 x) ,(30)

J ′( x) = A′(1 + ′0 ) exp(′0 x) + B′(1 − ′0 ) exp(−′0 x) ,(31)

where constants A and B are determined by boundary
conditions, and a'0 and b'0 are defined as=′0′(′ + 2 ′) ,

(32)

=
′0

′ /(′ + 2 ′) .

(33)

Kubelka showed that the same equations can be derived
for diffuse light and scattering in all directions. As light
does not always have normal incidence on the phosphor
layer, the mean light path dx is longer than dx. It was
shown thatd = 2dx .

(34)

If one defines the new coefficients K' and S' by
K ′ = 2′, S ′ = 2 ′ ,(35)

Eqs. 32 and 33 can be replaced withdJ ( x) = dJ A + dJ SJ − dJ SI − dJ E .

K ′( K ′ + 2S ′) ,

(36)

=
′0

K ′ /( K ′ + 2S ′) ,(37)

and then, general solutions of Schuster-Kubelka-Munkequations can be expressed by Eqs. 30 and 31 again.
In the case of photoluminescence, one has to accountfor both exciting and emitted light. There are the following
contributions to the light emitted in the forward direction(T-mode)
(38)

(39)

The intensity of the light emitted by the infinitesimal
phosphor layer of thickness dx is
dI E ( x) + dJ E ( x)= qK ′[I ′( x) + J ′( x)]dx ,(40)

where q is the efficiency of luminescence, K' is theabsorption coefficient of the exciting radiation, and I'(x)and J'(x) are the intensities of the exciting light in the forward and backward directions, respectively. By combining Eqs. 30 and 31, one obtains
dI E ( x) +=dJ E ( x) 2qK ′[ A′ exp(′0 x) + B′ exp(−′0 x)]dx .

For infinitesimal phosphor layers,dI ( x) E = dJ E ( x) , dI SI = dJ SI , dI SJ = dJ SJ .

(41)
(42)

As a result, one obtains a set of differential equationsdI ( x)=−(K + S )I ( x) + SJ ( x)dx
+qK ′[ A′ exp(′0 x) + B′ exp(−′0 x)] ,(43)

dJ ( x)=+(K S ) J ( x) − SI ( x)dx
−qK ′[ A′ exp(′0 x) + B′ exp(−′0 x)] .

(44)

The general solutions of these equations are=
I ( x)

qK ′A′ ′0 0 − 0
⋅ 2
exp(′0 x)
0′0 − 0 2−

qK ′B′ ′0 0 + 0
⋅ 2
exp(−′0 x)
0′0 − 0 2

+ A exp( 0 x) + B exp(− 0 x) ,=′0dI ( x) =−dI A − dI SI + dI SJ + dI E ,where dIA denotes changes due to absorption of emitted
light; dI SI and dI SJ stand for scattering from the forward
and backward modes, respectively; dIE accounts for theprocess of light generation from the absorbed exciting
radiation. For the backward direction, it holds(45)

qK ′A′ ′0 0 + 0−
⋅ 2
J ( x) =exp(′0 x)
0′0 − 0 2+

qK ′B′ ′0 0 − 0
⋅ 2exp(−′0 x)
0′0 − 0 2+

A
exp(0 x) + BR∞ exp(−0 x) .
R∞

(46)

The values of A and B are determined by the boundary
conditions. This allows for, e.g. taking into account the27Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

presence of the substrate or reflecting coatings, which aresometimes deposited over one side of the screen in order
to increase the light output from the other side.
If absorption is not strong, the scattering coefficient S ispractically independent of the absorption coefficient K.
Furthermore, for conventional phosphor particles which arelarger than the wavelengths of emitted light, the scattering
coefficient is approximately constant over a wide wavelength range (Kortüm et al., 1963; ter Vrugt, 1965). However, in the ranges of strong absorption (e.g. for the
UV-light), the described method of measuring the scattering constant cannot be used. The Kubelka-Munk theory
does not predict the interdependence of K and S andrequires special care when applied to the UV-range (Narita,2007).
Another shortcoming of the Kubelka-Munk theory isthat it completely disregards the size and shape of phosphor
particles, as well as their mutual arrangement inside of thescreen. It is known from experiments that S is reciprocally
proportional to the particle size between 1 and 10 mm(Kortüm et al., 1963; Narita, 2007). In many practically relevant circumstances, the absorption coefficient K linearly
depends on the volume concentration of particles f V (volume fraction filled by particles, Buxbaum, 2005). However,
the onset of multiple scattering results in a strong deviationfrom the linear dependence between the concentration f V
and the scattering coefficient S. It was shown that S/f V islinearly dependent on f V 2/3 (Buxbaum, 2005). Several
authors attempted to derive the relations between the coefficients K and S and the properties of single particles (Liuet al., 2005; Mudgett and Richards, 1971).
The assumption of symmetric and semi-isotropic (twoflux) scattering made in the Kubelka-Munk theory is notalways valid. In some cases, a many-flux (>  2) radiativetransfer calculation procedure can produce noticeably
more accurate results (Mudgett and Richards, 1971).
Some further alternative approaches, such as Johnson’s
theory or the p-layer model, make reference to the phosphor particle size where the phosphor screen is treated asa stack of particle monolayers (Fonger, 1982a; Fran andTseng, 1999; ter Vrugt, 1965; Yen et al., 2007). Once theref lection and transmission of such monolayers aredefined, one can calculate the optical properties of thephosphor coating of any thickness. In this case, recursion
formulas are used instead of differential equations. However, it should be noted that there are no strict reasons forthe unit particle layer to be related to the phosphor particle size, when used for the purposes of modeling the optical properties of phosphor screens. The thickness of such
an elementary layer may actually be chosen arbitrarily
small. For example, a single phosphor layer can beassumed infinitesimally thin, and then the recursive formulas reduce to differential equations equivalent to the
Schuster-Kubelka-Munk equations (Fonger, 1982b). In

28

other words, Johnson’s theory and other “discontinuous”
models based on the notion of the particle layer are very
similar to the “continuous” theory of Kubelka and Munk,and also do not explicitly account for the size and shapeof phosphor particles.
The simplest bottom-up approach to modeling the collective properties of packed phosphor particles is basedon stochastic computational algorithms explicitly using
random numbers—generally termed as the Monte-Carlo
method. It can be applied to any problem, which allows
for probabilistic formulation. It was used for spherical andpolyhedral particles, monosized ones and those possessing a size distribution, ordered and randomly distributedon the substrate (Konrad et al., 1999a; Soules and Klatt,1988; Urabe, 1980). There are numerous reports on theMonte-Carlo modeling of properties of CRTs (Busselt andRaue, 1988), X-ray imaging systems (Badano, 2003;
Liaparinos et al., 2006), and LEDs (Borbely and Johnson,
2005; Chang et al., 2005). Along with the possibility to
explicitly account for the size, shape, and arrangement ofphosphor particles on the substrate, it allows further
parameters (e.g. roughness of particle surface, Konrad etal., 1999a) to be added and can be combined with theoretical methods (e.g. Mie scattering theory, Soules andKlatt, 1988; Liaparinos et al., 2006). The very important
advantage of the Monte-Carlo method over the two-flux
methods is that it can be used for calculations of theangular distribution of light intensity, for assessing thequality of image reproduction by the information displays
and radiation converters, and can handle powder screenswith a complicated structure (Urabe, 2007).

2.4 Resolution of the phosphor screens
Along with high efficiency of the conversion of external energy into visible light, phosphor screens used for
acquiring or displaying any visual information have tosatisfy several additional requirements. The imaging performance of a phosphor screen is determined by theamount of the information it can convey and is usuallyassessed by the limit of resolution, i.e. by the size of thefinest structural details of an image that a display or animage converter is able to reproduce.
The smallest element of an image is a single point. In
an ideal imaging system, excitation by a radiation beamof infinitesimal diameter would result in a perfect infinitesimal image point. In reality, the smallest point always
has a certain finite size. Therefore, the resolution of thescreen can be characterized by defining a corresponding
point spread function (PSF), i.e. measuring the size of the
spot produced by the point-like excitation source. The
PSF is a unique characteristic of the imaging performanceof a phosphor screen. The intensity distribution in theentire image, which should be considered as an aggregateRoman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

Fig. 4

Example of a point spread function (a) and the corresponding modulation transfer function (b) (Kubrin,2012), © Cuvillier Verlag.

of image points, can be obtained by convolution of theintensity distribution of exciting radiation with the PSF of
the phosphor screen. When two image points are spaced
by less than the width of the PSF, they cannot be fully
resolved. Such blurring of an image leads to losses ofvisual information.
For isotropic imaging systems, the two-dimensional
point spread function is rotationally symmetric (Rossmann,1969) and can be described by a curve for one spatial
dimension (Fig. 4a). Often a simple Gaussian intensity
profile is assumed and the full width of the PSF at half the
maximum intensity (FWHM) is commonly used as therepresentative value. The shape of the PSF of different
screens, however, may vary significantly, so that it isadvisable to measure it down to at least several percent of
the peak intensity (Gruner et al., 2002), and the full widthcorresponding to 1–5% of the maximum is sometimes
specified as well (e.g., Pokric and Allinson, 2002).
Direct measurement of the PSF is quite cumbersome
because it requires a point source of excitation. In many
applications, it is difficult to reduce the area of the screen
exposed to the exciting radiation to a vanishingly small
size and to have sufficient intensity at the same time. It
can be more convenient to measure the line spread function (LSF)—another transfer characteristic of phosphor
screens. Similarly to the PSF, which describes the transfer
of intensity distribution from the point source of excitation to its image, the LSF defines the intensity profile ofthe image of a line source. The LSF is related to the PSF
by the expression (Gruner et al., 2002)
LSF ( x) = ∫+∞−∞PSF ( x, y) dy .

(47)

The LSF is a one-dimensional function but, for the isotropic imaging systems, the two-dimensional PSF can beobtained from the single LSF by the Abel transform(Koch et al., 1998; Rossmann, 1969). If a PSF has aGaussian shape, the corresponding LSF is a Gaussianfunction as well. Width of the LSF is also usually measured

by its FWHM value and by the full width at some intensity in the range of several percent of the peak response(Busselt and Raue, 1988). Sometimes, the full width comprising most of the area of the integrated LSF (e.g. 90%)
is applied (Koch et al., 1998).
How much overlap of the spread functions is needed for
adjacent points/lines in the image to become irresolvable?
There are several resolution criteria used in various fields
of applied optics. The most well-known is the Rayleighcriterion, which states that two equally bright point objects
can be resolved if the maximum of the PSF of the first point
falls into the first minimum of the PSF of the second one(Sayanna et al., 2003). This definition of the limit of resolution was developed for diffraction-limited optical systems
where the PSF is represented by the Airy pattern of concentric rings with multiple minima. For the PSFs without
local minima (e.g. those of Gaussian shape), the Rayleighcriterion is ambiguous. Furthermore, it cannot be applied
to the resolution of unequally bright point objects. Veryoften the limit of resolution is simply identified with the
FWHM of the PSF. The so-defined Houston criterion canbe used with the spread functions of any shape. However, it
is also impractical for resolving the points/lines of different
brightness. In many cases, the Sparrow criterion is preferred (Sayanna et al., 2003). Sparrow has suggested thatthe natural definition of resolution is the point separation atwhich the saddle point between the two maxima firstdevelops, i.e. when the second derivative of the sum of
the PSFs in the midpoint between the points vanishes. If
the distance between the points is less or equal to the
Sparrow limit, they will be perceived as a single elongated point. The same applies to the LSFs. For example, it
is known that a series of equidistant Gaussian profiles
separated by 2s, where s is a standard deviation of thespatial intensity distribution, should produce a uniform
intensity (2s ≈ 0.85FWHM). This property, referred to asa merging raster, is utilized for the reproduction of images
with pixelated screens, i.e. screens composed of an arrayof pixels (discrete picture elements). If the distance29

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

between the lines increases, a variation of intensity withthe corresponding spatial frequency will be observed assoon as this variation exceeds some perceivable threshold,i.e. the lines will be resolved.
For a general case of an arbitrary LSF, any quantitative
treatment would require extensive calculations and it haslong been recognized that the problem can be simplified
by solving it in the (spatial) frequency domain. Thisapproach is based on the notion of the optical transfer
function (OTF), a representation of the frequency
response of the optical system. The one-dimensional OTF
can be obtained by the Fourier transform of the LSF (or of
the PSF for two dimensions) (Koch et al., 1998; Williams
and Becklund, 1989). It can also be directly measured forsinusoidal excitation patterns. As the emission and excitation of luminescence are incoherent, only the modulusof the OTF, termed modulation transfer function (MTF),
has importance and its phase component (phase transfer
function) can be disregarded. Modulation is defined as aratio of the amplitude of the sinusoid to its average value
and, therefore, cannot be greater than unity (Rossmann,1969). An example of MTF is shown in Fig. 4b. The limitof resolution of a phosphor screen is usually associatedwith the spatial frequency (measured in cycles per unit
length) at which the MTF decreases to 3–5%.
The contrast transfer function (CTF) is another transfer
characteristic conventionally applied to phosphor screens.
The CTF quantifies the frequency response of an imaging
system for a square-wave input instead of the sine wave,
which is more convenient for experiments (e.g. with bar
charts or rectangular slits, Franks et al., 2003). For thesame reason of simpler experimental procedure, the line
spread function is sometimes obtained by differentiating
an edge trace, i.e. intensity distribution on a boundary
between “black” and “white” half-planes in the image ofthe knife edge (Williams and Becklund, 1989). The CTF
equal to one designates perfect transfer of contrast. The
limit of resolution of the imaging system is specified inlines per unit length. Such units are very convenient for
pixelated displays and radiation converters where thesmallest resolvable details of an image are inherently
limited by the size of single pixels. However, when two
neighboring lines of pixels have the same intensity, theycannot be resolved. “Black” lines should be interlaced with“white” lines, i.e. at least two lines of pixels are needed forthe reproduction of each line in the image. In the sampling
theory, this is justified by the Nyquist-Shannon theorem. In
order to avoid confusion in the specification of resolution,
the units of line pairs per unit length (e.g. lp/mm) are
widely accepted. Generally, the cut-off spatial frequency
for pixelated screens is in the best case approximately equal
to half of the density of lines in the raster (or pixels in theline). It is somewhat worse if there is any cross-talk of theneighboring pixels, i.e. if their PSFs significantly overlap.

30

The resolution of homogeneous unpixelated screens isdetermined by several parameters. The following primitive
example reveals the major factors of influence for a screen
consisting of superwavelength-sized particles. Let us consider a single layer of phosphor particles deposited on thetransparent substrate (Fig. 5a). Light emitted inside of thephosphor particle experiences multiple internal reflections
and can escape the volume of the particle in any direction
at an arbitrary point of its surface. Therefore, even for asingle layer of phosphor particles, the smallest light emission spot would be approximately equal to the phosphor
particle size. However, if neighboring particles have equal
intensity, it is impossible to say whether those are two separate points or a single elongated one (Particles 1 and 2 inFig. 5a). Similarly to the pixelated screens, two image
points should be separated by at least one more “pixel” —in this case, another phosphor particle (Particles 2, 3, and 4
in Fig. 5a). The diameter DIP of the smallest resolvable
image point can be approximately expressed as follows:
DIP= 2 + 2c ,(48)

where f is the phosphor particle size and c is theinter-particle clearance. Obviously, both the phosphor
particles themselves and the gaps between them must be
kept as small as possible for improved resolution.

Fig. 5

Schematic illustration of the influence of phosphor
particle size, packing density and screen thickness on
image resolution. The darker appearance corresponds
to a higher intensity of emitted light. See text for
explanation.

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

The influence of phosphor layer thickness on screen resolution is illustrated in Fig. 5b. It is assumed that thecoated side of the screen is exposed to excitation with electrons or strongly absorbed photons which are completely
absorbed in the top layer of phosphor particles, and particles
in the deeper layer(s) merely scatter emitted light without
contributing to the emission of luminescence. Nearly 50
percent of produced light is emitted towards the substrate
and these photons impinge upon the particles in the second
and the third layers and are either reflected or refracted on
their surface. Light diffuses inside of the phosphor coating
in all directions until it escapes on either side of the screen.
If the screen is observed in the T-mode, the light intensity
pattern (the image) produced in the top particle layer undergoes gradual degradation (blur), which makes closely
spaced image points unresolvable, as in the bottom layer ofthe screen in Fig. 5b. The image observed in the R-mode ismuch less prone to the optical blur, although light scattered
back from the deeper particle layers may escape from thescreen at the spots which were not excited (Particle 3 inFig. 5b) and in this way slightly impair the MTF. Experiments show that for powder phosphor screens exposed tothe strongly absorbed exciting radiation, the MTF in the
R-mode is almost independent of the screen thickness. The
reflecting CRTs have 3–4 times better resolution as compared to the conventional transmitting ones (Zege et al.,1991).
Obviously, the resolution of unpixelated screens can be
improved by decreasing the thickness of the phosphor
screen, increasing the packing density of phosphor particles and, finally, by reducing the phosphor particle size.
This conclusion is generally valid for any cathodo- or
photoluminescent powder screens as well as for those
excited by X-rays. However, each parameter affecting thescreen resolution can be varied only within a certain limited range determined by other application-specificrequirements or available technology. For example, X-rays
are weakly absorbed by phosphors, and a considerable
thickness of the screen may be required for sufficient efficiency of conversion into visible light. Usually in suchcases, a trade-off between better resolution and fainteremission intensity has to be found. On the other hand, thepenetration depth of an electron beam into the phosphor
is often much smaller than the size of a single phosphor
particle. However, from the point of view of manufacturing CRTs, it is difficult to deposit such thin phosphor
coatings free of voids and irregularities. The thickness ofphosphor screens in conventional CRTs often has to be
increased in order to assure uniformity and thus theobtained resolution is compromised due to technologicalconstraints.
A general relation for the optimum screen density Wopt of
CRTs, which accounts for the non-close packing of phosphor particles, was obtained by Busselt and Raue (1988)

2

Wopt = 2V 50  fV 3 ,(49)

where V 50 is the volume median diameter (measured by
sedimentation), r is the phosphor density, and f V is thepacking density of the phosphor screen. In the same work,a simple relation between the width of the LSF at 5% peakintensity L05 and the geometric thickness d of the screen
was found for practical CRT phosphors (Busselt andRaue, 1988)
L05 = 4.5d .

(50)This equation may be rewritten for the optimum screen
density Wopt and combined with Eq. 47 to obtain
Wopt

(51)
L05 4.5==
9 VM1 .
 fV
fV 3
Therefore, an increase in the packing density of phosphor
particles in the screens of optimized density leads to a“sharpening” of reproduced images. It can be considered
as a general trend that screens with a high packing density of particles have a better resolution but decreased
brightness (Sasaki and Talbot, 1999). It should be emphasized that Eqs. 47–49 are valid only for the T-mode ofscreen observation.
A combined effect of the size and packing density ofphosphor particles can be expressed by the change of thescattering mean free path of the emitted photons (Busselt
and Raue, 1988). Intensive optical scattering is found to
suppress the tails of the spread functions, i.e. to decrease
the L05 in Eq. 47. As a result, the MTF of the powder
phosphor screens at low spatial frequencies often surpasses that of non-scattering ones (e.g. single-crystalline
or glass plates, Faruqi et al., 1995; Gruner et al., 2002;
Swank, 1973).
Scattering of the exciting radiation usually has a minor
effect on the quality of image reproduction in most of theapplications. For example, in the case of CRTs, changes ofthe MTF introduced by an increase of the energy of electrons from 5 to 40 keV were less than 15% (Zege et al.,1991). For the X-ray excitation, the scattering of X-rays
can be completely neglected.
If the exciting radiation is weakly absorbed, the resolution of the screen is still to a large extent determined byits geometric thickness, so that the values of the MTF
corresponding to the same product of spatial frequency
and phosphor thickness stay unchanged (Swank, 1973).
The necessity of large values of thickness for the complete
absorption of X-rays leads to a relatively low resolution of
powder phosphor screens, which usually is limited to therange of 10–20 lp/mm (Badano, 2003; Sklensky et al.,1975). For a given thickness of the X-ray intensifying
screen, the resolution may be improved by several methods, e.g. by depositing a reflective or absorbing coating31

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52(backing) over the rear side of the screen or by introducing small amounts of impurities which provide weak
self-absorption of luminescence in the phosphor material,
thus removing long tails of the LSF without strongly
impairing the light output (Swank, 1973; Zege et al.,1991). Also for the X-ray excitation, the resolution of thescreens in the R-mode is somewhat better than that for the
T-mode (Zege et al., 1991).
Although the R-mode seems to be preferable forhigh-resolution imaging, it is highly impractical in mostof the applications. In order to achieve superior resolution
in the T-mode without sacrificing the efficiency of detection of X-rays, special structured screens are sometimes
used. Columnar (needle-like) phosphor particles aligned
parallel to the incident X-rays allow elimination of thestrong interdependence between the width of the LSF andthe screen thickness (Badano, 2003). Alternatively, amask with an array of thin holes filled with a phosphor
can be used. Screens with the resolution on the order of
1 mm were realized based on the latter approach (Flannery
et al., 1987). Nonetheless, the screens with a spatial resolution close to the optical diffraction limit could beobtained only by decreasing the thickness of the phosphor
film to 1 mm (Koch et al., 1998; Martin and Koch, 2006).

3. Limits of performance of the luminescentscreens
Let us consider a powder phosphor screen which is
excited by the UV-light (the wavelength and intensity are
fixed). What can be its highest brightness and resolution?
For a semi-infinite phosphor plaque, the R-mode brightness is at most (see Sec. 2.3 and Eq. 21)
I R → qI ′(0) ,(52)

where q is the quantum efficiency of the phosphor andI'(0) is the intensity of the incident exciting radiation. For
the T-mode, the maximum achievable intensity (for the
optimized screen thickness and without reflecting coatings on the rear side of the screen) would beIT ≤1
qI ′(0) .
2(53)

Thus, the maximum brightness of the phosphor screen isultimately limited by the quantum efficiency of the phosphor. The quantum efficiency of phosphors used in fluorescent lamps, PDPs, and LEDs is about 100% (Ronda,
2008). In this aspect, the performance of the state-of-theart inorganic phosphors is quite close to the physicallimits. One has to distinguish, however, between the quantum efficiency and energy efficiency of a phosphor. If
luminescence is excited with photons which have energy
exceeding that of the emitted photons by more than a32

factor of 2, the quantum efficiency may reach 200% in
certain luminescent materials, i.e. two photons could beemitted per each incident exciting photon. This process isreferred to as quantum cutting. Quantum-cutting phosphors have attracted a lot of attention in the past decade,particularly in the fields of photovoltaics and mercury-freefluorescent lamps (Huang et al., 2013; Meltzer, 2007;
Ronda, 2008; Zhang and Huang, 2010).
Resolution of the screen is another major figure of
performance. For the screens designed for observation
with the naked human eye, the resolution of 20 lp/mm is
usually sufficient. However, there are several imaging
applications such as the excimer laser beam profiling,inspection of photolithographic masks, tunneling electron
microscopy, and X-ray microtomography where the phosphor screens with a resolution beyond 1000 lp/mm would
provide a definite advantage.
The resolution of the unpixelated phosphor screens ismainly determined by their geometric thickness (see Sec.
2.4). In principle, any desired resolution could be obtainedwith an appropriately thin phosphor coating, provided
that it absorbs a sufficient amount of exciting radiation fora detectable light output. However, the ultimate limit ofresolution is set by the diffraction of light and not by thescreen thickness. If no special super-­resolution techniques
are utilized, the resolution of an optical system cannot bebetter than

k≈

2n
,


(54)

where k is the Abbe limit of detection (measured in spatial
frequency), n is the refractive index of the surrounding
medium, and l is the wavelength of emitted light (Evanko,2009). The highest spatial frequency that can be opticallyresolved (for l=400 nm) is therefore, about 5000 cycles/
mm. For longer wavelengths and a finite aperture of thedetector, the limit of detection can significantly decrease.
If we assume, for simplicity, that the FWHM of the LSF
exactly equals the thickness of the phosphor coating(Koch et al., 1998), the corresponding thickness thresholdof the diffraction-limited phosphor screen would be on
the order of 200 nm. For the pixelated phosphors, this isalso the value of the smallest pixel pitch that could everbe needed for the optical imaging.
On one hand, several works on phosphor screens withsubmicrometer resolution very close to theoretical limits
were already reported (Koch et al., 1998; Martin andKoch, 2006; Martin et al., 2012), so that the room for
improvement of the spatial resolution per se is also rather
limited. On the other hand, high-resolution phosphor radiation converters in the form of non-scattering single crystal
films or transparent ceramics are much more difficult to
produce (Kuntz et al., 2007; Martin et al., 2012; Park et al.,2012b; Touš et al., 2007) as compared to the conventional

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

processing methods of phosphor powder coatings. It would
be beneficial to find a means to manufacture phosphor
screens with submicrometer optical resolution by simpler,
more economical methods.
As follows from the discussion above, phosphor powder
screens may approach diffraction-limited imaging if their
thickness could be reduced below 200 nm. Obviously, themanufacturing of such screens would require the application of nanophosphors with a much smaller particle size.
The reduction of phosphor particle size in the superwavelength regime is relatively straightforward because it
does not affect the luminescent properties of particular
phosphor materials. Submicrometer-sized phosphor particles are used, e.g. in plasma display panels, because they
can be processed in smaller pixels than for conventional
phosphors produced by solid-state firing and retain thesame brightness for significantly lower screen weights(Kubrin et al., 2007; Kubrin, 2012), thus allowing for a
reduced consumption of sometimes extremely costly
phosphors. However, when their particle size enters thenano-range, many physical properties of solids undergo
dramatic changes. These size effects are summarized in
the next sections.

4. Physical implications of reducing the phosphor
particle size
4.1 Independent scattering and absorption of lightby nanoparticles
As discussed in Sec. 2.4, the scattering of light inside
the phosphor layer degrades the resolution of powder
screens. We also learned in Sec. 2.2 and 2.3 that scattering
affects the thickness dependence curves of light emitted
from the screen in the R- and T-modes. It is therefore
desirable to derive a mathematical relation between theparticle size and the scattering coefficient b (as used inSec. 2.2 and 2.3) and to compare the behavior of conventional phosphor powders and nanophosphors.
It is convenient to introduce a quantity that specifies
the ability of a single phosphor particle to scatter light.
The amount of light removed from the incident light by asingle phosphor particle is proportional to its geometricprojected area AP
C SCA = QSCA AP(55)

where CSCA is the scattering cross-section of the particle(measured in the units of area), the proportionality factor
QSCA is termed scattering efficiency. In the general case ofparticles that both absorb and scatter, the attenuation
cross-section (also called extinction cross-section) should
be used instead of CSCAC ATT = Q ATT AP = C ABS + C SCA = (Q ABS + QSCA ) AP , (56)where QATT and QABS are the attenuation and absorption
efficiencies, respectively; CATT and CABS are the corresponding cross-sections.
Calculation of the scattering and absorption efficiency
factors is the central problem of the Mie scattering theory.
The theory provides the exact solution of the Maxwell
equations, describing the propagation of electromagnetic
radiation for a plane wave incident on spherically symmetric particles. The intensity of scattered light at any
angle can be calculated for a particle with the given relative refractive index nR and size parameter x, defined byexpressions

nR =

nP
,
nA

(57)

where nP and nA are the refractive indices of the phosphor
material and ambient medium, respectively; and

x=


,


(58)

where f is the particle diameter and l is the wavelength oflight incident on the particle. The desired attenuation/
scattering efficiency factors are obtained in the form of aseries of Legendre polynomials. If no additional simplifying assumptions can be made, the required calculations
are computationally quite intensive. The comprehensive
description of the procedure may be found in numerous
textbooks on the scattering of light by small particles, e.g.
in Bohren and Huffman (2004) Mishchenko et al. (2002),
or van de Hulst (2009). An important outcome is that the
scattering efficiency factor asymptotically tends to a valueof 2 as the size parameter increases (i.e. for particles
much larger than the wavelength of light). In the range ofsmall values of the size parameter, a steep decrease of thescattering efficiency is observed.
For particles which are much smaller than the wavelength of light (f < 50 nm), the intensity and pattern of
scattering can be obtained by a much simpler Rayleighscattering theory. For such particles, the incident electromagnetic field behaves almost as an electrostatic field andis homogeneous inside of the particle. This results in thefollowing equations for the scattering and absorption efficiencies (Mishchenko et al., 2002)
QSCA =

2

8 4 n R2 − 1 ,x 2
nR + 23(59)

 n2 −1  .
(60)
Q ABS = 4 x Im  2R
 nR + 2 
It is important to note here that the scattering efficiency
scales with the fourth power of the size parameter,whereas the absorption efficiency has a linear dependence.

33

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

This means that the decrease in size of the nanoparticles
strongly increases the contribution of absorption to theoverall attenuation.
If the effective attenuation cross-section of phosphor
particles is known, it can be used for assessing the collective optical properties of ensembles of particles. For theidealized scenario of single scattering by N particles perunit of volume (particles are assumed to be sparsely
spaced), the Beer-Lambert law (see Eq. 12) can be rewritten to yield (Hinds, 1999)=
I T I 0 exp(−( +  )=d ) I 0 exp(− NQ ATT APd ) .

(61)

S=

const.


relating the scattering coefficient S with the size of phosphor particles can also be applied in the framework of the
Kubelka-Munk theory (Butler, 1980). When particles are
separated from each other by sufficiently large distances
so that the scattering from each single particle is notaffected by the proximity of its neighbors, it is possible todirectly relate the parameters of the Kubelka-Munk theory with those of the Mie theory by introducing additionalparameters (Liu et al., 2005)

Alternatively, it could be reformulated for the particle
3 fV
K N=
 C ABS Q ABS ,volume fraction f V by assuming particles of spherical =2shape and diameter f

fV = N 3
,
6

(62)

AP =

 2
,
4

(63)

=
I T I 0 exp(−

3 fV Q ATT
d) .
2

(64)

For non-absorbing particles substantially larger than
the wavelength of light,
Q=
Q=
2.
ATT
SCA

(65)

one obtains a simple relation between b and f=


3 fV QSCA 3 fV
=
.
2


(66)

If the volume concentration of particles (i.e. f V) does notchange, the scattering constant in the Beer-Lambert law
is inversely proportional to the phosphor particle size. For
nanoparticles (see Eq. 59),
2

=


2

3 fV QSCA 4 fV 4 n R2 − 1
4 4 fV  3 n R2 − 1, (67)==x 22
nR + 2n R2 + 2
4

it is expected that the scattering constant scales in direct
proportion to f3. For the absorption constant (Eq. 60), we
have

=

3 fV Q ABS 6 fV
 n 2 − 1  6 fV
 n 2 −1 
x Im  2R  =Im  2R  ,=2 nR + 2  nR + 2 (68)which seems not to be affected by the size of nanoparticles. It is important that both a and b become dependent
on the wavelength light. We should also keep in mind thatthe refractive index is also a function of the wavelength.
For superwavelength-sized particles, expressions of thegeneral form

34

(69)

3f
S=
N  (1 −  d ) C SCA = V  (1 −  d ) QSCA ,
2

(70)

(71)

where  is the average path-length parameter (assumed
equal to 2 in the original Kubelka-Munk theory), and  dis the forward-scattering ratio for diffuse radiation (i.e. afraction of energy that each particle scatters in the forward direction; it can also be determined by the Mietheory). It is possible to derive K and S for nanophosphorssimilar to Eqs. 67 and 68. However, such expressions cannot properly describe light propagation in the nanophosphor screens because the previously made assumption of
independent light scattering by each particle, which
requires their large separation, is never fulfilled forpacked nanoparticles.

4.2 Dependent scattering and absorption in densely
packed powders
In some cases, the collective optical properties ofdensely packed particles can still be treated as if theseparticles were attenuating incident light independently
from each other. In many cases, however, the influence ofthe neighboring particles cannot be neglected. For example,
effects generally termed as particle crowding play a verysignificant role in the technology of pigments (Auger et al.,2009; Koleske, 1995). With increasing packing density, thedistances between neighboring particles decrease and more
and more particles come into contact with each other. The
mean free path of the photons between two successive scattering events is determined by the average interparticle
spacing and thus it should decrease as well. If it becomescomparable to the particle size, the wavefront of the scattered light incident on the next particle along its path canbe appreciably different from the plane wave. As a consequence, the accuracy of calculations based on the efficiency factors obtained from the Mie theory can be
impaired. Furthermore, in such a case phosphor particles
cannot be treated as point-like scatterers. The absorption

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

and scattering coefficients (see Eq. 66) should be corrected
for volume scattering (Brewster, 2004) =3 fV QSCA
3 fV Q ABS
=,− fV )2 .
(1(1 − fV )2

(72)

These expressions differ from those derived for the point
scattering by the factor (1-f V) in denominator, which is
introduced in order to account for shadowing of particles
by each other for f V > 0.1.
Significant qualitative changes in the interaction oflight with particulate matter occur when the interparticle
distances enter the size range of a single wavelength ofincident light. At this scale, the scattered fields of theneighboring particles can become spatially coherent evenfor an incoherent radiation source. Coherent addition of
the scattered light strongly affects the scattering characteristics of particles in the far field (Tien, 1988). At thesame time, the near-field interactions become pronounced(McNeil et al., 2001). At a subwavelength distance fromthe particle surface, electromagnetic fields include contributions from non-propagating evanescent waves (Li et al.,2005; Mendes et al., 2010). Their influence on the radiation transfer is manifested, for example, by a phenomenon
known as the frustrated total internal reflection, whichcauses transmission of light between two media with highrefractive indices separated by a small gap filled withmaterial of lower refractive index at the angles of incidence, for which the total internal reflection would occur
in the absence of the second high-index medium. The
near-field interactions affect both absorption and scattering of light by particulate matter (Tien, 1988).
The onset of the dependent scattering and absorption isusually determined by a 5% deviation from the independent Mie theory. It was found that this threshold is usuallysurpassed when the interparticle clearance decreases
below approximately one half of the wavelength of theincident radiation (Tien and Drolen, 1987)
cd ≤ 0.5 ,(73)

where cd denotes the clearance for which the dependent
effects are significant, and l is the wavelength of light inthe medium between the particles (not l0 for vacuum). It
was shown that the criterion given by Eq. 73 approximately
corresponds to the clearance at which the near-field zones
of scattering particles begin to overlap (Kamiuto, 1984).
Although in general particles are randomly packed andhave different sizes and shapes, the ratio of the averageinterparticle clearance to the wavelength is very often
assessed by a formula derived for a periodical rhombohedral arrangement of monosized spheres (Tien, 1988)cx  0.905 =− 1 ,  f 13
 V


(74)

where f V is the particle volume fraction, x is the particle
size parameter. For nanoparticles, the clearance and the
distance between the centers of the particles are practically equal. The position of the boundary between the
independent and dependent regimes almost does notchange with the particles size parameter, and therefore forRayleigh particles, the critical particle volume fraction of
0.006 is generally assumed.
The “dependent” effects described above result in adecrease of the effective scattering cross-section of particles. For small absorbing particles, the absorption efficiency factor was found to increase (Kumar and Tien,
1990; Prasher, 2007). In the range of Rayleigh scattering,the contribution of absorption to the total attenuation
dominates over scattering, and therefore the dependent
attenuation efficiency of absorbing particles increases aswell (Kumar and Tien, 1990; Prasher, 2007; Siegel andHowell, 1992).
Quantitatively, the problems of radiation transfer in theregime of dependent multiple scattering are usually
solved by numerical simulations (Tien and Drolen, 1987).
In several cases, analytical relations between the depenDdent scattering efficiency factor QSCA
and the independentM(i.e. Mie-) scattering efficiency QSCA
could be obtained.
For example, the pioneering work by Hottel et al. (Hottel
et al., 1971) resulted in the following empirical expression
for c/l > 0.092c QM 
= 0.25 − 3.8 ,log log  SCA
D Q SCA (75)

which was verified for x < 1 (Tien and Drolen, 1987).
For the size parameter x→0, an analytic relation between
M
D
QSCA
and QSCA
could be derived for the Percus-Yevick
hard-sphere model (Tien and Drolen, 1987)
4

D
QSCA
(1 − fV ) .
=M
QSCA(1 + 2 fV ) 2(76)

An approximate expression for the dependent absorpDin the limit of Rayleigh particles
tion efficiencies Q ABS(i.e. x→0) was identical for several different models(Kumar and Tien, 1990)
2
D = 4 x Im  n R − 1  ,Q ABS
 n2 + 2 
 R


(77)

where
 n2 −1 = 1 − 2R
fV  .
 nR + 2 (78)

Recently, it was shown that changes to the effective
refractive index of a nanoparticulate medium should betaken into account when modeling the radiation transfer
with dependent absorption and scattering (Prasher, 2007).

35

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

A turbid medium filled with particles much smaller thanFor the scattering coefficient, we combine Eq. 67 and 76
the wavelength of light acts upon photons, which traverse
2
4D
2
3 fV QSCA
4 fV 4 n EFF− 1 (1 − fV )it, as an optically homogeneous medium with a refractive =
 =
x 2
2

nEFF + 2 (1 + 2 fV ) 2
index determined by the refractive indices of constituting
media and the particle volume fraction. From this point of
2
4
2
view, the influence of the volume concentration of nanopar4 4 fV  3 n EFF− 1 (1 − fV )
.
(85)
=
2
ticles on the effective refractive index can be considered as
4n EFF+ 2 (1 + 2 fV ) 2
a further effect of dependent scattering and absorption.
Assuming a substantial number concentration N of
The coefficients K and S for the Kubelka-Munk model
nanoparticles in vacuum (there should be many nanoparcould be derived in similar way. However, their complexity
ticles in a sphere with a radius equal to the wavelength of
precludes convenient comparison of the scattering andlight), the effective refractive index nEFF can be related byabsorption properties of conventional phosphors and nanothe Lorentz-Lorenz equation (van de Hulst, 2009), also
phosphors. To complete this section, the experimentally
known as the Clausius-Mossotti relation (Meltzer et al.,observed wavelength dependence of the attenuance of coat1999)
ings made of the same phosphor with different particle
sizes is shown in Fig. 6. One can see that the values mean2 −1
4
sured
in the range of strong absorption (l < 280 nm) are
N = 2EFF,(79)
n EFF + 2
3very close, whereas near the main emission peaks (l ≈where N is the number concentration of particles and a is590–650 nm), scattering of the nanophosphor coating (i.e.
the polarizability of the nanoparticles. The polarizability
attenuance minus absorbance, the latter is negligible in thisdefines a dipole moment of the Rayleigh particles induced
wavelength range) is two orders of magnitude lower thanby an external electric field and can be used to describethat of phosphors with larger particle sizes. Furthermore,their scattering. Alternatively, the effective refractive
an increase of the particle volume fraction from 0.03 to 0.1
index can be derived from the volume concentration ofdoes not practically affect the curve in the short wavelength
particles f V and their refractive index nPrange but the scattering in the red part of the spectra substantially decreases due to the more pronounced dependent
2
n EFF
−1
n P2 − 1effects. The scattering of conventional phosphors is practi.
(80)
f
=
V
2
n EFF
n P2 + 2+2
cally independent of the wavelength. For nanophosphors, a
For particles dispersed in a medium with refractive index
steep decrease is observed toward longer wavelengths in
nA it becomes (Klein, 1988)
agreement with the predictions of Eq. 67. A consequence ofthe dramatically decreased scattering can be seen in the
2
n EFF
−1
n P2 − 1
n A2 − 1
f
f
=
+
1
−
(
)
shape of the thickness dependence curve for the T-mode
V
V
.
(81)
2
n EFF
n P2 + 2
n A2 + 2+2
intensity of luminescence in Fig. 7. Once the maximal
value is reached, the brightness of the screen stays virtually
In many cases, however, a simplified expression below isconstant for any thicker phosphor coating, very similar to
applied (Meltzer et al., 1999; Vollath, 2008)
the theoretically expected behavior for non-scatteringn EFF= fV n P + (1 − fV ) n A .
(82)screens (Fig. 2).
The imaginary part of the effective refractive index (usuAs shown above, the intensity of scattering in theally referred to as the extinction coefficient k) can be transnanoparticle coating dramatically decreases with increasformed into the absorption coefficient of the nanophosphor
ing wavelength of scattered light, decreasing the size oflayer by the expression (Bohren and Huffman, 2004)
particles and increasing their packing density. Theoretically it should be possible to almost completely eliminate
4 Im(n EFF ) 4 k EFF
 ==the scattering of light emitted by nanophosphor, if the par,
(83)
0
0
ticles could be made arbitrarily small and/or the particle
volume fraction in the screen could be increased to values
where l 0 is the wavelength of light in vacuum.
that are as high as possible (ideally up to the bulk density
A potentially more exact expression can be derivedof the phosphor material). In this way, non-scatteringfrom Eq. 68 and 77
phosphor screens suitable for diffraction-limited imaging
D2
could be obtained. At the same time, nanophosphor
3 fV Q ABS
6 fV
−1 
 n
x Im  2EFF==screens are less prone to losses due to internal reflection2
 n EFF + 2 (see Sec. 2.1) because their surface is not smooth (or can be2made deliberately rough, if needed), and their effective
−1 
6 fV
 n
.
(84)
Im  2EFF=refractive index is usually much lower than that of single
 n EFF + 2 
crystal films or fully sintered transparent ceramic phosphor

36

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

Fig. 6

Attenuance spectra Y2O3:Eu nanophosphor coatings(NP) of different coating densities and particle volume
fractions deposited by flame aerosol deposition. For
comparison, spectra of a commercial phosphor powder(CP) and a fine phosphor powder produced by flame-­
assisted spray pyrolysis (FP) are also shown. Their
thickness was optimized for the highest T-mode output.
The figure is a compilation of data published in Fig. 7
and 9, Kubrin et al. (2010), © IOP Publishing.

plates. Now we can try to figure out the limiting factors,
which counteract the advantages of weak light scattering
by nanoparticulate matter.

4.3 Influence of particle size on emission of
luminescenceHow do the particle size and packing density influence
the process of light emission by the particles of doped
dielectrics? The quantum efficiency of a phosphor isdetermined by the competing processes of radiative andnon-radiative relaxation of excited states. It can be
expressed by the corresponding contributions to the decay
times of luminescence

q=


,
R

(86)

where tR is the radiative decay time constant (without
non-radiative processes) and t is the observed emission
decay time constant. In the simplest case, when both theradiative and non-radiative contributions can be represented by a first-order exponential decay, t would change
according to

1
1
1
=
+
,

 R  NR(87)

where tNR is the non-radiative decay time constant.
Changes to the quantum efficiency and the luminescencedecay time of doped phosphors are not very pronounced
until they enter the size range of nanoparticles (i.e.
< 100 nm). A further reduction of the size of phosphor particles usually has a profound effect on the performance ofFig. 7 T-mode thickness dependence curve of Y2O3:Eu nanophosphor coatings normalized to the highest brightnessof the screen made of the commercial phosphor powder. The figure is a modified version of Fig. 8, Kubrin
et al. (2010), © IOP Publishing.

doped phosphors.
In the deep subwavelength size regime, the emission
rate usually decreases with decreasing phosphor particle
size. It is mainly attributed to the changes in the effective
refractive index of the particulate medium (see Eqs.
80–82) (Liu and Chen, 2007a). The radiative decay timeof an excited ion embedded in a medium with a refractive
index n can be expressed as follows (Henderson and
Imbusch, 1989; Meltzer et al., 1999)

R=

1
 02
,
2
f (ED)  1 2
(n + 2) n
 3


(88)

where f(ED) is the oscillator strength of the electric dipole
transition. In the case of nanoparticles, the effective refractive index nEFF defined in the previous section should be
used. Thus it can be expected that for vanishingly small
phosphor particles separated by large distances (c > l,i.e., f V→0), the radiative lifetime of electronic transitions
can be increased from its bulk value by a factor of

nP 2(nP + 2) 2 .
9(89)

For the magnetic dipole transitions, Equation 88 should
be replaced by (Liu and Chen, 2007b)
R=

1
 02
f (MD) n 3 ,(90)i.e. the radiative lifetime of the nanoparticles could differ
from that of the bulk phosphor by a factor of n P3 .
According to Eqs. 86 and 87, the decrease of the radiative decay rate due to the typically low effective refraction
index can cause substantial reduction of the quantum efficiency. This effect has to be taken into account whilemeasuring the efficiency (Mialon et al., 2009) because it37

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

becomes dependent on the packing density of nanophosphor. Compaction of the porous nanophosphor layer from
3 to 10 vol.% particle volume fraction discussed in theprevious section, not only decreased its scattering but also
increased the T-mode brightness of luminescence by 13%(Kubrin et al., 2010).
The non-radiative decay time of luminescence for conventional phosphors also affects quantum efficiency. It is
usually described by the temperature-dependent multiphonon relaxation rate (Liu and Chen, 2007a) −∆E   exp(m kT ) = C exp  NR m   exp(m kT ) − 1 
1

∆E

m

, (91)

where ħw m is the maximum phonon energy of the lattice
vibrations, DE is the energy gap between the populated
state and the next low-lying state, k is the Boltzmann constant, T is the temperature, and C and a are empiricalparameters characteristic for the particular crystals. In
nanocrystals, the phonon density of states becomes discreteand the low-energy acoustic phonons are gradually eliminated with decreasing particle size so that the non-radiative
relaxation rate of excited states and the efficiency of thephonon-assisted energy transfer in nanophosphors can besubstantially reduced as compared to that in bulk materials(Liu and Chen, 2007a).
The excited state can also migrate between the activator ions in insulating hosts due to the resonant energy
transfer (Liu and Chen, 2007a). However, a slight variation of the energy levels of the embedded ions due to latticestress and defects noticeably decreases the probability of
the resonant energy transfer, especially for particles with asize below 40 nm (Chen et al., 2003). As a result, bothmechanisms of migration of excitation energy are inhibitedin nanophosphors.
On one hand, the decreased efficiency of the phonon-­assisted energy transfer impairs sensitized or upconversion
luminescence (Chen et al., 2003). And on the other hand,
the increase of the non-radiative lifetime of luminescence
due to restricted energy transfer should favorably influence
the overall quantum efficiency of conventional downconverting phosphors by postponing the onset of the concentration quenching, especially when the size of the particles
approaches 1–2 nm (Mutelet et al., 2011). As a generalobservation, nanophosphors are significantly less efficientthan their micrometer-sized counterparts (Liu and Chen,
2007a; Ronda, 2008), which means that the non-radiative
decay rate either does not decrease with the size of
nanoparticles or it decreases too slowly to counteract thedecrease of the radiative decay rate discussed earlier in thissection. It is widely accepted that the main obstacle forachieving the performance of bulk materials is constitutedby the increased specific surface area of nanoparticles (i.e.

38

by large values of surface-to-volume ratio).
In the presence of migration of excitation, the non-­radiative relaxation rate is determined not only by theefficiency of the inter-ionic energy transfer but also by
the concentration of lattice defects acting as emission
quenchers. The particle surface itself should be considered as a distortion of the crystalline structure. Atoms
within several lattice constants from the surface are displaced due to the surface reconstruction, and dangling
bonds are often terminated by chemical species with highphonon frequencies (e.g. OH-, CO3 - or NH-groups)
adsorbed from the ambience (Bogdan et al., 2011; Igarashi
et al., 2000; Liu and Chen, 2007a; Nayak et al., 2007;
Ronda, 2008). The phonon spectra of nanoparticles arefurther modified by the introduction of surface phononmodes which are localized at the interface with sur­rounding medium and can provide new channels for non-­radiative relaxations (Prasad, 2004). For nanoparticles
dispersed in solvents, polymers, or glasses, the effect of size
confinement leading to inhibition of the energy transfer
does not play any significant role and the non-radiative
decay time of luminescence is usually shorter than that of
the same particles not embedded in any medium (Liu andChen, 2007a). All these effects generally referred to as
surface quenching effects become more pronounced withdecreasing phosphor particle size and may dramaticallychange the dynamics of the luminescence emission ofultrafine phosphor powders.
One of the size effects attributed to the surface quenching consists in deviation of the luminescence decay curvefrom single-exponential behavior (Zhang et al., 2003). It
was discovered that even for relatively low concentrationsof activator, the decay of emission of nanophosphors ismuch better fitted with a second-order exponent (Kubrin,2012). Following the explanation proposed in Zhang et al.
(2003), the shorter decay time constant should correspondto activator ions situated on or near the particle surface.
However, it is very unlikely that there are only two dissimilar kinds of activator ions (on the surface and in thevolume of nanoparticles) without any intermediate states.
It was suggested that the decay time constants gradually
increase from the surface into the depth so that it could be
described by a stretched exponential function (also called
Kohlrausch function)
I (t) I 0 exp − t
=
 ,



( )

(92)

where 0 < b ≤ 1 (Kubrin, 2012). The parameter b characterizes the width of distribution of the lifetimes and isoften used as a measure of “disorder” present in the system under investigation. The Kohlrausch function is successfully applied to describe relaxation processes in many
areas of physics including molecular fluorescence andluminescence of nanoscale semiconductors (Berber-Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

an-Santos et al., 2005; Chen, 2003; Martin and SheaRohwer, 2006).
Obviously, it is desirable to have a means to suppress thesurface quenching. A simple strategy was proposed, whichallows the quantum efficiency of nanophosphors to be
improved. A thin shell of undoped host material or someother dielectric with low-as-possible maximum phonon
frequency and similar lattice constant has to be grownaround each nanoparticle. The external layer efficiently
reduces the energy transfer to the quenching centers at thesurface (Gnach and Bednarkiewicz, 2012; Liu and Chen,
2007a, Ronda, 2008, Wang et al., 2010). This strategy madeit possible to achieve an exceptionally high quantum efficiency of 70% for CePO4:Tb/LaPO4 core-shell nanoparticles(Kömpe et al., 2003). The same method has been successfully applied for semiconductor quantum dots with a highquantum yield (Liu and Chen, 2007a). In certain cases, an
undoped shell around phosphor nanoparticles can perform
some further functions, e.g. protect the dopant ions fromoxidation to a non-luminescent state (Buissette et al.,2006). It should be noted that “finishing” of the surface ofphosphor particles is sometimes also used for conventional
micrometer-sized phosphors in order to improve theirmaintenance or stability in suspensions (Jüstel et al., 1998).
For coarse-grained phosphor powders, passivating coatings
do not directly affect the luminescent properties.
Although the large surface-to-volume ratio of nanophosphors is usually a problem, it also can provide unique
opportunities. For example, it has been demonstrated thatthe surface of Y2O3:Eu nanophosphor, which usuallyemits pure red light and is efficiently excited with only
UV-light of wavelengths below 280 nm, can be passivatedwith organic ligands acting as a molecular antenna (Daiet al., 2011). Acetylacetonate ligands increase the absorption cross-section of phosphor nanoparticles so that theemission from Eu-ions and oxygen vacancies can be
excited by a UV-LED (l=350–370 nm) resulting in white
luminescence.
The number of emitting ions inside of each nanoparticle
decreases with its size and it becomes possible to observe
emission from single ions of the activator. The constantintensity of emission under the constant excitation andexponential decay of luminescence, when excitation ceases,
turns into discrete on-off blinking events (Barnes et al.,2000). Studies of luminescence of single phosphor
nanoparticles offer additional opportunities for research.
For example, they provided evidence of the dipole nature ofelectronic transitions involved in the emission of light(Bartko et al., 2002).
The luminescence spectra of nanophosphors are practically not affected by quantum confinement, as opposed to
semiconductor quantum dots. Characteristic luminescence
results from electron transitions inside of single impurity
ions, which are strongly localized (this is especially true forrare earth ions predominantly used as activators for nanophosphors). As a result, the positions of the energy levels
participating in radiative transitions hardly change even for
nanophosphors with particle sizes well below 10 nm (Liuand Chen, 2007a; Ronda, 2008). This is the reason why theterms nanophosphors and quantum dots should not be usedinterchangeably. A sometimes reported broadening of thepeaks in the spectra of emission is mostly attributed to
distortions of the crystalline structure of nanoparticles(Lebbou et al., 2005; Tanner, 2005). The most pronounced
changes related to quantum confinement of electronic
states are reported for the peaks in the spectra of excitationof photoluminescence which involve the edges of the
bandgap of the host material, such as shifts of the chargetransfer bands (Shang et al., 2011).

4.4 Non-optical effects of reduced particle size
It is not only the optical properties of phosphors thatare modified by the downscaling of phosphor particle
size. There are several further particle size effects which
can have implications for the technology of manufacturing and which indirectly influence the performance of thepowder screens.
The increase of the surface-to-volume ratio affects thethermodynamics of the phase transformation. The
Gibbs-Thomson effect favors crystallization of nanoparticles
in high-pressure polymorphs due to additional hydrostaticpressure P (Dosev et al., 2006; Skandan et al., 1992)

P=

4
,


(93)

where g is the surface energy (value of 1.5 J/m2 is typical formany ceramic materials) and f is the size of nanoparticle.
More generally, it can be stated that reduction of the particle
size decreases the temperature of phase transformations(Vollath, 2008). The melting points of nanoparticles arelower than those of the bulk substances (Kondepudi, 2008;
Vollath, 2008). In addition, it can result in a particle size
limit for the crystallization of some ceramic hosts (e.g. 8 nm
for Al2O3, Vollath, 2008).
The contact mechanics of solid particles undergoes
major changes when their size decreases. For nanoparticles, the adhesive forces can exceed other common forcesby orders of magnitude. As a result, they stick firmly to
any surface they contact (Hinds, 1999). Furthermore,such particles become cohesive, i.e. they tend to agglomerate with each other. For example, a clustering of
nanoparticles dispersed in transparent matrices can cause
a dramatic increase of light scattering (Vollath, 2008).
Agglomeration and large interparticle friction forces arealso responsible for the extremely low filling fraction of arandom loose packing of fine and ultrafine powders(Valverde and Castellanos, 2006) as well as for low density

39

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

of compacted nanopowders (< 45% of the theoretical values) (Gonzalez and Piermarini, 2000).
The size of phosphor particles directly influences theirstability in colloidal suspensions. A particle in a liquid oflower density settles with a velocity that is proportional to
the square of its size (Stokes’ law, Hinds, 1999). For
well-dispersed nanoparticles, this velocity becomes
extremely small. This has a strong impact on the technology of phosphor screens. On one hand, it renders screen
deposition methods based on sedimentation, which areotherwise very popular in the manufacturing of monochromatic displays, highly impractical. On the other hand, byusing colloidal methods, nanophosphors could be processed
into special elaborate structures with the feature sizes on
the order or below the wavelengths of incident/emitted lightto gain additional functionality, e.g. to produce luminescent
3D photonic crystals with a morphology of inverse opal
(Zhang et al., 2010). The technology-related issues will be
reviewed in the next section.

5. Manufacturing of nanophosphor screens
5.1 Synthesis of nanophosphors
Many research groups all over the world are currently
investigating different methods for the synthesis of nanophosphors. The most popular approaches have beenreviewed several times (Chander, 2005; Dosev et al.,2008; Tan, 2012; Tanner, 2005; Tissue, 1998; Tissue,2007) and are only briefly summarized here.
According to Tissue (2007), two main groups of synthesis methods can be defined. The first one includes
different ways of producing nanophosphors in the gas
phase, including synthesis in a vacuum, inert or reactive
gas atmospheres. A source of heat for the vaporization ofelements of the synthesized compounds is implied. Thisfunction can be performed by an electron beam, a laser
beam, or a flame. Solid nanoparticles condense in the gas
phase upon cooling. Such methods as laser-assisted
gas-phase condensation (Bihari et al., 1997, Tissue, 2007),
chemical vapor condensation (Konrad et al., 1999b;
Schmechel et al., 2001), and flame spray pyrolysis (Laineet al., 2000; Camenzind et al., 2007; Kubrin et al., 2010;
Sotiriou et al., 2011, 2012) fall under this category. Somewhat ambiguous is the assignment of pulsed laser deposition (Bär et al., 2005; Jones et al., 1997; Rajan and
Gopchandran, 2009, Xu et al., 2011) and related laser ablation methods (Masenelli et al., 2013), which are sometimes
included in this group of methods although they rather
produce dense solid films and not nanopowders.
In the second group of synthesis methods, phosphor
nanoparticles are obtained in a liquid solution. The group
includes various realizations of chemical precipitation

40(Bazzi et al., 2004; Buissette et al., 2006; Khan et al.,2008; Lebbou et al., 2005; Mutelet et al., 2011; Wang etal., 2011), hydrothermal (Jacobsohn et al., 2007; Huang etal., 2012b; Riwotzki and Haase, 2001; Song et al., 2011;
Zhang et al., 2010) or solvothermal (Gong et al., 2013;
Kasuya et al., 2007; Nyman et al., 2009; Vorsthove andKynast, 2011) synthesis, thermal (Si et al., 2006; Ye et al.,2010) or microwave (Dai et al., 2011) decomposition, solgel methods (Back et al., 2012; Dhanaraj et al., 2001; Eidet al., 2005; Gupta et al., 2010; Zhang et al., 2002), inverse
micelle method (Barnes et al., 2000; Hirai et al., 2004),
laser ablation in liquid media (Mhin et al., 2009; Singh etal., 2010), and combustion synthesis (Jacobsohn et al.,2007; Qi et al., 2002; Vu et al., 2007; Ye et al., 2009;
Zhang et al., 2003), including flame-assisted spray pyrolysis, which is also capable of producing nanoparticles if the
precursor solution is appropriately modified (Purwanto etal., 2008).
Chemical precipitation, sol-gel and some other methodsof wet chemistry are very attractive because of simple andthe relatively cheap process arrangement, but the collected products often require thermal post-treatment toimprove their crystallinity and quantum efficiency. From
this point of view, hydrothermal and solvothermal methods have a crucial advantage as they can facilitate thesynthesis of well-dispersed crystalline nanoparticles at
low temperatures (usually in the range 100–300°C).
Another common shortcoming of many synthesis methods is a relatively low production rate of nanopowders.
Upscaling of batchwise wet chemical processing is notalways straightforward although for some methods thislimitation is less pronounced. For example, sol-gel techniques are known for a high yield of the products. Highproduction rates can be achieved with flame spray pyrolysis, where values on the order of 1 kg/h were alreadydemonstrated (Mueller et al., 2003; Mueller et al., 2004).
As a next step towards the practical application ofphosphors with decreased particle size, the optical performance of screens and coatings made of the new materials
should be investigated. The choice of the screening technique is crucial because it affects both the optical andmechanical properties of phosphor coatings.

5.2 Deposition of separately produced nanophosphor
powders
The simplest and most widely used method for depositing flat monochrome screens is gravitational settling (orsedimentation) of a suspension of phosphor particles in asolution containing a binder, e.g. potassium silicate buffered by barium nitrate or barium acetate (Sadowsky, 1949;
Sasaki and Talbot, 1999; Tomita, 2007; Widdel, 1992).
However, it is suitable only for large particles which settle fast.
For particles smaller than 5 mm down to 1 mm, a centrifugal

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

force should be applied in order to reduce the sedimentation time and to increase the packing density. Settling
could hardly be applied for nanophosphors.
Electrophoretic deposition (EPD) is often used withfine particle size phosphors (Sadowsky, 1949; Sasaki and
Talbot, 1999; Sluzky and Hesse, 1989; Yum et al., 2003).
In this method, the phosphor in liquid suspension (e.g.
isopropyl alcohol) is attracted to an immersed electrode.
Phosphor particles should be electrically charged (e.g. by
the introduction of charging ions such as Mg2+); the particles will then deposit onto the electrode of the opposite
charge. Therefore, EPD requires a conductive substrate(e.g. ITO glass). Deposited samples are dried and baked.
Smooth, dense phosphor layers with exceptional resolution
and low noise can be deposited by EPD from conventional
micrometer-sized phosphors, although the adhesivestrength of EPD coatings is relatively weak (Yum et al.,2003). The deposition of luminescent nanoparticles by
EPD and similar approaches has been reported (Lee et al.,
2000; Smith et al., 2003; Wakefield et al., 2001; Zhang etal., 2006) but it does not seem to gain much popularity,
which could be at least partly explained by the fact that theneed for transparent and uniformly conductive substrates
diminishes the attractiveness of the method for currently
developing applications of nanophosphors other than fieldemission displays.
One of these applications (we will discuss them later inthis review) is in phosphor-converted LEDs and there isongoing research on the processing of nanophosphors by
the corresponding standard manufacturing methods.
Phosphor powders deposited onto UV- or blue LED chips
are usually encapsulated by epoxy or silicone resins. Thisapproach was successfully tested not only with epoxy(Nyman et al., 2009) and silicone (Revaux et al., 2011a)
but also with poly(methyl methacrylate) (PMMA, Saladinoet al., 2010), derivatives of ethyl methacrylate (Davion etal., 2011), poly-N-vinylpyrrolidone (PVP, Potdevin et al.,2012), and cyanoacrylate (Super Glue, Dai et al., 2011). In
an interesting recent publication by Mutlugun et al. (2012),
InP/ZnS quantum dots embedded in PMMA were processed into free-standing film with an area exceeding
50 cm × 50 cm. Requirements imposed on the encapsulation of nanophosphors and semiconductor quantum dot
are very similar, so that the results obtained for the latter should be taken into account for the future work on
nanophosphor-converted white LEDs. Furthermore, thisknowledge could also be useful for X-Ray or UV-enhanced
CCD image sensors, where similar strategies for the deposition of phosphor layers were proposed (Franks et al.,
2000; Franks et al., 2003). Properties of the encapsulant are
crucial because it may impair the quantum efficiency of thenanophosphor as discussed in Sec. 4.3. Nanophosphorsshould not agglomerate in the polymeric phase, which substantially limits the achievable particle volume fractions(e.g. < 20% w/w for CdSe quantum dots in 13 different
polymers, Schreuder et al., 2008). Another related common
problem is the photodegradation of encapsulants which lose
their transparency under exposure to UV-light (Edwards etal., 2001; Koh et al., 2013, Narendran et al., 2004).
Thick layers of nanophosphors could be deposited withthe well-known Doctor Blade method (Fujiwara et al.,2008) or by pressing a viscous paste between two substrates (Kasuya et al., 2007; Park et al., 2012a). The screen
printing technique, in which a concentrated phosphor ink
containing a liquid organic vehicle is applied to a substrate through a mesh screen and then calcinated toremove organic additives, could also be implemented fornanophopshor plasma display panels (Song et al., 2012a;
Song et al., 2012b), field emission screens (Wang et al.,2011), and X-Ray imaging systems (Kim et al., 2007).
Sol-gel coatings and pastes can be applied by dip-coating(Pang et al., 2003; Wu et al., 2007) or spin-coating(Bedekar et al., 2010; Buissette et al., 2006; Huang et al.,2012a; Khan et al., 2008; Klausch et al., 2012; Psuja et al.,2009; Revaux et al., 2011b; Song et al., 2011). Wet spraying, known for many decades (Sadowsky, 1949), could be
adopted for the deposition of nanophosphors as well
(Fleury et al., 2012; Revaux et al., 2011a).
In all the above-mentioned techniques, phosphor
nanoparticles have to be dispersed in liquids and therefore
obey the principles of colloidal chemistry. The composition of the solvent plays an extremely important role
because it should prevent the agglomeration of nanoparticles (to ensure low scattering in the deposited screens andlow viscosity of the phosphor slurry/ink/paste during processing) as well as the contamination of the screen by
non-luminescent substances (residues of dispersants, surfactants, and chemical species adsorbed on the particle
surface), which could decrease its quantum efficiency.
Furthermore, the solvent is usually removed in the final
step of deposition. Drying can cause substantial shrinkage of the phosphor layer potentially leading to the formation of cracks. For example, sol-gel coatings are especiallyprone to drying-induced cracks so that the crack-freedeposits can be obtained only if the layer thickness does
not exceed a certain critical value (typically on the orderof 1 mm, Brinker and Scherer, 1990).
On the other hand, colloidal methods offer unique
opportunities for processing nanophosphors such as
shape-directed self-assembly (Si et al., 2006, Ye et al.,2010) and templating of colloidal crystals (Zhang et al.,2010). It also facilitates novel methods of the deposition of
nanoparticles which are not applicable for conventional
phosphors: layer-by-layer assembly (Camacho et al., 2012;
Jang and Grunlan, 2005, Varahramyan and Lvov, 2006),
Langmuir-Blodgett technique (Lu et al., 2005), and ink-jet
printing (Fuller et al., 2002).

41

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

5.3 Simultaneous synthesis and deposition of
nanophosphors
Not all methods of processing conventional coarse-grained
phosphors require wet processing of powders. For example,
in dry spraying, a fine spray of dry phosphor powder isblown from a gun onto the tacky surface (Sadowsky,1949). This technique is hardly feasible for nanophosphorsbecause dry nanoparticles tend to build agglomerates sothat the advantages of reduced particle size could not be
fully utilized even if spraying would succeed. However,premature agglomeration of ultrafine particles can be precluded by combining processes of gas-phase synthesis
and film deposition in a single technology step. In such away, all intermediate steps are excluded (i.e. dispersion inliquids is not required), and the deposition of phosphor
coatings can be performed very rapidly. This approach is
exploited in laser-assisted gas-phase condensation (Tissue,2007) and electrostatic-directed deposition (Tsai et al.,2005), microwave plasma synthesis (Milewski et al.,1998) and hypersonic plasma particle deposition (Hafiz etal., 2004), as well as in flame aerosol deposition (FAD,
Kubrin et al., 2010).
Flame aerosol deposition, also known as direct nanoparticle deposition (DND), is the best studied method as it was
already tested for manufacturing advanced gas sensors(Kuehne et al., 2008; Mädler et al., 2006; Sahm et al.,2007), porous catalysts (Kavitha et al., 2007; Thybo et al.,2004), and battery electrodes (Chew et al., 2009), as well as
for the deposition of anti-fogging films (Tricoli et al., 2009)and optical coatings (Pimenoff et al., 2006). It is also industrially applied in the fabrication of optical fiber preforms(Mendez and Morse, 2007; Tammela et al., 2006).
FAD is derived from flame spray pyrolysis and should
be distinguished from other spray-based coating methods
which could also be used for the deposition of phosphors
but do not produce dispersed nanoparticles. One suchmethod is spray deposition, where inorganic films aredeposited by spraying solutions of appropriate reagentsover a heated substrate. The chemical transformation
occurs directly on the surface of the substrate. Phosphors
can be deposited in this way (e.g. Y2O3:RE, Hao et al.,2001) but this method produces continuous films rather
than powder coatings.
Flame spray pyrolysis (FSP) can be defined as a sprayprocess where the high-temperature environment forchemical reactions is provided by heat released by a burning spray. FSP of flammable precursors should be opposedto the flame-assisted spray pyrolysis (FASP) of precursors
that are not combustible themselves (e.g. aqueous solutions), and where heat is generated exclusively by an
external flame. Different methods of synthesis of inorganic powders by FSP can be further classified into
processes of direct droplet-to-particle conversion (DPC)42

and chemical vapor condensation (CVC). The droplet-to-­particle conversion occurs when the precursor solute is
not volatile. In such cases, the final weight of each single
particle is proportional to the initial size of the droplet.
The DPC usually produces submicrometer-sized particles.
The CVC involves the combustion of volatile precursors
which evaporate, react in the gas-phase, and condense to
produce nanoparticles of the desired compounds. In thecontext of this review, both FSP and FAD refer to the
CVC-type of particle formation. Latest reviews on thesubject can be found in Pratsinis (2010); Teoh et al., (2010)
and Strobel and Pratsinis (2007).
For the purposes of the deposition of particulate coatings, a substrate can be placed directly into the flame.
Under certain conditions, this could result in the heterogeneous condensation of pyrolyzed compounds from thevapor-phase directly on the surface of the substrate, i.e.
without producing free nanoparticles. This deposition
technique, first published in 1993 (Hunt et al., 1993), iscalled combustion chemical vapor deposition (CCVD). It
could also be used for the deposition of phosphors (e.g.
Zn2SiO4:Mn, Kang et al., 2006) in the form of solid films.
However, when the substrate is placed outside the reaction
volume, airborne nanoparticles can be formed. In thisway, the high temperature of the flame required to obtain
particles with improved crystallinity is separated from thedeposition zone. The substrate temperature can be
decreased down to 150°C so that it can facilitate the direct
deposition of nanopowders onto electronic chips (Tricoli
et al., 2008).
FAD essentially shares the main strengths and weaknesses of FSP. On the one hand, it is exceptionally rapid
and allows producing relatively thick deposits withinminutes (Kubrin et al., 2010). From this point of view,
FAD-deposited nanophosphor screens probably could
compete with conventional phosphors even for applications which do not require optical transparency or highimage resolution. On the other hand, due to the inherent
limitation of all combustion synthesis methods, FAD/FSP
is best suited for the production of oxides. Nevertheless,certain important non-oxide phosphors can still beobtained by appropriate post-treatment (Y2O2S:Er, Chenet al., 2003; Liu et al., 2002), flame pyrolysis in controlled
inert atmosphere (ZnS:Mn, Athanassiou et al., 2010), orby simply using an appropriate halide source (NaYF:RE,
Stepuk et al., 2013). The size of produced nanoparticles iscontrolled by parameters of the flame and, if needed, canbe further decreased by charging them during the synthesis with a corona discharge (Vemury and Pratsinis, 1995).
The deposits are extremely porous (particle volume fraction < 3 vol.%) but could be manually compacted to atleast 10 vol.% without destroying the integrity of thephosphor layer (Kubrin et al., 2010). Further compaction
should be possible through the elaboration of proper tech-Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

niques. Even for the thickness on the order of 100 mm, thedeposits were fairly homogeneous and free of cracks.
FAD should be considered a powerful tool for futurestudies on nanophosphors, and can certainly inspire
research on other functional nanoparticle coatings andother methods for the rapid processing of nanopowders.

6. Applications of nanophosphor screens
Phosphor-converted white LEDs was probably the field
where the advantage of low scattering of light was recognized first. Most of work here is focused on YAG:Cenanophosphor, which converts blue light from the LED
chip into yellow so that white light is obtained by color
addit ion. Kasuya et al. (20 07) demonst rated a
200-mm-thick nanophosphor film with 82% transparency
at the emission wavelength. No absolute figures of conversion efficiency or quantum efficiency were reported,but the doubling of photoluminescence intensity by placing a mirror on the rear side of the sample was pointed
out. In the case of conventional micrometer-sized phosphor, the use of the mirror had no appreciable effect onscreen performance. Nyman et al. (2009) reported anincrease of quantum efficiency of YAG:Ce nanopowder to
57% and its successful epoxy-encapsulation. The quantum
yield of the phosphor was further increased to 60% by a“protected annealing” in porous silica by Revaux et al.
(2011c). The same group investigated the incorporation of
nanophosphors into a TiO2 sol-gel coating in order to matchthe refractive index and thus further decrease scattering(Revaux et al., 2011a; Revaux et al., 2011b). A systematiccomparison of the performance of pc-LEDs incorporating
YAG:Ce with the morphology of a nanophosphor, thin-film
phosphor, ceramic plate and micrometer-sized powder was
performed by Park et al. (2012a), also including a 2D photonic crystal layer for improving the extraction efficiency
and short-wave pass filters for recovering the light emitted
backwards. Nanophosphor-based LEDs showed a conversion efficiency of 31%, packaging efficiency of 82%, andluminous efficacy of 40.2 lm/W, not much worse than thatof the ceramic plate or conventional phosphor powder andoutperforming the thin-film phosphor. Recently, a luminosity of 100 lm/W was obtained with ligand-passivated
Y2O3:Eu nanophosphor (Dai et al., 2011) discussed in Sec
4.3. This performance is competitive with current commercial products.
The optical transparency of nanophosphor layers was
crucial in the development of transparent plasma display
devices (PDD) first published in 2010 by the group of H.
Yang at the Hongik University, Seoul, Korea (Song et al.,2010). Initially starting with monochrome green-emitting
nanophosphor LaPO4:Ce,Tb, they reached a luminance of
97 cd/m 2 (Song et al., 2011). The transparency of thephosphor layer in the wavelength range of emission
exceeded 90% and that of the fully assembled test devices
was at least 40%. The work on red-emitting Y(V,P)O4:Eu
followed soon after (Song et al., 2012b) and finally, thefull-color PDDs based on LaPO4:Ce,Tb, Y(V,P)O4:Eu,and blue-emitting Y(V,P)O4:Tm were reported (Song etal., 2012a). The phosphors were deposited by means ofscreen printing and combined by line patterning. The
brightness of white emission was 96 cd/m 2 and could be
increased to 137 cd/m 2 by the application of a 2D photonic crystal (a monolayer of ordered polystyrene microspheres of a uniform size). Transparency could be held on
the level of 30%.
The advantageous properties of nanophosphors for fieldemission displays (FED) were demonstrated more than adecade ago (Lee et al., 2000; Wakefield et al., 2001). In thiscase, however, the main benefit was the increased phosphor
efficiency attributed to the improved crystallinity and surface microstructure, not the decreased scattering. New
works on nanophosphors for low-voltage cathodoluminescence have occasionally been published since then (Changet al., 2010; Shang et al., 2012; Wang et al., 2011).
There were a few reports on the application of nanophosphors for X-ray imaging (Cha et al., 2011; Kalyvas etal., 2012; Kim et al., 2007), but none of them clearlyaddressed the effects of phosphor particle size. A comprehensive theoretical treatment applying the Mie scattering
theory and Monte Carlo simulations showed that the best
imaging performance should be expected from scintillator powders with a particle size greater than 200 nm(Liaparinos, 2012). It should be concluded that there is noadvantage of utilizing nanophosphor screens for conventional digital radiography with a resolution lower than
20 lp/mm. This does not apply to X-ray microtomography and other imaging applications with submicrometer
resolution (discussed in Sec. 2.4.), because nanophosphors have a great potential in this area.
Another promising application of nanophosphor
screens is in the technology of solar cells, which absorb
electromagnetic radiation and convert it into electricity.
The efficiency of this process cannot exceed a so-called
Shockley-Queisser limit (usually about 30%) unless they
are enhanced by appropriate spectral converters (SC,Richards, 2006; van der Ende et al., 2009). Downshifting(conventional photoluminescence) and downconverting(quantum-cutting luminescence) SCs absorb high-energy
photons and convert them to photons of wavelengths more
efficiently absorbed by the corresponding solar cells. Suchcoatings are placed in front of the cell and ideally theyshould not interfere with light which does not need to beconverted. Obviously, transparency of the converter layer
is strongly desired so that nanophosphor coatings should
be preferred over conventional phosphors (Huang et al.,2012a; Khan et al., 2008; Peng et al., 2011; Takeshita et43Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

al., 2009). Upconverting SCs perform a complimentaryfunction of absorbing low-energy photons, for which thesolar cell itself is transparent, and convert to photons ofshorter wavelength so that they could also be absorbed by
the solar cell. Upconverters are usually mounted on therear side of the cell and can be processed from phosphor
nanoparticles as well (Chen et al., 2012). It was predictedthat the Shockley-Queisser limit for the efficiency of asingle junction solar cell can be raised to 40% (using
downconversion) or even 50% (using upconversion, vander Ende et al., 2009).
One more potential application of nanophosphors which
relies on the transparency of powder coatings is in flat
dielectric discharge lamps published recently (Klausch etal., 2012). A nanophosphor layer of YVO4:Eu with > 90%
transmittance in the visible range was tested as a prototype of a light-emitting window.
The luminescent properties of nanophosphors areaffected by environmental conditions. For example, theintensity and decay time of luminescence or ratio of intensities of certain peaks in the spectra may substantiallychange for different ambient temperatures. Such effects
further extend the list of possible applications of nanophosphor coatings, e.g. by scanning nanothermometry (Jaqueand Vetrone, 2012). The options here are almost unlimited:
if a high sensitivity in the physiological range is required,
one can use upconverting nanoparticles (Fischer et al.,2011). In the range of extreme temperatures, nanoparticlesof refractory phosphors could probably be applied even
above 1000°C because the emission of bulk thermographic
phosphors such as YAG:Dy can be measured up to 1700°C(Chambers and Clarke, 2009). The resolution of nanothermometry is approaching the size of the single nanoparticle
and allows the temperature inside the living cells to bemeasured (Vetrone et al., 2010). The small size of nanoparticles facilitates numerous further ways of their utilizationin biomedical imaging as fluorescent labels (Dosev et al.,2008), but these methods do not involve phosphor screens
and thus will not be further discussed here.

7. Conclusions
In this review, we try to present the advantages ofphosphor nanopowders for applications where continuous
phosphor layers—screens—are used. The basic optics ofphosphor screens is treated in detail so that the influenceof particle size on the screen performance can be comprehensively explained. We discuss various further effects ofparticle size which modify the quantum efficiency of luminescent devices and have implications for the manufacturing technology. The most popular methods of depositionand suggested applications of phosphor screens/coatings
are analyzed. Here, we summarize the main outcomes.

44

First of all, nanoparticles barely scatter light. Thismeans that even relatively thick coatings can be virtuallytransparent and thus, nanophosphors are preferred for
application as spectral converters in photovoltaics, andcould potentially be applied in “augmented reality” displays including, e.g. contact lens displays (Lingley et al.,2011). Vanishingly weak scattering leads also to a dramatic qualitative change in the shape of the thickness
dependence curves for the brightness of phosphor screens.
Nanophosphor layers behave similarly to non-scattering
screens (e.g. single crystalline films). It can be expectedthat their T-mode performance will only weakly dependon the thickness, both in terms of brightness and resolution,
especially when excited by strongly absorbed radiation.
Ideally, the excitation energy should be absorbed withinsome 200 nm from the exposed surface of the screen sothat the emitting volume corresponding to a single image
point could be kept smaller than the limit of diffraction. If
emitted light was not scattered, the perfect image point
could be observed from any direction, thus approaching
the diffraction-limited image resolution, irrespective ofthe total screen thickness. For X-ray applications or otherweakly absorbed radiation, the full thickness of the diffraction-limited nanophosphot screen would have to be
kept below 200 nm.
The quantum efficiency of nanophosphors is usually
lower than that of the corresponding bulk materials. Thisis explained to a large extent by the increased surface-­
to-volume ratio of the nanoparticles, which promotes thesurface quenching effects. However, it is possible to turnthis drawback into an advantage, e.g. by improving theefficiency of excitation of photoluminescence throughappropriate functionalization of the particle surface withorganic ligands. The same approach would not work withconventional coarse-grained phosphors.
A thorough characterization of the quantum efficiencyof the luminescence lifetime of nanophosphors requires
special care regarding the porosity of the deposits andrefractive index of the medium filling the pores, because
the observed luminescent properties are strongly affectedby the effective refractive index of the surroundings ofemitting ions. For example, compaction of the nanophosphor layer leads to improvement of the quantum efficiency as well as shortening of the emission decay time.
Nanophosphors offer special opportunities for processing the screens as their small particle size can facilitate
untypical deposition methods such as self-assembly, templating of colloidal crystals, and ink-jet printing. Due totheir cohesive nature, they could also be directly attached
to a substrate in a very rapid process of flame aerosol
deposition without using any adhesive or a binder. Moreover, we observed that the nanophosphor coating itself
can act as an adhesive when we investigated compactionof the deposits between two substrates.

Roman Kubrin / KONA Powder and Particle Journal No. 31 (2014) 22–52

Continuous progress in the technology of nanophosphors
will surely stimulate development of numerous new imaging applications. There is still ‘plenty of room’ spanning all
possible excitation sources and all conceivable dimensionsof the nanophosphor screens—starting from single
nanoparticles excited by X-rays, as in recently published
X-ray luminescence computed tomography (Cong et al.,2011; Carpenter et al., 2012), and ending with macroscopic
volumes excited by infrared radiation, as in solid-state 3D
displays (Downing et al., 1996).

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Author’s short biography
Roman Kubrin
Roman Kubrin graduated from the North-Caucasus State Technical University in Stavropol,
Russia, in 2002 and received his M.Sc. degree in Microelectronics and Microsystems fromthe Hamburg University of Technology (TUHH) in 2005. He later worked on the technologyof phosphors with reduced particle size at the Institute of Optical and Electronic Materials at
the TUHH, was a visiting researcher at the Particle Technology Laboratory at the Swiss
Federal Institute of Technology (ETH Zurich), and received his Ph.D. (Dr.-Ing.) in 2012. He
is currently working at the Institute of Advanced Ceramics at the TUHH on the synthesis ofceramic nanostructures for high-temperature photonics.

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KONA Powder and Particle Journal No. 31 (2014) 53–81/Doi:10.14356/kona.2014010

Review Paper

A Review of the Fire and Explosion Hazards of Particulates †Saul M. Lemkowitz 1* and Hans J. Pasman 2
1
2

Department of Chemical Engineering, Delft University of Technology, the Netherlands
Mary Kay O’Connor Process Safety Center, Department of Chemical Engineering of Texas A&M University, USA

Abstract
Particulate fires and explosions cause substantial loss of life and property. With the goal of understanding, preventing,or at least mitigating particulate fire and explosion hazards, we review basics. We distinguish between ‘hazard’ and‘risk’ and discuss the fire and explosion hazards of particulates, the many factors determining such hazards, hazard
indexes, and ways to reduce fire and explosion hazards. While our primary goal is to improve safety, we briefly discuss
how fundamental knowledge can be extracted from weapon technology based on particulate combustion. We review
the prevention of and protection against particulate explosions and discuss ongoing and future research.
Keywords: fire, explosion, (nano)particles, hazard indexes, prevention, protection, modeling

1. Introduction; hazard versus risk
Although the basics are well understood, fires and explosions of solid particulates (powders, ‘dusts’) and liquid
particulates (‘mists’), especially the former, continue tocause considerable material damage and loss of life. Particle safety therefore remains important. In discussing particulate safety we distinguish between the concepts of‘hazard’ and ‘risk’.
Hazard is the potential to create an adverse effect. Typicalhazards of particulates are fire and explosion. Hazards canbe quantified using certain substance properties, often expressed as hazard indexes, which are discussed later. Quantitative values of hazards are always relative, never absolute.
As a technical concept, risk is composed of two quantifiable factors: an adverse effect (e.g. number of deaths)
and the probability (0 to 100%) of that adverse effect occurring. If both of these factors are accurately quantified,risk can, at least in principle, have a correct absolutevalue. In practice, however, calculated risks are often subject to large uncertainties.
Particulate hazards include fire and explosion, which fora given particulate, are determined by its properties, suchas its chemical composition, particle size distribution, etc.
The risk of a given particulate is, however, not solely determined by its properties, but also by factors external tothe particulate itself, such as amounts, conditions (e.g.
†
1
2

*

Accepted: July 12, 2013
2628 BL Delft, The Netherlands
College Station, Texas 77843-3122, USA
Corresponding author:
E-mail: s.m.lemkowitz@tudelft.nl
TEL: +31-152-789-111©2014 Hosokawa Powder Technology Foundationpressure, temperature), size and strength of containment,(distance to) possible ‘targets’, good management, adherence to legislation, etc. Here we discuss particle hazards
and their reduction. The more extensive concept of particle risk falls outside the scope of this review1).

2. Fire and explosion hazards of particulates:
the basics
Fire is a (usually relatively continuous) combustion(burning) process consisting of exothermic (= heat-­
producing) chemical reactions involving a fuel and producing besides combustion products, such as water andcarbon dioxide, heat and, via flame, also light. In addition
to simply burning, an insidious form of fire called smoldering can occur when large volumes of a combustible
powder are stored, typically in a pile for an extended time
period. Through oxidation of the surface of the particulates, heat is generated, and if the rate of heat generation
exceeds the rate of heat loss (as can occur in a large pile),
the temperature within the pile can reach the ignition temperature. The result is a relatively slow burning (slow because oxygen must diffuse into the pile and reaction gases/
vapors out). Aside from generating poisonous gases (e.g.
carbon monoxide), smoldering can lead to fires and even
explosions. We mention smoldering further in Table 2(under Minimum Ignition Temperature). In the following
text, we shall focus on dust explosions.
Given the right conditions, most unoxidized materials
can burn. Most substances industrially produced (e.g. plastics, oils) or processed (e.g. wood, petroleum) are unoxidized or not fully oxidized and can therefore burn. One

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must be aware that:
ALL POWDERS THAT CAN BURN CAN ALSOEXPLODEA L L L I Q U I D S T H AT C A N B U R N C A N — A S
PARTICULATES (MISTS)—ALSO EXPLODE
No definitive, quantitative definition of the term ‘explosion’ exists. Characteristic of explosions are: “much energy”(Joules, J), “in a short time” ((fraction of) seconds(s); thus
high power (J/s)), “in a small volume” (m3, thus high power
density (J/(s m3)). Further: creation of a ‘blast’ as a pressure
wave (Fig. 1, left) or a more destructive shock wave (Fig. 1,
right), both of which can wound/kill people, destroy buildings, and create deadly high-velocity fragments. The energy
source of explosions can be physical (e.g. lightning) or
chemical (e.g. combustion). Here we discuss the explosion
hazards of particulates, and therefore we consider only explosions caused by chemical reactions, i.e. combustible
substances undergoing combustion in air or oxygen.
A reason why no unambiguous scientific definition of
explosion exists is that the most common type of chemical
explosion, the deflagration, is simply a ‘very rapid burning’. How rapid? Rapid enough to create a pressure wave
and, when it occurs in the open air and is rapid enough, an
audible signal (‘bang’). When an explosion occurs in aclosed vessel and the vessel cannot sustain the pressure, itwill produce a blast (i.e. destructive pressure or shock
wave in the surrounding air) at the moment of bursting.
A key difference between fire and explosion is that in
fire, the fuel (e.g. burning candle) and the oxidizer (air) areclearly separated. Oxygen molecules, necessary to maintainthe occurrence of combustion, reach the flame largely bydiffusion. By contrast, explosions are characterized by apre-mixing of fuel and oxidizer. Examples of increasing intimacy of pre-mixing are: a cloud of combustible dust or
mist (combustible particles suspended in air); an explosive
gaseous mixture (e.g. methane molecules and oxygen molecules in air); a solid high explosive, such as TNT (atomsof fuel (carbon and hydrogen) adjacent to atoms of oxidizer(oxygen) in the same molecule). It is this pre-mixing of fueland oxidizer, and its degree of ‘intimacy’ (most ‘intimate’ atthe atomic level, as in an explosive such as TNT), that form
the basic reason why explosions occur (much) more rapidly
than fires do, thereby resulting in a (much) higher (volumetric) rate of energy release, i.e. power (W or W/m3).
Explosions of powders, commonly called dust explosions and/or explosions of liquid particulates, called mist
explosions2), are almost always a type of explosion called
deflagration. The propagation mechanism of deflagrationis heat conduction: heat is transferred from the hot reaction
zone (the flame) to the much cooler unreacted material
ahead of the flame, thus preheating it until it reaches its ignition temperature, at which it ignites and burns (combusts).

