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

cornell university

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