Neural Network Water Model Based on the MB-Pol Many-Body Potential-Reference-Cited by-同舟云学术

Neural Network Water Model Based on the MB-Pol Many-Body Potential

Published:2023-10-12 Issue:42 Volume:127 Page:9165-9171
ISSN:1520-6106
Container-title:The Journal of Physical Chemistry B
language:en
Short-container-title:J. Phys. Chem. B

Author:

Muniz Maria Carolina¹^ORCID,Car Roberto²^ORCID,Panagiotopoulos Athanassios Z.¹^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, United States

2. Department of Chemistry, Department of Physics, Program in Applied and Computational Mathematics, and Princeton Materials Institute, Princeton University, Princeton, New Jersey 08544, United States

Funder

Basic Energy Sciences

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,Surfaces, Coatings and Films,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.3c04629

Reference53 articles.

1. A general purpose model for the condensed phases of water: TIP4P/2005

2. A potential model for the study of ices and amorphous water: TIP4P/Ice

3. Quantum, intramolecular flexibility, and polarizability effects on the reproduction of the density anomaly of liquid water by simple potential functions

4. Comparison of simple potential functions for simulating liquid water

5. Characterization of the TIP4P-Ew water model: Vapor pressure and boiling point

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