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