Machine learning-assisted materials design, mechanistic insights, and predictive modeling for high performance lithium-sulfur batteries

Energy storage materials 2026

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Authors: Kaijie Miao, Chengwei Ma, Jiangqi Zhou
DOI: 10.1016/j.ensm.2026.105315
Cited by: 1
References: 137

Fields of Study & Subjects

Advanced Battery Materials and Technologies Advanced Battery Technologies Research Machine Learning in Materials Science

Publication details

Journal / source
Energy storage materials
Publisher
Elsevier BV
Volume
90
Pages
105315–105315
Publication date
21 June 2026
Language
EN