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Quantum Calculations on a New CCSD(T) Machine-Learned Potential Energy Surface Reveal the Leaky Nature of Gas-Phase Trans and Gauche Ethanol Conformers
External Source
chorus
Document Type
Accepted Manuscript
Authors
Apurba Nandi (Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States)
Riccardo Conte (Dipartimento di Chimica, Università Degli Studi di Milano, via Golgi 19, 20133 Milano, Italy)
Chen Qu (Independent Researcher, Toronto 66777, Canada)
Paul L. Houston (Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States)
Qi Yu (Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States)
Joel M. Bowman (Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States)
Date Acquired
February 10, 2024
Publication Date
August 11, 2022
Publication Information
Publication: Journal of Chemical Theory and Computation
Publisher: American Chemical Society (ACS)
Volume: 18
Issue: 9
Issue Publication Date: September 13, 2022
ISSN: 1549-9618
e-ISSN: 1549-9626
DOI: 10.1021/acs.jctc.2c00760
Funding Number(s)
funding: PSR, Azione A Linea 2 - Fondi Giovani Ricercatori
funding: 911NF-14-1-0471
funding: 80NSSC20K0360
Distribution Limits
Public
Keywords
physical and theoretical chemistry
computer science applications

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