Machine Learning-Enabled Development of Accurate Force Fields for Refrigerants
Author:
Affiliation:
1. Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
Funder
U.S. Department of Education
National Science Foundation
Publisher
American Chemical Society (ACS)
Subject
Physical and Theoretical Chemistry,Computer Science Applications
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c00338
Reference67 articles.
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3. Phase Equilibria and Diffusivities of HFC-32 and HFC-125 in Ionic Liquids for the Separation of R-410A
4. Separation Process Synthesis for High-GWP Refrigerant Mixtures: Extractive Distillation using Ionic Liquids
5. Phase Equilibria, Diffusivities, and Equation of State Modeling of HFC-32 and HFC-125 in Imidazolium-Based Ionic Liquids for the Separation of R-410A
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