Grand-canonical molecular dynamics simulations powered by a hybrid 4D nonequilibrium MD/MC method: Implementation in LAMMPS and applications to electrolyte solutions

TL;DR

This paper presents an efficient implementation of a hybrid nonequilibrium MD/MC method for grand-canonical simulations in LAMMPS, enabling faster electrolyte solution studies with significant computational savings and practical exchange rates.

Contribution

The authors implemented and validated a hybrid 4D nonequilibrium MD/MC method in LAMMPS, significantly improving the efficiency of grand-canonical electrolyte simulations.

Findings

Electrostatic interactions are crucial for efficiency in electrolyte exchange.

Salt-pair exchange efficiency improved by approximately four orders of magnitude.

NaCl-pair exchange acceptance rate reaches about 3% at optimal conditions.

Abstract

Molecular simulations in an open environment, involving ion exchange, are necessary to study various systems, from biosystems to confined electrolytes. However, grand-canonical simulations are often computationally demanding in condensed phases. A promising method (L. Belloni, J. Chem. Phys., 2019), one of the hybrid nonequilibrium molecular dynamics/Monte Carlo algorithms, was recently developed, which enables efficient computation of fluctuating number or charge density in dense fluids or ionic solutions. This method facilitates the exchange through an auxiliary dimension, orthogonal to all physical dimensions, by reducing initial steric and electrostatic clashes in three-dimensional systems. Here, we report the implementation of the method in LAMMPS with a Python interface, allowing facile access to grand-canonical molecular dynamics (GCMD) simulations with massively parallelized computation. We validate our implementation with two electrolytes, including a model Lennard-Jones electrolyte similar to a restricted primitive model and aqueous solutions. We find that electrostatic interactions play a crucial role in the overall efficiency due to their long-range nature, particularly for water or ion-pair exchange in aqueous solutions. With properly screened electrostatic interactions and bias-based methods, our approach enhances the efficiency of salt-pair exchange in Lennard-Jones electrolytes by approximately four orders of magnitude, compared to conventional grand-canonical Monte Carlo. Furthermore, the acceptance rate of NaCl-pair exchange in aqueous solutions at moderate concentrations reaches about 3 $\%$ at the maximum efficiency.