Affiliation:
1. College of Polymer Science and Engineering State Key Laboratory of Polymer Materials Engineering Sichuan University Chengdu Sichuan 610065 China
2. Jiangsu Yaoning New Energy Innovation Technology Co., Ltd Binhaier Road No. 818, Hangzhou Bay New Area Ningbo Zhejiang 315336 China
3. School of Chemistry and Environment Southwest Minzu University Chengdu Sichuan 610225 China
4. State key Laboratory of Biotherapy and Cancer Center West China Hospital Sichuan University Chengdu Sichuan 610041 China
5. Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing 100084 China
Abstract
AbstractThe success of liquid/solid‐state batteries is fundamentally determined by the electrode microstructures, which is particularly true for high‐energy‐density electrodes with either thick configuration or high‐capacity active materials. Unfortunately, high‐energy‐density electrodes usually suffer from fast performance degradation due to various challenging issues in microstructures. Therefore, a better understanding of electrode microstructures and the strategies toward optimizing them are in urgent need by the research community and battery industries. In this review, the authors attempt to rethink and comprehensively understand the multiscale microstructures for particularly thick electrodes and to summarize the corresponding structuring strategies. Specifically, in analogy to proteins, the multiscale electrode microstructures are classified into the primary structures of rigid building blocks, the secondary structures of active material microenvironment, and the tertiary structures of electrode architectures. Meanwhile, the design principles and structuring strategies at different levels of microstructures are detailed with consideration given to efficiency, energy consumption, eco‐friendliness, and scalability. Finally, a concept of a battery manufacturing genome based on structuring strategy profile (similar to amino acid profile) is proposed as the forthcoming opportunity for the future connection of machine learning with battery microstructure optimization, which may promote the development of next‐generation on‐demand batteries.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Sichuan University
Subject
General Materials Science,Renewable Energy, Sustainability and the Environment
Cited by
10 articles.
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