Predicting Noble Gas Separation Performance of Metal Organic Frameworks Using Theoretical Correlations

In this work, we examined the accuracy of theoretical correlations that predict the performance of metal organic frameworks (MOFs) in separation of noble gas mixtures using only the single-component adsorption and diffusion data. Single component adsorption isotherms and self-diffusivities of Xe, Kr, and Ar in several MOFs were computed by grand canonical Monte Carlo and equilibrium molecular dynamics simulations. These pure component data were then used to apply Ideal Adsorbed Solution Theory (IAST) and Krishna-Paschek (KP) correlation for estimating the adsorption isotherms and self-diffusivities of Xe/Kr and Xe/Ar mixtures at various compositions in several representative MOFs. Separation properties of MOFs such as adsorption selectivity, working capacity, diffusion selectivity, permeation selectivity, and gas permeability were evaluated using the predictions of theoretical correlations and compared with the data obtained from computationally demanding molecular simulations. Results showed that theoretical correlations that predict mixture properties based on single-component data make accurate estimates for the separation performance of many MOFs which will be very useful for materials screening purposes.