Predicting single-phase solid solutions in as-sputtered high entropy alloys:High-throughput screening with machine-learning model

作     者：Ji-Chang Ren Junjun Zhou Christopher J.Butch Zhigang Ding Shuang Li Yonghao Zhao Wei Liu Ji-Chang Ren;Junjun Zhou;Christopher J.Butch;Zhigang Ding;Shuang Li;Yonghao Zhao;Wei Liu

作者机构：Nano and Heterogeneous Materials CenterSchool of Materials Science and EngineeringNanjing University of Science and TechnologyNanjing 210094China Department of Biomedical EngineeringNanjing UniversityNanjing 210023China 

出 版 物：《Journal of Materials Science & Technology》 (材料科学技术（英文版）)

年 卷 期：2023年第138卷第7期

页      面：70-79页

核心收录：

学科分类：08[工学] 080502[工学-材料学] 0805[工学-材料科学与工程（可授工学、理学学位）] 

基　　金：We acknowledge support from the National Natural Science Foundation of China(Nos.52271006,22173047) the Fundamental Research Funds for the Central Universities(Nos.30922010716,30920041116,0920021159,and 30919011405) 

主　　题：High entropy alloys Phase structures Machine learning Density functional theory 

摘      要：Searching for single-phase solid solutions(SPSSs)in high-entropy alloys(HEAs)is a prerequisite for the intentional design and manipulation of microstructures of alloys in vast composition ***,to date,reported SPSS HEAs are still rare due to the lack of reliable guiding principles for the synthesis of new SPSS ***,we demonstrate an ensemble machine-learning method capable of discovering SPSS HEAs by directly predicting quinary phase diagrams based only on atomic composition.A total of 2198 experimental structure data are extracted from as-sputtered quinary HEAs in the literature and used to train a random forest classifier(termed AS-RF)utilizing bagging,achieving a prediction accuracy of 94.6%compared with experimental *** AS-RF model is then utilized to predict 224 quinary phase diagrams including∼32,000 SPSS HEAs in Cr-Co-Fe-Ni-Mn-Cu-Al composition *** extrapolation capability of the AS-RF model is then validated by performing first-principle calculations using density functional theory as a benchmark for the predicted phase transition of newly predicted ***,interpretation of the AS-RF model weighting of the input parameters also sheds light on the driving forces behind HEA formation in sputtered systems with the main contributors being:valance electron concentration,work function,atomic radius difference and elementary symmetries.