Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures-Reference-Cited by-同舟云学术

Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures

Published:2019-04-10 Issue:9 Volume:31 Page:3089-3102
ISSN:0897-4756
Container-title:Chemistry of Materials
language:en
Short-container-title:Chem. Mater.

Author:

Sasikumar Kiran¹,Chan Henry¹^ORCID,Narayanan Badri¹²,Sankaranarayanan Subramanian K. R. S.¹³^ORCID

Affiliation:

1. Center for Nanoscale Materials, Argonne National Laboratory, Argonne, Illinois 60439, United States

2. Department of Mechanical Engineering, University of Louisville, Louisville, Kentucky 40292, United States

3. Computation Institute, University of Chicago, Chicago, Illinois 60637, United States

Funder

Argonne National Laboratory

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemmater.8b03969

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