학술논문
Physically informed artificial neural networks for atomistic modeling of materials
Document Type
article
Author
Source
Nature Communications, Vol 10, Iss 1, Pp 1-10 (2019)
Subject
Language
English
ISSN
2041-1723
Abstract
Traditional machine learning potentials suffer from poor transferability to unknown structures. Here the authors present an approach to improve the transferability of machine-learning potentials by including information on the physical nature of interatomic bonding.