Leaching kinetics of manganese from pyrolusite using pyrite as a reductant under microwave heating

Chen, Geng; Jiang, Chunling; Liu, Renlong; Xie, Zhiyong; Liu, Zuohua; Cen, Shaodou; Tao, Changyuan; Guo, Shenghui

doi:10.1016/j.seppur.2021.119472

Cited by 45 publications

(21 citation statements)

References 39 publications

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“…In addition, the change of the ferrous sulfate concentration at a high liquid−solid ratio has more obvious effects on the leaching rate, which is caused by improving the mass transfer effect and increasing the space for particle movement at a high liquid−solid ratio. 7 The leaching rate observed by Figure 5c increased continuously with the increase of leaching time, but the increasing trend gradually flattened after the time reached 160 min. As shown in Figure 5c, when the sulfuric acid concentration is lower than 1 mol/L, the leaching rate always remains at low levels and there is no response to the increase in leaching time.…”

Section: Effect Of the Combination Of Leachingmentioning

confidence: 82%

“…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%. Lan et al 8 applied bioleaching pyrolusite, which proved that the leaching rate can be as high as 98%.…”

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: Effect Of the Combination Of Leachingmentioning

confidence: 82%

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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“…With the leaching progression of the cathode material, the product is dissolved in water, and the shape size of the solid particle gradually decreases until it completely is disappeared. This kind of reaction can be described by the "unreacted shrinking core model" [34]. The model can be divided into the following three types: (A) surface chemical control model; (B) diffusion control model; (C) log rate law model [35].…”

Section: Kinetic Analysismentioning

confidence: 99%

Recovery of Valuable Metals from Spent LiNi0.8Co0.1Mn0.1O2 Cathode Materials Using Compound Leaching Agents of Sulfuric Acid and Oxalic Acid

et al. 2022

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The recovery of valuable metals from spent lithium-ion batteries is beneficial to protect the environment and avoid resource depletion. Based on the synergistic effect of the reducing ability of oxalic acid and the acidic strength of sulfuric acid, this study was conducted to recover valuable metals from spent LiNi0.8Co0.1Mn0.1O2 lithium-ion battery cathode materials with the compound leaching agents of sulfuric acid and oxalic acid. Under the optimized conditions of sulfuric acid concentration at 2.5 mol·L−1, oxalic acid concentration at 20 g·L−1, liquid-to-solid ratio at 10 mL·g−1, reaction temperature at 85 °C, and reaction time at 100 min, the leaching rate of Li, Ni, Co, and Mn measured by ICP-OES was, respectively, 99.26%, 98.41%, 96.95%, and 97.54%. It was further validated that the valuable metals were almost completely leached when combined with the XRD and SEM-EDS analysis of spent cathode materials before and after leaching. The leaching of Li, Ni, Co, and Mn was all in accordance with the Avrami model with their activation energies of 31.96 kJ·mol−1, 41.01 kJ·mol−1, 47.57 kJ·mol−1, and 42.95 kJ·mol−1, indicating that the diffusion was the control of the Li leaching process, and the surface chemical reaction was the control of the other three metals. This work provides a new idea and method for the recycling of spent lithium-ion batteries.

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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.…”

mentioning

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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Leaching kinetics of manganese from pyrolusite using pyrite as a reductant under microwave heating

Cited by 45 publications

References 39 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 Valuable Metals from Spent LiNi0.8Co0.1Mn0.1O2 Cathode Materials Using Compound Leaching Agents of Sulfuric Acid and Oxalic Acid

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

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