Optimization of alumina leaching from microcline using particle swarm optimization and response surface methodology

Alumina has found wide application in technological and engineering fields. However, due to the environmental effects of the traditional Bayer process of production, there is a need for a more eco-friendly and cost-effective procedure. The optimization of alumina extraction from microcline in nitric acid (HNO<sub>3</sub>) solution is considered in this work. The optimization exercise was performed with the optimization tools of response surface methodology (RSM) and particle swarm optimization (PSO). The optimum conditions predicted by RSM include 82.11 <sup>o</sup>C reaction temperature, 3.53 M HNO<sub>3</sub> concentration, 0.023 g/mL solid/liquid (S/L) ratio, 356.14 rpm stirring speed, and 99.92 min reaction time. At these conditions, about 83.21% alumina leaching rate was predicted. PSO however predicted optimum conditions of 90<sup>o</sup>C, 4 M, 0.021 g/mL, 420 rpm, and 118 min, respectively, for the parameters above. Hence, the two techniques were viable tools for the optimization exercise.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-03-17
DOI
https://doi.org/10.1038/s41598-025-93326-5
Citations
1
Primary Topic
Minerals Flotation and Separation Techniques
Type
article
Field-Weighted Citation Impact
0.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of alumina leaching from microcline using particle swarm optimization and response surface methodology

Chinyere Ezekannagha, Cyril Sunday Ume, Valentine Chikaodili Anadebe, Ikechukwu Abuchi Nnanwube et al.
1 citations
Scientific Reports
Minerals Flotation and Separation Techniques
0.82
article

Optimization of alumina leaching from microcline using particle swarm optimization and response surface methodology

Chinyere Ezekannagha, Cyril Sunday Ume, Valentine Chikaodili Anadebe, Ikechukwu Abuchi Nnanwube, Christopher Nnaemeka Igwilo, Monday Omotioma, Okechukwu D. Onukwuli, Chizoo Esonye
article en
1 citations

Abstract

Alumina has found wide application in technological and engineering fields. However, due to the environmental effects of the traditional Bayer process of production, there is a need for a more eco-friendly and cost-effective procedure. The optimization of alumina extraction from microcline in nitric acid (HNO<sub>3</sub>) solution is considered in this work. The optimization exercise was performed with the optimization tools of response surface methodology (RSM) and particle swarm optimization (PSO). The optimum conditions predicted by RSM include 82.11 <sup>o</sup>C reaction temperature, 3.53 M HNO<sub>3</sub> concentration, 0.023 g/mL solid/liquid (S/L) ratio, 356.14 rpm stirring speed, and 99.92 min reaction time. At these conditions, about 83.21% alumina leaching rate was predicted. PSO however predicted optimum conditions of 90<sup>o</sup>C, 4 M, 0.021 g/mL, 420 rpm, and 118 min, respectively, for the parameters above. Hence, the two techniques were viable tools for the optimization exercise.

Scientific ReportsVol. 15(1)
Enugu State University of Science and Technology (NG), Nnamdi Azikiwe University (NG), Madonna University (NG), Federal Medical Centre (NG), Michael Okpara University of Agriculture (NG)
Openalex Percentile: Top 28%
Minerals Flotation and Separation Techniques
0.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Optimization of alumina leaching from microcline using particle swarm optimization and response surface methodology — Chinyere Ezekannagha, Cyril Sunday Ume, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS