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整合分子动力学和机器学习用于金属电池的溶解导电解质优化

Xiwang Chang1,2, Yang Yang3, Weiheng Xu3

  • 1School of Materials Science & Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|June 30, 2025
PubMed
概括

研究人员使用模拟和机器学习开发了用于金属电池的新电解质. 这种优化的电解质显著提高了循环稳定性和库伦比效率 (CE),使电池寿命更长.

关键词:
电解质的电解质是一种电解质.金属电池是金属电池的一种.机器学习是机器学习.分子动力学分子动力学最好的趋势最好的趋势最好的趋势

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