Materials Fingerprinting Classification-Reference-Cited by-同舟云学术

Materials Fingerprinting Classification

Published:2021-09 Issue: Volume:266 Page:108019
ISSN:0010-4655
Container-title:Computer Physics Communications
language:en
Short-container-title:Computer Physics Communications

Author:

Spannaus Adam^ORCID,Law Kody J.H.,Luszczek Piotr,Nasrin Farzana^ORCID,Micucci Cassie Putman^ORCID,Liaw Peter K.,Santodonato Louis J.,Keffer David J.^ORCID,Maroulas Vasileios^ORCID

Funder

National Science Foundation Directorate for Engineering

Oak Ridge National Laboratory

US Army Research Office

The University of Tennessee Knoxville

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Hardware and Architecture

Reference46 articles.

1. Machine learning for molecular and materials science

2. The high-throughput highway to computational materials design

3. Machine learning for phase selection in multi-principal element alloys

4. Learning atoms for materials discovery

5. Insightful classification of crystal structures using deep learning

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