XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1033
between the fraction by number of highly liberated parti-
cles and the fraction by number of poorly liberated grains is
given across the size fractions. The calculations were carried
out using equation (3).
n n
j j,h j,l m =-(3)
where λi is the extent of liberation for the size fraction j,
nj,h is the number of particles in the size fraction j with a
surface liberation of at least h, and nj,l is the number of par-
ticles in the size fraction j with a surface liberation below l.
h and l can range from 0 to 100%. It is important to stress
that positive values of λj are favourable, indicating a greater
proportion of liberated particles.
Given that iron content was exceptionally high for the
ore used in this study, particles of more than 80% libera-
tion were considered as highly liberated and those of less
than 80% as poorly liberated. However, these values can be
easily tailored depending on the process and mineral type.
CONCLUSIONS
A new approach to interpret surface liberation was pre-
sented. This interpretation involves using the information
obtained from any surface exposure quantification soft-
ware (such as QEMSCAN, MLA, TIMA, micro-CT, etc)
but representing the values in a novel manner. While the
standard description of a comminution process is carried
out nowadays by considering the mass fraction of particles
with a given surface exposure per size class, we propose that
the number fraction be used and that not only liberated
particles are considered, but also the poorly liberated ones
to optimise comminution devices and enhance production
efficiency. Furthermore, the main reason to use the number
fraction rather than the mass fraction is that a small num-
ber of liberated particles can make up a significant mass
fraction, resulting in misconception of the efficiency of the
comminution circuit being studied. We define the quantity
Extent of Liberation, λ, as the difference between the num-
ber of highly liberated grains and the number of poorly
liberated grains for the size fraction j. Positive values of λ
indicate a greater proportion of liberated particles.
This new analytical technique has the potential to allow
the comparison of different ores and operations, enabling
comminution circuits to target desired “liberation curves”
for improved downstream performance, in a similar way to
the use of energy curves to improve energy efficiency.
ACKNOWLEDGMENTS
The authors would like to acknowledge Dr Joshua Rasera
and Mr Jose Martinez for their help and advice during
the conduct of this study. The authors would also like to
acknowledge Rio Tinto Company Limited for providing
the samples and funding LSF during this study.
REFERENCES
Kamath, B.P., Ramarao, V.V., Mohanty, D.B. (2006).
Proceedings of the International Seminar on Mineral
Processing Technology, Chennai, India. pp. 398–404.
Microwave Energy Aided Mineral Comminution
Ashish Kumar.
Garcia, F., &Smith, P. (2017). “Grinding Parameters and
Their Effects on the Liberation of Values in a Porphyry
Copper Ore during Grinding.” Minerals Engineering,
115, 14–22.
Jones, M., &Truelove, J.S. (2018). “Impact of Mineral
Liberation on Flotation Efficiency—A Review.”
Minerals Engineering, 123, 167–178.
Li, H., &Smith, D.J. (2021). “Recent Advances in
Mineral Liberation Analysis Techniques.” Minerals
Engineering, 167, 107929.
Reyes, F., Lin, Q., Cilliers, J.J., Neethling, S.J. (2018)
‘Quantifying mineral liberation by particle grade and
surface exposure using X-ray microCT’, Minerals
Engineering, 125, pp. 75–82.
Salinas-Farran, L., Batchelor, A. and Neethling, S.J. (2022)
‘Multimodal assessment of the curing of agglomerated
ores in the presence of chloride ions’, Hydrometallurgy,
207, p. 105776.
T.G. Vizcarra, E.M. Wightman, N.W. Johnson, E.V.
Manlapig, The effect of breakage mechanism on the
mineral liberation properties of sulphide ores, Minerals
Engineering, Volume 23, Issue 5, 2010, Pages 374–382.
Wang, C., Li, X., &Zhang, S. (2019). “Towards Sustainable
Mining: The Importance of Mineral Liberation.”