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Behind the flame, expanding hot, oxidized gaseous products and (possibly) unburned material are present.
Characteristic of deflagrations is that the flame speed,Sf, is always subsonic (i.e. flame propagates at less than
the speed of sound, which in air at ambient conditions is
ca. 330–340 m/s). At non-turbulent conditions, deflagrative flame speeds in air at ambient conditions typicallyrange between a few m/s and about 10 m/s.
In a closed vessel filled with a flammable mixture undergoing deflagration and ignited in the center, the flame expands spherically from the vessel’s center until it reaches
the vessel’s wall. During this process, the pressure in thevessel continuously rises. Both the pressure and the rate ofpressure rise reach a maximum when the flame reaches thevessel’s wall. Characteristic of deflagrations in a closed vessel are therefore a maximum explosion pressure, Pmax, and afinite maximum rate of pressure increase, (dP/dt)max. (Inpractice, pressure is often expressed as bara (= bar absolute,
1 bara (≈ atmospheric pressure) being 105 Pa) and rate ofpressure rise expressed in bar/s.) Maximum pressure, Pmax,
and maximum rate of pressure increase, (dP/dt)max, arefound at optimal particulate concentration.
While deflagrating flames propagate less rapidly than
the speed of sound, the pressure waves produced by the
expanding flame propagate ahead of the flame at sonic velocity; i.e. 330–340 m/s. Therefore in deflagrations, theflame (subsonic velocity) and pressure waves (sonic velocity) are separated from one another, pressure waves
preceding the flame.
Only at conditions rarely existing in industrial applications can particulates explode via a mechanism other thandeflagration: the detonation. A detonation is a chemicallyreactive shock wave. A shock wave (Fig. 1, at right) is a
special case of a pressure wave. Like pressure waves,
shock waves have a maximum pressure, Pmax, but differ
from pressure waves by having an almost infinite rate ofpressure rise, dP/dt. Additionally, the flame speed of a detonation is supersonic, i.e. faster than the speed of sound.
Also in contrast to deflagrations, in which the deflagrative
flame and pressure waves are separate from one anotherand propagate at different speeds, both the detonation
flame and the shock wave propagate at the same (supersonic) speed, with the combustion occurring within theshock wave, ignited by the high temperature resulting
from the sudden compression. In general, per unit mass ofmaterial exploding (e.g. per kg), detonations are much
more devastating than deflagrations because detonationpressures are much higher (ca. 2 to 16 times greater) thanmaximum deflagration pressures and rates of pressure risenear infinite. Detonations are also much more difficult toprotect against than deflagrations, since detonations propagate supersonically.
For deflagrations occurring in a closed volume at an initial pressure not far from atmospheric (i.e. ca. 0.1 to 10

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Fig. 1Pressure wave (left) and shock wave (right) propagating in an open system (i.e. constant pressure system,
such as atmospheric).

bar), the ideal gas law expresses the maximum explosion
pressure simply and usually sufficiently accurately (< 10%error):
Pexplosion ≈ (nexplosion/ninitial) · (Texplosion/Tinitial) · Pinitial (1)where:
Pexplosion = final pressure (bara) of the explosion forgiven conditions of mixture composition, etc.
(nexplosion/ninitial) = ratio of number of gaseous moles produced by the explosion relative to the initial number, including, in both cases, the inert gas molecules; Texplosion/
Tinitial = ratio of absolute explosion temperature (K) relative to initial temperature (K).
Pinitial = initial pressure (bara).
The presence of roughly 80% inerts (nitrogen + argon)
in air causes the factor (nexplosion/ninitial) to be approximately unity. Therefore Equation 1 simplifies to:
Pexplosion ≈ (Texplosion/Tinitial) · Pinitial(2)

Under optimal conditions Pexplosion becomes the maximum possible explosion pressure Pmax. Equation 2 predicts
that the maximum possible explosion pressure of a deflagration within a closed vessel is reached when the maximum
possible temperature is obtained. For gases, this occurs to a(near) stoichiometric mixture composition. For particulates,
it is in a fuel-rich area. The maximum combustion temperature is the adiabatic flame temperature, ‘adiabatic’ referring
to ideal conditions in which no heat loss occurs. The adiabatic flame temperature is a chemical thermodynamic property; i.e. it is determined solely by the chemical propertiesof the substances involved (e.g. its heats of combustion),
mixture composition (e.g. oxygen concentration), and initial
temperature and pressure of the system.
Generally the faster the explosion process, the less time

to lose heat, and the closer adiabatic conditions are attained,
manifesting itself as a closer approach to the theoreticalmaximum adiabatic explosion temperature and thus greater rate of temperature rise, dT/dt, and pressure rise, dP/dt.
Maximum adiabatic flame temperatures for common organic powders (i.e. plastics, coal) and/or droplets of combustible liquids exploding in air (e.g. oils) typically range
between 1,500 and 3,000 K. Eq. 2, based simply on theperfect gas law, predicts that maximum explosion pressures for particulate explosions (deflagrations) of mostparticulates occurring in air in closed vessels initially atatmospheric pressure (1 bara) and ambient temperature (T= ca. 300 K) should typically be in the range of ca. 5 to 10
bara (= 4 and 9 baro (baro = bar overpressure)); in practicethis is indeed the case3).
Two parameters essential for assessing particulate explosion severity (Table 1) are maximum explosion pressure, Pmax, and maximum rate of pressure rise, (dP/dt)max,
the latter usually volume-normalized and called the KSt
factor (or simply K factor; see Table 1). As Eq. 2 shows,the maximum possible explosion pressure of deflagrations
is largely determined by the adiabatic flame temperature.
The (volume-normalized) rate of pressure rise is largely
determined by the speed of the flame, Sf. For a deflagration occurring in closed spherical equipment and ignited at
its center, the time duration of the explosion, Δt, is, by approximation, simply the radius of the sphere, Rsphere, divided by the flame speed, Sf. Therefore the faster the flame,
the quicker the explosion occurs, and thus the faster thepressure rise. Indeed, the following approximations can beeasily derived4,5,6):
dP/dt = ΔP/Δt = (Pmax − Pinitial)/(Rsphere/Sf)(3)

KSt = (dP/dt)max ∙ V1/3 ∝ Pinitial · Sf

(4)

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in which Pmax and Pinitial are, resp., the maximum explosion pressure and the initial pressure, Rsphere the radius of
the sphere in which the explosion occurs, and Sf the averaged flame speed; the symbol µ means ‘proportional to’.
More exact models are available, see e.g. Dahoe et al.6)
In the absence of turbulence, the flame speed, Sf, being
the propagation velocity of the flame front, is the vector
result of the laminar burning velocity, SU, and the expansion of the hot gas. In a closed vessel, the latter is large atfirst, when pressure is still near the initial value, and zeroat the end when maximum pressure is reached. In a tube
open at one end and closed at the other, and ignited at the
open end, as the flame propagates into the tube, the hot reaction gases flow out of the tube and thus in a direction
opposite (i.e. countercurrently) to that of the flame. In thisspecial case, and assuming laminar conditions: Sf = SU.
Like the adiabatic flame temperature, the laminar burning
velocity is determined only by substance properties, mixture composition, and initial temperature and pressure
conditions. Typical laminar burning velocities for gases/
vapors in air at stoichiometric concentrations are roughly
0.4 m/s or less; for most powders they are less, typicallyroughly 0.25 m/s. However, unlike the maximum explosion pressure which follows directly from chemical thermodynamics, the laminar burning velocity is also strongly
influenced by chemical kinetics (e.g. reaction mechanism).
Chemical kinetics is usually much more complex thanchemical thermodynamics, which is a reason why laminarburning velocities usually cannot be calculated from theory. As we discuss later, while laminar burning velocities
are typically in the 1 m/s range, through turbulence flame
speeds can accelerate enormously (to more than 600 m/s)
causing pressure increases of several bars. Explosion
behavior is determined by a complicated interplay between chemical thermodynamics, chemical kinetics, andturbulence-generated physical transfer phenomena.
Surprisingly small overpressures can cause considerable
damage. An overpressure of 0.1 baro typically shatters
glass windows and lethal effects start also at this pressure;
1.0 baro damages typical industrial equipment used forhandling powders such as silos, and totally destroys normal buildings (houses, office blocks), causing their collapse and killing those inside. Normal structures react toeven small overpressures because pressure is force/area,
e.g. overpressures of 0.1 and 1 baro correspond to forcesof, respectively, 1 ton/m2 and 10 tons/m2. Typical verticalsurfaces of buildings (e.g. windows, walls) cannot withstandsuch huge lateral forces and are thus highly vulnerable7).
In dust or mist explosions, typically deflagrations, occurring in closed systems such as silos, it is the maximum
pressure, Pmax, that largely determines the explosion’s destructiveness. For explosions occurring in open systems,
however, such as in the open air, the situation is different.
In this case it is the combination of maximum pressure,

56

Pmax, the duration of the explosion (shown as Δt in Fig. 1),
and even the form of the pressure wave (e.g. its dP/dt) that
determine explosion destructiveness. The combination of
explosion overpressure and explosion duration, i.e. the integral of the overpressure over time, is called the explosion impulse, Iexplosion:
Explosion impulse = Iexplosion = ∫Pdt

(5)

In practice, the explosion impulse can often be approximated sufficiently accurately by assuming a right triangle for the pressure or shock wave (i.e. right-hand side ofFig. 1), so that
Explosion impulse = Iexplosion = ∫Pdt ≈ ½ Pmax ∙ Δt

(6)

Once certain thresholds of over-pressure and impulse
are reached to be able to create damage, explosion destructiveness generally increases as explosion impulse increases, i.e. increasing Pmax and/or increasing explosion
duration, Δt.
We again distinguish between an explosion occurring ina closed system or in an open system and deflagrations
versus detonations. As discussed above, in a closed system(e.g. reactor or silo), an explosion—deflagration and detonation—manifests itself as a sudden pressure rise leading
to a maximum pressure. In a completely open system, forexample an explosion occurring in the open air, a typicaldeflagration generally results in a large (hot) gas volume
increase, but only in a very small pressure increase (i.e.
ΔP << 0.1 baro)8). This fact follows from the ideal gas
law, as applied to an open system (i.e. constant pressure
system, as in the atmosphere):
Vexplosion ≈ (Texplosion/Tinitial) · Vinitial(7)

By approximation, the adiabatic flame temperature andthus the explosion temperature of a given substance remains roughly the same independent of whether the system
is at a constant volume (i.e. closed system) or at constantpressure (i.e. open system); i.e. the factor (Texplosion/Tinitial)
remains approximately constant. Therefore Eq. 7 showsthat in an open system, the ratio of the volume of the explosion products (Vexplosion) to the initial unexploded volume (Vinitial) will be approximately the same as thepressure ratio obtained in a closed system, namely 5–10. It
is also because deflagrations occur relatively slowly (typical flame speeds being only about 10 m/s) that deflagrations occurring in completely open areas do not usually
produce large overpressures, but they can when occurringin congested areas.
However, detonations occurring in open air behave quite
differently. Detonation pressures of particulate clouds are
typically around 20 times the initial pressure in both open

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and closed spaces. Also, because of aerodynamic phenomena caused by supersonic flow, pressures resulting fromreflections of detonative shock waves can be much higher—
ca. 40 to even 160 times the initial pressure. Because of
these huge initial detonation pressures and even higher reflected pressures, detonation is much more destructive thandeflagration, especially in the open air.
Concerning explosion behavior in general, Abbasi et al.,20099) and Mannan, 201210) provide detailed descriptionof types and characteristics of explosions, including deflagrations and detonations.

3. Fire and explosion hazard indexes
The more energy released during combustion and thefaster this occurs, the greater the destructiveness—the severity—of the resulting fire/explosion. The less energy
needed to initiate combustion, the greater the sensitivity toignition (to fire and/or explosion), and thus the greater the
probability of a fire/explosion occurring. Fire and explosion hazards of particulates (and also of gases and vapors)
are therefore expressed in terms of severity indexes andsensitivity indexes, which Tables 1 and 2 list, along withmeaning and significance.
Assessment of the fire and explosion hazards of particulates requires knowing the values of the indexes listed inTable 1

Tables 1 and 211). We stress that with the possible exception of Pmax and SU, which in principle are invariant, values for most explosion indexes either cannot or not yet
reliably be predicted theoretically. It is essential to be awarethat the index values are influenced by testing procedures
and equipment (which have been standardized; e.g. fortemperature, pressure, turbulence, etc.). Note further thatvalues found in the literature are often not directly applicable to one’s own case, as these index values are affectedby ambient changes (e.g. temperature, pressure, turbulence)12). Additionally, indexes of a given type of particulate (e.g. grain dust) may vary greatly, depending on which
type of grain (species and sub-species), average particle
size and particle size distribution, and even weather conditions (temperature, humidity) under which the powder has
been stored, and for how long (this related to possible adsorption/absorption of moisture from air and its effect onparticle size). The literature gives a detailed discussion oftest methods and their evaluation13).
While test methods are standardized, research leads to
new insights and improved testing improvements. Gao etal., 2013, describe examples of how sensitive explosion
behavior is to variations in testing procedures14). This isalso true for an essential explosion severity index, the KSt
value, once thought to be invariant. Proust et al. show thatthe assumption that it is independent of the two standard
types of testing equipment is not generally true15).

Hazard severity indexes of particulates dispersed in air (or other oxidative gases)
Severity index

Meaning/significance/dimensions of severity index

Tendency towards detonation

Per kg of material, detonation is the most destructive explosion type. Generally, thetendency towards detonation increases with increasing mixture reactivity and decreasing
particle size.

Maximum explosion pressure,
Pmax*

For deflagrations the maximum explosion pressure is largely determined by the maximum explosion temperature (Eq. 2); (bara (absolute pressure) or baro (overpressure)).
Explosion hazard increases with greater maximum explosion pressure.

Maximum rate of pressurerise, (dP/dt)max*

Maximum rate of pressure rise, with initial conditions of 1 bara and room temperature;
usually expressed as bar/s. Usually cannot be calculated and must therefore be measured. Explosion hazard increases with greater maximum rate of pressure rise.

Maximum volume-normalized
rate of pressure rise, called KSt
factor (or simply K factor),
where: KSt = V1/3 • (dP/dt)max;(relationship often called‘cubic law’)Maximum rate of pressure rise (bar/s), normalized to a sphere of 1 m3 volume, withinitial conditions of 1 bara and room temperature. (This equation is called the ‘cubic
law’.) Since it depends on (dP/dt)max, the KSt factor must be measured; usually expressed
as bar m–1s–1. Explosion hazard increases with increasing value of Kst factor. Both the
maximum rate of pressure rise and the volume-normalized rate of pressure rise arelargely determined by the flame speed, Sf, see Eqs. 3 and 4.

Flame speed: Laminar burning
velocity, SU, m/s; (turbulent)
flame speed, Sf; m/s

Speed of flame relative to stationary observer, Sf. Laminar burning velocity, SU, is the
speed of flame relative to the unburnt gas at completely laminar (i.e. non-turbulent)conditions and stoichiometric concentration; at constant pressure this is only possible if
the expanding hot combustion gases flow away backwards countercurrently to themoving flame front. SU is typically in the range of ca. 02–0.4 m/s. Through turbulence,
the flame speed (Sf) can accelerate from a few m/s to near sonic velocities, and even tosupersonic during a deflagration-detonation transition: DDT*Note that in non-optimal composition and hence not maximum output, these quantities are indicated as Pex and (dP/dt)ex.

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Table 2

Hazard sensitivity indexes of particulates dispersed in air (or other oxidative gases)

Explosion sensitivity index

Meaning/significance/dimensions of explosion sensitivity index

Lower Flammability Limit (LFL);
also called Lower Explosion
Limit (LEL)* or Minimum
Explosive Concentration (MEC)

Lowest concentration of a substance (g/m3 or kg/m3) dispersed in air that canburn or explode. Is measured at initial conditions of 1 bara and room temperature.
Must be measured. Fire and explosion hazard increases as LEL decreases, aseven very low concentrations of particulates are still flammable and thus explosive. From here onwards all “LEL”= “LFL” and “UEL” =“UFL”.

Upper Flammability Limit (UFL);
also called Upper Explosion Limit(UEL)*

Highest concentration (g/m3 or kg/m3) of a substance dispersed in air that canburn or explode. Is measured at initial conditions of 1 bara and room temperature.
Compared to gases/vapors which have a more or less definite UEL, the UEL for
particulates has a more limited practical utility, as particulate concentrations tend
to fall due to particulate deposition. Thus a particulate whose concentration is
initially above its UEL may settle out due to gravity, causing its concentration to
decrease to below the UEL and thus enter the explosive range.

Explosive range: UFL—LFL

The range of concentration (g/m3) that is explosive. Generally the larger the
explosive range, the greater the probability of ignition, and thus the greater thefire and explosion hazard.

Lower Flash point (LFP)

Lowest temperature (°C or K) at which a substance reaches a vapor pressure
sufficient to form a flammable mixture in air (i.e. reach the LEL). LFP usuallyrelates to liquids but is also applicable to solids with high vapor pressure (e.g.
naphthalene, benzoic acid). A lower LFP increases fire and explosion hazard.

Minimum Ignition Energy (MIE)

Lowest amount of energy (mJ) of an electrical spark that can cause a particulate
dispersed in air to explode. Fire and explosion hazard usually increase as MIE
decreases, as even very weak ignition sources are then capable of causing fire
and/or explosion.

Minimum Oxygen Concentration(MOC); also called Limiting
Oxygen Concentration (LOC)

Lowest concentration of oxygen (mol- or volume-percent O2) in a gas mixture
that can support combustion. Below this oxygen concentration explosion is notpossible. The lower the MOC, the more difficult it is to produce a carrier gas inwhich fire and explosion cannot occur.)Maximum Experimental Safe Gap(MESG)The maximum gap width (mm) that allows flame propagation of a given particulate. A smaller gap width quenches the flame, thus preventing fire/explosion
propagation. The lower the MESG value, the greater the fire/explosion hazard/
risk of a given particulate.

Minimum Ignition Temperature(MIT); also sometimes called:
Minimum Auto-ignition Temperature (AIT)

Lowest temperature (T in °C or K) of a surface that can ignite a cloud of aparticulate dispersed in air to explosion. Fire and explosion hazard increases as
AIT decreases.

For powders initially dispersed in
air but that have deposited on asurface forming a surface layer:
Minimum Ignition Temperature(MIT); also often called Minimum Smoldering Temperature

Lowest temperature (T in °C or K) of a surface that can cause a dust layer of agiven depth to catch fire or at least smolder.
Fire and explosion hazard increases as surface MIT decreases,* Note that LEL and UEL are in use in European standards while LFL and UFL are basically American terms. Wording of definitiondiffers between America and Europe. In Europe the LEL is the highest concentration starting from zero that just does not explode,while in the USA the LFL is defined as the lowest concentration starting from zero at which the mixture can just explode. In practice,
however, the meaning is the same. We use the American wording.

We concentrate here on discussing how particulate
properties determine particulate hazards. Reducing hazards requires an understanding of the basics and actively
applying this understanding to designing, manufacturingand handling particulates and the design and handling of
relevant equipment.

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4. Chemical and physical factors determining
particulate hazards
4.1 Chemical factors
Particulates composed of unoxidized or not fully oxidized

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substances are usually combustible; if combustible they
can also explode. Here we divide combustible particulates into three categories: 1. Unstable reactive substances;
2. Stable reactive substances; 3. Stable flammable substances.
Unstable reactive substances are substances whose decomposition is exothermic. By themselves (e.g. no air
present), unstable substance therefore tend to spontaneously decompose, and since decomposition is exothermic,
heat is generated. When stored with insufficient cooling,
unstable substances thus tend to heat up, causing a temperature increase. Since increased temperature generally exponentially increases the chemical reaction rate (of further
decomposition, which is exothermic), a vicious cycle may
result leading to increasingly fast temperature increase, increasingly fast decomposition reaction, etc., a ‘run-away’,
ultimately causing explosion.
Examples of unstable reactive liquid substances produced in large quantities are ethylene oxide, propyleneoxide, and organic peroxides; in much smaller quantities,
concentrated hydrogen peroxide and nitroglycerine16). Examples of solid unstable substances produced in large
quantities are ammonium nitrate, TNT, and other high explosives. Most large-volume unstable powders are, however, not commonly used in industry17).
Stable reactive substances are stable in that by themselves, they do not decompose or their decomposition isendothermic (i.e. requires heat). They are reactive because
they can spontaneously burn or explode—but only whenin contact with air or water. Pyrophoric substances form acategory of stable reactive substances; these spontaneously
burn or explode when exposed to air. Examples are finely
divided unoxidized metals, such as iron and aluminum,
which spontaneously ignite when exposed to air18). Water-reactive substances which spontaneously react violently(burn, explode) in contact with water, form another categoryof stable reactive substances. Examples are the elements sodium, potassium, rubidium, and cesium and compounds
such as aluminum bromide and calcium carbide19).
The third category of substances, stable substances,consists of substances that by themselves do not spontaneously decompose and, in contact with air or water, do
not spontaneously burn or explode. Stable materials thatare non-oxidized (e.g. polyethylene powder, gasoline), or
incompletely oxidized (e.g. alcohols, grain dust) are flammable, but will only burn/explode when pre-mixed withair, and additionally are also subjected to an ignition
source (e.g. flame, spark) of sufficient energy (i.e. greaterthan the particulate’s MIE and/or MIT). It is such substances—non-oxidized or only partially oxidized substances,and thus combustible—that by far cause the greatest number of fires and explosions.
In general, explosion sensitivity and in particular explosion severity tend to increase as certain chemical thermodynamic properties, such as heat of combustion, increase(expressed in terms of mass (e.g. kJ/kg) or, even more importantly, in terms of volume (kJ/m3)). Higher heats of
combustion usually result in higher adiabatic flame temperatures and thus (Equation 2) higher maximum explosion
pressures. Since chemical reaction rates tend to increase exponentially with increasing temperature, substances withhigh adiabatic flame temperatures also tend to have higher
laminar burning velocities and flame speeds, and thus higher rates of pressure increase, (dP/dt)max. Finely divided reactive metals such as aluminum and magnesium haveparticularly high heats of combustion, thus high adiabatic
flame temperatures (up to nearly 3600 K20)), and thus highmaximum explosion pressures (typically around 12 bara)
and high KSt values (well above 300 bar m/s).

4.2 Physical factors
4.2.1 Similarities of gas/vapor and particulate explosions

Explosions of particulates (i.e. dust explosions, mist explosions) resemble gas and vapor explosions in that theyalso occur via chemical combustion; furthermore both deflagration and detonation are possible. Additionally, maximum explosion pressures of particulate explosions are
generally similar to maximum explosion pressures of gas/
vapor explosions. Thus (for deflagrations) typically 5–10
times the original pressure (Eq. 2), and for detonations
roughly 20 times the initial pressure. As previously noted,
this similarity is caused by the fact that the maximum
adiabatic flame temperatures of common combustible particulates burning in air are usually similar to those of combustible gases/vapors, i.e. usual1y 1,500 to 3,000 K.

4.2.2 Differences: combustion mechanism of particulate
explosions

The most fundamental difference between gas/vapor
explosions and particulate explosions lies in their respective explosion mechanisms. Gas/vapor explosions occur
homogeneously—within one phase, the gaseous phase.
Mechanistically, gas/vapor explosions thus occur in a premixed mixture of molecules (e.g. methane molecules andoxygen molecules) which react with one another at a molecular level.
Relative to gas/vapor explosions, the mechanism of particulate explosions is more complex. Particulate combustion occurs heterogeneously (i.e. involving at least two
distinctly different phases, a solid phase (solid (powder))and/or liquid phase (e.g. mist)) and a gaseous phase (normally air)21). The complexity of the mechanism of particulate explosions is caused by many possible steps occurring
sequentially in time:
1.	Heating of the unreacted particles due to radiantheat from the approaching flame and/or conductive/
convective heating via hot unburned gases.
2.	Heating of the particle surface and, via heat conduction,

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Fig. 2

Schematic presentation of various stages of the combustion (explosion) mechanism of burning aluminum particles: an example of the possible complexity of particulate explosion mechanisms according to Puri and Yang23).

heating of the particle interior (particle volume).
3.	Depending on the temperature reached by heating
and the volatility of the particles (e.g. melting andboiling points), either no, partial or complete vaporization of the particles before the flame reachesthem.
4.	For relatively volatile substances (e.g. diesel fuel,polyethylene), complete vaporization and subsequent ignition and combustion of the resulting vapors which have been pre-mixed into the gaseous
phase. This is essentially a gas explosion.
5.	For partially vaporized particles, ignition of the
combustible vapors formed (e.g. aluminum vapor
boiling off molten aluminum particles) followed byignition of the particles and further combustion attheir surface. For such burning particles, diffusionof oxygen to the combusting surface zone and diffusion of combustion products (e.g. carbon dioxide,water vapor) into the bulk gaseous phase.
6.	For substances of very high sublimation, melting
and/or boiling points (e.g. graphite, tungsten) combustion exclusively on the surface of the particles.
Various phase transformations depending on themelting and boiling points of oxides formed relative
to the adiabatic flame temperature of the particles22).
7.	Eventually: further combustion on the surface of thecharred remains of out-gassed organic particles (e.g.
coal). Reaction rate controlled by diffusion to, from,and within the particle.

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Mechanistically, of all these steps, gas/vapor explosions involve only step 4. Due to all this, the three-zone
burning model has been developed, Dahoe et al.6) for adust explosion.
Diffusion is the rate-determining step of the heterogeneous combustion mechanism process pictured in Fig. 2:
oxygen molecules must diffuse in from the bulk gaseous
phase to the particle surface, and reaction products fromthe burning particles must diffuse out into the bulk gaseous phase. Diffusion usually occurs much more slowly
than the rate of chemical reaction, whose rate tends to increase exponentially with temperature.
The complex mechanism of particulate combustion is
influenced by many chemical and physical parameterssuch as: chemical composition; particle size (distribution);
phase(s) of the particulates involved (solid and/or liquid);
for liquids, volatility (vapor pressure as function of temperature (e.g. boiling point)); for solids, idem, including
sublimation, melting, and boiling point; surface structure/
specific surface area; heat conductivity and heat capacity;
for substances forming liquid or solid oxides (e.g. coal,many metals, such as aluminum, magnesium, iron), melting and boiling points of the oxides; turbulence (affects
rate of mass transfer (e.g. diffusion versus mixing via convection)); flame temperature (K) and thermal intensity(kW/m2) of the combustion process (affects rate andmechanism of heat transfer).
Fig. 2 illustrates the sequential steps of a mechanism pro­
posed for the ignition and combustion process occurring

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in the explosion of aluminum particles23).
Point number 4 listed above is the simplest mechanismof the explosion of particulates: the rapid combustion (deflagration) of small liquid droplets of a volatile combustible
liquid (e.g. a mist of gasoline droplets) or cloud of small
particles of an easily volatilized combustible solid (e.g.
polyethylene) in turbulent air. Well before the flame of the
explosion reaches such particles, the explosion’s heatcompletely evaporates them into the vapor phase, and theturbulence pre-mixes the vapor molecules with the oxygen
molecules of air. The ensuing explosion thus occurs homogeneously, i.e. as a gas/vapor explosion.
More complicated, and typical of many particulate explosions, is the case of droplets of a complex organic
heavy liquid (e.g. heavy tar oil) or particles of a complex
organic solid (e.g. bituminous coal). Also in this case, particulates of organic materials undergoing fire or explosion
are first (partially) evaporated and/or (partially) pyrolyzed,
i.e. pre-heated and thus brought into the gaseous/vapor
phase as molecules, which chemically react further. Like
the previous case, this evaporation/pyrolysis (pre-heat) isbrought about by the heat of the approaching flame. The
difference with the previous case in which the combustion
process occurs completely in the gaseous/vapor phase (i.e.
homogeneously), is that here the combustion process whichbegan in the gaseous phase continues on the surface of theparticles, i.e. this combustion occurs heterogeneously.
Because of the existence of two distinct phases, gaseous/vapor and solid (or liquid), the pre-heat zone and theflame zone of particulate explosions are much thicker thanin gas explosions (cm versus mm). Furthermore, once the
combustion process is going, it may become even more
violent due to micro-mist formation as a result of the dragon liquid particulates by the faster-flowing gas24).

Fig. 44.2.3 Particle size and particle size distribution: smaller
particles = greater hazard

Reducing particle size tends to increase the particulatehazard, as expressed by both explosion severity and explosion sensitivity indexes. Figs. 325) and 4 show examplesof the huge effect of the particle size on, respectively, LEL
and MIE (explosion sensitivity); Fig. 5 shows the effect ofparticle size on maximum pressure and rate of pressure
rise (explosion severity).
Given the decisive effects of particle size on the particulate explosion hazard it is surprising that many, especiallyolder (ca. pre-2000), studies presenting explosion behavior
as a function of the particle size are neither clear as to how
the particle size is defined nor how it is measured. Alreadyin 1980, Ballal29) noted this hiatus, commenting: “Clearly,
from the point of view of fundamental combustion studies, it is the Sauter mean diameter (SMD)30), particle size

Fig. 3

Effect of mean particle diameter on Lower Explosion
Limit (LEL; here expressed as ‘Minimum Explosive
Dust Concentration’) of polyethylene powder and highand low-volatile coal (Dobashi25)).

Effect of particle size on Minimum Ignition Energy (MIE). At left26): effect of median particle size by masson the Minimum Ignition Energy (MIE) of polyethylene powder. At right: effect of particle size (Sauter
Diameter) on the MIE of three mists27). Results seem to indicate that within this size range, MIE increases
with the third power of increasing particle diameter.

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and severity.
Note that the diameter axis of Figs. 3, 4 (left), and 6 (fromDobashi, 2008) extends to (near) zero and thus to molecularsize. These figures suggest that while explosion hazards
generally strongly increase as the particle diameter decreases, below a certain diameter value, the explosion hazard increases much more slowly, or hardly at all, the limiting
value occurring at particle diameters of zero, i.e. molecular
diameter. We return to this question when discussing
nanoparticles in Section 7, Current and future research.

4.2.4 Effects of turbulence

28)

Fig. 5

Effect of median particle size by mass on explosion
severity: maximum rate of pressure rise of powderedpolyethylene as a function of particle size. (Section
4.2.4, which discusses the importance of turbulence,
explains why ethylene gas is also included here.)

distribution, and equivalence ratio that are of great importance.” Yet even in Eckhoff’s 2003 text31), presently perhaps
the best single general source on dust explosions, the Sautermean diameter is not mentioned32). Föster explicitly discusses the importance of how the particle size is measured
and expressed, including the Sauter diameter33). Experimental results that do not clearly state how the particle size isexpressed should be viewed with circumspection.
Particulates with the same average particle size often
have different particle size distributions, which can resultin significantly different particulate explosion hazards. For
example, a powder having a broad particle size distribution may exhibit high explosion sensitivity and severity,
whereas the same powder—with exactly the same chemical composition, but with a much more narrow particle
size distribution around the same median size—may (atstandard test conditions) not explode at all. The reason isthat the first powder contains a significant fine fraction
which is much more sensitive to ignition than the coarse
fraction. These fines are easily ignited, and the ensuing
combustion is sufficiently energetic to ignite the coarser
fraction. Particle size distributions should therefore not becharacterized by median size or an undefined mean size,
but by a well-chosen mean size, such as the Sauter mean
diameter. During size measurements, the size of so-called
equivalent spheres is determined which is dependent on
both particle shape and measurement principle34). We stressthat measurement results should be critically reviewed whencomparing results coming from different techniques.
Particles are often assumed to be spheres. However, ingeneral practice particles may well have irregular shapes,
resulting in a larger surface area than the corresponding
sphere with the same volume. Not surprisingly, increasing specific particle surface area (m2/g) generally increases powder explosion hazards, explosion sensitivity

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By turbulence we mean the highly irregular motion of
fluids (here gas) in which instantaneous velocities (i.e.
speed and direction of fluid motion) exhibit rapid, irregular,
and apparently random fluctuations. Superimposed on the
net velocity of the fluid are separate small pockets of fluid
called eddies or vortexes, whose size and (rotational) velocity similarly exhibit rapid, irregular, and apparently
random fluctuations. Turbulence is a prime example ofso-called complex behavior: i.e. behavior in a system inwhich a seemingly negligible change in a part of the system
can greatly change the whole system’s behavior, making
accurate and precise prediction impossible. Complex behavior is not deterministic; it is stochastic (i.e. probabilistic).
Turbulence is essential for the occurrence of particulate
explosions, being necessary to disperse particulates, mix
them with air, and keep them suspended. Additionally, turbulence has a complex effect on the dust explosion hazard.
On the one hand, increased turbulence reduces the hazard
by reducing explosion sensitivity (e.g. increasing MIT,
MIE, LEL, etc.)35). This effect is due to the fact that at thelimits of ignition (i.e. at the conditions of MIT, MIE, LEL,etc.), increased turbulence hampers ignition by dispersing
ignition energy. The physical reason for this is that increased turbulence mixes more cold fluid into thejust-barely ignitable kernel of air plus particulates, and thisquenching effect prevents ignition.
On the other hand, for an already ignited, highly
energy-­rich particle-air mixture (e.g. an already ignitedpolyethylene-air mixture in the middle of its explosive
range), increased turbulence vastly increases the hazard
by increasing explosion severity (i.e. especially by increasing flame speed, Sf, and thus (dP/dt)max and the KSt factor).
Reasons for this effect are firstly, that greater turbulence
tends to increase the surface area of the flame of a burning
mixture. Turbulent eddies cause an initially flat (two-­
dimensional) flame to transform into a (severely) ‘wrinkled’ three-dimensional flame, thus greatly increasing theflame’s surface area. Since the flame’s surface is the area
on which energy is being released (W/m2), an increase insurface area increases the total rate of energy release. Thatturbulence increases the explosion severity applies not
only for dust and mist explosions, but also for gaseousSaul M. Lemkowitz et al. / KONA Powder and Particle Journal No. 31 (2014) 53–81

explosions occurring in energy-rich mixtures, as Fig.  5
illustrates for the effect of turbulence on deflagrations of
ethylene gas. Turbulence is the mechanism that can accelerate the flame speeds of deflagrations from ca. 10 to hundreds of meters per second and even cause deflagrations totransit into detonations.
A second reason is that turbulence also tends to decrease
the slowing effect of diffusion, diffusion being a factor inherently reducing the rate of combustion of multi-phase(i.e. heterogeneous) mixtures. One can consider each particle to be enveloped in a thin laminar ‘film’ of a given
thickness, through which diffusion takes place 36). Increased turbulence reduces the thickness of this laminar
film, thereby reducing the time it takes for diffusion
through the film to occur. When diffusion is the rate-determining step, faster diffusion speeds up the rate of energy
release, thus increasing the severity of the explosion.
(However, at a high turbulence intensity, this effect can becountered by flame quenching and extinction due to a highcooling rate.)
Through turbulence, a particulate explosion can become
self-feeding; i.e. a small explosion starting somewhere ina plant grows due to the settled/deposited dust (or a liquidfilm) on floors and machinery being stirred up by the pressure waves and turbulence generated before the flame arrives. Explosions can in such cases propagate from one
plant or installation to another—with devastating effects.
Many disastrous dust explosions of this kind—in which a
primary explosion generates and ignites one or more secondary explosions—are known37). Dust deposits of only a
few millimeters thickness or less, usually caused by badhouse-keeping38) (and thus ultimately poor management),
are sufficient to raise dust concentrations into the explosive range (i.e. above the LEL).
Additionally, inside a process installation a small, incipient explosion can, as it propagates through piping connecting vessels within the installation, generate increasing
turbulence. It is this self-generated turbulence that cancause flame speeds to accelerate dramatically. In the extreme case, flame acceleration accelerates the flame speed
from values typical of a deflagration, i.e. ca. 10 m/s, to supersonic velocities: a detonation. This feared phenomenon
is called a deflagration-to-detonation-transition: DDT39).
Another dangerous phenomenon associated with turbulence as an explosion propagates between interconnectedvessels is pressure piling40). Effects pressure piling causes
in a secondary vessel are pressure increase, temperaturerise (due to this compression), turbulence caused by theflow into the secondary vessel from a primary vessel, andpossibly also flame-jet ignition as the explosion propagates from the primary to the secondary vessel. These factors can result in vastly increased explosion pressures andrates of pressure rise in secondary vessels. It is for thesereasons that the propagation of incipient explosions must

be prevented (e.g. via compartmentalization; see Table 4).
Theoretically, turbulent flow can be analytically predicted using Newton’s Laws of motion applied three-­dimensionally (i.e. Navier-Stokes equations). In practice,
however, turbulence is ‘too complex’ for analytical solution. This is frustrating, considering the importance of predicting the behavior of turbulent systems, such as theweather, fluid flow of all types (e.g. around automobiles,
ships, aircraft), combustion of fuel in engines (e.g. diesels,
jet turbines), and explosive combustion. The great breakthrough in calculating turbulent behavior was the development of Computational Fluid Dynamics (CFD), madepossible by the advent of (super-)computers. A great breakthrough in directly measuring turbulence before and during
particle explosions, e.g. in testing equipment, was the development and application of Laser Doppler Anemometry41,42).
Computational Fluid Dynamics (CFD) has led to breakthroughs in modeling and thus predicting gas/vapor explosions, and more recently, particulate explosions. We returnto CFD in Section 7, Current and future research.

4.3 Combined chemical and physical effects
4.3.1 Effects of humidity

Chemical composition determines not only combustibility, but also whether and to what degree a particulate
is hydrophilic (‘water-loving’) or hydrophobic (‘water-­hating’). Hydrophilic powders tend to adsorb/absorb
air moisture, thus forming a layer of water molecules on
the particle surface. This layer causes particles to stick together (agglomerate), which can strongly increase thevirtual particle size and thus reduce the specific surface area.
The specific surface area plays an important role in chemical kinetics and adsorption/absorption kinetics and therefore strongly influences the explosion hazard. In particular
the Minimum Ignition Energy of hydrophilic powders isoften strongly reduced by reducing the concentration ofadsorbed/absorbed water. In particular, MIE values may
decrease by a factor of 100 or even more43).
Additionally, a layer of adsorbed water tends to increase
the electrical conductivity of powders, thereby reducing thetendency to generate and retain a static electrical charge,
thus reducing the hazard of ignition by static electricity44).

4.3.2 Upper explosion limit, explosive range, volumetric
explosion energy
Mixtures of combustible gases and vapors with air generally have sharply defined explosion limits (LEL andUEL values) and thus sharply defined explosive ranges(UEL – LEL). Additionally, the UEL values of gases andvapors at ambient pressure and temperature are typicallyroughly two times the stoichiometric concentration.
By contrast, particulates have less sharply delineatedexplosion limits; in particular, the upper explosion limits

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Fig. 6 Comparison of explosion limits for a gas explosion (methane) and a dust explosion (polyethylene powder) in air.
Stoichiometric concentration of methane = 67.8 g/m3
(vertical striped line); stoichiometric concentration ofpolyethylene in air = 87.1 g/m3 (solid vertical line).

(UELs) of particulates are poorly defined for two reasons.
Firstly, a particulate-air mixture initially above the
UEL-concentration will, through deposition caused bygravity, eventually enter the explosive range. For thisreason the UEL value for a particulate usually has little
practical significance and can even be dangerous by engendering false confidence.
Secondly, while a gas/vapor explosion takes place between molecules, a particulate explosion involves the surface of the particles. As the mass concentration of thepowder in a powder-air mixture increases to (far) above
the theoretical (mass-based) stoichiometric concentration,
the powder particles simply burn to a thinner depth. Thus,
while gas/vapor explosions generally show a sharp maximum explosion severity at roughly the stoichiometric concentration, and explosion severities fall sharply past thisconcentration, the dust explosion severity is generally
reached (far) above the (mass-based) stoichiometric concentration and, additionally, it falls off slowly (often far)above the stoichiometric concentration. Fig. 6 illustrates
this effect graphically, contrasting the sharply defined explosion severity of methane in air compared with the muchflatter behavior of polyethylene powder in air, as a function of concentration45).
Energy content increases with substance amount. Common gases typically have a density of roughly 1 kg/m3 (atSTP). Solids and liquids generally have a much higher
density, typically 1,000 kg/m3 or more, thus at least about
1,000 greater than gases. Therefore a typical powder-air
mixture often contains more energy per unit volume (i.e.
volumetric energy content, J/m3) than a gaseous mixture.
This greater amount of energy manifests itself in that a
particulate explosion lasts longer in time than gas explosions. Important to note is that, for these reasons, explosions of aerosols (dusts, mists) also tend to cause more fire64

Fig. 7 Hybrid mixture: Effect of adding flammable gas (propane). Minimum Ignition Energies (MIEs) of various
powders.

damage than explosions of gases.
Furthermore, since particulate explosions can occur atconcentrations far above stoichiometric concentrations, aparticulate explosion occurring in and rupturing closed
equipment within a factory can emit large quantities of hot
unburned material. Upon contact with air this hot unburned material can explode, resulting in a second explosion occurring inside the factory.

4.4 Hybrid mixtures
Hybrid mixtures are mixtures of combustible solid particles and air containing a combustible gas and/or vapor.
Minimum ignition energies (MIEs) of typical flammablegas/vapor mixtures (e.g. methane in air, gasoline vapor inair), which are mixtures of individual molecules, are oftenvery low (e.g. MIE values typically between 0.1 to 1 mJ;
by comparison a human body can generate a static electric
spark of 10 mJ); such low MIE values of gases/vapors
lead to a large ignition hazard. Many common powders,
however, have MIEs at least an order of magnitude higher
than flammable gases/vapors, i.e. above 10 mJ. The insidious hazard of hybrid mixtures, first clearly discussed by
Bartknecht already in 198046) and illustrated in Figs. 747)
and 848), is that the presence of even low concentrations offlammable gases/vapors (e.g. originating from traces of
evaporated solvents) can greatly increase the explosion
sensitivity by reducing LEL values and drastically reducing
MIE values; idem for the explosion severity, in particular
the rate of pressure rise. Mixtures of combustible solid
particles and air containing a combustible gas and/or vapor(hybrid mixtures) thus combine the worst hazards of dust
explosions and gas explosions: the high explosion sensitivity of gas explosions, the high energy density of dust
explosions, the high rate of pressure rise of gas/vapor

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Fig. 8Hybrid mixture: Effect of adding flammable gas (methane) on Lower Explosion Limit (LEL), maximum
explosion pressure (Pmax) and maximum rate of pressurerise, (dP/dt)max, of PVC-powder.

explosions, and explosion pressures as high as those ofgas/vapor explosions.
We discuss recent research on hybrid explosions in Section 7, Current and Future Research.

5. Knowledge of the explosion behavior ofparticulates applied in fuel air explosive(FAE) weapon technology
5.1 General
So far we have reviewed scientific and technologicalknowledge with the goal of identifying and reducing particulate fire and explosion hazards. But such science canTable 3also be used for military goals, and additionally, understanding the technology can lead to safety improvements.
As noted, the most powerful explosions are detonations.
Detonations of explosive solids such as TNT occur at supersonic velocities (flame speeds between 5,000 to almost
10,000 m/s) and produce extraordinarily high maximum
explosion pressures (between 200,000 to nearly 500,000baro). However, from a military standpoint, conventional
high-explosives such as TNT have some inherent limitations. Firstly, while the maximum explosion pressuresgenerated are enormous, they decrease rapidly with distance, since the TNT explosion is by approximation a‘point source’. Thus the destructive effect is restricted to a
relatively small area and volume. Secondly, the extraordinarily high pressures developed are actually much toohigh for a number of military purposes. Thirdly, conventional explosives such as TNT contain oxygen within theirmolecule. This oxygen is necessary to sustain the detonation process, but it also makes up a substantial part of theweight of the explosive. But oxygen is freely available inair. By using atmospheric oxygen, rather than having oxygen within the explosive itself, the destructive effect of agiven mass of explosive can be substantially increased.
From a military standpoint, a useful explosive device(e.g. bomb) would have the following properties (Table 3).
Perhaps ironically, and partly as a result of investigating accidental industrial explosions such as the devastating vapor cloud explosion at Flixborough (UK) in 1974,
with the goal of preventing such explosions and increasing industrial safety, scientific discoveries were madethat facilitated the creation and further development of
weapons meeting all the above-mentioned specifications;these are called Fuel-Air Explosives (FAEs)49).
A typical fuel-air explosive (FAE) such as a bomb, consists of a container of fuel and two separate explosive
charges. After the bomb is dropped the first explosive

Possible general requirements for a particle-based bomb as shown feasible in open sources

1.

Generate a maximum pressure wave of approximately 15 to 20 bar overpressure, as such pressures are 100% lethal
to humans, obliterate conventional buildings, destroy communication antennae, and severely damage and/or overturn vehicles.

2.

Generate this overpressure over a large surface area and large pie-like volume. Generate and maintain this pressure
for a sufficiently long time duration (Δt), giving it more time to do damage (i.e. by creating a larger explosion
impulse, ∫Pdt (Eqs. 5–6)). Additionally, create a flame with the highest possible temperature to generate morelethality and damage.

3.

Produce the above-mentioned effects with a device of minimum volume and weight (e.g. by using the oxygen
available in air).

4.

When used within an enclosed area such as bunkers or caves, consume the oxygen in the air, and by the nature of
the combustion process sustaining the explosion, generate toxic gases such as carbon monoxide to poison those notkilled by blast. Additionally, due to the rapid cooling of the hot explosion gases within the enclosed area, subsequently create a significant underpressure that can fatally damage lungs (i.e. create a partial vacuum, also called
rarefaction).

5.

Be cheap to produce and safe to store and to transport.

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charge bursts open the container and disperses the fuelinto a cloud of fine particulates (droplets and/or dust) thatmix with atmospheric oxygen. This cloud flows aroundobjects and penetrates into structures. The second chargethen detonates the entire fuel-air cloud50), which has a substantial volume and is thus certainly not a ‘point source’.
The detonation, which occurs throughout the whole cloud,generates a blast wave of ca. 20 bar overpressure within
the cloud which completely destroys unreinforced buildings and kills 100% of exposed people (e.g. soldiers in
foxholes). Outside the fuel-air cloud the explosion blast
wave attenuates, but since overpressures of even sometenths of a bar can cause severe damage, the ‘death­-anddestruction diameter’ of an FAE (i.e. inside and outside
the fuel-air cloud) can be very large relative to normalbombs; e.g., for a 500 kg bomb ca. 100 m, thus an areaof ca. 8,000 square meters51). For obtaining a blast andflame, FAEs are the most powerful non-nuclear bombs. It
was once thought that they might even be used to simulate
nuclear explosions52). (We add, however, that in addition
to offensive use, FAEs are important defensively. Throughtheir low detonation pressure and long explosion duration,
FAEs are used to clear minefields, thus obviating the needfor manual clearance.)
A problem with FAEs is that their initiation to detonation is quite difficult, requiring an ignition energy typicallyup to a million times greater than that needed to ignite a
deflagration53). Additionally, to ensure complete detonation in the entire fuel-air cloud, the particle concentrationmust vary little around an optimum value. (This fact canalso help to increase civil safety by designing measuresthat reduce the chance of accidental detonations.)
The nature of FAEs is such that up-to-date information
continually appears in (in the authors’ opinion) relatively
reliable websites such as Wikipedia, IMAS (International
Mine Action Standards), and Global Security.

6. Preventing and mitigating particulate explosion
hazards
An abundance of literature exists describing course,
prevention and mitigation of particulate explosions, including not only scientific and technological aspects, butalso relevant standards, norms, legislation, and proper
management (e.g. see Appendix). Here we divide prevention/mitigation into four categories:
1. Good management
2. Reducing the hazard of the particulate itself
3.	Reducing the hazard of the system producing theparticulate
4. Combinations of Points 1 to 3

6.1 Reducing hazard through good management
It is now known that poor management is the root causeof the overwhelming majority of industrial fires and explosions, as shown by countless investigations54). Not the lackof knowledge, but unawareness or not properly applying
it. It is for this reason that comprehensive safety management systems have been developed over the last three
decades. Indeed, Points 2 to 4 above follow from goodmanagement. It is beyond our scope to discuss this extensive topic; here we merely cite two representative publications55) and discuss this point a bit further in 6.4.

6.2 Reducing the hazard of the particulate itself
Most technical methods to reduce particulate hazards
follow logically from the basics described in previous sections, being simply negations of causative or exacerbating
factors; e.g. since smaller particles increase the hazard, increase the size of particles. Most of these methods are thus
‘scientifically trivial’—but nevertheless effective: e.g. “increasing particle size”, “increasing particle humidity”,“preventing hybrid mixtures”, etc. Such measures havebeen known for decades and are described in detail in literature (e.g. see Appendix).

6.3 Reducing the hazard by improving the system
in which the particulate is produced, stored,transported
The hazard is reduced by firstly preventing explosions
from occurring and secondly, mitigating their effects
should an explosion nevertheless occur. Prevention isachieved largely by, where possible, eliminating sourcesof fuel (e.g. practicing ‘good housekeeping’) and eliminating possible ignition sources such as (static) electrical andmechanical sparks and hot spots56). The indexes listed inTable 2, which relate to ignition, logically suggest possible preventive measures: e.g. keeping particulate concentrations below LEL; through inertization, reducing oxygen
concentrations ideally to below LOC; maintaining all surface temperatures below MIT; etc. Protective measures relate to hindering the propagation of an explosion. We
briefly summarize a number of these measures in Table 4.
Our discussion is necessarily superficial; in addition to extensive description in textbooks (see Appendix), excellent
reviews of prevention and mitigation also exist57).

6.4 Combinations of Points 1 to 3: Inherently Safer
Design (ISD), Layers of Defense Approach(LOPA), ‘Holistic’ Approaches—componentsof ‘Loss Prevention’Over the past decades, new design methodologies called66

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Table 4

Some important mitigative measures
Type

Compartmentalization

Working principle
Prevent an explosion occurring in one part of the system from propagating into otherparts of the system; e.g. by placing quick-acting valves in interconnecting piping

Explosion-proof construction Build equipment strong enough to withstand maximum explosion pressure
Explosion suppression

Rapidly disperse materials that stop explosion at very early stage

Explosion venting

Provide system with weak spots that burst open to the atmosphere at low overpressuresoccurring at the beginning stage of deflagration, thus preventing development of maximum explosion pressure

Inherently Safer Design (ISD) and Layers of Protection
Analysis (LOPA) have been developed that systematically
avoid or at least mitigate chemical hazards like fire andexplosion. Inherently Safer Design (ISD) is based on the
logical negation of basic factors causing and exacerbatinga hazard58). ISD uses keywords such as: Reduce, Substitute, Attenuate, and Simplify. Layers of Protection Analysis, whose starting point in the ideal case is Inherently Safer
Design, is based on designing successive rings of ‘protective
layers’ (“Layers of Protection”) around a process59). Eachlayer offers protection and/or mitigation in the event ofdisturbances and failure of a preceding layer. ISD and
LOPA are examples of the systematic, comprehensive, andscience-based discipline known as Loss Prevention60),
which has been developing since the 1980s. The ISD- andLOPA-concepts date from approximately the end of the20th century, but apparently only during this last decade
have they been specifically applied to controlling dust explosion hazards61) and, most recently, explosion hazards ofnano-particles62). Incorporating the ISD and LOPA design
methodologies into computer-based ‘Expert Systems’,
which also include explosion indexes (Tables 1 and 2) forthe materials used and produced, represents a formidable
new tools for achieving safety through basic process design63). Perhaps even more promising are ‘holistic’ approaches to process safety. These include systematic
technical approaches (e.g. ISD, LOPA, Quantitative Risk
Analysis (QRA)), but expand considerably to include broadsocial-economic factors affecting top management such as
the ‘emergent’ (i.e. ‘complex’) nature of society. A key goal
is to find a proper balance between the pressure to increase
profitability and (the costs of) adequate safety, and to provide top management with effective tools64).

7. Current and future research
7.1 General
A plethora of knowledge already exists concerning thefire and explosion hazards of particulates and their effective
control. Once again we emphasize that awareness, dissemi-

nation, and proper application of existing knowledge, i.e.
the key responsibilities of management, are sufficient toprevent the overwhelming majority of industrial incidents.
Nevertheless research continues, with interesting and useful results. Particulate explosion falls within the much larger
field of particle combustion, which is of major importancebecause a significant part of total world energy generation
occurs through particulate combustion (e.g. diesels, jet engines, coal-based electric power generation). Up-to-datereviews of state-of-the-art particle combustion science andtechnology of this type therefore regularly appear in textbooks65). Combustion science also relates to achieving advanced (military) goals such as powering hypersonicaircraft using detonation-based engines, possibly fueled byaluminum nanoparticles66).
Here we concentrate on the particulate research relating
to industrial hazards. Many excellent reviews of particulate fire and explosion hazards have appeared over theyears67). A general line of progress in research has been
firstly, an increasing knowledge and insight into particulate explosion behavior and explosion mechanisms andbetter quantitative description and prediction. Secondly,
stimulated through further development of CFD, bettermodeling, enabling more accurate prediction of fire andexplosion ignition and propagation and the design of morecost-effective preventive and protective measures. Below
we summarize some interesting areas in which progress
and, for particulate explosion modeling, certain breakthroughs have been made.
We divide our discussion into particles themselves(nanoparticles and hybrid mixtures) and systems containing particles.

7.2 Effects of reducing particle size towards thesize of molecules: Nanoparticles
Spherical nanoparticles are defined as those having a
diameter of less than 100 nm (0.1 micron); non-spherical
nanoparticles are defined as those having at least two dimensions smaller than 100 nm. Due to their special properties, the production and use of nanoparticles is strongly
increasing. Interest in health and safety aspects of67

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nanoparticulates has grown recently because of their ability to penetrate into the deepest parts of the lung68) andtheir suspected heightened explosion hazards69).
In discussing the effects of reduced particle size it isuseful to distinguish between different groups of materials
that may exist in the nano range such as:
1.	Natural organic materials (e.g. grain, linen, sugar,
etc.)
2.	Synthetic organic materials (e.g. plastics, pigments,
pharmaceuticals, etc.)
3.	Carbon, coal and peat
4.	Stable reactive substances such as reactive metals(e.g. Al, Mg, Si, Ti, etc)
5.	Unstable reactive substances such as high explosives (e.g. TNT, HMX, CL-20)
6.	Unstable mixtures composed of different powdered
substances (e.g. gunpowder)(Note that ‘Stable reactive substances’ and ‘Unstable
reactive substances’ are defined in Section 4.1.)
In a thorough review, Eckhoff70) compares the explosion
behavior of nano- versus micron-sized particles and presents a number of general conclusions:
1.	For all commonly used powders (Groups 1 to 4),
the explosion hazards, as expressed by the explosion
severity (our Table 1) and explosion sensitivity indexes (our Table 2), increase strongly as the particle size decreases from mm values to the lower endof the micron range (roughly 1 to 10 microns (seeour Figs. 3–5).
2.	Nearly all experimental data on nanoparticle explosion hazards are available only in the upper-end of
the nano range, i.e. around 100 nm or not much
lower (usually >> 10 nm; lowest values found were
15 nm71)).
3.	Explosion sensitivity, particularly as expressed in
the MIE value, continues to increase as particle size
decreases down into the (higher end) of the nanorange; i.e. MIE values continue to decrease with decreasing particle size into the nano range.
4.	By contrast, explosion severity, as expressed byPmax- and KSt values, appears not to increase as particle size decreases from the micron range into the(high) nano range.
Point 1 above follows logically from the fact that specificsurface area increases as particle size decreases (e.g. wooden logs do not explode, but finely powdered sawdust does;
the finer the sawdust, the greater the explosion hazard).
Concerning Points 2 and 4 above, Eckhoff notes inherent
physics-based limitations in creating true nanoparticles anddispersing them into stable clouds of true nanoparticles72).
Coagulative forces such as van der Waals’ forces increasesignificantly as particle size decreases from the micron
into the nanometer range. Thus nanoparticles inherently
tend to coagulate into conglomerates of multi-particles.

68

Also due to strong coagulative forces, it is difficult todisperse nanoparticles as nanoparticles, and even once
dispersed into a cloud, true nanoparticles will, throughcollisions, tend to rapidly (e.g. before ignition occurs) coagulate into larger, micron-sized conglomerate particles.
With this explanation in mind, Eckhoff explains the apparent anomaly of Point 3 (explosion sensitivity, expressed
as MID) by theorizing that the electric spark, inherent to
the MIE testing procedure, may be powerful enough tocause eventually formed conglomerates to break up intotrue nanoparticles.
Concerning Group 4 powders mentioned above (Stable
reactive metals such as aluminum), Eckhoff briefly mentions another factor affecting explosion severity and sensitivity: the degree to which reactive metal particles arecovered with an oxide layer. An oxide layer is completely
non-reactive and is a heat sink, thus tending to inert thepowder. Obviously the finer the particles, the greater the
relative mass of even a thin oxide layer and thus the greater the reduction of explosion hazard73). This phenomenon
was widely known already decades ago, since the production of fine powders of reactive metals.
Nanoparticles of reactive metals form a special case as
more explosion research has been done on them than on
any other type of nano-particulates. This is due to theirwidespread (military) use—past, present, and future—ascomponents of pyrotechnics, rocket propellants, and (fuel-­air) explosives. It has long been known, for example, that
if sufficiently fine and sufficiently pure (e.g. free of oxidefilm), many metals are so reactive that if suddenly dispersed
in air they will spontaneously—without any external ignition source—burn/explode; i.e. they are pyrophoric74).
Being pyrophoric, their MIE is zero and their MIT isbelow ambient temperature. Whether pyrophoricity occurs
in practice depends on a heat balance involving factors
like exothermicity of the oxidation reaction, particle size,
thickness of oxide layer, and boiling points of metal andoxide relative to adiabatic flame temperature75,76). The pyrophoric nature of fine powders of reactive metal, especially those in the nano range, complicates testing procedures
to determine explosion indexes, requiring modification ofstandard dust explosion testing equipment and proceduresfor explosion severity77) and explosion sensitivity78).
Experimental measurements, complemented with theoretical studies, suggest some very interesting particle combustion and explosion phenomena unique to sub-micron/nano-sized particles. The following figures illustrate someof this behavior.
For powders that do not readily volatilize such as carbon and metals with high melting points, Fig. 9 illustrates
the change in reaction mechanism as the particle size decreases from the low mm range to below roughly about
1–10 μm: the combustion mechanism changes from being
diffusion-controlled in the region of large particles to being

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Fig. 9 Combustion time (ms) versus particle diameter (micron)of carbon79).

chemical-kinetically controlled in the region of increasingly
smaller particles80). As previously noted in Section 4.2.2,
gas/vapor explosions, which occur between molecules, arechemical-kinetically controlled and dust explosions oflarge particles are diffusion-controlled. But as particle size
decreases and begins to approach that of gas molecules, it
is to be expected that powder explosions will progressively become more like gas/vapor explosions.
Huang et al. (Fig. 10)81) also illustrate the transition
from diffusion control to chemical-kinetic control of thereaction rate as particle size decreases from the micron
range into the nanometer range (Bidabadi et al. present
nearly identical results and conclusions82).) As alreadynoted, a fundamental property of the flame of a given
mixture of a combustible substance in air at given conditions is its laminar burning velocity, SU. Also as mentioned
before, hydrocarbon fuels in air exhibit laminar burning
velocities of tens of centimeters per second or somewhat
higher. Highly reactive combustible gases such as hydrogen and acetylene have laminar burning velocities in air
typically in the meters-per-second range. Reactive combustible particulates in the micron range have laminarburning velocities in air that are typically approximately afactor of ten smaller. Fig. 10 illustrates the effect of decreasing particle size on the laminar burning velocity (SU)of powdered aluminum in air, with extrapolation into thenanometer range and even to the particle size range ofmolecules. Huang et al.81) thus predict that as the particle
size decreases and eventually reaches the molecular range,
the laminar burning velocities of aluminum, a highly reactive metal with a very high adiabatic flame temperature,
will be quite similar to those of reactive gases and vapors(i.e. ca. 5 m/s for aluminum versus 3 m/s for hydrogen).
This same line of reasoning—nanosized particles in thehomogeneous, chemical-kinetically controlled regime, andmicron-sized particles in the heterogeneous, diffusion controlled regime—can also be applied to the ignition of fineFig. 10

Effect of decreasing particle size on laminar burning
velocity (SU) of reactive (i.e. non-pre-oxidized; here
called ‘nascent’) aluminum particles81).

Fig. 11

Effect of reduction of the particle diameter on the Minimum Ignition Energy (MIE) of powdered aluminum(chemical-kinetically controlled at small particle sizes
and diffusion controlled at larger sizes)83).

metallic particles (i.e. their MIE and MIT), as is shown in
Fig. 11 for the Minimum Ignition Energy (MIE) of aluminum particles83). That is: As the particle diameter approaches the molecular diameter, the MIE values of particulates
approach those of gases/vapors, i.e. for reactive metal powders, MIE values below 1 mJ. (And, as noted above, veryfine powders of non-oxidized stable reactive metals are pyrophoric: MIE = 0; MIT below ambient temperature.)
Concerning Group 5 powders (unstable substances suchas high explosives), it appears that reducing particle size
from the micro to the nano range increases (military) usefulness by increasing explosive power while reducing
sensitivity to ignition (the latter as expressed by impact
sensitivity). This was found for one of the most powerful
explosives known, CL-2084), as well as the explosives
TATB and HMX85) (all these explosives are more powerful

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than TNT).
Concerning Group 6 powders (unstable mixtures suchas gunpowder), it is reported that, at least for flash powder
used in fireworks, reducing particle size from the micro tothe (upper) nano range increases explosive power but incontrast to results reported above for a number of high explosives, also increases ignition sensitivity (as expressedby impact sensitivity)86).
We conclude this section by commenting that more research needs to be done in the lower regions of nano-sizedparticulates (i.e. << 100 nm) to be certain about the explosion behavior of particles closely approaching molecular size. It would seem reasonable to these authors (SMLand HJP) to assume for the time being that for such particles, their explosion indexes as expressed in Tables 1 and
2 will increasingly resemble those of gases/vapors with asimilar basic molecular structure, as chemical kinetics
starts to control the rate of overall reaction. But this must
be experimentally verified, because pyrolysis and diffusion rates in the case of organic dusts and the breachingof oxidized surfaces of metal particles can stretch reaction
times. Such effects will mitigate explosion index values.

7.3 Hybrid mixtures
Recent research largely validates but also complements
Bartknecht’s basic findings (e.g. Figs. 7–8) by providing
additional information87) and a more fundamental description of relevant explosion phenomena, linking hybrid mixture behavior with modern safety analysis methods,
modeling hybrid explosion behavior, and even modifying
industrial standards. Dufaud et al.88) comment on how better knowledge of hybrid explosion behavior is used tomodify an important industrial norm (NFPA 68; venting of
deflagrations). Dufaud et al.89) study effects of pyrolysis
gases/vapors evolving during dust explosions of organic
powders and develop a predictive model. Garcia-Agreda
et al.90) develop an insightful way of graphically presenting hybrid explosion behavior in terms of measured KSt
values and 5 combustion regimes: non-explosive, dust-­
driven, gas/vapour-driven, gas-gas/vapour-driven, and‘synergistically’ driven. Denkevits performed unique experiments, namely combining a highly reactive gas, hydrogen, with a much less reactive substance (tungsten)91),
or a very much less reactive element, pure carbon (graphite)92); both pure carbon and tungsten are, for practical
purposes, non-volatile. Previous researchers had combined
flammable gases/vapors with powders that volatilize (i.e.
most organic materials). Especially interesting are the results with graphite, which show that a hybrid explosion witha highly reactive substance (hydrogen) and a combustible
substance of low reactivity (e.g. graphite) can occur in two
distinct stages: initial fast explosion of the reactive substance, followed by a second, relatively slow explosion of70

the inactive substance, ignited by the initial explosion. On
the subject of approaching hybrid explosion hazards withnew methods, using polyethylene production as an example,
Abuswer et al.93) combine controlling the hazard (and risk)of hybrid dust explosions with Inherent Safer Design (ISD,
described in Section 6.3), Quantitative Risk Analysis (QRA,
e.g. employing Fault Tree Analysis), and CFD modelingusing DESC (described below in Section 7.5).

7.4 Predicting values of particulate hazard severity(Table 1) and sensitivity (Table 2) indexes
Reyes et al. predict dust severity indexes (Pmax and KSt
value) using Quantitative Structure Property Relations(QSPRs) relations94). Such an approach (also commonly
called Quantitative Structure Activity Relations: QSARs)
is used with increasing success to predict a whole host of
the physical, chemical, and even physiological-medical (e.g.
anti-carcinogenic) effects of substances, thus obviating, orat least greatly reducing, the need for (expensive) testing.
We caution, however, that even Pmax, which theoretically isa chemical thermodynamic entity and thus invariant, candepend strongly on how it is measured (e.g. degree of turbulence)95). The reason is that at higher heat loss, maximum
temperatures are lower, resulting in slower kinetics, which
in turn hampers reaching the equilibrium reaction productcomposition and thus the adiabatic flame temperature.

7.5 Modeling the propagation of particulate
explosions using computational fluid
dynamics (CFD)
Particle technology engineers are used to applying Discrete Element Modeling (DEM) when they want to study
particle flow in various situations. As regards dust dispersion, even a combination of DEM and Computational
Fluid Dynamics (CFD) proves very useful, as shown byHilton and Cleary96). However, so far computer capabilities fall short of depicting model heating, gasification andcombustion around discrete elements; only a code basedon differencing a continuum is capable of modeling flow
and flame (reactive gas dynamics). Norwegian Gexcon, aspin-off of Bergen University, obtained over a period of atleast 20 years considerable experience in modeling vapor
cloud explosions by developing the CFD-code FLACS(Flame Acceleration Simulator). For instance, applying
this code, Gexcon was able to successfully simulate thesurprisingly high pressures which occurred in the explosion of a gasoline components cloud resulting from an
overflowing storage tank at the Buncefield site near London in 200597). The FLACS code simulates the flame
speed-overpressure dynamics of an exploding cloud bysolving the Navier-Stokes conservation flow equations, thegas equation of state, a sub-grid scale turbulence modelSaul M. Lemkowitz et al. / KONA Powder and Particle Journal No. 31 (2014) 53–81

and the combustion energy release rate. The latter is dependent on the turbulent intensity which an advancing
flame faces. This turbulence is generated by the flow
ahead of the flame, pushed forward by the expansion of
hot gases behind the front and the interaction and frictionof the flow with obstacles and congestion in the environment. This phenomenon of turbulence in the unburnt gas
by which the expanding hot reaction products accelerates
the flame is called a feedback mechanism. The results ofruns of the code have been extensively validated against
explosion test results at various scales.
Already in 1996, Van Wingerden98) of Gexcon clearly
listed the necessity and possibility of applying Computational Fluid Dynamics (CFD) for creating an overall modelof propagating dust explosions within a contained spacesuch as a process plant, and using this model to optimallydesign safeguarding measures. In analogy to vapor cloud
explosion modeling, the Norwegian-based Gexcon company
initiated in 2003 a multi-partner European research project
DESC, an acronym which stands for Dust Explosion Simulation Code99). Additional problems with dust explosions
are, however, that flame propagation occurs with an evenmore complex mechanism than in gas explosions and thatthe flame in a dust explosion is also “feeding itself” bywhirling up settled dust. This dust dispersion part is still not
fully developed and further experimental work is being carried out in shock tubes to investigate all relevant parameters, with the aim of being able to more reliably model thedust concentration and turbulence intensity into which the
explosive flame propagates. More advanced codes apply
large-eddy simulation but are limited with respect to thespace dimensions they can cover. Nevertheless, comparedto the capabilities of CFD to successfully model gas explosion behavior, at this moment CFD modeling for particulate
explosions is still in its infancy. In his 2010 lecture, Skjoldpresents a detailed and frank evaluation of the state of CFD
for modeling dust explosions100), concluding that: “Thereremains much to be done before dust explosions are adequately understood”. Meanwhile, Castellanos et al.101) haverecently published an interesting application of DESC in amodel calculation of a vented dust explosion with and without a duct and comparing it with experimental findings andcalculation results based on guidelines and standards andempirical correlations.
As regards flame propagation in a dust cloud, there has
been a long quest to unravel the mechanism and to be able
to describe it in fundamental terms. An obstacle is the inhomogeneous conditions of testing the explosiveness of adust. The instrument by choice is the 20-litre vessel, but
the concentration of the dust cloud generated in this vessel
and the turbulence intensity decrease rapidly as a functionof time and space. There have been several attempts tomeasure the laminar burning velocity, SU, of a homogeneous dust-air mixture, e.g. by applying a vertical tube inwhich dust particles float statically in position by an
up-going flow of air, as in a fluidized bed102). A recent andmore successful series of experiments measuring the laminar burning velocity of coal dust-methane-air mixtures has
been performed by Xie et al.103) The measurement takes
place on the principle of obtaining a steady-state flame fed
by a continuous flow of fuel-air and observing the flame
cone by applying a shadow-graph technique, for which
special equipment had to be developed. The methaneserves to stabilize the flame. The dust concentration is varied over quite a wide range. The experimental results werecompared to calculated ones based on a straightforward
one-dimensional heat balance deflagration model and applying a devolatilization rate model of coal particles as afunction of temperature. The devolatilization also acts as aheat sink. The model yields a devolatilization zone thickness and a burning velocity. This approach is rather promising; it can also be applied on controlled turbulent intensity
flames as shown by Rockwell and Rangwala104), and can be
expected to be applied on a variety of dust-fuel-air systems.
Di Benedetto and Russo105) tackled the aspect of combustion after the devolatilization stage of organic dusts, which
is very important to the burning velocity of the dust-air
mixture, and hence to the KSt value. By applying devolatilization test results from various sources, carried out by thermogravimetry with attached chromatographic analysis of
the pyrolysis gas produced, the composition as well as therate of formation of flammable gas at various temperaturelevels was obtained from a number of dusts, namely cornstarch, polyethylene, and cellulose. The authors then used
the CHEMKIN Premix module to calculate the laminarburning velocity given the gas composition and the known
GRI-Mech 3.4 kinetic combustion mechanism. In addition,
they applied a relation between the pressure increase in aclosed vessel, its radius, and the ratio of specific heats developed by Dahoe and De Goey106) to calculate the rate ofpressure rise. Subsequently, they derived the Kst value or
deflagration index from the rate of pressure rise and the
cube root of the vessel volume. Although the results did notcover the experimental values very accurately, the trends ofthe effect of concentration with the Kst value fitted the experimental ones surprisingly well. To obtain the best fit, thepyrolysis composition to be used in the model must be determined at the highest temperature and heating rate of thethermogravimetric apparatus. Low-temperature gasification
kinetics differ from higher-temperature ones. The missing
link is now the relation between the burning velocity andturbulent intensity. As mentioned above by the work of
Rockwell and Rangwala, there is some progress also in thisdirection, albeit slow.
An interesting further step is modeling the effect of particle size on dust explosion indices. Di Benedetto et al.107)
performed a study of the effect of particle size on the deflagration index. As explained above, devolatilization can

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be measured by performing thermogravimetric experiments
over a certain range of temperatures. In this study it wasalso modeled. This was done as a two-step kinetic rate process: first step is the formation of a molten phase, while thesecond step is a pyrolysis (cracking) and volatilization.
Mass and energy balances in differential form were derived
for the conversions under influence of convected and radiant heat. The volatilization depends on the dimensionless
Biot number, Bi, being the ratio of the time constant of heat
conducting into the particle and that of the external heattransfer. Two cases were considered: one in which the external heat transfer dominated (Bi << 1) and the other in whichinternal heat transfer controls (Bi >> 1). For the first case,the dimensionless Damköhler number, Da, is considered,being the ratio of the external heat transfer time constantand the characteristic pyrolysis conversion time. Next, tworegimes are distinguished: regime I in which the external
heat transfer controls the pyrolysis (Bi << 1 and Da >> 1),
and a second (II) where the pyrolysis is the slowest (Bi <<1 and Da << 1). For the second case (Bi >> 1), the dimensionless Thiele number, Th, is applicable, being the ratio
between conducted heat time constant and the characteristic pyrolysis time. This results in a third and fourth regime(III and IV) with pyrolysis controlled rate (Bi >> 1 andTh << 1) and conversion controlled by internal conduction(Bi >> 1 and Th >> 1), respectively. Particle size appears
in the nominator of both Bi and Th number. A third dimensionless number, Pc, is defined as the ratio between thetime constants of pyrolysis and combustion. This ratio is
equal to the quotient of the product of density and laminarburning velocity, and the product of particle size and flame
thickness. If Pc is larger than unity and if pyrolysis is controlled by conversion kinetics (regimes II and III), the pyrolysis reaction rate controls the explosion. Alternatively,
at a Pc smaller than one, the combustion of volatiles controls. In the case of regime I, the product of Da∙Pc shouldbe evaluated, and in the case of regime IV Th∙Pc. Depending on the particle size, one or the other regime dominates.
When the particle size is smaller than a certain criticalvalue depending on the dust material, heating and devolatilization rates are relatively high (Pc, Da∙Pc and Th∙Pc<< 1) and combustion kinetics determine flame propagation which can be considered to produce a maximum Kst
value. The other regimes can be defined by evaluating thedimensionless numbers. On this basis, simulations were
performed which gave further insight. For instance, the simulations yielded for the four regimes the ratio of maximum
volatiles production rate at any particle size and at a particle
size near zero as a function of particle size. The model wasapplied to polyethylene dust. The particle size was varied
between 10 and 900 microns. Compared with experimental
results of the Kst values, the simulated ones were in fairagreement. More dust types should be investigated.
Finally, Di Benedetto et al.108) accomplished a CFD study72

to simulate the dust dispersion in the 20-liter explosion vessel. The dust concentration variation in time and space after
its injection into this vessel, being the standard test equipment used by many, is still unknown. This is important, because the 20-liter vessel is supposed to produce the same
results as a 1-m3 vessel and for that purpose, the ignition
delay time and pressure difference ratio which determine
the pre-ignition turbulence and dust dispersion have been
carefully selected. How large the margin is, is uncertain.
Measuring of the turbulence level with a laser velocimeter(also named Laser Doppler Anemometer) as in the case ofgas is not possible with dust. The dust concentration selected was 250 g/m3, the dust density 2100 kg/m3, so that it appeared possible to apply an Eulerian approach to thetime-averaged Navier-Stokes equations for the gas phaseand a Lagrangian one for the dust particles. A solution was
obtained with the ANSYS Fluent code. The solid-phaseflow was simulated by means of the (Lagrangian) Discrete
Phase Model. It appears that multiple vortex structures develop which push the dust towards the walls. Hence theconcentration is far from uniform. The turbulence level atthe center near the ignition is rather high. Further studies
will be needed to investigate the effect of particle size distribution and of other particle characteristics.

8. Summary and Conclusions
Particulate hazards include fire and explosion. The key
difference between fire and explosion is that the rates ofphysical and chemical processes occurring during explosions are much faster than those occurring during fires because during a fire, fuel and air are clearly separated,while in explosions fuel is ‘pre-mixed’ with air. Particulate
explosions, like particulate fires, produce flames, intense
heat, and high temperatures, but unlike fire, particulate explosions produce a ‘blast’, a destructive pressure or shock
wave, and sometimes also high-velocity fragments causedby bursting equipment. It is essential to be aware that:
ALL COMBUSTIBLE POWDERS AND MISTS CAN EXPLODE

Characteristics of explosions are the propagation velocity(called flame speed, Sf), maximum pressure; Pmax, maximum rate of pressure rise, (dP/dt)max; time duration of the
explosion, Δt; and the integral of explosion overpressure
over time, ∫Pdt, called explosion impulse, Iexp. Most particulate explosions occur as a deflagration, which is simply
a very rapid burning. Deflagrations propagate at less than
the speed of sound and produce pressure waves which havefinite (dP/dt)max values. Typical Pmax values for particulate deflagrations at optimum composition are ca. 5–10
times the initial pressure, and flame speeds (Sf values) are
typically around 10 m/s. Under certain circumstances ofSaul M. Lemkowitz et al. / KONA Powder and Particle Journal No. 31 (2014) 53–81

confinement, however, the flow of unburnt mixture over obstacles can greatly increase turbulence by creating large numbers of pockets of rapidly moving/rotating fluid called eddies.
Eddy formation can greatly increase the surface area of theflame, which in turn leads to flame acceleration. Due to increased turbulence intensity, flame speeds can even accelerate
to supersonic velocities, at which a deflagration transits
into a detonation. Detonations produce a special type ofpressure wave called a shock wave, characterized by a (near)infinite rate of pressure rise, dP/dt. Detonations propagate
supersonically (up to 2000–3000 m/s) and produce muchhigher Pmax values than deflagrations. Therefore they aremuch more hazardous than deflagrations.
Most particulate explosions are deflagrations; safety measures aim to ideally prevent deflagrations, or should theyoccur, mitigate their effects. A key safety design priority isfurthermore to prevent deflagrations from transforming into
the much more deadly detonation. However, fundamental
explosion knowledge can be used not only to increase safety, but also to cause particulate clouds in air to directly detonate, forming the basis of Fuel-Air Explosives (FAEs), a
powerful, relatively new, blast weapon.
The hazards of a given particulate are characterized by
two types of fire and explosion indexes. The first type, fireand explosion sensitivity indexes, relates to the probabilityof fire and/or explosion occurring (i.e. probability of ignition). Examples are: Lower and Upper Explosion Limits(LEL and UEL), Minimum Explosion Temperature andEnergy (MIT and MIE), and Limiting Oxygen Concentration (LOC). The second type of indexes, explosion severity indexes, relates to the magnitude of adverse effects
caused by explosions. Such indexes include the type of
explosion occurring (deflagration of detonation), Pmax, and(dP/dt)max, the latter volume normalized and called the KSt
factor. In general, particulates produce roughly the same
maximum explosion pressures (i.e. 5–10 times initial pressure) as gas explosions, but their rate of pressure rise isusually (much) less than that of gas/vapor explosions. On
the other hand, because of the much greater density ofparticulates relative to gases/vapors, particulate-air mixtures contain more energy per unit volume than mixturesof combustible gas/vapor with air. This manifests itself ina longer explosion time duration (Δt) than gas/vapor explosions, and thus a larger explosion impulse, I, which cancause more damage.
The explosion hazards of a given particulate, as expressed by values of its explosion sensitivity and explosion severity indexes, are determined by the particulate’s
chemical and physical properties. Increasing chemical reactivity (e.g. higher combustion energy, J/kg, leading tohigher adiabatic flame temperature) tends to increase allfire and explosion indexes (e.g. lower MIT and MIE; higher Sf, Pmax and KSt factor), and thus to increase the hazard.
The most important physical property affecting fire andexplosion parameters is particle size (particle size and particle size distribution). In general, the finer the particles,
the greater their hazard. The explosion mechanism of mostparticulates is controlled by diffusion (of oxygen to andreaction products away from the particle’s surface). Diffusion control is typical of a heterogeneous (i.e. multi-phase)chemical reaction. The rate of gas and vapor explosions
which occur homogeneously (i.e. within one phase: gas) isdetermined not by diffusion, but by chemical kinetics.
Compared to rates of chemical reaction, which increase
exponentially with temperature, diffusion is a relatively
slow process. This is the basic reason why explosions of
the most commonly used particulates which are in theupper micron region generally proceed more slowly thangas/vapor explosions (i.e. similar Pmax, but slower dP/dt).
However, even low concentrations of flammable gases orvapors (the latter possibly originating from the evaporationof traces of solvents) present in particulate-air suspensions(called ‘hybrid mixtures’) can greatly increase both the
explosion sensitivity and severity of particulate explosions(hybrid explosions).
Turbulence has a complex effect on particulate explosions. Turbulence is essential for creating and maintaining
particle clouds in air, and increased turbulence tends to increase all particulate explosion severity indexes. As previously mentioned, turbulence can even cause a deflagration
to transit into the vastly more hazardous explosion type,the detonation, a phenomenon known as a deflagration-detonation transition (DDT). By contrast, however,increased turbulence tends to reduce most particulate explosion sensitivity indexes. A breakthrough in the ability
to describe turbulent flow, a highly ‘complex’ area ofphysics, and predict flame speed and pressure build-up has
been the development of Computational Fluid Dynamics(CFD). In spite of considerable progress, application todust explosions is, however, still in its infancy.
Various chemical and physical properties of particulates
are aggregated to form an internationally used fire and explosion index, that of the National Fire Protection Agency(NFPA).
A plethora of information exists concerning the basics
of particulate fires and explosions and ways of preventing
and/or mitigating the fire and explosion hazards (see Appendix). Extensive analysis of industrial accidents showsthat it is not lack of knowledge that is the most generalcause of accidents, but rather unawareness and/or non- or
improper application of such knowledge, thus management failure. Therefore, while we outline the basics ofprevention and protection, we stress that the generic causeof most particulate fires and explosions is poor management. To tackle this problem, modern safety management
systems are evolving. Such management systems are beingcombined with new design methods such as Inherently
Safer Design (ISD) and Layers of Defense Analysis

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Saul M. Lemkowitz et al. / KONA Powder and Particle Journal No. 31 (2014) 53–81(LOPA) to create even more integrated and ‘holistic’ management methodologies. These tools and methods are partof the systematic, integrative, and comprehensive safety
science field known as Loss Prevention.
While an abundance of knowledge (data, theory) exists,
research on the fire and explosion hazards of particulates
nevertheless continues, with interesting and useful results.
One important area is nanoparticles, whose production anduse are increasing rapidly. Research so far shows that reducing the particle size down from the mm range to the
1-micron range (1000 nm) strongly increases both the explosion severity and explosion sensitivity. Further reduction
into the (high) nanometer range shows a continuing explosion sensitivity increase (i.e. lower MIE), but no further increase in explosion severity (i.e. Pmax and KSt values remain
constant, or even increase slightly with further particle size
reduction). We note, however, that nearly all research has
been restricted to the high end of nanoparticle size; i.e. toparticles around 100 nm or somewhat smaller (≥ ca.
15 nm). Creating smaller nanoparticles and dispersing
them into clouds is hampered by strong cohesive forces(e.g. van der Waals’ forces). Research on reactive metallic
nanoparticles is further complicated by their tendency tospontaneously oxidize or even exhibit pyrophoric behavior. Nevertheless, it is clear that as the particle size decreases from the micron range into the nanometer range,
the mechanism of particulate explosions increasingly resembles the mechanism of gas/vapor explosions; i.e. thereaction rate is less controlled by diffusion and more bychemical kinetics. Various researchers theorize and extrapolate or calculate that in the extreme case, when particulates
approach the size of individual molecules, their explosion
mechanism will become identical with that of gases and vapors, namely controlled exclusively by chemical kinetics.
At these low nanodiameters, the fundamental explosion
parameters such as laminar burning velocity and sensitivity and explosion severity indexes will increasingly resemble those of gases and vapors (e.g. indexes of smaller andsmaller (nano-sized) polyethylene particles increasingly
resembling those of ethylene gas; aluminum (a stable but
reactive metal) nanoparticles, although chemically very different, having a laminar burning velocity increasingly close
to that of acetylene (a highly reactive gas)).
Another important area of research is acquiring a deeper
understanding of particulate fire and explosion reaction
mechanisms, and through such knowledge being able tobetter quantitatively describe and predict fire and explosion
behavior. Making use of Computational Fluid Dynamics(CFD), powerful models are being developed to predict thecourse of (particulate) explosions (e.g. Sf, Pmax, Δt, dP/dt,
these as functions of time, location, and initial conditions),
both inside and outside installations. Such models enable
more cost-effective safety design and operation. Present
CFD modeling of dust explosion behavior, however, still74

requires further development to reach the reliability presently achieved for modeling gas/vapor explosions.

Symbols and Abbreviations
AIT	Auto-Ignition Temperature (usually Minimum
Auto-Ignition Temperature)bara
bar absolute pressure
baro
bar overpressure
CCPS Center for Chemical Process Safety (USA)
DDT Deflagration-Detonation Transition
DIN	Deutsches Institut für Normung (German Institutefor Standardization)
ISD
Inherently Safer Design
LEL	Lower Explosion Limit (= LFL: Lower Flammability Limit)
LOC	Limiting Oxygen Concentration (below which
explosion is not possible)
LOPA Layer of Protection Analysis
MESG Maximum Experimental Safe Gap
MIE
Minimum Ignition Energy
MIT
Minimum Ignition Temperature
NFPA National Fire Protection Association (USA)PVC
Polyvinylchloride
SMD Sauter Mean Diameter (D3,2)
STP
Standard Temperature and Pressure
TNT
TriNitroToluene
UEL	Upper Explosion Limit (= UFL: Upper Flammability Limit)
D	Particle size (note: for non-spherical particles:
measured size depends upon technique)D3,2Area-weighted Sauter mean diameter
Kst	Volume-normalized maximum rate of pressure
rise in a vessel (= V1/3 · (dP/dt)max)
P
Pressure∫Pdt	Integral of explosion overpressure and time=explosion impulse
SU
Laminar burning velocity
Sf
Flame speed
t
Time
Δt
Time duration of explosion
T
Temperature
V
Volume of a vessel

Appendix. Some recommended literature sources
1. Bartknecht, W. (1993): “Explosionsschutz—Grundlagenund Anwendung”, Springer-Verlag, (ISBN: 3-540-55464-5).
2. Bartknecht, W. (1989): “Dust Explosions: Course, Prevention, Protection”, Springer-Verlag, (ISBN: 3-540-50100-2).
3. Bartknecht, W., (1981): “Explosions”, Springer-Verlag,(ISBN: 3-540-10216-7).

