2806
Optimization of Operating Parameters in a Reflux Flotation Cell
for Ultrafine Flotation
Linda D. Ayedzi, William Skinner, George B. Abaka-Wood
ARC Centre of Excellence for Enabling Eco-Efficient Beneficiation of Minerals, Future Industries Institute,
University of South Australia, Mawson Lakes Campus, Adelaide, Australia
Massimiliano Zanin
ARC Centre of Excellence for Enabling Eco-Efficient Beneficiation of Minerals, Future Industries Institute,
University of South Australia, Mawson Lakes Campus, Adelaide, Australia
MZ Minerals, Mineral Processing Consulting, Adelaide, Australia
ABSTRACT: The Reflux flotation cell (RFC) enhances mineral flotation performance by introducing a positive
bias of fluidization water to rising bubbles at the top section of the downcomer. This research focuses on
the optimization of the RFC using an ultrafine model mixture comprising pentlandite and quartz minerals.
Flotation experiments using Potassium amyl xanthate were aimed at upgrading nickel grade and recovery. The
optimization study determined the influence of operational parameters such as feed rate, wash water rate, and
airflow rate. The study showed that an airflow rate of 8 L/min and a wash water rate of 0.3 L/min coupled with
a pulp feed rate of 10 L/min, yielded the optimal flotation recovery, achieving approximately 80% pentlandite
recovery with an enrichment ratio of 25.1 and an entrainment factor of 0.05.
INTRODUCTION
Over the years, the mineral processing industry has
depended greatly on froth flotation as a primary tool for
enriching diverse minerals, revisiting the treatment of pre-
viously deemed non-economical complex ores. Although
the process is complex, froth flotation can be generalized
as the separation of particles based on the differences in
their natural or induced hydrophobicity (Ata, 2012). The
separation is not always the ‘cleanest’ attributed to the mul-
tifaceted nature of factors and many subprocesses inherent
in the flotation process (Ross, 1990). Some of these fac-
tors include the mineralogical variability of the ore being
processed, the particle size distribution, reagent choice and
dosage, pulp density, electrochemical potentials, and equip-
ment design (Derhy et al., 2020 Wills and Finch, 2015).
Additional factors involving particle-bubble interactions:
collision, attachment, and detachment efficiencies further
affect the flotation process and its efficacy. It has been found
that these sub-processes influence the hydrodynamic con-
ditions within the flotation cell, that is, the dynamics and
flow patterns in the pulp phase are greatly influenced by the
particle-bubble interactions (Farrokhpay et al., 2021).
The most prominent characteristic of particles that
plays a role in the particle-bubble interaction is particle
size. It is well documented in literature that fine particle
sizes often exhibit low collision with bubbles and subse-
quently low attachment efficiencies, primarily due to a
decrease in particle inertia (Arriagada et al., 2020 Ayedzi et
al., 2022 Farrokhpay et al., 2021 Miettinen et al., 2010).
On the other hand, larger particle sizes often report high
Optimization of Operating Parameters in a Reflux Flotation Cell
for Ultrafine Flotation
Linda D. Ayedzi, William Skinner, George B. Abaka-Wood
ARC Centre of Excellence for Enabling Eco-Efficient Beneficiation of Minerals, Future Industries Institute,
University of South Australia, Mawson Lakes Campus, Adelaide, Australia
Massimiliano Zanin
ARC Centre of Excellence for Enabling Eco-Efficient Beneficiation of Minerals, Future Industries Institute,
University of South Australia, Mawson Lakes Campus, Adelaide, Australia
MZ Minerals, Mineral Processing Consulting, Adelaide, Australia
ABSTRACT: The Reflux flotation cell (RFC) enhances mineral flotation performance by introducing a positive
bias of fluidization water to rising bubbles at the top section of the downcomer. This research focuses on
the optimization of the RFC using an ultrafine model mixture comprising pentlandite and quartz minerals.
Flotation experiments using Potassium amyl xanthate were aimed at upgrading nickel grade and recovery. The
optimization study determined the influence of operational parameters such as feed rate, wash water rate, and
airflow rate. The study showed that an airflow rate of 8 L/min and a wash water rate of 0.3 L/min coupled with
a pulp feed rate of 10 L/min, yielded the optimal flotation recovery, achieving approximately 80% pentlandite
recovery with an enrichment ratio of 25.1 and an entrainment factor of 0.05.
INTRODUCTION
Over the years, the mineral processing industry has
depended greatly on froth flotation as a primary tool for
enriching diverse minerals, revisiting the treatment of pre-
viously deemed non-economical complex ores. Although
the process is complex, froth flotation can be generalized
as the separation of particles based on the differences in
their natural or induced hydrophobicity (Ata, 2012). The
separation is not always the ‘cleanest’ attributed to the mul-
tifaceted nature of factors and many subprocesses inherent
in the flotation process (Ross, 1990). Some of these fac-
tors include the mineralogical variability of the ore being
processed, the particle size distribution, reagent choice and
dosage, pulp density, electrochemical potentials, and equip-
ment design (Derhy et al., 2020 Wills and Finch, 2015).
Additional factors involving particle-bubble interactions:
collision, attachment, and detachment efficiencies further
affect the flotation process and its efficacy. It has been found
that these sub-processes influence the hydrodynamic con-
ditions within the flotation cell, that is, the dynamics and
flow patterns in the pulp phase are greatly influenced by the
particle-bubble interactions (Farrokhpay et al., 2021).
The most prominent characteristic of particles that
plays a role in the particle-bubble interaction is particle
size. It is well documented in literature that fine particle
sizes often exhibit low collision with bubbles and subse-
quently low attachment efficiencies, primarily due to a
decrease in particle inertia (Arriagada et al., 2020 Ayedzi et
al., 2022 Farrokhpay et al., 2021 Miettinen et al., 2010).
On the other hand, larger particle sizes often report high