Artificial intelligence for the understanding of electrolyte chemistry and electrode interface in lithium battery

Artificial intelligence for the understanding of electrolyte chemistry and electrode interface in lithium battery

Recognizing the critical role of electrolyte chemistry and electrode interfaces in the performance and safety of lithium batteries, along with the urgent need for more sophisticated methods of analysis, this comprehensive review underscores the promise of machine learning (ML) models in this researc...

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Bibliographic Details
Main Authors: Chen Yawei, Liu Yue, He Zixu, Xu Liang, Yu Peiping, Sun Qintao, Li Wanxia, Jie Yulin, Cao Ruiguo, Cheng Tao, Jiao Shuhong
Format: Article
Language:English
Published: Science Press 2023-12-01
Series:National Science Open
Subjects:
lithium batteries
battery interfaces
artificial intelligence
machine learning
electrolyte chemistry
Online Access:https://www.sciengine.com/doi/10.1360/nso/20230039

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