Saul M. Lemkowitz et al. / KONA Powder and Particle Journal No. 31 (2014) 53–81

4. Barton, J. (2002): “Dust explosion prevention and protection—A Practical Guide”, Institution of Chemical Engineers, (ISBN 0-85295-410-7).
5. Britton, L. G. (1999): “Avoiding Static Ignition Hazards in
Chemical Operations,” Center for Chemical Process Safety,
American Institute of Chemical Engineers (ISBN:
0-8169-0800-1).
6. Bjerketvedt, D., Bakke, J. B., and van Wingerden, K. (1997):
Gas Explosion Handbook, Journal of Hazardous Materials
No. 52, pp. 1–150. (In spite of title, much information also
relevant to explosions of particulates.)
7. Center for Chemical Process Safety (2005): “Guidelines for
Safe Handling of Powders and Bulk Solids, 2005, American
Institute of Chemical Engineers (ISBN 0-521-03339-7).
8. Crowl, D. A. (2003): “Understanding Explosions, Centerfor Chemical Process Safety”, American Institute of Chemical Engineers, (ISBN 0-8169-0779-X).
9. Dahoe, A. E. (2000): “Dust Explosions: A Study of Flame
Propagation”, Ph.D. Dissertation, Delft University of Technology, 297 pages (ISBN: 90-90-13706-8).
10. Eckhoff, R. K. (2003): “Dust Explosions in the Process
Industries”, Third Edition, Butterworth-Heinemann, (ISBN:
0-7506-7602-7).
11. Eckhoff, R. K. (2005): “Explosion Hazards In The Process
Industries—Why Explosions Occur And How To Prevent
Them, With Case Histories”, Golf Publishing Company.
12. Glor, M. (1988): “Electrostatic Hazards in Powder Handling”,
Wiley, (ISBN: 0-471-92024).
13. M. Hattwig, M. and Steen, H. (2004): “Handbook of Explosion Prevention and Protection”, Wiley-VCH, 2004, (700pages; ISBN: 3-527-30718-4).
14. Hetzberg, M. and Cashdollar, K. L. (Eds.) (1987): “Industrial
Dust Explosions Symposium on Industrial Dust Explosions”, (ASTM Special Technical Publication), (ISBN-10:
0803109571, ISBN-13: 978-0803109575).
15. Mannan, S. (Ed.): Lees’ Loss Prevention in the Process In­
dustries, Third Edition, Elsevier Butterworth Heinemann,
2005. (Set ISBN: 0-7506-7555-1; Set consists of Volumes 1,
2, and 3 (ca. 3,000 pages) discussing in great detail a broad
scale of topics and issues related to loss prevention (e.g.,fire and explosion prevention and protection) in the processindustries. Note that a Fourth Edition is being prepared.
Presently (2013) Volumes 1 (ISBN-10: 0123971896) and 2(ISBN-13: 978-0123971890) of the three volume series
have been published.
16. Nolan, D. P. (2011): “Handbook of Fire and Explosion Protection Engineering Principles for Oil, Gas, Chemical and
Related Facilities”, Second Edition, Elsevier, (ISBN:
978-1-4377-7857-1).
17. UKELG 46th (2010): “Meeting on Causes, severity and mitigation of aerosol and particulate explosions”, Dept. Chem.
Eng., Imperial College, London, 22nd Sept. 2010. Lectures
available at: http://ukelg.ps.ic.ac.uk/UKELG46.htm

End notes and cited literature
1) Lemkowitz, S. M. and Pasman, H. J. (2013): discuss

particulate fire and explosion risks in “Assessment and Controlof Fire and Explosion Hazards and Risks of Particulates”,
Chapter 4, Merkus, H. G. and Meesters, G. M. H. (Editors),“Particulate Products—Design Properties for Performance
Optimization”, pp. 77–120, .Springer, 2013 (ISBN:
978-3-319-00713-7).
2) While dust explosion hazards are extensively studied, muchless is available for mist explosions. Examples are: Gant, S,
Bettis, R., Santon, R., Bickland, I., Bower, Ph. and Kay, P.
(2012), “Generation of Flammable Mists from High Flashpoint Fluids: Literature Review”, presented at Institution ofChemical Engineers, XXIII Conference, Southport, UK,
12–15 November 2012, available as: http://s177835660.websitehome.co.uk/research/gant_bettis_santon_buckland_
bowen_kay_2012_mists_lit_review_preprint.pdf, 19 pages;
Förster, H. (2004), Chapter 5, “Properties of Flammable
Mists and Foams”, p. 419–480, from M. Hattwig, M. andSteen, H., “Handbook of Explosion Prevention and Protection”, Wiley-VCH, 2004 (ISBN: 3-527-30718-4); Krishna,K., Rogers, W. J. and Mannan, M. S. (2003), “The use ofaerosol formation, flammability, and explosion information
for heat-transfer fluid selection”, Journal of Hazardous
Materials 104, pp. 215–226; Holness, M. H. and Smith, B. J.
(2002), “Oil Mist and Machinery Space Fires”, Marine
Technology, 39(1), 2002, pp. 62–66; Britton, L. G. (1999),“Avoiding Static Ignition Hazards in Chemical Operations,”
Center for Chemical Process Safety, American Institute ofChemical Engineers, pp. 83–96, 209–211.
3) See for example, Eckhoff, “R. K. (2003), “Dust Explosions
in the Process Industries”, Third Edition, Elsevier, (ISBN:
0-7506-7602-7), in particular Table A.1, pages 686–699,
which lists explosion severity and sensitivity indexes,
including Pmax, for ca. 600 different powders.
4) Lemkowitz, S. M. and Scholten, R. M. (1999), “Explosion
theory for dummies”, NPT Process Techniek, 2, pp. 19–24.
Derivation is based on assumptions that flame thickness issmall relative to vessel diameter and that flame speed isindependent of temperature and pressure.
5) Hertzberg et al, 1986 derive a formula very similar to Eq. 4
applied to gases, i.e. for flames whose thickness is small
relative to the radius of vessels in which explosion occurs.
Hertzberg, M., Cashdollar, K. L., and Zlochower, I. A.
(1986), “Flammability Limit Measurements For Dusts andGases: Ignition Energy Requirements and Pressure Dependences”, Twenty-first Symposium (International) on Combustion, the Combustion Institute, pp. 303–313; see Eq. 5,
page 307. Cashdollar (2000) obtains the same equation as
Hertzberg et al. (1986), but applies it to dust explosions,commenting that the equation is probably more valid in thestandard 1000 liter testing sphere than in the, also standard,
20 liter sphere due to the greater radius of the 1000 liter
sphere, relative to dust flame thickness. Cashdollar, K. L.
(2000), “Overview of dust explosibility characteristics”,
Journal of Loss Prevention in the Process Industries, 13,
pp. 183–199. See Eqs. 6–7, page 188.
6) Dahoe et al. (1996, 2003) derive more realistic—and considerably more complex—equations describing flame speed
effects on pressure rise and K factor for thick dust flames,

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which are typical of particulate explosions. Dahoe, A. E.
and de Goey, L. P. H. (2003), “On the determination of thelaminar burning velocity from closed vessel gas explosions”, Journal of Loss Prevention in the Process Industries, 16, pp. 457–478; Dahoe, A. E., Zevenbergen, J. F.,
Lemkowitz, S. M., and Scarlett, B. (1996), “Dust explosions in spherical vessels: the role of flame thickness in thevalidity of the ‘cube-root-law’”, Journal of Loss Prevention
in the Process Industries, 9, pp. 33–44
7) Center for Chemical Process Safety (2012), “Guidelines for
Evaluating Process Plant Buildings for External Explosions,
Fire, and Toxic Releases”, Second Edition, Wiley (ISBN978-0-470-64367); see p. 62.
8) Center for Chemical Process Safety (1994), “Guidelines for
Evaluating the Characteristics of Vapor Cloud Explosions,Flash Fires, and BLEVEs”, first edition, American Instituteof Chemical Engineers; see Table 4.1a, p. 72.
9) Abbasi, T., Pasman H. J., Abbasi S. A. (2010), A scheme forthe classification of explosions in the chemical process industry, Journal of Hazardous Materials, 174, pp. 270–280.
10) Mannan, S. editor (2012), “Lees’ Loss Prevention In The
Process Industries, Fourth Edition, Chapter 17, “Explosion”,
Elsevier, ISBN 978-0-123-971890
11) Using such indexes (Tables 1 and 2), in combination withchemical thermodynamic data and data from practice (e.g.,
accidents), the National Fire Protection Agency (NFPA)
ranks hazards of powders in terms of Health, Fire, andInstability. See Center for Chemical Process Safety,(2005), “Guidelines for Safe Handling of Powders andBulk Solids”.
12) On the basis of a number of simplifying assumptions,and using only secondary school chemistry and physics,
Lemkowitz and Scholten correctly derive, in terms of trends,
how changes in ambient temperature, pressure, and flow (turbulence) affect nearly all important fire and explosion indexes:
Lemkowitz, S. M. and Scholten, R. M. (1999), op cit.
13) Detailed discussions of test methods for powders and theirevaluation are given in: J. Barton (2002)), “Dust Explosion
Prevention and Protection—A Practical Guide”, Institution ofChemical Engineers; see Chapter 2: “Determination of dust
ignitability, flammability and explosibility characteristics”,
pp. 8–20; Eckhoff, R. (2003), “Dust Explosions in the Process Industries”, Third Edition, Butterworth-Heinemann,see Chapter 7, “Assessment of ignitability, explosibility,
and related properties of dusts by laboratory-scale tests; pp.
473–548.
14) Gao, W., Zhong, S., Miao, N., and Liu, H. (2013), “Effect ofignition on the explosion behavior of 1-Octadecanol/air
mixtures”, Powder Technology, 241, pp. 105–114.
15) Proust, Ch., Accorsi, A., and Dupont, L. (2007), “Measuring
the violence of dust explosions with the “20 l sphere” and thestandard “ISO 1 m3 vessel—Systematic comparison andanalysis of the discrepancies”, Journal of Loss Prevention
in the Process Industries, 20, pp. 599–606.
16) Detailed descriptions of hazards of unstable liquids andtheir control are given by L. A. Medard (1989) in: “Accidental Explosions” Volumes 1 (ISBN 0470215305) and Volume 2 (ISBN 0-7458-0436-5). Ellis Horwood Ltm (English

76

translations of the original French language text of 1987).
17) Powdered ammonium nitrate, mixed with an inert compound such as calcium carbonate to reduce its explosion
hazard (‘phlegmatizing’ it), is a widely used fertilizer. In
spite phlegmatizing inerts, a number of serious explosionsof large piles of powdered ammonium nitrate have nevertheless occurred.
18) Examples of pyrophoric substances are found in Johnson, R.
W., Rudy, S. W., and Unwin, S. D. (2003), “Essential Practices for Managing Chemical Reaction Hazards”, Center for
Chemical Process Safety, American Institute of Chemical
Engineering, Table 3.2, page 45.
19) The above source also lists common water-reactive substances (Table 3.4, page 50) as also does ‘Common Water
Reactive Chemicals’, http://www.esd.uga.edu/chem/pub/waterreactivemat.pdf.
20) Going, J. E. and Snoeys, J. (2002), “Explosion Protection
with Metal Dust Fuels”, Process Safety Progress, 21(4), pp.
305–312.
21) In some cases, such as explosions of finely divided metals(e.g., powdered aluminum), even three phases can be
simultaneously present: a solid phase (solid aluminumoxide), a liquid phase (molten aluminum), and a gaseous
phase (air, even vaporized aluminum).
22) P. Puri, P. (2008), “Multiscale modelling of ignition andcombustion of micro and nano aluminum particles”, PhD
Dissertation, The Pennsylvania State University, In his 235
page thesis Puri discusses combustion mechanisms of metal
particles in great detail, including many splendid color figures. Full dissertation available via: http://search.proquest.
com/docview/231495775
23) Lecture of Puri, P. and V. Yang, V. (2005), “Multi-Scale
Modeling of Nano Aluminum Particle Ignition and Combustion”, Sheet 6, lecture presented in 2005 at MURI
NEEM Program Review, Aberdeen, Maryland; full lecture
available as: http://soliton.ae.gatech.edu/people/vigor.yang/projects/Nano%20Aluminum...(Puneesh)/ARO-MURI%20
NEEM%20Website-(11-16-05).pdf. See also Yang, V.,
Sundaram, D., and Puni, P. (2010), “Multi-Scale Modeling of
Nano Aluminum Particle Ignition and Combustion”, lecture
presented in 2010 MURI NEEM Program Review, Aberdeen, Maryland, March 15, 2010. Sheet 3. Lecture available
as: http://www.neem.psu.edu/2010%20Review%20Meeting/GeorgiaTech_Yang _NEEM_MURI_Final_Review_15_
March_2010.pdf24) Kobiera, A., Szymczyk, J., Wolanski, P., and Kuhl, A (2009),“Study of the shock-induced acceleration of hexane droplets”, Shock Waves, 18.4, pp. 475–485.
25) Dobashi, R. (2008), “Risk of dust explosions of combustible
nanomaterials”, Journal of Physics: Conference Series, IOP
Publishing, 170, Figure 3 on page 3.
26) R. Dobashi, R. (2008), “Risk of dust explosions of combustible nanomaterials”, sheet 19 of lecture presented at Nanosafe
2008, International Conference on Safe Production and Useof Nanomaterials; lecture available as: http://www.nanosafe.
org/home/liblocal/docs/2008_Oral%20presentations/PL7_
Dobashi.pdf27) Föster, H. (2004), “Properties of Flammable Mists andSaul M. Lemkowitz et al. / KONA Powder and Particle Journal No. 31 (2014) 53–81

Foams”, Chapter 5 of “Handbook of Explosion Prevention andProtection”, edited by Hattwig, M. and Steen, H. Wiley-VCH
Verlag, 2004 (ISBN: 3-527-30718-4), Figure 5.1-6, page 435.
28) Dobashi, R. (2008), op cit, sheet 20 from 2008 lecture of
Dobashi29) Ballal, D. R. (1980), “Ignition and Flame Quenching ofQuiescent Dust Clouds of Solid Fuels”, Proceedings of theRoyal Society of London. Series A, Mathematical andPhysical Sciences, 369, pp. 479–500.
30) The Sauter mean diameter (SMD, d32 or D[3, 2]) is an average of particle size. It is defined as the diameter of a spherethat has the same volume/surface area ratio as the particle
of interest.
31) Eckhoff, R. K. (2003), op cit, page 47932) Eckhoff does, however, mention (p. 490) a related essential
point, namely that a measured particle size distribution may
be quite different from that occurring in practice, due to
how in practice a powder is dispersed and suspended.
33) Föster, H. (2004), op cit., see pages 423–425 and 235.
34) Merkus, H. G. (2009), “Particle Size Measurements—Fundamentals, Practice, Quality”, Springer (ISBN: 978-1-40209015-8 en e-ISBN: 978-1-4020-9016-5). See pp 140–146.
35) Amyotte, P. R., Chippett, S., and Pegg, M. J. (1989), “Effects
of Turbulence on Dust Explosions”, Progress in Energy andCombustion Science, 14, pp. 293–310; see also Lemkowitz
and Scholten, 1999, op cit.
36) A detailed discussion of film theory in describing heterogeneous combustion is given in: Annamalei, K. et al. (1994),“Interactive Processes in Gasification and Combustion-Part
III: Coal/Char Particle Arrays, Streams and Clouds”, Prog.
Energy Combust. Sci. 20, 487–618; see especially pages
491–494.
37) For detailed discussion of secondary dust explosions see:Taveau, J. (2012), “Secondary Dust Explosions: How toPrevent Them or Mitigate Their Effects”, Process Safety
Progress, 31(1), pp. 36–50.
38) A comprehensive and detailed analysis (85 pages) of suchan explosion, caused in part by poor housekeeping, is given
in: U.S. Chemical Safety and Hazard Investigation Board,
Sugar Dust Explosion and Fire (14 Killed, 36 Injured),Investigation Report No. 2008-05-I-GA, September 2009;
available as: http://www.csb.gov/assets/document/Imperial_
Sugar_Report_Final_updated.pdf
39) Proust discusses DDTs through flame acceleration in connecting pipe work: Proust, Ch. (1996), “Dust explosions inpipes: a review”, Journal of Loss Prevention in the Process
Industries, 4(9), pp. 267–277.
40) R. K. Eckhoff, R. K. (2003), op cit, pages 74 and 525; seealso Crowl, D. A. (2003), “Understanding Explosions”,
Center for Chemical Process Safety, American Institute ofChemical Engineers, (ISBN 0-8169-0779-X), pp. 63–64.
41) See for example, Dahoe, A. E., Cant, R. S., Pegg, M. J. andScarlett, B. (2001), “On the transient flow in the 20-liter
explosion sphere”, Journal of Loss Prevention in the Process Industries 14, pp. 475–487
42) For more detail see: Dahoe, A. E., “Dust Explosions: A
Study of Flame Propagation”, PhD Dissertation, Delft University of Technology, 2000, 297 pages (ISBN: 90-90-13706-8); see especially pages 174–181.
43) van Laar, G. F. M. and Zeeuwen, J. P. (1981), “On the Minimum Ignition Energy of Dust-Air Mixtures”, Archivum
Combustionis, 5, pp. 145–159R. A extensive study ofeffects ab//adsorbed water of explosion indexes is: J. P.
Zeeuwen and G. F. M. van Laar (1983), “An overview of theresearch at TNO in the dust explosion field over the last
decade”, Figure 6, page 83, of VDI-Berichte 494 (1983),“Sichere Handhabung brennbarer Stäube”, VDI-Verlag
GmbH, Verlag des Vereins Deutscher Ingenieurs, Düsseldorf.
44) Glor, M. (1988), “Electrostatic Hazards in Powder Handling”, Chapter 2, Charging of particles, Chapter 3, Ignitionof particles, Wiley (ISBN: 0-471-92024).
45) Hertzberg, M. and Cashdollar, K. L. (1987), “Introduction
to Dust Explosions”, from Hertzberg, M. and Cashdollar, K.
L. (editors), “Industrial Dust Explosions”, ASTM (American
Society for Testing Materials), 1987 (ISBN: 0-8031-0957-1);
modified version of Figure 5, page 14.
46) Bartknecht, W., (1981), “Explosions“, Springer-Verlag, 1981
(ISBN: 3-540-10216-7), pp. 49–55. Many of Bartknecht’s
original figures continually reappear in modified form instandard works on dust explosions, such as Eckhoff’s 2003
textbook.
47) Modified from Pellmont, G. (1979), “Explosions- und Zündverhalten von Hybriden Gemischen aus brennbaren Stäuben
und Brenngasen“, PhD thesis, No. 6498, ETH Zürich. Figure
7 here is taken from Eckhoff, R. K. (2003), op cit, Figure
1.60, p. 52.
48) Modified from Bartknecht, W. (1981), “Explosions—
Course, Prevention, Protection”, Springer-Verlag, Fig. 1-5.4,
p. 51. Figure 8 here is taken from Eckhoff, R. K. (2003), op
cit, Figure 1.65, p. 55.
49) Lavoie, L. (1989), “Fuel-Air Explosives, Weapons, andEffects”, Military Technology—MILTECH, 9, pp. 64–70.
50) Rao, A. A., (1987), “Fuel Air Explosives”, Defence Science
Journal, 37(1), pp. 23–28; Liu, G., Hou, F., Cao, B., Xie, L.,
Shen, Zh., and Zhou, T. (2008), “Experimental Study ofFuel-Air Explosive”, Combustion, Explosion, and ShockWaves, 44(2), pp. 213–217.
51) Dearden, P., (2001), “New Blast Weapons”, Journal of theRoyal Army Medical Corps, 147 (1), 2001, 80–86. Available
as: http://www.ramcjournal.com/content/147/1/80.full.pdf+
html; Wildegger-Gaissmaier, A. E., “Aspects of thermobaric
weaponry”, ADF Health (Health Journal for the Australian
Department of Defence—Joint Health Command), 4, pp.
3–6, 2003; article available as: http://www.defence.gov.au/
health/infocentre/journals/ADFHJ_apr03/ADFHealth_4_1_
03-06.pdf
52) Pierce, T. H., Sedgwick, R. T. and Groethe, M. A. (1982),“Investigation of a Reusable Fuel-Air Explosive Nuclear
Airblast Simulator”, Defense Nuclear Agency (Washington
D.C.), 133 pages.
Abstract available as: 
http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=
html&identifier=ADA149473
53) Direct ignition of detonations of gaseous fuel-air mixtures
requires high energies, typically (more than) a million
times greater than those required to ignite deflagrations.

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See for example, Center for Chemical Process Safety (2010),“Guidelines for Vapor Cloud Explosion, Pressure Vessel
Burst, BLEVE and Flash Fire Hazards”, Second Edition,
Wiley, (ISBN 978-0-470-25147-9), Table 4.2, page 55.
54) The generic nature of management failure in causing industrial explosions is clearly shown in, for example, many publications of the United States Chemical Safety Board. (http://
www.csb.gov/), like the investigation of the 2009 explosion
at the Imperial Sugar plant that killed 14 workers and totally
destroyed the plant. Other publicly available investigationsof industrial disasters (e.g., Flixborough, Seveso, Piper
Alpha, Chernobyl, BP Texas City explosion, BP Deepwater
Horizon oil spill) all show management failure, not lack ofscientific knowledge, to be the basic cause of disasters.
55) For example: Center for Chemical Process Safety: (2011),“Guidelines for Auditing Process Safety Management Systems, 2nd Edition”, Wiley (ISBN: 978-0-470-28235-9);(2008) Guidelines for the Management of Change for Process Safety, Wiley (ISBN: 978-0-470-04309-7)
56) For example see: Britton, L. G. (1999), “Avoiding Static
Ignition Hazards in Chemical Operations”, Center for
Chemical Process Safety (ISBN: 0-8169-0800-1); and Glor,
M. (1988), op cit.
57) For example: Vijayaraghavan, G. (2011), “Review Article:
Dust Explosions - A Major Industrial Hazard”, International Journal of Advanced Engineering Technology, Vol.
II/Issue IV, pp. 83–87; Amyotte, P. R. and Rolf K. Eckhoff,
P. R. (2010), “Dust explosion causation, prevention and mitigation: An overview”, Journal of Chemical Health &Safety, pp. 15–28; Eckhoff, R. K. (2009), “Understanding
dust explosions: The role of powder science and technology”, Journal of Loss Prevention in the Process Industries,
22, pp. 105–116; Eckhoff, R. K. (2009), “Dust Explosion
Prevention and Mitigation, Status and Developments in
Basic Knowledge and in Practical Application”, International Journal of Chemical Engineering, pp. 1–12; Abbasi,
T and Abbasi, S. A., (2007) “Dust explosions—Cases,causes, consequences, and control”, Journal of Hazardous
Materials, 140, pp. 7–44; Amyotte, P. R., Pegg, M. J., Khan,
F. I., Nifuku, M., and Yingxin, T., (2007) “Moderation ofdust explosions”, Journal of Loss Prevention in the Process
Industries, 20, pp. 675–687; Pekalski, A. A., Zevenbergen, J.
F., Lemkowitz, S. M. and Pasman, H. J., (2005), “A Review
of Explosion Prevention and Protection Systems Suitable asultimate Layer of Protection in Chemical Process Installations”, Trans IChemE, Part B, Process Safety and Environmental Protection, 83(B1), pp. 1–17;
58) Center for Chemical Process Safety (2009), “Inherently
Safer Chemical Processes: A Life Cycle Approach”, 2nd
Edition (ISBN: 978-0-471-77892-9). Layer of Protection
Analysis (LOPA) and Inherently Safer Design (ISD) are
examples of parts of the systematic, science-based discipline of Loss Prevention.
59) Center for Chemical Process Safety (CCPS), Layer of Protection Analysis—Simplified Process Risk Assessment,
American Institute of Chemical Engineers, 2001 (ISBN0-8169-0811-7).
60) For an overview of Loss Prevention, see, for example, Mannon,

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Ref. 15 in the Appendix.
61) See, for example, Chapter 13, “The Role of Inherently Safer
Design in Dust Explosion Prevention and Mitigation”, from
Kletz, T. and Amyotte, P. (2010), “Process Plants: A Handbook for Inherently Safer Design”, Second Edition, CRC
Press, ISBN: 978-1-4398-0455-1, pp. 289–318; Amyotte, P.
R., Pegg, M. J. and Khan, F. I. (2009), “Application of
inherent safety principles to dust explosion prevention andmitigation”, Process Safety and Environmental Protection,
87, pp. 35–39; Dufaud, O., Perrin, L. and Laurent, A. (2010),“State of the art: promotion of early inherently safer design
against dust explosions”, paper presented at CISAP4, 4thInternational Conference on Safety and Environment, Florence, Italy; available as: 
http://www.aidic.it/CISAP4/webpapers/74Dufaud.pdf62) Vignes, A., Muñoz, F., Bouillard, J., Dufaud, O., Perrin, L.,
Laurent, A. and Thomas, D. (2012), “Risk assessment of theignitability and explosivity of aluminum nanopowders”, Process Safety and Environmental Protection, 90, p. 304–310.
63) Zhang, Q., Zhong, S. and Jiang, G. (2011), “Development of
an Expert System for Dust Explosion Risk Management
Based on ASP. Net and Prolog”, Journal of Software, 6(9),pp. 1857–1865.
64) Pasman, H. J., Knegtering, B., and Rogers, W. J. (2013),“Review: A holistic approach to control process safety
risks: Possible ways forward”, Reliability Engineering and
System Safety, 117, pp. 21–29
65) See, for example, Baukal, C. E. (2013), “The John Zink
Hamworthy Combustion Handbook”, Second Edition: Volume
1—Fundamentals, CRC Press. ISBN: 978-1-4398-3962-1.
66) For example: Veyssiere, B., Khasainov, B. A., and W.
Ingignoli, W. (2010), “Shock Initiation of Detonations in
Aluminum-Oxygen Mixtures”, pp. 297–310, in Roy, G. D.
and Frolov, S. M. (editors) “Deflagrative and Detonation
Combustion”, Torus Press (ISBN: 978-5-94588-071-9).
67) Examples being: Proust, Ch. (2006), “A few fundamental
aspects about ignition and flame propagation in dust
clouds”, Journal of Loss Prevention in the Process Industries,
19, pp. 104–120; Eckhoff, R. K. (2005), “Current Status
and Expected Future Trends in Dust Explosion Research”,
Journal of Loss Prevention in the Process Industries, 18, pp.
225–237; Eckhoff, R. K. (1993), “Dust explosion research.
State-of-the-art outstanding problems”, Journal of Hazardous
Materials, 35, pp. 103–117; Kauffman, C. W., Sichel, M.
and Wolanski, P. (1992), “Research on dust explosions at the
University of Michigan”, Powder Technology, 71, pp. 119–134.
68) Hinkley, G. K. and Stephen M. Roberts, S. M. (2013),
Chapter 5, pp. 121–149, “Particle and Fiber Toxicology”,
from Merkus, H. G. and Meesters, G. M. H. (Editors), “Particulate Products—Design Properties for Performance
Optimization”, Springer, 2013 (ISBN: 978-3-319-00713-7)
69) Safety and health issues are central in the Nanosafe: Safe
Production and Use of Nanomaterials. International conferences held biannually in Grenoble, France in 2008, 2010,
and 2012. Noticeable is that while in 2008 and 2010 fire andexplosion safety issues were discussed in many lectures,
since then these issues seem relatively clear, in comparison
with health issues, which in 2012 still received much atten-

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tion. Lectures available on the web.
For 2008: http://www.nanosafe.org/scripts/home/publigen/content/templates/show.asp?P=96&L=EN&ITEMID=42.
For 2010: http://www.nanosafe.org/scripts/home/publigen/content/templates/show.asp?P=118&L=EN.
For 2012: http://www.nanosafe.org/scripts/home/publigen/content/templates/show.asp?P=124&L=EN70) Eckhoff, R. K. (2012), “Does the dust explosion riskincrease when moving from µm-particle powders to powders of nm-particles?”, Journal of Loss Prevention in theProcess Industries, 25, p. 448–45971) Wu, H-C, Chang, R-C, and Hsiao, H-C. (2009), “Researchof minimum ignition energy for nano Titanium powder andnano Iron powder”, Journal of Loss Prevention in the Process
Industries, p. 21–24
72) Eckhoff, R. K. (2013), “Influence of dispersibility and coagulation on the dust explosion risk presented by powders consisting of nm-particles”, Powder Technology, 239, p. 223–230.
73) Yetter, R. A., Risha, G. A., and Son, S. F. (2009), “Metal
particle combustion and nanotechnology”, Proceedings of
the Combustion Institute 32, p. 1819–1838; e.g. see p. 1822.
74) Evans, J. P., Borland, W. and Mardon, P. G. (1976) “Pyrophoricityof fine metal; powders”, Powder Metallurgy, 1, p. 17–21.
75) Mohan, S., Ermoline, A. and Dreizin, E. L. (2012), “Pyrophoricity of nano-sized aluminum particles”, Journal of
Nanoparticle Research, 14(2), p. 1–6.
76) Sundaram, D. S., Puri, P. and Yang, V. (2013), “Pyrophoricity of nascent and passivated aluminum particles at nanoscales”, Combustion and Flame, in press.
77) Krietsch, A., Romahn, T., Scheid, M. and Krause, U. (2013),“Modified Setup of 20-L-Sphere for the Determination of
Safety Characteristics of Nano Powders”, Chemical Engineering Transactions, 31 (online).
78) Randeberg, E. and Eckhoff, R. K., (2007), “Measurementof minimum ignition energies of dust clouds in the <1 mJ
region”, Journal of Hazardous Materials, 140, p. 237–244
79) Bouillarda, J., Vignesa, A., Dufaud, O, Perrinb, L, andThomas, D. (2010), “Ignition and explosion risks of nanopowders”, Journal of Hazardous Materials, 181, pp. 873–
880. Fig. 4, p. 875;
80) See also: Lecture of O. Dufaud, A. Vignes, F. Henry, L.
Perrin, and J. Bouillard (2010), “Ignition and explosion of
nanopowders: Something new under the dust”, Sheet 8; lecture presented at Symposium Nanosafe 2010: Safe Production and Use of Nanomaterials, 16–18 November 2010,
Grenoble, France. Complete lecture available on web as:
http://www.nanosafe.org/home/liblocal/docs/Nanosafe%20
2010/2010_oral%20presentations/O11-1_Vignes.pdf
81) Huang, Y., Risha, G. A., Yang, V. and Yetter, R. A. (2009),“Effect of particle size on combustion of aluminum particle
dust in air, Combustion and Flame 156 (2009), pp. 5–13
(Figure 11, p. 11). See also lectures of P. Puri, T. Lui, Ying,
Huang, and V. Yang, “Modeling and Simulation of Supercritical Fluid Processing of Nano Energetic Materials”:
Sheet 22, lecture presented in 2006 at MURI NEEM Program Review at Pennsylvania State University. Lecture
available on web as: http://www.neem.psu.edu/2006%20
Review%20Meeting/ Yang%20M UR I%20NEEM%20

Year%202%20PSU%20Nov%202006.pdf82) Bidabadi, M., Fereidooni, J., Hosseini, S. N. andAsadollahzadeh, P. (2012), “Investigation of particle size
effect on flame velocity in the combustion of nano/micronsized aluminum particles in air”, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace
Engineering, p. 1–8)
83) Bouillarda, J., Vignesa, A., Dufaud, O, Perrinb, L, andThomas, D. (2010), “Ignition and explosion risks of nanopowders”, Journal of Hazardous Materials, 181, pp. 873–
880. Fig. 9, p. 878.
84) Yadollah Bayat, Y. and Zeynali, V. (2011), “Preparation andCharacterization of Nano-CL-20 Explosive”, Journal ofEnergetic Materials”, 29: p. 281–291
85) Yan-fei, X, Jiang, Y, Chang-fu, X and Yan-feng, G. (2012),“The Study On Ultrafine Explosives’ Sensitivity”,
Advanced Materials Research”, 631–632, p. 395–398
86) Selvakumar, N, Azhagurajan, A. and Suresh, A. (2012),“Experimental analysis on nano scale flash powder composition in fireworks manufacturing”, Journal of Thermal
Analysis and Calorimetry (published online).
87) See for example: Dufaud, O., Perrin, L., Traore, M. Chazelet,
S., and Thomas, D. (2009), “Explosions of vapour/dust
hybrid mixtures: A particular class”, Powder Technology,
190, pp. 269–273
88) Dufaud, O., Perrin, L., Traoré, M (2008), “Dust/vapour
explosions: Hybrid behaviors?”, Journal of Loss Prevention
in the Process Industries, 21, pp. 481–484.
89) Dufaud, O., Poupeau, M., Khalili, I., Cuervo, N.,
Christodoulou, M., Olcese, R., Dufour, A., and Perrin, L.
(2012), “Comparing Pyrolysis Gases and Dusts Explosivities: A Clue to Understanding Hybrid Mixtures Explosions?”, Industrial & Engineering Chemistry Research, 51,
pp. 7456–7662.
90) Garcia-Agreda, A., Di Benedetto, Russo, P., Salzano, E.,
and Sanchirico, R. (2011), “Dust/gas mixtures explosion
regimes”, Powder Technology 205, pp. 81–86.
91) Denkevits, A. (2010), “Hydrogen/dust explosion hazard in
ITER: Effect of nitrogen dilution on explosion behavior ofhydrogen/tungsten dust/air mixtures”, Fusion Engineeringand Design, pp. 1059–1063
92) Denkevits, A. (2007), Explosibility of hydrogen–graphite
dust hybrid mixtures, Journal of Loss Prevention in theProcess Industries 20 (2007) 698–707
93) Abuswer, M., Amyotte, P. and Khan, F. (2013), “A quantitative risk management framework for dust and hybrid mixture explosions”, Journal of Loss Prevention in the Process
Industries, 26, pp. 283–289.
94) Reyes, O. J., Patel, S. J. and M. Sam Mannan, M. S. (2011),“Quantitative Structure Property Relationship Studies for
Predicting Dust Explosibility Characteristics (Kst, Pmax) ofOrganic Chemical Dusts”, Ind. Eng. Chem. Res., 50, pp.
2373–2379
95) Dahoe, A. E., van der Nat, K., Braithwaite, M., and Scarlett,B. (2001), “On the sensitivity of the maximum explosion
pressure of a dust deflagration to turbulence”, KONA, 19,
pp. 178–195.
96) Hilton, J. E. and Cleary, P. W. (2013), “Dust modelling

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using a combined CFD and discrete element formulation”,
International Journal for Numerical Methods in Fluids; 72:
528–54997) Bakke, J. R., Van Wingerden, K., Hoorelbeke, P., Brewerton, B. (2010): “A study on the effect of trees on gas explosions”, Journal of Loss Prevention in the Process Industries,
23, pp. 878–884.
98) Van Wingerden, K. (1996), “Simulations of dust explosion
using a CFD-code”, Proceedings of the 7th International Colloquium on Dust Explosions, Bergen Norway, pp. 6.42–6.51.
Paper available as: http://www.t-solutionglobal.com/ts-upfiles/file/other/2009-1-4/Simulation_of_dust_explosions_using_a_CFD.pdf
99) Skjold, T. (2007), “Review of the DESC project,” Journal of
Loss Prevention in the Process Industries, 20, pp. 291–302.
100) Skjold, T. (2010), “Modelling of industrial dust explosions
in complex geometries,” lecture presented at UKELG 46th
Meeting on Causes, severity and mitigation of aerosol andparticulate explosions, Dept. Chem. Eng., Imperial College,
London, 22nd Sept. 2010. Full lecture of Skjold available at:
http://ukelg.ps.ic.ac.uk/46TS.pdf
101) Castellanos, D., Skjold, T., van Wingerden, K., Eckhoff, R.
K., and Mannan, M. S. (2013), “Validation of the DESC
Code in Simulating the Effect of Vent Ducts on Dust
Explosions”, Industrial & Engineering Chemistry Research,
52, 6057–6067.

80102) Proust, Ch. (2006), “On the sensitivity of the maximum
explosion pressure of a dust deflagration to turbulence,”
Journal of Loss Prevention in the Process Industries, 19, pp.
104–120.
103) Xie, Y., Raghavan, V., Rangwala, A. S. (2012), “Study ofinteraction of entrained coal dust particles in lean methane–
air premixed flames”, Combustion and Flame, 159, pp.
2449–2456
104) Rockwell, S. R. and Rangwala, A. S. (2013), “Influence ofcoal dust on premixed turbulent methane–air flames”,
Combustion and Flame, 160, pp. 635–640.
105) Di Benedetto, A., and Russo, P. (2007), “Thermokinetic
modeling of dust explosions”, Journal of Loss Prevention in
the Process Industries, 20, pp. 303–309.
106) Dahoe, A, and De Goey, L. P. H. (2003): “On the determination of the laminar burning velocity from closed vesselgas explosion experiments”, Journal of Loss Prevention in
the Process Industries, 16, pp. 457–478.
107) Di Benedetto, A., Russo, P., Amyotte, P., Marchand, N.
(2010), Modelling the effect of particle size on dust explosions, Chemical Engineering Science, 65, pp. 772–779.
108) Di Benedetto, A., Maccariello, A., Russo, P. Sanchiricco, R.,
Di Sarli, V. (2013), “CFD simulations of turbulent fluid flow
and dust dispersion in the 20 liter explosion vessel”, AIChE
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Saul M. Lemkowitz et al. / KONA Powder and Particle Journal No. 31 (2014) 53–81

Author’s short biography
Saul M. Lemkowitz
Saul Lemkowitz studied chemical engineering (B.Sc.) at Rutgers University in the UnitedStates. After working at Allied Chemical Europe in The Netherlands, he studied chemicalengineering at Delft University of Technology (M.Sc. Ph.D.). He remained at Delft University, as an associate professor of loss prevention and austainability, researching dust
explosions and teaching explosion safety (later together with Prof. Hans Pasman). For almost 30 years he has also taught explosion safety to industry. While being formally retired, Dr. Lemkowitz still actively teaches at Delft University and to industry andpublishes articles.

Hans J. Pasman
Dr.Ir. Hans J. Pasman is a research professor at Mary Kay O’Connor Process Safety Centerof the Department of Chemical Engineering of Texas A&M University and emeritus professor chemical risk management of the Delft University of Technology in the Netherlands. He
has also been a member of the Dutch Council of Hazardous Substances until this council
was disbanded in 2012.
Graduated in chemical technology at Delft University of Technology in 1961, and finishinga doctor’s thesis in 1964 while employed by Shell, he joined the Dutch organisation for applied research, TNO, in 1965, performing research in reactive materials, gas, dust and energetic material explosions, investigation of industrial accidents and risk analysis, while also
managing part of the organization. He has been a member of the Working Party on Loss
Prevention and Safety Promotion in the Process Industries since 1972, and has been chairman of the International Group on Unstable Substances for 10 years, of the European Study
Group on Risk Analysis (1980–1985), of a NATO Group on Explosives (1982–1992), andchairman of the EFCE Working Party on Loss Prevention (1986–2004). In this latter capacity, he was instrumental in founding the European Process Safety Centre in 1992. He is active in writing and reviewing process safety articles and has obtained numerous awards.

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KONA Powder and Particle Journal No. 31 (2014) 82–91/Doi:10.14356/kona.2014014

Review Paper

Design of Optimum Sampling Plans for Dry Powders andSlurries †Hassan El-Shall 1* and Brij M. Moudgil 1, 2
1
2

Materials Science and Engineering, University of Florida, USA
Particle Engineering Research Center, University of Florida, USA

Abstract
Generally, in order to learn about a certain quality of a population, a small portion (sample) is extracted andanalyzed for the desired property. In order to obtain accurate information, the sample has to represent the stream it
is taken from (plant feed, intermediate product, and/or final product). In materials processing sampling of materials(powders or slurries) is very important to the quality control and quality assurance purposes. This sample can be toolarge and has to be further subdivided, or too small and a two-stage sampler has to be introduced. In most cases, thedesired property is determined by analyzing a sample as small as a few milligrams. In this regard, obtaining a
representative sample is not as straightforward as it sounds. For homogeneous materials, it is easy to use statisticalprobabilities to estimate numbers and sizes of samples that accurately represent the whole population. However,this is not so easy in the actual practice especially dealing with inhomogeneous materials. Therefore, sampling
representativeness, perhaps the most important aspect of sampling practice is emphasized in this paper. Samplingstrategies and equipment for dry materials and slurries are discussed with links to related literature and sampling
equipment manufacturers.
Keywords: sampling, representative samples, dry powders, slurries, sampling errors, sampling equipment, samplingrules

1. Introduction
In order to learn about a certain quality of a population,a small portion is extracted and analysed for the desired
property. If the sample is extracted correctly (representative of the population), it can provide information that isused to describe the population. In powder production, as
in any materials processing operations, sampling is very
critical to the quality control and for quality assurance
purposes. Such sampling could be done on the feedstream, the intermediate products, and/or the final products. If this sample is too large then it has to be further
subdivided, and if it is too small then a two-stage sampler
has to be introduced. In most cases, the desired property isdetermined by analysing a sample as small as a few milligrams. Using a defined statistical parameter, we can determine if the sample is representative of the larger quantity.
We can utilize automatic analysis equipment in process­control sampling to minimize detrimental time delays.
The sampling process is as follows:
†
1, 2

*

82

Accepted: August 1, 2013
P.O. Box 116135, Gainesville, FL 32611, USA.
Corresponding author:
E-mail: helsh@ad.ufl.edu
TEL: 1-352-846-3557 FAX: 1-352-846-1196

1. Take a gross sample from bulk material.
2.	Divide the sample into smaller weights as requiredby the subsequent processing step. Sample crushing
and/or grinding may be needed during such step.
3. Conduct required tests.

2. Sample Weight
Variations in materials quality dictate sampling techniques. For example, materials containing wide size distributions will require more rigorous sampling than those of
close size distributions. In addition, coarse material needs
to be sampled more carefully as the desired valuable mineral could be non-uniformly distributed in all the particles.
Thus, finer materials may require less sampling thancourse ones as shown in Table 1.
To specify minimum sample size for estimating particle
distributions within allowed variance, we use a simple
approach based on a screening process in terms of binomial distribution. The particles will either pass through thescreen or not. This is clear from examining the following
example given in Perry’s Chemical Engineering handbook(1997). The sample weight needed for screen analysis canbe calculated as follows:©2014 Hosokawa Powder Technology Foundation

Hassan El-Shall et al. / KONA Powder and Particle Journal No. 31 (2014) 82–91

Table 1Minimum Weight of Samples as a Function ofParticle Size
http://www.mine-engineer.com/mining/sample_1.htm

Particle Diameter
In Inches

Minimum Weight ofSample (pounds)

0.04

0.0625

0.08

0.5

0.16

4

0.32

32

0.64

256

1.25

2048

2.5

16348

W = G (100 – G) w/V(1)

Where:
G = % weight did not pass the desired screen
w = weight of one particle remaining on that screen
V = variance = (Standard error)2
Another example is given by Allen (2003) and summarized by Davies (2009) relating a minimum weight for the
sample depending to the particle size and the variance ofthe tolerated sampling errors as expressed in the following
equation:
Ms = 1/2{ρ/φ2}{1/Wλ – 2}d3λ × 103(2)

Where:
Ms is the limiting weight in grams
ρ is the powder density in gm/cm3
Φ is the variance of the tolerated sampling error
Wλ is the fractional mass of the largest size class in thebulk
dλ is the arithmetic mean of the cubes of the largest
diameter in the size class in cm3

3. Number of Samples
In practice, there will always be some differences
between the sample and the population. Repeated samples
from the same population may also yield different results.
Therefore, it is important to answer questions such as“What are the sources of such variations?”, “What is the
optimum number of samples?”, and “How to minimize theerrors?” The answers to these questions are very importantso that cost effective and efficient sampling plans can be
designed to achieve the desired information. These sampling principles are covered by the Theory of Sampling(TOS) which, if properly applied, can lead to information
gathering at a minimum cost and in the shortest possible

time. For materials processing, there are several challenges
encountered due to the nature of the material and/or theprocessing methods (Gy, 1998). Various sampling errors
are discussed in details by Petersen et al. (2005) and will
be summarized later in this paper.
In statistics it is convenient to use the term population
for the aggregate of all possible measurements or observations of a given type. Of course, one sample (n = 1) drawn
from a population would not give enough information.
However, more samples (n = 100 for example), if properly
drawn, could be very informative about that population.
Important statistical information can be derived from theobservations. For example, the average and the variancecan be calculated as shown below.
Usually, the population is characterized by value of themean η, and the variance σ2. The information in the sample is unfolded by calculating the average, yav.
yav = (y1 + y2 + ... + yn)/n = [Σ yi]/n

(3)

i=1
In practical situations we have a sample, from which weestimate the average, as mentioned above, and the variance as:
s2 = [Σ (yi – y)2]/(n – 1) or
s2 = [Σ yi2 – (Σ yi)2/n]/(n – 1)s2

(4)

Where:
Σ yi2 = Crude Sum of Squares.
(Σ yi)2/n = the Correction Factor.
[Σ yi2 – (Σ yi)2/n] = the Corrected Sum of Squares(n – 1) = v = the degrees of freedom
Thus, s2 = the Corrected Sum of Squares/degrees of
freedom.
√s2 = standard error (s.e.)
From the Central Limit Theorem, if y1, y2 ... yn is a random sample of size n from a distribution with mean η andvariance σ2, then yav = η and the variance V = σ2/n. Itshould be noted that increasing the number of observations(samples) can lead to reduction in the variance. The implications related to sampling materials will be clarified later.
Variation in a particular result may be contributed by anumber of different sources.
For example, the yield of a chemical process on a particular day might be determined by taking one small sample of the product and submitting that sample to a single
laboratory test. Variation in the resulting observed yieldwould be contributed by:1) the intrinsic day-to-day variability of the process,2) the sampling error, and3) the analytical error.

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Before efforts can be directed at reducing the over-all
variation it is necessary to know the relative importance of
these different potential sources of variation.
To estimate these sources of variation a special hierarchical (or nested) design may be run in which two or more
samples are taken on each of a number of days, and two
more chemical analyses are run on each sample.
An analysis of variance of the results (ANOVA) makes
it possible to isolate and estimate the separate components
of variance associated with:
1) variation of the process alone,2) the sampling error alone, and3) the analytical testing error alone
As a result of such a special study, the researcher who isinterested in reducing over-all variation can direct her/his
inquiries to the process itself, to the sampling technique, orto the analytical method, as appropriate. Alternatively, she/he may increase the number of samples, or the number ofanalytical tests, so that through the process of averaging
the variance, contribution by any component may be
reduced.
Therefore, it is important to be aware of the sources oferrors in any sampling plan. These errors are summarized
below and explained in details by Petersen, et al. (2005).

4. Sampling Errors
In addition to particle size, all the constituent elementsof the stream should have an equal probability of being
represented in the sample. Thus, good sampling plans aredesigned to avoid the following errors (Petersen et al.
2005):●	Compositional error: variations caused by temporal
differences in the chemical nature of the bulk material give rise to this error. This error is usually
reduced by milling the sampling stream and taking
many sample increments from the resulting production cycle.
●	Segregation error: this depends on the nature of thematerial and the ranges of size, shape and density
distributions present. Thus, it is directly related to theamount of segregation in a lot. It can be minimizeda) by mixing or building up a well-mixed compo­
site sample from a large number of increments andb) by a correct design of the sampling system.
●	Statistical error: it is the only sampling error thatcannot be suppressed and occurs even in ideal sampling. It can be estimated beforehand and reduced
by increasing the sample size (number of samples)
as explained above.
In this paper, we will focus on mechanical extraction ofrepresentative samples of proper weight and numbers.
Manual sampling methods are also used in practice; how-84

ever mechanical sampling techniques should be used asmuch as possible to obtain best results with minimum
errors. In addition, a good sampling strategy should
involve important unit operations as emphasized by several authors (Allen, 2003, Minnitt et al., 2007, andPetersen et al., 2005) including:○ Heterogeneity characterization of new materials○	Sampling bulk material or powder only when inmotion.
○	Sampling the whole of the moving material stream
in many short increments, rather than part of thestream for the whole of the time.
○	Mixing (homogenization) well before all further
sampling steps○ Composite sampling○	Particle size reduction (comminution or milling)whenever necessary○ Representative mass reduction

5. Sampling Practice of Particulate Materials
5.1 Sampling/mass reduction tools and methods
There are several sampling tools and methods that may
be used to extract the primary sample. The choice of particular method depends on many factors including the relative
reliability, type of lot to be sampled, etc. Mass reduction isoften done via scooping devices or using specific mass
reduction devices. Some common mass reduction techniques and devices include: grab sampling, alternate shoveling, fractional shoveling, spoon method, riffle splitters,
and rational splitters. Examples of these tools are given
below for free and non-free flowing materials.

5.2 Thief or spear sampling●	There are several companies that produce and/or
sell such equipment including Samplers direct,
Sampling Systems Ltd. UK, EET Corporation, etc.
(Specific sampling equipment supplier names areprovided for information purposes only and do notnecessarily imply endorsement of the equipment by
the author) Links to these companies’ web sites are
given at the end of the paper. Sampling steps generally include,●	Thrusting the spear into the bulk (Fig. 1).
(Powder falls through holes into the spear.)●	Rotating handle and extracting spear with enclosed
sample5.3 Coning and Quartering
Sampling of small heaps is frequently done by coning

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Fig. 1 Thief or spear sampling. (Courtesy of EET Corporate,www.eetcorp.com)

Fig.   3 A photograph of a micro Riffler. (Courtesy of Quantachrome Instruments, www.quantachrome.com)

Fig. 2 Coning and quartering as described by Davies (2009).

and quartering. The heap is flattened and separated into
four equal parts by a sharp edged tool, opposite quadrants
are recombined, half the heap is discarded, and theremaining half is quartered again (Fig. 2). This process isrepeated until the desired sample mass is achieved. Quartering should not be used for the sampling of free flowing
powders. It is more accurate to sample the powder while itis being poured into a heap rather than after. It is not recommended to sample stationary free-flowing powder due
to segregation. However, if it must be done, samples
should be taken and analyzed separately to determine thedegree of segregation. Fine particles will be concentrated
in the center of the heap while coarser particles will belocated in the outer portions.

5.4 Laboratory Spinning Rifflers
There are several companies producing such splitters.
Among them is Quantachrome Instruments Company. A

Fig.   4 A picture of Chute Rifflers. (Courtesy of Sepor, www.
sepor.com)

picture of a Micro Riffler is given in Fig. 3. There are acouple of videos on the company’s web site showing theoperation of such splitters. For particles of larger size andsamples of larger mass, chute rifflers are used. A couple ofthese rifflers are shown in Fig. 4.
It should be noted that reliability of some of these methods is low as shown in the following Table 2.

5.5 Sampling non-free flowing stored material
The following points should be taken into consideration
before sampling takes place:■	It is usually assumed that the material is well
mixed, but this assumption is often incorrect and85

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Table 2

Reliability of some sampling/mass reduction
techniques
MethodEstimated Maximum error (%)

Cone & Quartering

22.7

Scoop Sampling

17.1

Table Sampling

7.0

Chute Riffling

3.4

Spinning Riffling

0.42

biased sampling results.
■ Surface sampling by scoop is unreliable.
■	Better accuracy is obtained if samples are takenfrom the body of the material by the use of a sampling spear or thief.
■	A template should be devised so that samples canbe withdrawn from various parts of the material
volume.
■	Never take scoop samples if at all possible fromheaps. If it must be done, use coning and quarteringor chute riffling of the whole heap.
■	Sampling materials in bags, bins, wagons, bottles
should not be done using scoop or spatula samples.
Try to sample the materials when the containers arebeing filled.
■	Expect large sampling errors from stored material
sampling.

Fig. 5 Screw Sampler. (Courtesy of Sentry Equipment, www.
sentry-equip.com)

5.6 Sampling from a hopper/silo
Examples of point samplers for free-flowing and nonfree-flowing materials from gravity lines and hoppers arealso given in the web site of Sentry Equipment Corporation. A picture of this sampler in operation is given in Fig.
5 below.
The sampler takes a sample when a gear motor-driven
auger draws the product to the discharge point. A schematic of similar operation is shown in Fig. 6 below (After
Davies 2009).

5.7 Sampling Flowing Streams
In this case, Terry Allen’s Golden Rules of Samplingshould be applied as suggested by Davies (2009):●	A bulk material or powder should only be sampledwhen in motion.
●	The whole of the moving material stream should besampled in many short increments, rather than partof the stream for the whole of the time.
●	The sampling cutter should be designed to introduce no bias in the sampling of the largest particles
present, and the cutter must never be allowed to86

Fig.   6 Schematic of a Screw Sampler. (Courtesy of Sentry
Equipment, www.sentryequip.com)

overflow.
●	To sample a moving stream the gross sample is madeup of a series of increments. In this case, the minimum incremental weight is given by multiplying theflow rate times the cutter width (for a traversing
cutter) and the cutter velocity. The cutter width
should be large enough (about 10 times the largest
particle diameter) so that a biased sample deficientof coarse particles may be avoided.

Hassan El-Shall et al. / KONA Powder and Particle Journal No. 31 (2014) 82–91

When sampling from a conveyor belt, it is best to sample material as it cascades over the end of the conveyor
belt as shown in Fig. 7. If this is not possible samples
must be taken from the belt itself. Some automatic samplers have a moving arm that sweeps across the belt collecting all of the materials within a particular area.
Sampling from a moving stream can be done continuallyor intermittently. Poor and good sampling procedures areshown below. A schematic drawing is shown in Fig. 8 toillustrate the reasons for such classification (Courtesy ofDavies, 2009).
In Fig. 8 (a) the sample will not represent the wholesize distribution as the course particles will not be collected together with the fine particles. However, this does
not happen in part (b). There are several samplers that canbe used for Belt Conveyor sampling such as the ones soldby Sentry Equipment Corporation [www.sentry-equip.
com] and Intersystems Company [www. intersystems.
com]. The picture of this machine is shown below. The
company’s web site contains more details as well as avideo for this sampler and others.
Point samplers for sampling granules from a screw conveyor are also among the automatic sampling devices soldby various manufacturers. An example is the one sold bySentry Equipment Corporation [www.sentry-equip.com]
shown in Fig. 9 below. Their web site contains moredetails as well as a video of an operating sampler.

6. Slurry Sampling
Slurries (a mixture of liquid and solid) are generally
easier to sample than solids. Since slurries can be pumped

Fig. 8 A schematic drawing explaining the reasons for good andbad sampling techniques. (Courtesy of Reg Davies, 2009)

Fig.   7

Sampling from falling conveyors: (a) bad samplingtechnique, (b) good sampling technique, (c) sampling
procedure to be adopted for high mass flow rate. (Courtesy of Reg Davies, 2009)

Fig. 9 Sampling a moving belt.
(Courtesy of Sentry Equipment, www.sentry-equip.com)

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through pipes and are in constant motion, we can almost
get a perfect representative sample. However, getting acomplete cross section can be difficult due to the pipes
being round. In-pipe samplers do not adequately extract
particles at the pipe walls and thus you must consider boththe location and the type of sampler in order to obtain arepresentative sample.
For accurate primary sampling, it is recommended thatyou sample at a dumping point. Samples are taken at apipe discharge point using a cross stream sampler alongwith a slurry cutter. For secondary sampling, the primary
sample can be split using a vezin sampler discussed on the
web site of Multotec Company, 2012 (www.multotec.com.
au.). Fine particles can be reduced by using a 2% cutter,
reducing the primary sample by 98%. Two or three vezinscan be used to split larger samples to final lab size volumes for the quality control testing.
In order to assure a representative sample, all material
in a process flow should have an equal probability of being
part of the sample. Typical process streams require a turbu­
lent flow to keep the slurry in suspension (speed >1.5 m/s)
as turbulence keeps the slurry well mixed. Lighter andfiner solids in slurry require a greater level of mixing.
When particles are above 100 μm in size and/or of highspecific gravity material, mixing still produces the desired
effect in the horizontal direction. We can use several
mechanical sampling equipment, as discussed below, toobtain representative samples.

6.1 Mechanical sampling equipment
For slurry that flows by gravity through launders andsloped pipes, samples are taken from the point of discharge. Samples can also be taken at an open discharge
from a vertical gravity pipe. There are two basic mechanical sampler designs for sampling material from a gravity
flow such as sampling with linear cutter motion and sampling with radial cutter motion. When equipment is properly designed and operated, both designs produce the same
result. Based on flow quantity, we can determine themechanical installation factors. Equipment suppliers
should be consulted to provide the proper design for any
particular application. For helpful information, you may
consult Perry’s Handbook of Chemical Engineering(1999).

6.2 Sampling from Pipes
In Florida phosphate industry, sampling equipment iseither home-custom made or obtained from suppliers suchas in Fig.10 from Sentry Equipment Corp. The following
is a general description of sampling slurries either flowing
under pressure or by gravity.

88

Fig. 10 Sampling a Screw Conveyor. (Courtesy of Sentry Equipment, www.sentry-equip.com)

6.2.1 Pressure Flow

We must determine the primary sample flow for process
streams under pressure. This is done by finding the balance between sampler pressure head and sample pipe friction. Outokumputechnology.com (2011) offers a fulldescription of primary samplers and criteria relating sampler specifications to pipe size and flow rates. In addition,
sentry-equipment.com offers a wide array of sampling
equipment that can be used for slurry sampling from pipes
under pressure flow or gravity flow. Fig. 11 shows anexample of such equipment (ISOLOK® SAA Automatic
Fixed Volume Sampler).

6.2.2 Gravity Flow

Gravity flowing slurries either through in launders,sloped pipes or vertical gravity flow pipe, should be sampled at the point of discharge. A vertical sample cutter canbe used for process streams at/around ambient pressure. In
order to obtain a proper sample using this technique, youmust ensure that the cutter used has an opening manytimes larger than the largest particle size of sample slurry(preferably greater than 20 mm, no less than 8 mm). You
can use an adjustable cutter opening to adjust sample flowfor pipe sizes up to 400 mm. Several sampling steps or
innovative sampling designs are required
Outokumputechnology.com (2011). In addition to Outokumputechnology (now Outotec), Sentry Equipment Corporation and other suppliers have several samplers thatcan be used for this purpose. These companies’ web sites
are given below to guide you to choose the best sampler
for your application. Another example of samplers thatcan be used for flowing streams either under pressure orunder gravity is shown in Fig.   11 as published by Sentry
Equipment Corporation (2011).
There are other types of samplers using linear androtary traverse mechanisms. The following is an exampleof how to calculate amount of sample in every increment

Hassan El-Shall et al. / KONA Powder and Particle Journal No. 31 (2014) 82–91

ISOLOK® SAA Automatic Fixed Volume Sampler
Captures 3 or 8 cc per cycle of liquids and slurries

ISOLOK® SAB Automatic Fixed Volume Sampler
Captures 10 or 25 cc per cycle of liquids and slurries

Fig. 11 In-line Sampling Equipment for Pressure Flows.
(Courtesy of Sentry Equipment www.sentry-equip.com)

Fig.    12 Automatic Sampler for Tanks, Mixers, and Reactors.
(Courtesy of Sentry Equipment www.sentry-equip.com)

as mentioned in Perry’s Handbook of Chemical Engineering (1997).

6.2.4 Calculation of Sample Extraction Increments

6.2.3 Slurry Sampling by Rotary Traverse of Gravity
Flow

Given the following information, the quantity of slurry
extracted by one rotation, S, can be calculted.
S = increment volume (quantity of slurry extracted by
one rotation)
B = bulk slurry flow, in volume/unit timeR = rotation of cutter, in rpm
D = cutter angle opening, D/360 = extraction ratio forcontinuous cutter rotation
S = D × B/360 × R(5)In addition to mechanical sampling equipment, handsampling can be used to obtain samples from gravity flowing material from chutes, vibrating screens, belts, etc.
When sampling from such streams, it is best to sample
material as it cascades over the end of the equipment as
explained earlier in the case of belt conveyors.
Suppliers of sampling equipment are eager to help inchoosing the proper samplers for specific applications.
Another example of such equipment is presented in Fig.
12 as a courtesy of Sentry Equipment Corp. The ISOLOK®
SAB operates when compressed air forces the plunger into
the process line to capture a fixed volume of material.
Compressed air then acts on the opposite side of the piston
to retract the plunger to a position which allows the sample to drop by gravity into a container. The operator is isolated from the process at all times by the sampler’s seal
design, and the sample captured in the container is “lockedout” from external influences. The reader is advised toconsult the manufacturer catalogue for further details.

Cooper in Perry’s Handbook of Chemical Engineering(1997) presents clearly several examples illustrating calculation of incremental weights obtained by three commonly used sampling methods. These methods include: (a)Linear Traversing Trajectory Cutter, (b) Slurry Samplingby Rotary Traverse of Gravity Flow as explained above,and (c) Cross-Belt Sampling of Solids from Conveyors

6.2.5 Processing Wet Samples

Collected samples are dried in air and/or ovens provided
that drying does not affect the chemistry of the sample
contents. The dried samples then will be treated as dry
powder sampling procedure explained earlier.

7. Summary Highlights of Sampling Rules
Several authors including Allen 2003, Davies 2009, Gy
1998, 2004a, 2004b, Minnitt et al. 2007, and Petersen etal. 2005 stressed the importance of the following points:
There are several sampling tools and methods that may
be used to extract the primary sample. The choice of particular method depends on many factors including the relative reliability, type of lot to be samples, etc. It should be
noted that reliability of some of these methods is low.
It is usually assumed that the material is well mixed,
but this assumption is often incorrect and biased sampling results.
Select general guidelines for obtaining reliable sampling
results are as follows.
●	Never take scoop samples if at all possible fromheaps. If it must be done, use coning and quarteringor chute riffling of the whole heap.
●	Sampling materials in bags, bins, wagons, bottles
should not be done using scoop or spatula samples.

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Try to sample the materials when the containers arebeing filled.
●	A bulk material or powder should only be sampledwhen in motion.
●	The whole of the moving material stream should besampled in many short increments, rather than partof the stream for the whole of the time.
●	When sampling from a conveyor belt. It is best to
sample material as it cascades over the end of theconveyor belt. If this is not possible samples must
be taken from the belt itself.

Acknowledgements, Copy right statement anddisclaimer
Financial support of this work was provided by theCenter for Particulate and Suspension Systems (CPaSS) a
NSF I/UCRC (NSF Grant #0749481). Opinions expressed
are those of the authors and do not necessarily represent
the views of the NSF or the CPaSS Industry Members.
Commercial suppliers of the various equipment are provided for information purposes only and do not necessarily
imply endorsement of the specific equipment by theauthors.

References
Allen T., Powder sampling and particle size determination, firsted., Elsevier, New York, 2003.
Cooper H., Sampling of Solids and Slurries in Solid-Solid
Operations and Equipment, section 19, Perry’s Handbookof Chemical Engineering, seventh edition, McGraw-Hill,
1997.

90

Davies R., Sampling Particulate Materials, A short course atParticle Engineering Research Center, University of Florida, (April 2009).
Gy P., Sampling for analytical purposes, John Wiley & Sons,
New York, 1998.
Gy P., Sampling of discrete materials, A new introduction to thetheory of sampling: I. Qualitative approach, Chemometrics
and Intelligent Laboratory Systems, 74(1) (2004a) 7–24.
Gy P., Sampling of discrete materials: A Quantitative approach—sampling of zero-dimensional objects, Chemometrics andIntelligent Laboratory Systems, 74(1) (2004b) 25–38.
Minnitt R.C.A., Rice P.M., Spangenberg C., Part 1: Understanding the components of the fundamental sampling error: A
key to good sampling practice, Journal of the South African
Institute of Mining and Metallurgy, 107(8) (2007) 505–511.
Petersen L., Minkkinen P., Esbensen K.H., Representative
sampling for reliable data analysis: Theory of sampling,
Chemometrics and Intelligent Laboratory Systems, 77(1-2)(2005) 261–277.

Links to Literature● The Accuracy of Systematic Sampling from Conveyor Belts:
http://www.jstor.org/stable/pdfplus/2985832.pdf● Sampling equipment:
http://www.powderandbulk.com/analyzers/samplers.htm● Belt conveying equipment:
http://www.powderandbulk.com/conveying/belt.htm
http://www.directindustr y.com /industrial-manufacturer/
bulk-and-powder-handling-and-equipment-152/conveyor­belt-61357.html
http://www.ktron.com/products/pneumatic_conveyors/index.
cfm
http://www.flexicon.com/us/products/PneumaticConveyingSystems/­
index.asp
http://www.vac-u-max.com/pneumatic.html

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Author’s short biography
Hassan El-Shall
Dr. El-Shall is a professor emeritus at the Department of Materials Science and Engineering of University of Florida. He has been serving as an associate professor of Materials Science and Engineering and Associate Director for Research at The Particle
Engineering Research Center of University of Florida since 1994. He also served as
Associate Director for beneficiation research at the Florida Institute of Phosphate
Research from 1986–1992. In the early 80’s, he has served as assistant professor of Mineral Processing at Montana Tech from 1980 to 1986. He posses thirty nine years ofdiverse experience in research (both basic and applied), management, as well as hands-on
experience in the areas of Applied Surface and Colloid Chemistry, Mineral Processing,
Chemical Metallurgical Engineering, and related environmental services. His work
related to industrial minerals such as phosphate, gypsum, clay, etc is recognized by his
peers allover the world. In addition, he has extensive and practical experience in thedevelopment of training and teaching programs for both undergraduate and graduate students in the above fields. His major research interests include interfacial phenomena andits applications in mineral industry, and waste treatment in various industries. He
expanded his research efforts to include mineral modifications for medical applications.
Dr. El-Shall has published over 165 publications including: 11 patents, 9 edited books,
one authored manual, 19 chapter contributions to books, over 50 Refereed articles inprestigious journals such as Powder Technology, Mineral and Metallurgical Processing,International Journal of Mineral Processing, and others, in addition to many industrial
reports.
Dr. El-Shall is a dedicated teacher in the fields of Mineral processing Engineering,
Materials Science and Engineering, and Chemical Engineering. He has served as chair,co-chair, or a member of over 50 graduate committees for M.S. and Ph.D. students
including his own 15 M.Sc. and 13 Ph.D. students who are currently employed by various
industries.

BRIJ M. MOUDGIL
Dr. Brij M. Moudgil is a Distinguished Professor of Materials Science and Engineering, Director of the Particle Engineering Research Center (PERC), and the Center for
Particulate and Surfactant Systems (CPaSS–NSF I/UCRC) at the University of Florida,
Gainesville, FL. Dr. Moudgil also serves as the Director of the UF Mineral Resources
Research Center. He received B.E. (Metallurgy) degree from the Indian Institute of Science (IISc), Bangalore, and M.S. and Eng.Sc.D. Degrees in Mineral Engineering from theHenry Krumb School of Mines, Columbia University, New York, NY. His research andprofessional leadership accomplishments are recognized by several major awards including his election to the National Academy of Engineering (NAE), U.S.A. He has been also
elected as Foreign Fellow of the Indian National Academy of Engineering. He is recipientof the 2003 Distinguished Alumni Award of the Indian Institute of Science, Bangalore. He
served as 2006 President of the Society for Mining Metallurgy and Exploration, Inc.
(SME). His current research interests include engineered particulate systems for enhanced
performance in nano and bio technologies, advanced materials and minerals, microelectronics, photocatalytic degradation of hazardous microbes, nanotoxicity, and greener
reagents and particle technologies.

91KONA Powder and Particle Journal No. 31 (2014) 92–110/Doi:10.14356/kona.2014015

Review Paper

Versatile Fabrication of Complex Shaped Metal Oxide
Nano-Microstructures and Their Interconnected Networks
for Multifunctional Applications †Yogendra Kumar Mishra 1*, Sören Kaps 1, Arnim Schuchardt 1, Ingo Paulowicz 1, Xin Jin 1,
Dawit Gedamu 1, Sebastian Wille 1, 2, Oleg Lupan 1, 3 and Rainer Adelung 1
1

Functional Nanomaterials, Institute for Materials Science, University of Kiel, Germany
Department of Prosthodontics, Propaedeutics and Dental Materials, University Medical Center Schleswig-Holstein, Germany
3
Department of Microelectronics and Semiconductors Devices, Technical University of Moldova, Republic of Moldova

2

Abstract
Metal oxide nano-microstructures are applied in photocatalytic surfaces, sensors or biomedical engineering, proving
the versatile utilization of nanotechnology. However, more complex or interconnected nano-microstructures are still
seldomly met in practical applications, although they are of higher interest, due to enhanced structural, electronic
and piezoelectric properties, as well as several complex biomedical effects, like antiviral characteristics. Here we
attempt to present an overview of the novel, facile and cost-efficient flame transport synthesis (FTS) which allows
controlled growth of different nano-microstructures and their interconnected networks in a scalable process.
Various morphologies of nano-microstructures synthesized by FTS and its variants are demonstrated. These
nano-microstructures have shown potential applications in different fields and the most relevant are reviewed here.
Fabrication, growth mechanisms and properties of such large and highly porous three-dimensional (3D)interconnected networks of metal oxides (ZnO, SnO2, Fe2O3) nano-microstructures including carbon based
aerographite material using FTS approaches are discussed along with their potential applications.
Key words: Flame transport synthesis, metal oxide, ZnO, SnO2, Fe2O3, nano-microstructures, nanorods, nanowires,interconnected tetrapods networks, multifunctional applications, aerographite

1. Introduction
Metal oxide nano-microstructures such as nanorods,
nanowires, nanobelts, nanotetrapods and others are being
significantly investigated due to their new and extraordinary properties appropriate for versatile nanotechnologicalapplications1–3). Fabrication of several nanostructures fromvarious metal oxides like ZnO, SnO2, TiO2, and Fe2O3 hasalready been performed using several growth techniques
and their properties have been reported1–4). Among them,ZnO is one of the most investigated materials in the last
decades, because of its wide and direct bandgap of~3.37 eV, large exciton binding energy ~60 meV and simplicity in growth1–3, 5). Due to its hexagonal-wurtzite crystal

†
1
2
3

*

92

Accepted: August 20, 2013
Kaiser Str. 2, D-24143, Kiel, Germany
Campus Kiel, Arnold-Heller-Str. 3 - Haus 26, D-24105, Kiel,
Germany
168 Stefan cel Mare Blvd., MD-2004, Chisinau, Republic ofMoldova
Corresponding author:
E-mail: ykm@tf.uni-kiel.de
TEL: +49-431-880-6195 FAX :+49-431-880-6124

structure, Zn and O terminated polar surfaces, different
growth rates of the diverse crystal planes, quasi-1-Dimensional (Q1D) nanostructures and complex morphologies
from ZnO can be synthesized. The direct bandgap whichlies in the near ultraviolet -(UV) spectral region and alternating Zn and O stacking layers enable ZnO nanostructures to exhibit exceptional optical, luminescent6, 7) andelectrical properties5, 8–11). Bendability is also a very important property required for different applications but
bulk ceramics or metal oxides are brittle in nature1–3).
However, their Q1D structures can bent elastically to larger curvatures once their thickness is in the nanoscopic
range1–3, 12). Nanorods and nanowires from ZnO have already shown interesting piezoelectric properties for energy
or mechanical applications1–3, 13). Illumination of ZnO nanostructures with UV light creates electron-hole pairs andthus changes their conductivity and enables its uses forphotodetectors14–19). Additionally ZnO nano-microstructures
are extensively investigated for light emitting diodes andgas sensing applications14, 20–22). By doping with different
elements it is possible to enhance the sensing performances of ZnO nanostructures23, 24). ZnO nanostructures havealso been considered as biocompatible material and©2014 Hosokawa Powder Technology Foundation

Yogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

therefore have been significantly employed in biomedical
applications25–29). Furthermore, the interconnected nanostructures can build up microstructures or even highly porous 3D interconnected macroscopic networks which
avoid risks of toxicity as a result from nanoscale particles.
However, several issues like actual effect and cytotoxicity
are still open25, 30). In general, various physical and chemical properties of different metal oxide nanostructures depend not only on their sizes and morphologies, but also on
the synthesis techniques and experimental conditions (ortechnological ‘history’). Despite of such interesting applications, the scientific community is still looking for appropriate synthesis techniques, which can facilitate theversatile fabrication of different networked metal oxide
nano-microstructures for practical applications in a
cost-effective and scalable process.
Several synthesis methods have been utilized for growing different metal oxide nano-microstructures. Vapor-­liquid-solid (VLS) mechanism31) has been a very common
process for controlled growth of ZnO nanostructures like
nanorods32, 33), nanowires34), nanotrees35), and interpenetrating ZnO nanosails bridge36) at junctions, etc. Other methods
like hydrothermal synthesis37–39), chemical vapor deposition(CVD)40), microwave chemistry41), combustion synthesis42),
plasma process43, 44), electrochemical deposition14, 45, 46), gas
phase synthesis47) and flame based synthesis48–51) have been
employed to grow metal oxide nanostructures, especiallyZnO nanostructures. Thus, an easy scalable, cost-effective
and facile synthesis method which can produce large
amounts of different metal oxide nano-microstructures isstill a highly demanded aspect for various applications.
Although most of the mentioned synthesis methods enable controlled growth of metal oxide nanostructures, butthey lack with the feature of in-situ integration of suchnanostructures directly on the chip in form of device. One
requires nanoscale electrical contacts and this further hinders their application. To overcome such technologicallimitations a thin film fracture approach52) was invented
recently. It allows direct fabrication of desired metal or
metal oxide nanostructures between the electrical contacts
on the sensor or device chip53–55). However, most desirable
technological procedures are based on facile growth anddirect integration of nanostructures on chip in a single step.
Fabrication of large and porous 3D networks from interconnected metal oxide nanostructures might be an ideal choicefor utilizing its nanoscale properties at macroscopic scalefor different industrial technologies. It is important to mention that it has not been explored in details yet. Only few
groups56, 57) have reported fabrication of 3D networks frommetal oxide nanostructures using different techniques.
Recently Adelung and co-workers58, 59) have introduced
a very simple and novel flame transport synthesis (FTS)
approach which allows facile fabrication of versatile
metal oxide nano-microstructures and their macroscopic

networks. These FTS synthesized metal oxide nano-­
microstructures have already shown promising applications in different directions60–66). ZnO nanoseaurchin andtetrapod type structures grown by FTS approach exhibit
strong potential of blocking the viral (herpes simplex virus
type-1 and type-2) entry into the cells60, 61). The submicronsize tetrapods can be utilized for advanced linking technologies64) and designing multifunctional composites,e.g., new concept of self-reporting material65). In thiscontext, FTS approach offers a simple way to fabricate
large size 3D networks from interconnected metal oxide
nano-microstructures with desired porosity and mechanical strength. These 3D networks are stable at high temperatures (up to ~1400°C), electrically conducting andtherefore can be used in advanced technological applications57). Recently, such 3D interconnected ZnO tetrapods
networks were used as templates for the guided growthof the carbon based new aerographite material, which iscurrently one of the least dense materials in the world67).
In this paper, we present the growth of different metaloxide nano-microstructures and their interconnected 3D
networks by FTS approach and its variants. Different morphologies, growth mechanisms and properties of nanomaterials are presented and discussed in detail.

2. Experimental
2.1 Materials Requirements
Flame transport synthesis (FTS) method and its variants59) mainly require microscale diameter spherical metal
particles as precursor materials, sacrificial polymer (e.g.,
polyvinyl butyral (PVB), etc.) and ethanol for mixing homogeneously in slurry form. In our works59), different
metal particles powders (Zn, Fe, Sn, Bi, Al, Si etc.) withdiameters in the range from 3 μm to 45 μm have been used(purchased from GoodFellow UK, purities 99.9% to99.99%). PVB powder (supplied by Kuraray Europe
GmbH, Germany) was used as sacrificial polymer for thepresented experiments. A simple muffle type furnace
which can rapidly heat up to high temperatures was used
for our experiments. Also, in these experiments, no gas
control or vacuum equipment is necessary because it works
in normal air environment. Some ceramic plates, crucibles,
and cylinders and conventional burner type equipments are
required for different variants of FTS approach59).

2.2 Flame transport approach and its variants
The first variant of FTS approach (Fig. 1a) enables the
fabrication of nanoseaurchin type structures59). For this process the slurry mixture of precursor metal -microparticles,
PVB powder and ethanol is prepared in appropriate ratio

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Yogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

and coated on desired substrates (Si, Aluminum etc.).
After drying the coated layer on the substrate, it is heatedat different temperatures (depending upon the type of precursor metal microparticles) and formation of nanoseaurchin type structures occurs. For example, to synthesize
ZnO nanoseaurchins, a temperature above 550°C is sufficient. According to our experimental evidence for ironoxide nanoseaurchins, the optimum temperature is about
900°C. By increasing the precursor metal particle ratio versus PVB in the slurry and by increasing the thickness of thecoated layer, it was possible to fabricate a 3D networkfrom nanoseaurchins (Fig. 2a) in a similar manner. The
second variant of FTS approach allows direct transformation of precursor metal microparticles into metal oxide
nano-microstructures in powder form (Fig. 3a–3d). The
mixture Zn:PVB with ratio 1:2 was filled in the ceramic
crucible and heated up to 900°C, which results in formationof different ZnO nano-microstructures in form of powder.
These nano-­microstructures can be harvested from the furnace and accordingly utilized for desired applications59).
The yield per experiment mainly depends on the several
factors like ratio of Zn to PVB, amount of Zn and PVB
mixture and temperature of the furnace etc. In each standard
experiment for ZnO tetrapods production (Zn:PVB = 1:2,
900°C, 30 minutes) the yield was around 30–40% and ineach experiment and we harvest about 15–20 grams of ZnO
tetrapods depending upon initial conditions. The third variant of FTS approach utilizes an in-house ceramic cylinder
arrangement (Fig. 5a) and it enables controlled synthesis ofdifferent quasi-1D nano-microstructures and their networked bridges. The fourth variant utilizes a simple burner
approach (Fig. 6a) in which the precursor metal microparticles are directly inserted into the oxygen and propane gas
mixture inside the burner tube. On their way in the flame,these precursor metal microparticles are converted into various metal oxide nano-microstructures within milliseconds
and can be collected in form of powder or in-situ integrated
on the substrate/chip as per requirements59). The main aimof this paper is to provide an overview of different structures, which can be synthesized using proposed FTS approaches for practical applications. More technical details
about ratios, growth conditions, temperature time and substrate positions can be found in previous works58, 59).

2.3 Characterizations:
The obtained nano-microstructures by FTS approachwere characterized using scanning electron microscope(20 keV Philips-FEI XL30 equipped with LaB6 filament).
Electromechanical measurements of Q1D, 2D and 3D networks were performed by using a home made setup which
includes a micro-manipulator, a Keithley 2400 Sourcemeter, and a computer-controlled laboratory balance with thehelp of a LabView program59).

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3. Results and discussions
3.1 Growth of metal oxide nanoseaurchin structuresusing first variant of FTS approach
Fig. 1 demonstrates the growth mechanism of nanoseaurchin type structure and few examples of already synthesized nanoseaurchins from different metal oxides (ZnO,
SnO2, Fe2O3, Al2O3, Bi2O5). To grow ZnO nanoseaurchins,a dilute slurry mixtures from Zn, PVB and ethanol [Zn:{PVB:Ethanol}=1:3{1:2}] was prepared and coated on Si
substrates. After drying the slurry coated substrate washeated at 600°C in the muffle furnace for 2 hours. Depending upon the requirements the ratios of Zn, PVB and ethanol were varied and the coated substrates were heated
above 600°C for different durations to synthesize various
types of seaurchins59). In similar manner, nanoseaurchinsof several other metal oxides have been successfullygrown and can be found in previous work59).
For the growth of core-spike nanoseaurchins (Fig. 1),
the crystalline quality of precursor metal micro-particles
as well as processing temperature play very importantroles. The sacrificial polymer (PVB) and ethanol mixture
exhibit double roles: (i) it maintain necessary separation
between precursor microparticles which prohibits the agglomeration of metal microparticles and (ii) during heating it provides necessary local environmental control fornanospike growth on the surface of microscopic core. Also
above certain temperature (below the nanospike growth)
the PVB decomposes entirely and leaves no fingerprints
behind in the grown seaurchins or nanostructures, since it
contain only C and O. The heating ramp rate of the furnace is the most important parameter for growth of nanoseaurchins, e.g., faster heating rates result in a better
growth of such micro-nanostructures (we used furnacewith ramp rate above 100°C/min). It has been observedthat the metal oxide nanospikes were synthesized on thesurface of precursor metal microparticles only when thegrowth condition is far from thermal equilibrium. Under
such circumstances, the kinetic growth processes dominate
and it leads to a nanospike growth on the substrate/crucible surface. This type of the spherical precursor microparticles exhibit surface defects, like reconstructed surface
and grain boundaries68). It seems that the grain boundaries
most likely offer the energetically favorable nucleationsites to initiate the nanospike growth68). These nanospikes
were investigated in details using cross-sectional high resolution transmission electron microscopy along with precession electron diffraction studies and it was observedthat they consist of twin boundary propagating along thec-axis69). Such ZnO nanoseaurchin structures show theirpromising application as potential candidate for blocking
the viral (HSV-1) entry into the cells60). Further work on
this kind of micro-nanostructures is in progress.

Yogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

Fig. 1(a) Schematic drawing demonstrating the formation of core-spike nanoseaurchin type structure. (b)–(g)Nanoseaurchins of different metal-oxides (ZnO, SnO2, Fe2O3, Al2O3, Bi2O3) grown by using FTS
approach. (b) & (c) Two typical examples of ZnO nanoseaurchins grown at 900°C. (d) Tin oxide nanoseaurchin structure grown at 950°C. (e) Core-spike nanoseaurchin from iron-oxide obtained at 900°C. (f)Aluminum oxide nanoseaurchin grown by FTS approach (shown in 1a). (g) Bismuth oxide nanooctopus
type structure with branched nanoscopic arms fabricated at 900°C. [Partially reproduced from Fig. 1 withpermission from59)].

As mentioned already that growth of 3D interconnected
network from metal oxide nanostructures is a highly demanded aspect for practical applications. Using the growthconcept of nanoseaurchins, we have successfully grownlarge 3D interconnected networks from core-spike nanoseaurchins. The schematic drawing for 3D network growthis demonstrated in Fig. 2a in which a thick layer of slurry
mixture is coated on the substrate. The ratio of metal microparticles, PVB and ethanol is kept in such a mannerthat the precursor metal particles are homogenously dispersed in the slurry and during coating they are well separated by sacrificial polymer layer (mixed with ethanol).
After drying the substrate with slurry is heated rapidly up
to higher temperature (typically ~600°C for ZnO, and~900°C for Fe2O3, SnO2, Bi2O3 and Al2O3)59). Because of
rapid heating process, the growth of nanospikes on surface
of precursor metal particles is initiated like demonstrated
in Fig. 1. The sacrificial polymer layer plays a crucial role
here as it maintains the necessary separation between microscopic particles and at the same time nanospikes growand form interconnecting bridges between individual
cores59). These interconnecting nanospike bridges provide

mechanical strength to the network59). Using this concept,
large 3D interconnected networks from ZnO nanoseaurchins were successfully grown and are shown by zoomin series of SEM images in Fig. 2(b–d) (from left to right).
The interconnecting nanospike bridges can be clearly seen
in high magnification SEM image in Fig. 2d.
A large 3D network from ZnO nanoseaurchins grownon Aluminum substrate (shown in Fig. 2e) following asimilar FTS approach. Such kind of networks were investigated by SEM and confirmed that it is entirely madefrom interconnecting core-spike nanoseaurchins, as presented in Fig. 2(f). Its corresponding higher magnification
SEM image is shown in Fig. 2(g). The 3D networks fromZnO nanoseaurchins have been successfully grown andoptimized. However experiments for other metal oxide 3D
networks are currently under progress.
The second variant of FTS approach enables direct conversion of precursor metal microparticles into nanostructures within the flame created due to burning of sacrificial
polymer (PVB). The mixture of precursor metal microparticles and PVB (1:2 ratio by weight) is filled in the ceramic
crucible which is placed inside the furnace and heated95

Yogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

Fig. 2 (a) Fabrication principle of 3D interconnected networks by assembling nanoscale seaurchins. The precursor metal microparticles are mixed with sacrificial polymer and ethanol and then coated on substrate.
During heating, the sacrificial polymer decomposes completely and at the same time the nanospikes growand establish the interconnections among microscopic cores which provide the mechanical strength to the
network. (b)–(d) SEM images from a 3D interconnected ZnO nanoseaurchins network at increasing magnifications (from left to right) synthesized by approach described in (a). (e) Digital camera image a 3D
ZnO nanoseaurchins network synthesized using Aluminum substrate. (f) and (g) SEM images from the 3Dinterconnected network (shown in e) at higher magnifications (left to right). [Partially reproduced from Fig. 1
with permission from59)].

rapidly up to temperature of 900°C (for Zn microparticles). Because of high heating rate the PVB starts burningand creates intense flame59). Then, the precursor metal
microparticles travel in the flame stream and due to of highflame temperature are converted in ZnO nano-microstructures. After reaching 900°C, the temperature of the furnace
is maintained constant for different time spans (ranging
from 30 minutes to 4 hours depending upon the requirements) for proper growth of specific nano-microstructures.
The role of sacrificial polymer (PVB) is very important in
FTS process, as it maintains the separation of metal microspheres, creates the flame and also enables necessary environmental conditions for nano-microstructures growth59).
The conversion principle of precursor metal microparticles into the flame is demonstrated in Fig. 3a. For simplicity reasons only two types of structures (tetrapods andmultipods) are shown in the schematic however structureswith various complex morphologies have been grown.
Fig. 3b shows the digital camera image of the on going
FTS process and the intense yellow flame in the centre
shows the turbulent stream of flame in which microparticles

96

are being converted into nano-microstructures. Once theprocess time is achieved, the furnace was turned off. Aftercooling one can see the crucibles and the base of the furnace are entirely covered with snowflake type white powder (Fig. 3c). These snowflake type powders consist of
tetrapods, multipodes, branched ZnO nano-microstructures
depending upon the location in the furnace. The snowflake
type powder was harvested from positions 1 and 2 (Fig.
3c) was analyzed inside SEM. Morphological studies ofthe powder harvested from position 1 (Fig. 3c), i.e., fromthe crucible, revealed that it mainly consists of ZnO tetrapod structures with different sizes as shown by SEM images
in Fig. 3(d–f) at increasing magnifications (from left toright). However, the fluffy powder at the base (position 2,
Fig. 3c) consists of ZnO tetrapods, ZnO multipodes andseveral other complicated shapes as evident by SEM images in Fig. 3(g–i) at increasing magnifications (from left
to right). The ZnO tetrapod and multipode structures canbe harvested and can be utilized accordingly for desired
applications. The ZnO tetrapods have shown promising
applications, as antiviral agents60, 61), in advanced linking

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Fig. 3 Flame transport synthesis of different nano-microstructures: (a) Schematic drawing showing the conversion
principle of precursor metal microparticles into different nanostructures by flame; (b) digital photograph ofongoing flame transport process in the furnace. The mixture of precursor metal microparticles and sacrificial
polymer powder are filled (~60% by volume) into ceramic crucible and then heated in the furnace at 900°C.
The intense yellow flame in the centre of crucible shows the ongoing flame transport process. (c) Digital
photograph of the furnace chamber after the flame transport process. The converted nano-microstructures aredeposited everywhere inside the furnace. These structures can be harvested from different locations (e.g., 1
and 2 within the crucibles and at its base). (d)–(f) SEM images of ZnO tetrapods at increasing magnifications(from left to right) harvested from location 1. (g)–(i) Zoom series (from left to right) of SEM images from thefluffy powder harvested from the base of the furnace (location 2 in image c) showing formation of tetrapod,
multipods and their mixed structures. [Partially reproduced from permission from59)].

technology64) and designing self-reporting composites65).
Since growth of desired 3D networks was the strong
motivation for our research, the harvested ZnO tetrapods
from second variant of FTS were further processed to synthesize different interconnected networks59). Appropriate
amounts of tetrapods were filled in open cylindrical ceramic scaffolds, pressed and reheated at high temperature(~1150°C) for 4 hours. Such a reheating results in the formation of interconnections between tetrapod arms providing
mechanical strength to the entire network59). For example,
the 3D ZnO networks fabricated using this approach isshown in Fig. 4a. These 3D networks were analyzed inside
SEM in details to study the underlying growth process. Fig.
4(b–d) shows the SEM images taken inside the network at
different magnifications. It is clearly visible that at someplaces the tetrapod arms interpenetrate fully (Fig. 4d is ahigh magnification of Fig. 4b) and at some places they interpenetrate partially (Fig. 4c). It seems that formation ofinterconnections initiates from the positions where the arms
are touching each other during re-heating. However, further
investigations for understanding the exact mechanism ofarms’s interpenetrations are under progress59).
Based on proposed approach macroscopic and highly porous (up to 98%) 3D interconnected networks were fabricated using ZnO tetrapods59). These networks are electricallyconducting and high temperatures stable (up to 1400°C).
Flexibility of 3D porous networks is a very important property which enables their use for various applications. It wasobserved that by varying the density, one can tune the elastic modulus of these networks from few kPa to rubber elastic region (less than 100 MPa) and thus they fall in the
category of flexible ceramics59). These flexible conducting
highly porous 3D interconnected networks exhibit potential
applications for new advanced technologies. Recently, these3D networks have been used as templates for guided growthof carbon based aerographite material67).
The third variant of FTS offers controlled growth of different Q1D metal oxide nano-microstructures employing
the cylindrical arrangement as shown in Fig. 5(a). The precursor metal microparticles, sacrificial polymer and ethanol
mixture (in form of slurry) is placed in the crucible and thesubstrates can be mounted at positions 1 to 4 (Fig. 5a) for97

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Fig. 4Fabrication of the 3D interconnected networks from the ZnO tetrapod powder (shown in Fig. 3d). Appropriate amounts of ZnO tetrapods were filled in ceramic crucible and re-heated at high temperatures(between 1100°C to 1200°C) for 4–5 hours. (a) Digital camera image of the 3D network tablets obtained
after heating the ZnO tetrapods in the ceramic scaffolds (at 1150°C for 4 hours). (b)–(d) SEM images fromthese 3D network tablet confirming the formation of interconnections between the tetrapod arms. Formationof partial (c) and full (d) interpenetrations between the tetrapod arms can be seen. [Partially reproduced
from permission from59)].

different nano-microstructures. The cylindrical arrangement
is inserted into the furnace and heated at high temperaturesin air environment. The cylinder arrangement enables further control on the nanostructure growth process and Q1Dnanostructures, like nanorods, nanowires, nanonails andtheir large arrays can be grown in a controlled manner59).
The conversion mechanism of precursor microparticles in
the flame is similar like mentioned in Fig. 3(a) but inclusionof ceramic cylinder adds extra features. At positions 1 and 4(Fig. 5a), the nanostructure growth process is almost similar
to that demonstrated in Fig. 3.
Nano-microstructures grown at position 2 and 3 (Fig.
5a) are quite different, because position 3 is located inside
the cylinder at the base surrounding the crucible and position 2 on the top holes, where substrates are mounted vertically downwards. SEM studies from structures depositedon position 1 (Fig. 5a) confirmed the growth of different
types of ZnO tetrapods, as shown in Fig. 5b and Fig. 5c.
Growth of different Q1D nanorods and their arrays occurs
on substrates mounted at position 2, (Fig. 5a). On substrates at position 3, located inside the cylinder, more converted nano-microstructures are deposited during growth
process and therefore 3D networks are formed. These 3D
networks are quite different as compared to those obtained98

by reheating the tetrapods (Fig. 4). Since growth and interpenetration simultaneously occur at position 3, these 3D
networks are much stiffer and exhibit relatively higher
elastic modulus59).
The fourth variant of FTS approach utilizes a burner
equipped with Oxygen and Propane gases for the flameas shown in Fig. 6a59). The precursor Zn microparticles
are inserted into the gas stream in controlled manner andthey travel along with the flame when coming out fromthe nozzle. During their travel, these precursor metal microparticles are converted into nano-microstructures because of very high flame temperature of the flame. These
nano-microstructures can be deposited on the substrates orcollected in form of powder depending upon the requirement.
The 3D interconnected networks can be synthesized if
process is continued for longer durations at same locations59). The conversion of Zn microparticles into nano­microstructures depends on transport time within the flameand transformation stages as marked by positions 1, 2
and 3 (Fig. 5a). A large copper plate coated with ZnO
tetrapods using burner approach is shown in Fig. 6b. The
SEM images (1–3) presented in Fig. 6 correspond to particle transformation stages shown in Fig. 6a. The image 4 inFig. 6 shows SEM of a single ZnO nanotetrapod, whichYogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

Fig. 5(a) Schematic drawing demonstrating the controlled variant of FTS approach using a ceramic cylinder. The
crucible in centre contains the slurry mixture and the substrates are mounted at positions 1 to 4. (b) & (c)SEM images for different ZnO tetrapod structures grown at substrate mounted at position 1. At position 2(top cover of cylinder having holes) the substrates are symmetrically mounted with the desired surface
pointing vertically downwards towards the crucible. Typically quasi-1D nano-microstructures and theirarrays grow at position 2. (d)–(f) SEM images of different ZnO nanorods array grown on Si substrate at
position 2. (g)–(i) SEM images of different types ZnO tetrapods networks grown at position 3 inside thecylinder. (j)–(l) SEM images of different types of ZnO structures i.e., flowers, dumbbells, bolts and othermorphologies were grown at substrate mounted at position 4. Nano-microstructure grown at positions 1
and 4 are almost same. For demonstration reasons, only few structures are shown here. [Partially reproduced from Fig. 2 with permission from59)].

was coated on copper plate. More details about different
experiments are elaborated in previously publishedpaper59) and experiments are still under progress to optimize the growth of other metal oxide nano-microstructures. The FTS grown nano-microstructures have alreadyshown promising applications and few are summarized in
the next section. Recently using burner-FTS approach, aninterconnected ZnO nanotetrapods network bridge was
directly integrated between electrodes in a chip for UV
photodetector applications which demonstrated very fast
photodetection response70).

4. Applications of the ZnO networked structures
4.1 Antiviral activity of ZnO nanoseaurchins andtetrapods against HSV-1
The synthesized structures by FTS approach were tested
for antiviral applications and it was observed that ZnOnanoseaurchins and tetrapods (shown in Fig. 7a and 7b)
block the HSV-1 viral entry into cells60). The confocal microscopy images (A–C) in Fig. 7c confirm the attachmentof viruses on the surface of ZnO structures. The plot D in
Fig. 7c shows the HSV-1 entry level into the cells in presence of unilluminated and illuminated ZnO structures with99

Yogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

Fig. 6(a) Modified FTS technology using burner approach. The precursor metal microparticles are inserted into theburner, which are transported and converted to metal oxide nano-microstructures in the flame. The transformation of precursor microparticles depends on their time of travel in the flame which are marked 1–3 and at 4
corresponds to substrate where converted structures are collected (for simplicity only tetrapod shape is shown
but typically various shapes can be obtained). (b) Digital camera image of a copper plate coated with ZnO
tetrapods. Inset in (b) shows the SEM image of nanoscale ZnO tetrapod deposited on the Cu plate. SEM
images (1–4) shows the transformation of precursor ZnO microparticles into ZnO nanostructures. [Partially
reproduced from Fig. 4 with permission from59)].

UV light. It was observed that in presence of such ZnO
structures, the HSV viral entry level goes down as someviruses get attached on the ZnO surface. After UV illumination of these ZnO structures, the HSV-1 viral entry into
the cells is significantly decreased because of enhanced attachment of viruses on the ZnO surface60).
The HSV-1 entry mechanism into the cells is demonstrated by schematic drawing shown in Fig. 7d. The HSV-1
virus exhibits heparan sulfate (HS) groups as virion envelop
which interacts with gD-receptors on the cells and enter into
the cells. The presence of ZnO nano-microstructures screens
the HSV-1 entry into the cells as some viruses are attracted
by the oxygen deficient surfaces of ZnO nano-microstructures. After preparation, the ZnO nano-microstructures areseveral times under sun-shine, it is sufficient to create oxygen vacancies60). After UV illumination, further O vacancies
are created in such ZnO structures which enhance the virus
attachments on the ZnO surface and results in the significantly decreased HSV-1viral entry into the cells decreased.
More details can be found in previous work60).

4.2 Antiviral activity of nano-micro ZnO tetrapods
against HSV-2
Since herpes simplex virus type 2 (HSV-2) is more fatal
as compared to HSV-1 and antiviral community is still
waiting for appropriate treatments. We utilized the ZnO

100

tetrapods to study the HSV-2 viral entry into the cells61)
and its antiviral activity is demonstrated in Fig. 8. The
SEM images of ZnO tetrapods used for experiments with
HSV-2 are shown in Fig. 8(a–c) at increasing magnifications (from top to bottom). The confocal microscopy results of ZnO tetrapods without and with HSV-2 viruses areshown in Fig. 8(d) and Fig. 8(e, f), respectively.
The HSV-2 viruses were labeled with green markers
using a dye. The viral entry mechanism of HSV-2 viruses
into the cells in presence of ZnO tetrapods is demonstrated
in Fig. 8(g–i). As mentioned above, in presence of ZnO tetrapods, some viruses are attached at the surface of ZnO tetrapod arms due to inherent oxygen vacancies (Fig. 8g). In
absence of ZnO tetrapods, the HSV-2 viruses make normal
entry into the cells in natural manner (Fig. 8h). After UV illumination on such ZnO tetrapods, the HSV-2 viral entry
into the cells goes significantly down (Fig. 8i) because moreviruses are attached on the surface of ZnO tetrapods arms
due to additional oxygen vacancies created by UV illumination61). Few studies relating to blocking capability of theseZnO tetrapods have already reported in recently publishedarticles60, 61, 63). Further in-vivo experiments are under progress to understand the process in more details. Similar phenomenon was observed in case of SnO2 nanowire networks,
synthesized by FTS approach shows strong potential ofblocking the HSV-1 entry into the cells62). For biomedical
applications of different nano­-microstructures, cytotoxicity

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Fig. 7 Antiviral activity of the ZnO nanoseaurchins and tetrapods against herpes simplex virus type -1 (HSV-1). The
SEM images (a) & (b) show morphology of the ZnO nano-microstructures used for HSV-1 experiments. (c)Confocal microscopy results (A–C) and antiviral activity (D) of ZnO structures: Image (A) shows the confocal microscopy image of ZnO tetrapods. The confocal microscopy images in (B) and (C) shows the attachment of HSV-1 with ZnO structures (viruses were leveled with green markers). Plot in (D) demonstrates theantiviral activity of ZnO nano-microstructures without and with UV illumination. (d) Schematic model
demonstrating the blocking of HSV-1 entry into cells by ZnO structures. When illuminated with UV light,
these ZnO structures significantly bind HSV-1. [Reproduced with permission from60)].

is very important issue and these nano-micro scale ZnO
tetrapods exhibit very low level of cytotoxicity as compared to conventional spherical nanoparticles and ZnCl2
reference71), which implies towards better utilization inbiomedical engineering.

