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DOE OSTI · 1678825

Neural Network Interatomic Potentials

Saavedra, Gary Joseph·Thompson, Aidan P.
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Abstract

In this project, we investigate the use of neural networks for the prediction of molecular properties, namely the interatomic potential. We use the machine learning package Tensorflow to build a variety of neural networks and compare performance with a popular Fortran package - Atomic Energy Networks (aenet). There are two primary goals for this work: 1) use the wide availability of different optimization techniques in Tensorflow to outperform aenet and 2) use new descriptors that can outperform Behler descriptors.

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74 ATOMIC AND MOLECULAR PHYSICS97 MATHEMATICS AND COMPUTING

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BibTeXRIS

Saavedra, Gary Joseph, Thompson, Aidan P.. 2020-09-01. Neural Network Interatomic Potentials. https://doi.org/10.2172/1678825

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