Journal of Minerals and Materials Characterization and Engineering, 2013, 1, 285-292
Published Online November 2013 (http://www.scirp.org/journal/jmmce)
Open Access JMMCE
Use of Mineral Liberation Analysis (MLA) in the
Characterization of Lithium-Bearing Micas
Dirk Sandmann1*, Jens Gutzmer1,2
1Department of Mineralogy, TU Bergakademie Freiberg, Freiberg, Germany
2Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany
Received September 17, 2013; revised October 20, 2013; accepted November 2, 2013
Copyright © 2013 Dirk Sandmann, Jens Gutzmer. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The capabilities and opportunities of the application of automated mineralogy for the characterization of lithium-bear-
ing zinnwaldite-micas are critically assessed. Samples of a crushed greisen-type ore comprising mostly of quartz, topaz
and zinnwaldite (Li-rich mica) were exposed to further comminution by cone crusher and high voltage pulse power
fragmentation. Product properties were analyzed by using a Mineral Liberation Analyser (MLA) and the obtained min-
eralogical and mineral processing relevant parameters were carefully evaluated with special focus on the characteristics
of zinnwaldite. The results illustrate that both samples contain a significant quantity of very fine particles that are prod-
ucts of comminution. The modal mineralogy in the different sieve fractions is characterized by the accumulation of
minerals of low hardness in the finest fraction and the enrichment of topaz, having a high hardness, in the somewhat
larger fractions. Based on the results of mineral association data for zinnwaldite, a displacement of the muscovite-quartz
ratio, in comparison to the results of modal mineralogy, was observed by indicating good quartz-zinnwaldite boundary
breakage and weak muscovite-zinnwaldite breakage. Liberation as well as mineral grade recovery curves indicate that
fraction -1000 to +500 µm is most suitable for beneficiation. The results of this study demonstrate that SEM-based im-
age analysis, such as MLA, can effectively be used to investigate and evaluate phyllosilicate minerals in a fast and pre-
cise way. It is shown that the results of MLA investigations, such as modal mineralogy, are in good agreement with
other analytical methods such as quantitative X-ray powder diffraction.
Keywords: Mineral Liberation Analysis; Zinnwaldite; Conventional Comminution; High Voltage Pulse Power
Comminution is one of the most energy intensive, and
thus most costly processes in industrial mineral proc-
essing. As energy costs continue to rise, comminution
can compromise the profitability of a mining operation.
Innovative concepts for energy-efficient comminution
are therefore of great relevance. Comminution by high
voltage pulse power fragmentation is such a novel con-
cept that may be considered. Recent studies by Wang 
illustrate that this technology, in certain cases, can be
more energy-efficient compared to conventional me-
However, particle size reduction is only one tangible
attribute to be achieved by comminution. Liberation of
ore minerals is a second parameter that is of equal inter-
est and that cannot be neglected. The present study de-
scribes the degree of liberation and particle/mineral grain
size distribution achieved from samples treated with high
voltage pulse power fragmentation as well as conven-
tional mechanical comminution. Automated mineralogy,
using a Mineral Liberation Analyser [2,3], was used to
quantify liberation and other tangible particle and min-
An example of coarse-grained and isotropically tex-
tured raw material was selected for the experimental
study. This material is originated from the Zinnwald Sn-
W-Li greisen deposit and contains zinnwaldite, next to
quartz, topaz as well as minor cassiterite, wolframite, and
fluorspar. Zinnwaldite, a Li-rich mica and main com-
modity of interest in this study (as a potential ore min-
eral), ranges up to 5 mm in grain size .
Lithium is an emerging commodity because of its im-
D. SANDMANN, J. GUTZMER
portance in energy storage systems (e.g., Li-ion batteries).
Future demand for lithium is set to increase rapidly,
mainly due to the continuous growth of world automo-
bile market, rising prices for crude oil and the resultant
increasing demand for lithium-ion batteries . In 2011,
about two thirds of global lithium production came from
surface brine deposits (e.g., from Chile, China and Ar-
gentina) and one third from hard-rock silicate ores. In the
latter case, spodumene-bearing pegmatites are the domi-
nant source of Li-bearing hard-rock silicates, with Green-
bushes (Australia) and Bikita (Zimbabwe) as prominent
Li-bearing micas, namely lepidolite and zinnwaldite,
currently have very limited economic significance in
lithium production as they are mined only in Portugal
and Zimbabwe. However, due to their wide distribution
and abundance, such Li-bearing mica may well become
an attractive proposition, if the demand for lithium will
indeed increase as predicted. It appears thus imperative
to define and optimize technological approaches to liber-
ate and concentrate Li-bearing mica .