4.3 ZnO nano-micro tetrapods for advanced linking
technology
A brand new method of joining polymers with low surface energy was developed by the utilization of the ZnO
nano-micro tetrapods (Fig. 9) produced by the second FTS
variant shown before59). This method employs the convex
shape of tetrapodal microparticles which works as an anchor to mechanically interlock two polymer layers together. Its efficiency was demonstrated by joining two
extremely difficult-to-join polymer layers, namely thepoly(tetrafluorethylene) (PTFE) and cross-linked poly(dimethylsiloxane) (PDMS)64). Both polymers have very low
surface energies and it was difficult to find a single report

describing that both polymers can be strongly joined byany technique. Even PTFE alone is notoriously difficult tomodify. The surface modification methods developed before, such as plasma treatment and ion beam treatment, require specific instruments. Chemical treatments are
difficult and involve hazardous chemicals with PTFE,
which is highly chemically inert. The new method
achieved a peeling strength of 220 N/m by an easy applicable approach, without modification of the chemicalcomposition of each polymer layers64).
Fig. 9a demonstrates the adhesion technology between
two polymer layers employing ZnO tetrapods (T-ZnO) at
the interface between two layers. It was observed that with
the T-ZnO at the interface the peeking strength was improved significantly (Fig. 9b). In order to compare the effect of shape, some ZnO tetrapods (Fig. 9c) were ground(G-ZnO), which resulted in microrod type structures (Fig.
9d). These G-ZnO (ground ZnO tetrapods) structures werealso embedded at the interface between two polymer layers
and peeling strengths from both (T-ZnO and G-ZnO) were101

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Fig. 8 Antiviral activity of ZnO tetrapods against herpes simplex virus type -2 (HSV-2). (a)–(c) SEM images of
ZnO tetrapods utilized for HSV-2 experiments. (d)–(f) Confocal microscopy images of ZnO tetrapod (d)without and (e, f) with HSV-2. The viruses are leveled with green markers and confocal microscopy
images in (e) and (f) show that they are attached with ZnO tetrapods. (g)–(i) Schematic drawings show therole of ZnO tetrapods in HSV-2 entry into the cells. (h) In absence of ZnO tetrapods viruses enter into thecells in normal manner. (g) In presence of ZnO tetrapods some viruses are attached with ZnO tetrapods
and thus their entry into cell decrease. When these ZnO tetrapods are illuminated with UV light, moreviruses are attached with tetrapods and this further reduces the viral entry into cells. [Reproduced withpermission from61)].

compared which are shown in Fig. 9e. It can be clearly seenthat employing T-ZnO gives much better adhesion as compared to G-ZnO. Since there was no chemical treatment applied to ZnO structures and polymer surfaces, the strong
adhesion is purely due to mechanical interlocking. Therefore the concave shaped particles such as tetrapods produced by FTS approach has shown unique potential in
improving the mechanical adhesion of polymer laminates64).
More details can be found in report by Jin et al.64)

4.4 ZnO nano-micro tetrapods as fillers forfabricating self-reporting composites
Semiconducting tetrapod type structures have alreadyshown interesting stress dependent luminescent responses72, 73). An important possible application of tetrapodal
shaped ZnO nano-microstructures in polymers is the development of a new concept for self-reporting materials65).
The concept assumed that, the deformation of the crystals
induces changes in the photoluminescence (PL) signal of
the ZnO nano-microtetrapods and therefore it can be used102

to indicate the stress state of the material. This concept
was tested by embedding the tetrapodal particles in anelastomeric matrix as shown in Fig. 10a. Typical SEM
image of ZnO tetrapods used in the experiments are shownin Fig. 10b and digital camera image of the final prepared
T-ZnO: PDMS (Polydimethylsiloxane) composite is shownas inset in Fig 10b. Desired size and shape of composite canbe fabricated as reported by Jin et al.65) The PL spectra of
T-ZnO: PDMS composites with respect to tensile stress areshown in Fig. 10c. It can be seen that the intensity of blue
PL peak (from UV excitons in ZnO) remains constant but
intensity of green PL peak (~523 nm) has increased whichmost likely appears from surface defects in ZnO10, 11).
A strong correlation between the tensile stress and green
PL signal was observed as shown in Fig. 10d. Furthermore, the polymer was reinforced by the addition of tetrapodal microparticles, which was not the case in otherstress-sensing mechanisms involving photoluminiscentparticles as fillers65). Detailed analysis revealed that theformation of network of tetrapodal micro-particles is important for such correlations and a detailed monitoring ofYogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

Fig. 9ZnO tetrapods used as cross-linkers for joining the least surface energy polymers (PDMS and PTFE). (a)Schematic drawing demonstrating the experiment for testing the adhesion strength between two polymer
layers with tetrapods at the interface as cross-linkers. (b) Peeling strength between PTFE and PDMS polymer layers without and with ZnO tetrapods. (c) & (d) SEM images of ZnO tetrapods (T-ZnO) and groundZnO tetrapods (G-ZnO). (e) Peeling strength between PDMS and PTFE layers when filled with T-ZnO and
G-ZnO as fillers. Utilizing ZnO tetrapods as cross-linkers, the peeling strength between PDMS and PTFE
layers significantly increased. [Reproduced with permission from64)].

intensity ratio one might be able to extract to damage informations inside the composites. Further details can befound in the article by Jin et al.65)

4.5 ZnO 3D networks as templates for growth ofultra light weight aerographite material
The 3D interconnected metal oxide nano-microstructures
networks are extremely important for practical applications. Next, we demonstrate an example of growing new
carbon based Aerographite material (shown in Fig. 11),which is one of lightest solid materials so far67). The interconnected networks from ZnO tetrapods were used as
templates inside CVD chamber for growth of aerographite
material. It was observed that the material growth follows
exactly the tetrapods morphology and the existing interconnections in the 3D ZnO network template. The hydrogen gas flowing in the CVD chamber plays main role in
the transformation of ZnO into aerographite as it etches

ZnO from the surface of ZnO tetrapods and simultaneously
deposits carbon at this place67). It was reported that belt likeearly stage growth is most likely responsible for this type oftransformation of ZnO tetrapods into aerographite material67). This is an ultralight weight material with lot of interesting physical and chemical properties suitable for different
applications67). Just for demonstration, SEM images fromthe fabricated aerographite material and some of its properties are summarized in Fig. 11.
The 3D aerographite networks with desired sizes can begrown by proposed technique. For example digital camera
image of a large cylindrical (1.4 cm diameter large with
1 cm height) aerographite network is shown in Fig. 11a andcorresponding low and high magnification SEM images areshown Fig. 11b and Fig. 11c respectively. The high magnification SEM image (Fig. 11c) confirms the hierarchicalhollow framework networks of microtubes inside aerographite network. Fig. 11e and d display mechanical data of
aerographite material. In Fig. 11d, a mechanical load cycle

103

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Fig. 10

Use of luminescence features of ZnO tetrapods (T-ZnO) for designing self-reporting composites: (a)Schematic drawing showing the change in luminescent response from ZnO tetrapods under tensile stress.
(b) SEM image of ZnO tetrapods. The inset in (b) shows a digital camera image of the fabricated
T-ZnO:PDMS composite. (c) Photoluminescence spectra (raw data for plot d) from the T-ZnO: PDMS
composite (50 weight % T-ZnO) under tensile stress (at every 2.5 s interval, 100 spectra were collectedduring tensile test and 85 spectra are plotted here in which a clear change of intensity of PL peak ~523 nm is visible). (d) Stress-strain plot of the T-ZnO:PDMS (50 weight % T-ZnO) composite (left side)and variation of intensity ratio of green to blue PL emissions regions with respect to strain. [Reproducedwith permission from65)].

containing compressive and tensile load is shown. The inset
in Fig. 11d shows how the electrical conductivity increases
during the mechanical compression in a similar experiment.
Fig. 11e is an Ashby material selection map74) as it is a convenient guideline in modern lightweight engineering. It
compares the specific modulus and density for a plenty ofmaterials (including aerographite) because these two properties are very crucial to build stiff and light parts from anindividual material. The here demonstrated Aerographite
material exhibits interesting electro-mechanical properties(Fig. 11d) and material selection map (shown in Fig. 11e)suggests it to be a potential candidate for material engineering applications67). It is among one of the extremely porous
materials (porosity > 99.9%) and still superhydrophobic innature67). The aerographite material possesses a lot of otherinteresting features suitable for various advanced applications and more details can be found from the previous paper
by Mecklenburg et al.67)

104

5. Conclusion
In conclusion, we point out that proposed flame transport
synthesis FTS and its approaches offer really facile, cost-­
effective and scalable synthesis processes for versatile
micro-nanostructures of various metal oxides. It also enables successful fabrication of different 3D interconnected
networks with desired sizes, porosities, electrical conductivities etc. The tunable elastic modulus of these 3D networks
in the range of rubber elastic region enables them as flexible ceramics for various technological applications. Three-­dimensional interpenetrated micro-nanostructures can beused as appropriate networks for controlled growth different other structures for example and ultralight weight aerographite material. The nano-micro-scale ZnO tetrapods
have already proved their promising applications in the direction of biomedical engineering, advance linking technologies and designing self-reporting composites etc. The
controlled variant of FTS technology offers facile growthYogendra Kumar Mishra et al. / KONA Powder and Particle Journal No. 31 (2014) 92–110

Fig. 11 (a) Digital camera image of half-tablet of aerographite material. (b) & (c) SEM images of aerographite
material at low (b) and high (c) magnifications. (d) Loading and unloading stress-strain response of aerographite demonstrates elastic behaviour under compressive and tensile stresses. During compression, areversible increase of conductivity can be observed, see inset. (e) Specific modulus versus density map
comparison of aerographite with respect to other light weight engineering materials. This materials selection map shows the theoretical superior properties of aerographite for the case of a minimized bending ofa free standing bar with defined weight74). [Reproduced with permission from67)].

of quasi-1D nanostructures and their arrays. Preliminary
experiments using ultralong single crystalline ZnO needles
have shown promising features for applications in various
fields. Most relevant applications of the metal oxide micro-­nanostructures grown by FTS approach and its variants
have been summarized in this paper and several others areunder progress.

Acknowledgements
YKM sincerely thanks to Prof. Sotiris E. Pratsinis (Particle Technology Laboratory, ETH-Zurich) for kind invitation to write the article and to Ms. Natalie Winzer(HOSOKAWA ALPINE Aktiengesellschaft, Germany) for
her enormous patience in terms of deadline extensions andreviewing. This project was funded by German Research
Foundation (DFG) under the schemes SFB 855-A5 andpartially by SFB 677-C10 and Ad/183/10-1. YKM and OL

acknowledge the researcher fellowships from Alexandervon Humboldt Foundation at the University of Kiel, Institute of Materials Science, Germany.

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Author’s short biography
Yogendra Kumar Mishra
Yogendra Kumar Mishra is currently working as a senior research assistant and habilitantin the Functional Nanomaterials Group at the Institute for Materials Science in the University of Kiel, Germany. He received his Ph.D. in physics (plasmonics) from Jawaharlal
Nehru University, New Delhi, in September 2008, and since October 2008 has been working in the Functional Nanomaterials Group. During February 2009 to February 2011, heworked as an Alexander von Humboldt fellow in the group. At Kiel, he introduced a new
fabrication technique called ‘Flame Transport Synthesis’ which allows the versatile fabrication of different metal oxide nano-microstructures and their interconnected 3D networks.

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Author’s short biography
Sören Kaps
Sören Kaps studied materials science at the University of Kiel and received his diploma in 2008. He joined the group of Prof. Rainer Adelung (Functional Nanomaterials) as a
Ph.D. candidate in 2008. His research is focused on the application of ZnO in magnetoelectric sensors as in the DFG project SFB 855 Biomagnetic Sensing.

Arnim Schuchardt
Arnim Schuchardt received his B.Sc. (materials science) in 2008 at the University ofKiel. In 2010 he received his M.Sc. (materials science) at the University of Kiel. Since
2010, he has been a Ph.D. student in the Functional Nanomaterials Group, Institute forMaterials Science in the University of Kiel, Germany. He is mainly working on the fabrication and electromechanical characterization of highly porous carbon-based 3D networks(aerographite).

Ingo Paulowicz
Ingo Paulowicz is currently working as a Ph.D. candidate in the Functional Nanomaterials Group at the Institute of Materials Science, University of Kiel, Germany. He finishedhis M.Sc. in 2010 at the very same place on the synthesis and characterization of tin oxide
nanostructures. He prepared his B.Sc. at Hochschule Bonn-Rhein-Sieg on the topic of laser-­sintered titanium dioxide, which he finished in 2008. His present field of work is mainly thesynthesis of zinc oxide, in particular via a modified burner approach synthesis (m-BAS).

Xin JinXin Jin studied Physics at the East China Normal University in Shanghai. She obtained
her Master’s degree (2010) in material science and engineering from the University ofKiel. Since 2010 she has been a Ph.D. candidate in the group of Prof. Dr. Rainer Adelung(Functional Nanomaterials), University of Kiel, Kiel, Germany. She is working mainly on
the DFG project SFB677 which focuses on photoswitchable adhesives. She recently introduced the new concept of joining the un-joinable polymers employing ZnO tetrapods
as linkers.

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Author’s short biography
Dawit Gedamu
Dawit Gedamu is a Ph. D. candidate. in materials science at the Functional Nanomaterials Group, Institute for Materials Science, University of Kiel. His research interest
mainly includes the synthesis of different metal and metal oxide nanowires and their potential for various nanoelectronic devices and sensors. He received an M.Sc. in materialscience and engineering in 2008 from the University of Kiel, Kiel, Germany.

Sebastian Wille
Sebastian Wille is currently working as a leader of the dental materials group in the
Department of Prosthodontic, Propaedeutics and Dental Materials at the UKSH in Kiel on
various projects about dental materials. A key topic is the aging of dental zirconia ceramics. He received a Ph.D. degree in materials science (Dr.-Ing.) from the University of Kiel
in May 2009. He continued working in the group of Functional Nanomaterials in Kiel
until December 2012 as a scientist, concentrating mainly on several projects about the application and synthesis of metal oxide micro- and nanostructures.

Oleg Lupan
Oleg Lupan is a research fellow supported by the Alexander von Humboldt Foundation at the University of Kiel, Institute of Materials Science, Functional Nanomaterials.
He received his M.S. in microelectronics from the Technical University of Moldova(TUM) in 1993. He received his Ph.D. in solid-state electronics, microelectronics and nanoelectronics from the Institute of Applied Physics, Academy of Sciences of Moldova in
2005. His post-doctorate research activities were carried out at the CNRS, Paris, France,
and the University of Central Florida, USA. He received his doctor habilitate degree in
2011. He is an associate professor at the TUM. His current research interests include
nanosensors and optoelectronic devices.

Rainer Adelung
Rainer Adelung is a full professor and chairholder of the Functional Nanomaterials
Group established in 2007 at the Institute for Materials Science, University of Kiel,
Germany. He received his Ph.D. (rer. net) in physics in 2000 from the Institute of Experimental and Applied Physics, University of Kiel, and during 2001–2002, he was at Case
Western Reserve University in Cleveland (USA) as a Feodor Lynen (Alexander von
Humboldt) Research Fellow. In 2006 he finished habilitation at the Institute for Materials
Science in Kiel and then continued as a Heisenberg Professor (DFG grant) with his own
Functional Nanomaterials Group until 2012.

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Review Paper

Aerosol Processing of Graphene and Its Application to Oil
Absorbent and Glucose Biosensor †Sun Kyung Kim1,2, Hankwon Chang 1, Jeong-Woo Choi 2,
Jiaxing Huang 3** and Hee Dong Jang 1*
1

Rare Metals Research Center, Korea Institute of Geoscience and Mineral Resources, Korea
Interdisciplinary Program of Integrated Biotechnology, Sogang University, Korea
3
Department of Materials Science and Engineering, Northwestern University, USA
2

Abstract
2Graphene (GR) is a flat monolayer of sp -bonded single carbon atoms densely packed into a honeycomb crystal
lattice. Due to its unique characteristics, GR is expected to contribute to enhanced nano-electronic, bio-electronic
devices, etc. in the near future. However, the single-layered GR sheets have a tendency to form irreversible
aggregates or even to restack easily due to strong attraction between sheets. Preventing of aggregation andrestacking of GR is achieved by the dimensional transition from flat sheets to fractal-dimensional, nearly spherical
crumpled balls using aerosol spray pyrolysis. This review first introduces the fabrication of crumpled GR andGR-composite by aerosol spray pyrolysis, and then discusses the material properties of GR: strain-hardening,
compression and aggregation-resistant behavior. Finally, we introduce effective applications of hollow crumpled
GR balls for oil absorbent and crumpled GR-composites for glucose biosensor, respectively.
Keywords: graphene, crumpled graphene, composite materials, aerosol spray pyrolysis, biosensor, oil absorbent

1. Introduction
Graphene (GR) is a flat monolayer of sp2-bonded single
carbon atoms densely packed into a honeycomb crystal lattice1). GR can be synthesized by various methods such asmechanical exfoliation of graphite, chemical vapor deposition from carbon based precursor, and chemical oxidation
and reduction of graphite. Fig. 1 shows structural models of
GR, GR oxide (GO) and reduced GO (r-GO). r-GO is often
mentioned as chemically modified GR. So here, we use GR
and r-GO interchangeably for convenience. The structure of
GR has been demonstrated to have a high specific surface
area, high thermal conductivity, excellent mechanical stiffness, high optical transparency, good biocompatibility, andfast electron transportation2–7). The unique characteristics
of GR have attracted tremendous interest for many applications. GR-based polymer nanocomposites exhibit improved
mechanical, thermal, and electrical properties8–15). GR is†

Accepted: September 8, 2013
Daejeon, 305-350, Korea
2
Seoul, 121-742, Korea
3
Evanston, Illinois 60208, USA* Corresponding author:
E-mail: hdjang@kigam.re.kr
TEL: +82-42-868-3612 FAX: +82-42-868-3415** Corresponding author:
E-mail: jiaxing-huang@northwestern.edu
TEL: +1-847-491-5940 FAX: +1-847-491-7820
1©2014 Hosokawa Powder Technology Foundation

also able to replace metal conductors in electronic and electrical devices due to its excellent electrical conductivity andmechanical flexibility16–18). A few ongoing studies havereported that GR can replace brittle and chemically unstableindium tin oxide in flexible displays and touch screens. Dueto its excellent electronic properties, GR can be used in an
enzyme immobilization matrix in the construction of a biosensor. In addition, GR as an electronic circuit material isconsidered to be potentially superior to other carbon-based
nanofillers19–21). Therefore, GR is expected to contribute toenhancing nano-electronic and bio-electronic devices innear future22). It is obvious that these excellent propertiesare relevant at the nanoscale and the manufacture of nanocomposites is highly dependent on the single-layered GR in
the matrices.
However, single-layered GR sheets have a tendency toform irreversible aggregates or even restack easily due toπ-π stacking and van der Waals attraction if the sheets are
not well separated from each other23). Preventing aggregation and restacking is essential for GR sheets because theunique properties are only associated with individual sheets.
Restacking and aggregation of GR sheets not only reduce
their effective application but also compromise their properties, such as accessible surface area. Making exfoliated GR
sheet materials will help to standardize the materials andtheir performance for various applications. Many methods
for preventing aggregation in solution have been developed111

Sun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

Fig.   1 Structural model of (A) graphene, (B) GO and (C) r-GO.

and typically include reducing the size of the sheets, tailoring the solvent-GR interactions, employing dispersing
agents and attaching functional groups24–29). However, oncethe dispersions are dried, preventing aggregation of thesolid state GR products and making them re-dispersible
have been challenging topics23).
It will also be beneficial to develop crumpled paper balls
because the dimensional transition technology from flat
sheets to near three-dimensional (3D) crumpled balls canresist compression and aggregation properties. Like crumpled paper balls, crumpled GR is capable of tight packing
into a near three-dimensional (3D) form without significantly losing surface area30).
In order to make crumpled GR, the free-standing
aqueous droplets containing exfoliated graphene oxide(GO) in an inert atmosphere are evaporated. Then, thesoft GO sheets can be compressed to form a near-sphericalparticle just like a crumpled paper ball and are then converted into r-GO by thermal reduction at high temperature31). This concept has been experimentally achievedby an aerosol-assisted capillary compression process
called aerosol spray pyrolysis (ASP).
All the previous studies employed a liquid phase reaction that included many time consuming unit operation
stages, such as liquid-solid separation, washing, and drying, in order to synthesize the GR32–40). On the other hand,
the ASP has many advantages in fabricating of crumpled
GR from GO because it is a very fast, simple and continuous process for fabricating self assembled composites as a
one-step method41). It also takes a very short time of several seconds for crumpling and reducing of GO together
and does not require any post heat treatment, purification or
reduction agents23,41–43). The size of the crumpled particles
and the degree of crumpling can be tuned with the concentration of GO in the aerosol droplets. The as-prepared crumpled GR by ASP is compression-resistant just like paperballs as compressive stress makes them stiffer and harder,
and it has consistently higher and much more stable surface areas after the same processing steps compared to the
GR sheets23). In addition, an anode modified by the crumpled GR exhibits enhanced performance in electricity generation over those covered with activated carbon and112

regular GR sheets, which lead to a significantly highshort-circuit current and maximum power density44).
As mentioned above, GR-supported composites haveattracted a great deal of attention for their enhanced material properties, such as their high electrical and thermal
conductivity, and so on. Many materials such as polymers,
metal oxides and noble metals have been used widely tofabricate functional GR composites31,45). When the crumpled GR-based composite is fabricated, improved material
properties for many applications are expected.
In this review, we introduce the aerosol processing of GR
and demonstrate the superior properties and interesting
potential applications for crumpled GR. We first introduce the fabrication of crumpled GR and its composite by
ASP. The material properties of crumpled GR, such as
strain-hardening, compression and aggregation-resistantbehavior, are then discussed. Applications for crumpled
GR balls and GR-composite such as oil absorbent andglucose biosensor are also introduced, respectively.

2. Fabrication of Crumpled GR
2.1 Graphene Oxide
To fabricate crumpled GR by ASP, a colloidal solutionof exfoliated graphene oxide (GO) is prepared as an aerosol precursor. The colloidal GO is generally prepared byoxidation of graphite powder using a modified Hummers’
method as follows46–49). In the first step, graphite, K 2S2O8,
and H2SO4 are stirred together in an 80°C oil bath for the
pre-oxidation process. Then, for the oxidation process,
KMnO4 is slowly added in 30°C oil bath. Once mixed, thesolution is transferred to an ice bath and forms a thickpaste. Next, distilled water is carefully added, and thesolution is stirred for 30 min while the temperature ismaintained below 50°C. Finally, H2O2 is slowly added,
turning the color of the solution from dark brown to yellow. The warm colloidal mixture is then filtered, washedwith distilled water and dried. The dried filter cake is thendispersed in distilled water under ultra-sonication for the
exfoliation process. Low-speed centrifugation is done atSun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

3000 rpm for 15 min. It is repeated until all visible particles are removed (about 5 times) from the precipitates. The
supernatant then undergoes two more high-speed centrifugation steps at 8000 rpm for 30 min to remove small GO
pieces and water-soluble by-products. The final sedimentis re-dispersed in distilled water using an ultrasonic bath,giving a colloidal solution of exfoliated GO47).
Fig. 2 demonstrates how the GO is successfully synthesized from graphite by the modified Hummers’ method.
The X-ray photo emission spectroscopy (XPS) spectrumof the as-prepared GO shows that C and O peaks appearedat 285 and 533 eV, respectively (Fig. 2(A)). Further, theC1s spectrum shows two peaks at 284.7 and 286.6 eV, which
are attributed to C-C and C-OH/C=O, respectively31).
According to the result of the XRD analysis, the peak of
GO appears at 10.21° (Fig. 2(B)). The Raman spectrum of
the as-prepared GO shows a G band at 1600 cm–1 and a Dband at 1337 cm –1 (Fig. 2(C)) 45). The G band of the GO
is broadened compared to graphite, mainly due to theextensive oxidation. The UV-Vis spectrum of the GO dispersion shows a peak at 225 nm (Fig. 2(D)).

2.2 Crumpled GR
Fig. 3 shows a schematic illustration of aerosol process forfabricating crumpled GR from a colloidal GO solution. Since
exfoliated GO sheets are essentially soft, water-dispersible,
and in single atomic layers, crumpled GR can be easily
fabricated from the GO colloid using the ASP process. The
experimental apparatus for the ASP process consists of an
ultrasonic atomizer, an electrical tubular furnace, and a filter sampler. An aqueous colloid of micron size GO sheets issprayed to generate many aerosol droplets of micron sizeand flowed through a tube furnace preheated at 800°C by
inert carrier gas (nitrogen or argon). Rapid evaporation of
the solution causes shrinkage of the droplets, first concentrating the GO sheets and subsequently compressing theminto crumpled balls of sub-micrometer scale. By heating, theGO is thermally reduced to GR as indicated by the color
change from brown to black. It takes only several seconds toprepare the crumpled GR and there is no need for any postheat-treatment or purification steps23).
Field emission scanning electron microscopy (FE-SEM)
images indicate morphology of crumpled GR by the ASP(Fig. 4). The samples reveal the near three-­dimensional crumpled ball-like structures with many ridges and vertices23).

2.3 Hollow GR
The fabrication of hollow GR has been studied because of
their promising properties, such as large specific surface
area, low density, and high porosity50–63). Accordingly,
various methods such as the sol-gel and hydrothermal
methods have been developed to synthesize hollow parti-

Fig.   2

A: X-Ray photoelectron spectroscopy of the GO.
Reprinted with permission from ref 31. Copyright 2012ELSEVIER. B: The x-ray diffraction of patterns of
the GO. C: Raman spectra of (a) graphite and (b) GO.
Reprinted with permission from ref 45. Copyright 2013
ELSEVIER. D: UV-Vis spectrum of GO.

cles of inorganic materials using templates and a series ofmany steps for treatment64–69).
However, when the ASP technique is employed, rapid

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Fig. 3

Schematic illustration of the formation of crumpled GR from GO via aerosol spray pyrolysis.

Fig. 4 FE-SEM images of GR as shown in the (A) representative high magnification single particle and (B) low
magnification overview.

Fig. 5

Schematic illustration showing the preparation of hollow GR capsules.

formation of hollow GR balls can be achieved by capillary
molding and template removal in one step and a continuousmode of production. The schematic drawings in Fig. 5
illustrate the process for fabricating hollow GR capsules.
Aqueous aerosol droplets containing GO sheets and polystyrene (PS) colloids are first generated by an ultrasonicatomizer, and then flowed into a preheated tube furnace byargon carrier gas. As they pass through the heating zone,
the aerosol droplets first rapidly evaporate. Then hollow
GR balls are eventually shaped by wrapping PS beads by
GO, GO reduction and PS evaporation. The low magnification scanning electron microscopy (SEM) image in Fig.
6(A) gives an overview of the sample morphology, whichclearly shows their spherical shape and hollow nature. The
transmission electron microscopy (TEM) image showsthat the diameter of the capsules is around 580 nm, which114

is similar to that of PS templates. When a second component, such as metal or metal oxide nanoparticles, is added
to the colloidal precursor, metal or metal oxide nanoparticles decorated by hollow GR composites can be easily
synthesized (Fig. 6(B))43).

2.4 Crumpled GR Composite
For the synthesis of the crumpled GR-metal oxide or crumpled GR-noble metal composite by ASP, a colloidal mixture
as a precursor must be prepared with the as-prepared GO
colloid and sub materials (metal oxide particles (TiO2) or
noble metal precursor (H2PtCl6·6H2O and HAuCl4·3H2O)31,45).
The experimental apparatus for crumpled GR can be employed to synthesize the crumpled GR composite. An ultrasonic atomizer is used to generate micron-sized droplets

Sun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

Fig. 6

A: (1) SEM image showing an overview of the hollow GR capsules. (2) The hollow nature of the spheres
can be clearly seen in the TEM image. (3) High resolution TEM image taken at the edge of a capsule.
Scale bars: (1) 4 mm; (2) 200 nm; (3) 20 nm. B: SEM (1 and 2) and TEM (inset) images showing hollow
GR capsules decorated by (1) Au and (2) Fe3O4 nanoparticles, respectively. Scale bars: (1 and 2) 1 mm;(inset) 100 nm. Reprinted with permission from ref 43. Copyright 2012 The Royal Society of Chemistry.

Fig. 7

Schematic illustration of the formation of TiO2-GR composite from colloidal mixture of TiO2 nanoparticles and GO via aerosol spray pyrolysis.

of the metal oxide-GO or noble metal-GO colloidal precursor. The droplets are then carried into a tubular furnace
by argon gas. Crumpled GR composites are formed in the
furnace and then collected by a Teflon membrane filter.
Figs. 7 and 8 show the schematic drawing of the formation of a crumpled GR-TiO2 composite and a crumpled
GR-noble metal composite by the ASP process. For thesynthesis of the crumpled GR-TiO2 composite, rapid evaporation of water, self-assembly between GO and TiO2, andthermal reduction of GO are carried out in series in the

furnace (Fig. 7). In case of the crumpled GR-noble metalcomposite, the evaporation of water, formation of crumpled
GO, thermal reduction of crumpled GO and the noble metal
precursor, and the self-assembly between crumpled GR andnoble metal nanoparticles are carried out (Fig. 8)45).
In Fig. 9, the FE-SEM image shows the morphology ofa crumpled GR-TiO2 composite according to the concentration of the GO colloid. The TiO2 nanoparticles are en­
capsulated by the GR. The GO accumulates at the water
surface of a sprayed droplet during evaporation and finally115

Sun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

Fig. 8 Schematic illustration of the formation of noble metal-GR composite from colloidal mixture of noble metal
precursor and GO via aerosol spray pyrolysis. Reprinted with permission from ref 45. Copyright 2013
ELSEVIER.

Fig. 9

FE-SEM images of TiO2-GR composite at different weight ratios of GO/TiO2 (A) 2, (B) 0.5, (C) 0.1, (D)0.05 at TiO2: 0.1 wt%. Reprinted with permission from ref 31. Copyright 2012 ELSEVIER.

forms a GR ball. In contrast, hydrophilic TiO2 nanoparticles are agglomerated and positioned inside of the GR ballduring the evaporation process. Further, as the GO concentration decreases from high to low concentration, adecrease in the degree of coverage of GR to TiO2 is clearlyobserved. Fig. 10(A) shows the X-ray photoemission spectroscopy (XPS) spectra of TiO2-GR composites. The C, Ti
and O peaks are measured at 285, 480 and 533 eV, respectively. As the concentration of GO decreases, the intensityof C becomes lower whereas that of Ti and O become
higher. This occurs because TiO2 is exposed at a lower
concentration of GR. These results prove that the as-­prepared crumpled GR composites can be harmoniously
made from every piece of precursor by the ASP process.
Additionally, according to the XRD analysis, the diffraction patterns of the crumpled GR-TiO2 composite show the116

anatase and rutile phase of TiO2 only. Although the GR
content in the composite varies, the intensity of the TiO2
phases does not change because the intensity of the GR
phase is much lower than that of TiO2 (Fig. 10(B))31).
Fig. 11(A, B) reveals that the morphology of the crumpled GR-noble metal composites is generally the shape ofa crumpled paper ball and that noble metal nanoparticles
are deposited on the surface of the GR crumples. TEM
analysis shows that Pt and Au nanoparticles 3 and 5 nm indiameter, respectively, are uniformly deposited on GR
sheets. Fig. 11(C) shows the diffraction patterns of thenoble metal-GR composites according to the XRD analysis. The crystallinity of the as-prepared composites synthesized at 800°C indicates the same peaks as those of thenoble metal reference. The peak detected at around 25
degrees is GR. The crystallite sizes that are calculated by

Fig. 10

A: X-ray photoelectron spectra of TiO2-GR composite
prepared at different GO/TiO2 weight ratio (a) 0.5, (b)0.1, (c) 0.5, and (d) pure GO at TiO2: 0.1 wt%. B: XRD
patterns of TiO2-GR composite with different GO/
TiO2 weight ratio (a) 0.05, (b) 0.1, (c) 0.5, (d) 2, and (e)pure GO at TiO2: 0.1 wt%. Reprinted with permission
from ref 31. Copyright 2012 ELSEVIER.

Intensity [a.u.]

Sun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

the Scherrer equation are 3.3 and 5.5 nm in Pt and Au,
respectively45).
Fig. 11

3. Properties of Crumpled GR
In a crumpled paper, the crumpled structure is stabilizedby plastically deformed ridges made of kinked paper fibers,
which prevent the structure from unfolding. The microstructure analysis of the crumpled GR reveals that the plastic deformation in the crumpled graphene particles is due tostrong π-π stacking at the ridges70–72). It is also found that the
crumpled GR particles are compression-resistant because
compressive stress makes them stiffer and harder.
The crumpled GR balls were remarkably stable against
aggregation in solution as well as in a solid state due to theπ-π stacked ridges and strain-hardening properties. Whenpelletized, crumpled GR formed a piece of isotropic, blacksolid with rough microstructures at both the surface andthe cross section (Fig. 12(A, B)). In contrast, flat GR

A: FE-SEM and TEM images of as-prepared crumpled Pt-GR composites. B: FE-SEM and TEM imagesof as-prepared crumpled Au-GR composites. C: The
x-ray diffraction of patterns of as-prepared noble metal-­
GR composites (above: Au-GR and below: Pt-GR).
Reprinted with permission from ref 45. Copyright 2013
ELSEVIER.

formed an anisotropic, shiny pellet with very smooth,nearly featureless surface but with a laminated microstructure at the cross section (Fig. 12(C, D)). Moreover,the strongly compressed pellet of crumpled GR was readily redispersed in solvents upon shaking by hand (Fig.
12(E)). An SEM image of redispersed particles (Fig.
12(F)) shows that the crumpled GR morphology is notlargely affected by the compression. However, pellets ofthe flat GR under the same pressure were not redispersed

117

Sun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

118

Fig. 12Compressed pellet of crumpled GR particles (inset of panels A and B) has rough and isotropic microstructures as shown in the SEM images taken at both (A) the surface and (B) cross section due to theirnear-spherical, pointy shape. In contrast, flat GR sheets restack along the compressing direction, resulting in a highly anisotropic pellet (inset of C, D) with (C) very smooth surface and (D) lamellar crosssection. (E, F) The pellet of the crumpled particles can be readily dispersed by gentle hand-shaking
after being compressed at 55 MPa. (G, H) However, the pellet of regular GR sheets cannot be redispersed due to extensive aggregation. Reprinted with permission from ref 23. Copyright 2011 American
Chemical Society.

Fig. 13

A: Photos showing oil absorption capability of the 3 carbon particles. In each vial, 1.0 mg of carbon
particles was added to 17.5 ml of vegetable oil colored with a red dye. The oil-carbon blends weresuspended on water for better view. B-E: Photos showing 100 ml of dyed vegetable oil absorbed by
10 mg of Fe3O4 decorated magnetic r-GO hollow capsules. F-I: 150 ml of dyed vegetable oil absorbedby 10 mg of r-GO hollow capsules. Reprinted with permission from ref 43. Copyright 2012 The Royal
Society of Chemistry.

Sun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

even after sonication due to extensive irreversible stacking(Fig. 12(G, H)). The electrical conductivity at the surface of
crumpled GR pellets was similar to that of a flat GR. Thisreveals that crumpled GR can help to prevent aggregation
without decreasing the overall electrical characteristics23).

4. Application of Crumpled GR
4.1 Oil Absorbent
The hollow GR balls exhibit properties such as hydrophobic structure, light weight, large free volume, andmany small pores on the surfaces. Those features makethe hollow GR balls attractive for oil absorption andrecovery43).
In order to compare the oil absorption capability ofhollow GR balls against some high surface area carbon
materials, such as commercial activated carbon (Norit
Darco G60) and commercial carbon black powders (Cabot
Vulcan XC-72), we performed a set of control experiments
using vegetable oil colored with a red dye (Fig. 13).
The specific surface areas of the hollow GR balls, carbon
black and activated carbon were 84 m 2/g, 230 m2/g, and789 m2/g, respectively. The oil absorption experiments
showed that the hollow GR had the highest oil absorption
capacity among the three samples (Fig. 13(A)). The result
demonstrates that a high specific surface area is advantageous for molecular adsorption, but not necessarily for oil
absorption. This result also suggests a basic design principle
for oil absorption materials, which can be used to prepare
as high a free volume as possible. After oil absorbing, the oil
filled GR balls were aggregated on the water surface. Fig. 13(B–E) demonstrates that initially vegetable oil coloredwith a red dye was spread on the water surface. Then, hollow
GR balls decorated with magnetic nanoparticles were
dropped onto the oil film, which quickly shrank within a
few minutes (Fig. 13(C)), and eventually transformed intoa thick carbon-oil droplet (Fig. 13(D)), which could berecovered by a magnet. When undecorated hollow GR
balls were used, the resulting blend could be directly
picked up and removed by a glass rod (Fig. 13(F–I))43).
Therefore, the hollow GR balls prepared by the ASP
process have a high free volume determined by the size ofthe template, and show promising oil absorption properties. In addition, hollow GR balls with many opening poreswith a hydrophobic structure have an excellent oil absorption ability43).

4.2 Glucose biosensors
As GR is expected to enhance bio-electronic devices in
the near future, many studies have been conducted to findpotential applications of GR73). Chen et al. (2008) showed

Fig.   14 A: Cyclic voltammograms of glucose biosensors
prepared with GR, TiO2, and TiO2-GR composite,
respectively. B: Amperometric responses of the glucose biosensor based on TiO2-GR composite preparedat different weight ratios of GO/TiO2 (b) 0.5, (d) 0.1, (a)pure TiO2, and (c) pure GO. Reprinted with permission from ref 31. Copyright 2012 ELSEVIER.

that GR sheets may be biocompatible and therefore suitablefor biomedical applications based on the cell culture experiments74). Yang et al. (2011) showed that no obvious toxicityof GR was observed in blood biochemistry, hematology, or
histology analysis75). Park et al. (2010) proved that GR
sheets are noncytotoxic to mammalian cell lines76). Thus,
GR is expected to play an important role in improving thecatalytic performance of biosensor applications due to its
biocompatibility and unique properties.
Recently, glucose biosensors fabricated with GR andGR-based composites have been a great concern among
enzyme-based biosensors since they can monitor blood
glucose for the treatment and control of diabetes77,78).
In case of glucose biosensors fabricated with GR,
Nafion-flat GR/GOD film-modified electrodes were developed for the detection of glucose and showed good stability. The glucose sensor exhibited a linear response in therange of 2.0 × 10 –6 to 1.0 × 10 –4 M with a detection limit of
1.0 × 10 –6 M. The good response was due to the fast electrontransfer in the GR composite film79). The self-assembled GR
platelet-GOD nanostructures were reported as an enhanced

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glucose biosensor. The linear detection range of their sensor
was estimated to be from 2 to 22 mM, and the detection
limit was estimated to be 20 μM, which revealed that the
GR platelet-GOD had a notable catalytic performance fordetection of glucose80).
In case of glucose biosensors fabricated with a GR-based
composite, Chitosan-flat GR/Au nanocomposite films
were also reported as a potential glucose biosensor due totheir good amperometric response to glucose with wide
linear ranges81). The glucose biosensor fabricated with
Pt-graphite nanoplatelets was suggested as an enhanced
glucose biosensor as well and showed a high sensitivity
and selectivity82). The results revealed that the graphite
nanoplatelets incorporated into the biosensor interface
increased the effective electrode surface area. Using afabricated Au-flat GR composite, a prominent electrochemical response to glucose with wide linear ranges anda high sensitivity due to the synergistic effect of GR and
Au nanoparticles was reported83,84).
In the above studies, flat GR and graphite platelets were
employed to fabricate a GR or metal-GR composite-based
biosensor electrode and improved properties for glucose
biosensors were obtained. Therefore, if the glucose biosensor with the crumpled GR is used, more enhanced properties are expected.
Recently, it has been reported that a glucose biosensor
fabricated with a crumpled GR-TiO2 composite demonstrated enhanced properties such as sensitivity and stability31). When cyclic voltammogram of glucose biosensors
prepared with crumpled GR, TiO2, and the crumpled
GR-TiO2 composite was measured, the biosensor preparedwith the crumpled GR-TiO2 composite had the highest
current flow as well as clear oxidation, with reduced peaks
at -0.5 V and -0.6 V (Fig. 14(A)). The amperometricresponse by the glucose biosensor based on the crumpled
GR-TiO2 composite was linear against the concentration of
glucose ranging from 0 to 8 mM at -0.6 V (Fig. 14(B)).
The highest sensitivity of the glucose biosensor based on
the crumpled GR-TiO2 composite was about 6.2 μA/
mM·cm 2. This reveals the synergistic effect of TiO2
nanoparticles with crumpled GR as the electrode materials
for biosensors31).
Furthermore, a crumpled GR-noble metal composite
was developed for glucose biosensor application45). Fig.
15(A) shows the cyclic voltammetry result of the glucose
biosensor prepared with the crumpled GR-noble metalcomposites. The current flow of the biosensor prepared by
the crumpled GR-Pt was higher than other composites,
crumpled GR-Au or crumpled GR. The redox peak of theelectrochemical reaction by the crumpled GR-Pt was thestrongest at -0.07 and -0.25 V among the three electrodes.
The sensitivity was 62 and 15 μA/mM·cm2 for the crumpled GR-Pt and the crumpled GR-Au composites, respectively (Fig. 15(B)). This result showed that the noble

120

Fig. 15

A: Cyclic voltammograms of the glucose biosensor
prepared by noble metal-GR (Pt-GR and Au-GR).
B: Amperometric responses of the glucose biosensor
based on Pt-GR composite, Inset graph indicate thatof Au-GR composite. Reprinted with permission fromref 45. Copyright 2013 ELSEVIER.

metal-crumpled GR composite covered with uniformly
distributed noble metal nanoparticles had higher electrochemical activity, as noble metals can enhance the electrontransfer between the enzyme and the electrode45). The superior electrochemical activity could have originated from the
crumpled GR that can tightly pack without significantly
reducing the area of accessible surface and can also deliver
much higher specific capacitance ability and better rate
performance44).

5. Summary
This review first introduced crumpled GR and its composite fabricated by aerosol spray pyrolysis (ASP). We thendiscussed the material properties of crumpled-GR such as
strain-hardening, compression and aggregation-resistantbehavior. Finally, we introduced potential applications of a
crumpled GR ball and its composite such as oil absorbent
and glucose biosensors.
In the section on the fabrication of crumpled GR, weSun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

described the preparation of colloidal GO by the oxidationof graphite powder using a modified Hummers’ method.
Then, we presented the experimental apparatus and schematic procedure of ASP for fabrication of crumpled GR,
hollow GR, and GR-based composites.
In the section on the materials properties of crumpled
GR, we demonstrated that crumpled GR is stabilized byexternal influences, and thus does not unfold or collapse
during various types treatments. We further discussed thedifference in specific surface area between flat GR andcrumpled GR processed under the same conditions.
Finally, we discussed strain-hardening behaviors of crumpled particles, which make them remarkably resistant toaggregation in both solution and dried states.
In the section on the applications of crumpled GR, first,
we discussed application of hollow GR balls for oil absorption and recovery since the hollow GR balls have properties,
such as hydrophobic structure, light weight, large free volume, and many small pores on the surfaces, and introduced
the superior capacity for oil absorption of hollow GR capsules. Second, we introduced glucose biosensors fabricatedwith crumpled GR-TiO2 and crumpled GR-noble metalcomposites since GR-supported composites are known for
their superior biocompatibility, electrical conductivity, andchemical and electrical properties. The biosensor preparedwith the crumpled GR-Pt composite showed the highest
current flow as well as clear oxidation, which results in highsensitivity. The results for the biosensor prepared with the
crumpled GR-noble metal composite showed that the noble
metal-crumpled GR composite covered with uniformly distributed noble metal nanoparticles had higher electrochemical activity, as noble metals can enhance the electron transfer
between the enzyme and the electrode.

Acknowledgements
This research was supported by the General Research
Project of the Korea Institute of Geoscience and Mineral
Resources (KIGAM) funded by the Ministry of Science
ICT and Future Planning. J.H. thanks supports from theInitiative for Sustainability and Energy at Northwestern(ISEN) through an Early Career Investigator Award (initial
seed fund) and the Office of Naval Research (ONRN000141310556).

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Author’s short biography
Sun Kyung Kim
Sun Kyung Kim received her B.S. (2006) and M.S (2010) degrees from Chungnam
National University and Sogang University in Korea, respectively. She is currently working toward her Ph.D. degree in Rare Metals Research Center at Korea Institute of
Geoscience and Mineral Resources and Interdisciplinary Program of Integrated
Biotechnology at Sogang University. Her current research interests include aerosol synthesis of nano-materials and their applications for electrochemical sensors.

Hankwon Chang
Hankwon Chang received his B.S. (1998) and M.S. (2000) degrees from Yeungnam
University, Korea and Ph.D. (2003) degree in Chemical Engineering from Hiroshima
University. In 2004, he returned home country, Korea and joined in Nano-Materials Research
Team of Korea Institute of Geoscience and Mineral Resources (KIGAM) as a SeniorResearcher. He is now a Principal Researcher in Rare Metals Utilization Research Team of
KIGAM and an Associate Professor of Nanomaterials Science and Engineering Major of
University of Science and Technology (UST). As a societal service, he has been working as
an Editorial Board Member of Advanced Powder Technology from 2009 and a Chair for
Nano-Materials Division of the Korean Association for Particle and Aerosol Research(KAPAR) from 2012. His current research interests include aerosol synthesis of functional
nano-materials and their applications for energy conversion and storage materials.

124Sun Kyung Kim et al. / KONA Powder and Particle Journal No. 31 (2014) 111–125

Author’s short biography
Jeong-Woo Choi
Jeong-Woo Choi received his B.S. (1982) and M.S. (1984) at Sogang University, Korea,
and Ph.D. (1990) at Rutgers University, USA. He worked at the IBM Almaden ResearchCenter and Mitsubishi Electronics Advanced Technology R&D Center as a visiting
researcher from 1993 to 1996. He also received D. Eng. (2003) from Tokyo Institute ofTechnology, Japan, as well as MBA (2005) from the University of Durham, UK. He has
been a Professor of the Department of Chemical & Biomolecular Engineering, Sogang
University, South Korea, after 1990. His main research area is nanobioelectronics including biomemory device, nanoprotein chips, and cell chips based on nanotechnology. He has
published over 313 peer-reviewed papers including in Angewandte Chemie, Advanced
Materials, Biomaterials, Biosensor and Bioelectronics, etc. His current research interest is
the application of nanoparticles to nanobioelectronic device.

Jiaxing Huang
Jiaxing Huang is an Associate Professor of Materials Science and Engineering at
Northwestern University. He received a B.S. in Chemical Physics from University of
Science and Technology of China (USTC) in 2000 and a Ph.D. in chemistry from the
University of California, Los Angeles (UCLA) in 2004, and became a Miller Research
Fellow at the University of California, Berkeley before joining Northwestern in 2007. His
research interest is in the general area of materials chemistry, processing and manufacturing. Some materials of interests include 2D materials, organic crystals and metal nanostructures. He has been a recipient of the IUPAC Young Chemist Prize, the Alfred P. Sloan
Research Fellowship, the NSF CAREER Award, the inaugural ISEN Early Career
Investigator Award at Northwestern, and the Gustav Olling Outstanding Young
Manufacturing Engineers Award from the Society of Manufacturing Engineers.

Hee Dong Jang
Hee Dong Jang received his B.S. (1982), M.S. (1984), and Ph.D. (1993) at Sogang University
in Korea, and Dr. Eng. (2005) at Hiroshima University in Japan. He has worked as a postdoctoral researcher at the University of California at Los Angeles from 1996 to 1997 anda visiting scholar at the Northwestern University from 2009 to 2010. He has been appointed
as a President of Korea Association for Aerosol and Particle Research from 2012, and an
Executive Editor of Advanced Powder Technology from 2009. He has been working at
Korea Institute of Geoscience and Mineral Resources (KIGAM) from 1985, and he iscurrently a distinguished principal researcher and a Director of Rare Metals ResearchCenter at KIGAM, and Professor in the Nano-Materials Science and Engineering Major
of University of Science and Technology. His area of expertise is the aerosol processing
and application of nanostructured materials. His current interests involve the synthesis ofGraphene based nanocomposite materials and their application for energy, environmental
and biomaterials.

125

KONA Powder and Particle Journal No. 31 (2014) 126–134/Doi:10.14356/kona.2014019

Review Paper

Physicochemical Properties and Factors that Induce
Asbestos-Related Respiratory Disease †Hiroto Izumi * and Yasuo Morimoto1

Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan

Abstract
It is thought that inhaled dusts such as asbestos and man-made mineral fibers in the lung repeatedly induce
persistent inflammation and finally lead to pulmonary fibrosis and respiratory cancer. There have been manystudies about whether a variety of factors, such as oxidative stress including free radicals, chemokines,
inflammatory cytokines, and fibrosis-related cytokines are related to pulmonary fibrosis, lung cancer and malignant
mesothelioma. In this paper, we introduce the relationship between these factors and these diseases. It is important
to determine what physicochemical properties of fibrous materials such as asbestos are related to asbestos-relateddiseases. We show the relationship between the physicochemical properties of not only asbestos but also otherfibrous materials and inflammation, fibrosis and biopersistence in the lung.
Keywords: asbestos, lung cancer, malignant mesothelioma, cumulative exposure

Asbestos exposure and respiratory tumor
It is thought that a high concentration of asbestos exposure induces lung cancer 1). There are some reports that acumulative exposure of 25–100 fiber-years induced theonset of lung cancer caused by asbestos, and the Helsinki
criteria showed that a cumulative exposure of 25 fiberyears, the minimum cumulative exposure level, is necessary for the onset of lung cancer induced by asbestos2).
Cumulative exposure correspond to a 2-fold risk of lungcancer. The indexes of the risk of lung cancer are 1)
retained fiber levels of 2 million amphibole fibers (> 5 μm)
per gram of dry lung tissue or 5 million amphibole fibers(> 1 μm) per gram of dry lung tissue measured by electron
microscopy, (Fig. 1); 2) 5000 asbestos bodies per gram ofdry tissue measured by light microscopy, or 5 asbestos
bodies per milliliter of bronchoalveolar lavage fluid measured by light microscopy (Fig. 2); and 3) a profusion scoreof 1in a chest x-ray finding, which means early asbestosis.
Henderson et al.3) proposed, as a revised version of theHelsinki criteria, that a cumulative exposure of 20 fiberyears for amphibole asbestos, cumulative exposure of 25
fiber-years for asbestos yarn spinning, cumulative exposure of 200 fiber-years for chrysotile asbestos only (workin chrysotile mine quarrying, crushing and friction mate†1*

Accepted: September 18, 2013
1-1, Iseigaoka, Yahata-nishi-ku, Kitakyushu, Fukuoka, 807-8555,
Japan
Corresponding author:
E-mail: h-izumi@med.uoeh-u.ac.jp
TEL: +81-93-691-7466 FAX: +81-93-691-4284

126

rials production in Canada) , or cumulative exposure ofmore than 25 fiber-years for the combined exposure ofchrysotile and amphibole asbestos is necessary for the
onset of lung cancer induced by asbestos.
The onset of malignant mesothelioma is thought to be
induced by a low concentration of asbestos exposure,although there is no significant evidence of a relationshipbetween the occurrence of mesothelioma and the amountof exposure to asbestos. Previous studies4) reported thatmalignant mesothelioma was contracted by workers who
were engaged in indirect asbestos exposure in a shipyardor in the vehicle manufacturing industry developed malignant mesothelioma, a person who washed workers’ clothes,to which asbestos was attached, and neighboring inhabitants around asbestos mines and the asbestos product man-

Fig. 1

Scanning electron microscope of asbestos bodies©2014 Hosokawa Powder Technology Foundation

Hiroto Izumi et al. / KONA Powder and Particle Journal No. 31 (2014) 126–134

Fig. 2

Light microscope of asbestos bodies

ufacturing industry. Therefore, asbestos exposure otherthan in occupation induced the disease. For that reason, in
examining asbestos-related diseases, it is very important
to know not only the occupational history of workers but
also the residential history of families. It is thought thatfrom cohort studies the degree of risk of developing mesothelioma by asbestos depends on the kind of asbestos,namely when the strength of chrysotile, amosite and crocidolite is 1: 100: 500, respectively5). In addition, the onset isunrelated to smoking.

performed6). The solubility in the solubility test is associated with pathological lesions in acute and chronic inhalation studies. In the solubility test, fibers with low solubility,
such as crocidolite and amosite, induced a long half-life of
the fiber in an acute inhalation study and developed pulmonary fibrosis and cancer in a chronic inhalation study.
On the other hand, fibers with high solubility, such as
slagwool and HT stone wool, reduced the half-time of thefiber and caused no significant pathological lesions.
Taken together, the physicochemical properties ofasbestos which affect the lung tissue are its length andsolubility. Long and thin fibers with low solubility induce
biopersistence in the lung and finally cause lung disorders.
From the clinical point of view, the length of the fiber
affects the development of lung cancer. There are regulations based on the length of fiber, such as more than 1 μm
or 5 μm, to measure the number of asbestos fibers in lungtissue in order to examine whether or not lung cancer isrelated to asbestos exposure. This may show that the lengthof fibers is related to the onset of lung cancer induced byasbestos.
In malignant mesothelioma, the association between
physicochemical properties and the development of mesothelioma is unclear, but it has been reported that shortfibers induce malignant mesothelioma. In the case of
malignant mesothelioma, it may be important that theonset of mesothelioma is associated with the movement of
the asbestos to the parietal pleura. The physical limitationof phagocytosis of the fibers by the macrophages may berelated to the shortness of the fibers.

Relationship between size of asbestos andasbestos-related tumor

Lung damage by free radicals and inflammation

The physicochemical properties of asbestos in the
induction of lung cancer are thought to be 1) fibers withlow solubility and 2) fibers which are thin and long.
If fibers reach the lung, some of them melt in body fluid
and some are divided into small fragments. These fibers,
which become small, are phagocytized by alveolar macrophages and are excreted outside the lungs with mucociliary escalator. Even if fibers have low solubility, short fibers
are also excreted by alveolar macrophages. However, it isdifficult for macrophages to phagocytize the fiber physically, particularly when fibers with low solubility are longer than the diameter of the macrophages. Thus fibers withlow solubility and long length are deposited in the lung in
the long term and will influence the lung continuously
without being excreted. It is thought that fibers which are
not excreted from the lung have a physically and chemically harmful effect on the lung.
Solubility tests (in vitro test to examine how fibers
dissolve in medium) and inhalation studies of not only
asbestos but also man-made mineral fibers have been

Inhalation of fibers can cause inflammation in the respiratory tract and pulmonary alveolar space in not only theacute phase but also in the chronic phase7) These inflammations, especially continuous inflammation, progress tofibrosis of the lungs and pleura, or lung tumor (malignant
mesothelioma and lung cancer)7, 8). We performed intratracheal instillation of different mineral fibers to rat, and examined lung inflammation from 3 days up to 6 months9).
Harmful respirable particles like crystalline silica or crocidolite asbestos, which are kinds of asbestos, caused persistent inflammation from the initial instillation until six
months. However, transient inflammation was only ob­
served early in the instillation when less harmful titanium dioxide of micron size was inhaled. In the inhalation
exposure examination to rat with chrysotile for 20 days,
continuous inflammation and fibrosis containing mainly
neutrophils were observed10). Continuous inflammation
causes lung injury, and free radicals play a central role inthis injury. There are two types of free radicals, one is reactive oxygen species and the other is reactive nitrogen127Hiroto Izumi et al. / KONA Powder and Particle Journal No. 31 (2014) 126–134

species11, 12). In the reactive oxygen species, there are asuperoxide ion (O2–), hydroxyl radicals (·OH), hydrogen
peroxide (H2O2), and singlet oxygen (1O2). On the other
hand, in the reactive nitrogen species, there are nitric oxide(NO), nitrosonium ion (NO+), nitrite ion (NO2–), and peroxynitrite (ONOO –).·OH and ONOO – have the highest reactivity in each species. There are two main production
locations of the free radicals. One is produced directlyfrom the surface of the asbestos13), and the other is produced indirectly from cells. Free radicals can attack DNA
and proteins including cell membranes14,15). Free radicals
have not only cytotoxic activity but also functions of signaling molecules against immunoreaction16), remodelingof extracellular matrix17,18), regulation of cell proliferation19) and malignant transformation20).
It is known that exposure to asbestos induces cell dysfunction, such as cell death, DNA damage and protein
damage. Apoptosis is one kind of cell death, and asbestos
exposure induces apoptosis of epithelial cells21). We havereported that chrysotile induces apoptosis of A549 lungepithelial cancer cell lines in a dose-dependent mannerand that this mechanism occurs through the activation of
caspase 3 and 922). In an animal model using rats, we also
observed that intratracheal instillation of chrysotile
induced apoptosis of alveolar epithelial cells and alveolar
macrophages and that the activation of caspase 3 and 9 wassustained. These findings suggest that epithelial cells canprotect the lung from inflammation and fibrosis, and that
apoptosis of epithelial cells by asbestos is involved infibrosis and tumor progression. Anti-oxidative stress
enzymes, such as heme oxygenase-1 (HO-1) and macrophage inflammatory protein-2 (MIP-2), a transcription
factor involved in inflammation such as NF-κB, have beenstudied as indications of oxidative stress. HO-1 is useful as
an indicator of oxidative stress because it has the ability toinhibit the production of active oxygen and its expression
is increased in response to the amount of active oxygen23,24). We have reported that the protein expression of
HO-1 was enhanced continuously up to six months whenchrysotile or crocidolite was injected intratracheally to
rat25,26). Driscoll et al.27) reported that exposure to crocidolite induced the expression of MIP-2 and NF-κB in alveolar epithelial cells and that this induction was suppressedby administering an antioxidant. Fattman et al.28) using
knockout mice with deleted EC-SOD gene, which caneliminate active oxygen, reported that free radicals
advance the inflammation and fibrosis of asbestos. These
results suggest that the oxidative stress caused by asbestos
might promote inflammation and fibrosis.
As for DNA damage, it has been reported that 8-hydroxy
deoxyguanosine and 8 nitroguanine are generated byasbestos29,30). 8 nitroguanine was generated in airway epithelial cells of mouse lung tissue by intratracheal injectionof chrysotile and crocidolite. At the protein level, it has

128

been reported that the tumor suppressor gene p53 is phosphorylated by chrysotile and crocidolite in vitro31). Thismight indicate that asbestos exposure can repress thetumor suppressor function.

Genetic abnormality of malignant pleural
mesothelioma and lung cancer
Asbestos is known as a carcinogen, and it can cause
malignant pleural mesothelioma and lung cancer32).
However, the mechanism of carcinogenesis has not been
sufficiently clarified. Its oncogenesis might be influenced
by complicated factors, such as diversity of the asbestos(type, geometry, dose of the fiber, and so on), individual
sensitivity, and synergistic effects with other carcinogens
like cigarette. Abnormality of gene expression is broadlyclassified into genetic abnormality and epigenetic abnormality33–35). Genetic abnormality is a disorder which is
directly caused by a mutation in the nucleotide sequence ofthe gene. On the other hand, epigenetics is a study thatreveals the diversity of gene expression inherited evenafter cell division without a change in the nucleotide
sequence. Both genetic abnormality and epigenetic abnormality are associated with not only oncogenesis but also
malignant progression. In cancer cells, there are two typesof mutations. One is passenger mutations, which are accumulated only by chance, and the other is oncogenic driver
mutations, which occur in important genes involved in thephenotype of cancer36). Oncogenic driver mutations havebeen found in the EGF receptor, K-ras, HER2, AKT1, etc.
(Table 1). In addition, there is a cancer that is completelydependent on the oncogenic signal associated with cellproliferation and survival of cancer by only one mutatedgene. This is called oncogene addiction, and its representative example is L858R mutation in the EGFR gene37).
In the genetic abnormality of asbestos-related lung cancer, mutations of the k-ras and TP53 (p53) have beenreported38–48). K-ras mutation is an oncogene that plays animportant role in the signal transduction of the epidermal
growth factor receptor (EGFR). Husgafvel-Pursiainen etal.42) reported that asbestos exposure alone was not significantly associated with an increased occurrence of K-ras
mutations. However, a strong and significant association
was found between adenocarcinoma and K-ras mutation ina group of combined smoking and asbestos exposure42,47,48).
Nelson et al.40) suggested that asbestos exposure increases
the likelihood of mutation at K-ras codon 12 and that thisprocess occurs independently of the induction of interstitial fibrosis. Mutant p53 proteins acquire oncogenic properties that enable them to promote invasion, metastasis,proliferation and cell survival49). Wang X et al. reported
that p53 mutations occurred significantly more frequently
in patients with a history of occupational exposure toHiroto Izumi et al. / KONA Powder and Particle Journal No. 31 (2014) 126–134

Table 1

Oncogenic driver mutations for lung cancer
Entrez GeneID

KRAS (Kirsten rat sarcoma viral oncogene homolog)

3845

EGFR (epidermal growth factor receptor)

1956

HER2 (v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2)

2064

BRAF (v-raf murine sarcoma viral oncogene homolog B)

673

MET (met proto-oncogene, hepatocyte growth factor receptor)

4233

AKT1 (v-akt murine thymoma viral oncogene homolog 1)

207

MAP2K1 (mitogen-activated protein kinase kinase 1)

5604

PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha)

5290

1

EML4-ALK*

27436/238

1* EML4-ALK is a product of the fusion gene lined the N-terminus of EML4 (echinoderm microtubule associated protein like 4,
GeneID 27436) and the C-terminus of ALK (anaplastic lymphoma receptor tyrosine kinase, GeneID 238).

asbestos46). It has also been reported that the mutation of
p53 gene is common in asbestos associated cancers43).
An analysis of specific gene copy number changes inasbestos-related lung cancer revealed some allelic imbalances50). In particular, allelic imbalances of 19p51), 9q3352),
and 2p1653) were important in asbestos-related lung cancer.
FHIT, a candidate tumor suppressor gene, contains the
FRA3B common fragile site and is highly susceptible tocarcinogen damage54). Deletion of the FHIT gene in thechromosome 3p14.2 and reduced expression of the FHIT
protein are correlated with malignant non-small cell lungcancer. It has also been indicated that these mutations areassociated with smoking and asbestos exposure55, 56).
There are many reports about the genetic abnormality ofmalignant pleural mesothelioma. Mutations of K-ras andp53 in malignant pleural mesothelioma have been reported
in the same way as other malignant tumors57, 58). However,association with malignant pleural mesothelioma and theBRCA1 associated protein-1 (BAP1), the cyclin-dependent
kinase inhibitor 2A (p16/CDKN2A), neurofibromin 2(NF2), and EGFR genes have been well investigated. BAP1
binds to BRCA1 and acts as a tumor suppressor59, 60). p16/
CDKN2A acts as a negative regulator of the proliferationof normal cells by interacting strongly with CDK4 andCDK661) and is associated with cellular senescence andtumor suppressor62). NF2 is associated with a signaling
pathway that plays a pivotal role in tumor suppression by
restricting proliferation and promoting apoptosis63).
Frequent mutations of the BAP1, p16/CDKN2A and NF2
genes are detected in malignant mesothelioma cells64, 65).
There are reports of mutation66, 67) and overexpression68, 69)
of EGFR in malignant pleural mesothelioma. Downstreamof EGFR signaling is activated in both cases, and mutations in EGFR downstream pathways are not rare in malignant pleural mesothelioma58). Murthy and Testa reported

that specific sites of chromosome arms are deleted inmalignant mesothelioma and that p16/CDKN2A at 9p21
and NF2 at 22q12 are frequently altered70).
The status of DNA methylation, structural changes in
the chromatin by chemical modification of histones (Table2), the action of non-coding RNA, etc., are important in
epigenetic abnormality71). For the methylation of DNA,
guanine and cytosine rich regions as the promoter of thegene (CpG island) are easily transferred by the addition ofa methyl group by a specific enzyme. Transcription factor
can not bind to the methylated promoter and transcriptional activity is suppressed. For example, when the promoter or cording region of a tumor suppressor gene ismethylated, tumor suppressor proteins can not be synthesized and the tumor suppression effect is attenuated.
Same reported DNA-hypermethylated tumor suppressor
genes are, p16/CDKN2A, mutL homologue 1 (MLH1),
epithelial-­cadherin (E-cadherin), runt-related transcription
factor 3 (RUNX3), adenomatous polyposis coli (APC),
O(6)-methylguanine-DNA methyltransferase (MGMT),
Ras association domain family 1A (RASSF1A), death­associated protein kinase (DAPK), cell adhesion molecule 1 (CADM1), retinoic acid receptor beta (RARB),
metalloproteinase inhibitor 3 (TIMP3), and FHIT72–75).
Hypermethylation of tumor suppressor genes is also
involved in malignant mesothelioma and lung cancer
caused by asbestos. When Dammann et al.76) analyzed the
methylation from the lung tissue of lung cancer patients,
hypermethylations of p16 were observed in 47% of lungcancer tissue and in 14% of normal lung tissue of patients.
They also reported that there is a correlation between
inactivation of p16 and asbestos exposure. On the other
hand, Fujii et al.77) reported that hypermethylation of p16
was observed in 7.7% of malignant pleural mesothelioma,
which was lower than 30.4% of lung cancer. Further

129

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Table 2 Epigenetic regulation of gene expression
1) Modification of promoter region
Gene expression
Demethylation in CpG island

On

Methylation in CpG island

Off2) Modification of histone
Gene expression
Acetylation

On

Deacetylation

Off

Phosphorylation

On or Off

Ubiquitination

On or Off

Methylation

On or Off

SUMOylation

On or Offinvestigation is required to clarify the relationship between
asbestos exposure and DNA methylation.
Structural changes in the chromatin by the chemical
modification of histones are also involved in epigenetic
regulation78). Histone acetylation induces transcription,
while deacetylation of histone suppresses transcription(Table 2). There are few reports about the association ofmalignant progression of mesothelioma and histone acetylation. However, a number of molecular-targeted agentsthat are currently under evaluation for mesothelioma, suchas the Histone deacetylase (HDAC) inhibitors, havedemonstrated promising anticancer activity79).
Micro RNA is a non-coding RNA which binds to thetarget mRNA and reduces the protein expression by inhibiting translation. An association between miRNA andmalignant pleural mesothelioma has been reported. Froman analysis of miRNA expression in mesothelioma tissue,
it has been suggested that miRNAs could be potential
biomarkers of prognosis and therapeutic targets80–87).
Benjamin H et al.87) reported that Hsa-miR-193-3p wasoverexpressed in malignant pleural mesothelioma, whilehsa-miR-200c and hsa-miR-192 were overexpressed inperipheral lung adenocarcinoma and carcinomas that frequently metastasize to lung pleura. This indicates that thisdiagnostic assay might be a useful tool in the differential
diagnosis of malignant pleural mesothelioma from othermalignancies in the pleura. Interestingly, there have been
attempts to diagnose malignant mesothelioma by measuring the miRNA in serum, and some useful miRNAs havebeen reported81, 82, 86). Some reports indicate the target
genes of miRNA and the effects on cell transformation88–93). There are few reports of miRNA in asbestos-­
related lung cancer94). Previous studies have reported thatmiRNA expression is not affected by asbestos exposure82).

130Conclusion
It is thought that asbestos inhaled into the lungs causes
inflammation and eventually leads to pulmonary fibrosis
and tumors. In this inflammation, free radicals such as those
produced by reactive oxygen species and reactive nitrogenoxide species induce not only cell and tissue damage but
also the progression of fibrosis and inflammation. Theseobservations are forming a consensus that continuous
inflammation is important in the formation of pathogenesis.
It is believed that additional mutations in the bronchial-­
alveolar epithelial cells and pleural mesothelial cells cause
the onset of lung cancer and pleural mesothelioma, respectively. The characteristics of the fibers that are related tofibrosis and carcinogenicity are low solubility and thin-long
type. It is necessary to elucidate the molecular mechanismsof asbestos-related lung cancer and malignant pleural mesothelioma. The development of biomarkers using serummiRNA is also required. In particular, the development ofbiomarkers to distinguish between asbestos-related and nonasbestos-related lung cancer and biomarkers for early detection of malignant pleural mesothelioma is anticipated.

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Author’s short biography
Hiroto Izumi
Hiroto Izumi M.D. & Ph.D. is an associate professor in Department of Occupational
Pneumology, Institute of Industrial Ecological Sciences, University of Occupational andEnvironmental Health, Japan. He graduated from Oita Medical University in 1988 andobtained doctorate in 1996. He joined Department of Molecular Biology, University ofOccupational and Environmental Health Japan, in 1996. He was visiting Researcher at
Institute of Anatomy and Cell Biology, Göteborg University in Sweden from 1997 to 1999.
From 2013, he joined current department. Research theme is the analysis of the biologicalproperties of cancer. In particular, he has focused on the analysis of mechanisms of theanti-cancer drug resistance.

Yasuo Morimoto
Yasuo Morimoto graduated from Kagoshima University, Faculty of Medicine at 1986. Hereceived his Ph.D. at 1993 from University of Occupational and Environmental Health,Japan (UOEH). Since 2000 he is professor of Institute of Industrial Ecological Sciences,
UOEH. His topics of research are hazard assessment and pulmonary toxicity of environmental particles including nano and fibrous materials.

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KONA Powder and Particle Journal No. 31 (2014) 135–145/Doi:10.14356/kona.2014003

Original Research Paper

Transient Flow Induced by the Adsorption of Particles †Naga Musunuri, Bhavin Dalal, Daniel Codjoe, Ian S. Fischer and Pushpendra Singh*
1

Department of Mechanical and Industrial Engineering, New Jersey Institute of Technology, USA

Abstract
The paper describes the physics of particle adsorption and the spontaneous dispersion of powders that occurs
when they come in contact with a fluid-liquid interface. The dispersion can occur so quickly that it appears
explosive, especially for small particles on the surface of mobile liquids like water. Our PIV measurements showthat the adsorption of a spherical particle at the interface causes an axisymmetric streaming flow about thevertical line passing through the particle center. The fluid directly below the particle rises upward, and near thesurface, it moves away from the particle. The flow, which develops within a fraction of second after the adsorptionof the particle, persists for several seconds. The flow strength, and the volume over which it extends, decrease
with decreasing particle size. The streaming flow induced by the adsorption of two or more particles is acombination of the flows which they induce individually. The flow not only causes particles sprinkled together
onto a liquid surface to disperse, but also causes a hydrodynamic stress which is extensional in the direction
tangential to the interface and compressive in the normal direction. These stresses can cause the breakup ofparticle agglomerates when they are adsorbed on a liquid surface.
Keywords: dispersion, powders, agglomerates, particle image velocimetry (PIV), interfacial tension.

1. Introduction
The focus of the paper is to describe the physics of particle
adsorption and the spontaneous dispersion of powders that
occurs when they come in contact with a fluid-liquid interface. While past studies have been concerned with understanding the mechanisms by which particles alreadytrapped on fluid-liquid interfaces interact leading to theirself-assembly into monolayered patterns (Kralchevsky
and Nagayama, 2000; Kralchevsky et al., 1992; Nicolson,
1949), (Singh et al., 2010, and the references therein), thesudden dispersion of particles coming into contact with afluid-liquid interface described in this paper has not been
considered prior to our recent study (Singh et al., 2009)
and (Gurupatham et al., 2011, 2012).
It was shown in (Singh et al., 2009) that (i) particles
sprinkled over a small area almost instantaneously spreadover an area that can be several orders of magnitudes
larger (see Fig. 1); (ii) a newly-adsorbed particle causes
particles already trapped on the interface to move away
creating a particle-free region around itself (see Fig. 2);
and (iii) dispersion influences the nature, e.g., structure
and porosity, of the monolayer clusters that are formed.

†
1*

Accepted: June 1, 2013
Newark, New Jersey 07102, USA
Corresponding author:
E-mail: singhp@njit.edu
TEL: +1-973-596-3326 FAX: +1-973-642-4282©2014 Hosokawa Powder Technology Foundation

These phenomena have importance in a wide range ofapplications, such as pollination in hydrophilous plants,
transportation and spreading of microbes and viruses, andthe self-assembly of particles leading to the formation ofnovel nano-structured materials, stabilization of emulsions,etc. (Aveyard et al., 2003; Binks and Horozov, 2006; Cox,
1988; Cox and Knox, 1989; Dryfe, 2006; Gust et al., 2001;
Pickering, 1907; Tang et al., 2006; Wasielewski, 1992).
The dispersion can occur so quickly that it appears
explosive, especially on the surface of mobile liquids likewater. An experiment showing this can be performed easily
in a household kitchen by filling a dish partially with water

Fig. 1 Sudden dispersion of flour sprinkled onto water in a dish.
Streaklines were formed due to the radially-outward
motion of the particles emanating from the location
where they were sprinkled. The size of flour particles
was ~2–100 μm. Taken from (Gurupatham et al., 2011)135

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Fig. 2

Trapping (or adsorption) of particles at an interface. (a) The particle comes in contact with the interface. (b) The particle
is pulled downwards by the interfacial force (γ12). (c) The particle oscillates about the equilibrium height within the interface causing a radially outward flow on the interface. Both the side and top views are shown. The lengths of the arrows
are not proportional to the flow strength. (d) (Left) A glass sphere of diameter 1.1 mm being dropped onto a monolayer of
18 μm tracer glass particles on the surface of a 60% glycerin in water. (Right) The flow on the surface causes all of the
nearby tracer particles to move away so that a roughly circular, particle-free region is created.

and then sprinkling a small amount of a finely-groundtion of the particle (Singh et al., 2009). By assuming that
powder such as wheat or corn flour onto the water surface.
the particle floats without significantly deforming the
The moment the flour comes in contact with the surface itinterface, it can be shown that Wa for a spherical particle
quickly disperses into an approximately-circular shapedof radius R isregion, forming a monolayer of dispersed flour particles on(1)
Waa  R 2 12 (1 + cos ) 2W
the surface (see Fig. 1). The interfacial forces that cause =this sudden dispersion of flour particles are, in fact, so
where θ is the contact angle and γ12 is the interfacial tension
strong that a few milligrams of flour sprinkled onto thebetween the upper and lower fluids (see Binks and Horozov,
surface almost instantaneously covers the entire water sur2006 and Tsujii, 1998).
face in the dish.
Therefore, when two or more particles are simultaneIt was shown by (Singh et al., 2009) and (Gurupatham
ously adsorbed at the interface, each of the particles
et al., 2011) that the initial dispersion of particles is due tocauses a streaming flow on the interface away from itself
the fact that when a particle comes in contact with thethereby causing the other particles to move away. Wheninterface, the vertical capillary force pulls it into thetwo particles are adsorbed the maximum distance byinterface, thereby causing it to accelerate in the direction
which they move apart is about a few diameters. However,normal to the interface (see Fig. 2). The maximum velocity
as the number of particles being adsorbed increases, theincreases with decreasing particle size; for nanometer-sized
distance travelled by a particle, especially if it is near theparticles, e.g., viruses and proteins, the velocity on anouter periphery of the cluster, can be very large—several
air-water interface can be as large as ~47 m/s. Also, sinceorders of magnitude larger than any dimension of the area
the motion of a particle on the surface of mobile liquids
over which particles are sprinkled. For example, as noted
like water is inertia dominated, it oscillates verticallyabove, a few milligrams of flour sprinkled over a very
about its equilibrium height before the viscous dragsmall area on the water surface almost spontaneously
causes it to stop. This gives rise to a streaming flow ondisperses to cover the entire water surface in the dish.
the interface away from the particle (see Fig. 2c).
The dispersion phase, which lasts for a short period of
The energy needed to pull a particle into the interface
time (about one second for the case described in Fig. 1),
and to induce the streaming flow comes from the net
is followed by a phase that is dominated by attractive
decrease in the interfacial energy (Wa) due to the adsorplateral-capillary forces during which particles slowly

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come back to cluster. The latter phase has been a focus ofmany past studies (Fortes, 1982; Kralchevsky et al., 1992;
Lucassen, 1992; Nicolson, 1949). Particles trapped at a
fluid-fluid interface generally interact with each other via
attractive capillary forces that arise because of theirweight. A common example of this capillarity-driven
self-assembly is the clustering of breakfast-cereal flakes
floating on the surface of milk. This mechanism is widelyused for two-dimensional assembly of particles at liquidsurfaces. However, if the buoyant weight of particles isnegligible, as is the case for colloidal particles, then theparticles will only disperse since the attractive capillary
forces between them are negligible (Aubry et al., 2008;
Bresme and Oettel, 2007; Singh and Joseph, 2005; Stamou
and Duschl, 2000).
One may postulate that the gradient of particle concentration gives rise to a (Maringoni) force that causes particles to disperse because the concentration of particles in
the region in which they are sprinkled is larger than in thesurrounding region. However, this is clearly not the case,as the dispersed particles cluster again under the action oflateral capillary forces. This shows that the gradient ofparticle concentration does not give rise to a dispersion
force and that particles disperse only when they come incontact with the interface for the first time (during which
each of the particles gives rise to a flow away from itself
as they are pulled into the interface).
Also, one may postulate that the dispersion is becauseof the presence of contaminants on the surface of particles
which are released into the liquid when they come in contact with the interface and their presence in fact causes
particles to disperse. If this is the case, then the intensitywith which the particles disperse should diminish when
they are washed. We ruled out this possibility by repeatedly
washing the particles and showing that their dispersive
behavior did not change when the experiments wererepeated (Gurupatham et al., 2011).
Particles also disperse on liquid-liquid interfaces. In
fact, as Fig. 3 shows, the dispersion forces can breakapart agglomerates of micron-sized particle that remain
intact in the upper liquid (Gurupatham et al., 2012). This
breakup and spreading of particle clumps (agglomerates)on liquid surfaces is important in various processes in thepharmaceutical and food industries such as wet granulation and food processing (Nguyen et al., 2010; Tüskea etal., 2005; Zajic and Buckton, 1990).
The sudden dispersion of particles plays an important rolealso in some physical processes occurring on fluid-fluid
interfaces, including the rate at which germs/microbes
disperse on a water surface. An example in botany is theformation by hydrophilous (water-pollinated) plants offloating porous pollen structures called “pollen rafts”(Cox, 1988; Cox and Knox, 1989). A crucial first step intheir formation is the initial dispersion of pollen that occurs

Fig. 3

Breakup and dispersion of agglomerate on the interfaceof corn oil and water, looking down from above (500xmag.). The size of glass particles of the agglomerate
was ~4 μm. (left) An agglomerate sedimented throughcorn oil and was captured at the interface. (right) Aftercoming in contact with the interface it breaks apart
explosively dispersing radially-outward into an approximately-circular region. Notice that some of the particles
remained agglomerated. Taken from (Gurupatham etal., 2012).

after it comes in contact with the water surface (if it did notdisperse, it would remain clumped/agglomerated).
In the next section, a description of the forces that act
on a particle during adsorption and of the pertinent
dimensionless parameters is given. The experimental
set-up and results of our PIV measurements are presented
in Sections 3 and 4. Finally, we summarize and conclude
in Section 5.

2.   Governing equations and dimensionlessparameters
As discussed above, when a particle comes in contact
with a fluid-liquid interface it is pulled inwards from theupper fluid into the interface with the lower fluid by thecapillary force to its equilibrium position in the interface.
It is crucial to understand this motion of the particle in the
direction normal to the interface, as it gives rise to thestreaming flow on the interface away from the particle.
The motion of the particle can be obtained by solving
the governing equations for the two f luids and themomentum equation for the particle, which are coupled,along with the interface stress condition and a condition
for the contact line motion on the particle surface. This is
a formidable problem because the capillary force at theline of contact of the three phases on the particle surface
depends on the slope of the interface which in general
requires the solution of the aforementioned equations(Pillapakkam and Singh, 2001; Singh et al., 2003; Singhand Joseph, 2005). However, a decoupled momentum
equation for a particle can be derived by modeling theforces that act on the particle (Singh et al., 2011; Singh etal., 2009). These forces are: the vertical capillary force(Fst), the buoyant weight (Fg), the Brownian force (FB),137

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and the viscous drag (FD). A decoupled equation for the
motion of the particle under the action of these forces canbe written as:mdV= Fstst + FDD ++ FFgg ++FFBB
dt(2)

where m is the effective mass of the particle which
includes the added mass contribution (Currie, 1974), V isthe velocity, Fst = 2πRγ12sin(θc)sin(θc+α) is the capillary
force, α is the contact angle, and θc is the particle positionin the interface. The Brownian force in Eq. (2) is negligible compared to the capillary force (Singh et al., 2011;
Singh et al., 2009).
The added mass and the drag calculations are complicated by the fact that the fraction of the particle that is
immersed in the upper and lower fluids changes as theparticle moves in the direction normal to the interface.
We will assume that the added mass is one half of themass of the fluid displaced, but this result is for a particle
fully immersed in a fluid (Currie, 1974). The drag force
will be assumed to be given by FD = 6πμRV f D, where μ is
the viscosity of the lower liquid, and f D is a parameterthat accounts for the particle being immersed in both
upper and lower fluids.

2.1 Governing dimensionless parameters
Let the characteristic velocity, length and time be given
by U = γ12/μ, R, and R/U, respectively. Then, Eq. (2) can
be nondimensionalized to give (Singh et al., 2011):
ρ dV ′
i m′ pWe=ρ dt′sin(θc )sin(θc + α)
+ 3V ′f D +2 ρp − ρc
B
fb .
3
ρ

(3)

Here the primed variables are dimensionless. f b is thedimensionless buoyancy which is O(1) but depends on the
profile of the deformed interface. ρ and ρa are the densitiesof the lower and upper fluids, ρc is the effective density ofthe volume displaced by the particle, and ρp is the particle
density. The dimensionless parameters in the above
2 R12equation are: the Weber number We =
, the
3 2
ρ
Bond number B = ρR2g/γ12, p , and the contact angle α.
ρ
The Weber number is the ratio of inertia forces to capillary
forces, and the Bond number is the ratio of gravitational
forces to surface tension forces.
For an air-water interface, the parameters have the values:ρ − ρcμ = 0.001 Pa.s, ρ = ρ p = 1000 kg/m 3, p
= 0.1 and
ργ12 = 0.07 N/m. Let us assume that μa = ρa = 0, m' = 1.5,
f D = 0.5 and f b = 1. Then, We = ~108R and B = ~105R2,
where R is in meters. Therefore, the role of particle inertia

138

becomes negligible only when R is much smaller than
10 nm because only then We is much smaller than one. The
influence of gravity becomes negligible when R < ~1 mmin the sense that such small particles float so that theinterfacial deformation is negligible. However, even a
negligibly-small deformation of the interface gives rise to
attractive lateral capillary forces which, even though small,cause floating particles to cluster. This happens because aparticle floating on a liquid surface is free to move laterally.
The only resistance to its lateral motion is the hydrodynamic
drag which can slow the motion but cannot stop it. Consequently, only very-small particles, for which lateral capillary
forces are smaller than Brownian forces, do not cluster.

3. Experimental Setup
The setup consisted of a square Petri dish which waspartially filled with Millipore water (see Fig. 4). The
cross-section of Petri dish was 10 × 10 cm, and the depth
was 1.5 cm. PIV measurements were performed in a vertical plane (normal to the camera axis) illuminated by alaser sheet. The vertical position of the camera was in linewith the water surface, providing an undistorted view ofthe volume directly below the water surface. The test particles were released very close to the liquid surface, about
1 mm from the surface, in an area near the intersection of
the laser sheet and the camera axis.
A high-speed camera was used to record the motion ofseeding particles visible in the laser sheet. A Nikon 1 series
V1 camera equipped with a 30 mm Kenko automatic
extension tube and a Tamron SP AF 60 mm 1:1 macro lens
was used to provide the required magnification. The laser
sheet was generated using a ZM18 series 40 mw solid state
diode laser of wavelength 532 nm (green color). Movies
were recorded at a resolution of 1280 × 720 pixels. For theparticle size range considered (~500 μm to 2 mm), the optimal recording speed for performing the PIV analyses wasfound to be 60 frames per second. This was determined bya trial and error procedure.
The water was seeded with silver-coated hollow glass
spheres of density around 1 gm/cc and average size ofaround 8–12 μm. The density of seeding particles closely

Fig. 4

Schematic diagram of the experimental setup.

Naga Musunuri et al. / KONA Powder and Particle Journal No. 31 (2014) 135–145

matched the water density, but there was a small particle-­
to-particle variation. Consequently, some particles sedimented and some rose slowly giving us ample time torecord their motion when a flow was induced due to theadsorption of one or more test particles. The seeding particles were silver coated which ensured that the intensityof the scattered light was sufficient to track their motion.
An open-source code, PIVlab, was used for performing
the time-resolved PIV analysis. PIVlab is a MatLab-based
software which analyzes a time sequence of frames to givethe velocity distribution for each of the frames. A MatLabcode for post-processing and plotting results was written.

4. Results
We first discuss our PIV measurements of the transient
flow on a water surface that was induced due to theadsorption of a single test particle. Glass particles of threedifferent diameters, 2.0, 1.1, and 0.65 mm were used toobtain the qualitative nature of the flow, and determine
how the strength and time duration of the induced flow
vary with the particle size.
In agreement with the analytic results obtained in(Gurupatham et al., 2011), test particles in all cases oscillated
vertically before reaching their equilibrium positions in theinterface. The frequency of oscillation increased, and theadsorption time decreased, with decreasing particle size inagreement with the analytic results. For example, the frequencies for the diameters 2.0, 1.1 and 0.65 mm were

Fig. 525 Hz, 50 Hz and 85.71 Hz respectively.
The adsorption of a test particle caused a flow on the
air-water interface, which caused tracer particles trappedon the surface to move away from the adsorbed test particle. Consequently, the water surface near the test particle
had few tracer particles which made fluid velocity measurement at and near the water surface difficult. Also, theair-water interface near the test particles was deformed
since their density was larger than the water density. In
fact, the center of particles was a fraction of radius below
the position of the undeformed interface. The deformationof the interface made viewing of the interface by a camera mounted on a side difficult (see Fig. 4). Therefore, in
our PIV measurements, the velocity was measured onlyin the region below a horizontal line passing through thepoint of contact of the interface with the particle which
was a fraction of the particle radius below the undeformedinterface (see Fig. 5).
Although the water near the test particle started tomove as soon as the particle came in contact with the surface, the adsorption-induced streaming flow intensity
developed over a period of time. The intensity reached amaximal strength after a fraction of a second and then it
decreased. In the time interval after which the streaming
flow reached its maximal strength, the vertical oscillationsof the test particle were already negligible. The PIV measurements show that the streaming flow was approximately
axisymmetric about the vertical line passing through thecenter of the test particle (see Fig. 5). Tracer-particles in
the region below the test particle moved upwards, and(Left) The origin of the coordinate system was at the intersection of the vertical lines passing through thecenter of the test particle and the horizontal line passing through the point of contact of the interface
with the particle. The center of the test particle was a fraction of particle radius below the position of the
undeformed interface. (Right) Velocity vectors for the streaming flow induced by a 2 mm test particle
0.67s after it came in contact with an air-water interface. The particle was dropped in a vertical plane
illuminated by a thin sheet of laser light. The velocity vectors of tracer particles have been superimposedon the PIV image, and the interface is marked by a horizontal white colored line. A purple-colored mask
was used in the PIV analysis to define the region occupied by the test particle. The velocity distribution
was approximately axisymmetric about the vertical passing through the center of the particle.

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Fig. 6 Temporal evolution of the streaming flow induced by the adsorption of a 650 μm particle. The velocity is shown at fivedifferent time intervals after the test particle came in contact with the water surface. (a) The vertical component ofvelocity (V) is shown as a function of –y/R. (b) The horizontal component of velocity (U) is shown as a function of x/R.

those near and in the water surface moved away from thetest particle. The trajectories of fluid particles were qualitatively similar to that for a stagnation point flow, with thecenter of the test particle being the stagnation point. Thisimplies that the stress on the test particle due to the
induced flow was extensional in the horizontal plane near
the water surface, and compressive in the direction normal to the surface.
Since the induced velocity field was approximately
axisymmetric, it can be conveniently quantified in termsof its y-component along the vertical line passing throughthe center of the test particle and the x-component along
the x-axis as defined in Fig. 5. Time was measured fromthe instant at which the test particle came in contact withthe water surface and the distance was measured from theorigin of the coordinate system. The former was identified
by a frame-by-frame analysis the movie images. Fig. 6ashows the y-component of velocity for a 650 μm test particle along the vertical line passing through its center atfive different times; the x-component of velocity along
this line was relatively small. The y-component of velocity
was positive, indicating that the flow was in the upward
direction towards the particle. The fluid velocity near thesurface of the test particle was small, as the test particle
was not moving, and increased with increasing distancefrom the particle reaching a maximal strength at a distance of about one particle radius from the surface. The
velocity then decreased with increasing distance from theparticle, but remained significant for a distance of several
diameters.
The figure also shows that the fluid velocity did not
develop instantaneously after the particle was adsorbed.
For example, at t = 0.167 s, the maximum velocity of
3.10 mm/s was at a distance of 0.78 mm from the particle,
and the velocity at a distance of 5.5 mm was only
0.09 mm/s. The velocity increased with time to reach the140

maximum value of 8.9 mm/s at t = 0.37 s and y =–1.04 mm. At y = –5.5 mm, the velocity at this time was
1.07 mm/s. After reaching the maximum strength, thefluid velocity started to decrease. The decrease firstoccurred closer to the test particle, while it was still
increasing farther away from the particle. For example,
the maximum velocity at t = 0.82 s was 7.12 mm/s at
y = –1.3 mm, and at t = 1.25 s and y = –1.82 it was
5.47 mm/s. The velocity at larger distances from the particle continued to increase for a longer time interval before
starting to decrease. At a distance of y = –5.5 mm, thevelocity at t = 1.58 s was 1.60 mm/s, which was larger thanthe velocity at this location at t = 0.37 s. The streaming flow
slowly reduced in strength but continued for several seconds.
Fig. 6b shows the x-component of velocity for a
650 μm test particle along a horizontal line at five different times; the y-component of velocity along this line wasnegligible. The velocity was positive which means thatthe water near the surface was moving away from theparticle. As in Fig. 6a, the fluid velocity near the test particle was small because it was not moving, and increased
with increasing distance from the particle and then after
reaching a maximal value it decreased with increasing
distance. However, the maximal velocity was at a distanceof about two particle diameters from the particle surface,whereas below the particle the maximum was reached at a
distance of one particle radius. The velocity remained
significant for a distance of several diameters. The maximum water velocity near the surface was comparable tothe maximum velocity below the test particle.
The temporal evolution of streaming flow near thewater surface was qualitatively similar to that in the water
below the test particle. The flow started when the particle
touched the water surface, and reached a maximal value
after a time interval which was comparable to that below
the particle. At t = 0.167 s, the maximum velocity of

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Fig. 7 Temporal evolution of the streaming flow induced by the adsorption of a 2 mm particle. The velocity is shown at fivedifferent time intervals after the test particle came in contact with the water surface. (a) The vertical componentof velocity (V) is shown as a function of –y/R. (b) The horizontal component of fluid velocity (U) is shown as afunction of x/R.

Fig. 8 The figure shows the streaming flow induced by two 650 μm test particles after they came in contact with an air-waterinterface. The particles were dropped in a vertical plane illuminated by a thin sheet of laser light. The velocity
vectors have been superimposed on the PIV images. The flows induced by the particles caused them to moveapart. The size of velocity vectors is arbitrary, and for clarity a larger magnification is used in the plot at t = 0.033 s
than in the later plots.

1.91 mm/s was at a distance of 2.1 mm from the particle,
and the velocity at a distance of 5.5 mm was 1.1 mm/s.
The velocity increased with time to reach the maximum
value of 8.2 mm/s at t = 0.37 s and x = 1.82 mm. At thistime, the velocity at x = 5.5 mm was 4.4 mm/s. Thisshows that the velocity near the water surface was more
intense over a larger area than below the particle. The
strength of the streaming flow then decreased with timewith the decrease first occurring closer to the test particle.
The time interval after which the streaming flow
attained the maximal intensity and the volume over which

the flow extended varied with the particle size. The velocity distribution for a 2 mm particle is shown Fig. 7. The
figure shows that the streaming flow evolution was qualitatively similar to that for a 650 μm particle describedabove. However, it developed relatively more slowly. The
maximum velocity of 13.5 mm/s was reached 1.58 s after
the particle came in contact with the water surface. For a
650 μm particle, on the other hand, the maximal velocity
was reached at t = 0.38 s. For a 2 mm particle, not only
the maximum velocity was larger, it occurred at a larger
distance of 1.38 mm from the test particle, and so the141Naga Musunuri et al. / KONA Powder and Particle Journal No. 31 (2014) 135–145

Fig. 9The figure shows the streaming flow induced by about 20, 650 μm particles after they came in contact with an
air-water interface. The particles were dropped in and near a vertical plane illuminated by a thin sheet of laser light,
and towards the left side of the photographs. The figure shows the motion of the particles that moved to the rightside (some of the particles moved in other directions and so are invisible in the photographs). The velocity vectors
have been superimposed on the PIV images. The size of velocity vectors is arbitrary.

volume over which the flow was intense was larger thanfor a 650 μm particle. Our PIV measurements of the threeparticle sizes considered show that the time interval after
which the maximal flow strength was attained, the volume over which the flow intensity extends, as well as thetime interval for which the flow persists, increase withincreasing particle size.

