Machine Learning-Guided Adaptive Parametrization for Coupling Terms in a Mixed United-Atom/Coarse-Grained Model for Diphenylalanine Self-Assembly in Aqueous Ionic Liquids-Reference-Cited by-同舟云学术

Machine Learning-Guided Adaptive Parametrization for Coupling Terms in a Mixed United-Atom/Coarse-Grained Model for Diphenylalanine Self-Assembly in Aqueous Ionic Liquids

Published:2023-09-19 Issue:19 Volume:19 Page:6718-6732
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Ge Yang¹,Wang Xueping¹,Zhu Qiang¹,Yang Yuqin²,Dong Hao²³⁴^ORCID,Ma Jing¹^ORCID

Affiliation:

1. Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China

2. Kuang Yaming Honors School, Nanjing University, Nanjing 210023, China

3. State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing 210023, China

4. Institute for Brain Sciences, Nanjing University, Nanjing 210023, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c00809

Reference97 articles.