The Differences in Evaluation of Flotation Kinetics of Talc Ore Using Statistical Analysis and Response Surface Methodology

Bacillus subtilis was used as a bio-surface modifier to improve the floatability of talc mineral (Mg3Si4O10(OH)2) in the talc ore. The surface behavior of chlorite mineral as the main associated gangue with talc mineral was studied in the presence of B. subtilis using zeta potential, scanning electron microscopy, and Fourier-transform infrared spectroscopy techniques. The floatability of both minerals was investigated as a function of pH, contact time, and concentration of B. subtilis. The results showed that the zeta potential of the talc mineral was strongly influenced by the treatment with B. subtilis. The maximum separation efficiency of talc from chlorite was achieved at pH 4. A talc concentrate with 98% quality and about 95% recovery was prepared from a binary talc-chlorite mixture containing 85% talc under optimum conditions of 8 × 105 cells/mL B. subtilis, pH 4, 35°C, and a contact time of 10 min.

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Response Surface Methodology for Copper Flotation Optimization in Saline Systems

Arancibia-Bravo

Lucay

Sepúlveda

et al. 2022

Minerals

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Response surface methodology (RSM) is one of the most effective tools for optimizing processes, and it has been used in conjunction with the Analysis of Variance (ANOVA) test to establish the effect of input factors on output factors. However, when this methodology is used in mineral flotation, its polynomial model usually performs poorly. An alternative is to use artificial neural networks (ANNs) in such situations. Within this context, the ANOVA test is not the best option for these model types; moreover, it requires statistical assumptions that are difficult to satisfy in flotation. This work proposes replacing the polynomial model of the RSM with ANNs and the Sobol methods to determine the influential input factors instead of the ANOVA test. This proposal is applied to two porphyry copper ores with a high content of pyrite, clay, and dilution media. In addition, this study shows how other computational intelligence techniques, such as swarm intelligence, can be incorporated into this type of problem to improve the learning process of ANNs. The results gave an adjustment of over 0.98 for R2 using ANNs, in comparison to values of around 0.5 when the polynomial model of RSM was utilized. On the other hand, the application of Global Sensitivity Analysis (GSA) identified the aeration rate and P80 size as the most influential variables in copper recovery under the conditions studied. Additionally, we identified significant interactions that affect the recovery of copper, with the interactions between the aeration rate, frother concentration, and P80 size being the most important.

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The Differences in Evaluation of Flotation Kinetics of Talc Ore Using Statistical Analysis and Response Surface Methodology

Cited by 3 publications

References 30 publications

A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm

A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm

Influence of Bacillus subtilis on the surface behavior and separation of talc and chlorite minerals

Response Surface Methodology for Copper Flotation Optimization in Saline Systems

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