4.1 Adsorption of two or more particles
We next consider the case in which two 650 μm particles
were simultaneously adsorbed at an air-water interface.
The particles were dropped onto the interface such thatthe line joining their centers was in the plane of the laser
sheet. This ensured that the induced flow was approximately symmetric about the vertical plane passing though
the centers of the two particles, and also about the verticalplane bisecting the line joining their centers. Fig. 8 showsthat each of the particles induced a streaming flow which
was similar to that which was induced by a single particle.
The combined flow below the particles was in the upward
direction and near the water surface the flow was awayfrom the particles. In the region between the particles, thehorizontal flow contributions approximately cancelled andthe vertical contribution added. Thus, the combined
streaming flow was approximately the sum of the flows
induced by the two particles individually, and thus stronger than the flow induced by one particle. The combined
flow developed in about 0.4 s which was comparable tothe time in which the streaming flow developed for a single 650 μm particle.
For the case shown in Fig. 8, the two particles were initially close to each other and so the streaming flow
induced by the first particle caused the second one tomove away, and vice versa. The symmetry of the streaming flow with respect to the laser sheet ensured that thetwo particles remained in the plane of the laser sheet
while they moved apart. However, when the particles

142

were dropped so that the angle between the line joining
their centers and the laser sheet was not small, the streaming flow carried them away out of the plane of the laser
sheet, and so they were visible only for the time duration
for which they were illuminated. For the case shown in
Fig. 8, the speed at t = 0.167 s was approximately
12.3 mm/s. The speed decreased as they moved farther
apart, and also with time as the streaming flow intensity
diminished with time. In fact, after the distance between
them was about 10R their speeds became negligible.
We also considered cases where about 10–30 particles
were dropped onto an air-water interface in and near thelaser sheet (see Fig. 9). Again, each of the particles
induced a streaming flow in the water that was similar to
the flow induced by a single particle. These flows inducedby the particles caused neighboring particles to move
away, and so the net result was that particles moved radially outward from the location where they were dropped.
Experiments show that clusters of particles disperse radially outward from the center (see Fig. 1 which shows
streak lines), and that when the cluster size was larger theradius of the approximately-circular area over which its
particles dispersed and the dispersion velocity werelarger. This increase in the dispersion velocity withincreasing number of particles was also seen in our direct
numerical simulations (Singh et al., 2009). The PIV measurements show that the water rises in the region below
the particles and on the surface it moves away from theparticle.

5. Conclusion and discussion
When a particle comes in contact with a fluid-liquidinterface the vertical capillary force pulls it into theinterface which gives rise to a transient streaming flow.
The PIV measurements show that the liquid below a
newly-adsorbed particle rises upwards and the liquid nearNaga Musunuri et al. / KONA Powder and Particle Journal No. 31 (2014) 135–145

the surface moves away from the particle. The induced
flow for a spherical particle was axisymmetric about thevertical line passing through the particle center. Also, theflow strength is not established immediately after the particle comes in contact with the interface, but builds up
over a short time interval. For a 650 μm glass sphere themaximum flow strength occurred about 0.4 s after theparticle come in contact, and for a 2 mm sphere after
about 1.5 s. We also considered 1.1 mm, 850 mm and
550 mm glass spheres for which the maximal f low
strength occurred after 0.75 s, 0.47 s and 0.18 s, respectively. These results show that the time interval after
which the maximal flow strength occurred decreased withdecreasing particle size.
When two or more particles were simultaneously
adsorbed, the streaming flow was a combination of theflows induced by the particles individually and so the flow
strength increased with increasing number of particles.
Consequently, the distance travelled by the particles near
the outer periphery of a cluster sprinkled on a liquid surface can be several orders of magnitude larger than any
dimension of the area over which the particles weresprinkled. This can be important for some physical processes occurring on a water surface, such as the pollinationof hydrophilous plants, and the transportation and rateof spread of microbes and viruses on a water surface.
Furthermore, the streaming flow can break apart agglomerates of particles when they are adsorbed at a fluid­liquid interface which is important in various processes
in the pharmaceutical and food industries such as wet granulation and food processing.

Acknowledgements
We gratefully acknowledge the support of the National
Science Foundation (CBET-1236035).

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Author’s short biography
Naga Musunuri
Naga A Musunuri is a graduate student in the department of Mechanical and Industrial
Engineering at New Jersey Institute of Technology (NJIT), New Jersey, USA. He
received his B.S. from Jawaharlal Nehru Technological University (JNTU), India in2009 and M.S. from New Jersey Institute of Technology (NJIT) in 2011. His current
research interests include PIV measurements, adsorption, fluid mechanics, biologicalfluid mechanics, microfluidics, and Micro Electro Mechanical Systems (MEMS).

Bhavin Dalal
Bhavin Dalal completed his Ph.D. in Mechanical Engineering from the New Jersey Institute of Technology in 2012. He received his M.S. from Bradley University, Illinois, USAand his B.S. from Gujarat, India.

Daniel Codjoe
Daniel Codjoe graduated for St. Augustine’s College at Cape Coast in Ghana. He
received his B.S. in Mechanical Engineering form New Jersey Institute of Technology in2013. He is interested in working on the water and electricity issues in his native country
Ghana, and other related mechanical engineering related problems.

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Naga Musunuri et al. / KONA Powder and Particle Journal No. 31 (2014) 135–145

Author’s short biography
Ian S. Fischer
Ian S. Fischer is Professor of Mechanical Engineering at New Jersey Institute of Technology. He received his B.S. from Columbia University in 1970, his M.S.E. from Princeton
University in 1973, and his D. Eng. Sci. from Columbia University in 1985. His researchinterests include the flow of solid particles on fluid interfaces, and the dual-number modeling of mechanical systems. He is a member of the American Society of MechanicalEngineers.

Pushpendra Singh
Pushpendra Singh is Professor of Mechanical Engineering at New Jersey Institute ofTechnology. He received his B.S. form IIT Kanpur in 1985, and M.S. and Ph.D. from the
University of Minnesota in 1989 and 1991, respectively. His research interests include
Newtonian and non-Newtonian fluid mechanics, biological fluid mechanics, microfluidics,
direct numerical simulations and modeling of multiphase flows, including those on fluid-­liquid interfaces, and electrohydrodynamics. He is a fellow of the American Physical Society and the American Society of Mechanical Engineers.

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KONA Powder and Particle Journal No. 31 (2014) 146–155/Doi:10.14356/kona.2014004

Original Research Paper

Characterization of Oxide-Dispersion-Strengthened (ODS)
Alloy Powders Processed by Mechano-Chemical-Bonding(MCB) and Balling Milling (BM) †Longzhou Ma 1*, Bruce S.-J. Kang 2, Mary A. Alvin 3 and C. C. Huang 4
1

Harry Reid Center for Environmental Studies, University of Nevada, USA
Department of Mechanical and Aerospace Engineering, West Virginia University, USA
3
US DOE National Energy Technology Laboratory, USA
4
Hosokawa Micron Powder Systems, USA
2

Abstract
Two types of powder processing techniques, Mechano-Chemical-Bonding (MCB) and MCB plus ball- milling(BM) with reduced time, have been employed to process the nickel-based oxide-dispersion-strengthened (ODS)
alloy powders with composition of Ni-20Cr-5A1-3W-1.5Y2O3 to explore the alternate routes for fabricating,homogenizing and mechanical alloying (MA) the ODS alloy powders, which are usually processed by a prolonged
ball-milling or rod-milling technique. In order to examine and evaluate the microstructure, morphology, blending
homogeneity and MA effect of alloying powders, the commercial ball-milled ODS MA 956 alloy powders andexperimental alloy powders processed by MCB only and MCB plus BM were subjected to microscopic andspectroscopic characterization and analysis using X-ray diffraction (XRD), scanning electron microscopy (SEM),
and transmission electron microscopy (TEM). A FIB (focus ion beam) lift-out technique was employed to prepare
the TEM cross-section samples of processed powders. The results showed that the MCB plus BM with reduced
time could produce the ODS alloying powders with homogeneous lamellate structure similar to MA 956 powders
processed by conventional BM technique with a prolonged period of time. The ODS alloy powders processed by
MCB plus BM are to be utilized to fabricate the bulk ODS alloy product in the further research phase.
Keywords: oxide-dispersion-strengthened (ODS) alloy, Mechano-Chemical-Bonding (MCB), ball-milling (BM),
X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy(TEM), lamellate structure

1. Introduction
Nickel-based oxide-dispersion-strengthened (ODS)
superalloys such as MA 956 or MA 6000, synthesized via
mechanical alloying (MA) and consolidation process,exhibit the intermediate temperature strength as well as
elevated temperature strength and creep resistance bymeans of the combined strengthening of gamma primeprecipitates and nano-sized yttrium oxide (Y2O3) particles(Chou and Bhadeshia, 1993; Haghi and Anand, 1990;
Howson et al., 1980). The Ni-based ODS superalloys are

†
1
2
3
4

*

Accepted: June 1, 2013
Las Vegas, Box 454009, 4505 Maryland Parkway, Las Vegas,
NV89154, USA
Morgantown, WV26506, USA
Pittsburgh, PA15236, USA
Summit, NJ07901, USA
Corresponding author:
E-mail: lma@nanosteelco.com
TEL: +1-702-217-2966 FAX: +1-208-552-2923

146

very promising for use in aircraft and advanced gas turbine engines due to their mechanical property and environmental resistance at high temperature. Also since
yttria particles serve for interfacial pinning of the moving
dislocations as well as yttria can be transformed to thenano-sized cluster during manufacturing, ODS alloys
offer not only the improved creep resistance at elevatedtemperatures (up to 1200°C) but also low void swelling atcondition of high energy high speed neutron irradiation.
For example, recent extensively studied ferritic ODS
alloys, MA 957 and 14WYT alloy with nominal composition of Fe-14Cr-1Ti-0.3Mo-0.3Y2O3 and Fe-14Cr-1Ti-3W0.3Y2O3, respectively, are being considered for a numberof advanced nuclear reactor applications at temperature of
500–600°C as well as in neutron irradiation higher than
300 dpa and elevated gas (Helium) concentration levelowing to their high temperature strength and low void
swelling (Odette et al., 2008; Schaublin et al., 2006; Ukai
et al., 1998). Fabrication of ODS alloys is a complicated,costly and time-consuming process, which involves the©2014 Hosokawa Powder Technology Foundation

Longzhou Ma et al. / KONA Powder and Particle Journal No. 31 (2014) 146–155

mechanical alloying (MA) powder metallurgical process,consolidation by hot deformation and post heat treatment(Gilman and Benjamin,1983; Suryanarayana, 2008). The
MA process is the core step to fabricate ODS alloys,
involving that the elemental alloying powders or oxide
compounds are subjected to the high energy ball millingor rod milling for up to 60–72 hours to allow the nanosized yttria particles to be dispersed homogenously
throughout the master particles. After MA processing, theblended and alloyed powders are degassed, canned andconsolidated by hot isostatic pressing (HIP) or hot extrusion. The consolidated material is then hot worked tosemi-finished products. The hot worked material is further annealed and aged to yield the desired microstructure
and properties for various applications. The complicatedfabrication process has become a major barrier to commercially produce the ODS materials, leading to an
extremely high raw material cost. For example, it costs
about $345/kg for Ni-based ODS MA 956 alloy, however
it only costs about $30–35/kg for Ni-based superalloys
such as INCONEL 718 and 617 (Busby, 2009). In addition, numerous hours of MA milling time can cause highlevels of contamination from milling debris and gaseousenvironment.
Recently developed Mechano-Chemical-Bonding(MCB) technology is an effective approach to blend alloying powders, forming the composite particles consistingof the hosting particles as core and small particles orfibres that are coated around the core. The MCB-induced
particle bonding process takes place in the solid state
without needing solvents or external heating avoiding
potential contaminations and reactions. During MCB processing, the starting powder mixtures are subjected tohigh compression, shear, and impact forces as they passthrough a narrow gap in a high speed rotating device. As
a result, the particles are dispersed, mixed, shaped, andbonded together, consequently forming the composite
particles composed of various combinations of the starting ingredients (Du Pasquier et al., 2009; Murata et al.,
2004; Nam and Lee, 1999; Welham et al., 2000). So far,
the green MCB technology has been utilized to make various composite particles used in the fields of functional
gradient materials, batteries, cermets, fuel cells, polymers, cosmetics, and pharmaceuticals. Preliminary studies showed that utilization of MCB processing to blend
ODS alloying powders was able to homogenously
disperse yttrium oxides on the base particles to form thecomposite structure (Kang et al., 2010). Also, the newly
developed MCB processing technique is simple, environmentally friendly, and can be scaled up to 300 litres perbatch. Thus, MCB or its combination technique is considered as an enhancement or alternative to the conventional
mechanical alloying (MA) process using balling millingor rod milling.

In this study, the technique of MCB as well as MCB plus
BM with reduced time were employed to process the ODS
alloying powders to explore the alternative method of theconventional time-consuming ball milling or rod milling
technique. The processed alloying powders were examined
and analyzed microscopically and spectroscopically using
TEM, SEM and XRD to identify the mechanical alloying
effects such as powder microstructure, morphology, andchemical homogeneity. In order to compare the blending
effects, commercial ODS MA 956 alloy powders processedby conventional BM were examined in parallel as a benchmark, while it is iron-based. As a preliminary researchphase, the goal of this study is to examine the mechanicalalloying effects produced by the proposed techniques,
MCB only and MCB plus BM. The processed ODS alloying powders will be either used as spray powders foradvanced coating or followed by canning, HIP, hot rolling
and annealing to form final ODS products in the next
research phase. This study is an attempt to fabricate the
ODS alloying powders using the proposed techniques as a
substitute or to simplify and improve the MA processes.

2. Materials and Experiments
2.1 Materials
Commercial metallic and ceramic powders including
Y2O3 (< 50 nm, 99.99% pure), Al (4.5–7 mm, 97.5% pure),
Cr (7.5–10 mm, 99.5% pure), and Ni (4–8 mm, 99.9% pure)
were purchased from Sigma Aldrich Inc. Saint Louis,MO., Alfa Aesar, Ward Hill, MA, F.W. Winter Inc. & Co.
Camden, NJ, and Atlantic Equipment Engineers, Bergenfield, NJ, respectively. These powders were stored separately in an inert environment in sealed bottles full of argon
gas. Considering the short time milling as well as no ballpowder-ball collision involved during MCB only process,the average sizes of all starting powder constituents ranged
from 0.5 to 15 microns in this study (Du Pasquier et al.,2009; Nam and Lee, 1999; Welham et al., 2000). For conventional ball milling or rod milling MA process, however,the starting powders usually have average diameters ranging from 30 to 500 microns (Suryanarayana, 2008). The
starting powders were initially mechanically blended undergas protection inside a glove box chamber according to thenominal composition (wt%) of Ni-20Cr-5A1-3W-1.5 Y2O3.
The just-blended powders were then placed into bottles thatwere sealed and filled with argon gas to prevent oxidationof powders. Each bottle containing the just-blended ODS
alloying powder sample weighed approximately 200 g. To
compare the effects of different processing techniques, thecommercial ODS MA 956 alloy powders, which have anominal composition of Fe-20Cr-4.5Al-0.5 Y2O3-0.5 Ti andhave been subjected to conventional BM at 200 RPM (rota-

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tion per minute) for 72 hours, was obtained from Special
Metals Co., Huntington, WV, as a benchmark material.

2.2 Powder Processing
Two types of processing technique, MCB only and
MCB plus BM, were employed to process the as-justblended starting powders to fabricate the experimental
ODS alloy powders. For MCB only procedure, the starting powders were MCB processed at a speed to 4000
RPM for only 30 minutes. It was expected to have Y2O3
nanoparticles dispersed and bonded onto the surfaces oflarger hosting particles such as Ni and Cr particles, which
in turn created oxide dispersion and MA (mechanicalalloying) effects. After MCB processing, the powders
were stored in the sealed bottles filled with argon gas. The
MCB processing was conducted in Hosokawa Micron
Powder Systems, Summit, NJ. Following MCB processing, a portion of MCB-processed powders (200 g) was
then conducted ball milling (BM) at 200 rpm for 20 hours
under inertial gas protection condition. Considering thepowders have been processed using high speed MCB for
30 minutes, the BM processing time was reduced to 20
hours in comparison with conventional BM time of 70
hours for MA processing. The BM processing was performed at West Virginia University, Morgantown, WV.
After processing, small amount of powders (5–10 g) weretaken for micro-structural analysis using TEM (transmission electron microscopy), SEM (scanning electron
microscopy) and XRD (X-ray diffraction), and the rest of
powders were stored for the next research phase use. The
micro-structural analysis of experimental powders was
conducted at University of Nevada Las Vegas, NV.

2.3 Characterization
2.3.1 X-Ray Diffraction (X-RD) Analysis

The processed powders were characterized by X-ray
powder diffraction (XRD) using a PANalytical X’Pert PRO
X-ray diffractometer with a CuKa radiation (45 kV, 40 mA),
and a multiple-strip solid state detector (X’Celerator ®).
The sample was prepared by suspending 2–3 g powders
in ethanol to make slurry. The slurry was then set on a
low-background silicon sample holder. The XRD patterns
were recorded at room temperature with step-sizes of
0.017°, 2q, and 46 s per step. The phase constitution andcrystallographic parameters were characterized using theInternational Center for Diffraction Database (ICDD) for
powder diffraction data. The analysis of line broadening
effect would be conducted to measure the mechanicaldeformation and crystal size.

2.3.2 Electron Microscopy (EM) Analysis

The microstructure, morphology, topology and elemental

148

chemical distribution of the processed powder samples
were studied by EM techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM). SEM imaging was performed on a JEOL
scanning electron microscope, JSM-5610 SEM, equippedwith secondary electron (SE) and backscattered electron(BE) detectors and an Oxford ISIS EDS system. The
acceleration voltage used in SEM was 15–18 kV using the
SEM BE and SE mode. In order to improve the conductivity and image contrast, the powder samples were
coated with a layer of gold. Gold-coated samples weresuspended on the double-sided carbon tapes for SEM
observation and imaging. Also, SEM images of processed
powders were employed to measure the size of powder
particle using an image processing software, Image J withversion of 1.46. Note that since most particles showedround morphology, the particle size indeed referred to an
equivalent diameter of a particle. Following the particle
analysis procedure of Image J, 10 SEM images totally atleast containing about 200 sampling particles were analysed to obtain the particle size at different processing
conditions.
A TECNAI-G2-F30 transmission electron microscopewith a 300 keV field emission gun was used to characterize
the powder samples. Samples were analyzed using the conventional bright field (BF), selected-area diffraction (SAD)
and high-angle annular dark-field scanning-transmission
electron microscopy (HAADF-STEM) mode for defects,
diffraction and Z-contrasting imaging, respectively. All
TEM images were recorded using a Gatan SC 200 CCD
camera with resolution of 2k × 2k. The elemental distribution of each sample was also determined using the corresponding X-ray energy dispersive spectrometry (EDX)
under the STEM mode. For STEM/EDX mode, the electron probe with a size of 0.2 nm was used to examine thededicated area of sample. In order to examine the internal
microstructure of processed powders using TEM in afiner scale, the cross-sectioned TEM sample of experimental powders was prepared, involving that 4–6 mg of
powders were mixed with spur resin in a micro-vial,which was then solidified by furnace drying at 60°C overnight. The spur resin used for these samples was a mixtureof 10.0 g of ERL (vinylcyclohexene dioxide), 4.0 g of DER(a diglycidyl ether of polypropylene glycol), 26.0 g of NSA(nonenyl succinic anhydride), and 0.4 g of DMAE (dimethylaminoethanol). The powders embedded in the resin wasthen thinned into membranes with a thickness of 50–80 nm
using a FEI Nova 200 FIB (focus ion beam) system, which
combines the FIB technology with SEM in a single tool.
This system can provide SEM imaging in order to monitor
the whole process during FIB milling. A FIB cross-section
lift-out technique based on a TEM-wizard program in FIB
system was used to obtain the cross-sectioned TEM sample
of powders (Giannuzzi and Stevie, 1999; Stevie et al.,Longzhou Ma et al. / KONA Powder and Particle Journal No. 31 (2014) 146–155

Fig. 2

Fig. 1XRD patterns of starting and processed powders.

2001). The preparation of TEM cross-sectioned samples
by FIB was conducted at Arizona State University,
Tempe, AZ.

3. Results and Discussions
3.1 X-RD Analysis
Fig. 1 presented the X-RD spectrum of all experimental
powder samples including as-received Y2O3 powder,
as-blended starting powder, MCB processed powder, MCB
plus BM processed powder, and commercial MA 956 powder samples. For as-received yttria and just-blended starting powders, the typical sharp diffraction peaks of all
alloying constituents, Al, Cr, Ni, W and Y2O3 wereobserved in X-RD spectrum. The spectrum of as-received
Y2O3 particles displayed the line-broadening effects due tonano-scaled size of yttria. For MCB processed sample, allindividual alloying elemental peaks are still observed withidentical intensities relative to the spectrum of just-blended
sample. Also the line broadening effect was noticed inspectrum of MCB processed sample, suggesting small
deformation occurred during MCB processing. However,for MA 956 and MCB plus BM processed samples, only
major elemental peaks with substantially reduced intensities, NiAl (110) and FeCr (110) peaks, were observed, suggesting significant change of crystallographic structure due
to formation of solidified phase and presence of defects
compared to the spectrum of as-blended sample. Also,
extensive line-broadening effects were evident for MA 956
and MCB plus BM processed samples, suggesting extensive plastic deformation involved during processing. Using
the peak width of just-blended powders as a reference, theline-broadening effect could be used to estimate the microstrain and crystal size of powder. X-RD line broadening
effect is usually contributed from micro-strain, fine crystal
size, and systematic error of instrument. The following

Analysis of line-broadening effect.

equation can be written to account for these contributions(Cullity and Stock, 2001; Suryanarayana and Norton,
1998):
Br cos=k+  sin 
L(1)

Where, Br is peak FWHM (full width at half maximum);q is diffraction angle; k is a constant (0.89–1.39); l is
X-ray wavelength; L is the average crystal size; and h is
micro-strain of crystal.
Using the average width at FWHM, Br, and corresponding diffraction angle, q, obtained from spectrum,
Fig. 2 presents Br× cos (q) as a function of sin (q) basedon equation (1). The slop and intercept of the fitting line
represent the micro-strain and crystal size of powder,
respectively. From Fig. 2, the powders processed by MCB
have micro-strain of 0.26% and crystal size of 720 nm,
and the powders processed by MCB plus BM have microstrain of 1.45% and crystal size of 177 nm. The X-RD
broadening analysis suggests that MCB plus BM produced larger strain and smaller crystal size than MCB
only. X-RD spectrum analysis of powders processed by
MCB indicates that the MCB process in this study would
not remarkably change the crystallographic structure andpowder size, and MCB could disperse the nano-sized
Y2O3 particle resulting in the disappearance of Y2O3 peakin XRD spectrum.

3.2 SEM Microscopy
SEM imaging was conducted on the experimental powder samples showing the morphology, topology, anddimension. Fig. 3 presents SEM micrographs of MA 956
powders and experimental powders processed by MCB
and MCB plus BM, indicating that conventional BM andMCB plus BM processing produced the random shaped
particles, Fig. 3 (a) and (b). The insets in Fig. 3 (a) and (b)show that the powders processed by BM and MCB plus
BM contain numerous lamellate structures, suggestingthat large deformation, cold-welding, and fracture

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Fig. 3

SEM micrographs of processed powders. (a) Powders of MA 956, (b) Powders processed by MCB plus
BM and (c) Powders processed by MCB only.

occurred during processing. For powders processed by
MCB only, the powder size almost kept unchanged comparing to the starting size, Fig. 3 (c). However the composite structure and topography was observed, indicatingsmall particles were bonded with master particle forming
the composite one as seen in insets. All MCB processed
powders keep spherical, suggesting small crystal microstrain. Based on the SEM observation results, particle
analysis of processed powders was conducted to statistically measure the distribution of effective particle size.
Fig. 4 plots histogram of particle size distribution for
powders subjected to different processing, indicating that
MA 956 alloy powders, powders processed MCB plus
BM, and powders processed by MCB have mean effective
particle size of 121.50, 28.42, and 5.40 mm, respectively.

3.3 TEM Microscopy and Spectroscopy
As an example, Fig. 5 presents SEM micrographs of
TEM cross-sectioned powder sample prepared by a FIB
lift-out technique procedure for the powders processed by
MCB, showing powder particles were mounted by thespur resin and particle area in resin specimen was delineated and protected from sputtering by deposition of a platinum line. Then, trenches were cut and milled in front andback of the deposited line until an electron-transparent
membrane was available, Fig. 5 (a). The thin membrane150

was cut at all ends, lift out by a needle, and welded on agrid for TEM observation, Fig. 5 (b) and (c). Fig. 6 presents TEM micrographs of the cross-sectioned powder
sample of MA 956 alloy powders. TEM BF image in Fig. 6(a) showed numerous of defects and lamellar structures,and inset with high magnification showed the lamellar
structures contained lots of moiré fringes, indicating heavy
deformation occurred during powder BM processing. The
overall microstructure of MA 956 powder is very uniform. The corresponding SAD image in Fig. 6 (b) reflects
the ring patterns with Fe, Cr and solid-solution phase(FeCr) contribution. The Fe-matrix produced diffuse
rings, suggesting fine grains of heavily deformed. The
FeCr phase was identified which was consistent with XRD
results.
Fig. 7 and Fig. 8 show TEM micrographs of samples
processed by MCB plus BM and MCB, respectively.
Compared to the well-defined lamellar structures of MA
956 alloy powders, TEM BF image of powder sample processed by MCB plus BM displays numerous deformed
fragments and defects, Fig. 7 (a). Some layered structures
still appeared and inset shows numerous moiré fringes.
Fig. 7 (b) represents the corresponding SAD pattern
including Ni-matrix diffuse ring, faint rings and spots
associated with reflections of Ni, Cr, NiCr, and yttria,
suggesting formation of secondary phase, NiAl, and thepresence of some un-deformed metals. For powder sample

Longzhou Ma et al. / KONA Powder and Particle Journal No. 31 (2014) 146–155

Fig. 4

Histogram of size distribution of processed powders. (a) Powders of MA 956, (b) Processed by MCB plus
BM, and (c) Processed by MCB only.

Fig. 5

Powder TEM cross-section sample preparation by FIB Lift-out procedure. (a) A metal line was depositedover region of interest and trenches were milled in the front and back side of deposited line. (b) A membrane was cut and picked out. (c) A TEM cross-section sample of powders processed by MCB.

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Fig. 6

TEM micrographs of MA 956 powder sample. (a) TEM BF image, (b) Corresponding SAD image.

Fig. 7

TEM micrographs of powders processed by MCB plus BM. (a) TEM BF image, (b) Corresponding SAD
image.

Fig. 8

TEM micrographs of powders processed by MCB. (a) TEM BF image, (b) Corresponding SAD image.

processed by MCB only, lamellar structure did not appear
in TEM BF image, Fig. 8 (a). Instead, lots of nano-sizedparticles distributed on the Ni-matrix and moiré fringes
are still visible, but amount is less than samples processedby BM and MCB plus BM. SAD pattern in Fig. 8 (b)152shows lots of individual spots associated with Ni, Al, Cr,and yttria reflection, indicating lots of metal particle werebonded with matrix, but solid-solution phase wasn’t
formed yet. Therefore, powders processed by MCB plus
BM have similar microstructure to MA 956 powder, while

Longzhou Ma et al. / KONA Powder and Particle Journal No. 31 (2014) 146–155

Fig. 9

STEM/EDX line-scanning analysis. (a) MA 956 powder sample, (b) MCB plus BM processed sample, (c) MCB processed powder sample, and (d) Close-viewed plot of (c).

the latter has more uniform lamellar structure. To get better
MA and dispersion effects using MCB plus BM route, aproper combination of the starting powder sizes, energy
input, and MCB processing time should be optimized.
In order to examine the chemical homogeneity of alloying elements across the powder cross-section, STEM
Z-contrast imaging and EDX line-scanning analysis wereconducted. Fig. 9 presents the results of EDX line-scanning
analysis and the insets show Z-contrast imaging and scanning direction. For MA 956 and MCB plus BM processed
powder sample, EDX line scanning results show the alloy
elements and Y2O3 have been dispersed homogeneously
throughout the matrix, and Fe-Cr and Ni-Cr could beexchangeable, Fig. 9 (a) and (b). The inset images show thehomogeneous contrast profile, indicating the homogeneous
distribution of elements. For powder sample processed by
MCB as seen in Fig. 9 (c), Ni-matrix particle displays
strong intensity and other elements are relatively weak but
detectable. Fig. 9 (d) was the close-view of EDX spectrumwith weak counts in Fig. 9 (c), indicating that yttrium was
detected distributing around the edge of particle as highlighted by circle. Z-contrast image of hosting particle show
deformation occurred around particle edge.

4. Conclusions
A Mechano-Chemical-Bonding (MCB) as well as MCB
plus ball milling (BM) with reduced time technique
was used to fabricate, blend and homogenize the oxide
dispersion-strengthened (ODS) nickel-based superalloy
powders. The processed powders and MA 956 alloy powders have been characterized using X-RD, SEM andTEM. The results suggested the following conclusions:
1. As a benchmark material, MA 956 alloy powders
subjected to prolonged BM processing contained numerous uniform lamellar structures, moiré fringes, anddefects. The solid solution phase, FeCr, has been formed
during BM, and alloying elements have been homogeneously dispersed.
2. Utilization of MCB and MCB plus BM technique toblend the ODS alloying powders could introduce the latticestrain, and defects. The technical route of MCB plus BM
generated larger strain and smaller crystal size than MCB.
3. The MCB processing could produce composite particles bonded with other small particles such as nano-sized
yttria.
4. MCB plus BM with reduced time could produce thehomogeneous lamellate structure and chemical homoge-

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neity similar to MA 956 alloy powders. As an alternate,
MCB plus BM process is possible to be employed to prepare ODS powders with reduction of BM time. Further
exploring the effects of MCB plus BM processing parameters on microstructure and morphology of ODS alloying
powders would be necessary to optimize the process.
Also, follow-up work to produce surface coating or tofabricate ODS alloy final products by HIP, hot deformation and heat treatment using the MCB processed powders
are necessary to validate this technical route.
5. MCB technique is potential to be employed todisperse only nano-sized yttria particles on the pre-­alloyed micron-sized hosting particles to fabricate ODS
alloying powders.

Acknowledgements
This research is supported by US Department ofEnergy, National Energy Technology Laboratory (NETL),
and Advanced Research Materials (ARM) Program under
RDS Contract DE-AC26-04NT41817.606.01.01. The
encouragement and support by Patricia Rawls and Robert
Romanosky, Program Managers, are very much appreciated. Thanks are also due to TRP (Transmutation
Research Program), University of Nevada, Las Vegas, forsupporting X-RD, SEM and TEM analysis in instrument
usage and working time.

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Pittsburgh, PA, USA, May 25–27, 2010.
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Approach, Plenum Press, New York, 1998. pp. 207–221.
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Longzhou Ma et al. / KONA Powder and Particle Journal No. 31 (2014) 146–155

Author’s short biographyLongzhou Ma
Dr. Longzhou Ma is formerly a research scientist of Materials Engineering at Harry Reid
Center for Environmental Studies, University of Nevada Las Vegas. Currently, Dr.
Longzhou Ma is a senior research engineer of R & D, NanoSteel Company, Inc., Idaho
Falls, ID83404. His expertise includes microstructure characterization using transmission electron microscopy (TEM), scanning electron microscopy (SEM), optical microscopy. Dr. Ma is also known for his expertise in dislocation analysis in materials structure
and crack propagation analysis in metallic materials. Over the years, he has publishedover 35 peer-reviewed papers. Dr. Ma has affiliation with numerous engineering society
including TMS, MRS, MSA. As a PI or co-PI, he ever involved several US DOE-­
sponsored research projects. Dr. Ma can be reached at lma@nanosteelco.com.

Bruce S.-J. Kang
Dr. Bruce Kang is a Professor at the Mechanical and Aerospace Engineering Department, West Virginia University. Dr. Kang’s current research activities include: (1) SOFC
and CO2 re-use, (ii) Biomass energy conversion, (iii) high temperature materials foradvanced power systems, (iv) experimental and multi-scale computational modeling
analyses of metallic and intermetallic alloys, and (vi) surface material property evaluation using micro/nano indentation.

Mary A. Alvin
Mary Anne Alvin, DOE NETL: Ms. Alvin currently serves as a Division Director for
the Office of Research and Development (ORD), Department of Energy’s National
Energy Technology Laboratory. She also leads ORD’s advanced gas turbine engine
materials development and heat transfer research efforts for land-based power generation. Prior to joining DOE NETL in 2005, Ms. Alvin had thirty years of experience at
Westinghouse and Siemens Westinghouse, working in the area of advanced energy system. Ms. Alvin was awarded the Siemens Westinghouse Eagle Award in 1999, which is
the highest corporate award at Siemens that is granted to an employee. She currently
holds twenty-six patents with additional pending.

C. C. Huang
Dr. C. C. Huang is the Director of Business & Technology Development at Hosokawa
Micron Powder Systems, an operating unit of Hosokawa Micron International Inc., aglobal supplier of systems and equipment related to material sciences and engineering.
He holds an M.S. degree in engineering from Illinois Institute of Technology and a Ph.D.
degree in chemical engineering from West Virginia University. Dr. Huang specializes inpowder and nanoparticle processing, powder characterization, powder granulation, andfluidization. He has published over 30 articles and 8 patents, chaired several meetings,
and is an active member in a number of scientific and engineering societies.

155KONA Powder and Particle Journal No. 31 (2014) 156–162/Doi:10.14356/kona.2014005

Original Research Paper

Synthesis of Calcium Carbonate Particles in
Octylamine/Water Bilayer Systems †Jun Wang 1,2*, William B. White 1 and James H. Adair 1
1
2

NSF Particulate Materials Center, Department of Materials Science and Engineering, The Pennsylvania State University, USA
A123 Systems, LLC, USA

Abstract
Calcium carbonate particles with various shapes and morphologies were prepared via precipitation in an
octylamine/water self-assembly bilayer systems. Crystal structure and shape of the CaCO3 particles were
determined by the water to octylamine molar ratio R of the bilayer. At R = 16.0, phase pure calcite particles with a“hopper crystal” morphology were formed, the average particle size of the hopper crystal is 10 μm with welldefined edges on the hopper faces. Decrease the R ratio to 7.2 eventually leads to the formation of 3 μm tabular
CaCO3 particles which are predominated by vaterite structure. For an intermediate R of 10.8, spherical vaterite
aggregates and rhombohedral calcite particles were produced. Thermal decomposition of the CaCO3 particles wasobserved at around 710°C. The mechanism of particle evolution in the self-assembly bilayer, particularly theformation of “hopper crystal” calcite was discussed.
Keywords: powder, ceramics, chemical synthesis, Raman spectroscopy, crystal structure

1. Introduction
Calcium carbonate is one of the most abundant minerals
on earth and finds its increasing applications in pigments,
water treatment, biomineralization and energy storage(Colfen, 2003). It is equally important in scientificresearch and much attention had been focused on the
crystal growth and morphology development under anumber of conditions (Adair and Suvaci, 2000; Meldrum,2003). McCauley and Roy (1974) extensively explored theprocessing parameters that affected the crystal growth of
CaCO3 polymorphs precipitated from aqueous solutions.
The growth of CaCO3 crystals was intertwinedly determined by solution pH, reactant concentration, and impurity ions at ambient conditions. This effort was extended
by Wang et al. (1999) in the precipitation of Ca ions withurea at 90°C, and by Jung et al. (2000) for calcium carbonate formed in a Couette-Taylor reactor. A theoreticalunderstanding of the crystallization habit of precipitated
CaCO3 was carried out by de Leeuw and Parker (1998)
using atomistic simulation, which indicated the surface
and hydration energy may directly control the formationof favored crystal structures. More recently, the precipit­
†
1
2

*

Accepted: June 3, 2013
University Park, PA 16802, USA
200 West Street, Waltham, MA 02451, USA
Corresponding author:
E-mail: junwang@a123systems.com
TEL: +1-617-972-3456 FAX: +1-617-924-8910

156

ation of calcium carbonate particles was incorporated
with polymeric additives (Archibald et al., 1996; Osman
and Suter, 2002; Park and Meldrum, 2002; Rock et al.,
1997; Rudloff and Colfen, 2004; Wei et al., 2004; Xu et al.,2005) and gold nanoparticle template (Lee et al., 2001)
so as to gain adequate control of the crystallization andmorphology development.
The crystallization of CaCO3 particles under confinedenvironment was initially studied by Mann et al. (1991),
Rajam et al. (1991) and Heywood et al. (1991) using compressed Langmuir monolayers of stearic acid and octadecylamine. The structure and morphology of the CaCO3
particles were significantly dedicated by the type of surfactant molecule as well as Ca2+ concentration (Walker etal., 1991). Analogy to the monolayer-confined synthesis,
octylamine/water bilayer systems was employed by Adair
et al. (1998) to grow a number of nanoscale platelets
including CdS, (Adair and Suvaci, 2000; Adair et al.,1998) Ag (Yener et al., 2002) and SiO2 (Wang et al., 2006)
at ambient condition. When mixed with water underappropriate weight ratio, the amines will orient in such a
way that allows organic layer and aqueous layer to alternate in the solution, mainly because of the amphiphilic
nature of the organic molecules (Adair et al., 1998;
Ralston et al., 1942). The thickness of each layer isdirectly related to the amine to water weight ratio, which
provides an effective pathway to manipulate the template
thereby the nanoparticle thickness during synthesis. Thisapproach is applicable to numerous materials where©2014 Hosokawa Powder Technology Foundation

Jun Wang et al. / KONA Powder and Particle Journal No. 31 (2014) 156–162

chemical reactions such as precipitation, redox, andhydrolysis are feasible in aqueous media.
Previous studies demonstrated that crystal structureand shape of the CaCO3 particles are sensitive to a number of processing parameters (Colfen, 2003; McCauley
and Roy, 1974; Walsh et al., 1999), thus preparation of
CaCO3 with desired phase and shape may require precise
control over the experimental procedures. Therefore, theintent of this work is to report the preliminary study on
CaCO3 particles precipitated from octylamine/water
bilayer systems, an interesting crystal habit known as
hopper crystal was observed. The possible mechanisms
responsible for shape and morphology changes werediscussed.

2. Experimental Procedure
2.1 Particle Synthesis
All chemicals involved in the synthesis were reagent
grade and used as-received without further purification.
CaCl2 (99+%, J. T. Baker, NJ) and Na2CO3 (99+%, J. T.
Baker, NJ) were used as the precursors for CaCO3.
Octylamine (99%), amylamine and polyethylenimine
were purchased from Aldrich (Aldrich Chemical Co.,
Milwaukee, WI), while ethanol (94.4%, 188.8 proof),
nitric acid and glacial acetic acid were obtained from J. T.
Baker Chemicals. Deionized water was used (specificconductivity = 0.4 × 10 –7 S/m) for all experiments.
The procedure used to prepare CaCO3 particles is similar to that applied to produce platelet-like CdS particles in
the octylamine/water bilayer systems (Adair et al., 1998).
The general procedure can be described as follows, 25 mL
0.05 M CaCl2 and 0.05 M Na2CO3 aqueous solutions weremixed with 31.97 mL octylamine and 1.33 mL amylamine
to form two individual batches of self-assembled bilayers(amylamine is able to stabilize the octylamine/water bilayer
and provide a well-defined bilayer structure) (Yener et al.,2002). After shaking for 10 minutes, the two bilayers weremixed together and shaken for 24 hours. Precipitation andcondensation of CaCO3 particles takes place in the octylamine/water bilayer during vigorous shaking. The bilayer
system was subsequently broken by adding 60 mL 0.5 M
HNO3/ethanol solution and 1.25 mL 0.1 wt% PEI/ethanol
solution (1 w/w PEI). The washing step was repeated 5
times by simply collecting CaCO3 particles on the bottomof the beaker and removing the supernatant. It is important
to control pH of the suspension close to pH 9 in each washing step, which allows the maximum yields of CaCO3(McCauley and Roy, 1974). The final suspension of CaCO3
particles in ethanol has a concentration of 3.0 mg/mL and a
pH close to pH 9. A schematic flow sheet for the entire procedure is shown in Fig. 1.

Fig. 1

Flow sheet of CaCO3 particles synthesized from octylamine/water bilayer systems. The pH of the bilayer iscontrolled at pH 10. The octylamine to amylamine
weight ratio is 25 (Yener et al., 2002).

2.2 Characterization
The morphology of the CaCO3 particles was analyzed
with scanning electron microscope (SEM, Hitachi
S-3000H, Tokyo, Japan). Structural analysis for CaCO3
particles was carried out with powder X-ray diffraction(XRD, Scintag pad V, Cu Kα 1.5418 Å). Raman spectra of
the CaCO3 powders were obtained using an ISA microfocus Raman spectrometer (Spectra Physics 164 Ar+ laser,
λ = 514 nm), CaCO3 powders were placed on a zero background glass slide for each scan. Thermogravimetricanalysis (TGA, TA 2050, TA Instruments, USA) was used
to study the thermal stability and decomposition of
CaCO3 powders as a function of temperature under constant air flow.

3. Results
Fig. 2 shows the morphologies of the CaCO3 particles
with various processing conditions. At R = 16.0 (water tooctylamine molar ratio), CaCO3 particles precipitated in thebilayers are about 10 μm and form the so-called “hopper”
crystals (Fig. 2a) (Buckley, 1952), each face of the crystal
showing an inverse growth pyramid. The same hopper
crystal morphology was observed in CaCO3 precipitatedfrom alcohol/water solution (Dickinson and McGrath,2003) and in calcium iodate monohydrate (Shitole andSaraf, 2002) grown by silica gel technique. Decrease the R

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Fig. 2 SEM micrographs of CaCO3 particles prepared from octylamine/water bilayer systems. (a) R = 16.0, hopper crystals of calcite, (b) R = 10.8, sphere-like and rhombohedral CaCO3 particles, (c) R = 7.2, tabular CaCO3 particle aggregate. R is themolar ratio of water to octylamine.

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ratio to 10.8, the thickness of the aqueous layer is compressed due to a reduced amount of water, particle size
decreases accordingly. It is obvious that the particle shapechanges as revealed by the SEM analysis in Fig. 2b, twotypes of particles, sphere-like and rhombohedral coexist in
this condition. Fig. 2c shows that tabular CaCO3 particles
can be produced when R ratio is 7.2, corresponding to70 wt% octylamine in the bilayer. Average face diameter of
the tabular CaCO3 particles is about 3 μm. The thickness ofthe primary tabular particle is unknown because of theagglomerated nature of the particles as well as the limitation of the SEM. A well-defined crystal morphology isformed with R = 16.0, although particles show hopper habitof sharp growth edges. However, at low R values with thinner aqueous layers, the morphologies of the CaCO3 particles are poorly-evolved, resulting agglomerated sphere-like(R = 10.8) and tabular (R = 7.2) shapes. More precisely, themorphology at R = 10.8 is a mixture of near perfect rhombohedra and sphere-like particle aggregates.
The various crystal morphologies of CaCO3 shown in
Fig. 2 actually belong to different crystal structures as
illustrated by XRD analysis in Fig. 3. The hopper crystal
of CaCO3 particles takes on calcite at R = 16.0, and thedominant peak at around 30 degrees is assigned to thecalcite (104) face. At R = 10.8, the XRD result of thoseparticles shows a mixed pattern of calcite and vaterite
structures, which is consistent with the SEM results in
Fig. 2b. There are two kinds of particles produced in thebilayer under this condition, sphere-like and rhombohedral.
The rhombohedral particles can be assigned to calcite,whose space group is R3c. Obviously, the crystal structureof the sphere-like particles is vaterite. A supportive evident
for this assignment is achieved at R = 7.2, where tabular
CaCO3 particle aggregates are the dominant morphology.
The XRD pattern indicates that the crystal structure forthe tabular particles remains the same, but the intensity ofcalcite (104) peak decreases significantly, which suggests
the ratio of calcite to vaterite decreases. Based on the
SEM and XRD measurements, combined with the crystallographic information available for CaCO3 polymorphs,
the sphere-like particles in Fig. 2b and the tabular aggregates in Fig. 2c are vaterite (Dickinson et al., 2002). The
other polymorph of CaCO3, aragonite, is not observed for
all the synthetic powders (Sunagawa, 1987).
The laser Raman scattering results of CaCO3 particles
are shown in Fig. 4. The Raman spectrum of CaCO3 issharp for hopper crystals prepared at R = 16.0 than that of
tabular CaCO3 particles at R = 7.2, which is primarily due
to different crystal structures. Five normal modes for calcite are observed in the hopper crystal CaCO3, with themost intense A1g mode at 1086 cm–1, the rest vibration
frequencies at 155, 281, 712 and 1435 cm–1 are associatedwith the Eg modes, their frequencies are well consistent
with those reported by Rutt and Nicola (1974). The

Fig. 3

X-ray diffraction patterns of CaCO3 particles preparedfrom octylamine/water bilayer systems. Note the intensity decrease from calcite to vaterite. Miller indicesfrom JCPDS ICDD 5-0586 (calcite) and JCPDS ICDD
33-268 (vaterite).

Fig. 4

Raman Scattering of CaCO3 particles prepared fromoctylamine/water bilayer systems. The excitation line
wavelength is 514 nm (Ar + laser). Only the two mostintense bands were observed in tabular CaCO3 vaterite
due to poor crystallinity.

tabular CaCO3 particles show only two weak over-lappedbands at 1084 and 1092 cm–1 because of the low crystallinity of the particles. The spectral profile at 1084 and1092 cm –1 is the characteristics of vaterite structure(Behrens et al., 1995; Boughriet et al., 2000; Lee et al.,2001), which verifies the crystal structure of the tabular
CaCO3 particles determined by SEM and XRD analyses.
Thermal stability of tabular CaCO3 particles (R = 7.2)
is measured by TGA and illustrated in Fig. 5. The

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Fig. 5

Thermal stability of CaCO3 particles measured by TGA(R = 10.8). The maximum weight loss occurs at 710°C
as shown in the dTGA curve. The total weight loss isless than 4% at temperatures lower than 600°C.

as-­synthesized particles are quite stable below 600°C, a
total of about 3.4% weight loss is found which indicatesthe removal of the bilayer template during washing.
When temperature goes above 600°C, a distinct weightloss of about 44% takes place from 600°C to 750°C. The
maximum weight loss occurs at 710°C as determined by
the derivative of the TGA curve, which is related to thedecomposition of CaCO3 that yields CO2. The TGA measurements on hopper crystal and sphere-like CaCO3 particles follow a similar trend.

4. Discussion
The formation of CaCO3 with various morphologies
under variable R ratio is quite understandable because of
the nature of the self-assembly bilayer template as well as
the particle growth mechanisms in confined environment(Adair and Suvaci, 2000; Mann et al., 1991; Walsh et al.,
1999; Yener et al., 2002). However, the presence of hopper
crystal calcite with square-like hopper faces is something
beyond the expectation. There are two possible mechanisms responsible for the growth of hopper crystal calcite(Buckley, 1952; Dickinson and McGrath, 2003), thermodynamic control based on a screw dislocation and kinetic
control linked to the diffusivity of constitute ions. Kinetic
control may be a favorable process in this case according
to Dickinson and McGrath (2003). Under kinetic model,
the growth rate is different in various directions during
crystallization, rapid growth appears to accentuate thedifferences between the preferred and other direction(Buckley, 1952). In the octylamine/water bilayer of pH 10,
rapid growth of CaCO3 crystals is feasible because of the160high supersaturation of Ca2+. The growth rate along body
diagonal direction is faster than any other crystal directions, which explains the face-centered cavity formation
as observed in SEM analysis. The apparent contradictionis that none of the three polymorphs of CaCO3 belongs to
the cubic system, specifically, XRD shows the hopper
crystal of CaCO3 is calcite, which means the cavity shouldbe triangular instead of square since the crystal is rhombohedral with a space group R3c. Furthermore, Dickinson
and McGrath (2003) claimed that higher viscosity(>1.6 mPa.s) alcohol water solution would promote theformation of hopper crystal calcite, unfortunately, an
opposite trend is observed in the octylamine/water bilayer
systems. Current results are far away from determining
the dominant mechanism including viscosity effect aswell as other contributions from solution pH, Ca2+ concentration and interaction of octylamine and Ca 2+.
However, the hopper crystal calcite may be used as a hostmaterial for inclusion chemistry where large cavity isrequired (Stucky and Macdougall, 1990).

5. Conclusions
Hopper crystal of calcite particles with square-likeface-centered cavity are prepared in the octylamine/water
self-assembly bilayer systems at R = 16.0. The morphology
and crystal structure of the CaCO3 particles demonstratesignificant dependence on the R ratio, with vaterite tabular
aggregate achieved at R = 7.2. The mechanism of particle
formation in alkaline self-assembly bilayer system is discussed with an emphasis on the observation of unique hopper crystal particles in rhombohedral calcite.

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Morrone A., Talham D.R., Ludwig M.H., Wang L., Recent
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Adair J.H., Suvaci E., Morphological control of particles, Current Opinion in Colloid & Interface Sci., 5 (2000) 160–167.
Archibald D.D., Qadri S.B., Gaber B.P., Modified calcite deposition due to ultrathin organic films on silicon substrates,
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Boughriet A., Gengembre L., Laureyns J., Recourt P., Langelin
H.R., Nacer A., Generation of uranyl/carbonate/hydroxide“coatings” at the vaterite surface, Phys. Chem. Chem.
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Buckley H.E., Crystal Growth, John Wiley and Sons, New
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Colfen H., Precipitation of carbonates: recent progress in controlled production of complex shapes, Current Opinion in
Colloid & Interface Sci., 8 (2003) 23–31.
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McCauley J.W., Roy R., Controlled nucleation and crystal
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American Mineralogist, 59 (1974) 947–963.
Meldrum F.C., Calcium carbonate in biomineralisation and biomimetic chemistry, International Materials Review, 48(2003) 187–223.
Osman M.A., Suter U.W., Surface treatment of calcite with fatty
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guest chemistry: probing a new dimension, Science, 247(1990) 669–678.
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Interface Sci., 218 (1999) 545–553.
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amorphous CaCO3 microparticles with hollow sphericalsuperstructures stabilized by phytic acid, Adv. Mater., 17(2005) 2217–2221.
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Author’s short biography
Jun Wang
Jun Wang started his professional career with Saint-Gobain Northboro R&D center in2004 prior to joining A123 Systems in 2011, where he is currently senior development
engineer in the innovations solutions group. Dr. Wang holds a BS degree from Universityof Science and Technology of China, a MS from Shanghai Institute of Ceramics and a
Ph.D. in material science from Penn State University. His research interests include novel
nanoparticle synthesis and dispersion, nanoabrasives for chemical mechanical planarization and nanomaterials for energy storage. Dr. Wang has published over 30 research
papers and 4 patents.

William B. White
William B. White is professor emeritus of geochemistry in the Department ofGeosciences and the Materials Research Institute at the Pennsylvania State University.
He holds a BS degree in chemistry from Juniata College (Huntingdon, PA, USA) and a
Ph.D. in geochemistry from Penn State. He joined the Penn State faculty in 1962 andremained there until his retirement in 2002. Dr. White has wide-ranging research interests in materials synthesis, crystal chemistry, glass science, phosphor materials, mineralogy, and hydrogeology. He has published more than 400 research papers and 13 books.

James H. Adair
James H. Adair is a Professor in Materials Science and Engineering, Bioengineeringand Pharmacology at Penn State University. His research and teaching interests
include biological-nanoscale composite particulates for nanomedical applications, colloid and interfacial chemistry, material chemistry, particle synthesis and characterization, and ceramic and metal particulate processing. Dr. Adair is the author or co-authorof over 240 publications, thirteen patents, several copyrights on computer softwareand co-editor of ten books.

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Original Research Paper

Development of a Particulate Solids Thermal Mass Flowmeter †Mary Kato, John Pugh and Don McGlinchey *1

Glasgow Caledonian University, UK

Abstract
An ideal mass flow meter should have the following properties: it should be non-invasive so as not to disrupt theflow profile; it should be easily installed on the conveying line to provide on-line and continuous measurements; itshould be able to provide an accurate indication of the mass flow rate regardless of the orientation of themeasurement section, inhomogeneities in the solids’ distribution, irregularities in the velocity profile, orvariations in particle size, moisture content and material properties.
A mass flow meter as described in this paper has been developed which uses a thermal method, a direct, noninvasive approach to measuring the mass flow rate. The thermal method uses the principle of heat transfer to solid
particles in a flowing fluid to determine the mass flow rate of particles. The mass flow meter is designed such thattemperature sensors are located at two ends of a heated pipe section. In the experiments carried out,measurements of gas and solids’ temperature were taken and used to calculate the heat transferred to the solids.
The mass flow rate obtained using the thermal mass flow meter was compared to that using load cells. The results
obtained are analysed and presented in this paper.
Keywords: gas-solids, pneumatic conveying, heat transfer, thermal mass flow meter

Introduction
Pneumatic conveying has proven to be an efficient anduseful method for applications requiring the transportationof bulk solids within processing plants. The process iscompletely enclosed, using pipes and vessels where thesolids are stored. The transporting gas, usually air, isreleased through a filter at the end of the process. This
ensures there is no release of solids into the environment,
making it a clean and safe procedure. Another advantage ofthis process is the fact that the air used as a transportinggas is readily available and does not react with the solids
being conveyed. In situations where the use of air is inappropriate, a non-reacting gas such as nitrogen can be used.
In various processing plants where pneumatic conveying is
employed, the conveying pipes can be constructed in sucha way that they span several kilometres and can be installed
in a variety of ways, vertically and horizontally. Thismeans any number of plant configurations can make use of
the method including multi-storey buildings, or plants withdifferent sections located at a distance from each other.
In pneumatic conveying plants, as in any other system,†
1*

Accepted: June 26, 2013
70 Cowcaddens Road, Glasgow, G4 0BA, United Kingdom
Corresponding author:
E-mail: d.mcglinchey@gcu.ac.uk
TEL: +44-14-1331-3713©2014 Hosokawa Powder Technology Foundation

optimal control of the processes is achieved by monitoring
the parameters within the system. A prerequisite isknowledge of the pressures, temperatures, velocities ofgas and solids, the volume of solids within the gas, andthe mass flow rate of solids being conveyed. The measurement of the mass flow rate of solids on-line presents
quite a number of difficulties. One method of determining
the quantity of solids being conveyed is to use a “gain-inweight” or “loss-in-weight” system where the mass ofsolids is measured using load cells located at the feed or
receiving vessel, respectively. This method is unable todetermine the amount of solids passing through a conveying pipe at a given period or position on the line, and ismore suitable for batch systems than for continuous flow
systems where the mass flow rate is required as the product is being conveyed. The advantage of measuring mass
flow rate on-line is the possibility of detecting problems
within the conveying line as they occur, for instance a
reduction in the mass flow rate along the line may suggest
a pipe blockage or solids deposition beginning to occur
somewhere along the line. Therefore the possibility of
having a device which can determine the mass of solids at
any given time during a process is quite attractive.
Research has been ongoing for a number of years
towards the development of an “ideal” mass flow meter.
For a mass flow meter to be described as ideal it shouldhave the following properties: it should be non-invasive
so as not to disrupt the flow profile; it should be easily

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installed on the conveying line to provide on-line andcontinuous measurements; it should be able to provide areliable and accurate indication of the mass flow rate
regardless of the orientation of the measurement section,
inhomogeneities in the solids’ distribution, irregularities
in the velocity profile, or variations in the particle size,
moisture content and material properties (Yan, 1996;
Arakaki et al., 2006). Finding all of these properties in
one single instrument has not been achieved yet, but
research is still ongoing.
The mass flow rate can be measured in two basic ways,
directly or inferentially. A direct mass flow meter is one
whose sensing element responds to the mass flow rate ofsolids passing through it, while an inferential mass flow
meter obtains the mass flow rate from a calculation ofvelocity and concentration of solids measured by its sensor(Yan, 1996; Beck et al., 1987). A variety of methods exist
for the measurement of solids’ concentration and velocity
using the inferential method (Carter et al., 2005; Arko etal., 1999; Hrach et al., 2008; Huang et al., 2001), as this has
proved to be more easily achievable than obtaining a direct
measurement of the mass flow rate. Certain limitations
experienced with the use of inferential methods have beenpresented in the review paper of Zheng and Liu (2010).

The thermal mass flowmeter
The thermal method of mass flow rate measurement uses
the principle of heat transfer to solid particles in a flowing
fluid-solid mixture to determine the mass flow rate ofparticles. Two approaches are used; the first involves ameasurement of temperature difference at sensors locatedbefore and after a heated region with a constant heat supplied to the system, while in the second method, a constanttemperature difference is maintained within the heatedregion and the heat required to maintain this difference ismeasured (Zheng and Liu, 2011; Yan, 1996). The mass flowrate is deduced from the relationship between the rate ofheat transferred, the measured temperatures, the heat transfer coefficient and the material’s thermal conductivity. In
his review of mass flow rate measurement methods, Yan(1996) stated that the problems with this method havebeen found to be poor repeatability of the instrument anda slow dynamic response time. Experiments conducted by
Moriyama (1996) using three different measurement
methods—cross-correlation, heat transfer and acoustic
emission—showed the heat transfer method to have thehighest time constant of the three methods. However,research is ongoing to develop the thermal method as it isnon-intrusive and expected to provide reliable, on-line,
continuous estimates of the mass flow rate. A thermal mass
flow meter has been developed which is non-invasive andemploys the use of infrared sensors for the temperature

164

Fig. 1A thermal mass flow meter (Yan, 1996).

measurement of solids (Zheng et al., 2008).
Thermal mass flow meters have been developed commercially for use in the measurement of liquid and gas
mass flow rates (Viswanathan et al., 2002a, 2002b; Han etal., 2005; Kim et al., 2007). A schematic diagram of athermal mass flow meter is shown in Fig. 1.

Heat transfer to gas-solid systems
In a study carried out by Farber and Morley (1957), it
was established that the addition of solid particles to aflowing gas increased heat transfer rates when compared
to a single phase flow of gas. Using a suspension of air
and alumina-silica particles, with carbon tetrachloride
vapour as the heat transfer medium, the heat transfer processes occurring in the suspension were investigated. The
authors observed an influence of the solids on the gas
boundary layer and the heat capacity of the suspension.
They concluded that for a constant gas flow rate, the ratioof the increase in the solids’ temperature to the increasein gas temperature was a constant and independent of thesolids’ loading ratio, but increased with increasing gas
flow rates or decreasing particle residence times. However, it is important to note that the solids’ temperature
increase was not a measured value, but was estimated bysubtracting the enthalpy increase of the air from the net
heat transferred, and dividing this quantity by the weightof the solids flowing and the specific heat of the solids(Farber and Morley, 1957).
The effect of particle size on heat transfer in a gas-solid
mixture of air and spherical glass particles was investigated by Farber and Depew (1963). In their study, varying
particle sizes of 30, 70, 140 and 200 microns were added
to air flowing in a borosilicate glass tube. Using a vertically mounted tube, heat was transferred to the medium
using carbon tetrachloride vapour as the heat transfer
medium. The results showed a substantial increase in thegas-side heat transfer coefficient for the 30-micron particles, and no visible increase in the heat transfer coefficientfor the 200-micron particles; showing that the heat transfer coefficient increased with decreasing particle size.
This effect was explained as being due to the fact that
increasing solids’ sizes prolonged the thermal entry

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length, with larger particle sizes having a longer thermal
entry length approaching the tube length, therefore thethermal boundary layer was not fully developed within
the tube length.
The heat transfer characteristics of a turbulent, dilute,
air-solids suspension flow was studied using a uniformly
heated pipe and glass beads (Aihara et al., 1997). Measurements of the bulk air-solid suspension temperatures
were made using thermocouples at a region stated to behydrodynamically and thermally fully developed. The
results of the Nusselt number showed a dependence on thesolids’ loading ratio as well as the air flow rates. A
decrease in the Nusselt number was observed upon addition of the glass beads to the air flow; however, after
reaching a minimum at a critical loading ratio, it began toincrease with increasing solid loading ratios.
This effect was also observed by Rajan et al. (2008).
Gas-to-particle heat transfer coefficients decreased withsolids’ feed rate at lower solids’ feed rates typical of dilute
flow regimes or fast fluidization regimes in packed beds.
The same was found to increase with increasing solid
feed rates as dense flow regime was approached. Experiments were carried out in a pneumatic conveying test rig
consisting of a galvanized iron duct of 54 mm inner diameter and 2.2 m height, fitted with 3 heaters of 5 kW heating capacity. Gypsum was used as the solid medium andhot air as the gas medium (Rajan et al., 2008). Results
showed an increase in the air-solid heat transfer coefficient with increasing air velocity in the range between
4.3 m/s and 5.8 m/s; this reached a maximum before
decreasing with a further increase in air velocity of about
6.3 m/s. Thermal conductance, defined as the ratio of theheat transfer rate to driving force, was found to increase
with solids’ feed rate and air velocity (Rajan et al., 2010).

Fig. 2Previous work
Research is ongoing at the Centre for Industrial Bulk
Solids Handling in Glasgow on the development of a thermal instrument for solids’ mass flow rate measurement.
The instrument is made up of a 1-m long pipeline section
which is referred to as the heated section. Thermocouples
are located upstream and downstream of this section formeasurement of the gas temperatures, while infrared sensors are located at similar locations for measurement of
the solids’ temperatures. The pipe surface temperature ismeasured using a thermocouple. The heat transferred tothe system is controlled within a set band, giving a pulsed
heat signal in which the heater is turned off when the pipe
wall temperature is above a fixed point, and then turnedon when the temperature falls below a fixed value. The
instrument described is shown schematically below.
The operation of a thermal mass flow meter is based on
the principle of heat transfer to a medium; in this case a
mixture of solids in air. To provide an understanding of
this, a study was carried out on the heat transfer mechanisms to solids flow. Zheng et al. (2008) reports the resultsof a numerical analysis and experimental studies carriedout to analyse the heat transferred to a flowing gas from theheated wall, and then from the heated gas to a single particle passing through the region. This study proposed thatthe heat generated was transferred along the pipe wall axially and radially by conduction, and then from the pipe
wall to the gas and then to the solid particle by convection.
In another study, the heat transfer coefficient from aheated wall to a gas-particulate plug flow was investigatedexperimentally and numerically (Zheng et al., 2007). The
results showed that the heat transfer coefficient increased
approximately linearly with the solids’ loading ratio, thisbeing consistent with Zheng et al.’s hypothesis that ahigher solids loading provides more carriers for heat

Schematic diagram of the thermal mass flow meter.

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transfer.
The operation of the thermal mass flow meter was further investigated with experiments conducted under dilutephase flow conditions, conveying ordinary Portland
cement on an industrial-scale pneumatic rig (McGlinchey
et al., 2010; McGlinchey et al., 2013). Using an energybalance approach between the heat entering the systemand the heat taken by the gas-particulate mixture, a measure of the mass flow rate was obtained which was thencompared to measurements obtained from load cells. The
results showed good agreement between the thermal mass
flow meter and the load cells; however, some important
observations were made. The analysis showed that thetemperature of solids being measured by the infrared sensors was affected by the ambient temperature around thesensor (Kato et al., 2012). Therefore a method to control
the infrared sensor temperature was developed using
cooling water which was passed through a copper pipe
coiled around the steel conveying line.
The following section describes further measurements
carried out on the industrial-scale pneumatic conveying
rig as a means to further understand the principle of operation of the thermal mass flow meter under development.

Fig. 3

166

Experimental procedure
A schematic diagram of the experimental rig used isshown in Fig. 3.
The experimental system is the same as that describedin a previous publication (McGlinchey et al., 2013). The
pipeline is of mild steel nominal bore 50 mm, with a total
length of about 50 m, of which 5 m is vertically up, theremainder in the horizontal plane, and included five
90-degree standard radius bends. The measurement system as shown in Fig. 2 was positioned at least 5 m fromany bend. Ordinary Portland cement with a mean particle
size of 25 mm was conveyed in a range of dilute phaseconditions with mass flow rates of air ranging from
0.4 kg/s to 0.14 kg/s and solid loading ratios in the range 4
to 136. The thermal properties of ordinary Portland
cement are listed in Table 1. The mass flow rate of solids
used to compare the results from the thermal instrument
was obtained from load cells at the receiving vessel.
The experimental procedure was as follows. Compressed air was supplied to the test rig via the pressure
control valve PRV1 shown in Fig. 2. The gas mass flowrate at the outset was determined using a combination of a

Schematic diagram of industrial-scale test rig.

Mary Kato et al. / KONA Powder and Particle Journal No. 31 (2014) 163–170

Table 1

to give:

Properties of Granular Material
Properties of Ordinary Portland Cement

Particle size

25 mm

Density

1500 kg/m3

Thermal conductivity

0.29 W/mK

Specific heat capacity

0.84 kJ/kgK

 susp Const ∗m=Const =

number of nozzles to achieve the required flow rate. Oncethe gas flow rate had been established, the measurementand data acquisition system was turned on. A program
developed using LabVIEW and the National Instruments
DAQ system was used to control the heater to maintainthe pipe wall temperature within a fixed band. After thesystem had reached a stable condition, solids wereinserted into the conveying line from the blow tank. A
record of the temperatures of the pipe wall, the gas andsolids was acquired, as well as the pressure drop within
the system and the mass of solids obtained from load cells
located at the receiving vessel.

Results and analysis
The amount of heat transferred to a system is defined
as a product of the mass of the system, its specific heat
capacity and the difference in temperatures measured
before and after heat is transferred. The heat transferred
to a gas-solid suspension is a function of the specific heat
capacity of the suspension, the temperature difference
and also the mass flow rate of the suspension.
Using the energy balance method (McGlinchey et al.,2013), the following equation was used to calculate a factor corresponding to the mass flow rate of solids measured
by the thermal instrument. The rate at which heat is transferred to the system is given by:(1)

and the rate at which heat is taken up by the gas-solids
suspension is given by:=
Q S susp

msusp
ΔTsuspΔt(3)where the constant value is given by:

Source: Holman, 2010

ΔTheater=
Q E in + S heater mheater
Δt

ΔTheater / Δt
ΔTsusp(2)where Ėin is the energy supplied to the heating system.
At a time when the electrical input to the heater is off(Ėin = 0) and the pipe wall temperature change is approximately linear with time, and if we assume the specificheats of the heater and the suspension to be relatively
constant, the mass flow rate of the suspension can beobtained by equating (1) and (2) and rearranging the result

S heater mheater
S susp(4)

Assuming a value of –1 kgs for the constant (so that theresults can be viewed in the positive graph axes), the following results were obtained for tests carried out over arange of air mass flow rates and varying solid loading
ratios. Results shown have been made dimensionless bydividing by corresponding air mass flow rates.
The results above show the thermal instrument’s
response to varying air flow rates and solid loading ratios.
The mass flow rate factor from the thermal instrument was
obtained using Eqn. 3. The graph shows three distinctive
regions: Region 1, where an approximately linear relationship can be observed between the thermal instrument andthe load cells; Region 2, where a very low solids’ temperature difference causes the measured mass flow rate to beuncharacteristically high for the given solids’ loading; andRegion 3, where we can observe a gradual approach todense phase flow conditions.
This factor obtained from the thermal instrument isdependent on the change in wall surface temperature withtime, as well as the heat taken in by the solids which ismeasured by the infrared sensors, assuming the specificheats of the heater and the suspension remain constant.
According to the equation, a high mass flow rate isrecorded by the thermal instrument when the change inwall temperature with time is high. This gradient should
increase with increasing air mass flow rates. In addition
to this, if the heat taken in by the solids as measured by
the temperature difference is a low value, then a highmass flow rate should also be observed. An increasing
solids’ loading ratio will reduce the relative air mass flowrate influence and hence the temperature gradient pertime at the wall for a given test, however, this does not
fully explain the observed results. This may be due to themeasurement method of the infrared sensors. For accurate
temperature measurement of moving solids using an
infrared sensor, it is necessary for the solids to completely
fill the viewing window of the sensor. At low solids loading ratios, it is possible that this requirement is not met,
and therefore the results obtained in this range are being
affected by the temperature of the inner pipe wall. See
Fig. 4, Region 2. At high solids loading ratios the measurement may be biased to detection of a solids fraction
in non-suspension mode which would be hotter than abulk temperature. See Fig. 4, Region 3.

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Fig. 4

Results obtained for the mass flow rates of solids using the thermal instrument. The legend shows thedifferent air mass flow rates used.

Conclusions

References

Investigation of the operation of a thermal mass flow
meter was carried out by analysing tests performed on apneumatic conveying rig with air flow rates between
0.04 kg/s to 0.14 kg/s, and solid loading ratios in the range
4 to 136. Results have shown a dependency of the mass
flow rate measurements on the solid loading ratio. The
thermal mass flow meter shows promise as a direct mass
flow rate measurement instrument. Further tests andinvestigations are ongoing to characterise the operation of
the mass flow meter.

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Manchester, 1999.
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NomenclatureĖinelectrical input rate to heater (W)mheatermass of heater (kg)msusp

mass of gas-solids suspension (kg)ṁsuspmass flow rate of gas-solids suspension (kg/s)

Qheat energy rate (W)S heater

specific heat capacity of heater (J/kgK)

Ssusp

specific heat capacity of gas-solids suspension(J/kgK)

Δtchange in time (s)ΔTheaterchange in temperature of heated wall (K)ΔTsuspchange in temperature of gas-solids suspension (K)168

Mary Kato et al. / KONA Powder and Particle Journal No. 31 (2014) 163–170

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Development, modelling and certain investigations on thermal mass flow meters, Journal of Flow, Measurement &Instrumentation, 12 (2002a) 353–360.
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pipelines, Measurement, Science & Technology, 7 (1996)
1687–1706.
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sensing array, Optics & Laser Tech., 39 (2007) 298–305.
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non-invasive mass flow measurement, Measurement, 41(2008) 446–454.
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Author’s short biography
Mary Kato
Mary Kato is a research student at Glasgow Caledonian University, working with theCentre for Industrial Bulk Solids Handling where she is investigating heat transfer inparticulate systems at the PhD research level. With a background in chemical engineering,she proceeded to study applied instrumentation & control and completed an MSc. She
has published works on the influence of windows on infra-red temperature measurement
towards the development of a thermal mass flow meter.

John PughJohn Pugh is a professor at Glasgow Caledonian University. He has pursued an interest
in instrumentation and measurement for over thirty five years—with at least twenty
years in the area of instrumentation for bulk solids handling. Current research work is on
the development of solids’ two-phase mass flow measurement, and he also maintains aninterest in industrial weighing. He is vice-president (Learned Society matters) of theInstitute of Measurement and Control in the UK, and chair of the institute’s Learned
Society Board. He has published over eighty papers and conference proceedings—
around 30 in the area of solids handling.

Don Mcglinchey
Professor Don McGlinchey is the head of the Centre for Industrial Bulk Solids Handlingat GCU. He is an academic of international standing in the particulate solids handlingcommunity. He has undertaken consultancy projects for both multinational companies
and small to medium enterprises, and has delivered short courses in Sweden, USA andthe UK. Don has also presented at international academic conferences in China, India
and Europe. He is a chartered physicist with a PhD on the subject of the effect of vibration
on particulate materials. Don is the editor of two books and has authored over 50
research articles.

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KONA Powder and Particle Journal No. 31 (2014) 171–180/Doi:10.14356/kona.2014008

Original Research Paper

The use of Highly Ionized Pulsed Plasmas for the Synthesis of
Advanced Thin Films and Nanoparticles †Iris Pilch 1*, Daniel Söderström 1, Daniel Lundin 2 and Ulf Helmersson 1
1
2

Plasma & Coatings Physics Division, Department of Physics, Chemistry and Biology (IFM), Sweden
Ionautics AB, Sweden

Abstract
Pulsed plasma processes open up the possibility of using very high plasma densities and modulated deposition in
the synthesis of thin films and nanoparticles. The high plasma densities lead to a high degree of ionization of thesource material, which creates new possibilities for surface engineering. Ions can, in contrast to atoms, be easily
controlled with regard to their energy and direction, which is beneficial for thin film growth. Furthermore, ionscan also increase the trapping probability of material on nanoparticles growing in the gas phase. The pulsed
sputter ejection of source material also has other consequences: the material in the plasma and the material arrivalon the growth surface will fluctuate strongly resulting in high level of supersaturation during pulse-on time. In
this paper, an overview of the generation and properties of highly ionized pulsed plasmas is given. In addition, theuse and importance of these types of discharges in the fields of thin-film and nanoparticle growth are also
summarized.
Keywords: HiPIMS, HPPMS, IPVD, sputtering, thin films, nanoparticle synthesis

1. Introduction
The processing of materials and surfaces is today very
important in many industrial branches. This includes thinfilm deposition to functionalize surfaces with different
properties such as wear resistance, color changes, corrosive
protection, catalytic behavior, or electrical and opticalproperties. The properties of thin films can further be
improved by, for instance, the incorporation of nanoparticles in solar cell applications (Atwater and Polman, 2010).
Nanoparticles are also of great interest in catalysis (Cuenya,2010) due to their large surface-to-volume ratio or plasmonics (Garcia, 2011), where the plasmon frequency is afunction of the size of the nanoparticle.
For fabricating thin films or nanoparticles, the material
that condenses onto the surface or into nanoparticles can beprovided by different means—e.g. thermic evaporation, arc
evaporation or pulsed laser evaporation. Another method is
to utilize a plasma discharge where the vapor is removed
from a target (source) by sputtering the material, which isthe focus of the present article. A plasma consists of ions,electrons and neutral atoms. Plasmas used for material
†
1
2

*

Accepted: July 1, 2013
SE-581 83 Linköping, Sweden
Linköping, Sweden
Corresponding author:
E-mail: iripi@ifm.liu.se
TEL: +46-13-286617©2014 Hosokawa Powder Technology Foundation

processing typically have a low ionization degree, which isthe fraction of the density of ions to the sum of the ion andneutral density. The target material is sputtered by ions thatcollide with the surface, which leads to the removal of surface atoms. The sputtered material is subsequently transported out into the bulk plasma and eventually condenses
on all surfaces. For thin-film deposition, a magnetic field
configuration is commonly used in a way that the plasma is
confined in front of the target to enhance the sputtering
process (Window and Savvides, 1986). This technique iscalled magnetron sputtering.
For improving the properties and structure of deposited
thin films, one needs to control, for instance, the energy
and the deposition rate of atoms and ions that condenseon the substrate (coated object). The motion of sputteredatoms is governed by ballistic transport as well as diffusion, but ions can be manipulated by electric or magnetic
fields, which allow the energy of the ions reaching thesubstrate surface to be tailored. It is therefore desirable tohave a high ionization degree of the vapor material. A
way of increasing the ionization degree is to increase theplasma density, which can be achieved by increasing thepower supplied to the sputter target. The maximum average power possible is defined by the melting temperatureand heat conductivity of the target material. Very highplasma densities can be achieved—without exceeding the
maximum average power—by supplying the power inshort, high-power pulses with a low duty factor. A

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technique that utilizes this approach to reach very highionization degrees of the sputtered material is high-power
impulse magnetron sputtering (HiPIMS) (Kouznetsov etal., 1999, Lundin and Sarakinos, 2012).
The same approach has also recently been applied tosynthesize nanoparticles (Pilch et al., 2013). A high ionization degree is beneficial because the collection probability of the sputtered material—i.e. ions and atoms—on
a nanoparticle is a function of the collection cross-section.
For atoms, the cross-section is given by the geometriccross-section of the nanoparticle but for ions, the collection cross-section can be much larger. The reason for thisis that nanoparticles attain a negative charge which isdefined by the equilibrium of electron and ion currents tothe nanoparticle (floating condition), and this increases
the ion flux of positively charged ions onto the nanoparticle. Two consequences follow in the case of negatively
charged nanoparticles. First, the collection probability ofpositively charged ions becomes larger than the collection
probability of atoms and this leads to a faster growth,which is the reason of having a plasma with a high ionization degree. Second, the agglomeration of nanoparticles
in the gas phase is inherently prevented when thenanoparticles are negatively charged.
In this contribution, results from both the deposition ofthin film and the synthesis of nanoparticles using highpower pulses are presented. In Section 2 an overview on
the pulsed plasma is given. Thin-film deposition and its
applications using HiPIMS is presented in Section 3, anddetails on nanoparticles using a pulsed hollow cathode arepresented in Section 4. A summary of the article is given
in Section 5.

2. Pulsed plasmas
2.1. High-power pulsed plasmas
There are many methods for pulsed plasma processing
and it is therefore appropriate to briefly discuss the mostcommon techniques. We will thereby come to understandwhat distinguishes high-power pulsed plasmas (HiPP),
discussed in the present article, from other types of pulsed
plasmas.
The introduction of pulsed magnetron sputtering in the
mid-90s boosted the deposition of dielectrics such as alumina, titania and silica (Kelly and Bradley, 2009). The reason is that DC discharges applied to cathodes using source
materials with poor conductivity charge up the cathodesurface positively during the discharge. This is due to theloss of electrons as the bombarding ions are neutralized at
the cathode, and thus eventually extinguish the discharge
or generate detrimental arc discharges. With the use of AC
discharges, it is possible to neutralize the positive charge

172

accumulated during one half-cycle by electron bombardment during the following half-cycle (Chapman, 1980). The
most common operation constitutes asymmetric bipolar
discharges, where the voltage Ud (t) during pulse-off isreversed (positive) to approximately 10% or less of themagnitude of Ud (t) during pulse-on at frequencies in therange 20–350 kHz and a duty cycle of about 50% (Kelly
and Bradley, 2009). The technique is often referred to as
mid-frequency pulsed DC sputtering.
Another pulsed sputtering technique is radio frequency(RF) sputtering. Here, a high-frequency (13.56 MHz)power is applied to achieve sputtering of the target material. This will also allow sputtering of isolators. However,the deposition rates for sputtering dielectrics are typicallylower compared to mid-frequency pulsed DC sputtering(Glöß et al., 2005).
In HiPP discharges, the power is applied to the cathodein unipolar pulses at a low duty factor (< 10%) and low
frequency (< 10 kHz), leading to peak cathode power densities of the order of several kW cm–2 while keeping the
average target power density low enough to avoid heatdamage to the cathode. In many ways, HiPP processes are
similar to the above-described pulsed DC discharges, butthey operate at a lower duty factor and considerably
higher instantaneous pulse power. This means that setting
up a system is fairly straightforward in the sense that it
only involves changing the power supply.
An early description of the HiPP technology for material processing was provided by Kouznetsov et al. in 1999,
where they used magnetron sputtering for thin-film deposition. The technique has since been commonly referred
to as high-power impulse magnetron sputtering (HiPIMS)
or sometimes high-power pulsed magnetron sputtering(HPPMS). It is also in this domain where we find a morestrict definition distinguishing this technique from otherpulsed plasma processes (Anders, 2011): HiPIMS is pulsed
magnetron sputtering, where the peak power exceeds thetime-averaged power by typically two orders of magnitude. This is very different from what one finds in, forexample DC, pulsed DC or RF discharges, and has a dramatic influence on the plasma characteristics and hence
the sputtered material, as will become apparent in thenext section.
Recently, HiPP technology using the same power supplies as in HiPIMS has been investigated in the case ofhollow cathodes for plasma-enhanced chemical vapor
deposition (PECVD) of thin films (Pedersen et al., 2012)
as well as for nanoparticle synthesis (Pilch et al., 2013).
The deposition of thin films and the synthesis of nanoparticles depend on the pulse parameters: frequency, pulse
width, and current, as well as other process parameters,such as operating gas pressure. The principles behind theplasma generation remain the same. Finally, a typical discharge pulse is seen in Fig. 1.

Iris Pilch et al. / KONA Powder and Particle Journal No. 31 (2014) 171–180

Fig. 1 A typical discharge voltage-current plot in a HiPIMS
discharge. This discharge was generated using a 6” circular magnetron equipped with a Cu target operated at
1.33 Pa Ar pressure. The peak current density is about
1.6 A cm –2 and the peak power density is approximately 1.5 kW cm –2 averaged over the entire cathodearea. The time-averaged power density is 5.5 W cm–2.

2.2. Pulsed plasmas for generating highly ionizedmaterial fluxes
In glow discharge processes such as magnetron sputtering, it is often difficult to achieve a large fraction of ionized sputtered material reaching the substrate (Christou
and Barber, 2000, Rossnagel and Hopwood, 1994,
Konstantinidis et al., 2004). When the deposition flux
consists of more ions than neutrals, the process is referred
to as ionized physical vapor deposition (PVD) or IPVD
(Helmersson et al., 2006).
Commonly used IPVD techniques are inductively coupled discharges (ICP) where the plasma density is
increased by inserting an antenna in the plasma and feeding it with RF-power (Hopwood, 2000), but also theindustrially widespread method of cathodic arc evaporation (Johnson, 1991), which in some cases also operates inpulsed mode (Rosén et al., 2007). A drawback with arc
evaporation is the formation of macro-particles throughexplosions caused by overheated spots on the sources.
The HiPP technology also belongs to the IPVD group.
The high instantaneous power densities applied to thecathode used for HiPP plasma generation result in astrong increase of charge carriers in front of the cathodeduring the discharge pulse. As an example, in a HiPIMS
discharge, the electron density in the region close to thecathode target surface is on the order of 1018–1019 m–3(Gudmundsson et al., 2009, Bohlmark et al., 2005). For anelectron density around 1019 m–3, the ionization mean freepath of a sputtered metal atom is about 1 cm, while for anelectron density of 1017 m –3, commonly observed in a
steady-state DC magnetron sputtering (DCMS) discharge,
the ionization mean free path is approximately 50 cm fortypical discharge conditions (Gudmundsson, 2010). Thus,
given the high electron density in the HiPP discharge a

Fig. 2

Schematic of the sputtering process based on the target
material pathway model by Christie (Christie, 2005).
The letters G and M stand for gas and metal, respectively. Adapted from Lundin (Lundin, The HiPIMS
process, 2010).

significant fraction of the sputtered material is ionized,
which has also been reported in a great number of publications [see Gudmundsson et al. (2012) and references
therein]. In Fig. 2, we schematically illustrate the sputter
ejection of neutral material atoms by ions from the volume plasma. The sputtered particles are then transported
out into the deposition chamber and may undergo an ionizing collision depending on the plasma conditions. A
fraction of the sputtered material eventually reaches thesubstrate, either as neutrals or as ions.
Worth pointing out is that although the ionized flux
fraction typically reaches > 50% (IPVD), there are, however, substantial differences in the degree of ionization of
the sputtered material depending on the target material,
ranging from only a few percent to almost fully ionized(DeKoven et al., 2003, Bohlmark et al., 2005). The reason
for this behavior is mainly related to the fact that the ionization potential is material-dependent and for commonlyused metals is in the range E IP = 5.99 eV (Al) to
EIP = 11.26 eV (C), meaning that Al is more easily ionizedthan C.
In the plasma discharge model by Samuelsson et al.
(2010), these trends are investigated in more detail in thecase of HiPP discharges by HiPIMS. As a reference, for
direct current discharges such as DCMS, the degree ofionization of sputtered material is found to be 5% or lessindependent of the target material used (Hopwood, 2000).

3. Thin film growth by high-power impulse
magnetron sputtering
The use of ionized deposition fluxes when growing thin

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films opens up several opportunities. It includes guiding
the deposition material to use the ions for substrate pretreatment, and using the ions for generating effects on thegrowing film through self-ion-bombardment. Below, wego through some of the most attractive features.
Guiding the material flux is a great advantage for coating complex-shaped surfaces and for trench filling applications (Kouznetsov et al., 1999). On the microscopic
scale, the electric field present in the sheath between theplasma and the substrate can be used. Since this field isperpendicular to the substrate surface, it will guide theions to arrive with an angle close to the surface normal.
This minimizes self-shadowing—a mechanism that promotes surface roughening—and smoother and denser
films can be grown. This was demonstrated by Alami etal. (2005) by growing films on the wall inside of a
10-mm-wide and 10-mm-deep trench, see Fig. 3. The useof an ionized flux for deposition made a dramatic difference, going from a low-density tilted columnar structure
when mainly neutral atoms were deposited by DCMS, toa dense microstructure with columnar grains parallel tothe substrate normal when the deposition material was
ionized by HiPIMS. Similar results have been demonstrated for cutting tool edges, where good film quality isachieved on both sides of the edge when using HiPIMS(Bobzin et al., 2009).
For very narrow trenches, where the plasma cannot penetrate into the small structures, the situation is different.
Here, the flux of deposition ions will be channeled down
the trench and an improved bottom coverage can beachieved. In this case, sidewall coverage can be achievedby increasing the substrate bias—allowing the incomingions to accelerate to higher energies and sputter material ofthe deposited coating at the entrance and at the bottom of
the trench. The sputtered material can then be re-depositedon the side walls. This has been elegantly demonstrated
and simulated by Hamaguchi and Rossnagel (Hamaguchi
and Rossnagel, 1995). On a large scale, the ionized deposition fluxes can be guided and directed by using magnetic
fields. An example of this is illustrated by Bohlmark et al.
(2006b) where they focus the deposition flux towards thesubstrate position. The guiding can also be used for filtering away neutrals to increase the degree of ionization of thedeposition material (Kouznetsov, 2004).
Ion bombardment during thin film growth is of great
importance when it comes to controlling the microstructure of the film. The ions generated in HiPP processes
have been found to have energy distributions shifted
towards higher energies than are expected from the commonly accepted Thompson sputter energy distribution(Thompson, 1968, Bohlmark et al., 2006a). From ion
energy measurements in HiPIMS discharges, it has beenreported that the average ion energy is around 20 eV
without using any substrate bias (Lundin et al., 2008). As

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Fig. 3

Cross-sectional scanning electron microscope (SEM)
images of Ta films grown by (a) HiPIMS and (b)DCMS on a Si substrate clamped on the side of atrench with an area of 1 cm 2 and a depth of 2 cm. The
HiPIMS-deposited film is dense with columns growing
perpendicular to the Ta/Si interface. The DCMS-­
deposited films have a porous microstructure with columns inclined toward the flux direction. [Reprinted
with permission from Alami et al. (2005). Copyright
2005, AVS.]

it turns out, ion energies in the range 20–30 eV have beenshown to have a densifying effect on thin films (Eriksson
et al., 2006), since the ion flux enhances the surface
mobility of the film-forming species on the growth surface and thereby reduces film porosity. Several researchgroups have demonstrated that HiPIMS results in denser
films [see Samuelsson et al. (2010) and references therein].
Ion-bombardment is also often used in non-IPVD techniques. However, in this case the bombarding species areions of the inert sputtering gas. For reasons not yet fully
understood, bombarding the growth surface with thefilm-forming species is more efficient than using inert gasions. The former also minimizes the incorporation of gas
into the film.
The ion bombardment of the growing film can also be
used for phase-tailoring. Alami et al. (2007) demonstrated
that it was possible to grow thermodynamically stablebcc-Ta. Commonly during film growth, the more brittle
tetragonal-Ta phase is formed. A similar case is the one
published by Aiempanakit et al. (2011). They found thatTiO2 films with anatase and rutile phases can be controllably grown at room temperature using different HiPIMS
conditions. X-ray diffraction patterns of the TiO2 films
where the change from the anatase to the rutile phase canIris Pilch et al. / KONA Powder and Particle Journal No. 31 (2014) 171–180

Fig. 4

X-ray diffraction patterns of TiO2 films grown on Si
substrates by HiPIMS at various values of peak target
power. The increase of the peak target power and thesubsequent increase in the number of ions available
during deposition promote the formation of the rutile
at the expense of the anatase phase. [Adapted from
Aiempanakit et al. (2011).]be seen in Fig. 4. A third example is Al2O3 that can form
a number of phases, but only one, the corundum phase,is thermodynamically stable and desired in many wear-­
protection applications (Selinder et al., 2009). However,for the corundum phase to form, usually very high substrate temperatures of up to 1000°C are needed. This limits
the type of substrates that can be used and thereby the
number of applications. Ion bombardment during growth
reduces the temperature needed to grow this phase andwith HiPIMS, it is possible to grow the corundum phaseat a growth temperature of 575°C (Wallin et al., 2008).

4. Nanoparticle Synthesis
There is a wide variety of gas-phase techniques to synthesize nanoparticles, e.g. flame synthesis (Wegner andPratsinis, 2000), thermal evaporation (Granqvist andBuhrman, 1976), and plasma synthesis (Vollath, 2007;
Binns, 2001). The technique presented in this article is a
plasma-based technique based on high-power pulses similar to what is used in the HiPIMS discharge. HiPP discharges for nanoparticle synthesis have not been studied
in detail; however, Straňák et al. (2011) used a pulsed
magnetron technique where the size of the clusters could
be varied, and Werner et al. (2011) synthesized nanoparticles with different shapes using a DC magnetron withlong pulse-off times.
To investigate the effect of high-power pulses and ahigh ionization degree on the nanoparticle synthesis, ahollow cathode was used as a sputter target which has
been shown to be suitable for nanoparticle synthesis (Ishii
et al., 1999). A sketch of the set-up is shown in Fig. 5 andmore details of the experimental procedure can be foundFig. 5

Sketch of the experimental set-up, HC: hollow cathode,
AR: anode ring, M: mesh, and S: substrate.

in Pilch et al. (2013). The nanoparticle synthesis was carried out in a stainless steel vacuum chamber in an argon
atmosphere at a pressure of 106 Pa. The process gas wasrouted through the hollow cathode at a flow rate of 60
sccm. Typical pulse parameters used for the nanoparticle
synthesis were: frequency f = 125 to 1300 Hz, peak current IH = 3 to 20 A, and pulse width t PW = 10 to 100 μs.
With the present set-up, it was possible to synthesize
nanoparticles by sputtering different metals: Cu, Ag, Ti,
Mo, and Zr. Examples of SEM micrographs of Ag and Cu
nanoparticles are shown in Fig. 6. In both examples, awide spread in sizes is found and two size populations
were synthesized. The Ag nanoparticles have a diameterof around 60 nm and the shape of the nanoparticles is facetted; even cubic nanoparticles were found. Nanoparticles
smaller than 5 nm (not seen in the image) were also synthesized. The Cu nanoparticles are spherical and two size
populations were found, one with a diameter of 20 nm
and the other of around 10 nm. TEM micrographs of the
Cu nanoparticles are shown in Fig. 7.
To control the characteristics of nanoparticles, both theirshape and size need to be controlled. For Ag it has beenshown that nanoparticles with different shapes can be synthesized. Similar results for cubic Cu nanoparticles werealso found. However, further control is needed to be able tosynthesize nanoparticles with a specific shape. The change
in size of Cu nanoparticles by adjusting the pulse parameters was studied in detail with the present set-up (Pilch etal., 2013). In Fig. 8, the variation of the nanoparticle diameter is shown for (a) varying peak current and (b) varying
frequency (at constant average power). The two size populations shown in Fig. 7(b)—note that this is not the samedata as shown in Fig. 8—can be avoided by choosing
appropriate pulse parameters. By increasing the peak current, the nanoparticles with the smaller size become lessand finally disappear. The nanoparticle size can also bechanged when the frequency is varied and the average
power is kept constant, see Fig. 8(b). To keep the average

175Iris Pilch et al. / KONA Powder and Particle Journal No. 31 (2014) 171–180

Fig. 6

TEM micrographs of copper nanoparticles. The inset
shows a high-resolution micrograph of a nanoparticle
with crystalline structure.

