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Machine Learning-Enabled Development of Accurate Force Fields for Refrigerants.

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Bibliographic Details
Title: Machine Learning-Enabled Development of Accurate Force Fields for Refrigerants.
Authors: Wang N; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States., Carlozo MN; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States., Marin-Rimoldi E; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States., Befort BJ; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States., Dowling AW; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States., Maginn EJ; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Source: Journal of chemical theory and computation [J Chem Theory Comput] 2023 Jul 25; Vol. 19 (14), pp. 4546-4558. Date of Electronic Publication: 2023 Jun 12.
Publication Type: Journal Article
Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101232704 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-9626 (Electronic) Linking ISSN: 15499618 NLM ISO Abbreviation: J Chem Theory Comput Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1549-9626
DOI:10.1021/acs.jctc.3c00338