Automated generation and ensemble-learned matching of X-ray absorption spectra

查看全文 作　　者：Chen [1]Zheng;Kiran [2]Mathew;Chi [1]Chen;Yiming [1]Chen;Hanmei [1]Tang;Alan [3]Dozier;Joshua [4]J.Kas;Fernando [4]D.Vila;John [4]J.Rehr;Louis [5,6]F.J.Piper;Kristin [2]A.Persson;Shyue Ping [1]Ong

机构地区：[1]Department of NanoEngineering,University of California San Diego,9500 Gilman Drive,Mail Code 0448,La Jolla,CA 92093-0448,USA;[2]Department of Materials Science,University of California Berkeley,Berkeley,CA 94720,USA;[3]Division of Applied Research and Technology,National Institute for Occupational Safety and Health,Centers for Disease Control,Cincinnati,OH 45226,USA;[4]Department of Physics,University of Washington,Seattle,WA 98195,USA;[5]Department of Physics,Applied Physics and Astronomy,Binghamton University,Binghamton,NY 13902,USA;[6]Materials Science&Engineering,Binghamton University,Binghamton,NY 13902,USA

出　　处：《npj Computational Materials》索引2018年第1期,共9页

基　　金：This work is supported by the National Science Foundation’s Cyberinfrastructure Framework for 21st Century Science and Engineering(CIF21)program under Award No.1640899;The Materials Project,supported by the Department of Energy(DOE)Basic Energy Sciences(BES)program,under Grant No.EDCBEE is gratefully acknowledged for web dissemination and data infrastructure.The FEFF project is supported primarily by DOE BES Grant DE-FG02-97ER45623;We also acknowledge computational resources provided by Triton Shared Computing Cluster(TSCC)at the University of California,San Diego,the National Energy Research Scientific Computing Center(NERSC),and the Extreme Science and Engineering Discovery Environment(XSEDE)supported by National Science Foundation under grant number ACI-1053575.L.F.J.P.acknowledges support from the National Science Foundation(DMREF-1627583). 摘　　要：X-ray absorption spectroscopy(XAS)is a widely used materials characterization technique to determine oxidation states,coordination environment,and other local atomic structure information.Analysis of XAS relies on comparison of measured spectra to reliable reference spectra.However,existing databases of XAS spectra are highly limited both in terms of the number of reference spectra available as well as the breadth of chemistry coverage.In this work,we report the development of XASdb,a large database of computed reference XAS,and an Ensemble-Learned Spectra IdEntification(ELSIE)algorithm for the matching of spectra.XASdb currently hosts more than 800,000 K-edge X-ray absorption near-edge spectra(XANES)for over 40,000 materials from the open-science Materials Project database.We discuss a high-throughput automation framework for FEFF calculations,built on robust,rigorously benchmarked parameters.FEFF is a computer program uses a real-space Green’s function approach to calculate X-ray absorption spectra.We will demonstrate that the ELSIE algorithm,which combines 33 weak“learners”comprising a set of preprocessing steps and a similarity metric,can achieve up to 84.2% accuracy in identifying the correct oxidation state and coordination environment of a test set of 19 K-edge XANES spectra encompassing a diverse range of chemistries and crystal structures.The XASdb with the ELSIE algorithm has been integrated into a web application in the Materials Project,providing an important new public resource for the analysis of XAS to all materials researchers.Finally,the ELSIE algorithm itself has been made available as part of veidt,an open source machine-learning library for materials science. 关键词：MATCHING XANES ENSEMBLE

相关文献

参考文献（50）
引证文献（4）
耦合文献（0）

参考文献(50)

引证文献(4)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

Automated generation and ensemble-learned matching of X-ray absorption spectra

参考文献(50)

引证文献(4)

用户提示