Graph network based deep learning of bandgaps-Reference-Cited by-同舟云学术

Graph network based deep learning of bandgaps

Published:2021-10-21 Issue:15 Volume:155 Page:154702
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Li Xiang-Guo¹^ORCID,Blaiszik Ben²³,Schwarting Marcus Emory²³,Jacobs Ryan¹,Scourtas Aristana²³^ORCID,Schmidt K. J.²³,Voyles Paul M.¹^ORCID,Morgan Dane¹^ORCID

Affiliation:

1. Department of Materials Science and Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA

2. University of Chicago, Globus, Chicago, Illinois 60637, USA

3. Argonne National Laboratory, Data Science and Learning Division, Lemont, Illinois 60439, USA

Funder

National Science Foundation

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

https://aip.scitation.org/doi/am-pdf/10.1063/5.0066009

Reference44 articles.

1. Machine learning for molecular and materials science

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4. Informatics-aided bandgap engineering for solar materials

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