Interpretable hybrid machine learning demystifies the degradation of practical lithium-sulfur batteries

doi:10.1016/j.jechem.2022.12.003

Journal of Energy Chemistry ›› 2023, Vol. 79 ›› Issue (4): 54-55.DOI: 10.1016/j.jechem.2022.12.003

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Interpretable hybrid machine learning demystifies the degradation of practical lithium-sulfur batteries

Zhi Wei Seh^*

Institute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis, Singapore 138634, Singapore

Received:2022-12-02 Accepted:2022-12-03 Online:2023-04-15 Published:2023-05-30
Contact: * E-mail address: sehzw@imre.a-star.edu.sg (Z.W. Seh).

Abstract

Zhi Wei Seh. Interpretable hybrid machine learning demystifies the degradation of practical lithium-sulfur batteries[J]. Journal of Energy Chemistry, 2023, 79(4): 54-55.

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URL: https://www.jenergychem.com/EN/10.1016/j.jechem.2022.12.003

https://www.jenergychem.com/EN/Y2023/V79/I4/54

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Interpretable hybrid machine learning demystifies the degradation of practical lithium-sulfur batteries

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