Application of response surface methodology in optimization of bioleaching parameters for high-magnesium nickel sulfide ore

Sun, Jianzhi; Wu, Bin; Chen, Bo-wei; Wen, Jiankang

doi:10.1007/s11771-022-5020-y

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…At the same time, acid addition is the most signicant variable affecting Mg leaching efficiency. 68 Tang et al (2021) examined Acidithiobacillus caldus's potential for biodesulfurization of sulde ore using a BBD-based RSM. The six studied parameters included temperature, particle size, shaking rate, inoculation, pH, and Tween80 concentration.…”

Section: Biorecovery From Soil and Oresmentioning

confidence: 99%

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A comprehensive review of bioleaching optimization by statistical approaches: recycling mechanisms, factors affecting, challenges, and sustainability

et al. 2023

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Section: Biorecovery From Soil and Oresmentioning

confidence: 99%

“…At the same time, acid addition is the most significant variable affecting Mg leaching efficiency. 68 …”

Section: Application Of Rsm In Bioleaching Processesmentioning

confidence: 99%

A comprehensive review of bioleaching optimization by statistical approaches: recycling mechanisms, factors affecting, challenges, and sustainability

et al. 2023

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“…Jalali et al [ 105 ] used the response surface technique to model laboratory-scale column bioleaching of low-grade uranium ore using an isolate of Acidithiobacillus ferridurans . Zhou et al [ 106 ], also using the response surface methodology, modeled the bioleaching of high fluorine and low sulfur uranium ore, and Sun et al [ 107 ] optimized bioleaching parameters for high magnesium nickel sulfide ore. Li et al [ 108 ], on the other hand, used the kinetic model controlled by surface chemical reactions or the kinetic model controlled by internal diffusion through the product layer to study the enhancement effect of sulfur on uranium bioleaching in column reactors from refractory uranium ore. Shang et al [ 109 ] modeled the dissolution kinetic of pyrite, chalcocite, and chalcopyrite by an empirical, diffusion-like equation. Sundramurthy et al [ 110 ] modeled the zinc bioleaching rate using a Leptospirillum ferriphilum isolate; the leaching data were analyzed using a shrinking core model, which revealed that the rate of leaching was inhibited by diffusion through product layer.…”

Section: Modeling Of Mineral Bioleachingmentioning

confidence: 99%

Bioleaching Modeling—A Review

et al. 2023

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The leaching of minerals is one of the main unit operations in the metal dissolution process, and in turn it is a process that generates fewer environmental liabilities compared to pyrometallurgical processes. As an alternative to conventional leaching methods, the use of microorganisms in mineral treatment processes has become widespread in recent decades, due to advantages such as the non-production of emissions or pollution, energy savings, low process costs, products compatible with the environment, and increases in the benefit of low-grade mining deposits. The purpose of this work is to introduce the theoretical foundations associated with modeling the process of bioleaching, mainly the modeling of mineral recovery rates. The different models are collected from models based on conventional leaching dynamics modeling, based on the shrinking core model, where the oxidation process is controlled by diffusion, chemically, or by film diffusion until bioleaching models based on statistical analysis are presented, such as the surface response methodology or the application of machine learning algorithms. Although bioleaching modeling (independent of modeling techniques) of industrial (or large-scale mined) minerals is a fairly developed area, bioleaching modeling applied to rare earth elements is a field with great growth potential in the coming years, as in general bioleaching has the potential to be a more sustainable and environmentally friendly mining method than traditional mining methods.

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Analysis of damage characteristics and optimization of fan-holes blasting design under high in-situ stresses

Zhang

Liu

Yang

et al. 2023

J. Cent. South Univ.

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Application of response surface methodology in optimization of bioleaching parameters for high-magnesium nickel sulfide ore

Cited by 5 publications

References 18 publications

A comprehensive review of bioleaching optimization by statistical approaches: recycling mechanisms, factors affecting, challenges, and sustainability

A comprehensive review of bioleaching optimization by statistical approaches: recycling mechanisms, factors affecting, challenges, and sustainability

Bioleaching Modeling—A Review

Analysis of damage characteristics and optimization of fan-holes blasting design under high in-situ stresses

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