Fig. 8

Variation of the size of copper nanoparticles by changing a pulse parameter: (a) peak current (energy perpulse) and (b) frequency at constant average power.
[Reprinted with permission from Pilch et al. (2013).
Copyright 2013, AIP Publishing LLC.]

SEM micrographs of (a) silver and (b) copper nanoparticles. The silver nanoparticles have cubic and facetted
shapes whereas the copper nanoparticles are sphericaland, in this case, with a wide spread of the size distribution.

power constant when the frequency was increased, theenergy per pulse was lowered by decreasing the peak current. The possibility of synthesizing nanoparticles with different sizes at constant average powers allows one to
optimize the nanoparticle synthesis with respect to power
consumption.
The increased control of the growth of the nanoparticles
comes from the interaction and timing of the pulses, andthe amount of ions also plays an important role for thegrowth of nanoparticles. The properties and dynamics ofthe discharge were modeled by Hasan et al. (2013) for an Al
target. It was found that the sputtered atoms become almost
fully ionized with an ionization degree of 85% at the end of
the pulse. To transfer this result from Al to Cu, which has aslightly higher ionization potential, the results from modeling the ionization degree for HiPIMS discharges can beused for comparison (Samuelsson et al., 2010). Assuming
the same ratio of the ionization degrees for Al (49% for
HiPIMS) and Cu (27% for HiPIMS), a high ionization of
about 50% for Cu is still reasonable. The high ionization
degree is required to be able to effectively utilize the chargeof the nanoparticles to collect ions and enhance the growth
speed of nanoparticles due to the larger collection
cross-section of ions (Pilch et al., 2013).
During each pulse it was found that a cloud of ions andneutrals of the sputtered species emanates from the176

Fig. 7

hollow cathode. The expansion and diffusion of the ion
and the atom cloud diverge because the motion of ions isgoverned by ambipolar diffusion, which is a faster process than the diffusion of neutrals in the background gas.
Due to the periodical ejection of material and the pulsingof the discharge, four mechanisms that affect the growth
have been proposed (Pilch et al., 2013): pulse strength,
neutral overlap, ion overlap, and discharge overlap.
The pulse strength is a measure of the density of the
sputtered material that is available for the growth ofnanoparticles. The sputtered material that is blown out of
the hollow cathode condenses into small clusters, which
may coalesce into larger clusters depending on the densityof the small clusters. Consecutive pulses provide morematerial to the region outside the hollow cathode. The
ejected neutral clouds can overlap and merge whereas theIris Pilch et al. / KONA Powder and Particle Journal No. 31 (2014) 171–180

ejected ion cloud flows, due to ambipolar diffusion, throughthe growth region providing material for nanoparticle
growth. The ion overlap becomes particularly importantwhen the nanoparticles attain a net negative charge. The
charged nanoparticles will repel each other and coalescenceand agglomeration of nanoparticles are prevented. Hencethe nanoparticles grow by accretion of atoms and ions,whereas the process of collecting ionized material is more
efficient than the collection of atoms. The higher collection
probability of ions is due to a larger cross-collection of ionswhich is given by (Pilch et al., 2013):

⎛
T ⎞
σ=
σ0 ⎜ 1 + k e ⎟ ,
coll
Ti ⎠
⎝
with the geometric collection cross-section for atoms
σ0 = πr2, r being the radius of a nanoparticle, the electron
temperature Te, ion temperature Ti, and a factor k that is afunction of electron and ion temperature and ion mass.
For a temperature ratio of Te / Ti  ≈  100, the collection crosssection for ions is about two orders of magnitude larger
than the geometric collection cross-section for atoms. The
dependency of the collection cross-section of ions on theelectron temperature is affected by the proposed discharge
overlap. In the growth region outside the hollow cathode, aplasma is generated between the hollow cathode and theanode ring which leads to electron heating and possibly
also ionization. A higher electron temperature will increase
the collection cross-section of ions, and ionization will
increase the density of ions in the growth region. Botheffects can enhance the growth of nanoparticles by ions.
The increase in the size of nanoparticles when changing
the peak current can be explained by an increase in pulse
strength which leads to a higher density of sputtered material available for growth. In the case of varying the frequency but keeping the average power constant by reducing
the pulse strength (i.e. the peak current), it can be assumed
that the average density remains constant when increasing
the frequency, though the density of sputtered material
ejected during each pulse becomes less. Thus, the size
increase can be ascribed to the overlapping of consecutive
pulses. From the presented results it is not possible todeduce which one of the overlaps—neutral, ion or discharge overlap—is the most important one.
Comparing the pulsed process to a DC discharge, it
was found that the pulse process can provide more tools
to control the properties of the plasma environment for
the growth of nanoparticles. The high power density leads
to ejection of a cloud with a high density of sputteredmaterial, which favors the nucleation of nanoparticles.
Short, high-power pulses increase the ionization of the
sputtered material substantially compared to a DC discharge. This is beneficial when the growth of nanoparticles
is limited to the accretion of atoms and ions.

5. Summary and Conclusions
High-power pulses have been shown to be able to generate plasmas with a high degree of ionized material. The
ionized material can be guided by electric and magnetic
fields and the energy can be controlled by, for instance, thesubstrate bias. The thin-film deposition by ions rather thanby atoms has shown to be capable of improving film properties such as higher density or better coverage of trench
walls.
For the synthesis of nanoparticles, it was shown that thepulsing allows the sizes of nanoparticles to be controlled.
The mechanism of size increase can be ascribed to thepulsing which causes a periodical ejection of source material. Nanoparticles of different metals were synthesized
and in the case of Ag, it was shown that different shapes
can be synthesized. This offers the possibility of obtaining a shape-selected growth by further manipulation of
the growth zone—e.g. by applying an additional coolingsource to quench the growth.

Acknowledgements
The authors thank Robert Boyd for providing the TEM
micrographs. The work was financially supported by the
Swedish Research Council under grant no. 2008-6572
through the Linköping Linneaus Environment LiLi-NFM
and by the Knut and Alice Wallenberg foundation throughgrant no. 2012.0083.

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Author’s short biography
Iris Pilch
Iris Pilch received her Ph.D. degree from Christian-Albrechts-Universität in Kiel,
Germany in 2010 where she studied the dynamics of dust-density waves and dust particles in a complex plasma. After her Ph.D., she joined the Plasma and Coatings Physics
Division at Linköping University, Sweden, as a post doc to investigate the growth ofnanoparticles in highly ionized pulsed plasmas. Her research interests include plasma
physics, complex plasmas, nanoparticle synthesis and the diagnostics of nanoparticles
during growth.

Daniel Söderström
Daniel Söderström is an assistant professor in the Plasma and Coatings Physics Division,
Linköping University, Sweden. He received his Ph.D. from Uppsala University, Sweden,in 2008, after which he joined the Linköping group as a post doc to develop a plasma
source for nanoparticle synthesis. His research interests include hollow cathode discharges, complex plasmas, and nanoparticle physics.

Daniel Lundin
Daniel Lundin received his Ph.D. in 2010 from Linköping University, Sweden, focusing
on plasma characterization and process optimization in high-power impulse magnetron
sputtering (HiPIMS). His research on the HiPIMS process won the Institute of Physics
Prize for novelty, significance and potential impact on future research in 2008. He is oneof the founders of the company Ionautics, which provides academia and industry with
HiPIMS coatings recipes as well as hardware. In 2009, he was ranked as one of Sweden’s
young ‘Supertalents’ by the Swedish business journal Veckans Affärer for his work oncommercializing HiPIMS.

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Iris Pilch et al. / KONA Powder and Particle Journal No. 31 (2014) 171–180

Author’s short biography
Ulf Helmersson
Dr. Ulf Helmersson, head of the Plasma & Coatings Physics division at Linköping
University (LiU), has focused his research on the complex relationship between thin-film
growth kinetics, microstructural evolution, and physical properties. Ulf started as anelectron microscopist, using the tools to investigate materials physics (i.e. nanoscience)
rather than using the microscope as an end in itself. Over the last several years, Ulf has
truly pioneered the development of High-Power Impulse Magnetron Sputtering(HiPIMS), the most significant development in physical vapor deposition over the last
decade. In 2008, Ulf become a fellow in the AVS Technology Society (former American
Vacuum Society).

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KONA Powder and Particle Journal No. 31 (2014) 181–199/Doi:10.14356/kona.2014009

Original Research Paper

Photophoresis – a Forgotten Force ?? †Helmuth Horvath
1

University of Vienna, Faculty of Physics, Aerosols and Environmental Physics, Austria

Abstract
In general a force will act on a particle illuminated by light or other radiation and absorbing part of the flux, andas a consequence a motion will result. It is caused by the interaction of gas molecules with the particle’s surface,which is hotter than the surroundings. This surface must be inhomogeneous with respect to accommodation and/or temperature. Gas molecules, impacting and reflected from the particle’s surface with accommodation, transfer
some momentum from the particle and thus cause the force. For a temperature variation on the particle’s surface,
the force points from the hot to the cold part, thus in the direction of the incident radiation, and under very special
conditions it can be the opposite. A particle’s surface having a variation in accommodation coefficient will cause
a force from the locations of higher to lower accommodation. Usually this will cause both a linear force and atorque. The latter in combination with Brownian rotation will result in a zero net force. But it is possible that an
external torque acting on the particles causes an orientation. The torque can be caused by magnetic or electricfields on magnetic or electric dipoles in the particles or by gravity orienting inhomogeneous particles. For
micrometer- and nanometer-sized particles, the photophoretic force can exceed gravity. Photophoresis is important
for levitation in the stratosphere and for planet formation, it can also be used for on-line particle separation, or inclean-room technology or in geo-engineering.
Keywords: levitation, radiation pressure, accommodation, disorientation, orientation, temperature gradientIntroduction
Particles illuminated by a beam of light or infrared
radiation, having sufficient flux density, can move in various directions. This phenomenon has been mentioned by
Thoré (1877), first described and later intensively studied
by Ehrenhaft (1918) and co-workers/students. Since lightis the cause for the motion, the expression “photophoresis”
has become common. Preining (1966) gives a concise
description of the important factors influencing photophoretic motion: “This motion can depend on the illumination, color, structure and shape of the light beam, onpressure and composition of the gas, on the particle’s
size, shape and material, and on additional fields such as
electric, magnetic, and so on.”The motion of the particles can range between simple tovery complex, and depends both on the particle and theexternal forces (see Fig. 1). The simplest motion is (a) positive photophoresis, in which case the particles move in the
direction of the light beam; motion in the opposite direction
is possible, this is called (b) negative photophoresis. For
particles having the right surface and volume properties,†
1

Accepted: July 9, 2013
Boltzmanngasse 5, 1090 Vienna, Austria
E-mail: Helmuth.Horvath@univie.ac.at
TEL: +43-142-775-1177 FAX: +43-142-779-511©2014 Hosokawa Powder Technology Foundation

a motion in or against the direction of an external field is
possible, this is called (c) gravito-, electro-, or magneto-­
photophoresis, depending on the field. Illuminated particles may perform an irregular motion, similar to an
enhanced Brownian motion, called (d) irregular photophoresis. In the case of inhomogeneous illumination and/or inhomogeneous fields, the particles may undergo (e)circular photophoresis, having circular or elliptical orbits,or (f) complex photophoresis, which can be a combinationof several motions. Finally no photophoresis can occur, i.e.
the illumination by light causes no motion in addition to
the motion without light.
The photophoretic force can be larger than gravity forparticle sizes comparable to the mean free path of the gas
molecules and thus can cause a motion against gravity,
leading to the formation of aerosol layers in the stratosphere, photophoresis also plays an important role inplanet formation. For geo-engineering, the photophoretic
force can help to keep particles suspended longer. In
intense laser light, absorbing and non-absorbing particles
can be separated on-line, the microchip production zone
can be kept particle-free, and single particles can be handled by a photophoretic trap. Photophoresis will slow
coagulation. Whenever strong light flux and microparticles occur simultaneously, photophoresis cannot be
neglected, such as during combustion of fuel droplets.

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Fig. 1 Types of photophoresis. When illuminated, particles can move in or opposite to the direction of light (a, b),
move in the direction of external fields (c), move similar to Brownian motion but more vigorously (d), movein closed loops (e) or perform complex motions.

The photophoretic force
The momentum transferred by photons hitting a surface
and absorbed or deflected obviously exerts a force on aparticle in the direction of the photon motion. Using theclassic electromagnetism interpretation of radiation pressure, it amounts to
p=

I
<S>
(1 + R) =(1 + R) cc(1)

with I the intensity (flux density), S the Poynting vector, cthe speed of light, and R the reflectivity for electromagnetic
waves (Landau and Lifschitz, 1988, p. 133). Corresponding
formulas exist for the quantum point of view.
The force exerted by incident light can easily bedemonstrated with a radiometer. It consists of a rotor withvanes (made of aluminum or mica which are dark on one
side, and reflecting on the other) in a partial vacuum.
When exposed to radiation the light mill turns (for a
motion picture see, e.g. http://en.wikipedia.org/wiki/
File:Radiometer_9965_Nevit.gif). A schematic of theradiometer can be seen in Fig. 2. The reflected photons
cause a higher momentum than the absorbed ones, thus
the rotor should turn counterclockwise. In reality the
opposite is the case. Applying formula (1) the motion
should be very slow (see, e.g. the problem 59 in chapter
29 of Tipler, 1991); it would need several years until a few
revolutions per second are reached, in reality the wheel
immediately turns after switching on the light. Except for
extremely intense radiation, this direct photophoresis(radiation pressure) is of minor importance for the

182

Fig. 2

Schematics of the radiometer wheel.

radiometer and also for aerosol science, and thus can beneglected. The indirect photophoretic force, as treatedbelow, is much stronger, but needs the presence of gas
molecules which are available in the radiometer and arealways present in an aerosol.
On a microscopic scale, gas molecules impacting on
the surface are reflected. The reflection can be specular(approximately 10% of the molecules) or diffuse (90%,
Fuchs 1964, p. 22), obviously with conservation of energy.
The diffuse reflection is accompanied by a more or lesscomplete accommodation (see below). For a particle moving through a gas, the molecules impacting at the front
side are reflected with a higher velocity compared to thebackside. This asymmetry in velocities leads to a momentum transfer to the particle and causes the friction force
acting on the particles when moving through a gas.
The reflection of gas molecules at the particle’s surface

Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

with accommodation is of special importance for photophoresis. A surface of a particle which absorbs radiation(visible of IR) is heated to a higher temperature Ts than
the temperature T0 of the surrounding gas. A gas molecule
hitting the particle’s surface can acquire some of the thermal energy of the hot particle and be “reflected” with avelocity corresponding to a temperature, T, that is higher
than the surrounding gas. The probability of taking up
additional thermal energy is characterized by the accomT − T0
, with α = 0 for no, andmodation coefficient α =Ts − T0
α = 1 for full accommodation (Knudsen, 1911). The valueof α depends on both the material forming the particles aswell as its surface structure and the gas. Values between
α = 0.3 and 0.8 have been reported in the literature(Angelo, 1951; Rohatschek, 1955). For example, glazed
platinum has α = 0.315, whereas platinum black, with avery structured surface, has α = 0.72. This can be understood by the multiple reflections of the molecules on thecomplex surface of platinum black, giving a bigger
chance to pick up the surfaces’ temperature. For surfaces
with linear dimensions considerably smaller than themean free path of the gas molecules, the pressure exerted
by molecules, reflected with accommodation, can be
determined from basic formulas of gas kinetics: Gas molecules exert a pressure on any wall due to elastic reflection and thus transfer of momentum. The value of thepressure can be obtained from the equation p.V = R.T. The
mean velocity of the gas molecules depends on the temperature, i.e. c ∝ T . In a gas having a higher temperature, the velocity of the molecules is higher and thus themomentum transferred to the surface is larger, and thereR ⋅T
fore the pressure. Using p =, the increase in presV
sure dp caused by an increase in temperature dT is
R
p
=
dp =
dT
dT . For molecules impacting on the surVT
face with a velocity equivalent to T0 and reflected after
accommodation with a velocity corresponding to a temperature T0 + dT, only half of the pressure increase can be
1 ptaken, yielding dp =dT . For the reflection of mole2 T
cules of temperature T0 on a wall with temperature Tw, thetemperature of the molecules after reflection with accommodation is T = T0 + α(Tw – T0), thus dT = α(Tw – T0)
or dT = α·ΔT with ∆T = Tww −–TT0 0. Thus the additionalpressure due to reflection with accommodation is1 p=∆p⋅  ⋅ ∆T and the force on a circular surface with
2 T0
diameter d amounts to

F=

 2
∆T
⋅d ⋅ p⋅⋅
8
T0

(2)

Fig. 3 Explanation of positive and negative photophoresis(Rubinowitz, 1920). The surface of a strongly absorbing particle is hotter on the side facing the radiation,
thus photophoresis is in the direction of the radiation.
A particle that slightly absorbs light focuses the light tothe rear side, which consequently is hotter, thus theparticle moves in the opposite direction.

Types of photophoresis
If the accommodation coefficient α of the surface of theparticles is α > 0 and the particle is heated by radiation, aphotophoretic force can act on the particle. Two different
idealized extremes can be distinguished: (a) Variation intemperature on the surface of the particles (ΔT force) and(b) variation of accommodation and constant temperature(Δα force):

Case (a): Constant accommodation coefficient
but variation in surface temperature (ΔTphotophoretic force)
Let us assume a spherical particle of diameter d consisting of a light-absorbing material with a thermal conductivity kp and immersed in a gas with pressure p,
viscosity η, and molecular weight M and illuminated byvisible or infrared light. The surface facing the radiation
source is warmer than the backside (see Fig. 3); due toaccommodation, the molecules on the warmer side leave
the surface faster, resulting in a force away from the lightsource (positive photophoresis). This was found to takeplace, e.g. for particles consisting of Au, Ag, Hg, Cd, K,
Na, Mg, soot produced by the combustion of turpentine,or camphor (Ehrenhaft, 1918).
For a slightly absorbing particle, a force in the opposite
direction has been observed. The maximum absorption
may be at the backside, causing the reversal of the force.
The early interpretation is the lens effect, see Fig. 3: Theconvex surface of the particle acts like a lens, concentrating the rays on the backside (Rubinowitz, 1920), whichbecomes hotter than the surface facing the radiation,
resulting in a motion towards the light source (negative
photophoresis). For par ticles comparable to the183Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

wavelength of light, the lens effect as a simplification may
not be permitted, but strictly applying Maxwell’s equation
to an absorbing spherical particle leads to the same results(Dusel et al., 1979; Figure 4.31 of Barber and Hill, 1990).
Negative photophoresis has been observed, e.g. forspheres of S, Se, J, Bi, Th, P, Pb, Te, As, Sb, for tobacco
or wood smoke particles (Ehrenhaft, 1918).
The direction of the photophoretic force is determinedby the direction of the radiation and is almost independentof the orientation of the particle, thus the force is called
space-fixed, the movement is called longitudinal photophoresis and since the temperature difference causes theforce, it is called ΔT force. Although all particles perform
Brownian rotation, the rotation is slow compared to thetime needed to establish the temperature gradient within
the particle (Fuchs, 1964, p. 62). The “ideal” particles
would have a low thermal conductivity and heat capacity.
In the free molecular regime, calculation of the force issimple: Molecules impacting on the particle are reflectedwith a larger velocity due to accommodation. Using considerations similar to the radiometer which was considered above, Rubinowitz (1920) determined the force on aspherical particle with diameter d at gas pressure p as:
Ffree=

ΔT
π
π
gradT
⋅ α ⋅ d2 ⋅ p ⋅=⋅ α ⋅ d3 ⋅ p ⋅
T
T
24
12

(3)

For the derivation in the continuum regime one has toconsider the thermal creep flow around the particle andthe resulting viscous forces. In contrast to the free molecular regime, the gas molecules around the particle havetemperatures similar to those on the surface of the particle (see Fig. 4). A gas molecule impacting on the surface
from the left (hot) side thus has a larger velocity than themolecule impacting from the colder side. After accommodation, the molecules have a symmetric velocity distribution with respect to the perpendicular direction of thesurface, therefore the warmer molecule coming from theleft side transfers to the particle a larger momentum to theright than the colder molecule to the left. This results in a
net force on the particle which directs from the hot to thecold side. The gas loses this momentum, thus a creep flow
around the particle from the cold side to the hot sideoccurs simultaneously which has its maximum flow at a
distance to the mean free path of the gas (Knudsen,
1910a, b; Hettner, 1924; Fuchs, 1964, p.57). Solving thehydrodynamic equations (similar to Stokes Law), the following formula for the photophoretic force is obtained(Hettner, 1926)
3π η2 ⋅ d ⋅ R ⋅ gradT
Fcont
=
⋅
p⋅M
2

(4)

with R the gas constant, η the viscosity of the gas, M themolecular weight of the gas molecules, p the gas pressureand d the diameter of the particle.

184

Fig. 4

Photophoretic force on a particle in the continuum
regime. The particle is hotter on the left side and in theimmediate vicinity of the surface, the gas molecules
have the same temperature as the surface. Molecules
impacting on the particle from the left are faster thanthose coming from the right, transferring a momentum
to the right onto the particle. This momentum is lost in
the gas, thus a thermal creep flow of the gas molecules
to the left occurs.

Formula (3) is valid for the free molecular range, i.e.
the particles must be considerably smaller than the mean
free path of the gas molecules (λ = 66 nm at standard conditions, with decreasing pressure the mean free pathincreases), whereas formula (4) is only valid for the continuum range, i.e. for particles much larger than λ.
Magnitudes influencing the force are the diameter of theparticle and the temperature gradient both proportional to
the force in formulas (3) and (4), the accommodation
coefficient only in (4) and the pressure in (3) and (4). The
force is proportional to the pressure in the free molecularregime (3) and inversely proportional to it in the continuum regime (4), i.e. a maximum force occurs in between,
which is the most important range for photophoresis.
Similar to Stokes’ Law, an interpolation is used for theintermediate range, as proposed by Hettner (1926):
1
1
1, or in detail:=+F
Ffree Fcont
⋅R⋅ gradT6M ⋅Twith p0 =
p
p0
d
+
p0
p

 2
⋅d ⋅⋅
F= 4

d0 =

6
p

RT
M

RT
M

or

(5)

The pressure-dependent force for a given particle size
has a maximum for p = p0, or for a given pressure themaximum photophoretic force is for particle diameter d0.
The pressure for the maximum photophoretic force
depends on the gas properties, the particle size and theaccommodation coefficient. For a pressure of 1 bar theHelmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

optimum particle size is 229 nm for α = 0.8 and 375 nm
for α = 0.3. For a pressure of 5500 Pa (20 km a.s.l.), thecorresponding diameters are 6.8 and 4.1 μm.
The viscosity of the gas, h, is obviously decisive for thephotophoretic force in (4). The viscosity of a gas is mainly
determined by the mean free path, λ, of the gas molecules
8M

=
⋅ p⋅
and the pressure. Using the relation9 RT(see, e.g. Hinds, 1982). Inserting this in (4), the size forthe maximum photophoretic force is obtained as

d0 = 4 ⋅

2
1
3.19
⋅
⋅ =
⋅  , therefore optimal photophoretic effects will be found if the particle size is in theorder of the mean free path of the gas molecules.
Denoting the maximum force at p0 with F0, (5) can be
written as
F
2
=
.
p
p
F0
+ 0
p0
p

(6)

This formula has been tested by many authors. Various
particle materials, particle sizes, gases and pressures havebeen used. Usually the accommodation coefficient andthe particle size are not known exactly, whereas the temperature gradient is completely unknown. The experimental procedure is quite elaborate, since the motion of
one and the same particle is measured for pressures varying over three orders of magnitudes, lifting the particle up
in between. Formula (6) contains only magnitudes thatare experimentally accessible. Since the size of the particle in relation to the mean free path of the surrounding
gas is important, it is also possible to make photophoretic
analogy experiments with centimeter-sized particles, aslong as the mean free path of the particles is large enough.
This requires a high vacuum but offers the advantage thatthe particle can be fixed, and the force can be measured
with a torsion balance. In this way many data points canbe gathered, without the fear of losing the particle during
pressure change (Schmitt, 1961). Compared to the experiments with sub-micrometer-sized particles, the distanceto the walls of the container is much smaller, and wall
effects cannot be neglected. A summary of various experiments is shown in Fig. 5. Particles consisting of Te, Se(Mattauch, 1928), Se (Reiss, 1935), CdS (Arnold et al.,1980) and also 1-cm polystyrene particles at correspondingly low pressures (Schmitt, 1961), all show the same
behavior for gases such as H2, A, O2, N2, CO2. All data
demonstrate the maximum photophoretic force at anintermediate pressure.
Once the size and the photophoretic force of the particle is known, equation (4) can be used to estimate thetemperature difference between the hot and cold side of
the particle. Ehrenhaft (1918) and Parankiewicz (1918)

Fig. 5Experimentally determined photophoretic forces as afunction of pressure. All data show a maximum photophoretic force at an intermediate pressure as postulatedby theory. The dark lines are results of model measurements with cm-sized spheres in vacuum, the points
result from measurements made with individual microor nanometer-sized particles consisting of various
materials, the gray line is theory (6).

have measured the photophoretic forces: They are in theorder of 10 –16 to 10 –15 N for particle radii ≤ 100 nm ofvarious materials in N2 and Ar. The estimate for the temperature difference across the particles is 10 –4 to 10 –2 K
(Hettner, 1926).
For calculation of the photophoretic force in (3) and (4),the temperature gradient in the particle is needed. For
this, both the inhomogeneous heat production within theparticle, the heat conduction to the surface, and themomentum transfer at the surface has to be solved. Fuchs(1964, p. 58) remarks: “The main difficulty in calculating
the radiometric force on a particle is the determination of
the temperature gradient in the particle itself.” For simple
shapes such as spheres this appears possible (see below),
but many particles showing photophoresis are not spheres.
A first attempt for spheres has been made by Rubinowitz(1920) yielding gradT =S, with S the flux den2(kp + kg )sity of the illumination and kp and kg the thermal conductivities of the material forming the particle and the gas. In
the meantime, several investigators have treated the problem in depth: Reed (1977) for low Knudsen numbers,
Yalamov et al (1976), Arnold and Lewittes (1982) close to
the continuum range, Akhtaruzzaman and Lin (1977) for
the free molecular range, Chernyak and Beresnev (1993)
and Mackowski (1989) for the whole range of Knudsen
numbers.
Using all available theories, Rohatschek (1995) formulated an empirical model. For the free molecular and thecontinuum regime, the force on a particle with diameter dilluminated by a flux density S is obtained as

185Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Fig. 6 Photophoretic ΔT force as a function of pressure for various particle diameters. The force is given relative tothe weight of the particle. The data points in the right graph are for sulfur spheres (Parankiewicz, 1918)

Ffree = D ⋅Fcont =

D ⋅ J1 p * 2
⋅
⋅d ⋅S
2kp
p

=
with Dp* =1dα ⋅ J1p⋅ d2 ⋅⋅ S and
p*
4kp


2

(7)


c ⋅
⋅
and
3
T

3 ⋅ c ⋅  =

6
T
⋅D⋅
.

d

(7a)

With kp the thermal conductivity of the particle, J1 theasymmetry parameter for light absorption (½ for opaqueparticles, J1 has the opposite sign if absorption is mainly
at the backside, e.g. for negative photophoresis), D a factor
only containing the gas properties, thus independent ofparticle size and pressure, κ the thermal creep coefficient(κ = 1.14 for a fraction of 0.1 of the specular-reflected molecules, Bakanov, 1992), and p* a reference pressure. (Thepressure for the maximum force is obtained by=p0
2  ⋅ p * ) Combining the forces for the two
regimes (7) as above, a formula for the ΔT force is1
11+
obtained for the entire pressure range: =.
F
Ffree Fcont
As an example, the ΔT forces on particles at various pressures are plotted in Fig. 6. The following properties of theparticles have been assumed: Accommodation coefficient
α = 0.7, density ρ p = 1000 kg/m 3, thermal conductivity
kp = 1 Wm–1K–1. The pressures p* for each particle size186

are indicated as data points on the curves. The maximum
force and the decrease both for lower and higher pressures
are clearly visible. The thermal conductivity appears in
the denominator and thus strongly influences the photophoretic force. The value chosen for the graph may be
representative, but it depends greatly on the particle’smaterial. For example, crystalline graphite (Pedraza andK le me n s 1993) ha s a t he r m al conduct iv it y of1200 Wm–1K–1 parallel to the layer planes, it thus reduces
the temperature difference in the particle considerably aswell as the photophoretic force. On the other hand perpendicular to the layer plane, the conductivity is only
6 Wm–1K–1. But agglomerates of carbon particles are more
likely. For soot the thermal conductivity has values of 3,
or even below 1 Wm–1K–1. Thus the photophoretic force
very much depends on the microstructure of the particle.
A few data points for sulfur spheres are added to thegraph on the right side. The values have been measured
by Parankiewicz (1918) for a pressure of 100 kPa; unfortunately she did not specify the flux density of the illumin a t io n . Su l f u r h a s a t he r m a l c o nd u c t iv it y of
0.205 Wm–1K–1, thus the force should be five times higher
than in the graph. On the other hand, sulfur only slightly
absorbs light and thus shows negative photophoresis, consequently the force is considerably less since only a small
fraction of the light causes a temperature increase. So
these data points can be considered merely as an indication, nevertheless they still show the rapid drop of the relative force for increasing particle size.

Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Case (b): Variable accommodation coefficienton the surface but constant temperature(Δα-photophoretic force)
As a simple model we assume a spherical particle ofdiameter d consisting of a light-absorbing material
immersed in a gas with pressure p, and temperature T (meanmolecular velocity c ). The particle’s surface shall have avariation in the accommodation coefficient, e.g. be caused
by a difference in surface roughness or by different materials forming the particle. For this simple model, one half ofthe sphere’s surface shall have the accommodation coefficient α1, the other α2 (see Fig. 7). At the location of larger
accommodation coefficients, the molecules are reflectedwith a higher average velocity, resulting in a thrust on theparticle from the location of the higher accommodation
coefficient to the location of the lower one. This can beconsidered similar to the jet of an airplane: this thrust has afixed direction relative to the airplane, approximately in theplane of symmetry of the airplane; if the airplane changes
direction the thrust vector changes as well. Likewise thedirection of the force on the particle is determined by theorientation of the particle and is independent of the direction of the illumination (the direction of the force is thus
given in a body axis system, we call it body-fixed or particle-­
fixed force). Upon a change of orientation of the particle,
the direction of the force likewise changes. Since all particles perform Brownian rotation, the direction of the force isdistributed randomly, and the motion of the particles can beconsidered as a strongly enhanced Brownian motion (seeFig. 1d). This has been observed by various authors, e.g.
Ehrenhaft (1907) and Steipe (1952), and was named the“trembling effect”. It only occurred if no orienting field
was present, therefore, e.g. for iron particles, the earthmagnetic field had to be compensated completely.
Obviously the average (net) force is zero, due to Brownianrotation.
The instantaneous Δα-photophoretic force on the particle in the direction from higher to lower accommodation
coefficients amounts to (Rohatschek, 1995)F=

1  −11∆⋅⋅⋅ H , or for air:
2 ⋅ c  + 1 1 + ( p p*)2 

1
1
∆
F=
⋅
⋅H
2
12 ⋅ c 1 + ( p p*) (8),1(1 + 2 ) , γ = cp /cv the ratio of2
the specific heats of the gas, and H the net energy flux
transferred by the gas molecules. This flux is obtained byan energy balance for the particle: Absorbed light flux A.S
plus infrared Eabs must equal the power H transferred tothe molecules due to accommodation plus the emitted
infrared radiative flux Eemitt. For pressures above 100 Pa,
with Δα = α 2 – α1=, Fig. 7

Photophoretic Δα force. A particle, hotter than the surrounding air, has a larger accommodation coefficienton the lower hemisphere. Consequently the molecules
reflected by the lower hemisphere are faster than theones on the upper hemisphere, resulting in an
upward-directed thrust.

there are sufficient molecules available to dissipate theabsorbed radiation thus Eabs and Eemitt can be consideredequal, and A.S = H. At lower pressures, the particle’s temperature increases due to a lack of sufficient energy transfer
by the reflected gas molecules undergoing accommodation,and thus Eemitt rises, therefore H < A.S. To determine theabsorbed light flux, the absorption cross-­section A can beobtained, e.g. for spherical particles by the absorption effi1
ciency factor Qa of the Mie theory as A = ⋅ d 2 ⋅ Qa
4
(Bohren and Huffman, 1983).
As an example, the photophoretic Δα force (formula (8))
for particles having Δα = 0.1 and α = 0.7, consisting of anabsorbing material with a refractive index m = 1.6 – 0.66 iand a density of 2000 kgm–3, illuminated by 1000 Wm–2 at
550 nm at a temperature of 293 K, is shown in Fig. 8 (left).
For better comparison, the force is given as a ratio to theweight of the particle. Similar to the ΔT force, it decreases
with increasing pressure, but there is no decrease for low
pressures. The force is considerable, for particles of 0.2 μm
it is more than 10 times the weight, causing, e.g. the trembling motion as observed, e.g. by Steipe (1952).
But this force continuously changes direction due to the
Brownian rotation of the particle. The mean squareangle of rotation  2 of a spherical particle with diameter
2 kT
d in time t is (Fuchs, 1964, p.245):  2 = ⋅⋅ t , with k the d 3Boltzmann constant and T the temperature. A few valuesof average revolutions per second are given below:
Diameter [μm]Average revolutions in 1

 1
⋅ 2 
2

second 

0.1

0.2

0.5

1

2

61.

21

5.44 1.92 0.68

Considering the vigorous rotation, it is immediately
evident that none of the above particles will perform areasonably straight motion.

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Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Fig. 8

Photophoretic Δα force as a function of pressure for various particle sizes. The force is given relative tothe weight of the particle. Left side: Force on a particle, which is assumed to be fixed in space. Rightside: average force for a particle oriented by a magnetic field, but disturbed by Brownian rotation.

the thermal energy Eth = k·T is a measure for the strength of
The situation changes immediately if the particle orientation is forced in a certain direction. For our considerorientation. No orientation means no magnetic field orations we will assume the particle is located in a magnetic
moment, or T→∞, which implies x = 0. Perfect orientation
field B and has some remanent magnetism characterized
would be for m·B→∞ or T→0 signifying x→∞. The theory
by the magnetic momentum m (Fig. 9). The particle oriof paramagnetism yields for the magnetization M the expresents itself such that its magnetic momentum points in the1sion M =Mˆ (coth x − ) =Mˆ ⋅ L( x) (Brand and Dahmen,
direction of the magnetic field. The direction of the phox
tophoretic force does not usually coincide with the direc2005, p. 293), with M̂ the saturation magnetization and11tion of the magnetic moment and the angle between the=
L( x)− the Langevin function. The asymptotic
two is δ. The particle can still freely rotate around thetanh x x
1
axis of the magnetic moment, therefore all force vectors
behavior of L(x) is: L( x) = x for x << 1, i.e. almost no
are located on a cone with an opening angle of 2·δ. But
3
Brownian rotation is stochastic, thus the photophoreticorientation for small magnetic field and/or moment, and1
force will cause a quasi-helical motion (see insert of Fig.
L( x) = 1 − for x  >>  1 which means perfect orientationx9). The averaged force on the direction of the field isfor a strong dipole and/or field.
obtained by multiplying the instantaneous force (8) with
Using the formalism of paramagnetism, the projectedcos δ. Brownian rotation is not only around the axis of theforce is multiplied with the Langevin function L(x), i.e.
magnetic momentum, but it will also disturb the orientathe average projected force in the direction of the magtion of the force vector, which we have so far assumed to
netic field using (8) is
be at angle δ to the magnetic field line. The stronger themagnet, the less deviations from this direction will be
1
1
∆
F
⋅
⋅ H ⋅ cos  ⋅ L( x) , withpossible. The competition between orienting torque by the =12 ⋅ c 1 + ( p p*)2 
magnetic field and the disorientation by thermal disturm⋅Bbance is very similar to the orientation of magneticx=. (see, e.g. Preining, 1966). This has been done
dipoles in the theory of paramagnetism (see, e.g. BrandkT
and Dahmen, 2005, pp. 290–294): The magnetic dipole
for the considered particles, assuming the material to havewith magnetic moment m in the magnetic field B has aa volume magnetization of 0.02 T/μ0, and a magnetic fieldpotential energy, m·B, its thermal energy is kT. The ratioof 7.10 –5 T (earth’s magnetic field). The mean projectedm⋅B
force is shown in Fig. 8 (right side). Besides the factor
x=of the maximum potential energy Ep = m·B andk ⋅T
cos 45°, there is little difference to the instantaneous force

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Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Fig. 9Particle containing a magnetic dipole in a magnetic field. The particle is oriented such that the magnetic
dipole moment points in the direction of the magnetic field. Rotation around the axis is possible, and thephotophoretic force vectors are positioned on a cone with an opening angle of 2δ (right). Due to the stochastic manner of Brownian rotation, the particle performs a quasi-helical motion (left).

for the particles of 5 and 2 μm in diameter since the magnetic moment is sufficiently large to orient the particles.
For the smaller sizes disorientation is essential, e.g. for
0.2-μm particles, the averaged force only is 25% of theinstantaneous one. Nevertheless the averaged photophoretic force can be larger than gravity, as is the case for the
0.2- to 1-μm particles, thus levitation by sunlight in theearth’s magnetic field is possible. Fig. 10 shows the size
dependence of the relative force for various air pressures.
For particles smaller than 0.1 μm, the Brownian rotation
prevents levitation, for particles larger than 1 to 5 μm,
depending on pressure, orientation would be optimal, but
the weight increases ∝ d 3 whereas the photophoretic force∝ d 2 , thus the relative force decreases.
The Δα force can be channeled around one direction if
an orienting torque exists. This has been shown above formagnetic orientation, but is also possible by electric fields
or by gravity. A typical everyday example of orienting
torque by gravity would be a fishing float which usually
stands upright in the water, when disturbed it will return
to its initial position due to the uneven distribution ofmass. An inhomogeneous distribution of mass will orient
the particle in the same way. This can be seen in Fig. 11:
Assume a particle having different accommodation coefficients on the two hemispheres causing a photophoretic
force to upwards right. (a) The center of gravity is displaced from the center of the photophoretic force by avector q. Gravity and photophoretic force vectors jointly
cause a motion of the particle to the right and slightly
upwards; (b) the motion of the particle causes a friction
force which is added to the photophoretic force. Now

gravity and the other forces are balanced and a stationary
state is reached; but, due to the offset of the center ofgravity and the center of photophoretic plus friction force,a torque acts on the particle, rotating it counterclockwise
until the center of photophoretic force is above the centerof gravity. This results in an upward motion, since thephotophoretic force is larger than the weight (c).
The orientation of the particle is disturbed by Brownianrotation, the important magnitude is the ratio of thepotential energy E p = m·g·q to the thermal energy
Eth = k·T, i.e. the value given by eq. (8) has to be multipliedm⋅ g ⋅qby L(x) with x =. Using the same procedure ask ⋅Tabove, the average force for particles of various sizes andat different pressures has been calculated and results canbe seen in Fig. 10 (right). The assumed density isρp = 1000 kgm–3 and the center of gravity is displaced by
q = 0.2·d. The only difference to magnetic orientation is
the smaller force and the larger diameter at which the relative force peaks. Levitation is only possible at lower
pressures. Since the force is directly proportional to theflux density of the radiation, levitation at atmosphericpressures is possible at flux densities which can beachieved easily by lasers or by intense illumination.
The Δα-photophoresis needs an orienting field, thus it iscalled field photophoresis, specifically gravito-, magnetoor electro-photophoresis. For optimum Δα-photophoresis,
the particles should have a considerable variation of theaccommodation coefficient on the surface and a highthermal conductivity, in order to have a homogeneoustemperature on the surface.

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Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Fig. 10

Relative photophoretic Δα force: Left: Magnetic orientation of the particle. Right: Orientation by gravity. For conditions above the horizontal line, levitation in the atmosphere is possible.

Fig. 11 Orientation of a particle by gravity: (a) The center of mass of the particles is displaced by a vector q. The
photophoretic force (due to different accommodation coefficients) added to the weight of the particles
causes a motion to the right. (b) The friction is a vector to the left (b), adding friction and photophoretic
force yields a vertical vector. Since the two vertical vectors are anchored at different points, a torque on
the particle forces it to rotate (c) until the two anchor points are above each other (c).

(c) Other types of photophoresis
In the two previous sections we have assumed the particle to be spherical and having a rather symmetric distribution of the accommodation coefficients on the surface. It is
hard to imagine that particles formed by combustion,

190

coagulation, condensation on existing surfaces, mechanicalabrasion or interstellar dust particles fulfill these requirements. It can be assumed that particles illuminated by lighthave a temperature gradient on their surface (needed in ΔT
force), but it is unrealistic for a particle to have the same
temperature everywhere on an inhomogeneous surface, asHelmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

we assumed for the Δα force. Thus Δα and ΔT photophoresis will most likely occur simultaneously.
An inhomogeneous surface of the particles will also
cause a photophoretic torque. The radiometer itself (Fig. 2)
is an example. Two arrangements where a photophoretic
torque will act are shown in Fig. 12. The shape (a) is the“Spitzenradiometer” (pointed radiometer) theoreticallyinvestigated by Hettner (1924). The pointed ends of the
body will release more thermal energy, thus be colder.
The photophoretic force is in the direction of the temperature gradient, resulting in a counterclockwise torque. The
particle (b) with an inclusion on the surface having a different accommodation coefficient will have a clockwise
torque, if the accommodation coefficient of the surface of
the inclusion is smaller than for the remaining surface.
Simultaneously, an upwards Δα force acts on this particle.
In addition to the torque and the Δα-force, this particle
with the inclusions (Fig. 12b) will also have a ΔT force. In
the stationary state, the orientation of the photophoretic
torque will be parallel to the direction of light, resulting ina helical motion around the direction of the illumination.
The direction of the photophoretic Δα force need not agreewith the direction of the photophoretic torque (both vectors
are particle-fixed). Depending on their angle to each other,
the resulting motion can be in the direction of the light or
opposite (for theoretical details, see Preining, 1966, p. 130,for observations, see Lustig and Söllner, 1932).
For the Δα force, an inhomogeneous distribution of theaccommodation coefficient on the surface is needed. In
reality this will not be two homogeneous hemispheres, asassumed above, but a particle with a complicated surface
structure. Therefore in addition to the Δα force, a photophoretic torque will make the particle rotate around a particle-fixed axis. This rotation has to be added to the linear
motion caused by the Δα force. Therefore the simple picture of Fig. 9 has to be replaced by a helical movement
around the field line with a constant pitch, obviously with
Brownian disturbances superimposed. The average velocity or the force in the direction of the magnetic field is notaltered. The same is true for gravito-photophoresis.
In an inhomogeneous horizontal illumination, oscillations along a vertical axis are possible. Consider a particle
performing gravito-photophoresis with an additional photophoretic torque. The particle will have a helical movement upwards and out of the horizontal beam of light.
With lower illumination, both the gravito-photophoretic
force and the torque decrease and after some time fortemperature adjustment, the particle follows a helical
downward movement with a different pitch and thenresumes the upward motion, see Fig. 1f.
In two inhomogeneous light beams in the opposite
direction, complicated closed loops in the horizontal
direction are possible, in rotating magnetic fields the particles have even more impressive orbits, for details see

Fig. 12

Examples for particle shapes which cause photophoretic torque. (a) The “Spitzenradiometer” (Hettner,
1924). The points dissipate more thermal energy andare thus colder. Due to the temperature difference, acounterclockwise torque arises. (b) A particle with an
impurity on the surface having a different accommodation coefficient. Both a torque and a Δα force arise.

Preining (1966).

Advanced theories of photophoresis
The theories above have postulated a spherical particle
with some inhomogeneities with respect to accommodation coefficient or density. Experimental evidence showsthat non-spherical particles are better suited for photophoresis than spherical particles. For a full theory similar to asphere, the following problems have to be solved: Heatsources in the particle, thermal conduction in the particle
to obtain the temperature distribution on the surface, andinformation on the accommodation coefficients on thesurface. This is already difficult for spherical particles;
but for simple particle shapes and structures, solutions do
exist: Spheroids (Ou and Keh, 2005), cylinders (Keh etal., 2001), convex particles with rotational symmetry(Zulehner and Rohatschek, 1990), and fractal structures,using the Berry-Percival method for light interaction anda Monte-Carlo method for molecular transfer to obtain ΔT
and Δα forces (Cheremisin and Vasilyev, 2004). The
Monte-Carlo method offers the advantage that for whatever shape and composition of the particle, a solution ispossible with the constraint of sufficient supercomputer
time and detailed information on the properties of theparticle, which is not usually available. Nevertheless,the findings for the simple assumption of spherical particles agree quite well with experimental results for non-­spherical particles.

Measurement of photophoretic forces I:
Longitudinal photophoresis:
The following components for a successful measurement of photophoresis are needed: measuring chamber,radiation source, observation device, particle generator,pressure gauge as already described above. Since monodisperse particles could not be produced in the early days,

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Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Fig. 13

Apparatus used by Ehrenhaft (1918) for the observation of photophoresis. Top: Light is concentrated byseveral lenses in the center of the observation cell. The observation is done through a microscope, perpendicular to the direction of illumination. The dark field illumination permits the observation of particles sizing down to tens of nanometers. The cell can be evacuated or pressurized and is made of anelectrically insulating material. Bottom: Two metal plates serve as a capacitor to exert vertical forces on
charged particles. The charging of the particles is done by ionizing radiation.

it was important to make as many measurements as possible with one particle. Electrostatic fields are used to bringthe (charged) particles back to the initial state, being avery tedious job, especially if the pressure in the chamber
was changed. So it required a lot of skill and patience toproduce series of measurements which lead to the data
points, e.g. shown in Figs. 5 and 6.
Ehrenhaft (1918) designed an observation cell and illumination system of maximum flexibility, a schematic canbe seen in Fig. 13. The cell can be illuminated by the lightof a carbon arc lamp, the infrared is filtered by a liquid
filter, thus the illumination is polychromatic with wavelengths between 400 and 1200 nm. The light is concentrated by several lenses into the center of the observation
cell. The flux density in the center can be up to 4000
times the solar constant. With a shutter, the illumination
can be chosen to be from the right or the left side, or both.
Particles in the cell are observed by a microscope, viewing perpendicular to the direction of illumination. The
intense dark field illumination permits the recognition ofparticles down to less than 100 nm in diameter. The
observation cell is made of the electrically isolating material ebonite, contains two metal plates forming a capacitor
and has two glass windows for illumination and one topermit observation. Operation at low pressure is also possible. Particles are generated in various carrier gases, byprocesses such as electrical arc between various metalelectrodes, evaporation in test tubes, or simply by using
smoke, e.g. from the combustion of paper or cigarettes.
The particles are charged by diffusion charging with ionsproduced by ionizing radiation.
To measure the photophoretic force, the particles are

192

illuminated by light and the velocity of the horizontal
motion is measured by stopping the time needed for a distance of 0.3 mm. Within this distance the light could beconsidered homogeneously. When the particle is close to
the end of the field of view, the opposite illumination isused, bringing the particles back. When settling too far, avoltage is applied to the plates of the capacitor, lifting thecharged particles up. In this way a series of measurements
is possible with one and the same particle. When the particle is outside of the intense beam, the photophoretic
force is negligible and the settling velocity and the velocity in the electric field can be measured. The diameter ofthe particle was measured by determining the settling
velocity v and applying Stokes’ Law: d =18 ⋅ η ⋅ v
ρp ⋅ g ⋅ Cs

with ρp the density of the material forming the particle
and Cs the slip correction. Using this technique, it waspossible to determine the dependence of the photophoretic
force on illumination, material, pressure, and with somemodifications (see below), on external fields.
An impressive experiment demonstrating light absorption to be the reason for photophoresis has been performedby Déguillon (1950): A droplet of a dye solution is illuminated by a white light beam and shows positive photophoresis. The dye has a strong light absorption in a narrow
band of wavelengths. If this wavelength range is filtered outof the beam by a slab of the same dye solution, the particle
is still strongly illuminated, but shows no photophoresis.
The laser, CCD cameras and methods to produce monodisperse particles made observations simpler by far: An
arrangement is shown in Fig. 14 (Haisch et al., 2008). The

Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Fig. 14

Experimental determination of the photophoretic
velocity: A continuous aerosol flow passes a small cellwhich is illuminated by a vertical laser beam. Whenilluminated by the horizontal laser beam, the particles
move in the direction of the light. The motion of theparticles is observed with a video camera. The path ofthe particles is shown on the right.

aerosol passes through a cell about 10 mm × 10 mm ×
80 mm in size, having windows on all planes of the
cuboid. The aerosol is illuminated by a green laser passing vertically through the cell. The excitation laser passes
from the right to the left, the observation of the particles’
path is performed with a CCD from the front (perpendicular to the drawing plane). The particles move verticallyin the cell until passing through the excitation laser beam,
which deflects particles with positive longitudinal photophoresis to the right. A schematic of the CCD picture isseen on the right side. Knowing the vertical velocity vv of
the particle, the photophoretic velocity v phot can beobtained by the angle φ between the vertical and the
direction in the laser beam by v phot = v v . tan φ.
Monodisperse polystyrene latex spheres with no absorption for green light were used, so the observation laser
does not cause photophoresis. With this set-up the dependence of the photophoretic velocity on the laser flux density and the particle size have been checked andagreement with theory has been found. The photophoretic

Fig. 15

velocity depends on the material of the particles; for substances such as CuSO4, NaCl, Cu(CH3COO)2, Ni(NO3)2,
KMnO4, and others, and a size of 200 nm ± 50 nm, values
between –0.48 and +0.03 mm/s have been found (Kykal,
2010, p. 100).
The force on a charged particles in the field of a capacitor offers the possibility to directly measure the photophoretic force. A capacitor having a homogeneous field
does not allow a stable positioning of the particles perpendicular to the electric field. By using a capacitor withan insulated inner circular electrode at a higher voltage, apotential well can be created, keeping the particles horizontally stable in the center. Vertical stability is attainedby observation of the particle’s location with a position-sensitive detector and a feedback to the voltage of thecentral plate (Arnold et al., 1980, see Fig. 15).
The electrodynamic levitation (e.g. Wuerker et al.,1959, see also Fig. 16, many other configurations are inuse, for a review see, e.g. Davis, 1997) offers the possibility of trapping the charged particles. The AC voltage 2 Vac
is applied between the ring electrode and the bottom andtop electrode. Additionally, the DC voltage 2 Vdc is added.
The non-uniform alternating field has a focusing effectand dynamically stabilizes the charged particle in the nullpoint of the field. The additional DC field compensates
the weight of the particle and brings it to the plane ofsymmetry of the electrodes. When illuminating the particle, e.g. by a vertical laser beam, the DC voltage Vg isadjusted to compensate the additional photophoretic force
in order to keep the particle in position. The additional
electric field multiplied by the particle charge equals thephotophoretic force. For an application see, e.g. Wurmand Krauss (2008).

Measurement of photophoretic forces II:
Field photophoresis
For measurement of field photophoresis, an orienting
field is obviously needed. For magneto- or electro-photophoresis this field can be simply generated in the

Capacitor for measurement of the photophoretic force. The upper plate of the capacitor has a circularinsert, which is kept at a higher voltage, stabilizing the particle horizontally in the center. The verticalstabilization is done with a position-­sensitive photodetector.

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Fig. 16

Electrodynamic levitation of particles. An AC voltage is applied between the bottom and top electrodeand the ring electrode in series with a DC voltage. By proper shaping of the electrodes, a rotational
symmetric parabolic potential is created, trapping the charged particle in the center. When illuminatedby a vertical beam, the position of the particle changes. By adjusting Vg, the particle is brought backinto position and the force can be determined.

laboratory, whereas the gravitational field is omnipresent.
Magneto-photophoresis has, e.g. been measured by Steipe(1952) and Preining (1953), using an arrangement similar
to that in Fig. 13, with Helmholtz coils to produce themagnetic field, or to compensate the earth’s magnetic
field. The particles were generated by an arc discharge
between iron electrodes, producing spherical particles offerromagnetic iron oxides with a diameter around 400 nm
and illuminated with flux densities comparable to thesolar constant. The measured photophoretic velocities
increased with increasing magnetic field strength due tobetter orientation. In the case of perfect orientation, thephotophoretic velocities were between 50 and 300 μm/s,
compared to the settling velocities between 6 and 30 μm/s.
For a field strength equaling the earth’s magnetic field, thephotophoretic velocities were 50 to 80% of the maximum
values, indicating that photophoretic levitation is possible
in the atmosphere.
Since gravity cannot be switched on and off, the measurement of gravito-photophoresis is more elaborate (see,e.g. Jovanović, 2005, Fig. 17): An observation cell which
can be evacuated has four windows. The illumination
comprises a Xenon arc lamp (similar to daylight) and alens system, producing a homogeneous illumination
within the cell comparable to sunlight. A mirror opposite
to the light entrance produces additional illumination,
reducing longitudinal photophoresis. Observation is perpendicular to the illumination through a microscope lensand a CCD camera. The particle reservoir contains a powder of soot or graphite, etc. Tapping on the reservoir produces about 1000 particles which fall into the beam, a few
of them show gravito-photophoresis, move upwards, andend their motion at the top of the illumination beam. The
shutter is closed for a few seconds, the particles sedimentand upon illumination move upwards again. In this way

194

Fig. 17 Measurement of gravito-photophoresis. The cell is illuminated by light through one of the windows, and observation is perpendicular to this direction. Particles in thereservoir are released by knocking the cell slightly. Particles which show photophoresis are trapped at the top of
the beam. Closing the shutter causes the particles to sediment, with open shutter the gravito-photophoretic
velocity can be measured (Jovanović, 2005).

the velocity due to sedimentation and photophoresis canbe measured. An electron microscope grid (normallyshielded) can be positioned under the observation volume
and the particles can be analyzed. Fig. 18 gives the relation
between the Feret diameter and the perimeter of the particles, the particles showing gravito-photophoresis have alarger perimeter, i.e. have a more irregular shape, as
expected. Spherical black carbon particles (obtained by theatomization of India ink) do not show gravito-photophoresis.

Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Fig. 18

Relation between the Feret diameter and perimeter ofparticles. The particles showing gravito-photophoresis
have the largest perimeter, i.e. are the most irregular(Jovanović, 2005).

Application of photophoresis in various fields
of aerosol science
Positive photophoresis can be used as a tool for theon-line separation of absorbing and non-absorbing particles. Particles are illuminated by an intense laser (808 nm),obtain a velocity in the direction of the light and perpendicular to the flow velocity due to the photophoretic force,and can be collected in a secondary flow (Haisch et al.,2008). Photophoretic particle trapping in a doughnut-­
shaped light intensity field and levitation is also possible(Desyatnikov et al., 2009).
Failures in electronic chip production are caused byparticles which settle on the chip during production.
Shielding the product from the unwanted contaminationis traditionally achieved by thermophoretic or electrophoretic forces; but both interfere with the production process. Longitudinal photophoresis has been investigated asa possibility to push particles out of the sensitive range(Selvaraj, 1994; Periasamy et al., 1993). Since the only
requirement for photophoresis is a light (laser) beam,interference with the production process is minimal.
Furthermore, the photophoretic force increases withdecreasing pressure for the particles of interest.
In the stratosphere and mesosphere, the air molecule’s
mean free path is between 1 and 100 μm due to the lower
pressure, thus appreciable photophoresis can occur for allparticles found there. Early laboratory investigations
under stratospheric conditions revealed considerable
upwards motion of NaCl particles by negative longitudinal photophoresis (Orr and Keng, 1964); on the other
hand, Hidy and Brock (1967) estimate the effect ofphotophoresis on the settling velocity of the particles as
negligible. Since an irregular particle or one with a magnetic or electric dipole moment has a preferred orientationin the gravitational, magnetic or electric field, gravitomagneto- or electro-photophoresis are important. Thishas been proven experimentally (Jovanović, 2005).
The existence of layers of particles in the stratosphereand mesosphere is a well-known fact (Junge et al., 1961;
Bigg, 1964; Volz, 1971; Zuev et al., 1996, 2009; Berthet etal., 2002, Mateshvili et al., 1999; Gerding et al., 2003).
Furthermore, soot particles are found at locations in thestratosphere with no evident sources (Pueschel et al.,2000). Soot particles absorb light, thus are hotter than thesurrounding air, and they have a complex shape, which isimportant for gravito-photophoresis. So the movement of
the particles upwards from the place where they are produced (Pueschel et al., 2000) can be explained. For the
existence of particle layers in the atmospheres, it is necessary that (1) a lifting force on the particles compensatesgravity and (2) that the particles return to their location
after disturbance. Due to the complex structure of thestratosphere and mesosphere, locations can be foundwhere these requirement are fulfilled (Cheremisin et al.,2005, 2011). The particles are illuminated by solar radiation amounting to 1360 W/m2, thus light-absorbing particles consisting of black carbon or iron oxides can belevitated by gravito-, electro- or magneto- photophoresis.
The outgoing terrestrial infrared radiation equals the solar
constant, thus particles that are transparent in the visible
but absorbing in the infrared are also candidates for photophoresis. For example, for ammonium sulfate, the imaginary part of the refractive index is < 10 –6 in the visible
but increases to more than 1.0 at 10 μm, thus (NH3)2SO4
is as absorbing in the infrared as black carbon in the visible (Bohren and Huffman, 1983, p. 438). In the Junge
layer (Junge et al., 1961), sulfate particles have been foundand Cheremisin et al. (2011) have shown that particles
which strongly absorb in the infrared only and sized
between 1 and 2 μm will be stable at ≈ 22 km. Particles
formed from meteor smoke or debris of rockets can havea magnetic momentum and thus be oriented by the earth’s
magnetic field. The magnetic orientation is stronger thanby gravity, see Fig. 10, so particles between 0.1 and0.25 μm can form layers, e.g. at 76 to 82 km. Favorable
conditions in the atmosphere for the formation of stablelayers depend on time, latitude, longitude, and particle
size. Particles with sizes between 0.1 and 5 μm can form
layers between 18 and 90 km altitude at various times ofthe year, latitude and longitude. For details see
Cheremisin et al. (2011). A comparison of the backscatterratio of the Kamchatka LIDAR station 2007 to 2008 andthe calculated stability zones shows an almost perfectagreement (Cheremisin et al., 2012).
Photophoresis can have an influence on coagulation:

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After reflection from the surface of a particle heated bylight absorption, the gas molecules have a higher velocity,
they can repel adjacent particles by impaction and thus
slow coagulation (Cheremisin and Kushnarenko, 2013).
The magnitude of the force is considerable and comparable to electrostatic forces: e.g. two 50-nm particles separated by three radii, illuminated by 1360 W/m 2 at apressure of 1000 Pa, the repelling force is 30 times theweight of the particles, for 250- and 500-nm particles thefactors are 10 and 7. At night, the particles are colder than
the surrounding air and thus have a small attractive force.
This repelling force slows coagulation, the coagulation
constant is reduced by a factor of up to 10.
During combustion, the high temperatures cause strong
infrared and visible radiation, and light-absorbing particles are present. The main force on the particles is bythermophoresis powered by the temperature gradients,
but the photophoretic forces cannot be neglected. They
are responsible for the formation of stable soot shells
around a fuel droplet (Pera et al., 1999), and amount toabout 10% of the deposition force to cold surfaces (Castillo
et al., 1990).
Photophoresis is an important force involved in planet
formation. In a gas-rich, optically thin circumstellar disk,
the motion of particles ranging from 1 μm to 10 cm will
be dominated by photophoresis, moving the particles
opposite to gravity to a distance from the star where thegas density reaches a value at which photophoresis equals
all other forces at work. Thus the formation of ring-likestructures of dust distribution around a star can be
explained naturally (Krauss and Wurm, 2005), and theformation of protoplanets is significantly influenced byphotophoresis (Wurm and Krauss, 2006; Krauss et al.,2007).
In the fight against global warming by geo-engineering,particles could be positioned in the stratosphere or mesosphere. They should reflect sunlight and remain suspended as long as possible. The photophoretic force canbe very helpful, since a long residence time can beachieved this way. A particle optimized for this purpose
could be a disk of 10 μm in diameter, having a layer of
Al2O2 at the top, Al in the middle and BaTiO3 at the bottom and a thickness of 10 nm. Orientation is caused by
the electric field (Keith, 2010), i.e. electro-photophoresis
prevents settling.
For completeness it is mentioned that the term photophoresis is also used for the motion of hydrocolloids illuminated by an intense laser beam. But for photophoresis,
the thermal slip is needed. In that case, it is actually theradiation pressure, see Eqn. (1), that makes the particle
migrate (Helmbrecht et al., 2007).

Acknowledgements
The author is thankful for the infrastructure madeavailable by Professor Tohno, School of Energy Scienceof the University of Kyoto and the Zentralbiliothek für
Physik Wien, which is an almost infinite source for hardto-find literature. Most of this paper was presented as aplenary lecture during the European Aerosol Conference
2012 in Granada. I thank the organizers L. Alados and F.J
Olmo Reyes for giving me the chance to investigate thisinteresting subject in depth.

List of symbols
SymbolName

Unit

Definition

A=

A

Absorption cross-section

m2

B

Magnetic flux densityTc

Mean velocity of gas
molecules

m·s –1

Cs

Slip correction

none

d

Diameterm, μm, nm

Eemitt Eabs

Emitted, absorbed IR
flux

W

g

Gravity constantm·s –2

H

Transferred energy flux

W

J1

Asymmetry parameter for
absorption

none

196

1 2
⋅ d ⋅QQaa
4c2 =RemarkFictitious surface through which the absorbed
light passes

3RTM

IR flux absorbed and emitted by a particle; must
be balanced with absorbed visible flux and powertransferred by accommodation to moleculesg ≈ 10m·s –2

Acceleration on earth due to gravity
Energy flux transferred by the gas moleculesfrom the particle surface

Yalamov et al., 1976

| J1 |=

1 for opaque particles
2Helmuth Horvath / KONA Powder and Particle Journal No. 31 (2014) 181–199

Symbol

Name

Unit
–1

Definitionk = 1.38·10

Remark–23–1

kBoltzmann constant

J·K

kg k pThermal conductivity

W·m –1·K–1L(x)Langevin function

none

M

Molecular mass

kg·kMol–1mMagnetic moment

Am 2

p

PressurePaq

Displacementm

Vector between center of gravity and center ofphotophoretic force

Qe

Absorption efficiency

none

Absorbed radiation divided by the radiation
incident on the particleR

Gas constant

S

Flux density

W·m –2T

Absolute temperatureKxα

Accommodation coefficientγ

J·K

kg conductivity of gas, kp conductivity of particle’s material

11−tanh x x=L( x)Symbol m also used for massR = 8314 J kMol–1 K–1

S=

dP
dA

none

x=

m⋅B
m ⋅ g ⋅ q Ratio of potential energy Ep = m·B or Ep = m·g·q
or =and thermal energy Eth = k·T
kT
kT

none

α=

T − T0Ts − T0

Probability for a gas molecule to diffusely reflect
from the particle’s surface with the temperatureof the surface

none

γ=

cp
cv

Ratio of specific heat at constant pressure andspecific heat at constant volume

Energy of radiation passing per time through asurfaceη

Viscosity

Pa·sκ

Thermal creep coefficientnoneκ = 1.14 for 10% specular-reflected moleculesρ

Densitykg·m –3

ρp density of material-forming particle

2

Square of angulardisplacement

rad 2

θ2 =

2 kT
⋅
⋅t
π ηd 3

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Yalamov Yu.I., Kutukov V.B., Shchukin E.R., Theory of thephotophoretic motion of the large-size volatile aerosol particle, Journal of Colloid and Interface Science, 57 (1976)
564–571.
Zuev V.V., Burlakov V.D., A.V. El’nikov, Results of long-term
lidar observation of eruption aerosol formations in thestratosphere over tomsk after the mount pinatubo eruption,
Proceedings of the Sixth Atmospheric Radiation Measurement (ARM) Science Team Meeting DOE CONF-9603149,
March 1996 San Antonio, Texas, 1996, 383–387.
Zuev V.V., Balin Yu.S., Bukin O.A., Burlakov V.D., Dolgii S.I.,
Kabashnikov V.P., Nevzorov A.V., Osipenko F.P., Pavlov
A.N., Penner I.E., Samoilova S.V., Stolyarchuk S.Yu.,
Chaikovskii A.P., Shmirko K.A., Results of joint observations of aerosol perturbations of the stratosphere at the cislinet network in 2008, Atmospheric and Oceanic Optics, 22(2009) 295–301.
Zulehner W., Rohatschek H., Photophoresis of nonsphericalbodies in the free molecule regime, Journal of Colloid andInterface Science, 138 (1990) 555–564.

Author’s short biography
Helmuth Horvath
Helmuth Horvath, born 1941 in Vienna, studied experimental physics in Vienna, Ph.D. in1966 under the guidance of O. Preining. Extended scientific visits with the universities of
Washington, Colorado, Santiago de Chile, Kyoto and Granada. Professor of Experimental
Physics in Vienna 1980 to 2006. Research interest in all aspects of the physics of aerosols,
especially optics.

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KONA Powder and Particle Journal No. 31 (2014) 200–213/Doi:10.14356/kona.2014011

Original Research Paper

Population Balance Model for Crushed Ore Agglomerationfor Heap Leach Operations †Nikhil Dhawan, Samira Rashidi and Raj K Rajamani *1

Department of Metallurgical Engineering, University of Utah, USA

Abstract
Agglomerate size distribution is a pretreatment step in low grade heap leach operations. The present work focuseson modeling the evolution of size distribution in batch agglomeration drum. Up to now there has been no successful
work on modeling of crushed ore agglomeration although the framework for population balance modeling ofpelletization and granulation is readily available. Different batch agglomeration drums were used to study the
agglomeration kinetics of copper, gold and nickel ores. The agglomerate size distribution is inherently subject torandom fluctuation due to the very nature of the process. Yet, with careful experimentation and size analysis theevolution of size distribution can be followed. The population balance model employing the random coalescencemodel with a constant rate kernel is shown to work well in a lab scale agglomerator experiments. It was observedthat in a small drum agglomerates begin to break in a short time whereas the growth is uniform in the larger drum.
The experimental agglomerate size distributions exhibit self-preserving size spectra which confirms theapplicability of coalescence rate based model. The present work lays out the fundamentals for applying the
population balance concept to batch agglomeration, specifically crushed ore agglomeration. The experimental
difficulties and how to overcome them are described.
Keywords: Heap leaching, crushed ore agglomeration, agglomerate size and population balance model

1. Introduction
Heap leaching is one of the promising economic andgreen processes for the treatment of lean ores of copper,
nickel, and gold. Acid or cyanide solution is percolated
through a large heap of ore body and leached out metal iscollected after several days.
During heap building i.e. the transport of ore material tothe heap, severe segregation of material can occur which
results in poor bulk permeability and ore percolation.
Introduction of agglomeration step prior to heap building
results in minimal segregation and solution flow throughheap. It is well understood that percolation is highly dependent on the size distribution of the crushed ore, because
fine particles tend to wash out and plug the pores in theheap. Therefore, it is important to bind fines to coarse
particles to improve overall percolation.
Agglomeration pretreatment is required for ores which
either contain excessive amounts of clay or an excessive
quantity of fines generated during crushing. While agglom†

Accepted: July 16, 2013
William Browning Bldg., 135 S 1460 E, Rm 412, Salt Lake City, UT
84112, USA* Corresponding author:
E-mail: raj.rajamani@utah.edu
TEL: +1-801-581-3107 FAX: +1-801-581-4937
1200

eration has become common pretreatment step in heap
leach operations, the fundamental understanding of theagglomeration process for crushed ores is still lacking(Bouffard, 2005; Dhawan et al., 2013).
Crushed ore agglomerates can take two forms: fine particles adhering to coarse particles and fine particles adhering to each other. The former is similar to granulation
whereas latter is referred as pelletization. For binder
assisted agglomeration, adhesion and cohesion forces are
dominant whereas surface tension and capillary forces prevail in non-binder/wet agglomeration (Kodali et al., 2011).
The residence time for agglomeration and the binding
agents dominantly control the growth and mechanism of
agglomeration. For hard to crush ores, the dominant mechanism of agglomeration growth is layering of fines on bigger
particles, i.e., rim agglomerates whereas, newly nucleatedagglomerates are expected to be more prevalent in high clay
content ores such as nickel-laterite ores.
Generally, the agglomerated ore has a distinct particle
size distribution (PSD) with a slight increase of the top size
but a very large increase in the lower sizes. Typically, sizes
are 60 mm to 2 mm with all of the minus 2 mm adheringto the coarser particles or between themselves (Miller,2010). The author reviewed the crushed ore agglomeration
process up to 2012 and did not come up on modeling studies on the topic (Dhawan, 2013; Dhawan et al., 2013). Some©2014 Hosokawa Powder Technology Foundation

Nikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

of the possible reasons can be the stochastic nature ofprocess, experimental difficulties and lack of instrumentation for fundamental studies. Therefore, in this work thefundamentals for applying the population balance concept
to batch agglomeration is laid out. Also, some other aspectsof the evolution of agglomerate size distribution (ASD) are
carefully studied using four different ores.

2. Literature review
Agglomeration results from direct interactions between
discrete particles, and the agglomerate formation andgrowth can be mechanistically described with phenomenological models (Hogg, 1992). The basic mechanisms
observed in agglomeration systems include coalescence,crushing and layering, snowballing and nucleation. These
have been discussed in detail in the past (Kapur andFuerstenau, 1969, Sastry, 1975; Kapur and Runkana, 2003;
Liu et al., 2012).
Coalescence refers to the production of large-size
agglomerates by clumping or fusing together of two or
more particles. When agglomerates collide and stick orpack together in a geometric configuration favorable withrespect to the rest of the moving charge, the conglomerateof agglomerates begins to roll and eventually deforms andforms the next larger agglomerate. The coalescence events
cause discrete changes in the size of the agglomerates withan overall decrease in the agglomerate population without
any change in their mass. Often coalescence is observed tobe the most important mechanism responsible for growth
in a batch system. Coalescence mechanism contributes
wholly or partially to the growth of agglomerates madefrom materials of wide size distributions, whereas crushing and layering mechanism is the dominant mode in narrow sized particle populations (Kapur and Fuerstenau,
1969; Sastry, 1975; Kapur and Runkana, 2003). Theseauthors reported that it holds strongly in the initial stagesof agglomeration and almost throughout the batch agglomeration of materials with naturally comminuted and wider
size distributions. Coalescence applies to wide distributions due to size independence, whereas crushing and layering applies to narrow size distributions due to size
dependence. Unlike pelletization, the crushed ore agglomeration primarily contains wider feed size distribution ofsizes up to 1.5 inch, employs retention times as low as
1-3 min and lacks stable acid-binder within the bed.
Moreover, the coexistence of fines (minus 75 micron)micron and larger sizes makes the growth mechanism andparticle-particle interaction cumbersome in agglomeration.
At present no definitive modeling studies have beenreported on crushed ore agglomeration (Dhawan et al.,2013). Considering these facts, modeling studies of pelletization and granulation forms the starting point. In thepast, pelletization and granulation have been studied indetail. The pelletization studies were carried out with veryfine sizes in the 100 μm size range whereas granulation
studies were also restricted to a maximum feed size of
10 mm. In these studies, it is important to mention thatnarrow feed size distribution, longer agglomeration times
and stable binder conditions were the influencing factors.
The size enlargement modeling has been done primarily
with the concept of population balance model. Pelletization
systems have utilized the coalescence model, whereas
granulation studies used partition coefficient for an equilibrium model without considering agglomeration kinetics(Litster et al., 1986; Kapur and Runkana, 2003).
The population balance for a well-mixed batch system
undergoing coalescence alone is described in the literature(Kapur and Fuerstenau, 1969; Kapur and Runkana, 2003)
as Eq. (1).
∂ n(v, t)
∂t

= −

1 ∞
 (u, v, t)n (u, t) n (v, t) du
N Ta ∫0+1 v
λ (u, v − u, t) n (u, t) n (v − u, t) du
2 N Ta ∫0(1)

In this equation, u and v refers to volume of agglomerate, n(v, t) is the number density function, λ(u, v, t) is coalescence kernel rate, NT is the total number of particles at timet, and α is space system parameter. This is the time continuous and size continuous population balance model.
The total volume should be conserved in the systemsince agglomerates of volume vi and vj combine together toform an agglomerate of volume vi + vj at all times as shownin Fig. 1.
In modeling, coalescence is the most difficult mechanism. However, it is needed to formulate the population
balance in terms of number distribution by volume because
granule volume is conserved in a coalescence event. An
important parameter in population balance modeling(PBM) is the growth rate (coalescence kernel (λ)) thatsignifies the degree of agglomeration. The kernel dictates
the overall rate of coalescence, as well as the effect of
granule size on coalescence rate. The order of the kernel
has a major effect on the shape and evolution of the granulesize distribution. Most of the kernels are empirical orsemi-empirical and must be fitted to plant or laboratory
data. Modeling growth where deformation is significant ismore difficult. It can be assumed that a critical cutoff size
determines which combination of agglomerate sizes is

Fig. 1

Schematic of coalescence mechanism.

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Fig. 3Fig. 2

Image of micro-agglomerator and ancillary equipment.

Feed size distributions of different ores used.

capable of coalescence. Coalescence of particles is mainly
dictated by its inertia. As with chemical reactors, thedegree of mixing within the agglomerator has an important effect on the final ASD because of its influence on theresidence time distribution (Snow et al., 2009).

3. Materials and methods
Four ores provided by different mining companies wereused in this study. The ores were screened into various size
fractions and the size distribution of ores used in theexperiments is shown in Fig. 2. The major difference
between the ores is weight percentages of minus 200 mesh.
Copper ore-II and nickel ore feeds are finer than gold ore
and copper ore-I (minus 200 mesh% Cu-I: 7.4, Cu-II: 23.6,
Au: 10.6, Ni: 14.9). The top size fed to the laboratory
agglomerator was limited to 13 mm to insure that agglomerates were not too large for subsequent column leachingand secondly to accommodate the size and capacity of thedrums used in this study. The bulk densities of copper-I,
copper-II, nickel and gold ores are 1.42, 1.55, 1.17 and1.67 g/cc, and the natural moisture content is 0.26, 2.6,
13.4 and 1.4%, respectively.
The preliminary experiments were conducted using a
micro-agglomerator as shown in Fig. 3. The agglomeration drum was made using a 1 liter fluorinated polyethylene (FLPE) Nalgene bottle 9 cm in diameter by 17 cm
in length. Three polytetrafluoroethylene (PTFE) lifters
placed 120° apart were attached in the drum. Each lifter
was 2 cm wide, 14.3 cm long and 6 mm thick. The small
drum was mounted in a horizontal bracket and was driven
with a 24 V D.C. motor and can run at variable speeds up
to 76 rpm (Dhawan, 2013).
Based on several experiments, it was observed that insmall drums the presence of large particles hindered thegrowth of other agglomerates. This caused incomplete
agglomeration and thereby failing the objective of study-

202

Fig. 4

Photograph of the agglomeration drum.

ing the behavior of each ore type. To avoid such behavior,lab-scale drum, shown in Fig. 4, was used in this study.
This drum is a copy of the drum used in previous studies
by Kapur and Fuerstenau (1969) and Sastry and Fuerstenau(1973) at the University of California Berkeley. The drum
is a fully enclosed water-tight drum machined from analuminum block, measuring 12 inches in diameter and 6.9
inches in length. Twelve lifters of 20 mm diameter wereattached length wise uniformly around the inner peripheryof the drum to prevent any sliding of the charge andimparted a rolling and cascading action to the agglomerates. The inner surface of the drum was lined consistently
with silicone coated polyurethane gloss finish to eliminate
ore charge sticking. The drum lining was refurbishedwhenever there was a change in ore type. The use of
scraper was not considered to avoid any interference withthe experiment. A transparent acrylic plastic cover on the
drum enabled convenient withdrawal of product andobservation of the charge motion.
In crushed ore agglomeration, volume loading is generally kept low, up to 8%. This low volume filling of thedrum can be seen as a single layer of charge and thereby
not enough capacity to carry on. In general, large particles
migrate to the outer side of cascading charge, whereas
smaller particles are at the lower or inner region. Under
these conditions large particles can break intermediate

Nikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

size agglomerates.
For PBM, number size distribution is a prerequisite.
Therefore, batch experiments corresponding to different
time intervals were conducted in the lab-scale drum.
Following the experiment, number size distribution foreach time step was also determined in an image analysis
set up. A batch of known weight corresponding to 7%
volume loading was introduced into the drum. Next, thedrum was rotated for 5 min without any other additives.
Then a premeasured amounts of sulfuric acid solution(Copper ore-I, II and nickel ore) or cyanide solution (goldore) was added to the drum in a short time (less than 30
seconds). In other words, the ore was prewetted to minimize the incomplete wetting of the tumbling charge duringsolution delivery.
After that, the drum was closed with the lid and wasplaced on two horizontal rubber rollers. It was rotated at
24 rpm (30% critical speed) for a specified time. At a predetermined time interval, the rotation was stopped and the
moist agglomerated ore was spread on a tarp. The material
was further sampled by cone and quartering technique arepresentative sample of 450–500 grams was collected.
The sample was air dried at room temperature for 24 hours.
Then the dried sample was analyzed under image analysis
set up for number size distribution. To avoid experimental
error or concerns regarding effect of drying and sampling,for each time interval, a new batch experiment was conducted for the entire duration of 1, 2, 2.5, 3 or 4 min.
The standard cone and quartering technique was used inthis work only because there are no other practical methods that will work with soggy ore agglomerates that have awide size distribution. The material is piled in a heap sothat the natural segregation in the heap is nearly symmetrical. The conical pile is then spread from the center toform a flattened disk of material. Then, the disk is divided
into quarters using a flat wooden plank. A pair of opposite
quarters is removed, and the other pair is used as the representative sample. Depending on the mass needed, thematerial can be coned and quartered again. Certainly, theprocedure is tedious, time consuming and prone to humanerror. The representative agglomerate sample was air driedat room temperature before sieve size analysis.
The procedure for number size distribution of agglomerates involves primarily image analysis and shape factor
to convert between mass and number distribution. A dry
sample was placed on black paper under the image analysis setup. Individual agglomerates particles were moved
apart from each other on the paper so that there was nooverlap. The setup requires proper lighting conditions sothat the particles do not reflect light. The pictures weretaken by a camera (Fujifilm® FINEPIX® XP10). Next, theimages were processed through ImageJ® software fromwhich the number size distribution was obtained. Once theparticles are captured in an image file, each particle area isknown and its size is determined. In the image analysis, it
is assumed that the particles are spherical in shape. Thismay be a very drastic assumption but very much necessary
for modeling. In the modeling part the volumes of particles
are added to generate agglomerate volume. Considering
the different response of each ore type, the shape factors
effect was not included in the population balance model.
However, using shape factors, converting number size distribution (image analysis) to weight size distribution (sievesize) is possible.

4. Model Development
The time evolution of the PSD is commonly obtained
from the solution of the general population balance model
governing the dynamic behavior of a particulate process.
Several numerical methods have been used for solving thesteady-state or dynamic population balance equation. These
include the full discretization method (Hounslow et al.,1988), method of moments, fixed and moving pivot discretized methods (Sastry and Gaschignard, 1981), high-order
discretized methods (Ramkrishna and Mahoney, 2002).
Based on the detailed literature review, the PBM equation
used in this work was adapted from Kapur and Runkana(2003).
The rate of coalescence in restricted-in-space environment should be proportional to number of particles of sizei and number fraction of particles of size j, or vice versa.
Hence, specific rate constant or coalescence kernel λ bydefinition is independent of the size of the interacting
agglomerates. Under these stipulations, the generalized
PBM Eq. (1) reduces to Eq. (2) (Kapur and Fuerstenau,
1969; Sastry and Fuerstenau, 1973; Kapur 1978).
dni (t ) i −1=− ni (t ) +∑ ni− j (t)n j (t)dt
2 N (t ) j =1

(2)

The basic postulate of the model is that the particle massis well mixed and the collision of frequency and the probability of coalescence are independent of size. The coalescence model also assumes that the nucleation of the moist
feed has already been completed in the first few revolutions
and hence, only the mechanism of coalescence is operative.
In this model, the size interval is discretized into a large
number of intervals. Interval i represents a volume vi ofparticles in that interval. Further, interval i is assumed torepresent a volume i × v1 where v1 is the smallest volume
representing the first interval. Such a formulation allows apair of size classes to coalesce and yet form a larger volume that is already defined as a size class. Thus, volumeconservation is guaranteed. In the model Eq. (2), ni(t) is thenumber of particles of size i at time t in the agglomeration
drum, λ is average random coalescence rate constant, N(t)is total number of particles at time t. The derivative term in203

Nikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

the Eq. (2) gives the time rate of number of particles of sizei. The second term depicts the disappearance of size i due
to agglomeration of size i with all other sizes. The third
term depicts that the formation of particles of size i due tocoalescence (below size i) of size i with size i-j.
In this formulation, particle of size i disappear in proportion to the number fraction nj(t)/N(t) of particles of size
j surrounding it. Likewise, particles of size i agglomeratewith size j in proportion for the number fraction of size isurrounding it. Summing Eq. (2) over all sizes, it can beshown that the rate of depletion of the total number ofagglomerates, N(t), conforms to the first order decay kinetics as shown in Eq. (3). The solution of Eq. (3), which is thetotal number of agglomerates at any instant N(t) is given by
Eq. (4).
dN (t)
= − N (t)
dt
2

(3)

N (t) = N (0) e 2

(4)

λ
− t

However, the random coalescence model includes someassumptions. It involves pure agglomeration process; allagglomerates are spherical and equal probability of coalescence for all size classes. It can be argued that a single-­parameter coalescence kernel is sufficient for shortagglomeration time provided the total volume of the system is conserved. If necessary, the single coalescence kernel can be transformed into a matrix form. In other words,
the coalescence between size class i with class j can be
distinguished with a coalescence rate λij instead of a single
value of λ used for all size classes. Under this formulation,
Eq. (2) is rewritten as Eq. (5). Therefore, the coalescencekernel becomes a set of m 2 values or m × m matrix, wherem is the total number of intervals. The kernel matrix issymmetric because rate of coalescence is identical for size
i with size j as it is for size j with size i.
The matrix enables the assignment of coalescence rate
values as is needed between particles. However, thisassignment is done from a primary value λ determined.
For example, two large particles of sizes 20 and 24 mm
cannot coalesce to form 44 mm agglomerate. Hence, theircoalescence rate may be set to a small value, small as
λ/100. The lambda matrix can predict size distribution
more accurately if the precise interaction between sizes
can be formulated.
m
n (t)
dni
= −ni (t) ∑ λij j
dt
N (t)
j =1

i −1

+∑ j =1 λi − j, j ni − j (t)n j (t)N (t)(5)

The matrix formulation is shown in Fig. 5. The coalescence rate λ is determined graphically by plotting the total
number of agglomerates remaining as a function of time.
The analytical solution to the integro-differential equation

204

Fig. 5

Formulation of Lambda matrix for random coalescencemodel.

is only known for special forms of the coalescence kernel
with an assumed initial number density distribution.
The lack of analytical solutions necessitates the use ofnumerical techniques. A popular method is method of size
discretization (Kapur and Runkana, 2003) that involves
discretizing the particle size domain into a relatively small
number of size classes, and then monitoring the number
and mass of particles in each size class so as to minimize
if not eliminate the finite domain error. Volume is used as
the size descriptor for the sake of convenience in handling
death and birth terms. Often in the laboratory, the size
distribution is measured with a set of sieves. Since a few
sieves are used, only size fractions are measured in eachsize interval. In other words, the measured information is
not sufficient to convert to the continuous density function. Therefore, the reverse course is followed: discretize
the continuous size model, and get a discretized modelwith discrete solution.
As per model Eq. (2), the volume intervals and numberof particles in each volume interval were specified.
Assuming all agglomerates as perfect spheres and knowing their respective size fractions were the prerequisites
for the model framework. Considering the maximum
agglomerate size to be approximately 25 mm that covers avolume of 10,000 mm3, 4,000 intervals each of volume
2.5 mm3 were used to cover the entire volume range. For
example, 1.7 mm agglomerate means agglomerate retainedon 1.7 mm screen and passed through 2.5 mm screen.
Similarly, the number size distribution of particles attime zero or particle size distribution of the drum feed was
also calculated. Based on the volume intervals, a set of
4,000 ordinary differential equations (ODE’s) were solved
simultaneously using Matlab software. After each experiment the number of agglomerates with their respective
sizes was determined. A MATLABTM code was written tocount the number of agglomerates in each volume interval.

Nikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

Fig. 6Comparison of experimental number size distribution
and model predictions for fine copper-I ore feed at different time.

The population balance model was solved using discretization procedure at defined screen sizes. The numerical
package used for solving the set of differential equations
was the Matlab function “ode45 and ode15s”, which is an
ODE solver within the “Optimization” toolbox. Both of thefunctions were yielding very similar results. Since ode45
function was taking less time, it was selected for all thesimulation work. The ode45 solver uses a variable step
Runge-Kutta numerical algorithm. For all the simulations,a time step of 0.001 min was used.

5. Results and Discussion
The experiments were determined based on the numerous preliminary experiments done in the lab-scale andmicro-agglomerator drums. The results of these experiments were also used for determining optimum agglomeration conditions. However, for the sake of brevity only
typical results are shown here. Preliminary experiments
were conducted on copper ore using fine feed size distribution (minus 1 mm) to test the applicability of the population balance model. For modeling purposes, one expects a
gradual and smooth coarsening of size distribution. The
evolution of PSD with time should be smooth as it is inother size enlargement operations.
From image analysis methodology, it was observed thatthe number of agglomerates remaining in the drum isdecreasing with increase in residence time. The coalescence rate was different for each experiment and also varies with the amount of solution added. The range of
coalescence rate for all the experiments is 0.4–2.4 perminute. A typical model prediction as compared to experiment results is shown in Fig. 6. It is evident that model
prediction and experimental results are in agreement.
Based on the success of PBM model predictions in fineFig. 7Comparison of experimental number size distribution
and model predictions for coarse copper-I ore at different time.

feed experiments, scoping experiments were performed in
the microagglomerator with wide feed size distribution.
Fig. 7 show typical copper ore model predicted and experimental agglomerate size distribution. It is evident fromthe figure that model prediction and experimental results
are not satisfactory. Moreover, there is not a smooth transition of ASD with time as was expected. In fact, ASD corresponding to 3 and 6 min are same, which indicatessaturation or equilibrium size distribution.
Based on many similar experiments, it was confirmedthat longer retention times lead to restricted growth or
finer ASD which indicates there is breakage of agglomerates. In particular, the majority of the experimental ASD
showed breakage after 3 min. Since ASD curves collapse
on each other it seems that after certain time there is anequilibrium size distribution. It can be argued that breakage and agglomeration occurs in the drum within 3 min.
Therefore, in this study, larger retention time was not
attempted because most plant scale agglomerators run at 2
or 3 min mean retention time. The expectation is that in
the first 3 min growth is much larger than breakage.
In regular crushed agglomeration, however, the evolution of PSD with time is not as smooth as it is in other size
enlargement operations such as pelletization. The sourcesof such behavior include, (1) irregular shape of agglomerates which makes it difficult to determine actual volume,(2) mixing of ore particles with acid solution seems to be
never uniform within the agglomerator unless prewetted,(3) agglomerates break mainly due to weak adhesion
between large and small particles, (4) due to lack of wetting of fine ore particles, the growth rates may vary in thesmall and intermediate sizes, (5) in general, small particles
layer large particles, but if too much fines are present, they
themselves, can agglomerate but they break up on collision. In the first few revolutions, the nucleation of the
moist feed completes, but due to lack of uniform wetting

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nucleation itself is random.
The modeling of agglomeration with PBM is approachedwith a view to make it reasonably simple so that it may
become a tool in plant operations for the prediction of
ASD. However, the inevitable irregularities in the experiments pose a severe challenge to the approach. Obviously,
agglomerates are not perfectly spherical and wetting withacid solution is not uniform either. However, with these
considerations, it is worthwhile to see how crushed ore
agglomeration may be brought under control to study theunderlying growth rates.
It was thought that the reason for some of the unfavorable model predictions is due to the use of single coalescence rate for all size classes. The logical next step is to try
different coalescence rate for pairs of size classes, i.e., thecoalescence rate constant is different pairs of coalescing
size classes, as described in model eq. (5).
The cumulative number fraction passing using a single
lambda value (scalar lambda), experimental data and amatrix of lambda values is compared in Fig. 8. It is quite
clear that experimental data do not fit really well with different matrix lambda for most of the ASD. Rather, themodel prediction fits well with the single value of lambda.
However, with a better understanding of coalescence rateof different sizes, the matrix predictions can be improved.
However, the matrix formulation requires more detailed
micro-scale investigation of underlying mechanisms thatwas beyond the scope of this work.
Coalescence rate model worked well even with anapproximated growth rate. The prediction for first few
minutes was accurate however it fails at longer retention
time because the size distribution does not conform toregular growth behavior for any ore. With these experimental and model analyses, it was realized that the experiments should be done in a larger drum. It was expectedthat due to more free space in a larger drum, better cascading action and regular growth will occur. Therefore, tostudy the agglomeration behavior of different ore types
and to delineate the other relevant effects all modelingexperiments were done in the lab-scale drum.
Although no rigorous statistical analysis of the experimental precision has been attempted, it is neverthelessimportant to consider in a qualitative sense the possible
source of errors. The two main sources of error are theprocedure adopted for measurement of the agglomerate
size and the stochastic nature of the process. Firstly, theagglomerates are not geometrically perfect spheres and themeasured agglomerate size is based on the estimate of
circular diameter. Moreover, the image analysis systemloses its precision at sizes less than 1 mm. The second
error is due to stochastic fluctuations of size distribution
about the average agglomerate size mean. Agglomeration
dynamics is subject to probabilistic laws, and as such, twoagglomeration experiments carried out under identical

206

Fig. 8Comparison of experiment and and model predictionsat t= 3 min for copper-I ore using lambda matrix.

conditions have only a finite probability of showing thesame ASD.
In the small agglomeration drum, however, the stochastic nature is magnified due to small number of agglomerates participating in each size class. In very large drums
the stochastic nature will be smoothed out by the verylarge number of agglomerates present.
Based on preliminary experiments it was evident thathigher retention time (i.e., more than 3-4 min) does notcontribute to further agglomerate growth. Therefore, themaximum retention time in the drum was limited to 4 min.
Since the coalescence rate plays a major role in the underlying model, its accuracy is vital. Hence, all experiments
were done at four time intervals so that better approximation of slope can be obtained. To avoid experimental errors
such as stopping the drum to collect the sample, each time
step was done in different batches. Therefore, one complete
experiment involves four batch experiments between
1-3 min. Each experiment was carried out at different moisture conditions and was part of the planned agglomeration
growth range. Also, the drum volume filling (7%) and drum
speed (30% Nc) were kept constant for all experiments.
The visual appearance of agglomerates is one of the firsthand experiences regarding agglomeration behavior. Long
duration agglomerates are generally characterized bysmoother surface and shape. A typical screen shot of copper-II ore agglomerates under image analysis set up is
shown in Fig. 9. It is evident from the figure that agglomerate shape becomes more regular (spherical) at a longer
retention time.
A series of experiments were done with copper-I ore in
the lab scale drum. A typical experiment results is shown
here. Fig. 10, 11, 12 show the photographs of the agglomerates, experimental ASD, semi-log plot of total number versus time, and model prediction overlaid on experimental
data. It is difficult to recognize any appreciable growth pattern from agglomerate photographs. But the surface sheen

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Fig. 9Fig. 10

Typical screenshot of copper-I ore agglomerate samples
under image analysis set up at different time intervals(increasing left to right: (a) 1.5 min, (b) 2 min, (c)3 min, (d) 4 min.

