Predicting Thermodynamic Properties of Alkanes by High-Throughput Force Field Simulation and Machine Learning-Reference-Cited by-同舟云学术

Predicting Thermodynamic Properties of Alkanes by High-Throughput Force Field Simulation and Machine Learning

Published:2018-09-11 Issue:12 Volume:58 Page:2502-2516
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Gong Zheng¹,Wu Yanze¹,Wu Liang¹,Sun Huai¹^ORCID

Affiliation:

1. School of Chemistry and Chemical Engineering, Materials Genome Initiative Center, and Key Laboratory of Scientific and Engineering Computing of Ministry of Education, Shanghai Jiao Tong University, Shanghai, China 200240

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.8b00407

Reference60 articles.

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5. Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids

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