Mechanical issues in sulfide-based all-solid-state batteries: Origin, monitoring, and intelligent analysis

被引:0
|
作者
Zhao, Yifei [1 ,4 ]
Qiang, Zhuomin [1 ]
Ning, Yanbin [1 ]
Li, Dalong [2 ]
Jiang, Tao [3 ,5 ]
Lou, Shuaifeng [1 ]
机构
[1] Harbin Inst Technol, Sch Chem & Chem Engn, State Key Lab Space Power Sources, Harbin 150001, Peoples R China
[2] Harbin Inst Technol Weihai, Sch Marine Sci & Technol, Weihai, Peoples R China
[3] China FAW Grp Co LTD, New Energy Dev Inst, Changchun, Peoples R China
[4] Tsinghua Univ, Dept Chem, Key Lab Organ Optoelect & Mol Engn, Minist Educ, Beijing 100084, Peoples R China
[5] China FAW Grp Co Ltd, Solid State Battery Grp, Changchun 130013, Peoples R China
基金
中国国家自然科学基金;
关键词
Sulfide all-solid-state batteries; Mechanical issues; In-situ monitoring; Intelligent analysis; LITHIUM; EXPANSION; CATHODE;
D O I
10.1016/j.nanoen.2024.110295
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The emergence of all-solid-state batteries(ASSLBs) for next-generation energy storage devices is garnering substantial attention due to ultrahigh energy density and safety. However, the coupling of electrochemical and mechanical issues in ASSLBs during long-term cycling presents significant challenges for potential applications. Inspired by that, this review provides an overview of the origin and evolution of mechanical issues in ASSLBs. The cross-scale electromechanical failure mechanisms are discussed, with an emphasis on approaches to stress- strain monitoring at various scales. The subsequent discussion elaborates on the immense potential of artificial intelligence techniques, particularly machine learning, in effectively addressing mechanical issues encountered in ASSLBs. The further development and application of machine learning technologies are proposed to significantly expedite comprehension of the electro-mechanical coupling mechanisms in ASSLBs, thereby providing novel insights for a more profound understanding and optimization of performance for ASSLBs.
引用
收藏
页数:15
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