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Optimizing the preparation of palm kernel shell activated carbon for lithium polysulfide adsorption using response surface methodology and artificial neural network for high performance lithium‑sulfur battery
This study used response surface methodology (RSM) and artificial neural network (ANN) to predict and optimize lithium polysulfide (LiP) adsorption on nitrogen-doped activated carbon (NDAC). Firstly, the NDAC production from palm kernel shell was optimized using RSM, where statistical analysis indic...
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Published in: | Journal of energy storage 2024-09, Vol.98, p.113141, Article 113141 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | This study used response surface methodology (RSM) and artificial neural network (ANN) to predict and optimize lithium polysulfide (LiP) adsorption on nitrogen-doped activated carbon (NDAC). Firstly, the NDAC production from palm kernel shell was optimized using RSM, where statistical analysis indicated the best conditions to be an impregnation ratio (IR) of 2.0, an activation temperature of 880 °C, and an activation time of 80 min—with IR having the most significant impact on LiP adsorption. Experimental results from the RSM were then used to train the predictive capabilities of the ANN for LiP adsorption. Although both approaches effectively predicted the adsorption process, ANN exhibited a superior prediction accuracy, characterized by a higher coefficient of determination (R2) and a lower mean square error (MSE). The NDAC synthesized under optimized conditions was subsequently made into a cathode composite with sulfur (NDAC/S) and evaluated for its performance in a lithium‑sulfur (Li-S) battery. Experimental data indicated that the Li-S coin cell battery consisting of NDAC/S had a remarkable initial specific capacity of 1054.96 mAh/g and maintained a favorable capacity retention of 66 % after 100 cycles at 0.1C. This outstanding electrochemical performance is attributed to the synergistic effect of a hierarchical pore structure, large surface area, substantial pore volume, and the presence of doped nitrogen that provides strong chemical bonding with LiP.
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•Systematic analysis of individual factors and their interactions on LiP uptake.•Nitrogen-doped activated carbon prepared from palm kernel shells.•RSM and ANN models used for optimization.•Performance analysis of optimum nitrogen-doped activated carbon sulfur-cathode composite in lithium-sulfur batteries. |
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ISSN: | 2352-152X |
DOI: | 10.1016/j.est.2024.113141 |