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McDonagh_et_al_2019.pdf (7.54 MB)
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Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields

preprint
submitted on 16.07.2019 and posted on 17.07.2019 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