Several thousands of metal organic frameworks (MOFs) have been reported to date, but the information on H/N separation performances of MOF membranes is currently very limited in the literature. We report the first large-scale computational screening study that combines state-of-the-art molecular simulations, grand canonical Monte Carlo (GCMC) and molecular dynamics (MD), to predict H permeability and H/N selectivity of 3765 different types of MOF membranes. Results showed that MOF membranes offer very high H permeabilities, 2.5 × 10 to 1.7 × 10 Barrer, and moderate H/N membrane selectivities up to 7. The top 20 MOF membranes that exceed the polymeric membranes' upper bound for H/N separation were identified based on the results of initial screening performed at infinite dilution condition. Molecular simulations were then carried out considering binary H/N and quaternary H/N/CO/CO mixtures to evaluate the separation performance of MOF membranes under industrial operating conditions. Lower H permeabilities and higher N permeabilities were obtained at binary mixture conditions compared to the ones obtained at infinite dilution due to the absence of multicomponent mixture effects in the latter. Structure-performance relations of MOFs were also explored to provide molecular-level insights into the development of new MOF membranes that can offer both high H permeability and high H/N selectivity. Results showed that the most promising MOF membranes generally have large pore sizes (>6 Å) as well as high surface areas (>3500 m/g) and high pore volumes (>1 cm/g). We finally examined H/N separation potentials of the mixed matrix membranes (MMMs) in which the best MOF materials identified from our high-throughput screening were used as fillers in various polymers. Results showed that incorporation of MOFs into polymers almost doubles H permeabilities and slightly enhances H/N selectivities of polymer membranes, which can advance the current membrane technology for efficient H purification.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6537470 | PMC |
http://dx.doi.org/10.1021/acssuschemeng.9b01020 | DOI Listing |
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