Unsupervised phase mapping of X-ray diffraction data by nonnegative matrix factorization integrated with custom clustering

作     者：Valentin Stanev Velimir V.Vesselinov A.Gilad Kusne Graham Antoszewski Ichiro Takeuchi Boian S.Alexandrov 

作者机构：Department of Materials Science and EngineeringUniversity of MarylandCollege ParkMD 20742USA Center for Nanophysics and Advanced MaterialsUniversity of MarylandCollege ParkMD 20742USA Joint Quantum InstituteUniversity of MarylandCollege ParkMD 20742USA Los Alamos National LaboratoryEarth Science DivisionLos AlamosNM 87545USA National Institute of Standards and TechnologyGaithersburgMD 20899USA Department of MathematicsUniversity of MarylandCollege ParkMD 20742USA Los Alamos National LaboratoryTheoretical DivisionLos AlamosNM 87545USA 

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

年 卷 期：2018年第4卷第1期

页      面：295-304页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：Velimir V.Vesselinov and Boian S.Alexandrov were supported by LANL LDRD grant 20180060 The work at UMD was funded by ONR N00014-13-1-0635,ONR 5289230 N000141512222 the National Science Foundation,DMR-1505103 

主　　题：properties. phase nonnegative 

摘      要：Analyzing large X-ray diffraction(XRD)datasets is a key step in high-throughput mapping of the compositional phase diagrams of combinatorial materials *** and automating this task can help accelerate the process of discovery of materials with novel and desirable ***,we report a new method for pattern analysis and phase extraction of XRD *** method expands the Nonnegative Matrix Factorization method,which has been used previously to analyze such datasets,by combining it with custom clustering and cross-correlation *** new method is capable of robust determination of the number of basis patterns present in the data which,in turn,enables straightforward identification of any possible peak-shifted ***-shifting arises due to continuous change in the lattice constants as a function of composition and is ubiquitous in XRD datasets from composition spread *** identification of the peak-shifted patterns allows proper quantification and classification of the basis XRD patterns,which is necessary in order to decipher the contribution of each unique single-phase structure to the multi-phase *** process can be utilized to determine accurately the compositional phase diagram of a system under *** presented method is applied to one synthetic and one experimental dataset and demonstrates robust accuracy and identification abilities.