Machine learning approaches for structural and thermodynamic properties of a Lennard-Jones fluid-Reference-Cited by-同舟云学术

Machine learning approaches for structural and thermodynamic properties of a Lennard-Jones fluid

Published:2020-09-14 Issue:10 Volume:153 Page:104502
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Craven Galen T.¹^ORCID,Lubbers Nicholas²^ORCID,Barros Kipton¹^ORCID,Tretiak Sergei³^ORCID

Affiliation:

1. Theoretical Division and Center for Nonlinear Studies (CNLS), Los Alamos National Laboratory, Los Alamos, New Mexico 87544, USA

2. Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87544, USA

3. Theoretical Division, Center for Nonlinear Studies (CNLS), and Center for Integrated Nanotechnologies (CINT), Los Alamos National Laboratory, Los Alamos, New Mexico 87544, USA

Funder

Los Alamos National Laboratory

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://aip.scitation.org/doi/am-pdf/10.1063/5.0017894

Reference71 articles.

1. Radial Distribution Function Calculated by the Monte‐Carlo Method for a Hard Sphere Fluid

2. Studies in Molecular Dynamics. I. General Method

3. Improved simulation of liquid water by molecular dynamics

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