Interfacial Optimization for AlN/Diamond Heterostructures via Machine Learning Potential Molecular Dynamics Investigation of the Mechanical Properties

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Zijun Qi, Xiang Sun, Zhanpeng Sun, Qijun Wang, Dongliang Zhang, Kang Liang, Rui Li, Diwei Zou, Lijie Li

, Gai Wu

, Wei Shen, Sheng Liu

ACS Applied Materials & Interfaces, Volume: 16, Issue: 21, Pages: 27998 - 28007

Swansea University Author: Lijie Li

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DOI (Published version): 10.1021/acsami.4c06055

Published in:	ACS Applied Materials & Interfaces
ISSN:	1944-8244 1944-8252
Published:	American Chemical Society (ACS) 2024
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa68007

Keywords:	AlN/diamond heterostructure; neuroevolution machine learning potential; molecular dynamics; interfacial mechanical property; interfacial structure optimization
College:	Faculty of Science and Engineering
Funders:	This work was funded by the National Natural Science Foundation of China (Grant Nos. 52202045 and 62004141), the Knowledge Innovation Program of Wuhan-Shuguang (Grant Nos. 2023010201020243 and 2023010201020255), the Fundamental Research Funds for the Central Universities (Grant Nos. 2042023kf0112 and 2042022kf1028), the Major Program (JD) of Hubei Province (Grant No. 2023BAA009), the Hubei Natural Science Foundation (Grant No. 2022CFB606), the Open Fund of Hubei Key Laboratory of Electronic Manufacturing and Packaging Integration (Wuhan University) (Grant Nos. EMPI2024014 and EMPI2023027), and the China Scholarship Council (Grant No. 202206275005). The numerical calculations in this paper have been done on the supercomputing system in the Supercomputing Center of Wuhan University.
Issue:	21
Start Page:	27998
End Page:	28007