The reductive leaching of waste lithium ion batteries in presence of iron ions: Process optimization and kinetics modelling

Ghassa, Sina; Farzanegan, A.; Gharabaghi, Mahdi; Abdollahi, Hadi

doi:10.1016/j.jclepro.2020.121312

Cited by 52 publications

(23 citation statements)

References 40 publications

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“…The equations are surface chemical reaction control model (Equation 3), diffusion control model (Equation 4), and mixed control model (Equation 5). [41,42] 1…”

Section: Kinetic Analysismentioning

confidence: 99%

“…The equations are surface chemical reaction control model (Equation 3), diffusion control model (Equation 4), and mixed control model (Equation 5). [ 41,42 ]

1 - {false(1 - x false)}^{1 / 3} = k t

1 - 2 / 3 x - {false(1 - x false)}^{\frac{2}{3}} = k t

1 / 3 \ln (1 - x) + {false(1 - x false)}^{- 1 / 3} - 1 = k t

where x is the leaching rate, k is the reaction constant, and t is the reaction time. According to the results in Figure 8, the appropriate data are selected for data fitting using Equation (3)–(5), respectively.…”

Section: Mechanism Of the Leaching Processmentioning

confidence: 99%

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Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi_0.6Co_0.2Mn_0.2O₂ Batteries

et al. 2022

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Considering the increasing price of raw materials and environmental pollution, the recycling of used lithium battery cathode materials has very important economic and environmental value. In this experiment, a green recycling method is used to recover valuable metals from spent LiNi0.6Co0.2Mn0.2O2 batteries using DL‐malic acid and H2O2 as a leaching system. The effects of reaction temperature, acid concentration, H2O2 volume concentration, reaction time, and solid–liquid ratio on the leaching efficiency are investigated by orthogonal and single variable condition experiments. Under the optimum conditions, the leaching efficiencies of Ni, Co, Mn, and Li are 96.2%, 97.1%, 97.6%, and 98.1%, respectively, while the leaching efficiency of Al is only 3.5%. The effect of H2O2 on the leaching process is further investigated by macroscopic characterization and kinetic analysis. The study indicates that the leaching process is controlled by a chemical reaction in the absence of H2O2, and the leaching process after the addition of H2O2 is controlled by the chemical reaction process and the diﬀusion process.

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“…The equations are surface chemical reaction control model (Equation 3), diffusion control model (Equation 4), and mixed control model (Equation 5). [41,42] 1…”

Section: Kinetic Analysismentioning

confidence: 99%

“…The equations are surface chemical reaction control model (Equation 3), diffusion control model (Equation 4), and mixed control model (Equation 5). [ 41,42 ]

1 - {false(1 - x false)}^{1 / 3} = k t

1 - 2 / 3 x - {false(1 - x false)}^{\frac{2}{3}} = k t

1 / 3 \ln (1 - x) + {false(1 - x false)}^{- 1 / 3} - 1 = k t

Section: Mechanism Of the Leaching Processmentioning

confidence: 99%

Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi_0.6Co_0.2Mn_0.2O₂ Batteries

et al. 2022

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“…The reductant is critical in the leaching process to promote solubility of Co by reducing insoluble Co 3+ in the spent LIB cathode (LiCoO 2 ) into soluble Co 2+ (1). Inorganic reductants suggested so far include bisulfite [23], sodium sulfite [24], and divalent iron [25], while organic reductants recommended were glucose [26], ascorbic acid [27], and ethanol [28].…”

Section: Introductionmentioning

confidence: 99%

Tannic acid as a novel and green leaching reagent for cobalt and lithium recycling from spent lithium-ion batteries

Prasetyo

Muryanta

Anggraini

et al. 2022

J Mater Cycles Waste Manag

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Tannic acid–acetic acid is proposed as novel and green chemicals for cobalt and lithium recycling from spent lithium-ion batteries through a leaching process. The synergism of both acids was documented through batch and continuous studies. Tannic acid promotes cobalt dissolution by reducing insoluble Co3+ into soluble Co2+, while acetic acid is critical to improve the dissolution and stabilize the metals in the pregnant leach solution. Based on batch studies, the optimum conditions for metal recovery at room temperature are acetic acid 1 M, tannic acid 20 g/L, pulp density 20 g/L, and stirring speed 250 rpm (94% cobalt and 99% lithium recovery). The kinetic study shows that increasing temperature to 80 °C improves cobalt and lithium recovery from 65 to 90% (cobalt) and from 80 to 99% (lithium) within 4 h at sub-optimum condition (tannic acid 10 g/L). Kinetic modeling suggests the leaching process was endothermic, and high activation energy indicates a surface chemical process. For other metals, the pattern of manganese and nickel recovery trend follows the cobalt recovery trend. Copper recovery was negatively affected by tannic acid. Iron recovery was limited due to the weak acidic condition of pregnant leach solution, which is beneficial to improve leaching selectivity.

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“…Although this equalization method reduces the energy loss, the circuit design is complex and the hardware implementation cost is high. In some studies, a new type of equalization circuit is designed by combining the advantages of active equalization and passive equalization, which improves the equalization efficiency to a certain extent and simplifies the circuit design [7][8][9][10]. In addition to improving balance efficiency and reducing balance time, different balancing strategies are proposed, which are mainly defined according to the battery cell voltage or the remaining capacity of the single battery.…”

Section: Introductionmentioning

confidence: 99%

Lithium Battery Allocation Decision-Making Scheme Based on K-Means Algorithm

Qin

2022

Mathematical Problems in Engineering

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Lithium-ion batteries, the core components of electric vehicles, have received unprecedented attention and undergone development in the era of huge energy demand. The traditional clustering algorithm cannot meet the requirement of the consistency of lithium battery distribution. In this study, we provide an improved K-means algorithm to meet the battery distribution needs of enterprises and combine it with reality. This model includes an early data processing model and a battery comparison method based on the new K-means algorithm. In the battery data processing model, the preprocessing process approach and actual production standards preclude problematic batteries. In the battery comparison algorithm, the number of batteries in each cluster becomes equal after the battery comparison. The algorithm can ensure the internal characteristics of lithium-ion power batteries, and, at the same time, after the matching is completed, the number of lithium batteries in each cluster is equal.

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The reductive leaching of waste lithium ion batteries in presence of iron ions: Process optimization and kinetics modelling

Cited by 52 publications

References 40 publications

Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi_0.6Co_0.2Mn_0.2O₂ Batteries

Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi_0.6Co_0.2Mn_0.2O₂ Batteries

Tannic acid as a novel and green leaching reagent for cobalt and lithium recycling from spent lithium-ion batteries

Lithium Battery Allocation Decision-Making Scheme Based on K-Means Algorithm

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The reductive leaching of waste lithium ion batteries in presence of iron ions: Process optimization and kinetics modelling

Cited by 52 publications

References 40 publications

Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi0.6Co0.2Mn0.2O2 Batteries

Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi0.6Co0.2Mn0.2O2 Batteries

Tannic acid as a novel and green leaching reagent for cobalt and lithium recycling from spent lithium-ion batteries

Lithium Battery Allocation Decision-Making Scheme Based on K-Means Algorithm

Contact Info

Product

Resources

About

Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi_0.6Co_0.2Mn_0.2O₂ Batteries

Effect of Hydrogen Peroxide on the Recovery of Valuable Metals from Spent LiNi_0.6Co_0.2Mn_0.2O₂ Batteries