Synopsis of the Zinnwald Deposit
The historic Zinnwald deposit, located in the Eastern
Erzgebirge/Východní Krušné hory, straddles the Saxon
(Germany), Bohemian (Czech Republic) border. Tin min-
ing took place there from the 16th century to the 1940s
(German part) resp. 1990 (Czech part). From the mid-
19th century, tungsten was mined and from 1869 to 1945
lithium-bearing mica concentrates were produced. Dur-
ing this period, Zinnwald was one of the few Industrial
sources of lithium globally. At present, the German side
of the deposit is explored by the Solarworld AG.
The Zinnwald deposit is classified as a greisen-type
orebody . This orebody is located in a fluorine-rich
granitic stock intruded into Palaeozoic rhyolites. The
highly altered granites host a series of lens-like Li-Sn-W-
bearing greisen bodies consisting mostly of quartz, zinn-
waldite, topaz and minor fluorite as well as vein-style
Sn-W mineralization .
The lithium content of the greisen deposit is solely
hosted in a series of mica named zinnwaldite (Formula:
KLiFe2+Al(AlSi3O10)(F,OH)2) extending in composition
from the mineral siderophyllite (KFe2+
(OH)2) to polylithionite (KLi2Al(Si4O10)(F,OH)2). Zinn-
waldite from the Zinnwald deposit is available as a can-
didate reference sample (Zinnwaldite ZW-C), and ac-
cording to , has an average Li2O content of 2.43 wt%
(n = 44).
The material for this study was part of a large bulk sam-
ple of approximately 4 metric tons that was taken from a
greisen body during a pilot project to the current explora-
tion program by Solarworld AG. The entire bulk sample
was crushed at the UVR-FIA GmbH, Freiberg, using a
jaw crusher with a gap width of 35 mm. The resultant
product was homogenized and split up in two representa-
tive subsamples at the Department of Mechanical Process
Engineering and Mineral Processing of the TU Berg-
akademie Freiberg. The entire process is illustrated in
2.1. Conventional Comminution Procedure
The first representative subsample was passed through a
Figure 1. Flowchart of the sample processing during this study (Note: sieve fractions are given in µm and the related cumula-
tive distribution Q3(x) in %).
Open Access JMMCE
D. SANDMANN, J. GUTZMER 287
short-head cone crusher with a product size of 4 mm at
the Department of Mechanical Process Engineering and
Mineral Processing of the TU Bergakademie Freiberg. A
representative subsample was taken and sized into seven
sieve fractions (Figure 1), used for Mineral Liberation
2.2. High Voltage Pulse Power Technology
A second subsample of crushed greisen was used as
educt for high voltage pulse fragmentation. A SELFRAG
lab instrument [1,9,10], installed at the Department of
Geology, TU Bergakademie Freiberg, was used for this
purpose. The following instrument settings were used:
voltage of the output impulse generator 150 kV, pulse
frequency 3.3 Hz, and working electrode gap 10 to 40
mm. An amount of 2 kg was processed using the
SELFRAG instrument feed sieve of 4 mm and on aver-
age 200 - 300 pulses. The product of high voltage pulse
fragmentation was classified into six sieve fractions
(Figure 1) for MLA analysis.
2.3. Mineralogical and Microfabric Analysis
All 13 subsamples were prepared as polished grain
mounts at the Department of Mineralogy, TU Berg-
akademie Freiberg. Great care was taken to avoid pre-
ferred orientation of the zinnwaldite mica that tends to
form thin plates on fragmentation. Several steps of sam-
ple preparation as described by Jackson  were con-
ducted including random subsampling by a rotary riffler,
mixing the sample with crushed graphite and mechanical
shaking of the mixture in cylindrical plastic moulds.
Quantitative studies of mineralogy and microfabric
were performed at the Department of Mineralogy, TU
Bergakademie Freiberg, using a FEI MLA 600F system
[2,3,12]. The scanning electron microscope FEI Quanta
600F is equipped with a field emission source (FEG) and
two SDD-EDS X-ray spectrometers (Bruker X-Flash)
combined with Mineral Liberation Analysis (MLA) soft-
ware. The polished grain mounts were carbon-coated
prior to measurement to obtain an electrically conducting
surface. The samples were analyzed with a grain X-ray
mapping measurement mode (“GXMAP”) at a magnifi-
cation of 175 times and a X-ray mapping threshold for
back scattered electron (BSE) image grey values of 25.
