Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry-Reference-Cited by-同舟云学术

Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Published:2020-03-26 Issue:5 Volume:16 Page:3084-3094
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Fabregat Raimon¹,Fabrizio Alberto¹²^ORCID,Meyer Benjamin¹²,Hollas Daniel¹^ORCID,Corminboeuf Clémence¹²^ORCID

Affiliation:

1. Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, École polytechnique fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland

2. National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École polytechnique fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland

Funder

Schweizerischer Nationalfonds zur F?rderung der Wissenschaftlichen Forschung

H2020 European Research Council

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

http://pubs.acs.org/doi/pdf/10.1021/acs.jctc.0c00100

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1. Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces

2. Metadynamics Simulations of the High-Pressure Phases of Silicon Employing a High-Dimensional Neural Network Potential