Fig.   11(a) Agglomerate size distribution for copper-I ore (weightpercent).

Photograph of copper-I ore agglomerate sample atdifferent time intervals (increasing left to right: (a)1.5 min, (b) 2 min, (c) 3 min, (d) 4 min.

Fig.   11(b) Semi-log population plot for growth rate determination for copper-I ore.

increases at high moisture conditions as seen in Fig. 10.
In each of these experiments some overlap between successive ASD was noticed as in Fig. 11(a). The growth rate
was not large enough to show sufficient advance in theseintervals. The closeness or cluster between ASD curves
possibly indicates that certain equilibrium size distribution
is unique for agglomerates and it will not move further
irrespective of retention time. In some experiments it isevident that the model prediction for initial time, i.e., 1 mindoes not fit well with experimental ASD. This is due to theslope approximation made from 0–4 min (Fig. 11b). It canbe seen from the population plot that the number of agglomerates decreases at a faster rate during the initial 1 min
period than other times. This is due to the presence of alarge amount of fines present at start time. In other words,
the decay or population of agglomerates is not progressing
at exactly same rate as expected in the model. Even then,with average growth rate, the model predictions are stillsatisfactory as shown in Fig. 12. Similar results wereobtained for different experiments involving different
moisture content. Similarly, copper-I ore experiments werealso conducted in the micro-agglomerator in order to study
the variation in growth rates in different size of drums.
Fig. 13 compares the growth rate as a function of moisture between the microagglomerator and the lab-scale
drum. The growth rate trend is the same in both thedrums. However, the coalescence rate was slightly less in
microagglomerator as compared to the lab-scale drum.
Obviously, there is better cascading and tumbling action
achieved in the lab scale drum and hence the higher
growth rate. Moreover, the breakage problem arises atlonger agglomeration times in the microagglomerator.
Considering the similar behavior of agglomerates in thesetwo drums, all experiments for nickel, gold and copper-IIores were only done in the lab-scale drum.
Similarly series of experiments were done with nickel
laterite ore, copper-II and gold ore at different moisturelevels in the lab scale drum. For the nickel ore, based on

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Fig. 12Fig. 13Comparison of experimental number size distribution
and model predictions for copper-I ore at different
time intervals.

Comparison of variation of coalescence rate withmoisture for copper-I ore.

the photos as shown in Fig. 14, there is a notable absenceof surface sheen on the agglomerates even at high moisture
content (36%). However, long duration agglomerates werepossessing smoother surface and shape. It was observedthat moist ore sticking was slightly higher at longer time
for this ore; therefore, agglomeration time was limited
only to 3 minutes.
The population decay or decrease in the number ofagglomerates with time was more uniform. On drying,agglomerates became highly friable and hence released asignificant amount of fines on contact. Hence, the size
measurement was restricted up to 2 mm for the same reason. It is important to mention that the background color ofimage analysis setup was changed to light grey to gain
contrast between agglomerates and background.
The gradual growth of agglomerate under specified conditions points to a good fit between experiments and model
prediction. The ASD at different time intervals were plotted in accordance with the random coalescence model. A
comparison of experimental and predicted ASD is shown

208

Fig. 14

Photograph of nickel ore agglomerate sample at different time intervals, increasing left to right: (a) 1.5 min,(b) 2 min, (c) 2.5 min, (d) 3 min.

Fig. 15 Comparison of experimental number size distribution
and model predictions for nickel ore at different timeintervals.

in Fig. 15. It can be seen that there is a reasonable fit
between experiment and the model prediction. The closeness between experimental data and the theoretical lines
confirms the soundness of the model.
It can be observed from Fig. 16 that moisture content
certainly alters the coalescence or growth rate. However,for most of the experiments it is close to 1.1 min–1, whichis slightly less than that for copper-I ore. For practical
purposes, an average value of coalescence rate 1.1 min–1 isreasonable for nickel ore.
For copper-II ore, there is slight difference in visualappearance among different experiments. The slight difference between appearances is the dark contrast at highmoisture conditions. A surface sheen was never observedon this ore type even at high moisture content, because ofhigh clay content. However, long duration agglomerates
had a smoother surface and regular shape as shown inNikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

Fig. 16 Variation of coalescence rate (λ) with moisture content
for nickel ore.

Fig. 18

Comparison of experimental number size distribution
and model predictions for copper-II ore at different
time intervals.

Fig. 17

Fig. 19

Variation of coalescence rate with moisture for copper-II ore.

Photograph of copper-II ore agglomerate sample atdifferent time intervals, increasing left to right: (a)1 min, (b) 1.5 min, (c) 2 min, (d) 3 min.

Fig. 17. Based on scoping experimental results, the agglomeration times were confined up to 3 min. It is important tomention that the population decay or decrease in the number of agglomerates with agglomeration time was steepest
for copper-II ore as compared to copper-I ore and nickel
laterite ore. The agglomerates were of different characteristics in terms of shape and partial wetting.
From experimental observations, it was seen that assoon as the liquid was added to the charge, lumps wereformed. Therefore, some particles were found unwetted
even after agglomeration. It was rare to observe any
remaining fine particles for copper-II ore. Since there isappreciable agglomerate growth under specified conditions, it is reasonable to expect a good fit between experiments and model prediction. The ASD at different timeintervals were plotted in accordance with the random
coalescence model as shown in Fig. 18. There is somemisfit between experimental and predicted ASD. This isbecause of steep slope change from 0–1 min as comparedto other times. Also, the absence of intermediate sizeclasses in this ore type leads to unusual agglomeration
behavior.
The value of coalescence rate is almost twice as compared to copper-I and nickel laterite ore as shown in Fig. 19.
In general, there seems to be a midpoint value close to 14%
moisture where the rate is at its maximum value. However,for most of the experiments it is close to 1.9 min–1, whichis almost twice that for nickel ore. For practical purposes,
an average value of 1.9 min–1 is useful.
Unlike other ores, the photographs of gold ore agglomerates at different time intervals and at different moisture
conditions show a significant variation. With each time
step, the transition to smoother surface and shape, appearance of coarser agglomerates at longer times are evident as209

Nikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

Fig. 20 Photograph of gold ore agglomerate sample at different time intervals (increasing left to right: (a) 1 min,(b) 1.5 min, (c) 2 min, (d) 3 min.

Fig. 22

Variation of coalescence rate (λ) with moisture forgold ore.

Fig. 21 Comparison of experimental number size distribution
and model predictions of gold ore at different timeintervals.

Fig. 23

Variation of coalescence rate for all ore types withmoisture.

shown in Fig. 20. The appearance of surface sheen on the
agglomerates indicates the range of optimum moisture
content. Considering the regular agglomerate growth
shown by agglomerates under specified conditions, it isreasonable to expect a regular fit between experiments andmodel prediction. A comparison of experimental and predicted ASD is shown in Fig. 21. It can be seen from thesefigures that there is reasonable fit experiment and model
prediction. The closeness between experimental data andthe theoretical lines confirms the soundness of the model.
The growth rate of gold ore under different moisture
conditions is shown in Fig. 22. In general, there seems to
be a midpoint value close to 7–8% moisture where thegrowth rate is maximum. However, for most of the experiments it is close to 1.2 min–1, which is nearly the same asthat of copper-I ore and nickel ore.
For comparison purposes, the variation of coalescence

rate with moisture for all ore types is shown in Fig. 23. For
each ore type, the moisture content certainly changes thegrowth rate. In general, there seems to be an optimum
moisture value where maximum rate was observed.
However, based on magnitude copper-II ore grows almost
at a rate two times as that of nickel ore.
In general, it can be seen that the overall agreement isreasonably good between experimental size distributions
and those predicted by the random coalescence model.
Considerable deviation occurs, especially at the initialtime step due to rapid coalescence of fines in the feed. In
some experiments the number size distribution curves
overlapped at two different times. This is expected inview of the fact that, firstly, the coalescence rate constantused in the development of this model was taken to be aconstant for all agglomerate sizes, and secondly, anyerror in the measurement of the circular diameter of the210Nikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

agglomerate is magnified on taking its cube when computing the agglomerate volume.

6. Theoretical validation
Sastry (1975) reported that agglomerate growth bycoalescence is a sufficient condition for observing theself-preserving size spectra, which implies that there exists
a unique ASD in a batch system which is independent of
the material and processing conditions. The similarity distribution of the agglomerates is independent of the ore
type and conditions of agglomeration, and is uniquelydetermined by the coalescence kernel.
It has been reported that the pellet growth by coalescence is a sufficient condition for observing the self-­
preserving size spectra and not necessarily the only one.
Also, self-preserving size spectra of green pellets is a char­acteristic of the batch agglomeration. Mathematical analysis of the coalescence process indicated that there exists
a self-preserving, pseudo-time- independent size distribution of agglomerates.
Based on mathematical transformations, it was argued
if the coalescence kernel is a homogeneous functionof its arguments, then the coalescence process has a self-­
preserving type of size distribution. However, it was em­
phasized that such a self-preserving distribution may be
only a particular solution and may or may not be unique(Sastry, 1975). In other words, when experimental data
exhibits self-preserving spectra then random coalescence isa valid approach to pursue. Therefore, the numerical solutionof the population balance model with constant coalescence
rate and experimental data for gold ore is plotted in Fig. 24.

7. Conclusions
Population balance model for batch agglomeration has
been developed. The model predicts the evolution of ASD
in the batch agglomeration drum. The size distributions of
the agglomerates in the specified time are adequately
described by the random coalescence model. The model
was verified for four ore types and different moisture levelfor each ore type. The kinetics of agglomeration designated by the coalescence rate is affected by the moisture
content of the system. The copper-II ore exhibits the highest growth rate, whereas nickel laterite ore exhibits theslowest rate among the ores tested. A reasonable fit implies
that the model accurately accounts for agglomerates
growth due to coalescence taking place in the drum. The
population balance model is more than adequate for application to batch agglomeration drums. The use of small
drums leads to both agglomeration and breakage within a
few minutes. The use of larger drums smooth out random

Fig. 24(a)Experimental self-preserving agglomerate number
size distribution for gold ore.

Fig.   24(b) Computed self-preserving agglomerate number
size distribution for gold ore.

fluctuations and minimizes breakage of agglomerates.
Hence, for modeling purposes the use of as large drum as
possible is recommended. Agglomerates are certainly
irregular particles. However, the assumption of sphericalagglomerates held pretty well in the population balance
modeling effort. Experimental ASD exhibit self-preserving spectra and is found to be independent of operating
conditions and is uniquely determined by the coalescencemechanism.

Acknowledgements
The authors would like to thank AMIRA International
and the sponsors (related mining companies) for permission to publish the work. The authors also acknowledge thefunding from AMIRA under P986 project. Any findings,
opinions, and conclusions in this paper are those of theauthors and not those of AMIRA International or its sponsors. Thanks are due to Professor Michael Moats, Michael

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Free and JD Miller for active discussions throughout thework.

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leach operations, PhD thesis, University of Utah, Publication No. 3561756, 2013.
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growth, and aggregation, AIChE Journal 34 (1988) 1821–
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417–427.
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Evaluation of stucco binder for agglomeration in the heap
leaching of copper ore, Minerals Engineering, 24 (2011)
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1036–1044.
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Technology, 223 (2012) 92–97.
Miller G., “Agglomeration drum selection and design,” Proceedings of XXV International Mineral Processing Congress,
Brisbane, Australia, 2010, pp. 193-202.
Ramkrishna D., Mahoney A., Population balance modelingpromise for the future, Chemical Engineering Science, 57(2002) 595–606.
Sastry K., Fuerstenau D., Mechanisms of agglomerate growth ingreen pelletization. Powder Technology, 7 (1973) 97–105.
Sastry K., Similarity size distribution of agglomerates during
their growth by coalescence in granulation or green pelletization, International Journal of Mineral Processing, 2(1975) 187–203.
Sastry K., Gaschignard P., Discretization procedure for the
coalescence equation of particulate process, Industrial &Engineering Chemistry Research 20 (1981) 355–361.
Snow R., Allen T., Ennis B., Litster J., Size reduction and size
enlargement, in: Perry Chemical Engineers Handbook,
McGraw-Hill, 2009.
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thesis, Department of Metallurgical Engineering, University of Utah, 2012.

Nikhil Dhawan et al. / KONA Powder and Particle Journal No. 31 (2014) 200–213

Author’s short biography
Nikhil Dhawan
Nikhil Dhawan did his B.Tech in Metallurgical Engineering at Punjab Engineering
College, India. Afterwards, he received his Ph.D. in Metallurgical Engineering at the
University of Utah, USA under supervision of Prof. Raj Rajamani. His research interest
includes comminution particularly HPGR technology and agglomeration practice.
Presently he is working as a scientist at CSIR-IMMT Bhubaneswar, India.

Samira Rashidi
Samira Rashidi is a Ph.D. student in Metallurgical Engineering. She received her BSc andMSc degrees from AmirKabir University, Iran. Her Ph.D. thesis is mainly about studying
energy-size relationships of different ores in lab-scale HPGR. Her background research
focuses on modelling and simulation of comminution technology.

Raj Rajamani
Raj Rajamani is a professor of Metallurgical Engineering Department at the University ofUtah. His research interests are: Modeling charge motion in ball, SAG and AG mills, fluid
flow in pulp lifters, CFD modeling of hydrocyclones, modeling of high pressure grindingrolls and eddy current separation of electronic waste. He is recipient of Gaudin Award(2008) for his work in the application of DEM methods in the modeling of charge motion
in grinding mills and for his contributions to the basic science of comminution and classification. He received his B.E. (Honours) degree from Annamalai University, India, M.
Tech from Indian Institute of Technology, Kanpur, India and Ph.D. from the University of
Utah.

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KONA Powder and Particle Journal No. 31 (2014) 214–233/Doi:10.14356/kona.2014012

Original Research Paper

Morphology and Nanostructure of Granular Materials Built
from Nanoparticles †Jose L. Castillo *, Santiago Martin, Daniel Rodriguez-Perez,
Alvaro Perea and Pedro L. Garcia-Ybarra
1

Departamento de Fisica Matematica y de Fluidos, Facultad de Ciencias, UNED, Spain

Abstract
Nanopowders or nanoparticles can be used as building blocks for the preparation of new materials with a prescribed
structure. Monte Carlo simulations have shown that the morphological properties (bulk porosity and surface
roughness) of a granular deposit can be tailored by properly adjusting the velocity of the particles approaching thedeposit. Based on these theoretical predictions, experiments have been conducted to prepare nanostructured
materials from carbon nanoparticles. By electrohydrodynamic atomization of a liquid suspension (carbon
nanoparticles dispersed in ethanol), an electrospray of small droplets is generated. The charged droplets are driven
by the electric field with the ethanol evaporating along the droplet path, leaving dry nanoparticles that deposit on
the collecting surface. The surface roughness of the resulting material has been characterized as a function of thevoltage drop. Moreover, catalytic suspensions of platinum supported on carbon nanoparticles (Pt/C) in Nafion®alcohol solutions have been electrosprayed over carbon paper to prepare electrodes for proton exchange membrane
fuel cells (PEMFC). The fuel cell power density was measured as a function of the platinum loading and the rangeof parameters leading to optimal platinum utilization was obtained.
Keywords: nanopowders, powder deposits, granular materials, deposit morphology, electrospray, catalytic materials,
fuel cell electrodes

1. Introduction
Powder technologies have increased their application
field ranging from environmental issues of social concern(i.e. the filtration and elimination of unwanted powders
and the reduction of particulate emissions from industrial
activities, car engines or energy production) to the fabrication of new materials with specific properties. Thus tocomply with the social needs and the environmental regulations, the control of particle emissions requires the development of clever filtration systems (Konstandopoulos andPapaioannou, 2008). On the other hand, the fabrication ofadvanced materials from aerosols promotes the development of new powder processing techniques (Milosevic etal., 2009; Naito et al., 2009; Yurteri et al., 2010). In allthese cases, a proper knowledge of the dynamics of particle-­laden gases is needed to control the particle motion(Garcia-Ybarra et al., 2006; Rosner et al., 1992) and thedeposition of particles on the walls confining the gas
stream (Castillo and Rosner, 1989; Castillo et al., 1990;†
1*

Accepted: July 18, 2013
Senda del Rey 9, 28040 Madrid, Spain
Corresponding author:
E-mail: jcastillo@ccia.uned.es
TEL: +34-913-987-122 FAX: +34-913-986-697

214

Garcia-Ybarra and Castillo, 1997). This dynamic control
allows either the delivery of the powdered material tospecific locations (as it is required in filtration systems orin some pharmaceutical applications of aerosols) or to
avoid the deposition of particles on some valuable surfaces(in applications ranging from large furnaces to the fabrication of microelectronic devices, for instance).
The distinctive large surface/volume (surface/mass) ratioof powders make them especially suitable for applications
requiring a large active surface area which is the case forcatalyst applications or pharmaceutical products, as well as
for different solvent-based fabrication techniques. In thisway, powders can be used as building blocks for the preparation of new materials (Luyten et al., 2010) which stillretain this large surface/volume ratio as a distinctive feature. This is the central topic of this work: the fabrication of
granular materials from powders (Section 3) emphasizing
several ways to control the structure of the final product(based on the simulations described in Section 2) and showing in Section 4 a specific application of these granularmaterials (their performance as fuel cell electrodes).
Granular materials formed by the accumulation andadhesion of incoming aerosol particles acquire a morphological structure controlled by the form of the constitutive
particles and by the way in which these particles arrive and©2014 Hosokawa Powder Technology Foundation

Jose L. Castillo et al. / KONA Powder and Particle Journal No. 31 (2014) 214–233

attach to the forming material (Rodriguez-Perez et al.,2005, 2007). A proper control of the aerosol particle
dynamics may lead to granular deposits with a well-­prescribed bulk morphology and surface structure.
This paper joins together three complementary studies.
First, in Section 2, a Monte Carlo simulation is used torelate the final structure of a granular material to thearrival dynamics of the constitutive particles. The knowledge gained with the simulations guides the preparation ofmaterials with a given morphology and nanostructure. To
achieve this goal, and as the key starting point, a simplified
theoretical model is implemented to simulate the growth ofa granular material from the deposition of aerosol particles.
Monte Carlo simulations of particle deposition provide a
correlation of the growing deposit morphology (bulk porosity and surface roughness) with the aerosol dynamics.
These theoretical predictions are then checked by performing some experiments conducted under controlled
conditions. Thus, in Section 3, a liquid suspension containing carbon nanoparticles is electrosprayed at a constantflow rate to form a cloud of small liquid droplets. The
electrically charged droplets are driven by an externallyimposed electrical field and evaporate along their flighttoward a collecting plate, leaving dry nanoparticles which
deposit on the collector. The parameters controlling theelectrospray dynamics are the physical properties of theliquid suspension (surface tension, electrical conductivity, ...), the flow rate and the voltages applied at the electrospray needle and at the collector plate. For a given liquid,
there is a range of flow rates where a proper combinationof needle voltage and collector voltage leads to an electricfield at the needle that keeps the electrospray working in astable cone-jet mode, Martin et al. (2012). These voltages
also play a major role in controlling the electrical field at
the collector (which affects the dynamics of the dry
nanoparticles arriving to the forming deposit). The structure of the final granular deposit is analyzed as a functionof some of these controlling parameters (applied voltages
and liquid conductivity) and the results are compared with
the Monte Carlo simulation predictions.
Finally, in Section 4, the use of these highly porous
materials as fuel cell electrodes is analyzed by preparing
cathodes made by this electrospraying and deposition
technique starting with a liquid suspension with carbon
nanoparticles doped with platinum. The performance ofsuch a cathode as compared with the performance of acathode prepared by a standard (impregnation) technique
is studied in a test fuel cell with controlled gas feeding,cell working temperature and outlet pressure. The platinum utilization (maximum fuel cell power per gram ofplatinum in the cathode) obtained with the electrosprayedcathode is an order of magnitude larger than the platinum
utilization achieved with standard cathodes.
The details of this research carried out at threecomplementary levels (i: theoretical simulations, ii: preparation of granular materials, and iii: demonstration of theirperformance as electrodes) are presented in the following
Sections 2–4. In Section 5, the relations between thesethree research lines are discussed.

2. Monte Carlo simulations of granular deposit
formation
2.1 Model description
The growth of a granular material from the depositionof nanopowders (aerosol particles in the surrounding gas
phase) comprises several steps: particle arrival, particle
attachment to the deposit and deposit re-structuring. Eachstep is governed by some distinctive mechanisms. Thus
the particle arrival is affected by the particle dynamics
above the deposit. Particle attachment depends on particle
arrival velocity and on the intensity of the forces between
the deposit and the impinging particle (see for instance
Walton, 2008). Moreover, deposit restructuring linked tothe coagulation, sintering and compaction of the deposit iscontrolled by particle coalescence dynamics which isstrongly dependent on temperature and on the presence ofvapors that may condense between the particles. One may
try to model the formation of a granular material including
all these phenomena, but it is clear that such a model would
require the determination of a large number of parameters
measuring the importance of the different physical mechanisms controlling these three steps. Instead of trying tomodel all these details, one may focus on the mechanisms
which play a major role and disregard all the other effects.
Following this approach, a Monte Carlo (MC) method
has been implemented to simulate the motion of particles
above the deposit and the other two effects have been
oversimplified by assuming a complete passive deposit.
Thus in this model (Rodriguez-Perez et al., 2005, 2007;
Tassopoulos et al., 1989) once a new particle reaches thedeposit, this particle remains attached at the touching location and does not move anymore. This assumption (absenceof rebounding and re-entrainment of particles in the gas) is
valid when the kinetic energy of the impacting particle is
low with respect to the potential energy of the interaction
between two particles in contact or when a kind of gluecoats the particles enhancing their sticking. Moreover,deposit restructuring is disregarded and the particles
incorporated into the deposit keep their original shape.
This frozen deposit assumption is valid when the working
temperature is not elevated (i.e. is much lower than thefusion temperature) and the ambient pressure is not too
high, in such a way that particle coalescence within thedeposit is precluded.
Under these simplified assumptions, the only remaining

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factor to control the deposit formation (i.e. the deposit evolution and the final structure of the resulting material) is the
dynamics of particle arrival to the collecting surface.
In the MC simulations, time and space are discretized,
depicting the particle motion at intervals of time τ and theparticle position on a cubic lattice of size a (which coincides with the particle diameter). That is, τ is the characteristic time for a particle displacement equal to the particle
diameter a. Therefore, time and space are measured inunits of τ and a, respectively. A spatial domain with asquare base L × L (i.e., na × na) and periodic boundary
condition on the lateral walls is used.
The concentration of particles in the gas phase isassumed to be small and thus the motion of each particle is
not affected by the other aerosol particles. In this case, thedeposit growth is due to the successive arrival of uncorrelated particles and can be modeled by a sequence ofindependent events, each due to a single particle. Thus one
can introduce a particle at a random position over the topmost height of the deposit and follow its motion until either
the particle moves far away from the deposit (escaping
from capture and being carried by the gas) or it touches thedeposit and attaches there. The MC model simulates the
motion of one particle after another, depicting the evolution of the deposit growth evolution.
The motion of an aerosol particle in a gas is split into
two distinct contributions:Fig. 1216• A deterministic motion that can be due to gas advection, inertia, sedimentation or any phoretic motion(thermophoresis, photophoresis, ...). This convective
motion is characterized by a mean value of the particle velocity, v. This mean (ensemble-averaged) velocity would be taken time- and space-independent andwith the same value for all incoming particles.
• A random motion superimposed on the mean particle
motion and due to a stochastic transport process(Brownian diffusion, eddy diffusion, random fields ...).
Thus in a reference system moving with the mean
velocity v, each particle performs a random motion
with the mean square displacement increasing linearly with time, ∆r 2 = 2nd Dt, Einstein (1905), wherend stands for the space dimensions (nd = 2 in a two-­
dimensional space, and, nd = 3 in the three-dimensionalcase). The importance of this random motion is measured by the diffusion coefficient, D.
In this way, the assumption of independent aerosol particles (i.e. that the motion of each particle is not affected by
the other aerosol particles) can be relaxed considering thatthe aerosol cloud generates a mean field (as in the case ofelectrically charged particles that will be considered in thefollowing section) plus a random force (due to the incessant temporal and spatial changes on the distribution ofparticles inside the cloud). The mean field affects thedeterministic motion of each individual particle (that is,

Two-stage Monte Carlo simulation. Deterministic stage and random-walk stage (with nrw consecutive
probabilistic walks).

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the characteristic convective time, τ = tconvective = a/v.
• The random walk stage. The diffusive time tdiffusive isof the order of Pe times the convective time τ. Eachtime step, the particle then undergoes nrw consecutive
probabilistic walks, each with the same probability pof moving to any of the 6 first neighboring sites in thediscretized space (and a probability for remaining at
its current site given by q = 1 – 6p), with
⎛ 6⎞=
nrw int ⎜+ 1⎟⎝ Pe ⎠

Fig. 2

Sketch of deposit growth on an attracting surface.
Particle arrival by deterministic + diffusive transport.

the value of v), whereas the random contribution adds tothe particle Brownian motion (or even plays the major rolein the random particle motion). These Monte Carlo simulations do not represent the motion of aerosol particles along
the whole particle path but the arrival of the particle toform the granular deposit, in this sense v stands for the(ensemble-averaged) arrival velocity which results fromthe gas-aerosol interactions and by the presence of otherfields acting on the particle dynamics.
Therefore, the model incorporates three independent
variables: a, v, and D. Once the direction of the particle
velocity is given (perpendicular to the collector in our
simulations), the particle speed, v, together with the characteristic length (the particle diameter, a) and the diffusion
coefficient (D) can be combined to form the Peclet dimensionless number
va
Pe =
(1)
D
This Peclet number, Pe, measures the relative importance of the mean particle motion with respect to the random particle motion. The limit Pe→∞ corresponds to aballistic behavior of the aerosol particles moving withconstant speed v and vanishing diffusion whereas the
opposite case, Pe = 0, accounts for the pure diffusive limit(v→0). Indeed, the Peclet number can be written as theratio of the characteristic times associated to the two contributions to the particle motion,(3)

The characteristic diffusion time is of the order of thecharacteristic time for each single random motion. As in
this two-stage scheme, there are nrw single random steps
for each time step τ, it results tdiffusive≈ τ/nrw≈ τPe. Thus thevalue of the probability p is chosen to provide the value ofPe; that is p = 1/(nrwPe).
The MC simulation starts with a flat and clean collecting
surface at the lower boundary of the computation domain.
The simulation scheme based on these two stages is implemented to trace the motion of one aerosol particle until
either it escapes from the computation domain or it touches
the deposit (the collecting surface or another particle thathas already being fixed to it). In the first case, the particle
escapes and in the second case the particle becomes part ofthe deposit contributing to the deposit growth. After that,a new particle is introduced at a random location on aplane parallel to the collecting plate and located one site
above the uppermost location of the deposit.
It can be shown (see for instance Tassopoulos et al.,1989 or Rodriguez-Perez et al., 2005) that this computation scheme corresponds to the discrete description of an
ensemble of diluted aerosol particles whose number density (number concentration per volume), np, is governed bya convective diffusive equation (in dimensionless variables, measuring time in tconvective units and distances inunits of the characteristic length, a, and therefore, velocities in units of the mean particle velocity)Pe∂ np+ Pev ⋅∇np = ∇ 2np∂t(4)

with Pe representing the ratio of characteristic times given
by Eq. (2).

(2)

2.2 Structure of granular (powdery) deposits formedon attracting surfaces

With the characteristic convective time given by tconvective= a/v, and the characteristic diffusive time by tdiffusive = a2/D.
On this discretized space, the two contributions to theparticle motion are simulated by two stages (Fig. 1):• The deterministic (ballistic) stage. Each time step, theparticle moves to the nearest neighboring site in the
direction normal to the collecting surface. Therefore, τ is

For an attracting surface, the mean particle velocity v is
directed towards the collecting surface and the relative
intensity of the surface attraction with respect to particle
diffusion is given by the Peclet number Pe. The sequenceof particles driven to the attracting surface forms a granular deposit on this surface (Fig. 2) whose main structuralfeatures were derived by Rodriguez-Perez et al. (2005,

Pe =t diffusive
t convective

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2007) and Castillo et al. (2010). A computer drawing of thestructure of the granular deposits is given by Fig. 3a showing the lateral view of a deposit for a low value of thePeclet number (Pe = 0.1) with the grey intensity decreasing
with the depth of the field in the figure (for illustration
purposes, only the upper half of the deposit is shown). On
the other hand, Fig. 3b shows the upper view of the samedeposit characterized by bunches of particles forming arough surface on the scale of the particle size. Moreover,Figs. 4a & b depict the lateral and upper view, respectively, of a deposit formed by particles whose motion ischaracterized by Pe = 1. Lastly, Figs. 5a & b correspond to
Pe = 100. In all these figures, the MC domain has a squarebase of 512 × 512 cells and the simulation is stopped when
the same maximum deposit height (hmax = 1024 a) is reached.
It becomes clear that ballistic-dominated deposition (large
Peclet numbers, Figs. 5) leads to compact deposits with arough patched surface. However, diffusion-­controlled deposits (low Peclet numbers, Figs. 3) are tree-like and218

fluffy, with a very porous bulk structure formed by open
structures and a highly branched surface.
The deposit bulk structure can be analyzed by determining the mean density (the occupation number or relative number of space cells occupied by particles within thedeposit) at different heights, ρ(h). To achieve representative values, the density at each height is averaged over 10
deposit simulations performed with the same Peclet number. It turns out that the bulk of the granular deposit
becomes layered in three different regions (Fig. 6):• A bottom layer (near-wall region) whose structure isaffected by the presence of the flat collecting surface.
Here, the density decreases continuously from a highsurface cover at the collecting plate down to the value
at the next layer.
• A middle layer (consolidated region) characterized
by a plateau with a constant mean density where newparticles can no longer arrive from the surroundinggas.

Fig. 3a, Lateral view of the granular deposit with the grey intensity decreasing with the depth of the field. HerePe = 0.1, L = 512a, hmax = 1024a. b, Upper view of the same deposit shown in Fig. 3a.

Fig. 4a, Lateral view of the granular deposit with the grey intensity decreasing with the depth of the field. HerePe = 1, L = 512a, hmax = 1024a. b, Upper view of the same deposit shown in Fig. 4a.

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Fig. 5a, Lateral view of the granular deposit with the grey intensity decreasing with the depth of the field. HerePe = 100, L = 512a, hmax = 1024a. b, Upper view of the same deposit shown in Fig. 5a.

Fig. 8Fig. 6 Density profile (averaged over 10 deposit simulations
performed with the same Peclet number) showing
the three-layer structure of a deposit for Pe = 0.1, thedeposit height h measured in units of cell size, a.

Fig. 7

Density profile (averaged over 10 deposit simulations)for Pe = 0.1 and different maximum heights hmax
(measured in units of cell size, a). The arrival of newparticles at the deposit (increasing hmax) enlarges the
thickness of the consolidated region where the meandensity is almost constant and time-independent.

• A top layer (active region) open to the ambient air andstill active for new particle attachment.

Density profile for the same maximum heighthmax = 400 (measured in units of cell size, a), and different Pe numbers.

The size of the bottom layer depends on the Peclet number, whereas the thickness of the active regions increases
slightly with time. Some properties of these two extreme
regions were provided by Rodriguez-Perez et al. (2005,2007). Here we will focus on the features of the consolidated region. The thickness of this central consolidated
region depends on the deposition time. In Fig. 7, the density profile (averaged over 10 deposits) for Pe = 0.1 is represented, depending on the maximum deposit height, hmax
(measured in units of cell size, a). It becomes clear that thearrival of new particles to the deposit (increasing hmax)
enlarges the thickness of the consolidated region where themean density is almost constant and time-independent, as
it was already obtained by Houi and Lenormand (1984).
In Fig. 8 the mean density profile is depicted for deposits grown at different Peclet numbers up to the same maximum height, showing that the consolidated region
becomes more porous (and the depth of the active region
thickness increases) as Pe decreases. When the tendencyof the particles to move toward the collecting surface isreduced, a more porous deposit with a larger active surface
is obtained.

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A detailed analysis of the granular deposits for different
Pe numbers leads to correlation of the mean density of theconsolidated region with the particle Peclet number, Pe(Fig. 9), resulting in Pe  (=Pe) ∞ 1 + 0 
Pe 


−B

(5)

where ρ∞ stands for the maximum occupation fraction andPe0 is a normalizing Peclet number. In our simulations
ρ∞ = 0.302; Pe0 = 4.8; B = 0.52

(6)

The fitting expression Eq. (5) has a general application
whereas the numerical values of the fitting coefficients
given in Eq. (6) indeed depend on the model features.
Thus, for on-lattice models like the one used here, thelimiting occupation fraction for ballistic deposition isρ∞ = 0.302. However, for off-lattice models (when the particle location is not restricted to the lattice cells but can be
any point in the computational space), a packing density(normalized with respect to the maximum density of fully
packed spheres) ρ∞ = 0.17 is achieved (Jullien and Meakin,1987). Moreover here, ρ∞ accounts for the relative numberof occupied cells, but for comparison with the mass density of actual deposits one has to take into account thefraction of the cell occupied by a particle, which in the caseof a spherical particle in a cubic lattice corresponds to π/6.
Moreover, the value of Pe0 depends on other model features such as the space dimension or the angle between themean velocity and the collecting surface (taken as perpendicular directions here).
Note that in the case of a material with fractal dimension DF , when looking at a cubic volume V of side 2R built
on any point inside the material, the mean occupation
fraction would depend on R in the form=
ρ (Pe, R)

N occupied (Pe, R)
R DF
∝ 3
N (R)
R

(7)

where Noccupied is the number of occupied cells, and N is thetotal number of cells in the volume V.
Based on Eq. (7), the fitting expression (5) defines acharacteristic length
RPe = 1 +

Pe0
Pe

(8)

such that the granular deposit looks fractal at length scales
smaller than R Pe, (measured in units of the particle size, a)with the mean density depending on the volume as specified by (7). However, for larger volumes, the fractal structure becomes embedded in V, with the mean occupation
fraction becoming independent of the size of V as indicated by Eq. (5). R Pe is thus a cut-off distance for the fractal structure of the consolidated deposit. In the absence ofparticle diffusion (ballistic limit), the cut-off distanceshrinks to the particle size whereas in the opposite (pure220

Fig. 9Mean density in the consolidated region of the deposit
as a function of Pe.

diffusion) limit, the whole deposit remains fractal at all thescales. The existence of a cut-off length for the fractal
structure was also proposed by Nagatani (1989) in thecontext of particle aggregation.
Thus diffusion dominates on the short distances being
responsible for the fractal structure of the deposit on thesmall length scales up to R Pe, whereas convection introduces the cut-off distance R Pe (which increases as diffusion becomes more and more important) beyond which aconstant mean density is achieved and the fractality is
swept off.
Therefore, the numerical value of the exponent B in Eq.
(5) is related to the fractal dimension induced by diffusion
at the short scales. For diffusion-limited deposition, adeposit in the pure diffusive limit (Pe = 0) has a fractal
dimension DDLD = 2.5 (Tolman and Meakin, 1989), and itturns out thatB = 3 – DF ≈ 3 – DDLD

(9)Eq. (5) provides the density of a granular deposit as afunction of the particle dynamics in the gas over the collecting surface, with the dynamics characterized by thePeclet number. On the base of these simulations, one canprepare materials with a prescribed bulk density or meanporosity and with a tailored structure by controlling theway the particles arrive at the attracting surface. Also,layered materials formed by the superposition of layerswith a different mean density can be prepared by modifying
the particle dynamics during different timed intervals.
This result has a broad application. For example, Elmøe
et al. (2009) carried out a simulation of particle capture byfilters and found out that the dusty layer growing over thefilter has a mean density which is well fitted by Eq. (5).
Indeed, the MC simulation described here is free fromany constraining hypothesis, and thus Eq. (5) is expected
to be valid in any dusty layer created by accumulation offine particles in the absence of erosion or deposit consolidation. The simulation opens doors for the design of controlled experiments dealing with material processing from

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Fig. 11

Fig. 10Sketch of the experimental set-up. The liquid suspension in the syringe is pumped through the needle anda potential difference between the metallic needle andthe collector substrate is maintained. Evaporation of thedroplets formed in the electrospray leaves dry charged
nanoparticles which are attracted by the substrate.

aerosols. One of these doors is explored in the following
section.

3. Granular materials built from the depositionof an electrosprayed liquid suspension
3.1 Electrosprayed liquid suspensions
The simple model underlying the MC simulations
described in the previous section shows the trends forcontrolling the deposit structure and indicates several
ways to prepare granular materials from nanopowders
with a tailored morphology depending on their final use. A
step forward in nanomaterial research will consist of theperformance of experimental studies that could confirm
these theoretical predictions. To achieve this goal, an
experimental set-up (sketched in Fig. 10) was implemented
to generate nanoparticles in a gas that are later driven
towards a collecting surface. In this study, a standard catalyst ink commonly used for preparing electrodes that are
valuable for proton exchange membrane fuel cells(PEMFC) was used. The inks are constituted by a catalyst
supported on carbon nanoparticles (Pt/C: 10 wt% Pt on
Vulcan XC-72R) dispersed in a liquid solvent (ethanol 96%v/v, Aldrich) and an ionomer (Nafion® 5 wt% in lower aliphatic alcohols and water). The Nafion® loading was fixed
to 30 wt% in the solid fraction (fraction of dry mass of
Nafion® on the dry mixture of Nafion® and Pt/C). The
electrical conductivity of the liquid suspension was

Liquid electrical conductivity dependence on the concentration of carbon nanoparticles in the suspension.

measured as a function of the concentration of carbon
nanoparticles (Fig. 11), showing that the electrical conductivity can be well fitted by a linear dependence on theconcentration of carbon nanoparticles.
The electrospray technique (Barrero and Loscertales,
2007, Jaworeck and Sobczyk, 2008) is used to generate
almost monodispersed sprays of small electrically charged
droplets from this liquid suspension. The liquid suspension is ultrasonically dispersed for at least 2 hours before
the electrospray deposition is started. Then, a syringe
pump (KDS 100) drives the liquid suspension through astainless steel needle (inside diameter of 0.75 mm) at aconstant flow rate Q. Moreover, by means of two DC
high-voltage power supplies (Bertan 225-30R andSpellman MM15P2.5W, respectively), a high voltage difference is applied between the metallic needle (kept at aconstant voltage Vn) and the flat collecting plate (at a voltage Vp) respectively, with this plate located some distanceaway from the needle tip. The electric charge passing
through the needle and the charge collected by the plate
are measured by two ammeters (Isotech IDM67) inserted
in the circuit lines of the needle and the substrate connections to their respective power supplies.
The electrically conducting liquid in the needle isaffected by the electric field there (Fernandez de la Mora,
2007; Higuera, 2010), which leads to an accumulation of
charges at the liquid surface formed at the needle exit.
Under suitable conditions, the electrical stresses elongate
this surface to form a Taylor cone with a very thin jet
emerging from the cone tip (Fig. 12). In this cone-jet configuration, the jet is steady and adjusts to the fixed flowrate Q. At some distance away from the cone tip, the jet
breaks up in a spray with droplets much smaller than theneedle diameter forming a cloud of tiny droplets with anarrow distribution of droplet sizes (Fig. 12). The flow rateand liquid properties (conductivity, surface tension, density) determine the characteristic droplet size (Chen andPui, 1997; Fernandez de la Mora and Loscertales, 1994;
Gañan-Calvo et al., 1997; Yurteri et al., 2010). Due to thedependence of the electrical conductivity on the nanoparticle concentration (Fig. 11), a wide range of droplet sizes

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Fig. 13

Fig. 12Composed picture of the electrospray depicting thecone-jet and the electrosprayed cloud together withthe resulting nanostructured deposit. For illustration
purposes, the SEM image of the deposit is enlarged
with a different length scale (given by the horizontal
bar at the bottom).

can be analyzed. These charged droplets evaporate along
their flight in the gas leaving dry charged nanoparticles
which are driven by the electric field towards the collecting surface. The arriving nanoparticles accumulate on thecollector plate and form a structured granular deposit. The
Nafion® covering the nanoparticles facilitates their adhesion to the deposit and reduces particle surface diffusion
after adhesion. Fig. 12 is a composed picture representing
the whole electrospraying process. The cone-jet at the needle exit forms the electrosprayed droplet cloud and the dry
nanoparticles form a nanostructured deposit on the collector plate. For illustration purposes, the deposit image in
Fig. 12 is an enlarged SEM image superimposed on theneedle-electrospray picture with the scale for the SEM
image given by the scale bar at the bottom, whereas the
2-mm bar is the scale for the rest of the picture.
The cone-jet mode remains stable for a range of parameters (Cloupeau and Prunet-Foch, 1994; Li, 2007; Martin
et al., 2012; Noymer and Garel, 2000; Ragucci et al., 2000;
Tang and Gomez, 1996; Yurteri et al., 2010). Roughly,
when the electrical field at the needle tip is weak, the surface accumulation of charges is low and the electricalstresses are not able to comply with the flow rate Q. Then,the cone-jet cannot be maintained in a steady way and thesystem works in a dripping mode with a sparse sequenceof large droplets being formed at the needle tip. The droplet grows by the continuous arrival of liquid pushed by thesyringe pump until the meniscus cannot support the222

Stability domain for electrospraying a catalytic ink
in the cone-jet regime when a voltage is applied to
the needle but the substrate is connected to ground.
The electrical conductivity of the catalytic ink was
5.77 × 10 –4 S m–1 and the needle-substrate distance
was fixed at 3.5 cm.

attached droplet (as large as the needle diameter) which
detaches from the needle and a new dripping cycle starts.
Moreover, for high enough voltage differences, the electricfield at the Taylor cone is quite large, the cone-jet becomes
unstable and the electrospray evolves to a more complex
configuration (Gu et al., 2010; Kim et al., 2011): oscillatorymode, multiple-jet mode or electrical discharges in thesurrounding gas, among others.
The parameter space where the electrospray works inthe steady cone-jet mode is one of the issues that must be
investigated in advance for determining the range of flow
rates and the corresponding applied voltages for which theliquid suspension can be electrosprayed in a regular andcontinuous manner (Martin et al., 2012). Fig. 13 shows thesteady cone-jet domain of a catalyst ink (whose electricalconductivity was 5.77 × 10 –4 S m–1 and for a needle-­
substrate distance fixed to 3.5 cm) when a positive voltage
is applied to the needle while the collector plate is connected
to ground. In this cone-jet mode the electrospray induces
primary droplets and smaller satellite droplets with mostof the electrosprayed liquid mass contained in the primary
droplets. To obtain the cone-jet mode domain given in Fig.
13, the different electrospraying regimes have been identified by observing the liquid meniscus at the needle tip. The
liquid shape at the needle exit was visualized using a CCD
camera (Panasonic AW-E600E) coupled with an opticalzoom (Optem 70XL). Due to the known hysteresis phenomena linked to the cone-jet stability, the voltage range
leading to a stable cone-jet was determined, startingalways with a formed cone-jet. Therefore, the resulting
range of voltages for a stable cone-jet corresponds to thewidest possible range. Starting with a stable cone-jet
within the stability island, the applied voltages were either
decreased or increased until the cone-jet became unstable,
giving rise to the dripping mode or the multijet mode,
respectively.

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In a recent work (Martin et al., 2012), the stable cone-jet
domain was extended by keeping the collector under anegative voltage (and the surroundings to ground). Larger
flow rates can be achieved with this double polarization
configuration and the electrospray remaining in a stablecone-jet mode.
Outside of this cone-jet domain, the nanoparticles arriving at the deposit would have a broader distribution ofsizes (due to the uneven atomization process and the subsequent coagulation of the nanoparticles within the original liquid droplets when drying), and each nanoparticle
will have a different dynamics when approaching the collector (due to the dependence of the electrical mobility on
size and charge of the particle). Therefore, to compare themorphology of the nanostructured deposits with the results
obtained with the MC simulations described in Section 2,
the electrospray should work in the steady cone-jet mode.
The main objective of the electrospraying process is tocollect all the charged nanoparticles emitted by the needle
on the substrate and to form, after the solvent evaporation,a porous deposit consisting of the catalyst particles. The
efficiency in the capture of the electrosprayed particles
may be substantially improved if an opposite voltage withrespect to the needle voltage is applied to the collector
substrate. In the double polarization scheme depicted inFig. 10, the charged particles are forced by the electricfield to deposit preferentially over the substrate, thus
reducing the leakage of flying nanoparticles and improving the performance of the deposition process. Moreover,the electrospray cone-jet domain may be substantiallyenlarged by proper selection of the voltage at the collecting
plate, and a noticeable increase in the flow rate range forelectrospraying in the cone-jet mode can be achieved(Martin et al., 2012). Thus, in summary, the double polarization can be used to control the electric field at the needletip (which indeed is the key factor for achieving a stablecone-jet electrospray) as well as the electric field at thecollecting plate (which determines the particle motion overthe deposited material and thus the corresponding particle
Peclet number). The Peclet given by Eq. (1) becomesPe=

va qE p a b qE p a
=
=
D
kT b
kT

(10)

where b is the particle mobility, q the particle charge, Ep
the electric field at the collecting plate, k the Boltzmann
constant and T the gas temperature. Eq. (10) indicates that
Pe is the ratio of the particle electrical drift to the intensityof the particle thermal motion, being proportional to theelectrical field over the collecting plate.

3.2 Morphology of the electrosprayed catalytic
layersAs expected from Eq. (10) and from the results of the MC

simulations given in Section 2.2, the nanostructure of the
granular deposit depends on the suspension properties, on
the mass flow rate Q, and on the voltages (Vn and Vp) applied.
In all the cases presented in this section, the electrosprayed deposits were carried out at a needle-substratedistance of 3.5 cm and a voltage drop of 7 kV between theneedle and the collector plate (+5.5 kV voltage applied at
the needle with the collector kept at –1.5 kV). This double
polarization configuration has two main advantages:• It reduces the particles losses by setting the collector
plate to a negative voltage with respect to ground,then favoring the deposition of the catalyst particles
on the electrode instead of on the surroundings which
are to ground potential.
• Larger flow rates can be achieved (beyond those indicated in Fig. 13) with the electrospray remaining in astable cone-jet mode (Martin et al., 2012).
Fig. 14 provides some SEM images of the depositedcatalyst layers with the same deposit accumulative mass
(same final ultra-low Pt loading, 0.01 mgPtcm–2) obtained
for several flow rates and different electrical conductivitiesof the catalyst ink (note that the liquid electrical conductivity increases with the concentration of nanoparticles in theoriginal liquid suspension as shown in Fig. 11). The micronbar in Figs. 14a–d and f is 20 μm in length, whereas inFig. 14e, it corresponds to 500 nm. Moreover, Fig. 15
shows a diagram of the flow rates and conductivities of thecatalyst ink that give rise to the different morphologies
depicted in Fig. 14.
Each SEM image in Fig. 14 is representative of a type ofdeposit. The morphology of the catalyst layer can be classified as a fractal-like structure (a), accumulation of patchedclusters (b), compact deposits based on a fractal structure (c)and compact deposits formed from patched clusters (d).
Thus Fig. 14a shows a fractal-like deposit characteristicof low Peclet numbers which are obtained for low-conductivity suspensions electrosprayed at moderate flow rates (♦points in Fig. 15). Moreover, Fig. 14e shows a closer viewof the same deposit.
The fractality of the granular deposit is better seen in
the general views a) to d) than in the closer views such ase). In Fig. 14a there is no evidence of any dominant macroscopic length because the corresponding characteristic
length R Pe (see Eq. 8) is larger than the picture size (compare with the simulation shown in Fig. 3b, corresponding
to Pe = 0.1, which leads to R Pe ≅ 50). Figs. 14b to 14dshow large and rather homogeneous clusters where fractality is confined to much smaller sizes (see Figs. 4b and 5b,
corresponding to Pe = 1 and Pe = 100, respectively, leading to R Pe ≅ 5 and R Pe ≅ 1, respectively).
These fractal-like structures (Figs. 14a and e) are composed of clusters (of a few catalyst particles each) with acharacteristic size of approximately 100 nm and arranged
in a dendritic way. This is the most appropriate type of223

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Fig. 14

SEM micrographs of the morphologies of the electrosprayed deposits classified as: a) fractal-like, b)
patched clusters, c) and d) compact structures. Moreover, e) shows a closer view of the building blocks
forming the fractal-like deposits, whereas f) shows the carbon paper substrate used as deposition
substrate. All the electrosprayed deposits were carried out at a needle-substrate distance of 3.5 cm, avoltage drop of 7 kV (+5.5 kV voltage applied at the needle and the collector kept at –1.5 kV) and thePt loading was 0.01 mgPtcm –2. The micron bar in figures a)–d) and f) is 20 μm in length, in e) the barcorresponds to 500 nm.

catalytic deposit for PEMFC electrode preparation (due tothe large active surface area). The small size of the catalyst
clusters causes most of the catalyst to be exposed to thesurface and available for the reactant gas. Besides this, thedendritic arrangement of the catalyst clusters results in ahighly porous deposit with an enhanced permeability andincreased active surface. One can expect that all thesemorphological properties of the granular material lead tohigh catalyst utilization when used as a catalyst layer.
On the other hand, Fig. 14b shows a deposit formed bypatched clusters of thousands of single particles (◇ points
in Fig. 15). These patched clustered deposits (composed oflarge aggregates of catalyst clusters with sizes in the
micrometer range) appear for moderate Peclet numbers(larger flow rates than those for fractals deposits). Here,224

the granular material is more compact, leaving void spaces
between the substrate fibers which diminish the effective
surface of the catalytic layer. There is a significant amountof the catalytic material located in the inner regions ofthese large clusters that may lead to poorer catalyst utilization. Furthermore, Fig. 14c & d are compact deposits(with the arriving particles compacting on the initial carbon paper which is shown in Fig. 14f) representative oflarge Peclet numbers (achieved when the flow rate is large
enough, see □ and △ points in Fig. 15). These compact
deposits result from an incomplete evolution of the droplets during their flight toward the substrate. The droplets
do not have enough time to evaporate and Coulomb fissions (Maxwell explosions due to the accumulation ofelectrical charges on the liquid droplet whose repulsion

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Fig. 15 Two-parameter diagram with the different types ofdeposit structures shown in Fig.14, depending on theelectrical conductivity of the catalytic ink and the flow
rate. Symbol ♦ corresponds to type a) fractal-like, ◇ isfor b), □ for c) and △ for type d) deposits.

overcomes the surface tension) are not in effect to reducethe droplet size. Therefore, the deposit is formed from wet
suspensions with the ethanol evaporating later on. Notethat the Monte Carlo simulation described in Section 2
considers that any particle reaching the deposit attaches tothe touching position. This condition is not fulfilled in thecase of collected droplets carrying a dry residue. Therefore,
the results derived from these simulations cannot bedirectly used when complete drying does not occur during
the droplet flight but the droplet evaporates after arrival.
When the Peclet number associated to the arriving droplets corresponds to a fractal-like deposit, the resulting dry
compact deposit is as the one depicted in Fig. 14c, withfractal patches formed on the original fibers. Lastly, when
the droplet Peclet number corresponds to a clustereddeposit, the structure of the dry deposit is depicted by Fig.
14d, with denser deposits on the fibers leaving larger voids
between them.
The diagram depicted in Fig. 15 represents the region of
the parameter space (electrical conductivity versus flow
rate, for a constant voltage drop and a fixed needle-plate
distance) leading to fractal-like structures (with the limitsof this fractal-like region depicted by the dashed line). The
deposit structure is different on each side of the dashedline. For a given electrical conductivity of the catalytic
suspension (see Fig. 11), there is a threshold flow rate
below which fractal-like structures are formed. Flow rates
higher than this threshold value give rise to patched cluster
structures or compact structures. The diagram shows thatthe range of flow rates leading to fractal-like structures
expands as the electrical conductivity of the suspension
decreases until a critical electrical conductivity is reached.
For even lower electrical conductivities, the range offractal-like deposits is substantially reduced. Moreover,beyond the fractal thresholds and above the critical electrical conductivity, the deposit structure is based on patchedclusters. Finally, for electrical conductivities lower that theFig. 16 Cross-sectional SEM micrographs of catalytic deposits
electrosprayed over a carbon paper substrate (a) fractal-like structures for a flow rate Q = 0.2 ml h–1 and (b)patched clustered deposit obtained for Q = 0.5 ml h–1.
Same platinum loading (0.1 mgPtcm –2) and same
micron bar (300 μm) in both images.

critical value, the fractal deposit becomes first compact
based on fractals and later on compact based on patchedclusters as the flow rate increases.
When the needle-substrate distance is increased sufficiently, the ethanol has enough time to evaporate along thedroplet flight and only dried base deposits (type a or b) areachieved. Work to obtain a complete diagram of the deposit
microstructure depending on several controlling parameters is currently underway.
On the base of the knowledge gained with these experiments, the suspension with an electrical conductivity of
5.77 × 10 –4 S m–1 was electrosprayed under the same conditions (3.5 cm distance between needle and collector, anda voltage drop of 7 kV) for longer time periods on a carbon
paper collector with two different flow rates: a flow rate
Q = 0.2 ml h–1 lying in the range of fractal deposits, and alarger flow rate Q = 0.5 ml h–1 beyond that domain andleading to patched cluster deposits (see Fig. 15). A squarecarbon paper with a dimension of 5 cm 2 was used as a
substrate. The mass of deposited nanoparticles was thesame in both cases (leading to the same Pt loading of225

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0.1 mgPtcm–2 in the catalytic layer). Fig. 16 shows SEM
lateral views of the respective catalytic layers depositedover the carbon paper substrate.
The SEM image of the deposit made at a flow rate of
0.2 ml h–1 (Fig. 16a) reveals its fractal character as it isformed by dendritic trees approximately 300 μm in height,
and resembling very much the MC simulated deposits for
low Peclet numbers (see Fig. 3a). However, the deposit
made at the higher flow rate of 0.5 ml h–1 (beyond thefractal threshold in Fig. 15) exhibits a more compact
structure as it is based on the growth of patched clusters
that lead to globular structures after a long deposition time
(Fig. 16b). The same amount of material was deposited inboth cases (Figs. 16a and b). Therefore, at the higher flowrate (Fig. 16b) and as consequence of the compactness, thethickness of the deposit was reduced to about one-halfwith respect to the deposit shown in Fig. 16a.
The porosity for these deposits has been estimated as
the proportion of the void volume to the total volume of thecatalytic layer (Baturina and Wnek, 2005; Gasteiger et al.,2003). Despite the difference in the thickness of the catalyst layer, the porosity is very similar in both cases. For thefractal deposit made at the lower flow rate (Q = 0.2 ml h–1,
Fig. 16a), a porosity of 98% was measured, whereas themore compact deposit (Q = 0.5 ml h–1, Fig. 16b) has a 95%
porosity (thus, the occupation fraction or mean density
was doubled in the second deposit as it becomes clear fromthe reduction in the deposit height). In any case given theirhigh porosity, both types of deposits will present similar
mass transport resistances in the gas phase although, as
was indicated before, the catalyst utilization will be lower
in the compact deposit because a significant amount of thecatalyst is incrusted inside the patched cluster and is thus
unavailable for the reactants in the gas.
It should be mentioned that these values of material
porosity are significantly higher than those reported in theliterature for catalyst layers prepared by other conventional techniques. Thus, for the decal method (Gasteiger etal., 2003) and the air-brush spray technique (Ihonen et al.,Table 1

2002), porosity values in the range of 60% and 30%,
respectively, have been obtained for catalyst layers withloadings close to 0.1 mgPtcm–2. Using the electrospraytechnique, Baturina and Wnek (2005) reported a porosityof 84% for a similar catalyst loading (0.09 mgPtcm–2).
To complete the analysis, the surface distribution of
the catalyst and the ionomer was determined by energy-­
dispersive X-ray spectrometry (EDX) for the fractal-likecatalytic layer presented in Fig. 16a. Fig. 17 shows the
EDX spectrum with the elements detected in the sample sur­face corresponding to the catalyst (Pt/C) and the Nafion®
ionomer (sulfonated tetrafluoroethylene). Table 1 provides
the results from a local quantitative analysis of the catalytic layer shown in Fig. 16a, measured at different locations
on the top surface of the material. No appreciable com­position differences on the surface of the catalytic layer
were observed, indicating that the electrospray process
occurs in a spatially uniform manner (same radial distri­bution). This means that in the electrospray phase, the consti­
tuents of the catalyst ink are homogenously distributed andthere is no accumulation of a component in any particularregion within the electrospray. Therefore, the atomization-­
deposition process maintains the homogeneous distribution

Fig. 17

EDX spectrum of the fractal-like deposit shown in
Fig. 16a.

Quantitative analysis of the elemental composition corresponding to the EDX spectra taken at different surface locations of the catalyst layer of Fig. 16a
EDX Location

Element composition(wt. %)

226

C

19.70

19.87

19.46

19.76

18.68

18.12

19.60

19.54

19.40

Pt

5.24

4.93

4.81

5.64

5.50

4.76

4.91

5.14

5.41

F

63.93

64.23

64.70

63.60

64.67

66.16

64.22

64.06

63.90

S

1.61

1.64

1.68

1.70

1.80

1.85

1.79

1.76

1.72

O

9.51

9.33

9.34

9.51

9.33

9.11

9.47

9.50

9.57

Jose L. Castillo et al. / KONA Powder and Particle Journal No. 31 (2014) 214–233

of the original liquid suspension. Note that the double
polarization with the collector at an opposite voltage withrespect to the needle is used to focus the charged parti­
cles to the collecting area. Moreover, the main contribution
to the deposit comes from the larger primary droplets as
the tiny satellite droplets carry a small fraction of thenanoparticles in the liquid suspension.
The morphological properties of the deposits discussed
in this section confirm the MC simulations results ofSection 2.2. Fractal and open deposits are obtained when
diffusion dominates the deposition process (low Peclet
number corresponding to a weak electrical field at thecollecting surface in the case of electrosprayed suspensions), whereas the deposit porosity decreases as the relative importance of diffusion decreases (the Peclet number
increases). These results provide a way to prepare materials from powders that have a given consolidated structure.
The main features of this analysis are not restricted to any
deposition mechanism (the electrical drift of charged
particles in the experiments shown here) but have a broad­er application. Indeed, it applies to any other particle-­
dominated transport combined with particle diffusion.
Given the morphology of the materials formed by thistechnique (high porosity and large effective surface area),
they can be used as catalytic layers with wide applications.
Their use as electrodes for PEM fuel cells is discussed in
the next section.

4. Applications. Electrodes for fuel cells
The morphological properties (structural stability, large
porosity, low weight and high active surface) of granularmaterial growth from nanopowders as those shown in Fig.
16 make them suitable for use as catalytic materials. A
small amount of catalyst on the nanopowders composing
the material will be enough to achieve a high catalytic
performance, as the catalyzers on the original powders
will still remain mostly at the active surface of the generated material. These days, the proper manufacture of fuelcell electrodes is one of the areas requiring a high utilization of catalyzers, as Pt requirements strongly affect thedevelopment of these technologies. Indeed, DOE 2007
pointed out that one of the main challenges that has to be
overcome for introducing fuel cells as competitive power
supply devices is to reduce the catalyst loading at the electrodes without compromising the fuel cell performance bymeans of increasing the catalyst utilization (maximum
power output per gram of Pt at the electrodes).
In a Proton Exchange Membrane Fuel Cell (PEMFC)
working with hydrogen and oxygen as reactants, bothgases (in some cases the oxygen diluted in an inert gas
such as nitrogen) enter through different inlet ports (Fig.
18) and are distributed by the gas diffusion layers (carbon

Fig. 18

Schematic of a hydrogen-oxygen PEM fuel cell.

fiber paper or carbon fiber cloth). These gas currents are
kept separate by a Membrane Electrode Assembly (MEA).
The MEA is formed by two porous catalytic materials(acting as electrodes) with a thin membrane (the polymericelectrolyte) between them. Hydrogen is dissociated byadsorption on the Pt at the surface of the anode; the electron in the hydrogen atom generates the fuel cell electricalcurrent, whereas the proton diffuses through the anodeand the electrolyte to reach the cathode surface. On thecathode side, oxygen molecules are also adsorbed on theplatinum dots and the oxygen atoms react with the incoming protons (receiving an electron from the electrode) toform water. Water management is quite important in thesefuel cells as a certain degree of humidity in the MEA is
required to favor the proton transport, whereas flooding of
the cathode would inhibit the adsorption of oxygen andstop the reactive process. To achieve an effective process,the electrodes should be:• Porous materials to facilitate the penetration of thegases.
• Good electrical conductors to allow for the electron
and proton transfer.
• Catalytically active. Thus, a catalyst must be evenly
distributed on the material surface with a very large
effective area available for catalytic reaction.
The materials described in the previous section whichwere generated by electrospraying a liquid suspension
containing Pt-doped carbon nanoparticles fulfill all theserequirements. They have over a 90% porosity (see Fig. 16)
and are good electrical conductors due to the combinationof the carbon nanoparticles (electron conductors) with
Nafion® (proton conductor). Moreover, the Pt dots on the
carbon nanoparticles form a large catalytically active area
not just restricted to the topmost region of the material but
well distributed on the entire surface inside the material

227

Jose L. Castillo et al. / KONA Powder and Particle Journal No. 31 (2014) 214–233

pores. Based on these properties, we used them as thecathode in an MEA and tested their efficiency in a fuel cell
monitored in our laboratory (Martin et al., 2010a, 2010b).
In these MEAs, the electrolyte was a Nafion® 212 membrane compressed between the two electrodes. The ensemble was bonded by hot pressing at a pressure of 5 MPa anda constant temperature of 120°C applied for 2 min. The
electrochemical performance of these MEAs was tested in
a commercial fuel cell hardware accommodating a 5-cm 2
single cell geometry (FC05-01SP Electrochem, Inc.) connected to an external electronic load (Hocher & Hackl
ZS-506). The fuel cell hardware employs machined graphite flow field plates with serpentine flow patterns and copper gold-plated current collectors. The feed gases were dry
oxygen and dry hydrogen supplied by mass flow controllers (Bronkhorst Hi-Tec). Thus the fuel worked in a self-­
humidifying regime.
A reference MEA was prepared with the two electrodes
made using a standard impregnation method with a Pt
loading of 0.3 mgPtcm–2 at the cathode and 1 mgPtcm–2 at
the anode. In a second MEA with the same electrode at theanode, the cathode was prepared by the described electrospray method with an ultra-low Pt loading of only
0.012 mgPtcm–2; that is, a reduction of 1/25 in the amountof Pt with respect to the reference cathode. The electrosprayed electrode was prepared under the conditions to
obtain the fractal material corresponding to the SEM
image shown in Fig. 16a (i.e. a flow rate Q = 0.2 ml h–1, acatalytic suspension with an electrical conductivity of
5.77 × 10 –4 S m–1, a needle-to-collector-plate distance of
3.5 cm, and a voltage drop of 7 kV).
The performance of both MEAs are compared in Fig.
19. Fig. 19a shows the fuel cell characteristic polarization
curve, voltage provided by the device (left vertical axis)
and the resulting power density (right vertical axis) versus
the current density (Martin et al., 2010a, 2010b). Solid triangles correspond to the reference MEA whereas squares
are for the MEA with the electrosprayed cathode. Although
the reference MEA seems to offer a higher performance, it
should be emphasized that the Pt content is 25 times larger
in the reference cathode. Therefore, the electrosprayed
MEA is able to attain 59% of the maximum power density
supplied by the reference MEA but with only 4% of thecatalyst loading on the cathode.
The potential benefits of the electrosprayed catalytic
layer become evident when the catalyst utilization is evaluated. The specific power (fuel cell power per gram of Pt
in the cathode) is represented in Fig. 19b. The maximum
catalyst utilization (referred to the cathode) attained for the
MEA with the electrosprayed cathode was 11.5 kW g–1,
whereas a significantly lower value of 0.78 kW g–1 was
obtained by the MEA with electrodes prepared by a conventional impregnation method. Thus, the MEA with theelectrosprayed cathode achieved a maximum catalyst

228

Fig. 19a) Polarization curve (left axis) and power density(right axis), and b) specific power curve. (▲) reference MEA with a cathode prepared by an impregnation technique and a Pt loading of 0.3 mgPtcm –2,(■) MEA with an electrosprayed cathode and a Pt
loading of 0.012 mgPtcm –2. All measurements werecarried out with dry (non-humidified) H 2/O2 at a celltemperature of 70°C and atmospheric pressure on
cathode and anode exits.

utilization almost 15 times larger than the utilization
reached by the reference MEA under the same working
conditions. This factor of 15 is quite promising for futureapplications.
Note that the catalyst utilization of the electrosprayed
MEA may even be increased if more suitable operating
conditions of the cell are selected. Thus Fig. 20 shows theincrease of the cell performance when the back-pressure at
the cathode and the anode exit lines is increased fromatmospheric pressure up to 1.7 bar overpressure. For theelectrosprayed MEA, a maximum cathode specific powerof 19.1 kW g–1 was attained (although not shown in thisfigure, the performance of the reference MEA also
increases with the fuel cell working pressure, but thisimprovement is rather moderate with respect to the electrosprayed MEA). The resulting platinum utilization iscomparable to that achieved by cathodes prepared by sputtering, a well-established method for depositing ultra-low
Pt loadings. Using these sputtered electrodes, specificpower values between 14 kW g–1 and 20 kW g–1 have been

Jose L. Castillo et al. / KONA Powder and Particle Journal No. 31 (2014) 214–233

Fig. 20 Polarization and specific power curves for the MEA
with the electrosprayed cathode when the back-pressure on the cathode and the anode exits is increased
from atmospheric (■) up to 1.7 bar (●). All measurements were carried out with dry (non-humidified) H 2/
O2 at a cell temperature of 70°C.

reported (Caillard et al., 2008; Cavarroc et al., 2009;
Gruber et al., 2005). However, the sputtering techniquerequires a strict atmospheric control and vacuum conditions that make it quite expensive and difficult to scale-up.
In contrast, the electrospraying method described in thispaper is carried out with a simple and inexpensive experimental set-up (only a pump-needle system and two
high-voltage power supplies), the technique has no vacuum requirements and can be easily scaled-up, making it
an attractive option for the mass-production of electrodes
for the fuel cell industry.

5. Discussion of results and conclusions
The results presented here open a new line of research
for the preparation of granular materials from nanopowders. Nanopowders or nanoparticles can be used as building blocks for making new materials with a prescribed
structure. For deposits formed by monodisperse particles,
a way of controlling the final deposit morphology byadjusting the dynamical behavior of the particles whenapproaching the collecting surface has been shown.
Thus a simple model of particle motion has been used tosimulate the deposit evolution, considering two contributions
to the particle motion: A mean (ensemble-average) determinist arrival velocity v normal to the collecting surface
plus a superimposed random motion characterized by adiffusion coefficient D. The resulting control parameter isthe Peclet number, Pe = va/D, where a is the particle diameter. This Peclet number measures the relative importanceof the deterministic motion to the random contribution.
Thus, the limit of infinite Peclet numbers corresponds toballistic deposition when particles follow straight trajectories normal to the collector. Whereas the opposite limit ofvanishing Peclet number accounts for a pure Brownian
motion. A Monte Carlo simulation has been performed to
track the particle motion and their attachment to the evolving deposit. These simulations have shown that deposits
formed by particles with a large value of the Peclet number(near the ballistic limit) are more compact (see Fig. 5a) but
have quite a rough surface (Fig. 5b). However, for low
Peclet numbers, the deposit presents a tree-like structurewith large voids (Fig. 3a) and its surface is quite roughwith large pores entering deep into the deposit bulk (Fig.
3b). In any case, an analysis of the deposit mean density
allows definition of three different regions in the deposit(Fig. 6). Thus there is a denser region close to the initiallyflat collecting surface where the density changes rapidly
from a maximum value at the deposit bottom until reaching a middle plateau region where the mean deposit density remains constant and independent of the deposit
height. These two regions form the frozen or consolidated
deposit where new particles can no longer be attached. On
top of the plateau regions, there is an active region where
the density decreases from the constant plateau value
down to a vanishing value at the uppermost layer of thedeposit. On this active region, new particles may be incorporated to consolidate the deposit. A detailed analysis of
the plateau region shows that the mean density there
depends only on the Peclet number associated with the
motion of the particles which arrive to form the deposit.
This mean bulk density is given by Eq. (5). This simple
relation is one of the main results of the Monte Carlo simulations because (when the features of the particle motion
are given) it allows the deposit densityt to be known inadvance. In summary, these Monte Carlo simulations haveshown that the morphological properties (bulk porosity
and surface roughness) of a granular deposit can be tuned
by properly adjusting the velocity of the particles approaching the deposit.
On the basis of these theoretical predictions, experiments have been conducted to prepare nanostructured
materials from carbon nanoparticles. These nanoparticles
enter the gas from the atomization of a liquid suspension
using the electrospraying technique (Fig. 10). Thus theliquid suspension is pumped at a fixed flow rate through asyringe where a high voltage is applied. The charges accumulate on the liquid surface and a stable cone-jet can beachieved (Fig. 12) by proper selection of the applied voltage and liquid flow rate (see Fig. 12). When the electrospray works in a steady cone-jet mode, the jet breaks up
forming small liquid droplets. These droplets are charged
and become affected by the externally imposed electricalfield that drifts them towards a collector plate located in
front of the ejecting needle and perpendicular to it. The
evaporation of the liquid along the droplet path leaves dry
nanoparticles which deposit on the collector. The intensityof the electrical field over this collector determines the229Jose L. Castillo et al. / KONA Powder and Particle Journal No. 31 (2014) 214–233

mean particle velocity there, and then the corresponding
Peclet number. Using this technique, nanostructured
deposits with a tree-like structure have been grown. The
scanning electron microscope (SEM) images of the deposits are quite similar to the images of the deposits formed byMonte Carlo simulations (compare the SEM image of thereal deposits shown in Fig. 16 with the simulated deposit
represented in Fig. 3). In general terms, the experiments
confirm the theoretical predictions that denser deposits (ormore porous deposits depending on the requirements) canbe made when the control parameters are properly adjusted.
The accordance of the theoretical predictions with theexperimental results facilitates the preparation of porous
granular materials made from powders. These materials
have a rough surface with large pores that penetrate into
the bulk resulting in a bulk structure of highly interconnected pores. This open structure is especially suitable forapplications requiring a large active surface area as in thecase of catalysis or any surface-activated heterogeneous
reaction. To check the validity of these materials for thesekinds of applications, a granular deposit prepared by theindicated electrospraying technique was used as a cathodein a PEM fuel cell. The resulting material surface can be
tailored to render a high-quality catalytic electrode for use
in a proton exchange membrane fuel cell (PEMFC).
Catalytic suspensions of platinum supported on carbon
nanoparticles (Pt/C) in Nafion®-alcohol solutions electrosprayed over carbon paper were used in an experimental
fuel cell set-up. In previous works, the fuel cell power
density was measured as a function of the platinum loading and the range of parameters was obtained, leading to
optimal platinum utilization for a given fuel cell efficiency(Martin et al., 2010a, 2010b). The tests on a controlled fuelcell have shown that the electrosprayed deposits were able
to reach a fuel cell performance which overcomes the
maximum catalyst utilization achieved with cathodes prepared by state-of-the-art techniques (Martin et al., 2013).
The results for the fuel cell cathode show the validityof the method in a particular case. But the same methodology can be used for other applications. The structure of
the material can be tailored according to the applicationneeds to have a given porosity and surface composition. Moreover, layered or composed materials (with a different porosity or different composition on each layer) canbe prepared by adequate changes in the control parameters (liquid flow rate and applied voltages in the electrospraying technique) which determine the dynamics of theparticles approaching the deposit.

Acknowledgements
This work was supported by research funding agencies in
Spain: Ministerio de Ciencia e Innovación (grant

230

ENE2008-06683-C03-01, and program Consolider-Ingenio
2010 grant CSD2010-00011), and also by Comunidad de
Madrid (project HYSYCOMB, S2009ENE-1597). A collaborative agreement with YFLOW Company (Malaga,
Spain) is also acknowledged. The advice from YFLOW
team, Prof. Ignacio G. Loscertales (University of Malaga)and Prof. Antonio Barrero† (University of Seville) was essential for the electrospray set-up and operation. Moreover, Jose
L. Castillo and Pedro L. Garcia-Ybarra thanks Prof. Daniel E.
Rosner (Yale University, New Haven, CT, USA) and Dr.
AthanasiosG.
Konstandopoulos(CERTH/CPERI,
Thessaloniki, Greece) for many years of fruitful discussions on these topics and Prof. Sotiris E. Pratsinis (ETH
Zurich) for encouraging us to write this paper.

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Author’s short biography
Jose L. Castillo
Jose L. Castillo received an M.Sc. in Physics from Universidad Autonoma de Madrid anda Ph.D. in Physics from UNED. He has been an associate research scientist at Yale
University (Chemical Engineering Department), collaborator at Los Alamos National
Laboratory (Center for Nonlinear Studies, Los Alamos, NM) and sabbatical visitor at
University of Miami (Department of Physics). He is a professor at UNED, member of theeditorial board of the Journal of Aerosol Science, and representative of the Spanish
Aerosol Society at the European Aerosol Assembly. He was president of the Experimental
Science Committee for the assessment of non-tenure university positions at ANECA(National Agency for Quality Evaluation and Accreditation, Spain), and is now an ANECA
deputy director for academic staff evaluation.

Santiago Martin
Santiago Martin received a B.Sc. in physics and an M.Sc. in applied physics (fuel cellresearch) from UNED. He received his Ph.D. thesis at UNED in the applications of electrohydrodynamic spraying for the generation of nanostructured catalyst layers for PEM
fuel cell use.

Daniel Rodríguez-Perez
Daniel Rodríguez-Perez received an M.Sc. and a Ph.D. in physics from UNED. He is asenior lecturer at UNED working, among other areas, in discrete Monte Carlo computer
simulation of growing structures.

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Jose L. Castillo et al. / KONA Powder and Particle Journal No. 31 (2014) 214–233

Author’s short biography
Alvaro Perea
Alvaro Perea received an M.Sc. in physics from Universidad Complutense de Madrid anda Ph.D. in physics from UNED. He is a senior lecturer at UNED, working in the area ofparticle transport phenomena.

Pedro L. Garcia-Ybarra
Pedro L. Garcia-Ybarra received an M.Sc. in physics from Universidad Autonoma de
Madrid and a Ph.D. in physics from UNED, after a predoctoral stay at Université deProvence (Aix-Marseille I, France). He has been a Chercheur Associé at Université deRouen (France), visiting research scientist at Yale University (Chemical Engineering
Department), Universidad Nacional Autonoma de Mexico (UNAM) and University ofCalifornia at San Diego (Center for Energy and Combustion Research). He is currently aprofessor at UNED, after being head of the Fossil Fuels Department at CIEMAT (Madrid).
He is the secretary of the Spanish Section of the Combustion Institute.

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KONA Powder and Particle Journal No. 31 (2014) 234–246/Doi:10.14356/kona.2014013

Original Research Paper

Scalable Production of Nanostructured Particles
using Atomic Layer Deposition †Aristeidis Goulas and J. Ruud van Ommen *1

Department of Chemical Engineering, Delft University of Technology, the Netherlands

Abstract
Core-shell nanoparticles and other nanostructured particles have high potential in applications such as heterogeneous catalysis and energy conversion and storage. However, a hurdle in their utilization is that typically, large
amounts of such nanostructured materials are required. Gas-phase coating using atomic layer deposition (ALD, avariant of chemical vapour deposition) can be used to provide the surface of a particle with either an ultrathin
continuous coating or a decoration of nanoclusters. When carried out in a fluidized bed, ALD is an attractive wayof producing nanostructured particles with excellent scale-up potential.
We demonstrate the fabrication of catalysts by deposition of the active phase (Pt) on fluidized nanoparticles (TiO2
P25) at atmospheric pressure. We show that ALD is a technique that 1) guarantees efficient use of the precursor; 2)
allows precise control of the size and loading; 3) can be used for low and medium loading of catalysts by adjusting
the number of repeated cycles; 4) leads to high-quality (low impurities level) end-products.
Keywords: atomic layer deposition, nanostructured particles, clusters, platinum, titania, catalyst

1. Introduction
In recent years, researchers have proposed a wide range
of novel nanostructured materials for applications such as
catalysis (Canlas et al., 2012; Li and Somorjai, 2010) andphotovoltaic devices (Jancar et al., 2010; Kamat, 2008).
Often, such materials use nanostructured particles asbuilding blocks. In this paper, we will use the term nanostructured particles for particles of at least two materials,
typically a host particle (not necessarily < 100 nm) onto
which a second material is present in some structured way,e.g. as a film or set of clusters with dimensions < 100 nm.
For most applications in catalysis and energy conversion
and storage, large amounts of such materials are required.
Most of the current synthesis routes for nanostructured particles, however, do not take into account the scalability ofthe process. It is not considered whether the synthesis ofsmall amounts of materials in stirred flasks could be taken
to some large-scale reactor to produce commercial amountsof materials. Moreover, the amount of waste produced insmall-scale synthesis typically receives little or no attention.
While for research purposes it is not a problem to produce 100 g of waste to obtain 1 mg of a desired product,†
1*

Accepted: July 29, 2013
2628 BL Delft, the Netherlands
Corresponding author:
E-mail: j.r.vanommen@tudelft.nl
TEL: +31-15-278-2133 FAX: +31-15-278-5006

234

such a ratio is unacceptable at industrial scale. Sheldon(1992) proposed quantifying the efficiency of chemical
processes by the E-factor: the mass ratio of waste to desired
product. Table 1 gives the E-factor for some industry segments. It is clear that nanomaterial production has thepoorest performance by far. If nanomaterials are going to
be widely applied in medicine, energy conversion andstorage, their product throughput will increase to approximately the levels of pharmaceuticals and fine chemicals,
respectively, which will give unacceptable amounts ofwaste. If we do not improve the manufacturing routes fornanomaterials drastically, it will lead to a low public
acceptance and fewer market introductions of products
based on such materials.
One of the reasons why the current synthesis of nanostructured particles is so polluting is that a combination ofsolvents and surfactants is often used, and the produced
concentration of nanoparticles is very low; this yields very
high E-factors. Moving to the gas phase eliminates the useof solvents, and is therefore intrinsically cleaner. Moreover,gas-phase processes are typically easier to scale up whennanostructured materials (Wegener et al., 2011) are concerned, although there are exceptions. For example,
graphene can be more easily synthesized in large amounts
in the liquid phase than in the gas phase (Coleman, 2012).
When producing nanostructured particles in the gas phase,
two basic approaches are possible:(1) Directly synthesizing the nanostructured particles fromprecursors.

©2014 Hosokawa Powder Technology Foundation

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Table 1

Annual product throughput for a typical plant and E-factor comparison for different material classes (basedon Sheldon (2007) and Eckelman et al. (2008)).

Industry segment

Annual productthroughput (log kg)

E-factor

Typical amount of waste(log kg)

Oil refining

9–11

~0.1

9

Bulk chemicals

7–9

< 1–5

8

Fine chemicals

5–7

5–50

7

Pharmaceuticals

3–6

25–1006

Nanomaterials

2–3

100–100,000

6(2) First producing the host or core particles, and thendepositing the second material on them.
The first approach has the advantage of minimizing
the number of steps in the production process; it can beconsidered as an example of process intensification.
Several illustrative examples of this approach can befound in literature (Knijnenburg et al., 2013; Minnermann
et al., 2013; Stepuk et al., 2012). However, it is not always
straightforward to control the obtained morphology, andtuning of parameters might be needed when moving to a
new combination of materials. The second approach—separating particle production and particle decoration—
gives more degrees of freedom. Moreover, it has theadvantage that commercially available particles can beused. It will depend on the individual application whichof the two approaches is preferred. In this paper, we will
focus on the second approach, and especially on its second step: depositing nanostructured material on alreadyavailable particles.
For the well-controlled deposition of material at thenanoscale, a number of approaches are available. Some ofthem are line-of-sight methods, and are therefore not easily applicable to particles; examples are e-beam deposition(Laukaitis et al., 2006) and sputtering (Ferguson et al.,2008). Other methods can be applied to particles, but are
not so easy to scale-up. An example is electrospraying
deposition of nanoparticles (Ellis et al., 2010; Yurteri etal., 2010), which might be useful for pharmaceutics production, but could be cumbersome for applications that
require large amounts of materials. Chemical vapour
deposition (CVD) and similar techniques can be applied
to particles and have a good scale-up potential, but havedifficulty in reaching nanoscale precision. Atomic layer
deposition (ALD) is a modified version of CVD that canachieve such precision. We will discuss it in more detailin the next section.
This paper will discuss ALD as a method of producing
nanostructured particles that is scalable and has a limited
production of waste. We will use the deposition of platinum nanoclusters on titania nanoparticles as an example.

2. Atomic layer deposition for the productionof nanostructured particles
2.1 Atomic layer deposition
Atomic layer deposition (ALD) is a technique that relieson the distinct, consecutive binding of two (or more)compounds in a combined structure under a self-limiting
chemisorption/reaction scheme. ALD presents basic self-­
assembly characteristics (Kim et al., 2009). However, one
can argue whether it fully matches the definition of self-assembly as given by Gates et al. (2005): the spontaneousorganization of two (or more) components to form larger
aggregates by means of covalent and/or non-covalentbonds. Nevertheless, ALD is an inherently rational technique relying on a layer-by-layer (or cluster-by-cluster)
assembly of the deposited materials. Similar to the production of layered composite natural or biomimetic materials
such as nacre (Finnemore et al., 2012), ALD can be con­sidered as a bio-inspired approach for the fabrication of
tailored nanomaterials. ALD proceeds through a sequenceof self-terminated gas-solid reactions (R1 and R 2) that canbe expressed as (King et al., 2007):
R1: [S]:(OH)*y + x(MLn) → [S]:(OH)yMx(L)*n-y + y(HL)
R 2: [S]:(O)yMx(L)*n-y+yH2O→ [S]:(MxOy):(OH)*y + (n – y)(HL)
where S represents the surface of the support particle, y is
the number of active sites, x is the number of metal-ligand
molecules involved in the reaction, n specifies the numberof ligands in the metal-ligand (M, L) precursor complex
and * indicates the location of the relevant active species inthe surface.
Unlike traditional wet-phase or gas-phase deposition(e.g. CVD) schemes, ALD offers digital control of theprocess since the growth of the materials relies on thenumber of repeated cycles rather than on the exposure

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time or concentration of precursors. Moreover, the sub-nm
precision (induced by the use of molecular-sized building
blocks) enables the exact translation of the material design
to an accurately fabricated structure.

2.2 Particle nanostructuring
Despite the foundation of ALD as a technique to growthin, uniform layers of materials (hence its alternative
name atomic layer epitaxy), the technique has also beenused in the deposition of particle clusters during the initial
growth stage (Haukka and Suntola, 1997). This observed
deviation from the ideal character of the technique gave riseto an interest in applications that essentially rely on theutilization of a support material of particulate matter forthe deposition of an active material. There are several factors affecting growth during the initial stages of ALD.
These factors can be divided into three groups as depicted inFig. 1. We will briefly discuss them with respect to the de­position of a (noble) metal on an oxide-terminated surface:(1) Looking at the surface properties of the particulate
support material, surface-termination-related growth
limitations can be the result of the surface density of thereactive adsorption sites (usually in the range of 1–10 OH
groups per nm 2 for oxide supports (Elam et al., 2007)) andof the preferential interaction of the precursor moleculeswith certain types of reactive sites. Additionally, surface
roughness can also affect the growth (Lu and Stair, 2010).
(2) The binding process of the precursor is also important with a number of key factors such as the steric hindrance of the ligand, poisoning of reactive adsorption sites
by contaminants or fragments of the precursor, and thechemisorption kinetics affecting the deposition (Elam etal., 2007; Haukka and Suntola, 1997).
(3) Considering the activation step (usually referring to
the second ALD half-cycle, where the activation of thesurface via the removal of the remaining ligand and therepopulation of the surface with reactive sites takes place),
the interaction of the deposited phase and the support ismainly responsible for a series of events that eventually
result in the formation of bigger clusters. Some of theimportant parameters are the temperature in the deposition chamber, the duration of the dosage times (Feng et al.,2010; Liang et al., 2012), the tendency of metals to minimize their surface energy through the formation of stable
metal-metal bonds, and the dewetting of the oxide-metal
surface due to the significance of lattice mismatch (Lu etal., 2012). Finally, the redistribution of active species
during the oxidation-reduction treatment can be considered as an overall affecting condition (Xie et al., 2012).
ALD line-of-sight independency for the precursor delivery enables the deposition in high-aspect-ratio, complex
topologies, and high-surface-area substrates. The limiting
condition is the presence of a certain surface functionality

236

Fig. 1Island growth dependence on surface-, binding- andactivation-related parameters during the ALD of noble
metals.

to promote material growth by ALD. Ultrathin seedinglayers deposited by ALD (usually 0.2–1.1 nm thick) canfurther enhance the growth in support surfaces that show
slow/inhibited growth behaviour.
So far, ALD has been used in the modification of oxide
supports via the growth of thin layers of oxides, resulting
in the fabrication of particulate support materials that canretain some inherited structural properties of the parent
material (e.g. external surface area) while modifying
others (e.g. acidity, pore size for mesopores, blocking of
micropores, surface functionality, etc.). ALD coverage—
especially in the initial growth regime—is just a fractionof a true monolayer value. An effort to study the monolayer coverage of various oxides on oxide powders showsthat the coverage increases in the order of SiO2/TiO2 < TiO2/
SiO2 < Al2O3/SiO2 or TiO2 (average values of 10%, 19%
and 30–57% as shown in Table 2.
Looking at the different structuring possibilities, ALD
can be used for particle nanostructuring, either to induce
or inhibit certain composition and structure functionalities. Depending on the growth type of the deposited material, core/shell or core/seed particles (inactive core/active
shell or seeds) can be fabricated in an activation scheme.
Noble metals (Pt, Pd, Ru, Ir) have been deposited as core/
seed active structures so far, while core/shell particles areusually functionalized with the deposition of transition
metal oxide shells (e.g. TiO2 and ZnO). ALD has proven its
potential to unlock new application areas for core/seed
nanoparticles, since it can reach extremely small sizes

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Table 2Growth per cycle (GPC) of ALD-deposited common oxides (TiO2, SiO2, Al2O3) on oxide powders (supports).
Support

References

SiO2

TiO2

Al2O3

SiO2

–

0.3

–

(Kim et al., 2009)

TiO2

0.6

–

–

(Lei et al., 2012; Mahurin et al., 2006; Sereda et al., 2012;
Williams et al., 2012)

Al2O3

1.1

2.0

1.2

(Cronauer et al., 2011; Feng et al., 2010; Feng et al., 2011;
Hakim et al., 2005; Hakim et al., 2006; King et al., 2007;
Lei et al., 2012; Sereda et al., 2012)–1

GPC (Å cycle )(about 1 nm) of deposited particles (clusters) compared toconventional (wet-chemistry-based) techniques. ALD candeposit a variety of different materials (or combinations ofthem); a comprehensive review of the compounds that canbe deposited by ALD was recently presented (Miikkulainen
et al., 2013).
In certain applications, it can be desirable to modify—
or even fully suppress—the activity of particles; a passivation scheme can yield core/shell particles of a reversed
composition (active core/inactive shell). In the case ofcore/seed particles, this technique was developed as aprotection scheme, applicable on the seed-nanoparticles.
The most commonly used passivation materials areoxides such as Al2O3 and SiO2, with the required thickness
ranging from values as low as 0.5 nm up to 50-nm films,
depending on the application. Special treatment can tailor
the nature of the protective layer to induce a certain accessibility (Canlas et al., 2012; Lu et al., 2012). Moreover,supported active multi-component materials (e.g. multi-­
metallic catalysts) can also be prepared via ALD either ina consecutive deposition scheme (He et al., 2010; He et al.,2012; Molenbroek et al., 1998) or—recently—a mixedmetal ALD process (Christensen et al., 2010; Lei et al.,2012). A schematic depiction of the different possibilities
for ALD modifications of different functionalities is shownin Fig. 2.
Thus, ALD offers a 3-stage rational design approach forthe synthesis of nanostructured particles. In the first stage,
the active phase can be deposited with high precision,
either in the form of thin films or nanoparticles. Protectionof the active phase can be achieved either by full overcoats(passivation) or partial coverage (preferential growth on the
support). Finally, selectivity is induced by manipulating theaccessibility of the active phase (in a passive, e.g. thermal
treatment, or active, e.g. blocking agent grafting way).