The analytical working distance was 10.9 mm, the emis-
sion current 190 µA, the probe current 10 nA and the
overall electron beam accelerating voltage 25 kV. Stan-
dard BSE image calibration was set with epoxy resin as
background (BSE grey value <25) and gold as upper
limit (BSE grey value >250). See further detail to MLA
measurement modes in .
3. Results and Discussion
The results of MLA measurements provide a broad range
of mineralogical and processing parameters [2,3]. The
most relevant parameters for the evaluation of effective-
ness of conventional as well as high voltage pulse power
treatment are presented hereinafter.
It should be noted that systematic errors can be in-
duced by sample preparation and MLA analysis methods.
As it is difficult to quantify them, a precise sample pre-
paration, which comprehends and minimizes preparation
problems, is needed to scale down the systematic errors
3.1. Particle Size Distribution/Mineral Grain
The results of particle size distribution of the combined
data for all size fractions show a minor amount of top
sized material and a larger quantity of finest material for
both the conventional comminution subsample as well as
the high voltage pulse power subsample (Figure 2(a)).
The same applies to the zinnwaldite grain size distribu-
tion which shows nearly the same distribution as the cor-
responding particle sizes (Figure 2(b)). It must be noted
Figure 2. Particle size distribution (a) and zinnwaldite min-
eral grain size distribution (b) of the combined data for all
size fractions for the conventional comminution subsample
and the high voltage pulse power fragmentation subsample.
Open Access JMMCE
D. SANDMANN, J. GUTZMER
that the sizes obtained by the mineral liberation analysis
are measured in 2D using the equivalent circle diameter
of the particle respectively grain area. These 2D gener-
ated size data give in general a smaller size in compari-
son to 3D data. In spite of this obvious limitation it has
been shown by a recent study that size data measured by
image analysis systems are in general in good agreement
to other size distribution measurement systems .
3.2. Modal Mineralogy
The data of modal mineralogy obtained by this MLA
study corroborate previous results of transmitted-light
microscopic studies [15-17]. Light-microscopic observa-
tions of polished thin sections showed that zinnwaldite
and quartz are usually coarse-grained with mineral grain/
aggregate sizes of 5 - 6 mm. Topaz mineral grains are
ordinarily somewhat smaller (up to 1 mm).
Main constituents of the two subsamples analyzed here
are quartz, zinnwaldite, and topaz. Further minerals in
minor portions are muscovite, kaolinite, fluorite, hema-
tite as well as in small quantities (each <0.1 wt%) barite,
crandallite, cassiterite, dolomite, columbite, scheelite,
monazite, zircon, xenotime, florencite, siderite, cerphos-
phorhuttonite, gypsum, apatite, wolframite, ilmenorutile,
sphalerite, chernovite, and uraninite. Both subsamples
display varying proportions of main minerals in the lar-
ger sieve fractions, whereas the amount of zinnwaldite is
more consistent in fractions of smaller particle size (−315
µm in the conventional sample and −500 µm in the high
voltage pulse power sample). In relation to the combined
educt sample there is a concentration of muscovite, kao-
linite, fluorite and hematite in the finest fraction as well
as a distinct enrichment of topaz in the fraction −500 to
+100 µm respectively +80 µm (Figure 3). This can be
interpreted by the different physical properties of the
minerals. For example, topaz is much harder (Mohs
hardness 8) than the minerals enriched in the smallest
fraction (e.g. kaolinite with Mohs hardness 2) and need
more specific energy to become comminuted.
It should be mentioned that a test of high-intensity
magnetic separation of zinnwaldite ore was conducted
with material from both subsamples, but is not part of
this paper. In a recent paper by Leißner  the entire
mineral processing (comminution and magnetic separa-
tion) of the zinnwaldite-bearing greisen-type ore from the
Zinnwald deposit is discussed. The authors show that in
all chosen size fractions liberation efficiencies are better
than separation efficiencies for zinnwaldite and conclude
that the separation process should be improved for proc-
3.3. Mineral Locking and Mineral Association
Mineral locking and mineral association data as gener-
Figure 3. Modal mineralogy of MLA measurements for the
subsample from conventional comminution (a) and high
voltage pulse power fragmentation (b). The diagram shows
as well the data of the educt (“combined”) as the data for
the different sieve fractions.
ated by MLA give valuable assistance to estimate the
grade of associated minerals (e.g., gangue), which is im-
portant to optimize the mineral beneficiation process.
