摘要
With its extremely strong capability of data analysis,machine learning has shown versatile potential in the revolution of the materials research paradigm.Here,taking dielectric capacitors and lithium‐ion batteries as two representa-tive examples,we review substantial advances of machine learning in the research and development of energy storage materials.First,a thorough discussion of the machine learning framework in materials science is presented.Then,we summarize the applications of machine learning from three aspects,including discovering and designing novel materials,enriching theoretical simulations,and assisting experimentation and characterization.Finally,a brief outlook is highlighted to spark more insights on the innovative implementation of machine learning in materials science.
基金
This study was supported by the Basic Science Center Program of NSFC(Grant No.51788104)
Major Research Plan of NSFC(Grant No.92066103)
NSF of China(Grant No.52002300)
Major Program of NSFC(Grant No.51790490)
Young Elite Scientists Sponsorship Program by CAST(Frant No.2019QNRC001)。
