(776d) Toward Efficient Prediction of Gas Self-Diffusivity in Porous Materials

Liu, Y., University of California, Riverside
Fu, J., University of California, Riverside
Wu, J., University of California Riverside

We present an efficient computation procedure for rapid prediction of gas self-diffusivity in nanoporous materials by combination of the Knudsen theory, Rosenfeld's entropy scaling method, and a classical density functional theory (DFT). The self-diffusivity conforms to the Knudsen diffusion at low molecular density and the effects of intermolecular interactions at higher density are accounted for with Rosenfeld's entropy scaling method. The excess entropy required in the scaling analysis is calculated from the classical DFT that is able to predict the adsorption isotherms quantitatively. The hybrid computational procedure has been calibrated with MD simulation for the adsorption of simple fluids such as H2, He, Ne and CH4 in metal organic frameworks. It predicts different types of diffusion curves in excellent agreement with simulation observations. The calculation time cost is within one minute, which is appropriate for practical application. The theoretical procedure is expected extendable to more complicated fluids in porous materials including polymers.


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