Efficient sampling of high-energy states by machine learning force fields-Reference-Cited by-同舟云学术

Efficient sampling of high-energy states by machine learning force fields

Published:2020 Issue:25 Volume:22 Page:14364-14374
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Plazinski Wojciech¹²³^ORCID,Plazinska Anita⁴⁵⁶³^ORCID,Brzyska Agnieszka¹²³^ORCID

Affiliation:

1. Jerzy Haber Institute of Catalysis and Surface Chemistry Polish Academy of Sciences

2. 30-239 Krakow

3. Poland

4. Department of Biopharmacy

5. Medical University of Lublin Chodźki 4a

6. 20-093 Lublin

Abstract

A method extending the range of applicability of machine-learning force fields is proposed. It relies on biased subsampling of the high-energy states described by the predefined coordinate(s).

Funder

Narodowe Centrum Nauki

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2020/CP/D0CP01399D

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