Machine Learning towards Screening Solid-state Lithium Ion Conductors  

作　　者：LU Yang CHEN Xiang ZHAO Chen-Zi ZHANG Qiang 

机构地区：[1]Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology,Department of Chemical Engineering,Tsinghua University,Beijing 100084,China

出　　处：《Chinese Journal of Structural Chemistry》2020年第1期8-10,1,共4页结构化学（英文）

基　　金：Supported by the National Key Research and Development Program(2016YFA0202500);National Natural Science Foundation of China(21825501)。

摘　　要：Machine learning is an emerging method to discover new materials with specific characteristics.An unsupervised machine learning research is highlighted to discover new potential lithium ionic conductors by screening and clustering lithium compounds,providing inspirations for the development of solid-state electrolytes and practical batteries.

关 键 词：UNSUPERVISED machine learning first principles calculation solid state lithium ion CONDUCTORS ANION frameworks high IONIC CONDUCTIVITIES 

分 类 号：O646.1[理学—物理化学] TM912[理学—化学]