General Atomic Neighborhood Fingerprint for Machine Learning-Based Methods
Author:
Affiliation:
1. School of Materials Science and Engineering, Georgia Institute of Technology, 771 Ferst Drive NW, Atlanta, Georgia 30332, United States
Funder
Office of Naval Research
Extreme Science and Engineering Discovery Environment (XSEDE)
Publisher
American Chemical Society (ACS)
Subject
Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.9b03925
Reference51 articles.
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