The diagram of zinnwaldite mineral associations shows
in general a decreasing amount of associated minerals
respectively an increasing amount of non-associated
zinnwaldite grains in smaller size fractions for both sub-
samples (Figure 4). Zinnwaldite mineral grains that are
not fully liberated are more associated with one mineral
(“binary particles”) than two or more minerals (“ternary+
particles”) (for examples see Figure 5). The results of
mineral association data reflect roughly the results of
modal mineralogy with quartz, muscovite, topaz and
kaolinite as the main minerals associated with zinnwal-
dite. It can be noted that the quartz-muscovite ratio in the
zinnwaldite mineral association results (≤1) is much
lower than expected from the results of modal mineral-
ogy (quartz-muscovite ratio: >5). This means that the
muscovite-zinnwaldite grain boundary breakage is not as
Open Access JMMCE
D. SANDMANN, J. GUTZMER 289
Figure 4. Mineral association for zinnwaldite mineral grains
in the different sieve fractions from conventional comminu-
tion (a) and high voltage pulse power fragmentation (b).
Figure 5. Line-up of three groups of different zinnwaldite
locking characteristics (Row 1—liberated zi nnwaldite grains;
Row 2—binary (with only one other phase) locked zinnwal-
dite grains; Row 3—ternary and higher (with more than
one phase) locked zinnwaldite grains) from the conventional
good as the quartz-zinnwaldite grain boundary breakage.
This can be observed in both the conventional comminu-
tion subsample and the high voltage pulse power sub-
sample and is explained by the overgrowth and replace-
ment of zinnwaldite by muscovite in a younger greiseni-
zation stage (Fig ure 6).
3.4. Mineral Liberation
The mineral liberation by particle composition diagram
for zinnwaldite-bearing particles shows not completely
an increasing degree of liberation from smaller sieve
fractions for both conventional comminution and high
voltage pulse power subsamples (Figure 7). This applies
only for the three largest sieve fractions. The sieve frac-
tion −500 to +315 µm resp. −500 to +250 µm shows, in
contrast, a worse degree of liberation as compared to
sieve fractions −1000 to +500 µm, which is the best lib-
erated fraction. The two smallest sieve fractions are again
not as good liberated as sieve fraction −500 to +315 µm
resp. −500 to +250 µm. All these apply for both conven-
tional comminution and high voltage pulse power sub-
samples. The shape of the different curves is related to its
starting point of the curve at the 100% liberation class.
The curves with a small amount of particles in this class
show a rapid increase in particles in the 90% - 95% lib-
eration class. Curves with a higher starting point show a
3.5. Theoretical Grade Recovery
Theoretical grade-recovery curves are defined by the
maximal expected recovery of a mineral at a given grade.
These curves are related to the comminution size of the
treatment process and determined from the liberation
characteristics. It should be noted that theoretical grade-
recovery curves are defined for the value minerals (e.g.,
zinnwaldite) and not based on a final product (e.g., metal
or compound) to be recovered. Furthermore, it is impor-
tant to advise that the theoretical grade-recovery curves
provided by the MLA are generated from 2D liberation
measurements and therefore overestimate the true libera-
tion by a certain amount .
Figure 6. Intense overgrowth and replacement of zinnwal-
dite (light gray; elongated) by muscovite (medium grey) in a
younger greisenization stage (BSE image from ).
Open Access JMMCE
D. SANDMANN, J. GUTZMER
Figure 7. Mineral liberation by particle composition for
zinnwaldite mineral grains in different sieve fractions from
conventional comminution (a) and high voltage pulse power
fragmentation subsamples (b).
The theoretical grade-recovery curves for zinnwaldite
in Figure 8 give reason to expect best results for zinn-
waldite recovery in the sieve fraction −1000 to +500 µm
for both the conventional comminution subsample and
the high voltage pulse power fragmentation subsample.
