On coarse-graining by the Inverse Monte Carlo method: Dissipative Particle Dynamics simulations made to a precise tool in soft matter modeling

TL;DR

This paper introduces a coarse-graining method that derives effective pairwise potentials from atomistic MD simulations using the Inverse Monte Carlo method, enabling accurate and larger-scale DPD simulations of soft matter systems.

Contribution

The paper presents a novel coarse-graining strategy that links atomistic MD with DPD via effective potentials obtained through Inverse Monte Carlo, improving simulation scale and accuracy.

Findings

DPD simulations agree well with MD results

Larger system sizes are feasible with the new method

Effective potentials accurately capture microstructure

Abstract

We present a promising coarse-graining strategy for linking micro- and mesoscales of soft matter systems. The approach is based on effective pairwise interaction potentials obtained from detailed atomistic molecular dynamics (MD) simulations, which are then used in coarse-grained dissipative particle dynamics (DPD) simulations. Here, the effective potentials were obtained by applying the Inverse Monte Carlo method [Lyubartsev and Laaksonen, Phys. Rev. E. vol. 52, 3730 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. In our first application of the method, the effective potentials were used in DPD simulations of aqueous NaCl solutions. With the same computational effort we were able to simulate systems of one order of magnitude larger as compared to the MD simulations. The results from the MD and DPD simulations are found to be in excellent agreement.