The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics
Author:
Affiliation:
1. Dept. of Chemistry and Biochemistry
2. The University of Notre Dame du Lac
3. USA
Abstract
We construct a robust chemistry consisting of a nearsighted neural network potential, TensorMol-0.1, with screened long-range electrostatic and van der Waals physics. It is offered in an open-source Python package and achieves millihartree accuracy and a scalability to tens-of-thousands of atoms on ordinary laptops.
Publisher
Royal Society of Chemistry (RSC)
Subject
General Chemistry
Link
http://pubs.rsc.org/en/content/articlepdf/2018/SC/C7SC04934J
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