Enhanced leaching of manganese from low-grade pyrolusite using ball milling and electric field

Luo, Zhenggang; Shu, Jiancheng; Chen, Mengjun; Wang, Rong; Zeng, Xin; Yang, Yong; Wang, Rui; Chen, Shuyuan; Liu, Renlong; Liu, Zuohua; Sun, Zhi; Yu, Keli; Deng, Yi

doi:10.1016/j.ecoenv.2021.111893

Cited by 25 publications

(12 citation statements)

References 40 publications

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“…The increase of ferrous sulfate concentration (Figure a) improves the leaching of manganese, which is due to the reducibility of Fe 2+ ions, which can promote the reductive leaching of high-valent manganese. In addition, the leaching of manganese still occurs in the absence of ferrous ions, which is caused by the direct reduction of high-valent manganese by the electric field . When the concentration of sulfuric acid is low (Figure b), the leaching rate of manganese remains low, which is due to the existence of colloidal alkaline ferric sulfate in the reaction solution under the environment of low-concentration sulfuric acid, which affects the leaching effect.…”

Section: Resultsmentioning

confidence: 99%

“…By studying the leaching mechanism of pyrolusite with an electric field, 4,5 it has been found that both the consumption of ferrous sulfate and the acid leaching reagent sulfuric acid could be reduced under electric field enhancement. Luo et al 6 combined ball milling and an electric field to make the optimal leaching rate of pyrolusite reach 97.79%. Chen et al 7 used pyrite as a reducing agent to leaching pyrolusite under microwave conditions, and the leaching rate reached 93.03%.…”

Section: Introductionmentioning

confidence: 99%

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Application of Machine Learning in a Mineral Leaching Process─Taking Pyrolusite Leaching as an Example

Zhang

et al. 2022

ACS Omega

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In this study, several machine learning models were used to analyze the process variables of electric-field-enhanced pyrolusite leaching and predict the leaching rate of manganese, and the applicability of those models in the leaching process of hydrometallurgy was compared. It showed that there was no correlation between the six leaching conditions; in addition to the leaching time, the concentrations of sulfuric acid and ferrous sulfate had great influences on the leaching of pyrolusite. The results of the prediction models showed that the support vector regression model has the best prediction performance, with regression index (R 2) = 0.92 and mean square error = 25.04, followed by the gradient boosting regression model (R 2 > 0.85). In this research, machine learning models were applied to the optimization of the manganese leaching process, and the research process and methods were also applicable to other hydrometallurgical processes for majorization and result prediction.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of Machine Learning in a Mineral Leaching Process─Taking Pyrolusite Leaching as an Example

Zhang

et al. 2022

ACS Omega

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“…The reduction of pyrolusite by some organic materials such as sawdust, cellulose, sugarcane, banyan‐leaves, and tealeaves as reducing agents has been proved to be feasible by some researchers 23–27 . Due to the characteristics of low energy consumption and environmental friendliness, hydrometallurgical reduction leaching is expected to become the mainstream process for manganese extraction from pyrolusite in the future 28,29 . Titanium white waste acid is rich in a lot of FeSO 4 , which are in a low chemical valence state, and both have excellent electron donor capacity 30 .…”

Section: Introductionmentioning

confidence: 99%

“…[23][24][25][26][27] Due to the characteristics of low energy consumption and environmental friendliness, hydrometallurgical reduction leaching is expected to become the mainstream process for manganese extraction from pyrolusite in the future. 28,29 Titanium white waste acid is rich in a lot of FeSO 4 , which are in a low chemical valence state, and both have excellent electron donor capacity. 30 Therefore, manganese can be directly leached from pyrolusite by titanium white waste acid under appropriate conditions.…”

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confidence: 99%

Recovery of Ti from titanium white waste acid with N1923 extraction and leaching of low‐grade pyrolusite using raffinate

Feng

2022

Asia-Pacific J Chem Eng

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Titanium dioxide industry produces a large amount of titanium white waste acid every year. In this work, to make full use of and recover valuable components in titanium white waste acid, a processing for recovery of Ti from titanium white waste acid with N1923 extraction and leaching of low-grade pyrolusite using raffinate was proposed. After a two-stage countercurrent extraction, 99.93% Ti was extracted, while 6.51% Fe, .11% Mg, .06% Mn, and .08% Al were co-extracted under N1923 concentration of 25% and phase ratio (O/A) of 2/1. The scrubbing efficiency of iron reached 98.53%, while the loss efficiency of titanium was only .94% with 1.5 mol/L sulfuric acid solution under the phase ratio of 1/1. Then, the Ti-loaded organic phase could be effectively stripped by .8 mol/L ammonia water; the single-stage stripping efficiency of titanium was 99.23%. Subsequently, the raffinate could be used for the extraction of manganese from low-grade pyrolusite. The leaching efficiency of manganese was 99.39% at the S/L ratio of 48.00 g/L, leaching temperature of 50 C, and leaching time of 40 min. In addition, thermodynamic calculations revealed that the titanium extraction process by N1923 from titanium white waste acid was an exothermic reaction. The proposed approach is suitable for co-recovery of titanium from titanium white waste acid and manganese from low-grade pyrolusite.

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“…In recent years, the electric field-enhanced leaching process has been widely applied to the leaching of heavy metal elements in solid waste. − In the early stage, the research group realized the efficient leaching of Mn from EMM under the synergistic effect of an electric field and Fe 2+ , and the leaching efficiency of Mn was as high as 92%. In addition, research shows that the leaching of Mn from low-grade pyrolusite, Au from insoluble gold ore, V from the converter slag, and Cu from electronic waste can all be realized under the action of an electric field. − Therefore, the enhanced leaching of Mn from EMAS under the action of an electric field provides a new way to utilize EMAS resources.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Leaching of Mn from Electrolytic Manganese Anode Slime via an Electric Field

et al. 2021

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Electrolytic manganese anode slime (EMAS) contains many Mn resources, and efficient Mn leaching is the key to realizing its high-value utilization. In this study, the effects of Fe2+ concentration, H2SO4 concentration, liquid–solid mass ratio, reaction temperature, and current density on Mn leaching efficiency were investigated. The enhanced leaching kinetics and mechanism of Mn from EMAS were analyzed. The results showed that the leaching efficiency of Mn in EMAS was 97.5%, the Pb content in the leaching residue was 42.24 wt % at a current density of 120 mA/cm2, the concentration of Fe2+ was 0.7 mol/L, the concentration of H2SO4 was 1.6 mol/L, the mass ratio of liquid–solid was 6 mL/g, and the reaction time and temperature were 150 min and 333 K. The leaching mechanism showed that the closed-cycle system of Fe2+–Fe3+–Fe2+ was formed in the process of electric field leaching, and Fe2+ and Fe3+ became the electron transport media, which realized the oxidation–reduction leaching of MnO2 and Fe2+ in EMAS. Leaching kinetics indicated that the apparent activation energy is 38.38 kJ/mol and the apparent efficiency equation is 1–2/3X – (1 – X)2/3 = A exp(−38.38/RT)t. This study provides a new method for resource utilization of EMAS.

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Enhanced leaching of manganese from low-grade pyrolusite using ball milling and electric field

Cited by 25 publications

References 40 publications

Application of Machine Learning in a Mineral Leaching Process─Taking Pyrolusite Leaching as an Example

Application of Machine Learning in a Mineral Leaching Process─Taking Pyrolusite Leaching as an Example

Recovery of Ti from titanium white waste acid with N1923 extraction and leaching of low‐grade pyrolusite using raffinate

Enhanced Leaching of Mn from Electrolytic Manganese Anode Slime via an Electric Field

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