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On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets

TitleOn-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets
Publication TypeJournal Article
Year of Publication2014
AuthorsKusne, AG, Gao, TR, Mehta, A, Ke, LQ, Nguyen, MC, Ho, KM, Antropov, V, Wang, CZ, Kramer, MJ, Long, C, Takeuchi, I
JournalScientific Reports
Volume4
Pagination6367
Date Published09
Type of ArticleArticle
ISBN Number2045-2322
Accession NumberWOS:000341937200007
Keywordsalloys, augmented-wave method, density-functional theory, diffraction, gradient, identification, Microstructure
Abstract

ture database (ICSD), we can substantially enhance the accuracy in classifying the structural phases across ternary phase spaces. We have used this approach to identify a novel magnetic phase with enhanced magnetic anisotropy which is a candidate for rare-earth free permanent magnet.

DOI10.1038/srep06367
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Bonded Magnets