Formation enthalpies for transition metal alloys using machine learning | Zendy

Shashanka Ubaru | Zendy; Agnieszka Międlar | Zendy; Yousef Saad | Zendy; James R. Chelikowsky | Zendy

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Formation enthalpies for transition metal alloys using machine learning

Author(s) -

Shashanka Ubaru,

Agnieszka Międlar,

Yousef Saad,

James R. Chelikowsky

Publication year - 2017

Publication title -

physical review. b./physical review. b

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.78

H-Index - 465

eISSN - 2469-9969

pISSN - 2469-9950

DOI - 10.1103/physrevb.95.214102

Subject(s) - intermetallic , enthalpy , variety (cybernetics) , thermodynamics , computer science , artificial intelligence , machine learning , binary number , feature selection , materials science , support vector machine , lasso (programming language) , algorithm , mathematics , alloy , physics , metallurgy , arithmetic , world wide web

Shashanka Ubaru,1,* Agnieszka Międlar,2,† Yousef Saad,1,‡ and James R. Chelikowsky3,§ 1Department of Computer Science and Engineering, University of Minnesota, Twin Cities, Minnesota 55455, USA 2Department of Mathematics, University of Kansas, Lawrence, Kansas 66045-7594, USA 3Center for Computational Materials, Institute for Computational Engineering and Science, and Departments of Physics and Chemical Engineering, University of Texas, Austin, Texas 78712, USA (Received 18 June 2016; revised manuscript received 14 February 2017; published 1 June 2017)

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