Machine Learning-Aided Exploration of Ultrahard Materials

journal contribution

posted on 2023-02-03, 05:01 authored by Sherif AbbasSherif Abbas, Phuoc NguyenPhuoc Nguyen, Truyen TranTruyen Tran, Tiffany WalshTiffany Walsh, Svetha VenkateshSvetha Venkatesh

Machine Learning-Aided Exploration of Ultrahard Materials

History

Journal

Journal of Physical Chemistry C

Volume

126

Pagination

15952-15961

Location

Washington, D.C.

Publisher DOI

https://doi.org/10.1021/acs.jpcc.2c03926

ISSN

1932-7447

eISSN

1932-7455

Language

English

Author URL

https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000856652700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a045e4b2bb1f2b747c68c720ec8913b7

Publication classification

C1 Refereed article in a scholarly journal

Issue

37

Publisher

American Chemical Society

Publication URL

http://dx.doi.org/10.1021/acs.jpcc.2c03926

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Keywords

AB-INITIO Chemistry Chemistry, Physical DEFORMATION DESIGN DYNAMICS ELASTIC PROPERTIES HARDNESS HYDROGEN MAGNESIUM Materials Science Materials Science, Multidisciplinary MECHANICAL-PROPERTIES Nanoscience & Nanotechnology Physical Sciences PREDICT Science & Technology Science & Technology - Other Topics Technology

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All Rights Reserved

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