Machine Learning Boosting the Development of Advanced Lithium Batteries

Abstract Lithium batteries (LBs) have many high demands regarding their application in portable electronic devices, electric vehicles, and smart grids. Machine learning (ML) can effectively accelerate the discovery of materials and predict their performances for LBs, which is thus able to markedly enhance the development of advanced LBs. In recent years, there have been many successful examples of using ML for advanced LBs. In this review, the basic procedure and representative methods of ML are briefly introduced to promote understanding of ML by experts in LBs. Then, the application of ML in developing LBs is highlighted for the purpose of attracting more attention to this field. Finally, the challenges and perspectives of ML are noted for the further development of LBs. It is hoped that this review can shed light on the application of ML in developing LBs and boost the development of advanced LBs.