The sodium-ion batteries have low energy density, low capacity and inferior cycling performance as compared to Li-ion batteries. However, lithium depletion poses a serious problem for production and cost of Li-ion batteries. In the present work, a NaNi1/3Mn1/3Co1/3O2 was synthesized as 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 modelling and optimization of fabrication process of 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 176 mAh/g obtained for 99 cycles was found which is better than those of conventional batteries used for commercial storage purposes.
Electrochemical Performance Enhancement of Sodium-ion Batteries Fabricated with NaNi1/3Mn1/3Co1/3O2 Cathodes using Support Vector Regression-Simplex Algorithm Approach
Manuscript received March 18, 2019; final manuscript received July 8, 2019; published online xx xx, xxxx. Assoc. Editor: Ying Sun.
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Ruhatiya, C., Singh, S., Goyal, A., Niu, X., Hanh Nguyen, T. N., Nguyen, V. H., Tran, V. M., Phung Le, M. L., Garg, A., and Gao, L. (July 25, 2019). "Electrochemical Performance Enhancement of Sodium-ion Batteries Fabricated with NaNi1/3Mn1/3Co1/3O2 Cathodes using Support Vector Regression-Simplex Algorithm Approach." ASME. J. Electrochem. En. Conv. Stor. doi: https://doi.org/10.1115/1.4044358
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