2.3 Reactor technology
Materials of a particulate nature often pose challenges
during their treatment with ALD due to the high total
surface area that needs to be coated and the—often present—requirement of coating high-aspect-ratio structures

Fig. 2Functionalization possibilities for active and inactive
particles by film or cluster deposition via ALD.

such as micropores. Flow-type reactors for ALD introduced by Microchemistry Ltd. (primarily designed for thetreatment of flat substrates) have been also used for thetreatment of powders; the MC-120/F-120 being one of themost commonly used reactor type. In the reaction chamber, the reactant, introduced from the top of the fixed
powder bed (up to 10 g), is allowed to chemisorb and react
for a sufficient time to reach saturation (Lakomaa et al.,1992). This reactor configuration yielded consistent saturation coverage (±0.2 atoms nm–2) but required reasonably
high pulsing times (on the hour-scale) due to the relatively
high operating pressure of 1–10 kPa. Recently, a modification of the reactor cell to a semi-fluidized powder cell was
reported for particle ALD (Rauwel et al., 2011).
A viscous-flow ALD reactor (Elam et al., 2002) oper­
ating at reduced pressure (120–270 Pa) has also been usedby researchers in Argonne National Laboratory for ALD

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treatment of powders. High-surface-area supports (up to
930 m2g-1) have been effectively coated, at faster saturation exposure times (on the min-scale). Only small batches(up to 1 g) of materials have been processed in this viscous-flow reactor type.
Additionally, modifications of conventional ALD reactors aiming at the minimization of gradients (concentration, temperature) during the deposition introduced the useof fluidized bed reactors (Hirva et al., 1994). A fluidized
bed ALD reactor operating at low pressure (133–1066 Pa)
introduced by Wank et al. (2004) has been extensively
used. Large batches of powders (up to 75 g) have beeneffectively coated in this reactor type, successfully proving the scale-up potential. Since many of the powders
used as substrates exhibit cohesive behaviour, fluidization
assistance methods such as stirring or vibration are typically required. van Ommen et al. (2012) give an overview
of the various assistance methods to fluidize nanopowders.
Although it may sound counterintuitive, nanopowders canindeed be fluidized. In contrast to particles of say 200 μm,
however, nanoparticles are not fluidized individually but asagglomerates: very dilute structures of around 200 μm consisting of ~1010 primary particles (van Ommen et al., 2012).
Despite the fact that the fluidized bed reactor provided agood scalability potential in terms of the batch handlingcapabilities, the high total surface area of the powders—
and the subsequent need for large amounts of precursor
dosing (due to the residence time of the gaseous precursor
in the fluidized bed)—called for research focussed on
more efficient utilization of the precursor. The use of arotary reactor operated at very low pressures (less than
133 Pa) was suggested (McCormick et al., 2007), in aneffort to obtain a static exposure scheme and proper
mixing during deposition. In this reactor, fluidization andagitation of the particles is achieved by rotation, and therefore a constant gas flow is not required. However, it was
not demonstrated that this reactor was more efficientthan a fluidized bed in terms of precursor utilization. Until
today, this reactor has been used to coat batches of up to
2 g. A different rotary reactor configuration was recently
proposed (Longrie et al., 2012). They operate this reactor
at a very low pressure (< 2 Pa). Their system is capableof applying both thermal and plasma-enhanced ALD.
Recently, the atmospheric pressure operation of a fluidized bed ALD reactor was demonstrated for the growth ofthin films (Beetstra et al., 2009) and the deposition ofhighly-dispersed nanoparticles (Goulas and van Ommen,2013). Although the pulsing times required are longer thanthe equivalent in low-pressure operation, the process wasproven to be efficient in terms of precursor utilization
while excluding the need for expensive vacuum equipment. Fluidization at atmospheric pressure is also more
attractive from the perspective of the scale-up potential.
To our knowledge, the 120 g-batch of LiMnO4 particles

238

Fig. 3Categorization of the main research ALD reactors used
for particle nanostructuring based on the operatingpressure range and maximum batch size reported (logarithmic scales).

coated via ALD in this fluidized batch is the largest amountreported in open literature. The next step is to move frombatch to continuous production, e.g. via the pneumatictransport of particles (van Ommen, 2010); research on suchreactors is currently being carried out in our group. A summary of the main types of reactors used is given in Fig. 3.
Moreover, certain commercial reactors such as the
Beneq P400 (Nevalainen et al., 2012), Ultratech/Cambridge
NanoTech Savannah 100 (Sun et al., 2013), Picosun
SUNALE R-200B (Williams et al., 2012) and a shower-head reactor from Korean Vacuum Tech. Ltd. (Yoon etal., 2011) have been already used for ALD on particles.

2.4    Example: deposition of platinum nanoclusters
by ALD
The ability to precisely tailor the structure of particles
on a nanoscale gives us a tool to greatly improve metal-­
supported catalysts, enhancing atom efficiency while mini­
mizing the cost of the expensive and scarce metal of theactive phase. Currently, Pt, Ir, Rh are all priced above$32,000 per kg. In an effort to establish well-definedstructure-reactivity correlations and unravel the role ofsize in nanocatalysis, materials with well-controlled dimensions in the size of (sub) nanometres have to be delivered.
Apart from achieving better material utilization—a highsurface-to-volume ratio yields a high amount of active
sites per active material mass—different functionalities
can also be assessed, due to the changed local reactivity
characteristics of nanoparticles (more corners, edges,
kinks) compared to their bulkier counterparts. Consideringthat in the fcc structure of Pt (atomic diameter of 0.278 nm),
12 shell atoms can cover 1 metal atom to form the single
full-shell cluster (n = 1) (Schmid, 1990), the structure has

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Fig. 4 Ratio of surface to total (Ns/Nt) atoms as a function of
the Pt nanoparticle size (inline graphic indicates thesize and percentage of Pt nanoparticles for 1 to 4 shells
in the fcc cluster).

93% of its atoms on the outer surface (Fig. 4). The Ns/Nt
is inversely proportional to the number of shells (n –1),
this decrease can be seen in a 2.5 nm nanoparticle, where
only 52% of its atoms are directly accessible and thus high­lighting the reactivity potential of smaller clusters.
The activity of catalytically promoted reactions is often
expressed as the turnover frequency (TOF) which describes the amount of moles converted per mole of the exposed catalyst material. The particle structure (size andshape) can affect the TOF if the reaction is intrinsicallydependent on size/shape or is structure-sensitive, whilesome other reactions are not affected by the size (intrinsically size/shape-independent or structure-insensitive). For
structure-sensitive reactions, a positive size effect marks
an inversely proportional relationship between particle
size and TOF, while a negative size effect shows a proportional interaction (antipathetic particle size-TOF dependence). For structure-insensitive reactions, the main
objective during deposition is the maximization of dispersion to achieve optimal use of the catalytic material.
Typical Pt-catalysed structure-insensitive reactions are eth­ylene and cyclohexane hydrogenation, while an example
of positively size-dependent reactions are the hydrogenolysis of ethane and the dehydrogenation of cyclohexane(Somorjai and Park, 2008). As seen from Fig. 5, small Pt
nanoparticles (≤ 3 nm) can greatly improve the TOF ofstructure-sensitive reactions. Additionally, the catalyst selectivity can also be improved by controlling the particle
size distribution over a narrow range, as demonstrated forhydrogenation reactions (Somorjai and Park, 2008).
The first report of a supported Pt catalyst fabricated by
ALD was the Pt/Al2O3 and Pt/SiO2 hydrogenation catalysts
prepared by Lashdaf et al. (2004). The cyclopentadienyl
precursor   (trimethyl)   methylcyclopentadienyl-platinum

Fig. 5 TOF values for structure-insensitive Pt-catalysed reactions, marks indicate experimentally determined datapoints (C2H4 hydrogenation: blue dotted line and ◆ ,C6H10 hydrogenation: red dotted line and ▲ ) andstructure-sensitive reactions (C6H10 dehydrogenation:
red solid line and △ , C2H6 hydrogenolysis: blue solidline and ◇ ; plotted on secondary vertical axis) (basedon Somorjai and Park (2008)).

(IV) (MeCpPtMe3) was used as a source of Pt and air wasused for the removal of the organic ligand at 350°C. For asingle exposure of the precursor, larger islands wereobserved in SiO2 (3.1 nm) as compared to the Al2O3 support (1.2 nm) in consistency with the available number ofactive OH groups (proportional to the available surface
area and surface density). Additionally, an acetylacetonate
Pt precursor (Pt (acac)2) was utilized at lower deposition
temperatures of 180–200°C, which had as a drawback theinclusion of carbon-based impurities of a high concentration (~3.5 wt.%) in the catalyst (Plomp et al., 2008; Vuori
et al., 2006).
The importance of Pt as a catalytic material has driven
efforts for deposition on strontium titanate, titania, zirconia and alumina high-surface-area supports in the temperature window of 150–300°C (Christensen et al., 2009;Enterkin et al., 2011; Lobo et al., 2012; Setthapun et al.,2010; Xie et al., 2012). Moreover, the technique has also
been used for the doping of Co-based Fischer-Tropschcatalysts with small amounts of Pt (0.1 wt.%) that acts as apromoter (Cronauer et al., 2011). Recognizing the technique’s potential for creating the high dispersion characteristics necessary in fuel cell applications, ALD has beenused for the decoration of relevant carbon-based supports
such as carbon aerogel, tungsten-carbide, multi-walledcarbon nanotubes, graphene nanosheets and carbon nanotube/graphene oxide hybrid materials (Hsieh et al., 2012;
Hsu et al., 2012; Hsueh et al., 2012; King et al., 2008; Sunet al., 2013). Additionally, bimetallic Ru-Pt and Pt-Pd catalysts have also been fabricated (Christensen et al., 2010;
Lei et al., 2012). All the aforementioned efforts were carriedout in fixed bed reactors that treated small batches of the239

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powders (< 1 g).
Zhou et al. (2010) reported the deposition of Pt islands
on TiO2 nanoparticles in a fluidized bed reactor operating
at reduced pressure. Additionally, highly dispersed Pt
clusters have been deposited effectively on micron-sized
SiO2 (Li et al., 2010), resulting in an extremely low loading of 3.1·10 –6 mg cm –2 (3.1 ∙ 10 –8 kg m –2) for 3 ALD
cycles. According to a recent publication, thermal decomposition of the Pt precursor along with Pt nanoparticle
sintering at a deposition temperature of 320°C are
responsible for the disruption of the self-limiting ALD
feature (Liang et al., 2011).

3. Experimental
Atomic layer deposition in a fluidized bed reactor operating at atmospheric pressure conditions was used for thedecoration of TiO2 nanoparticles with Pt nanoclusters. The
deposition scheme involves the sequential exposure of the
support material to MeCpPtMe3 and ozone (Goulas andvan Ommen, 2013) at 250°C. The ALD reaction proceeds
via a mechanism proposed by Kessels et al. (2009) adapted
to the following generic scheme:
R1:[Ti]:(O)*3 + 2(CH3C5H4)Pt(CH3)3→ [Ti]:2(CH3C5H4)Pt(CH3)*2 + CH4 + CO2 + H2O
R 2:[Ti]:2(CH3C5H4)Pt(CH3)*2 + 24O2
→ [Ti]:[2Pt]:(O)*3 + 16CO2 + 13H2O
The custom-built fluidized bed ALD reactor consists ofa vertical reaction chamber with an inner diameter of
10 mm that was loaded with ~0.25 g of nanoparticles, supported on a porous metallic gas distributor. The TiO2
nanoparticles used (Aeroxide P25 from Degussa, ≥ 99.5%
purity) were sieved prior to deposition. Their surface area
was ~50 m2g–1 and their average primary particle size was
21 nm with a crystal structure of about 85% anatase and
15% rutile. During fluidization, these particles formed
agglomerates of around 200 μm.
The precursor (trimethyl) methylcyclopentadienyl-platinum (IV) (Strem Chemicals, 99% purity) was utilized as a
Pt source. The precursor was transported in the reaction
zone by means of a dry nitrogen carrier gas (N2, 99.999
vol.%) that was diverted through the precursor bubbler(50°C). A dry air stream enriched with ozone (around
1.5 wt.%) was used as an oxidizer agent for the removal of
the precursor ligands and repopulation of the support surface with active sites. Ozone was obtained by feeding the
dry air flow (0.20 L min–1) through an ozone generator

240(OAS Topzone). No significant decomposition of ozone
was observed during the transportation of the stream to
the reactor zone via the reactor distributor. Nitrogen was
also used for the intermediate purging pulses that were
implemented to evacuate the reactor from the excess of the
precursor and the reaction by-products during the ALD
half-cycles. During operation, the TiO2 powder was suspended in an N2 flow of 0.20 L min–1 (corresponding
superficial gas velocity of 4.2 cm s–1), ensuring that theparticles were sufficiently mixed. Fluidization was assistedusing a dual vibromotor. The reaction temperature of
250°C was maintained by means of an IR-heater withfeedback control. A more elaborate description of the
set-up is given by Beetstra et al. (2009). The loaded TiO2
nanoparticles were pretreated (heating under inert atmosphere) to ensure a constant initial number of active
OH-groups in the surface. The typical pulsing sequence
for Pt-N2-O3-N2 consisted of exposure times of 3–12 min
for MeCpPtMe3, and 10 min for ozone separated by N2
purging pulses of 10 min.
Optical emission spectrometry (ICP-OES) using a
Perkin Elmer Optima 3000 DV spectrometer was used todetermine the amount of Pt deposited. The level of carbon
impurities in the samples was monitored by IR absorption
spectroscopy in a C/S determinator (LECO CS-225). The
structure of the deposited islands was determined from
TEM images using a FEI Tecnai TF20 microscope equippedwith an EDX detector (Oxford Instruments). XRD measurements were carried out with a Bruker D8 Advancediffractometer. The BET surface area of the coated anduncoated samples was determined via N2 adsorption witha Quantachrome Autosorb-6B surface area analyser.

4. Results and Discussion
Two of the important intrinsic properties of ALD are theself-saturating character of the growth for a single cycle
and the linear increase of the amount of material deposited by increasing the amount of cycles. Coating powder
batches of increased surface area (up to 14 m 2 per sample
batch) requires much longer precursor exposure, oxidationand purging times. It has been shown that during the prolonged exposure times, the reactor temperature should beproperly controlled to avoid thermal decomposition of the
precursor (Liang et al., 2011). When utilizing a lower
deposition temperature (250°C instead of 320°C), an indication of the self-saturating ALD characteristic was seen
(as shown in Fig. 6) with the Pt loading stabilizing at~1.6 wt.% after 12 min of precursor exposure.
The average Pt particle size from TEM image processing
was estimated to be about 1.5 nm for a Pt pulse of 3 min
and appeared to be stabilized for exposures up to 12 min.
Uniform decoration of the support material with Pt nano-Aristeidis Goulas et al. / KONA Powder and Particle Journal No. 31 (2014) 234–246

Fig. 6 Estimated Pt content (red line and ◆ ) and nanocluster
size (blue line and ▲ ; on secondary vertical axis) forvaried Pt precursor exposure times and 1 ALD cycle.

Fig. 8Pt particle size distributions derived from TEM image
processing for samples obtained after 3 min (whitebars), 6 min (grey bars) and 12 min (black bars).

Fig.  7

Fig. 9Pt content measured by ICP ( ▲ ) and predicted loading
value for ideal ALD ( ◇ ) along with specific surface
area ( ■ ) for 1–4 ALD cycles (Pt content values corrected for changes in surface area after deposition).

TEM image of the Pt nanoparticles decorating thesurface of the TiO2 support after 1 ALD cycle of 3 min
Pt precursor exposure. The inline image depicts thedecoration at the edge of the TiO2 crystal.

clusters was obtained as shown in Fig 7. The particle size
distributions presented in Fig. 8 verify that the process
was well controlled and resulted in very similar, narrowly
distributed particles. Moreover, the TEM pictures indicated that the Pt nanoclusters were nicely distributed over
the titania particles. This can be explained by the very
open structure of the agglomerates, as well as by theirdynamic nature: they constantly break-up and reform into
new agglomerates (van Ommen et al., 2012).
Precursor utilization for exposure times in the saturation regime was relatively low: only ~50% of the Pt precursor provided was eventually loaded in the support. Using
ALD for the fabrication of ultra-low loading catalysts,
sub-saturated pulses can be implemented to achieve maximum utilization of the precursor. An exposure time of ¼

the saturation time resulted in a deposition amount of
about half of the equivalent amount deposited for operation in the saturation regime. The corresponding precursor
utilization was estimated to be 95% in that case. An estimation of the E-factor value was made, considering Pt/
TiO2 as the final product (~10–20% of the loaded TiO2 islost as waste during handling). The outlet waste stream
contains the gas products of the organic ligand decomposition and the excess amounts of oxidizer gas used (O3/O2,
without taking into account N2). The equivalent calculated
E-factor of the deposition process is ~6–7, fitting in therange of 5–50 that describes processes of the fine chemicals industry (Sheldon, 2007).
Additionally, the loading of the catalyst can be precisely
controlled by the number of ALD cycles performed. Fig. 9241

Aristeidis Goulas et al. / KONA Powder and Particle Journal No. 31 (2014) 234–246

Fig.  10 Overview TEM images of Pt nanoclusters deposited on the TiO2 support for 1 ALD cycle (a) and 5
ALD cycles (b).

presents the measured content of Pt (wt.% of Pt) along withthe theoretically predicted value for ideal ALD growth,
together with the change in value of the specific surface
area of the support. Increasing the number of cycles from
1 to 4 shows a monotonic increase of the Pt loading, verifying the proportional relation between the deposited
amount and the number of ALD cycles. The surface area
showed a small increase of 5%, in agreement with deposition of small Pt nanoclusters on non-porous supports. The
loadings of the catalysts obtained here are higher than theones obtained in a fluidized bed reactor operating at
reduced pressures (Zhou et al., 2010). The use of ozone—amore powerful oxidizer—is one possible cause, but theeffect of pressure should also be carefully considered infuture studies.
The use of ozone allowed the process temperature to belowered during the oxidizing step. This can have a beneficial effect on the dispersion of the noble metal nanoparticles, as it prevents their sintering to a certain extent. To
further probe the dispersion of the Pt nanoclusters, we
examined several TEM images, applying image analysis(ImageJ). A sample of 1 ALD cycle deposited for 12 min
exposure time (1.6 wt.%) and 5 ALD cycles deposited for
5 min exposure time (5.8 wt.%) are shown in Fig. 10. As
the number of cycles increases, the particle nanoclusters
increase in size. All the particle size distributions were
calculated based on the processing of 100–200 Pt nanoparticles from different images. The presence of Pt (small
clusters of darker contrast on the lighter crystalline support material) was further verified by qualitative EDX
analysis. As discussed above, the average particle size
increased from 1.5 nm to about 2.3 nm while the particle
size distribution was—for both cases—very narrow (Fig.
11). The possibility of ALD to deposit small nanoparticles,
even for high loadings of noble metals, makes it a promising fabrication technique for low-and medium-loading
noble metal catalysts.
ALD offers a simple way to control the particle size of

242

Fig. 11 Particle size distribution derived from TEM image
processing for Pt nanoclusters deposited onto the TiO2
support after 1 ALD cycle (white bars) and 5 ALD
cycles (black bars). The inline graph shows the particle
size distribution of the 1 ALD cycle Pt/TiO2 (1.6 wt.%,
white bars) and of a Pt/TiO2 catalyst prepared via photodeposition (1.5 wt.%, grey bars) (Colón et al., 2010).

Pt, which is illustrated in the inline graph of Fig. 11. The
ALD catalyst is compared to a Pt/TiO2 catalyst of similarloading (1.5 wt.%) prepared via the photodeposition technique (Colón et al., 2010). The low average particle size
obtained by ALD (1.5 nm versus 3.9 nm) ensures a higher
utilization of the expensive active material. The increasein the noble metal specific surface area (186 m2g–1 versus
72 m2g–1) is expected to contribute positively to the performance of similar catalytic systems. This thus demonstrates
that atomic layer deposition using a fluidized bed reactor atatmospheric pressure is an attractive method that combines scalability and high precision for the fabrication of
catalysts and other nanostructured materials.

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5. Conclusions and outlook

Acknowledgements

In the past decades, ALD has firmly established its position as a high-precision thin-film manufacturing technique
for the microelectronics industry. Realizing the potential of
ALD as an integral nanofabrication toolbox for the design,
fabrication and modification of advanced materials is opening a new range of possibilities. The application of ALD toparticles enables the production of a whole range of novel
nanostructured particles for, among others, catalysis, energy
conversion and storage, and medical applications.
In this paper, we focused on the fabrication of catalysts
by deposition of the active phase (Pt) on a particulate substrate (TiO2 P25 nanoparticles). We demonstrated that
ALD is a technique that 1) guarantees efficient use of the
precursor; 2) allows precise control of the size and loading;3) can be used for low and medium loading of catalysts byadjusting the number of repeated cycles; 4) leads tohigh-quality (low impurities level) end products.
The future demands for the high-volume production of
tailored nanostructured materials require innovation inreactor design for ALD processes. Currently, fluidized
bed reactors are the first choice for particle ALD, enabling
tonne-scale production in the near future. Operatingthese reactors at low pressures favours the removal of
gaseous compounds in the purging steps; however, operation at atmospheric conditions is beneficial for the
scale-up potential.
Compared to liquid-based synthesis routes, ALD
improves the fabrication compliance with the principlesof Green Chemistry: absence of solvents/residues, minimization and easy handling of the reaction by-products(waste) and overall simplification of the production route(all process steps rely on robust gas-solid-based unit
operations). The low value of the E-factor (comparable tothe fine chemicals industry) clearly shows the way tomore sustainable production schemes. The high degree ofdeposition control (size, composition, distribution) highlights the potential for high-end-value products such as
noble metal-supported catalysts. Mild temperature andpressure conditions make the technique compatible withtemperature-sensitive materials.
As ALD matures further, certain research challenges
will have to be overcome: gaps such as the need forresearch on novel precursors (e.g. for silver and gold) andthe requirement of clear understanding of process parameters (effect of pressure, growth mechanisms, and overexposure role on the deviation from ideal behaviour). Many
challenging areas related to materials properties and nanostructuring can be addressed in a scalable production
scheme offered by ALD. Bringing fundamental scienceand engineering principles together, ALD is effectively
driving surface chemistry at an atomic resolution, while
enabling industrial-scale production.

Financial support from the European Research Council(AggloNanoCoat and CONiA projects) is gratefully
acknowledged. The authors would like to thank Ms. Andrea
Fabre for her careful proofreading of the manuscript.

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Author’s short biography
Aristeidis Goulas
Aristeidis Goulas received his Dipl. Eng. in chemical engineering from Aristotle
University of Thessaloniki in 2008 and his MSc degree in sustainable energy technology
from Delft University of Technology in 2011. He then joined the Product and Process
Engineering group (Delft University of Technology) as a researcher. His work focuses on
gas-phase nanostructuring techniques for the fabrication of novel nanostructured materials.

J. Ruud van Ommen
J. Ruud van Ommen received his MSc degree in chemical engineering in 1997, followed
by a Ph.D. in 2001, both from Delft University of Technology (the Netherlands). He has
been a faculty member at Delft since, with stints at Chalmers University of Technology(Sweden, 2004/2005) and the University of Colorado Boulder (USA, 2009). In 2011, he
received an ERC starting grant to investigate the interplay between the agglomeration andcoating of nanoparticles in the gas phase. Currently, he is an associate professor at Delft
University, leading a research team with the focus on scalable processes to make nanostructured materials.

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Original Research Paper

Recycling-Oriented Investigation of Local Porosity Changes in
Microwave Heated-Concrete †Nicholas R. Lippiatt and Florent S. Bourgeois *1

Laboratoire de Génie Chimique UMR CNRS 5503, Université de Toulouse, France

Abstract
Large quantities of concrete waste are being produced continuously throughout the world, of which only a fraction
are downcycled as construction backfill or as road-base. Seeking total concrete recyclability, this work concerns thedevelopment of microwave-based solutions for the separation of individual constituents of concrete. By focusing on
the interaction between microwaves and concrete at the microscopic level, the paper makes important connections
between local changes in the microwave-heated concrete texture and macroscopic changes in mechanical properties.
Through analysis of the concrete texture using SEM imaging, it is found that the microwave heating of concrete
causes fracture porosity. The size and shape of fracture porosity can be correlated with recycling performanceindicators; namely aggregate liberation, concrete strength and product fineness. In particular, the work finds that
only a short exposure to microwaves promotes the formation of a primary fracture network responsible for selective
liberation of aggregates. Longer exposure to microwave heating creates a secondary network of smaller fracturesthat spreads throughout the cement phase, which is directly associated with the changes in mechanical strength of
concrete and product fineness.
The work introduces the concept of textural versus physical liberation, and shows that while microwave heating
creates a high selective textural liberation of aggregate particles, the comminution of microwave-heated concrete
may not necessarily yield high physical liberation. The work concludes that the key to designing a microwavebased process for concrete recycling resides in finding comminution and separation technologies that can best
harvest the benefits of the textural and mechanical changes produced by microwave heating.
Keywords: concrete, recycling, microwave heating, fracture porosity

1. Introduction
Concrete is the most-used manufactured product on theplanet, as a consequence it also constitutes a large fractionof urban waste. Many countries already make use of concrete waste as backfill and road base. Countries such as
the Netherlands and Denmark manage to recycle over
80% of the construction and demolition (C&D) waste theygenerate (Fischer and Davidsen, 2011; Symonds, 1999).
Nonetheless, a large fraction of concrete waste is not used
and the concrete that is recycled is invariably downcycled,
as can be seen by the ratio of virgin aggregate to recycled
aggregate used in concrete production (Klee, 2009). Usingcrushed concrete as a replacement for coarse aggregate
reduces the mechanical performance of the final product inproportion with the fraction of crushed concrete used. This†

Accepted: August 20, 2013
CNRS-Laboratoire de Génie Chimique UMR 5503, 4 Allée Emile
Monso BP 84234, 31432 Toulouse Cedex 4, France* Corresponding author:
E-mail: florent.bourgeois@inp-toulouse.fr
TEL: +33-534-323-633 FAX: +33-534-323-700
1©2014 Hosokawa Powder Technology Foundation

effect is significantly greater when crushed concrete is used
as a replacement for fine aggregates, which is why concrete
waste is almost never used in this way. The reason crushedconcrete reduces the performance of concrete compared tovirgin aggregate appears to be due to adhered cement pasteand how it reacts to new cement as it cures (Tam et al.,2007). The first step to complete concrete recyclability
therefore is finding an effective technique to decrease thevolume of adhered cement on recycled aggregates.
Microwave heating is especially applicable to processing multiphase materials as it uses the differences in thermal and dielectric properties between distinct phases togenerate fractures and weaken the material. A simple
version of this scenario is a strongly dielectric material
embedded in a continuous microwave transparent material. In fact, this basic scenario closely resembles what isfound for mineral ores, for which microwave heating as acompanion treatment step before crushing and milling has
been considered for some time and has been shown to
weaken the ore and increase mineral liberation, hence
mineral yield (Kingman et al., 2004a). The ever-present
question is whether the benefit of the increased yield

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exceeds the energy required for the process. As the priceof minerals and metalliferous ores and the efficiency of
microwave processing technology increase, one might
predict that this will soon be the case.
In the case of concrete waste, one could argue that thedevelopment of a microwave-based recycling process has
perhaps even more potential than with mineral beneficiation. Some arguments to this effect include:–	Recycling concrete has the potential of eliminating awaste stream altogether by recycling all its constituents. Being a high-value man-made material with significant energy and material footprint, the recycling of
concrete is a priority.
–	Recycled cement can re-enter the clinker-making process (Costes et al., 2010) and thereby contribute to
reducing the CO2 emissions of clinker production bydirect substitution with natural carbonates. Reusing
cement will also contribute to preserving natural carbonate reserves. Also, the presence of already decarbonated and crystallised phases in recycled cement
may also have a positive effect on the energy balance
for making clinker, through a possibly reduced heatrequirement due to the reduced initial mass and lower
required temperatures.
–	Recycled aggregate can re-enter the concrete-making
process and contribute to preserving natural aggregate
resources, which is becoming a scarce resource indeveloped countries, particularly when dealing withaggregates of alluvionary origin.
–	The proximity of concrete waste to consumption areas
may contribute to reducing transport associated withthe concrete-making industry.
The sensitivity of concrete to microwaves has been
known for some time. Using a 5-kW multimode microwave oven and exposure times up to 30 minutes, the possibility of liberating aggregates from hardened cement for
concrete analysis purposes was tested over 30 years ago
by Figg (Figg, 1974). His pioneering work with 100-mm
cubes brought convincing evidence that microwaves could
indeed induce boundary fracture at the aggregate-cement
interface. At high power inputs, concrete has also beenshown to respond explosively, with commercial applications in drilling (Jerby at al., 2002) and controlled spalling(White et al., 1995).
The application of microwave-heating to the issue ofconcrete recycling is a relatively new endeavour, but one
that has already been shown to be effective. Akbarnezhad
and co-workers (Akbarnezhad et al., 2011), using a 10-kW
generator, showed microwave heating prior to physicalcomminution to improve recycled aggregate properties,
and that this effect is superior to comparable techniques
using purely mechanical means or a combination of
mechanical means and conventional (external) heating.
About the same time, the authors (Lippiatt and Bourgeois,

2482012) showed that microwave heating of concrete
increases the liberation of aggregate and cement, while
decreasing the strength of concrete.
Eventually, impact breakage of these microwave-heatedparticles of concrete was carried out using a short Hopkinson bar (Bourgeois and Banini, 2002). Liberation wasmeasured using a dissolution technique based on the workof Kiss and Schönert (Kiss and Shönert, 1980).
The results of this previous work validated the hypothesis that the microwave heating of concrete, followed by
impact breakage, improves aggregate liberation, thereby
opening avenues for recycling concrete. Moreover, thedegree of liberation was found to increase non-linearlywith exposure time, hence input microwave energy. The
short and medium exposures did lead to a similar level ofaggregate liberation, which exhibited a significant increase
after the long exposure.
Cement liberation was not measured directly but by themass lost during dissolution. Cement distributions were
nearly the same for samples that had undergone short andmedium microwave exposures, and cement fines increased
dramatically with the longest treatment. It is noted that the
sharp increase of cement liberation with the long exposure
to microwaves, followed by impact breakage, mirrors theincrease in liberation of aggregates by the same process.
Analysis of Hopkinson bar impact tests revealed both areduction in impact fracture force with increasing exposure, and a progressive loss of elasticity of the concretewith the mechanical behaviour of the most damaged samples resembling that of a loose-packed bed.
These quantitative observations are conclusive indicators of the value of microwave heating for recycling concrete. In summary, when followed by impact breakage, themicrowave heating of concrete increases aggregate liberation, increases cement fines and reduces concrete strength.
However, the macroscopic nature of these observations,which result from the combined effect of microwave heating and impact breakage, does not permit understanding
what is actually happening inside concrete during microwave heating. The authors argue that some understanding
about the microstructural changes that occur at the local
scale inside concrete during microwave heating is essential
for defining the scope and place of microwave heating in a
concrete recycling process. The ultimate goal that this paper
aims to move towards is to precisely unravel the elementsof reconciliation between variations at the microscopic andmacroscopic scales, so as to provide guidelines for thedevelopment of an efficient concrete recycling process.

2. Materials and methods
Our ability to relate observations between both scales
requires that we quantify the textural changes that takeNicholas R. Lippiatt et al. / KONA Powder and Particle Journal No. 31 (2014) 247–264

place inside concrete during microwave heating, especiallynear the aggregate-cement interface and inside the cement
matrix itself. In the process of developing a satisfactory
texture analysis protocol, several experiments were performed. This preliminary work led to some appreciationof what had to be quantified for the sake of understanding
the link between changes in the microstructure and macroscopic behaviour of concrete. It was concluded that mic­
rostructure quantification would have to focus on theproperties of cracks, whose patterns were found to change
most significantly during microwave heating. Mineralogical changes, as measured by X-ray diffractometry, did notreveal significant changes in comparison. Having decided
that the formation of cracks should be the focal point,
efforts were allocated during this work to establishing anexperimental protocol that would not alter the fracturescaused by microwave heating. A non-­destructive observation protocol using the scanning electron microscope for
texture image acquisition was designed for this very purpose, avoiding altogether any requirement for crack
impregnation, cutting or polishing after microwave treatment of the concrete samples.

hours they were removed and allowed to cure in water atroom temperature for a minimum of 90 days.
The samples were then removed from soak and separated into lots of 12 units. One sample was reserved for
mercury porosimetry analysis, ten for Hopkinson bar
impact testing, and one was cut using a water-lubricateddiamond saw to give an exposed cross-section. The purpose of this operation was to create a flat surface that
could be readily observed after microwave treatment,
without requiring any post-treatment cutting or polishingthat could potentially alter the fractures induced by theheating process. An alternative would have been to
impregnate uncut samples after microwave treatment witha polymer resin or Wood’s metal, and then cut and polishto expose an observable flat surface. However, thisapproach was rejected outright for it had the potential todamage the fractured microstructure. One downside of the
protocol that was adopted here over the alternative wasthat it made the observation of fractures possibly moredifficult due to the lack of contrast of the fractures against

Table 1

2.1 Concrete sample preparation
The concrete used in this work was made withcement-enriched mixture (CEM) 1 52.5 Portland cement.
Samples were mixed in five different ratios (See Table 1)with siliceous aggregate 2–2.5 mm in size. The sample
preparation protocol is schematised in Fig. 1. Samples
were cast in 20-mm cylinders, which after curing, would
weigh about 10 g each. After setting in the mould for 24

Fig. 1

Properties of concrete samples

Concrete samples

Water/Cement
mass ratio

Aggregate/
Cement mass ratio

S1

0.4

0.6

S2

0.4

0.85

S3

0.4

1.6

S4

0.5

1.6

S5

0.6

1.6

Illustration of the concrete sample preparation protocol.

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the solid phases. This was found to be a problem particularly with untreated samples. The measurement is basedon a subjective judgement of contrast and shape. Untreatedimages showed even less contrast than treated samples.
Some might consider ten samples an insufficient number of samples for mechanical tests of this type. At thisstage, the goal is merely to seek patterns so that more
extensive testing and results distribution analysis is unnecessary. All results are presented with the mean and fullrange of measured values.
Prior to testing, samples were systematically dried at
50°C for 24 hours before any microwave treatment or
analysis began so that all samples would be equally dry
before testing. This was validated by measuring the sample mass changes with drying. After 24 hours at 50°C, thesamples stopped losing mass at room temperature.

2.2 Microwave testing and sample post-treatment
Higher power densities are more effective in embrittling
multiphase materials (Ali, 2010) and the highest power
densities are produced in single-mode cavities (Kingman
et al., 2004b). The samples were heat-treated in a 2-kW/­
2.45-GHz single-mode horizontal waveguide applicator
designed by SAIREM. The samples were heated in the
microwave system individually; the sample moulds were
designed so as to make use of the 30-mm microwave trans­parent, cylindrical, silica sample holders. The position
for the iris and the short circuit for minimum reflectedenergy were found manually. The iris position was kept
constant for all tests. If the initial reflected energy was
higher than expected, the short circuit was moved toaccommodate. This change in position was never morethan a few millimetres.
The samples were treated for 3 characteristic times andthe power absorption signal was recorded. These times areseen in Fig. 2, and correspond to 15, 30 and 50 seconds
called ‘short’, ‘medium’ and ‘long’ treatment, respectively.
Short, medium and long microwave exposures are annotated as ‘S’, ‘M’ and ‘L’ so that S1-0, S1-S, S1-M andS1-L represent untreated, short, medium and long treatment times of concrete sample S1, respectively.
They were chosen as they were found to represent three
distinctly different stages in the microwave heating cycle
for the cast concrete samples under the conditions of thetest. The ‘short’ time comes just after the initial absorption
peak, during which 50 to 70% of the sample mass loss
occurs, as water evaporates readily. The ‘long’ time occurs
before the absorption starts to peak again, and the ‘medium’
time corresponds to an intermediate time between these two
events. The formation of this microwave absorption peakusually occurred after approximately 50 seconds but was
not totally predictable. It is assumed to occur after the formation of local thermal runway and consequently the for-250

Fig. 2 Typical microwave power absorption record for a
20-mm cylindrical concrete sample (S1).

mation of a plasma. Although the reflected power wasmeasured in real time, the microwave cavity is an open
system that can lose mass and energy by convection andevaporation, so the measured energy and power absorbed
by each sample is only a guide, and cannot be used as abso­lute energy absorption by the samples.
After cutting the power at the end of the test, an estimate of the average temperature reached by a sample wasobtained using a Jules Richards Instruments Flashpoint
FX400 infrared thermometer pointed at the sample surface. The temperature was measured on each of the sample’s three surfaces. The mean of the highest recorded
temperatures of each sample was recorded as the temperature achieved after treatment. Due to conduction with theexperimental surface between measurements, the highest
temperature measured was usually the first temperature
measured. The maximum temperature was chosen as therepresentative temperature because of the temperatures
measured, it exhibited the least variation. The four surfaces of cut samples were also measured but these values
were not used in the temperature calculation due to thedifference in sample mass. The samples were weighed
individually prior to and after microwave treatment, inorder to record the mass loss associated with the heatingprocess. Initially, they all weighed about 10 g.
Eventually, a number of tests were systematically performed on the samples. These measurements included:–	Total porosity and pore size distribution by mercury
intrusion porosimetry. This was performed using
standard 400 MPa intrusion with a Micromeritics
Autopore IV.
–	Impact breakage testing using a vertical Hopkinson bar.
The cylindrical steel bar used was 40 mm in diameterand 1.5 m long. The impactor was a 60-mm diameter,825-g steel ball bearing dropped from a height of
163 mm and 200 mm. In previous work, a drop heightof 163 mm was found to be the minimum required tobreak an untreated 20-mm concrete cylinder so it wasused again for consistency. The 200-mm drop was used

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Fig. 3Standard intensity histogram for SEM images of S1-0 sample. Left: 400× magnification = 0.9 μm/pixel, right 2000×
magnification = 0.2 μm/pixel.

to decrease the number of unbroken samples. This does
not affect the measure of force required to fracture asample unless a sample is sufficiently damaged that it
no longer displays brittle elastic fracture properties.
–	C apture of flat surface images using a Hitachi
TM3000 Tabletop Microscope SEM, at different
resolutions. The following section is dedicated to thisspecific part of the sample analysis protocol, which
deals with measuring the local effect of microwave
heating on the concrete texture.

2.3 Acquisition and analysis of concrete texture
imagesAs indicated previously, the flat surface of the concrete
samples, whether treated or untreated, was observed as is by
SEM, i.e. without any post-treatment tampering. The SEM
images were obtained in this work using a Hitachi TM3000
set to an acceleration voltage of 15 kV. Image analysis ofelectron microscope images have already been used withsuccess in concrete and cement analysis (Ben Haha et al.,2007; Igarashi et al., 2004; Wong et al., 2006). For the sakeof analysing the fractures transecting the flat surface of theconcrete samples, the use of SEM images proved to berather challenging. Indeed the grey-scale intensity of SEM
images shows significant overlap between the fractures andthe solid phases. Fig. 3 shows that almost every phasepresent is included in the same grey level peak.
Given the significant overlap in grey-scale intensity, thebinarisation of images is difficult to automate. By careful
preparation and observation of samples under sufficiently
high magnification, as per the image on the right of Fig. 3,
the intensity histogram can be separated sufficiently into
different peaks so that automated image analysis can be
performed on SEM images of concrete and other cementbased materials (Brough and Atkinson, 2000; Yang andBuenfeld, 2001). Examining larger objects such as aggregate particles and the fracture growth that occurs aroundthem requires a lower magnification, meaning greater
sample surface area in an image, for reasons of representativity. This lower zoom level has the side effect of condensing the grey-level histogram, making automatedimage analysis more difficult. Even when highlighted
manually, there is the fear that fractures are mislabelled
due to low contrast. By repeating the liberation measurement on 40× (9 μm per pixel) images, the uncertainty inthe liberation measure was estimated to be no greater than
5% total interface length.
The fractures observed in this work are spaced at distances such that if images were taken at high magnification, say 2000×, then it was very easy to take an image
that showed no fracture, even when the sample was highly
fractured. When using a low magnification, say 50×,
although the high area covered by an image meant the251

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image was more representative of the sample, it alsomeant that smaller cracks that were visible at higher magnifications would not be included in the analysis. The minimum zoom possible on the SEM equipment used is 40×,
which corresponds to a pixel resolution of 9 μm per pixel.
For this work, two zoom levels were chosen, 40× and200×. Images taken at 40× zoom were chosen to measure

Fig. 4 Comparison of area covered at different zoom levels on
sample cut surface.

Fig. 5

Fig. 6252

the liberation of aggregates as, after cursory examination,a large apparent variation was observed between aggregate
particles and this zoom level allowed the largest possible
fraction of a sample to be investigated. Another set ofimages was taken at a zoom level of 200× so that crack
networks not visible at a larger scale could be investigated.
The number of images was chosen in such a way as toyield a satisfactory compromise between representativity(giving a stable average of textural properties) and keeping the number of images to a minimum, given the strainof the manual digitisation work involved. A scaled comparison of the size of images taken at different SEM magnification levels is shown in Fig. 4.
To overcome the lack of contrast, sample images werehighlighted manually. This technique, despite its tediousness, presents a satisfactory way to deal with the aggregate/cement contrast overlap simultaneously with theporosity/fracture contrast overlap. Although the technique
has been rightfully identified as imperfect, it has also beenused to justify the accuracy of automated image analysis
methods (Brough and Atkinson, 2000). In this case, if oneof the techniques is accurate, then both must be. Fig. 5
shows an SEM image before and after highlighting.
Aggregates and fractures are easily recognisable. The
meaning of the colour-coding of the highlighted image
fractures is explained later.

Example of original and highlighted images taken at 40× zoom for an S1-M sample.

Illustration of the concrete SEM imaging scheme. Left: images sampled at 200× magnification, Right:
images sampled at 40× magnification.

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Quantification of fractures being the focal point of theanalysis of concrete microstructure after microwave heating, a number of properties were used to quantify fracture
porosity.
Straightforward variables that can be measured are thelength of, number of and width of cracks present in agiven sample area. For the purpose of quantitative image
analysis, it was decided to capture 10 SEM images forevery sample, 480 pixels by 640 pixels in size, at 9 μm per
pixel (40× magnification) and at 1.8 μm per pixel (200×magnification). Fig. 6 shows the scale and positions of the
10 non-overlapping images for both resolution settings,
relative to the 20 mm concrete sample.
Fractures were highlighted manually using a Wacom
DTU-2231 interactive pen display. One advantage of thismanual image analysis scheme is that it permitted careful
hand delineation of different components present in theimages, thereby differentiating different classes of fractures. The key highlighted components were:• Aggregate/cement interface with fracture• Aggregate/cement interface without fracture• Fractures within the cement bulk
• Fractures within aggregate particles
As illustrated in Fig. 7, every component of interest to
the work was highlighted using a distinct colour, which
could eventually be used for counting purposes. Six
colours, easily distinguished in RGB format, were used(pure green, pure blue, pure red, pure green/red-yellow,
pure blue/red-magenta, pure green/blue-cyan), sevenincluding the areas not highlighted (the entire grey-scalefrom black to white).

Fig. 7

Having highlighted different components of interest
with distinct colours, a number of insightful quantitative
properties, which will be eventually tied to macroscopic
variations in concrete properties and operating conditions,
could be easily post-treated. They included the propertiesof fracture per se, as well as the properties that weredeemed directly relevant to processing performance.
Starting with the former, the total crack length wasmeasured from skeletonised highlighted images, whereas
the total area of cracks, both in the cement bulk andbetween aggregate and cement paste, and average crack
width were measured directly from the highlighted
images.
In some images, it is sometimes difficult to tell the difference between a large pore that has formed from an air
pocket and one that is the result of an aggregate that is nolonger present. Both have a similar shape and appeared tohave a similar effect on fracture growth. For initial analysis, all such objects were marked as liberated aggregate.
This decision was made to reduce the subjectivity in theanalysis process. A side effect of this decision is that all
textural liberation values are overestimated. Re-analysis of
the S1-0 samples places this variation no greater than 10%of the total aggregate interface length. As all samples weremade in the same manner, it can be assumed that the quantity of such large pores is common between samples. Sucha systematic error can be ignored in that its biasing theactual values does not change the comparative analyses
and conclusions drawn.
Looking now at properties that relate directly to processing performance, the textural liberation of aggregates

Examples of highlighted SEM images. Clockwise from top left: S1-0 at 200× zoom, S1-S at 40× zoom,
S3-L at 200× zoom, S4-M at 40× zoom.

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Fig. 8

Example of aggregate textural liberation measurement, S1-M at 40× zoom.

was defined as the ratio between the fractured and total
aggregate boundary lengths. Fig. 8 shows an image with atextural liberation value of 76%.
Aggregate liberation was measured using the 40× zoom
(9 μm per pixel) images for the sake of representativeness.
The cracks in the cement paste, however, were significantly finer, and were observed using 200× zoom (1.8 μm
per pixel) images. During analyses it was found that there
appeared to be two different types of fractures forming

Fig. 9

Example of primary and secondary fracture network
highlighting.

Fig.  10254

within the microwave-treated concrete samples. The firstgroup formed the ‘primary network’, and included all thefractures at the interface of an aggregate particle and thecement paste and all fractures that branched from thisinterface. This network was visually identified as being
made of a few large fractures which ran from aggregate toaggregate throughout the sample. The second groupformed the ‘secondary network’, and included a large
number of smaller fractures that spread throughout thecement phase. Fig. 10 illustrates the 2 families of fractures,
which were assigned different colours for quantification
purposes. Aggregate fractures occurred also, especially in
long-treated samples. However, aggregate fractures
occurred to a far lesser extent than cement and grainboundary fractures so were not accounted for in the analysis, which allowed one of the nine colours to be re-­assigned so as to permit differentiation between primaryand secondary-network cement paste fractures. In Fig. 9
and Fig. 10, primary network fractures are displayed inyellow.
Once the images were skeletonised and fractures sorted
into primary and secondary networks, the nodes and endsof fracture branches were then counted automatically. A
branch is defined as a length of fracture between nodes
and/or fracture ends.
Because the post-treatment of highlighted images is

Example of identification of branches and nodes in the secondary network of fractures. Yellow:
primary-network-cement paste fracture, green: secondary-network fracture, red: aggregate/cement
interface fracture-primary network, red circle: node, blue circle: branch end.

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Fig. 11

Measurement of surface temperature as a function oftest duration (exposure time offset for clarity).

Fig. 12 Correlation between mass loss and energy absorption.

automated, some fractures will necessarily be misclassified, as for example some primary fractures will be connected to aggregates that are not contained in the image,or a primary fracture will branch into two almost identicalbranches. However, such occurrences are rather rare anddo not change the value of the results obtained considering
the large number of fractures.

3. Effect of microwave heating on concrete:
macroscopic level results and analysis
This section presents the results of measurements madeon concrete samples at a macro scale. It shows the temperature, mass loss, fracture strength and the MIP (mercury intrusion porosimetry) porosity changes associatedwith microwave treatment in different concrete samples.
This macroscopic level analysis is used to justify thenecessity for local, textural analysis of the effect of microwave heating on concrete.
Microwave treatment increases the temperature of concrete samples, albeit in a different way to that of conventional heating as external heating conducts from thesample surface, whereas microwave heating occurs within
the sample. Nevertheless, the longer the application ofFig. 13 MIP measurement of total sample porosity for S1 to S5
concrete samples.

microwave power, as shown in Fig. 11, the greater thetemperature measured at the surface of the concrete samples. Despite the S5 sample exhibiting a slightly different
trend, it is fair to say that the elevation of temperature, as
measured at the samples’ surface, is comparable for allconcrete sample types tested with short, medium and long
treatments.
With the samples tested, it can be concluded that the
average temperature reached by the samples does notdepend significantly on the variations in concrete properties, at least within the variable range represented in samples S1 to S5 (See Table 1). As can be seen in Fig. 11, theamount of energy absorbed by each sample is nearly proportional to time once the initial water absorption peak isover. The power input was set to the same 2 kW nominal
value for each test. This implies that the differences inthermal properties, dielectric properties and mass compensate for each other and/or they are insignificant in therange tested. As will be seen later, differences in texturalproperties within the samples are also marginal, suggesting that microwave heating of concrete exhibits a low sensitivity to concrete properties. This is a valuable result
from a recycling standpoint as it suggests a concrete recycling process will be insensitive to input properties and no
special expense or effort is necessary to accommodate
varying concrete waste streams.
The energy absorption by the concrete samples isstrongly correlated with the mass loss, as shown in Fig. 12,
which is itself caused by water loss during heating. It is
possible that mass other than water can be lost, however,this effect is deemed insignificant and so all mass changes
can be safely assumed to be due to the loss of water. It isalso noted that X-ray diffraction spectra did not show any
noticeable mineralogical changes between treated anduntreated samples, confirming that decomposition of crystallised phases such as portlandite and calcite are marginalat best at such temperatures (Piasta et al., 1984).
By means of MIP, the changes in porosity were characterized with all 5 samples under their untreated and255

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Fig. 14

MIP measurement of total sample porosity as a function of mass loss.

Fig. 15 Measurement of pore size distribution using MIP for
sample S4.

microwave-heated states. Fig. 13 shows the total intrusion
porosity, a measure of the total volume of pores in thesamples. The data is given on a sample mass basis. Thereis a consistent increase in total porosity with increased
energy input into the concrete samples, for all concrete
samples tested.
Although water loss plays a significant role in theporosity gain, as would naturally be expected, Fig. 14
shows that there is no clear trend between the measured
increase in sample porosity and the actual mass loss.
Assuming MIP accurately measures the total porosity,
converting the mass loss from Fig. 14 into the equivalent
volume of liquid water shows that bulk water loss could
not explain more than 60% of the pore volume that is created. Water loss must come from sources other than freewater, such as the decomposition of portlandite andhydrated calcium-silicate (CSH).
This simple calculation indicates that more than 40% of
the total porosity created and measured by MIP is associated with mechanisms other than bulk water loss during
the exposure of concrete to microwave heating. This trivial analysis illustrates further the intrinsic complexity ofporosity changes during the microwave heating of concrete, making a compelling argument for investigation ofporosity changes at the local scale, by direct observationof concrete texture.
Fig. 14 seems also to indicate that the higher the waterto cement ratio (w/c), the lower the contribution of water
loss to the increase in total porosity. This observation indicates that whatever phenomenon other than bulk water
loss is causing an increase in microwave-heated concrete
porosity, it is associated with the w/c ratio and its effect on
concrete microstructure, i.e. porosity. A more porous concrete sample is more prone to evaporation during microwave heating. If we assume the samples made with ahigher w/c ratio had less water in their pores (relative tosaturation) before treatment, then it makes sense that theevaporation of this type of water contributed less to pore
formation. It is also logical that these concretes were more

susceptible to other crack formation mechanisms related
to drying as they would dry faster and thus be affected bythese mechanisms sooner. The results also suggest that
there is no significant pore growth due to excessive porepressure as this would presumably occur more in the lower
w/c ratio samples due to their smaller pore volumes. This
does not mean that this phenomenon does not contributesignificantly to mechanical changes or aggregate liberation. The explosive spalling of some low a/c samples in
the first 5 seconds or so of microwave treatment (~100°C)
might suggest this is an important phenomenon in terms ofconcrete recycling, but it does not appear to be an important phenomenon in increasing sample pore volume.
Despite its limitations, the pore size distribution measured by MIP can give some appreciation of the evolutionof porosity within concrete samples with microwave heating. One example is given in Fig. 15 for concrete sample
S4. Bearing in mind the limitations of MIP measurement,
namely its sensitivity to the ink-bottle effect (Diamond,
2000), what the measurements confirm is that a connected
network of large pores, measured to be in the 1–100-μm
range, exists in all microwave-treated samples. MIP does
not measure this network in the untreated samples. Thisbehaviour was consistently found with all concrete samples tested. One possible explanation is that the connected
pores created by a short exposure are becoming larger as aresult of heat-induced shrinkage of the cement phase. Aninteresting observation is that MIP does not appear to see
noticeable changes below the 1-μm range between shortand long exposure.
Along with changes in porosity, concrete performanceis altered in a dramatic way by microwave heating. As
reviewed earlier in the paper, the liberation of aggregate
and cement was found to increase with exposure to microwaves. Analysis of microwave-heated samples using the
Hopkinson bar also revealed strong changes in mechanicalproperties. Fig. 16 shows the change in fracture force forthe 5 samples considered in this paper, as an illustration of
the embrittlement caused by microwave heating. Fracture256

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4. Effect of microwave heating on concrete:
local level results and analysis

Fig. 16

Hopkinson bar measurements of impact fracture force
on microwave-heated concrete samples (exposure timeoffset for clarity).

force is normalized by the fracture force for the untreatedsample, which takes value 100%. This allows a simple
assessment of the relative change in fracture force as afunction of microwave exposure.
It is consistently found that the relative fracture force
decreases continuously with increased exposure to
microwaves, possibly with the largest loss in mechanicalproperties occurring after the short exposure. These areinteresting observations, particularly in light of theknowledge that aggregate and cement liberation increases
most significantly after a long exposure to microwaves,as seen earlier in Figs. 1 and 2. These observations suggest that there is some embrittlement phenomenon that is
not effectively observed when using macro-scale measurement techniques, and there is not a direct link
between changes in mechanical behaviour and physicalliberation.
Overall, the macroscopic analysis has provided us withinteresting insights about the changes that occur insideconcrete during microwave heating, causing a change inmechanical behaviour, with a loss of resistance to impact
fracture that varies continuously with increased exposure,and an increase in liberation of both aggregate and cement
phases, albeit significant for the long exposure only. The
main change related to concrete microstructure is associated with porosity, which increases continuously with
exposure, as seen from both total porosity and pore size
distribution measured by MIP. The changes in mechanicalbehaviour seem to vary as per the changes in total porosity, and a link between porosity and physical liberation of
aggregates can be inferred.
The disparity between the evolution of physical liberation and mechanical properties with microwave exposure
illustrates the need to further understand the microwave-heating concrete-embrittlement mechanisms with alocal technique. For this work, image analysis of SEM
images was chosen.

As discussed in the preceding section, the changes inporosity that occur during microwave heating of concrete
are possibly numerous and complex, making the observation of porosity at the textural scale a compelling step
towards unravelling the mechanisms by which microwave
heating alters concrete. As will be shown here, textural
analysis of the structure of fracture porosity provides aninsightful angle on the mechanisms that take place insideconcrete as it is being heated by microwaves, with views
on recycling its elementary constituents.
Fig. 17 shows a superimposition of some highlighted
images of sample S1. It is noted that the same general pattern applies to all the concrete samples tested in this work,with differences in the magnitude of the observed changes.
Looking at the obvious changes in fracture porosity
between the images, Fig. 17 also validates the authors’
selection of the 4 characteristic times along the heatingprocess for the sake of quantifying the effect of microwave
heating on concrete texture.
–	Untreated concrete samples exhibit only few fractures, at both 40× and 200× magnification. Fractures
are essentially found around the aggregates, in theregion known as the interfacial transition zone (ITZ).
–	After the short treatment, the sample having beenheated for 15 seconds, a large-scale network of fractures appears, visible with the 40× magnification.
These fractures seem to form a network connecting
aggregate particles and also appear to run aroundthem, going through the entire sample texture. This
network is referred to as the “primary fracture network”. As it is associated with aggregate grain boundaries, the formation of this network is directly
associated with the liberation of aggregates.
–	When the concrete sample is further heated to themedium condition (30 seconds), fractures from theprimary network widen. Another network of smaller
fractures develops that invades the cement paste.
Because it appears to be nested within, and is of asmaller scale than the primary network of fractures, it
is referred to as the “secondary fracture network”.
–	At the long exposure (50 seconds), while the primary
network keeps widening, the quantity and length of thesecondary network fractures increases significantly.
These generic observations are visible with every tested
sample to a varying extent. From a range of observations
that were repeatedly made during this study, it was ascertained that a strong correlation exists between the properties associated with the primary network and the loss of
mechanical strength and liberation of aggregate particles.
The properties of the secondary network further explain
the mechanical changes but more importantly provide the257

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Fig. 17

Local observation of porosity changes with microwave treatment of S1.

Fig. 18 Variations in primary network fracture width withmicrowave treatment time.

Fig. 19 Variations in primary network length with microwave
treatment time.

link between textural liberation and physical liberation, as
measured by impact testing, specifically the fineness of thecement paste fragments after impact testing.
Because these networks correlate directly with the macroscopic properties of microwave-heated concrete samples
discussed in the previous section, their formation andgrowth are thought to hold the key to concrete recycling.
The following section is concerned with quantification ofboth primary and secondary fracture networks.

4.1 The primary fracture network

258

The primary network may be quantified in a number ofways. Accessible properties from two-dimensional images
include average properties such as total length, surface
area and crack branch number, and statistical properties
such as crack branch length and size distributions. As seenin Fig. 18, the width of primary network cracks increases
very rapidly with microwave exposure. Conversely, as
seen in Fig. 19, once the network is formed after a shortNicholas R. Lippiatt et al. / KONA Powder and Particle Journal No. 31 (2014) 247–264

Fig. 20 Comparison between physical liberation (Lippiatt andBourgeois, 2012) and textural liberation of aggregate
particles.

Fig. 21 Relative change in concrete strength, as measured by
the relative force at fracture as a function of the combined area of primary and secondary networks relative
to the cement paste area.

exposure, the length of the primary network is relatively
unchanged. What this indicates is that the fractures thatform this network widen with increased exposure, but do
not propagate significantly beyond the extent reached after
a short exposure to microwaves. The mechanisms associated with the change in thickness of primary-network fractures are deemed to be associated with drying shrinkage ofthe cement matrix. Because of the specific properties of
the ITZ with its high porosity, micro-fracturing and watercontent (Roy and Idorn, 1993), a strong local reaction to
microwave heating is bound to occur around the ITZ
during microwave heating, and the formation and growthof the primary fracture network is expected.
By definition, the primary network is associated withwhat was earlier defined as the textural liberation, which
accounts for the fraction of the aggregate perimeter that isliberated in the 2D analysis. Fig. 20 compares physicalliberation, as measured by acid dissolution, with texturalliberation. Because the work presented here spans a long
period of time, these measurements were not made on thesame samples, hence changes in sample properties may
contribute marginally to the observed differences. The
error bars represent the range of textural liberation values
from all the tested samples, the height of the bar representing the average value. The physical liberation values were
measured on 10 mm cubes (Lippiatt and Bourgeois, 2012).
Textural liberation is already significant with theuntreated sample. The high porosity of the ITZ, often withextensive micro-fracturing, is well documented (Roy and
Idorn, 1993). Using MIP, Roy and Idorn estimated values ofporosity in the ITZ as high as 37%. Mehta and Monteiro(Mehta and Monteiro, 2005) predict a high level of aggregate boundary fracturing from drying shrinkage during concrete heating, hence the observation of the primary network
formation during microwave heating is expected.
Fig. 20 shows that textural liberation reaches a very
high value after the shortest of the three measured microwave exposures, and it does not increase significantly after

that. Aggregates are highly liberated inside the concrete
texture after a short exposure to microwaves only. This is
an important piece of information from a processing
standpoint, as an increased duration of microwave heating
becomes directly an increase in energy consumption. Nevertheless, upon impact breakage testing, the aggregate particles remain trapped inside the cement matrix. Indeed, the2D analysis finds 70% of the aggregate boundaries being
liberated in the concrete sample for the short exposure,when only 15% of the aggregate is physically liberated
after single-particle impact breakage of a short-treatedsample. It is fair to conclude that single-particle impact
breakage cannot harvest the liberation induced by microwave heating. In other words, an alternate form of comminution is required to take advantage of the texturalliberation of aggregate particles.
Eventually, for the long exposure setting, the physicaland textural liberation of aggregates converge towards thesame value. This is explained by the secondary network
invading the cement phase, as intense fracturing of thecement phase is necessary for single-particle impact
breakage to yield liberated aggregates.
It was shown above that the strength of concrete decreased with microwave exposure, the same can be said ofconcrete stiffness. Textural image analysis showed an increase in the total crack length, total crack area and average crack width. This increase in crack width wassignificantly more pronounced in the primary network andspecifically the aggregate/cement paste interface fractures.
It is impossible to separate the effects of total fracture area
and aggregate interface crack width on the mechanicalproperties as these two values increase together during microwave heating, but it has been noted that concrete stiffness is largely dependent on the ITZ (Mehta and Monteiro,
2005). In this work stiffness is measured with Hopkinson
bar impact testing as defined by Tavares and King (Tavares
and King, 1998). Fig. 22 shows that as expected, the stiffness of the samples decreases rapidly with the increase in259

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Fig. 22 Change in concrete stiffness with aggregate interface
crack width.

Fig. 24 Number of branches per cement area in secondary network.

Fig. 23 Variations in secondary-network properties with microwave treatment time.

compatible with that required to capture the primary network, at a resolution of say about 10 μm per voxel. The
authors have started capturing tomographic images of
20-mm heated concrete samples, which confirm that the
primary network is a highly connected network that percolates through heated concrete samples. On the other hand,
capturing three-dimensional information about the secondary network is clearly more complex because the required
resolution must be of the order of a micrometer or less.
Nevertheless, the seemingly random occurrence of thisnetwork through the cement phase means that 3D properties of the secondary fracture network can possibly beinferred from 2D images using statistical means.

aggregate interface fracture width. The rate of change
slows at higher temperatures, presumably as once aggregate and cement paste is separated the stiffness becomes
dependent on the cement phase only, and increasing thesize of this separation has no further effect. Similarly, concrete strength has been linked with porosity, the textural
measure most analogous with porosity is the total crack
area which increases steadily with microwave exposureand shows a strong correlation with loss of concrete
strength and can be seen in Fig. 21. When comparedwith Fig. 19, it can be seen that the growth of the primary
network can not be responsible for the strength loss insamples that have experienced a longer treatment, because while strength continues to decrease, the increasein primary-network fracture length slows with further
microwave exposure.
Two-dimensional analysis of the fracture networks has
a limited scope for understanding the way by which theirproperties correlate with operating conditions and with re­cycling performance indicators. Having clearly establishedthat these fracture networks hold the key to concrete recyclability at the local scale, it appears that three-dimensional
observation and analysis is the next logical step. Currently, X-ray tomography has a resolution that is fully260

4.2 Analysis of the secondary network
The fracture network that forms during the microwave
heating of concrete has been divided in two. The primary
fracture network is associated with the aggregate grainboundary, and occurs with short exposure to microwaves,
whereas the secondary network occurs randomly in the
cement phase and spreads with increased exposure to
microwave heating. Just as for the primary network,
properties of interest of the secondary network include
average properties such as total length, surface area andcrack branch number, and statistical properties such as
crack branch length, nodes, ends and width distributions.
Contrary to the primary network fractures, Figs. 23, 24
shows that on average, cracks from the secondary network do not appear to grow wider with microwave treatment, but the total length and number of branches perunit area do increase with microwave heating time. The
crack branch length distribution follows a log-normal
distribution, as shown in Fig. 25, and does not change
significantly between samples nor with increased heating
duration. Put another way, the growth of individual fractures in the cement paste and the growth of the secondary
fracture network as a whole occur together and in constant proportion. This is not unexpected as once theNicholas R. Lippiatt et al. / KONA Powder and Particle Journal No. 31 (2014) 247–264

Fig. 26

Fraction of total crack length composed of secondary
network.

Fig. 25 Branch size distributions, secondary fracture network.
Top: for sample S2. Bottom: for samples S1 to S5.

cement paste is disconnected from the aggregate, shrinkage is no longer constrained. This distribution is directly
associated with the fineness of the fragments that form
after comminution of the microwave-heated concrete
samples. Additional research is required, however, inorder to correlate the topological properties of the secondary network to the size distribution of the fragments
obtained by comminution.
To finalise the discussion about the two fracture networks identified in this work, it was decided to take a lookat their relative significance on properties of relevance tothe recycling problem. As discussed earlier, the secondary
crack length increases with microwave exposure time, i.e.
with concrete energy absorption. Fig. 26 shows the variation between total secondary network crack length relative
to the total crack length and microwave exposure time.
Fig. 27 shows that while the total crack length increases
steadily with increased microwave exposure, the rate ofincrease of the secondary-network crack length is faster,and is the key player in the loss of mechanical strength of
microwave-heated concrete. As an illustration of this lastpoint, Fig. 28 shows the measured relationship between
the secondary network total crack length relative to thetotal crack length and the strength of the concrete samples
measured by HPB. The correlation is significant, withstrength dropping almost in linear proportion to theincrease in secondary network total crack length.

Fig. 27 Total combined crack length of primary and secondary
network.

Fig. 28

Relative change in fracture force with fraction of total
network length composed of secondary network.

5. Implications for development of a microwave­-based concrete recycling processThis work, through local analysis of changes in the
structure of porosity that occurs during the microwave
heating of concrete, has added additional evidence to thebody of existing knowledge about the potential value of
microwave heating for the development of a concrete
recycling process. The pattern of crack growth is evidenceof drying shrinkage as it is the only crack formation mechanism to occur over the entire temperature range observed.

261

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Importantly for concrete recycling, these results show thatmicrowave heating causes fractures to occur at the aggregate/cement paste interface, and importantly for energy
efficiency, these are the first microwave-induced fractures
to form. Also of note is the observation that the properties of individual concretes are relatively unimportant.
This will make the implementation of a microwave-based
concrete recycling process easier as it will not require ad­aptation to different waste sources.
The analysis of fracture porosity has shown that microwave heating interacts strongly with the ITZ to generate alarge-scale network of fractures at the aggregate/cement
paste interface. Experimental results indicate that this primary network of fractures forms with a short exposure to
microwaves. As previously stated, the most efficient
microwave generators for embrittlement are those withthe highest power output, however, this is based on theassumption that the key embrittlement mechanism isdifferential thermal expansion. It is still desired that theprocess is selective, and the higher the power of the
microwave generator, the faster heating occurs, the lessthat conduction can play a role and the more selective theprocess is. Therefore a high-power generator is most
likely still desirable but as dehydration appears to be thekey mechanism in the microwave processing of concrete
waste, one may expect the point at which increasing power
output is no longer economical is lower than it would be
for a similar application in mineral processing. In any casethe technology needs to be perfected and the appropriatecompromise found.
It was noted in a previous work (Lippiatt and Bourgeois,2012) that the liberation of aggregate particles is seen
only after extensive microwave treatment. This was measured using macro techniques, sample fracture then selective dissolution. Conversely, local techniques, i.e. SEM
inspection of treated samples used in this work, showthat fracture at the cement/aggregate interface occurs muchearlier in the treatment process. What occurs later under
extended microwave exposure is more extensive fracture
growth throughout the cement paste. This extended
cement crack growth greatly reduces the strength of theconcrete sample and causes the sample to break into muchsmaller fragments when crushed under impact. It wasdue to this fragmentation in the cement paste that liberation
was measured by impact fracture at such a high level for
long-treated samples in this previous work, rather than any
actual increase in the separation of the aggregate particles and cement paste.
The SEM results suggest that the aggregate and thecement were well separated, but unless an appropriate
mechanical comminution technique is selected, the aggregate samples will remain encased within larger cement
paste fragments. Development of an industrial solution
would also require identification of an appropriate commi-

262

nution process to exploit this primary network so as toclose the gap between physical and textural liberation withminimum energy consumption.
The above discussion considers optimisation of the liberation of aggregates, and ignores other important dimensions of the process, towards which results from this work
bring answers. Once comminution has taken place, a concrete’s aggregate and cement paste would have to be separated. One possibility that can be inferred from this work’s
results would be to induce a dense secondary fracture network by microwave heating prior to comminution in orderto generate cement fines, which could then easily be separated from liberated aggregates by dry screening. Moreover, reducing the cement paste to a fine powder would
help facilitate the recycling of the cement paste. From these
considerations, there is significant scope for developmentof a microwave-based recycling process, however, giventhat the microwave heating step is necessarily part of aprocessing chain that includes comminution, separationand transport, finding the right operating conditions isgoing to require additional research and development work.

6. Concluding remarks
The applicability of microwave heating to the recyclingof concrete is an important issue, given the increase indemand for concrete, the scarcity of natural aggregate
resources and the environmental footprint of clinker production. While a number of published works have shown
the potential of developing a microwave-based recycling
process based on macroscopic measurements relevant toconcrete recycling performance, namely aggregate liberation, product fineness and mechanical embrittlement, thiswork establishes links between fracture porosity andobserved macroscopic effects through local texture observation and analysis.
The work associates the formation of two fracture networks with specific recycling issues:–	The primary fracture network is constituted of large
connected fractures that are associated with the aggregate grain boundaries, and occurs with short exposure
to microwaves. This network, by essence, is responsible for the textural liberation of aggregates. The primary network appears to occur at the early stage of
microwave heating.
–	The secondary network is constituted of seemingly
randomly occurring cracks which spread through thecement phase with increased exposure to microwave
heating. This dense network of smaller fractures isstrongly linked to the loss of mechanical strength of
concrete, and the degree of actual physical liberationof aggregate particles obtained after impact fractureof microwave heated concrete samples.

Nicholas R. Lippiatt et al. / KONA Powder and Particle Journal No. 31 (2014) 247–264

Mechanisms responsible for the formation and growthof both primary and secondary fracture networks areundoubtedly complex, but the evidence from this work
indicate that they are controlled by local drying shrinkage,
which starts at the interfacial transition zone around aggregate particles and eventually spreads throughout the bulkof the cement matrix.
Capitalising on the high degree of textural liberationof aggregate particles obtained after a short microwave
heating time only, meaning lower energy consumption,requires identification of a suitable comminution solution.
The inefficiency of single-particle impact fracture to physically liberate aggregate particles that were texturally liberated suggests that impact-based comminution equipment
is not the best option. It is thought that shear-inducing
comminution technologies such as high-pressure grindingrolls should be investigated in conjunction with microwave heating.
The longer exposure to microwaves, however, yields
extensive growth of secondary network fractures in the
cement matrix and subsequent production of cement fines
through comminution. Increased cement fines may bevaluable for the separation of aggregates from cement andrecycling of the cement itself as part of the overall recycling scheme.
In the end, it can be concluded that finding the best position and operating conditions for the microwave heating
step in the concrete recycling chain is not a clear-cut situation. The setting of the microwave heating process to growthe primary and secondary fracture networks to a specificlevel depends on the subsequent process steps, including
comminution, product separation and possibly transport.
Having looked at the local scale, one important conclusion from this work is that development of a microwave-based concrete recycling process must consider theprocessing chain in its entirety.

Acknowledgements
The authors acknowledge the financial support of the
Agence Nationale de la Recherche (the French National
Research Agency) through the COFRAGE project from the
ECOTECH research programme. The authors want toacknowledge Dr. Emmanuel Cid, Senior Research Scientist
with the Laboratoire de Génie Chimique, for his valuable
contribution to the image analysis of the fracture patterns.

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Author’s short biography
Nicholas Lippiatt
Nicholas Lippiatt holds a masters in materials science (France) and completed hisbachelor’s degree in materials engineering at the University of Queensland in Brisbane,
Australia. He is currently completing a Ph.D. in materials science (Laboratoire de Génie
Chimique, Institut National Polytechnique de Toulouse) in France on the use of microwave heating technology for concrete recycling.

Florent Bourgeois
Prof. Bourgeois holds a B.Eng. in materials science (France) and a Ph.D. in extractive
metallurgy (University of Utah). He worked as a research fellow for the CRC Mining(Australia) from 1994 to 1996, and as a lecturer in minerals processing with the University of Queensland from 1997 until 2000. Between 2001 and 2005, he worked as project
leader for the French Geological Survey’s processing department. He now holds a tenured
position at the University of Toulouse. His field of expertise is particulate process design
and modelling, with emphasis on comminution, liberation, texture modelling, sampling ofminerals and wastes.

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KONA Powder and Particle Journal No. 31 (2014) 265–270/Doi:10.14356/kona.2014017

Original Research Paper

Numerical Prediction of the Bulk Density of GranularParticles of Different Geometries †Kasra Samiei *, Girma Berhe and Bernhard Peters
1

Research Group in Engineering Science, Faculty of Science, Technology and Communication, University of Luxembourg, Luxembourg

Abstract
The Discrete Element Method (DEM) is increasingly used to simulate the motion of granular material inengineering devices. The most widely used shape to model granular particles is the sphere due to its simplicity
which facilitates computations. However, with increasing advancement and popularity of the DEM approach, amore accurate representation of real granular shapes is becoming intensely important. This paper is an attempt topredict the bulk density of granular particles of cylindrical shape by DEM. The method used to model tube-likeparticles is the composite method where the tube-like particle is composed of a number of spherical sub-shapes. The
results show that the DEM prediction of the bulk density of tube-like particles were accurate provided that asufficient number of spherical sub-shapes was used to construct the particle. In addition, the bulk density of granularparticles in the shape of 32-face polyhedrons was also investigated. It was shown that 32-face polyhedrons can beapproximated as spheres provided that the rolling resistance of the shape is taken into consideration.
Keywords: bulk density, DEM, numerical analysis, granular matter, particle shape

1. Introduction
Granular materials are complex systems of a large number of particles of various sizes, shapes and materials.
Under different circumstances they reveal different behavior such as solid-, liquid- or gas-state behavior. In fact, thescience of granular flow is not yet as well understood andwell developed as other classes of materials (Pöschel and
Schwager, 2005; Campbell, 2006). In order to predict andoptimize the behavior and motion of granular matter inengineering devices, numerical simulation tools are
increasingly employed (Cleary, 2004). The continuous
increase in computing power is now enabling researchers
to implement numerical methods that deduce their global
characteristics from analyzing the individual behavior ofeach grain. This forms the foundation of the Discrete Element Method (DEM) which is, to date, the leading
approach to simulate the dynamics of granular media.
However, predicting the behavior of such a complex
physical system by computer models has its own challenges. One of the main challenges of DEM is in modelingthe complex shapes which the granular particles often
exhibit in reality. The most widely used particle shape in†
1*

Accepted: August 22, 2013
L-1359, Luxembourg
Corresponding author:
E-mail: kasra.samiei@unileoben.ac.at
TEL:+43-3842-402-5821 FAX: +43-3842-402-5802©2014 Hosokawa Powder Technology Foundation

DEM is the sphere due to its simplicity. With increasing
advancement and popularity of the DEM approach, theexpectations of its capabilities rise, too. More realistic
modeling of granular particles of various geometries is
becoming increasingly necessary.
Different methods already exist to model complex
shapes in DEM which will be briefly noted here. Morecomplete reviews of different methods in DEM to model
non-spherical shapes are reported by Hogue (1998),
Latham and Munjiza (2004), Haff (1993) and Ristow(1994).
One approach is to model the complex shape as a cluster of spherical sub-shapes. Different variations of theso-called composite method can be found in the literature.
The sub-shapes can be connected to one another bydamped springs (Buchholtz and Pöschel, 1994; Pöscheland Buchholtz, 1993; Maeno, 1996; Lu and McDowell,2007), or else the aggregate shape can be considered as
rigid (Gallas and Sokolowski, 1993; Nolan and Kavanagh,
1995; Mutze, 2006). The sub-shapes used to construct thecomplex shape might also overlap each other. The subshapes do not necessarily need to be spheres; for example,
triangular sub-shapes have been developed which are useful
to model shapes with sharp edges (Pöschel and Buchholtz,
1995), and arc sub-shapes can be used to construct oval
shapes (Wang et al., 1999). Another approach to model
non-spherical shapes is to address the shape as it is anddevelop analytical methods for the detection of contacts.
Such analytical methods are already developed for some265

Kasra Samiei et al. / KONA Powder and Particle Journal No. 31 (2014) 265–270

Table 1

Mechanical and contact properties used in the DEM analysis
unit

spherical
particles

container

tubularparticles

container

polyhedral
particles

container

density

kg/m3

1350

2520

1350

1350

1350

1350

Young’s modulus

N/m2

3.38 × 108

72 × 109

3.38 × 107

3.38 × 107

3.38 × 108

3.38 × 108

Poisson’s ratio

–

0.41

0.22

0.41

0.41

0.41

0.41

contact property coefficientunit

particles

particle/wallparticles

particle/wallparticles

particle/wall

restitution

–

0.8

0.85

0.8

0.8

0.8

0.8

sliding friction

–

0.5

0.5

0.5

0.5

0.5

0.5

rolling friction

–

0.001

0.001

0.001

0.001

0.00160.0016mechanical property

shapes such as ellipsoids (Lin and Ng, 1995; Lin and Ng,
1997; Allen et al., 1989; Perram et al., 1984; Perram andWertheim, 1985; Ouadfel and Rothenburg, 1999; Johnson
et al, 2004) and polyhedrons (Cundall, 1988; Zhao et al.,2006). Superquadrics are also proposed (Barr, 1981) andused in DEM studies, e.g. superellipsoids (Wellmann etal., 2008; Cleary et al., 1997). A different method is thevirtual space method where the space is divided into discrete voxels (Munjiza, 2004; Jia and Williams, 2001).
Each particle takes up some space in the digitized space forwhich the corresponding voxels would be identified. Twoparticles are in contact if they both occupy the same voxel.
Each of these methods has its own advantages and disadvantages but a common challenge remains the computational costs and complexity of modeling complex shapes.
The most widely accepted method, at least in commercial
software, is the composite approach. However, according
to Kruggel-Emden et al. (2008), the validity of the method
has not been sufficiently tested and verified. This paper,
therefore, is an attempt to further study the validity of thecomposite approach and to investigate its capabilities andlimitations.
The application chosen to verify the method is thepoured bulk density of granular particles. The dependencyof the bulk density on the shape of the individual particles
has long been recognized (Riley and Mann, 1972; Fonneret al., 1966; Ridgway and Rupp, 1969), which makes thecase suitable for validating the composite method.

2. DEM study
Specific boundary conditions for the DEM study arepresented for each case in Table 1. The friction and restitution coefficients are based on simple lab tests conductedon sample particles, and are verified by the available datain the literature (Engineers handbook; Engineering toolbox; Bennett and Meepagala, 2006; Beardmore, 2012).
The time step was fixed at 10–5 and the end time of the266

simulation was set to 8 seconds when all particles come torest and the kinetic energy tends to zero. Since the size ofthe container in all simulations and experiments was chosen to be identical, it suffices to compare the height of thepacked bed. The height of the packed bed is calculated as
the distance of the highest point of the packed bed after
complete settlement to the bottom of the container. It is
worth noting that the height of the packed bed in eachexperiment reported here is not comparable because ineach case, a different number of particles and sometimes
different size of container is used. The objective is therefore to compare the numerical results with the experimentsin three independent cases presented in Table 1.
The rolling friction is included in order to account for the
resistance of the spheres against rolling due to small deviations from the spherical shape. An assumption taken regarding the shape of the tube-like particles is that the hollownessof the tubes was neglected in the DEM study, i.e. the particles were assumed to be full. The explanation is that thehollowness of the tubes does not affect the packing of theparticles for small hole diameters because other particles
cannot penetrate through the inner hole or the penetration is
negligible. Another simplifying assumption is made regarding the Young modulus of the moving particles, whereas theYoung modulus is reduced one order of magnitude from theoriginal value. Conducting a sensitivity analysis confirmed
the findings of several other studies (Kawaguchi et al.,
1997; Ketterhagen et al., 2007; Ketterhagen et al., 2005;
Tuley et al., 2010; Hogue and Newland, 1994; Pérez, 2008;
Silbert et al., 2001; Kruggel-Emden et al., 2007) that lowering the stiffness within a certain range does not affect theresults of the DEM simulation. This is due to the fact that
although changing the stiffness constant does affect the
duration of a single collision, the velocity and trajectory of
the particle after the collision is only dependent on thecoefficient of restitution and the coefficients of friction.
However, the particle’s hardness should be large enoughso that the maximum overlap does not exceed the particle’s radius, in which case the particles pass through eachKasra Samiei et al. / KONA Powder and Particle Journal No. 31 (2014) 265–270

Fig.   1 Experimental and numerical results of the packing behavior of spherical particles.

Fig.   2 Experimental and numerical results of the packing behavior of tubular particles.

other. Without this assumption, the time step should havebeen reduced to accurately resolve the impact of small
sub-shapes used to construct the tubular particles. This
assumption is therefore necessary to reduce the high computational costs of the simulation of tube-like particles. The
tube-like particles are modeled by the composite method asan aggregate of spherical sub-shapes. In this case, each tube
is represented by 20 spheres which cluster and form thecylindrical shape. The same coefficient of rolling friction as
spheres is assigned to the cylinders when they roll aroundthe principal axis of rotation.
The 32-face polyhedrons used in the experimental study(Gan et al., 2004; Jia et al., 2007) are quite similar inshape to spheres and are therefore represented by spheresin this work. The coefficient of rolling friction is raisedslightly for the polyhedral particles because their divergence from perfect spheres is an intrinsic characteristic of
the shape. The diameter of the representative sphere canbe taken as either the outer or inner diameter of the polyhedron. Both assumptions are considered in this study. The
outer diameter of the polyhedron is defined as the diameterof the smallest sphere which can be drawn that contains
the whole polyhedron. Alternatively, the inner diameter ofthe polyhedron is defined as the diameter of the biggest
sphere which can be drawn that will be fully contained
inside the polyhedron. The outer diameter of the 32-facepolyhedron used in this study is 8.2 mm and the innerdiameter is 7.5 mm. Similar to the tube-like particles, thehollowness of the polyhedral particles is neglected and thespheres are assumed to be full.

results of the digital approach applied by Gan et al. (2004)
and Jia et al. (2007) based on the method of virtual spaceare presented. In their method called DigiPac, a particle isjust a coherent collection of digitized pixels which are
stored as integers or bits. Although DigiPac is able tomodel particles of arbitrary shapes, consideration of particle interactions is limited to their geometric constraints.
As an initial validation case, the packing behavior of 660
spheres was predicted by DEM. Validation of the simple
case of spheres is necessary before advancing to more complex particle geometries. The results, demonstrated in Fig. 1,
show that DEM prediction of the bulk density of sphericalparticles is in agreement with the experimental results.
The results of the prediction of the bulk density of tubular particles are shown in Fig.  2. Despite the slightover-prediction of the height of the packed bed, the DEM
prediction of the bulk behavior of the tube-like particles
is quite acceptable. The small error can be explained by
the approximation of the tube-like shape as a cluster ofspheres in the DEM study.
Fig. 3 shows the prediction of the bulk behavior of polyhedral particles. It is evident that the inner diameter approximation is a good approximation and provides results inquite good agreement with the experimental results. On theother hand, the outer diameter approximation does not yielda good approximation of the polyhedral shape.

3. Results
The results of the DEM study are presented in this section along with the corresponding experimental results tovalidate the numerical approach. Also for comparison, the

4. Conclusions
DEM modeling of granular grains of complex shapes isstill a young research topic. This study is an attempt toverify the most commonly used method to model
non-spherical shapes, i.e. the composite method. The
composite method is used to predict the bulk density
behavior of granular particles of cylindrical geometry.
The numerical results are compared with a digital

267

Kasra Samiei et al. / KONA Powder and Particle Journal No. 31 (2014) 265–270

Fig.   3 Experimental and numerical results of the packing behavior of 32-face polyhedral particles approximated in a
DEM study by spheres with either inner diameter orouter diameter of the polyhedron.

method called DigiPac applied by Gan et al. (2004) andJia et al. (2007). The results of both methods are comparedwith the experimental results provided by the sameauthors. The comparison verifies the competence of thecomposite method in predicting the bulk density of cylindrical particles. The capabilities of the DigiPac method
has already been discussed in the author’s work and is notrepeated here. In addition to cylinders, the bulk density of
32-face polyhedrons is also investigated and it is verified
that a 32-face polyhedron can be approximated by a spherewith a diameter being the inner diameter of the polyhedrons. Future work should attempt to predict the bulk
behavior of other geometries such as conical, cubic andellipsoidal particles.

Acknowledgements
Experiments presented in this paper were carried out
using the HPC facility of the University of Luxembourg.

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Author’s short biography
Kasra Samiei
Kasra Samiei graduated from Amirkabir University of Technology, Tehran, Iran as amechanical engineer specialized in solids design. He later completed his master’s degree
at the University of Boras, Sweden in “waste management and resource recovery technology”. He holds a Ph.D. in engineering science from the University of Luxembourg. His
main research focus is on computational granular dynamics in conjunction with computational fluid dynamics. He is currently a post-doctoral researcher at the University of
Leoben, Austria.

Girma Berhe
Girma Berhe received his bachelor’s degree in computer science (1996), and master’s
degree in information science (2001), both from Addis Ababa University, Ethiopia, and a
Ph.D. in computer science (2006) from INSA de Lyon, France. He worked as a post-doctoral researcher from December 2006 to November 2007 in Institut National Polytechnic
de Toulouse, France. He also worked as a senior researcher in the Faculty of Science,
Technology and Communication, University of Luxembourg, from January 2008 to
February 2011. His current research interests include distributed and high-performancecomputing, autonomic computing and mobile computing. He has published several journal papers and peer-reviewed international conference papers.

Bernhard Peters
A graduate in mechanical engineering (Dipl.-Ing.) and with a Ph.D. from the Technical
University of Aachen, Bernhard Peters is currently head of the thermo-/fluid dynamics
section at the University of Luxembourg and an academic visitor to the Lithuanian
Energy Institute. After being a post-doctoral research associate at the Imperial College ofLondon, he established a research team dedicated to the thermal conversion of solid fuels
at the Karlsruhe Institute of Technology (KIT), and worked thereafter in industry at AVL
List GmbH, Austria. His research activities include thermo-/fluid dynamics, in particularmulti-phase flow, reaction engineering, numerical modeling, high-performance computing
and motion and conversion of particulate materials.

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KONA Powder and Particle Journal No. 31 (2014) 271–272/Doi:10.14356/kona.2014023

Infomation Article

The 47th Symposium on Powder Technology and the Ceremony
for the 20th Anniversary of Establishmentof Hosokawa Powder Technology Foundation
The 47th Symposium on Powder Technology was held together with the Ceremony for the 20th Anniversary of
Establishment of Hosokawa Powder Technology Foundation at the Imperial Hotel Osaka, Japan on Tuesday,
September 3, 2013. They were organized by Hosokawa Powder Technology Foundation with the sponsorship ofHosokawa Micron Corporation and the latter as one of special events of the Foundation. Over 200 people from theindustries and academic organizations attended these events and had many discussions.
The theme of this symposium had been directly related with nanoparticles and nanotechnology since 2001 till lastyear for more than ten years but this time it has widened the range to the powder technology supporting the pioneering technology as well as the fundamentals in the fields of pharmaceuticals, ceramics, coal powder and composite
materials as well as from the aspects of advanced simulation and powder processing machines without restricting to
only the nanoparticles.
In the Ceremony for the 20th Anniversary of Hosokawa Foundation after the Symposium on Powder Technology,
the Hosokawa Powder Technology Fellowship Supporting Award was presented by the Foundation president,
Mr.Yoshio Hosokawa to six brilliant younger researchers in the field of powder technology. Following this presentation, Dr.Komiyama, the Chairman of Mitsubishi Research Institute and president emeritus of University of Tokyo,
gave the special lecture on the revitalization for Japan.

Part I The 47th Symposium on Powder Technology
Theme: Progress of powder technology supporting the pioneering technology to the fundamentals
Opening address

Prof. Hiroaki Masuda,Prof. emeritus of Kyoto Univ.

Session 1 Chaired by Prof. Ko Higashitani, Prof. emeritus of Kyoto Univ.
Lecture 1“Studies on novel pharmaceutical preparations based onparticulate design”

Prof. Hirofumi Takeuchi,
Gifu Pharmaceutical University

Lecture 2“Microstructure design of ceramics by controlling thedispersion of fine particles in a liquid, and the applicationof the design technique to fabricate novel materials”

Dr. Tetsuo Uchikoshi,
National Institute for Materials Science

Lecture 3“Particle composite and microstructure control process
and their application”

Prof. Junichi Tatami,
Yokohama National University

Session 2 Chaired by Prof. Makio Naito, Osaka Univ.
Lecture 4“Progress of simulation for particles behavior and its
application to powder processing”©2014 Hosokawa Powder Technology Foundation

Prof. Junya Kano,
Tohoku University271Lecture 5
Powder technology for the development of advanced
coal utilization power plant contributing to the energy
security and environmental protection”

Dr. Hisao Makino,
Central Research Institute of ElectricPower Industry

Lecture 6“The latest powder technology for enhancing thefunctional capability of fine particles”

Mr. Masahiro Inoki,
Hosokawa Micron Corporation

Part II	Ceremony for the 20th anniversary of establishment of Hosokawa Powder
Technology Foundation
Mr. Yoshio Hosokawa,
President of Hosokawa Powder
Technology Foundation

Speech of the president
Presentation ceremony for the fellowship supporting award
Special lecture “The Revitalization for Japan—Innovation to realize the Platinum Society”

Dr. Hiroshi Komiyama,
Chairman of the Institute, Mitsubishi
Research Institute, Inc.,
President emeritus, University of Tokyo

Closing address

Mr. Kiyomi Miyata,
President of Hosokawa Micron
Corporation

Symposium on Powder Technology with more than 200 participants

Presentation ceremony for the fellowship supporting award

272

KONA Powder and Particle Journal No. 31 (2014) 273/Doi:10.14356/kona.2014024

Infomation Article

The 20th KONA Award
Dr. Hirofumi Takeuchi, Professor of Gifu Pharmaceutical University (GPU), was selected as the winner of the20th KONA Award, which is sponsored by Hosokawa Powder Technology Foundation and given to the scientist(s)or group(s) who have achieved distinguished research works in the field of particle science and technology.
He received his B.S. (1979), M.S. (1981) and Ph.D. (1984) in pharmaceutical sciences from Kyoto University. He
joined GPU as a faculty member in 1984, and became Lecturer in 1988 and associate professor in 1991. He spent
1 year as a visiting scientist at Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, in 1989–
1990. He is now Professor of GPU (2005–present). He served as the director of department of pharmaceutical sciences (2008–2010) and the dean of graduate school in GPU (2010–2012), and now he is the dean of GPU
responsible for all students (2012–present).
He is now keeping a board member in several scientific societies such as the vice president of The Society of
Powder Technology, Japan, and a member of the board of directors of The Academy of Pharmaceutical Science andTechnology, Japan, and so on. He was also a member of Board of Scientific Advisors in Controlled Release Society(CRS) (2010–2012).
Dr. Takeuchi has made a great scientific contribution in the field of pharmaceutical technology based on powder
and particle technology. His works are concerned with preparing new dosage forms of drugs in several administration routes such as oral, parenteral, pulmonary and ophthalmic. The common research concept in his research fordosage form development is “particle design”, which means preparations of functional particles for highly effective
drug delivery.
He has reported several types of surface modified liposomes having pharmaceutical functions for drug delivery. It
has been demonstrated that mucoadhesive liposomes can facilitate absorption of peptide drugs in oral or pulmonary
administration by prolonging the retention time of the device at the objective part in the body. Recently the liposomal
systems with optimally designed were found to deliver drugs into the posterior part of the eye with a simple eye drop
administration. The research for developing these drug carriers has been highly evaluated because they are promisingtools to develop the non-invasive drug therapy as an alternative method to an invasive method, injection.
Particle design research is also applied to oral solid dosage form design and its preparation process. These investigations contributed to development of a novel preparation method of rapidly oral disintegration tablet, which is oneof the most interesting patient oriented dosage forms, by controlling the particle size of binder or preparing composite particles of excipient with fine silica particle for the tablet formulation. To complete these technologies, several
basic researches regarding to granulation, tabletting and grinding have been conducted.
So far, the number of published original papers in these research fields is 245 and that of reviewed papers, bookchapters and related articles is totally 100.
On March 6th , 2013, Mr. Yoshio Hosokawa, President of the Foundation, handed the 20th KONA Award to Dr.
Takeuchi at the presentation ceremony held at Hosokawa Micron Corporation in Hirakata.

©2014 Hosokawa Powder Technology Foundation

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Information Article

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