Multicomponent Diffusion in Nanosystems

TL;DR

This paper develops a comprehensive theoretical and numerical framework for analyzing multicomponent diffusion in nanosystems, integrating liquid state theory with lattice Boltzmann methods to study inhomogeneous fluid mixtures and their transport properties.

Contribution

It introduces a novel combined approach using kinetic and density functional theories with lattice Boltzmann implementation for multicomponent nanoscale diffusion analysis.

Findings

Numerical data on mutual diffusion in bulk fluids.

Analysis of diffusion under shear flow and Taylor dispersion.

Effective scheme for solving kinetic equations in nanosystems.

Abstract

We present the detailed analysis of the diffusive transport of spatially inhomogeneous fluid mixtures and the interplay between structural and dynamical properties varying on the atomic scale. The present treatment is based on different areas of liquid state theory, namely kinetic and density functional theory and their implementation as an effective numerical method via the Lattice Boltzmann approach. By combining the first two methods it is possible to obtain a closed set of kinetic equations for the singlet phase space distribution functions of each species. The interactions among particles are considered within a self-consistent approximation and the resulting effective molecular fields are analyzed. We focus on multispecies diffusion in systems with short-range hard-core repulsion between particles of unequal sizes and weak attractive long-range interactions. As a result, the attractive part of the potential does not contribute explicitly to viscosity but to diffusivity and the thermodynamic properties. Finally, we obtain a practical scheme to solve the kinetic equations by employing a discretization procedure derived from the Lattice Boltzmann approach. Within this framework, we present numerical data concerning the mutual diffusion properties both in the case of a quiescent bulk fluid and shear flow inducing Taylor dispersion.