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• W2963040553 abstract "Abstract Sodium-ion batteries have low energy density, low capacity, and inferior cycling performance when compared with Li-ion batteries. However, lithium depletion poses a serious problem for the production and cost of Li-ion batteries. In the present work, NaNi1/3Mn1/3Co1/3O2 was synthesized as the cathode material for Na-ion batteries using the sol–gel method. The conventional cathode material used in Na-ion batteries had been replaced with the synthesized cathode material, and the data had been collected by performing charging/discharging experiments. The support vector regression synchronized cross-validation simplex algorithm cluster was then used for predictive modeling and optimization of the fabrication process of the positive electrode material of sodium-ion batteries. The stable normal distribution without any skewness validated the robustness of the model for better accuracy and stability of the Na-ion batteries. The optimized value of capacity is 176 mAh/g for 99 cycles, which is better than those of conventional batteries used for commercial storage purposes." @default.
• W2963040553 created "2019-07-30" @default.
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• W2963040553 date "2019-09-23" @default.
• W2963040553 modified "2023-09-22" @default.
• W2963040553 title "Electrochemical Performance Enhancement of Sodium-Ion Batteries Fabricated With NaNi1/3Mn1/3Co1/3O2 Cathodes Using Support Vector Regression-Simplex Algorithm Approach" @default.
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• W2963040553 doi "https://doi.org/10.1115/1.4044358" @default.
• W2963040553 hasPublicationYear "2019" @default.
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