Hydrodynamic interactions and Brownian forces in colloidal suspensions: Coarse-graining over time and length-scales

TL;DR

This paper presents a detailed coarse-grained simulation method combining Molecular Dynamics and Stochastic Rotation Dynamics to accurately model hydrodynamic and Brownian forces in colloidal suspensions, emphasizing parameter tuning and validation against theoretical results.

Contribution

It introduces a systematic coarse-graining scheme that resolves multiple time and length scales, controlling numerical artifacts and improving agreement with theoretical predictions.

Findings

Quantitative agreement of velocity auto-correlation functions with theory

Identification of limitations of the Langevin equation in colloidal dynamics

Guidelines for mapping simulation parameters to real systems

Abstract

We describe in detail how to implement a coarse-grained hybrid Molecular Dynamics and Stochastic Rotation Dynamics simulation technique that captures the combined effects of Brownian and hydrodynamic forces in colloidal suspensions. The importance of carefully tuning the simulation parameters to correctly resolve the multiple time and length-scales of this problem is emphasized. We systematically analyze how our coarse-graining scheme resolves dimensionless hydrodynamic numbers such as the Reynolds number, the Schmidt number, the Mach number, the Knudsen number, and the Peclet number. The many Brownian and hydrodynamic time-scales can be telescoped together to maximize computational efficiency while still correctly resolving the physically relevant physical processes. We also show how to control a number of numerical artifacts, such as finite size effects and solvent induced attractive depletion interactions. When all these considerations are properly taken into account, the measured colloidal velocity auto-correlation functions and related self diffusion and friction coefficients compare quantitatively with theoretical calculations. By contrast, these calculations demonstrate that, notwithstanding its seductive simplicity, the basic Langevin equation does a remarkably poor job of capturing the decay rate of the velocity auto-correlation function in the colloidal regime, strongly underestimating it at short times and strongly overestimating it at long times. Finally, we discuss in detail how to map the parameters of our method onto physical systems, and from this extract more general lessons that may be relevant for other coarse-graining schemes such as Lattice Boltzmann or Dissipative Particle Dynamics.