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EN
Green cars and electronic products consume lots of lithium-ion batteries (LIBs), and massive spent LIBs are yielded due to performance degradation. This paper provides an economical and environmentally friendly approach to recover valuable metals from cathode materials of the spent LIBs. It combines the in-situ thermal reduction (self-reduction by polyvinylidene fluoride (PVDF) and residual electrolyte in cathode material) and sulfuric acid leaching. Elements of high valent are reduced by the binder (PVDF) and the residual electrolyte on the surface of NCM(LiNixCoyMn1-x-yyO2) material at high temperatures. Moreover, the changes in substance type, element valency, and contents of cathode materials reduced with various terminal temperatures and retention time are analyzed by Xray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). Results show that the optimal terminal temperature for in-situ thermal reduction is 600 °C, and the optimum retention time is 120 min. Under the best in-situ thermal reduction conditions, the results from XRD confirm that part of Ni2+ is converted to simple substance Ni, Co3+ is reduced to Co, and Mn4+ is reduced to Mn2+ and elemental Mn, which are confirmed by XRD. Analyzed results by XPS indicate that the content of Ni2+ decreases to 67.05%, and Co3+ is completely reduced to Co. Mn4+ is reduced to 91.41% of Mn2+ and 8.59% of simple substance Mn. In-situ thermal reduction benefits the leaching processes of cathode materials. The leaching efficiencies of Ni, Co, and Mn increase from 53.39%, 51.95%, and 0.71% to 99.04%, 96.98%, and 97.52%, respectively.
EN
In order to investigate the impact of density on the classification behavior of particles in the static classifier of Vertical Spindle Mill, the sensitivity of overflow yield to the increase of air amount for narrowly sized pyrite, carborundum, quartz and coal samples were compared in a lab-scale classifier, respectively. Response surface methodology is used to analyze the combined effect of size and density on the classification. Wide size classification was also conducted and results show that both the yield and R90 of overflow increase with the decreasing of density, and the growth of air amount would also lead them to rise. The Whiten’s model was applied to illustrate the influence of density on the sharpness of classification, corrected cut size and fishhook effect. Results show that material with a lower density would have a higher fishhook effect parameter, classification sharpness and corrected cut size. The increase of air amount would result in a more evident fishhook effect for the high density material. Based on the Whiten’s model, a new classification efficiency model with the addition of particle density in various forms was established. This new model could describe the classification efficiency of materials with different density in the identical experiment conditions.
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