Neural network aided development of a semi-empirical interatomic potential for titanium

Volume: 171, Pages: 109157 - 109157
Published: Jan 1, 2020
Abstract
Artificial neural networks, utilizing machine learning techniques to uncover subtle and complex patterns in big data problems, are able to condense large amounts of computationally expensive density functional theory and ab initio results into classical force field potentials. However, in order to produce a computationally efficient network, with minimal network architecture, a structural fingerprint whose components are highly correlated to the...
Paper Details
Title
Neural network aided development of a semi-empirical interatomic potential for titanium
Published Date
Jan 1, 2020
Volume
171
Pages
109157 - 109157
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