It has been shown that for zinnwaldite-bearing materials
from a greisen, ore-type high recovery rates can be reach-
ed for both the high voltage pulse power fragmentation
(SELFRAG technology) and the conventional particle
comminution. From the grade recovery curves, it is obvi-
ous that optimal results for both processes could be
achieved from the 1000 - 500 µm size fraction. Smaller
and larger size fractions show poorer results for the
zinnwaldite recovery. In contrast, the results of the zinn-
waldite mineral association show a continuous decrease
in associated minerals and an increasing amount of liber-
ated zinnwaldite grains by the decline of particle size
Figure 8. Theoretical grade recovery curve for zinnwaldite
mineral grains in different sieve fractions from conven-
tional comminution (a) and high voltage pulse power frag-
mentation subsamples (b).
To further assess the quality of size and liberation/re-
covery data of this MLA study, 3D measurements could
be useful. This has been studied for the example of phos-
phate samples by X-ray micro-computer tomography,
with better results in comparison to a 2D analysis .
Due to the method setting of this study, it was not pos-
sible to conduct a direct comparison between the effec-
tivity of the two comminution methods. However, a re-
cent study by  indicates on the example of sulfide
ores and PGM ores that high voltage pulse power frag-
mentation generates a coarser product with significantly
less fines than the conventional mechanical comminution
and that minerals of interest in the high voltage pulse
power product are better liberated than that in the con-
ventional product. It should be considered that various
minerals can have a different behavior (depending on e.g.,
Open Access JMMCE
D. SANDMANN, J. GUTZMER 291
electric conductivity, mineral cleavage, discontinuities in
the material and much more) at the high voltage pulse
power fragmentation. Hence, the results of single studies
should not be transferred to another type of material
without a reinvestigation. For a decision between differ-
ent comminution techniques, factors as throughput rates,
processing time, energy costs or water consumption should
be examined too as they will affect the processing effi-
ciency and overall costs.
The present study demonstrates the capabilities of au-
tomated SEM-based image analysis systems, such as the
Mineral Liberation Analyser (MLA), for the evaluation
of industrial comminution processes. The obtained data
provide valuable key information on quantitative miner-
alogy, mineral association, particle and mineral grain
sizes, as well as mineral liberation and theoretical recov-
ery data. Results illustrate that a MLA system can be
used to constrain parameters relevant to assess comminu-
tion success in a fast and reproducible way.
The authors would like to thank Thomas Zschoge from
the Department of Mechanical Process Engineering and
Mineral Processing (TU Bergakademie Freiberg) for
supporting the conventional comminution as well as
Thomas Mütze and Thomas Leistner from the same de-
partment for fruitful discussions and helpful suggestions.
For instruction in sample processing by high voltage pulse
fragmentation, we thank Peter Segler from the Depart-
ment of Geology (TU Bergakademie Freiberg). The pre-
paration of polished grain mounts and the support during
MLA measurement by Sabine Haser and Bernhard Schulz
of the Department of Mineralogy, TU Bergakademie
Freiberg is gratefully acknowledged. This study was sup-
ported by the Nordic Researcher Network on Process
Mineralogy and Geometallurgy (ProMinNET) and was
carried as part of a BMBF-funded research project (Hy-
bride Lithiumgewinnung, Project No. 030203009).
 L. Beloqui, J. M. Usategui, E. Wang, F. Shi and E.
Manlapig, “Pre-Weakening of Mineral Ores by High
Voltage Pulses,” Minerals Engineering, Vol. 24, No. 5,
2011, pp. 455-462.
 R. Fandrich, Y. Gu, D. Burrows and K. Moeller, “Modern
SEM-Based Mineral Liberation Analysis,” International
Journal of Mineral Processing, Vol. 84, No. 1-4, 2007,
 Y. Gu, “Automated Scanning Electron Microscope Based
Mineral Liberation Analysis an Introduction to JKMRC/
FEI Mineral Liberation Analyser,” Journal of Minerals
and Materials Characterization and Engineering, Vol. 2,
No. 1, 2003, pp. 33-41.
 P. Atanasova, “Mineralogy, Geochemistry and Age of
Greisen Mineralization in the Li-Sn(-W) Deposit Zinn-
wald, Eastern Erzgebirge, Germany,” Master Thesis,
Technische Universität Bergakademie, Freiberg, 2012.
 T. G. Goonan, “Lithium Use in Batteries,” U.S. Geologi-
cal Survey Circular 1371, 2012.
 E. Siame and R. D. Pascoe, “Extraction of Lithium from
Micaceous Waste from China Clay Production,” Minerals
Engineering, Vol. 24, No. 14, 2011, pp. 1595-1602.
