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McDonagh_et_al_2019.pdf (7.54 MB)

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields

preprint
submitted on 16.07.2019, 10:43 and posted on 17.07.2019, 18:49 by James McDonagh, Ardita Shkurti, David J. Bray, Richard L. Anderson, Edward O. Pyzer-Knapp
This work demonstrates the use of open literature data to force field paramterization via a novel approach applying Bayesian optimization. We have selected Dissipative Particle Dynamics (DPD) as the simulation method in this proof-of-concept work.

Funding

STFC Hartree Centre Innovation: Return on Research programme

History

Email Address of Submitting Author

james.mcdonagh@uk.ibm.com

Institution

IBM Research

Country

UK

ORCID For Submitting Author

0000-0002-2323-6898

Declaration of Conflict of Interest

No conflict to declare

Version Notes

Initial version of manuscript

Exports