Machine learning interatomic potential developed for molecular simulations on thermal properties of β-Ga2O3-Reference-Cited by-同舟云学术

Machine learning interatomic potential developed for molecular simulations on thermal properties of β-Ga2O3

Published:2020-10-14 Issue:14 Volume:153 Page:144501
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Liu Yuan-Bin¹,Yang Jia-Yue²³^ORCID,Xin Gong-Ming²^ORCID,Liu Lin-Hua²³,Csányi Gábor⁴,Cao Bing-Yang¹^ORCID

Affiliation:

1. Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China

2. School of Energy and Power Engineering, Shandong University, Jinan, Shandong 250061, China

3. Optics and Thermal Radiation Research Center, Shandong University, Qingdao, Shandong 266237, China

4. Engineering Laboratory, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom

Funder

Shenzhen Basic Research Program

Shandong University

National Natural Science Foundation of China

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0027643

Reference62 articles.

1. Deep-ultraviolet transparent conductive β-Ga2O3 thin films

2. A review of Ga2O3materials, processing, and devices

3. MBE grown Ga2O3 and its power device applications

4. Device-Quality $\beta$-Ga$_{2}$O$_{3}$ Epitaxial Films Fabricated by Ozone Molecular Beam Epitaxy

5. Thermal transport properties of GaN with biaxial strain and electron-phonon coupling

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