Monte Carlo adaptive resolution simulation of multicomponent molecular liquids

TL;DR

This paper presents an efficient Monte Carlo adaptive resolution simulation method for multicomponent liquids, addressing thermodynamic imbalances with a Kirkwood Thermodynamic Integration-based compensation scheme.

Contribution

It introduces a novel scheme to regulate thermodynamic balance in multicomponent systems within adaptive resolution simulations.

Findings

Successful simulation of binary mixtures with thermodynamic balance correction

Demonstration of the method's efficiency in multicomponent systems

Improved accuracy in modeling complex soft matter systems

Abstract

Complex soft matter systems can be efficiently studied with the help of adaptive resolution simulation methods, concurrently employing two levels of resolution in different regions of the simulation domain. The non-matching properties of high- and low-resolution models, however, lead to thermodynamic imbalances between the system's subdomains. Such inhomogeneities can be healed by appropriate compensation forces, whose calculation requires nontrivial iterative procedures. In this work we employ the recently developed Hamiltonian Adaptive Resolution Simulation method to perform Monte Carlo simulations of a binary mixture, and propose an efficient scheme, based on Kirkwood Thermodynamic Integration, to regulate the thermodynamic balance of multi-component systems.