 L. Baumann, E. Kuschka and T. Seifert, “Lagerstätten des
Erzgebirges,” ENKE im Georg Thieme Verlag, Stuttgart,
 K. Govindaraju, I. Rubeska and T. Paukert, “Report on
Zinnwaldite ZW-C Analysed by Ninety-Two GIT-IWG
Member-Laboratories,” Geostandards Newsletter, Vol.
18, No. 1, 1994, pp. 1-42.
 H. Bluhm, W. Frey, H. Giese, P. Hoppé, C. Schultheiß
and R. Sträßner, “Application of Pulsed HV Discharges
to Material Fragmentation and Recycling,” IEEE Trans-
actions on Dielectrics and Electrical Insulation, Vol. 7,
No. 5, 2000, pp. 625-636.
 E. Dal Martello, S. Bernardis, R. B. Larsen, G. Tranell, M.
Di Sabatino and L. Arnberg, “Electrical Fragmentation as
a Novel Route for the Refinement of Quartz Raw Materi-
als for Trace Mineral Impurities,” Powder Technology,
Vol. 224, 2012, pp. 209-216.
 B. R. Jackson, A. F. Reid and J. C. Wittemberg, “Rapid
Production of High Quality Polished Sections for Auto-
mated Image Analysis of Minerals,” Proceedings of the
Australasian Institute for Mining and Metallurgy, Vol.
289, 1984, pp. 93-97.
 M. MacDonald, B. Adair, D. Bradshaw, M. Dunn and D.
Latti, “Learnings from Five Years of On-Site MLA at
Kennecott Utah Copper Corporation,” Proceedings of the
10th International Congress for Applied Mineralogy
(ICAM), Trondheim, 1-5 August 2011, pp. 419-426.
 K. Bachmann, S. Haser, T. Seifert and J. Gutzmer, “Pre-
paration of Grain Mounds of Heterogeneous Mineral
Concentrates for Automated Mineralogy—An Example
of Li-Bearing Greisen from Zinnwald, Saxony, Ger-
many,” Schriftenreihe der Deutschen Gesellschaft für
Geowissenschaften, Vol. 80, 2012, p. 395.
 N. Vlachos and I. T. H. Chang, “Graphical and Statistical
Comparison of Various Size Distribution Measurement
Systems Using Metal Powders of a Range of Sizes and
Shapes,” Powder Metallurgy, Vol. 54, No. 4, 2011, pp.
 H. Bolduan, A. Lächelt and F. Malasek, “Zur Geologie
und Mineralisation der Lagerstätte Zinnwald (Cinovec),”
Freiberger Forschungshefte, Vol. C218, 1967, pp. 35-52.
 M. Sala, “Geochemische und Mineralogische Untersu-
chungen an Alterierten Gesteinen aus dem Kuppelbereich
der Lagerstaette Zinnwald (Osterzgebirge),” Ph.D. Thesis
(Dissertation), Technische Universität Bergakademie,
Open Access JMMCE
D. SANDMANN, J. GUTZMER
Open Access JMMCE
 O. Seibel, “Kartierung Ausgewählter Profile im Gruben-
bereich Zinnwald unter Besonderer Berücksichtigung
Paragenetischer und Struktureller Aspekte von Granit-
hochlagen,” Master Thesis (Diplomarbeit), Bergakademie
Freiberg, Freiberg, 1975.
 T. Leißner, T. Mütze, K. Bachmann, S. Rode, J. Gutzmer
and U. A. Peuker, “Evaluation of Mineral Processing by
Assessment of Liberation and Upgrading,” Minerals En-
gineering, Vol. 53, 2013, pp. 171-173.
 Min Assist, “What Is a Theoretical Grade-Recovery
Curve? An Example,” 2009.
 J. D. Miller, C. L. Lin, L. Hupka and M. I. Al-Wakeel,
“Liberation-Limited Grade/Recovery Curves from X-ray
Micro CT Analysis of Feed Material for the Evaluation of
Separation Efficiency,” International Journal of Mineral
Processing, Vol. 93, No. 1, 2009, pp. 48-53.
 E. Wang, F. Shi and E. Manlapig, “Mineral Liberation by
High Voltage Pulses and Conventional Comminution
with Same Specific Energy Levels,” Minerals Engineer-
ing, Vol. 27-28, 2012, pp. 28-36.