Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session D17: Disorder and Fluctuations in Chemical Physics II
3:00 PM–5:48 PM,
Monday, March 6, 2023
Room: Room 209
Sponsoring
Unit:
DCP
Chair: Rakesh Singh, IISER Tirupati
Abstract: D17.00010 : Understanding Metal Ion Interactions in Solvents Using First-Principles and Machine Learning Interatomic Potentials*
5:36 PM–5:48 PM
Presenter:
Julia H Yang
(Harvard University)
Authors:
Julia H Yang
(Harvard University)
Kyle Bystrom
(Harvard University)
Boris Kozinsky
(Harvard University)
As first-principles-based computational modeling of metal ion transport in DESs is limited by simulation size and high viscosity arising from strong H-bonding, we apply machine learning approaches to approximate the potential energy surface (PES) for a metal ion and DES system comprising of divalent nickel and ethaline (a 1:2 molar ratio of choline chloride and ethylene glycol). We describe how reliably benchmarked quantum chemistry calculations with on-the-fly active learning using FLARE: Fast Learning of Atomistic Rare Events [1] generates representative training data which are used to train machine learning interatomic potentials to learn the PES. We apply our computational approach to study the transport of divalent nickel in ethaline.
[1] Vandermause, J., Torrisi, S.B., Batzner, S. et al. On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events. npj Comput Mater 6, 20 (2020).
*J.H.Y. is an Environmental Fellow supported by the Harvard University Center for the Environment.
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