Machine learning for perovskite materials design and discovery

作     者：Qiuling Tao Pengcheng Xu Minjie Li Wencong Lu 

作者机构：Department of ChemistryCollege of SciencesShanghai UniversityShanghaiChina Materials Genome InstituteShanghai UniversityShanghaiChina 

出 版 物：《npj Computational Materials》 (计算材料学（英文）)

年 卷 期：2021年第7卷第1期

页      面：171-188页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Financial support to this work from the National Key Research and Development Program of China(No.2016YFB0700504) the Science and Technology Commission of Shanghai Municipality(18520723500)is gratefully acknowledged 

主　　题：materials perovskite inorganic 

摘      要：The development of materials is one of the driving forces to accelerate modern scientific progress and technological *** learning(ML)technology is rapidly developed in many fields and opening blueprints for the discovery and rational design of *** this review,we retrospected the latest applications of ML in assisting perovskites ***,the development tendency of ML in perovskite materials publications in recent years was organized and ***,the workflow of ML in perovskites discovery was *** the applications of ML in various properties of inorganic perovskites,hybrid organic–inorganic perovskites and double perovskites were briefly *** the end,we put forward suggestions on the future development prospects of ML in the field of perovskite materials.