The Maxwell-Stefan description of mixture permeation across nanoporous graphene membranes

There is increasing research interest on the use of two-dimensional (2D) nanoporous materials, such as graphenes and graphene oxides, in a variety of membrane separation applications. The membrane permeation selectivitites are governed by a variety of factors that include surface diffusion as an important constituent. The primary objective of this article is to present a Maxwell-Stefan (M-S) formulation for surface diffusion of binary (1, 2) mixtures on 2D nanoporous graphene surfaces. In the developed formulation, adsorbate-adsorbate interactions, either attractive or repulsive, are described by the quasi-chemical (QC) mean field approximation of Guggenheim. Such interactions have a direct influence on the occupancy dependencies of the M-S diffusivities, D-1 and D-2, that quantify molecule-surface friction. An essential feature of the M-S formulation is the inclusion of exchange coefficients, D-12, that quantify correlation, or slowing-down effects for surface diffusion; the tardier-more-strongly-adsorbed species usually slows down the more-mobile-less-strongly-adsorbed species. Kinetic Monte Carlo (KMC) simulations on 2D square lattice of adsorption sites are used to quantify the the loading dependence of the M-S diffusivities, and also correlation effects. The usefulness of the developed model, combining QC and M-S approaches, is illustrated for CO2/CH4, CO2/H-2, CO2/N-2, and CH4/H-2, mixture separations. For all four mixtures, the neglect of correlation effects leads to a severe underestimation of the membrane permeation selectivities that favor the more strongly adsorbed species. (C) 2018 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.