Bulletin of the American Physical Society
APS March Meeting 2019
Volume 64, Number 2
Monday–Friday, March 4–8, 2019; Boston, Massachusetts
Session K21: Emerging Trends in Molecular Dynamics Simulations and Data Analytics I
8:00 AM–11:00 AM,
Wednesday, March 6, 2019
BCEC Room: 157B
Sponsoring Unit: DCOMP
Chair: Rajiv Kalia, University of Southern California
Abstract: K21.00004 : Theoretical Studies of Water by Climbing Jacob’s Ladder with Deep Learning*
9:24 AM–9:36 AM
(Institute of Applied Physics and Computational Mathematics)
John P Perdew
Climbing up the so-called Jacob’s ladder within density functional theory is essential in order to accurately predict the properties of water. We use the Deep Potential (DP) model, a deep learning based potential energy model, to generate molecular dynamics trajectories with the accuracy of the fourth rung of Jacob's ladder of density functional, i.e., the SCAN meta-GGA functional mixed with a fraction of exact exchange (SCAN0). We further develop a deep learning methodology to characterize electronic properties of liquid water based on maximally localized Wannier functions. Due to the mitigation of self-interaction error and the ability to deal with large systems within the DP model, we observe systematically improved electronic, structural, and dynamical properties of liquid water. The excellent performance here leads to a new scheme in predicting water as well as aqueous solutions accurately.
*This work is supported by National Science Foundation (NSF), DMR Award DMR-1552287.
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