Journal of Cleaner Production, 218, 114–124.
between the fraction by number of highly liberated parti-
cles and the fraction by number of poorly liberated grains is
given across the size fractions. The calculations were carried
out using equation (3).
n n
j j,h j,l m =-(3)
where λi is the extent of liberation for the size fraction j,
nj,h is the number of particles in the size fraction j with a
surface liberation of at least h, and nj,l is the number of par-
ticles in the size fraction j with a surface liberation below l.
h and l can range from 0 to 100%. It is important to stress
that positive values of λj are favourable, indicating a greater
proportion of liberated particles.
Given that iron content was exceptionally high for the
ore used in this study, particles of more than 80% libera-
tion were considered as highly liberated and those of less
than 80% as poorly liberated. However, these values can be
easily tailored depending on the process and mineral type.
CONCLUSIONS
A new approach to interpret surface liberation was pre-
sented. This interpretation involves using the information
obtained from any surface exposure quantification soft-
ware (such as QEMSCAN, MLA, TIMA, micro-CT, etc)
but representing the values in a novel manner. While the
standard description of a comminution process is carried
out nowadays by considering the mass fraction of particles
with a given surface exposure per size class, we propose that
the number fraction be used and that not only liberated
particles are considered, but also the poorly liberated ones
to optimise comminution devices and enhance production
efficiency. Furthermore, the main reason to use the number
fraction rather than the mass fraction is that a small num-
ber of liberated particles can make up a significant mass
fraction, resulting in misconception of the efficiency of the
comminution circuit being studied. We define the quantity
Extent of Liberation, λ, as the difference between the num-
ber of highly liberated grains and the number of poorly
liberated grains for the size fraction j. Positive values of λ
indicate a greater proportion of liberated particles.
This new analytical technique has the potential to allow
the comparison of different ores and operations, enabling
comminution circuits to target desired “liberation curves”
for improved downstream performance, in a similar way to
the use of energy curves to improve energy efficiency.
ACKNOWLEDGMENTS
The authors would like to acknowledge Dr Joshua Rasera
and Mr Jose Martinez for their help and advice during
the conduct of this study. The authors would also like to
acknowledge Rio Tinto Company Limited for providing
the samples and funding LSF during this study.
REFERENCES
Kamath, B.P., Ramarao, V.V., Mohanty, D.B. (2006).
Proceedings of the International Seminar on Mineral
Processing Technology, Chennai, India. pp. 398–404.
Microwave Energy Aided Mineral Comminution
Ashish Kumar.
Garcia, F., &Smith, P. (2017). “Grinding Parameters and
Their Effects on the Liberation of Values in a Porphyry
Copper Ore during Grinding.” Minerals Engineering,
115, 14–22.
Jones, M., &Truelove, J.S. (2018). “Impact of Mineral
Liberation on Flotation Efficiency—A Review.”
Minerals Engineering, 123, 167–178.
Li, H., &Smith, D.J. (2021). “Recent Advances in
Mineral Liberation Analysis Techniques.” Minerals
Engineering, 167, 107929.
Reyes, F., Lin, Q., Cilliers, J.J., Neethling, S.J. (2018)
‘Quantifying mineral liberation by particle grade and
surface exposure using X-ray microCT’, Minerals
Engineering, 125, pp. 75–82.
Salinas-Farran, L., Batchelor, A. and Neethling, S.J. (2022)
‘Multimodal assessment of the curing of agglomerated
ores in the presence of chloride ions’, Hydrometallurgy,
207, p. 105776.
T.G. Vizcarra, E.M. Wightman, N.W. Johnson, E.V.
Manlapig, The effect of breakage mechanism on the
mineral liberation properties of sulphide ores, Minerals
Engineering, Volume 23, Issue 5, 2010, Pages 374–382.
Wang, C., Li, X., &Zhang, S. (2019). “Towards Sustainable
Mining: The Importance of Mineral Liberation.”
Journal of Cleaner Production, 218, 114–124.