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Position-dependent dynamics explain pore-averaged diffusion in strongly attractive adsorptive systems

Published

Author(s)

William P. Krekelberg, Daniel W. Siderius, Vincent K. Shen, Thomas M. Truskett, Jeffrey R. Errington

Abstract

Using molecular simulations, we investigate the relationship between pore-averaged and position-dependent self- diffusivity of fluids adsorbed in strongly attractive pores as a function of loading. Previous work [Krekelberg et al., Langmuir 2013, 29, 14527] established that pore averaged self-diffusivity in the multilayer adsorption regime, where the fluid exhibits a dense ``film'' at the pore surface and a lower density ``interior pore'' region, is nearly constant as a function of loading. Here we show that this puzzling behavior can be understood in terms of how loading affects the fraction of particles that reside in the film and interior pore regions as well as their distinct dynamics. Specifically, the insensitivity of pore-averaged diffusivity to loading arises due to an approximate cancellation of two factors: an increase in the fraction of particles in the higher diffusivity interior pore region with loading and a corresponding decrease of the particle diffusivity in that region. We also find that the position-dependent self-diffusivities scale with the position-dependent density. We present a model for predicting the pore-average self-diffusivity based on the position dependent self-diffusivity, which captures the unusual characteristics of pore-averaged self-diffusivity in strongly attractive pores over several orders of magnitude.
Citation
Langmuir
Volume
33

Keywords

molecular dynamics, statistical mechanics, self-diffusivity, confined fluids, adsorption, diffusion

Citation

Krekelberg, W. , Siderius, D. , Shen, V. , Truskett, T. and Errington, J. (2017), Position-dependent dynamics explain pore-averaged diffusion in strongly attractive adsorptive systems, Langmuir, [online], https://doi.org/10.1021/acs.langmuir.7b03401 (Accessed December 7, 2024)

Issues

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Created November 10, 2017, Updated November 10, 2018