Dielectric response with short-ranged electrostatics

Abstract

The dielectric nature of polar liquids underpins much of their ability to act as useful solvents, but its description is complicated by the long-ranged nature of dipolar interactions. This is particularly pronounced under the periodic boundary conditions commonly used in molecular simulations. In this article, the dielectric properties of a water model whose intermolecular electrostatic interactions are entirely short-ranged are investigated. This is done within the framework of local molecular field theory (LMFT), which provides a well controlled mean-field treatment of long-ranged electrostatics. This short-ranged model gives a remarkably good performance on a number of counts, and its apparent shortcomings are readily accounted for. These results not only lend support to LMFT as an approach for understanding solvation behavior, but are relevant to those developing interaction potentials based on local descriptions of liquid structure.

Main: 8 pages, 4 figures. SI: 4 pages, 1 figure. Link to publication in Proc. Natl. Acad. Sci: https://doi.org/10.1073/pnas.2005847117

References in corpus (24)

• Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics
• Statistically optimal analysis of samples from multiple equilibrium states
• Anomalously low dielectric constant of confined water
• A Performance and Cost Assessment of Machine Learning Interatomic Potentials
• Ab initio thermodynamics of liquid and solid water
• Symmetry-Adapted Machine-Learning for Tensorial Properties of Atomistic Systems
• Incorporating long-range physics in atomic-scale machine learning
• Connecting local structure to interface formation: a molecular scale van der Waals theory of nonuniform liquids
• Computing the dielectric constant of liquid water at constant dielectric displacement
• Interplay of local hydrogen-bonding and long-ranged dipolar forces in simulations of confined water
• Local molecular field theory for the treatment of electrostatics
• Note: On the dielectric constant of nanoconfined water
• Deconstructing classical water models at interfaces and in bulk
• Screened Coulombic Orientational Correlations in Dilute Aqueous Electrolytes
• Accurate Thermodynamics for Short-Ranged Truncations of Coulomb Interactions in Site-Site Molecular Models
• Efficient solutions of self-consistent mean field equations for dewetting and electrostatics in nonuniform liquids
• Finite field formalism for bulk electrolyte solutions
• On the efficient and accurate short-ranged simulations of uniform polar molecular liquids
• Relationship between Local Molecular Field Theory and Density Functional Theory for non-uniform liquids
• Interfacial ion solvation: Obtaining the thermodynamic limit from molecular simulations
• Analytic Theory of Finite-size Effects in Supercell Modelings of Charged Interfaces
• Using mean field theory to determine the structure of uniform fluids
• Screening of Coulomb interactions in liquid dielectrics
• Response Theory for Static and Dynamic Solvation of Ionic and Dipolar Solutes in Water

Cited by in corpus (16)

• Self-Consistent Determination of Long-Range Electrostatics in Neural Network Potentials
• Learning classical density functionals for ionic fluids
• Why neural functionals suit statistical mechanics
• Machine-Learning Interatomic Potentials for Long-Range Systems
• Macroscopic surface charges from microscopic simulations
• A classical density functional theory for solvation across length scales
• Quadrupole-mediated dielectric response and the charge-asymmetric solvation of ions in water
• Metadensity functional theory for classical fluids: Extracting the pair potential
• Equivariant Machine Learning Interatomic Potentials with Global Charge Redistribution
• Gauge invariance and hyperforce correlation theory for equilibrium fluid mixtures
• Learning intermolecular forces at liquid-vapor interfaces
• Can molecular simulations reliably compare homogeneous and heterogeneous ice nucleation?
• Static Dielectric Permittivity Profiles and Coarse-graining Approaches for Water in Graphene Slit Pores
• Metadensity functional learning for classical fluids: Regularizing with pair correlations
• Computing dielectric spectra in molecular dynamics simulations: using a cavity to disentangle self and cross correlations
• A unified machine-learning framework for ab initio multiscale modeling of liquids