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A deep potential model with long-range electrostatic interactions

Author(s): Zhang, Linfeng; Wang, Han; Muniz, Maria Carolina; Panagiotopoulos, Athanassios Z; Car, Roberto; et al

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Abstract: Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make molecular simulations with the accuracy of quantum mechanical density functional theory possible at a cost only moderately higher than that of empirical force fields. However, the majority of these models lack explicit long-range interactions and fail to describe properties that derive from the Coulombic tail of the forces. To overcome this limitation, we extend the DP model by approximating the long-range electrostatic interaction between ions (nuclei + core electrons) and valence electrons with that of distributions of spherical Gaussian charges located at ionic and electronic sites. The latter are rigorously defined in terms of the centers of the maximally localized Wannier distributions, whose dependence on the local atomic environment is modeled accurately by a deep neural network. In the DP long-range (DPLR) model, the electrostatic energy of the Gaussian charge system is added to short-range interactions that are represented as in the standard DP model. The resulting potential energy surface is smooth and possesses analytical forces and virial. Missing effects in the standard DP scheme are recovered, improving on accuracy and predictive power. By including long-range electrostatics, DPLR correctly extrapolates to large systems the potential energy surface learned from quantum mechanical calculations on smaller systems. We illustrate the approach with three examples: the potential energy profile of the water dimer, the free energy of interaction of a water molecule with a liquid water slab, and the phonon dispersion curves of the NaCl crystal.
Publication Date: 24-Mar-2022
Electronic Publication Date: 24-Mar-2022
Citation: Zhang, Linfeng, Wang, Han, Muniz, Maria Carolina, Panagiotopoulos, Athanassios Z, Car, Roberto, E, Weinan. (2022). A deep potential model with long-range electrostatic interactions. The Journal of Chemical Physics, 156 (12), 10.1063/5.0083669
DOI: doi:10.1063/5.0083669
ISSN: 0021-9606
EISSN: 1089-7690
Language: en
Type of Material: Journal Article
Journal/Proceeding Title: The Journal of Chemical Physics
Version: Final published version. This is an open access article.

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