Mapping between long-time molecular and Brownian dynamics

TL;DR

This paper uses computer simulations to develop an empirical mapping between long-time molecular and Brownian diffusivities in fluids with various particle interactions, aiding understanding of their dynamic behaviors.

Contribution

It introduces a semi-quantitative empirical expression for mapping diffusivities between molecular and Brownian dynamics across different interaction models.

Findings

Empirical mapping accurately describes inverse-power-law fluids.

The approach extends to softer, complex fluids like star-polymers and Gaussian-core.

It highlights challenges in relating dynamics of ultrasoft systems.

Abstract

We use computer simulations to test a simple idea for mapping between long-time self diffusivities obtained from molecular and Brownian dynamics. The strategy we explore is motivated by the behavior of fluids comprising particles that interact via inverse-power-law pair potentials, which serve as good reference models for dense atomic or colloidal materials. Based on our simulation data, we present an empirical expression that semi-quantitatively describes the "atomic" to "colloidal" diffusivity mapping for inverse-power-law fluids, but also for model complex fluids with considerably softer (star-polymer, Gaussian-core, or Hertzian) interactions. As we show, the anomalous structural and dynamic properties of these latter ultrasoft systems pose problems for other strategies designed to relate Newtonian and Brownian dynamics of hard-sphere-like particles.