Topology-Based Phase Identification of Bulk, Interface, and Confined Water Using an Edge-Conditioned Convolutional Graph Neural Network-Reference-Cited by-同舟云学术

Topology-Based Phase Identification of Bulk, Interface, and Confined Water Using an Edge-Conditioned Convolutional Graph Neural Network

Published:2023-01-26 Issue:5 Volume:127 Page:2612-2621
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Moradzadeh A.¹^ORCID,Oliaei H.¹,Aluru N. R.²^ORCID

Affiliation:

1. Department of Mechanical Science and Engineering, University of Illinois at Urbana−Champaign, Urbana, Illinois61801, United States

2. Oden Institute for Computational Engineering and Sciences, Walker Department of Mechanical Engineering, the University of Texas at Austin, Austin, Texas78712, United States

Funder

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.2c07423

Reference52 articles.

1. Nanostructured transition metal dichalcogenide electrocatalysts for CO 2 reduction in ionic liquid

2. A Phenomenological Model of Water Transport in a Proton Exchange Membrane Fuel Cell

3. Single-layer MoS2 nanopores as nanopower generators

4. Water desalination with a single-layer MoS2 nanopore

5. Relationship between structural order and the anomalies of liquid water

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