Machine-learning-accelerated high-throughput materials screening: Discovery of novel quaternary Heusler compounds | Zendy

Kyoungdoc Kim | Zendy; Logan Ward | Zendy; Jiangang He | Zendy; Amar Krishna | Zendy; Ankit Agrawal | Zendy; Chris Wolverton | Zendy

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Machine-learning-accelerated high-throughput materials screening: Discovery of novel quaternary Heusler compounds

Author(s) -

Kyoungdoc Kim,

Logan Ward,

Jiangang He,

Amar Krishna,

Ankit Agrawal,

Chris Wolverton

Publication year - 2018

Publication title -

physical review materials

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.439

H-Index - 42

eISSN - 2476-0455

pISSN - 2475-9953

DOI - 10.1103/physrevmaterials.2.123801

Subject(s) - flexibility (engineering) , materials science , stability (learning theory) , crystal structure prediction , chemical space , set (abstract data type) , characterization (materials science) , crystal (programming language) , machine learning , throughput , task (project management) , crystal structure , artificial intelligence , computer science , algorithm , nanotechnology , drug discovery , mathematics , crystallography , bioinformatics , statistics , telecommunications , chemistry , management , programming language , economics , wireless , biology

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