High-Throughput Aqueous Electrolyte Structure Prediction Using IonSolvR and Equivariant Graph Neural Network Potentials-Reference-Cited by-同舟云学术

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High-Throughput Aqueous Electrolyte Structure Prediction Using IonSolvR and Equivariant Graph Neural Network Potentials

Published:2023-10-16 Issue:42 Volume:14 Page:9508-9515
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Baker Sophie¹,Pagotto Joshua²,Duignan Timothy T.²³^ORCID,Page Alister J.¹^ORCID

Affiliation:

1. Discipline of Chemistry, College of Engineering, Science and Environment, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia

2. School of Chemical Engineering, The University of Queensland, St Lucia, Brisbane, QLD 4072, Australia

3. Queensland Micro- and Nanotechnology Centre, Griffith University, Nathan, Brisbane, QLD 4111, Australia

Funder

Australian Research Council

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.3c01783

Reference55 articles.

1. Molecular dynamics simulations of aqueous NaCl solutions at high pressures and temperatures

2. Is Water the Universal Solvent for Life?

3. Self-diffusion coefficients and orientational correlation times in aqueous NaCl solutions

4. Structure and dynamics of hydrated ions

5. X-ray and neutron diffraction studies on concentrated aqueous solutions of sodium nitrate and silver nitrate

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