QM/MM Methods for Crystalline Defects. Part 3: Machine-Learned MM Models-Reference-Cited by-同舟云学术

QM/MM Methods for Crystalline Defects. Part 3: Machine-Learned MM Models

Published:2022-12-20 Issue:4 Volume:20 Page:1490-1518
ISSN:1540-3459
Container-title:Multiscale Modeling & Simulation
language:en
Short-container-title:Multiscale Model. Simul.

Author:

Chen Huajie¹,Ortner Christoph²,Wang Yangshuai³

Affiliation:

1. School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China.

2. University of British Columbia, Vancouver V6T 1Z2, BC, Canada.

3. Corresponding author. Institute of Natural Sciences, School of Mathematical Sciences, and MOE-LSC, Shanghai Jiao Tong University, Shanghai 200240, China.

Funder

National Natural Science Foundation of China

Engineering and Physical Sciences Research Council

Leverhulme Trust

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Computer Science Applications,General Physics and Astronomy,Ecological Modeling,Modeling and Simulation,General Chemistry

Reference41 articles.

1. Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

2. Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces

3. Hybrid atomistic simulation methods for materials systems

4. Permutationally invariant potential energy surfaces in high dimensionality

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