Analytical Prediction of Gas Permeation through Graphene Nanopores of Varying Sizes: Understanding Transitions across Multiple Transport Regimes.

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2019
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Abstract
Nanoporous graphene is a promising candidate material for gas separation membranes, due to its atomic thickness and low cross-membrane transport resistance. The mechanisms of gas permeation through graphene nanopores, in both the large and small pore size limits, have been reported in the literature. However, mechanistic insights into the crossover from the small pore size limit to the large pore size limit are still lacking. In this study, we develop a comprehensive theoretical framework to predict gas permeance through graphene nanopores having a wide range of diameters using analytical equations. We formulate the transport kinetics associated with the direct impingement from the bulk and with the surface diffusion from the adsorption layer on graphene, and then combine them to predict the overall gas permeation rate using a reaction network model. We also utilize molecular dynamics simulations to validate and calibrate our theoretical model. We show that the rates of both the direct impingement and the surface diffusion pathways need to be corrected using different multiplicative factors, which are functions of temperature, gas kinetic diameter, and pore diameter. Further, we find a minor spillover pathway that originates from the surface adsorption layer, but is not included in our theoretical model. Finally, we utilize the corrected model to predict the permeances of CO, CH, and Ar through graphene nanopores. We show that as the pore diameter increases, gas transport through graphene nanopores can transition from being translocation dominated (pore diameter < 0.7 nm), to surface pathway dominated (pore diameter 1-2 nm), and finally to direct pathway dominated (pore diameter > 4 nm). The various gas permeation mechanisms outlined in this study will be particularly useful for the rational design of membranes made out of two-dimensional materials like graphene for gas separation applications.
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yuan2019analyticalacs Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yuan, Zhe;Misra, Rahul Prasanna;Govind Rajan, Ananth;Strano, Michael S;Blankschtein, Daniel;
Journal acs nano
Year 2019
DOI
10.1021/acsnano.9b05779
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