Data-driven discovery of formation ability descriptors for high-entropy rare-earth monosilicates  

作　　者：Hong Meng Peng Wei Zhongyu Tang Hulei Yu Yanhui Chu 

机构地区：[1]School of Materials Science and Engineering,South China University of Technology,Guangzhou,510641,China

出　　处：《Journal of Materiomics》2024年第3期738-747,共10页无机材料学学报（英文）

基　　金：support from the National Key Research and Development Program of China(No.2022YFB3708600);the National Natural Science Foundation of China(No.52122204 and 51972116);Guangzhou Basic and Applied Basic Research Foundation(No.202201010632).

摘　　要：Herein we establish formation ability descriptors of high-entropy rare-earth monosilicates(HEREMs)via the data-driven discovery based on the high-throughput solid-state reaction and machine learning(ML)methods.Specifically,adequate high-quality data are generated with 132 samples synthesized by the self-developed high-throughput solid-state reaction apparatuses,and 30 potential descriptors are considered in ML simultaneously.Two classifications are proposed to study the phase formation of HEREMs via the ML approach combined with the genetic algorithm:(Ⅰ)to distinguish pure HEREMs(X)from other phases and(Ⅱ)to categorize the detail phases of HEREMs(X2,X1,or X2+X1).Four formation ability descriptors(r_(Me),EF,d_(Eg),and d_(Z*))with a high validation accuracy(96.2%)are proposed as the optimal combination for Classification I,where a smaller r_(Me)is determined to have the most significant influence on the formation of HEREMs.For ClassificationⅡ,a 100%validation accuracy is achieved by using only two formation ability descriptors(rion and d_(Z*)),where the rion is analyzed to be the dominant feature and a lower rion is beneficial to the formation of X2-HEREMs.Based on our established formation ability descriptors,6,045 unreported multicomponent silicates are explored,and 3,478 new HEREMs with 2,700 X2-and 423 X1-HEREMs are predicted.

关 键 词：High-entropy rare-earth monosilicates Formation ability descriptors High-throughput experiments Machine learning 

分 类 号：O62[理学—有机化学]