Open AccessMachine-learning-accelerated high-throughput materials screening: Discovery of novel quaternary Heusler compounds
Author(s) -
Kyoungdoc Kim,
Logan Ward,
Jiangang He,
Amar Krishna,
Ankit Agrawal,
Christopher 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