Identifying materials that can efficiently separate CO2 from natural gas (CO2/CH4), power-plant flue gas (CO2/N2), and petroleum refinery gas streams (CO2/H2) is crucial. We used molecular simulations to examine the adsorption-based separation performances of MOFs in the separations of CO2/CH4, CO2/N2, and CO2/H2 mixtures under different operating conditions. We first compared the results of our molecular simulations with the experimentally available data for the CO2 adsorption and separation performances of various MOFs. Motivated by the good agreement between simulations and experiments, we extended our simulations to 100 different MOF materials. Several adsorbent evaluation metrics including selectivity, working capacity, adsorption figure of merit, sorbent selection parameter, and percentage regenerability were computed for each MOF and for each gas separation. The rankings of the MOFs based on these metrics were examined in detail to understand which parameters play key roles in assessing the gas separation potential of MOF adsorbents. The results showed that regenerability is a very important metric for screening materials in the first step of the adsorbent search and MOFs can then be ranked according to selectivity. We also examined the relationships between easily computable structural properties of MOFs, such as pore size, surface area, and porosity, and adsorbent evaluation metrics to provide structure–property relationships that can serve as a guide for experimental studies. Materials with pore sizes of 4–7 Å, surface areas of 200–800 m2/g, and porosities of 0.18–0.50 were found to be the best adsorbent candidates for CO2/CH4, CO2/N2, and CO2/H2 separations. Finally, the kinetic-based separation potentials of the MOFs that were identified as the top-performing materials for adsorption-based separations were analyzed. Both the membrane selectivities and the permeabilities of the MOFs were computed for three gas separation processes. Several MOFs were identified to outperform polymers and zeolites in membrane-based CO2 separations.

Metal organic frameworks (MOFs) have been widely studied as adsorbents and membranes for gas separation applications. Considering the large number of available MOFs, it is not possible to fabricate and test the gas separation performance of every single MOF using purely experimental methods. In this study, we used molecular simulations to assess both adsorption-based and membrane-based CH4/N2 separation performances of 102 different MOFs. This is the largest number of MOF adsorbents and membranes studied to date for separation of CH4/N2 mixtures. Several adsorbent evaluation metrics such as adsorption selectivity, working capacity, and regenerability were predicted, and the top performing adsorbents were identified. Several MOFs were predicted to exhibit higher adsorption selectivities than the traditional adsorbents such as zeolites and activated carbons. Relation between adsorption-based separation performances of MOFs and their structural properties were also investigated. Results showed that MOFs having the largest cavity diameters in the range of 4.6–5.4 Å, pore limiting diameters in the range of 2.4–3.7 Å, surface areas less than 2000 m2/g, and porosities less than 0.5 are promising adsorbents for CH4/N2 separations. We then combined adsorption and diffusion data obtained from molecular simulations and predicted both membrane selectivities and gas permeabilities of MOFs for separation of CH4/N2 mixtures. A significant number of MOF membranes were identified to be CH4 selective in contrast to the traditional membrane materials which are generally N2 selective. Several MOFs exceeded the upper bound established for the polymeric membranes, and many MOFs exhibited higher gas permeabilities than zeolites. The results of this study will be useful to guide the experiments to the most promising MOF adsorbents and membranes for efficient separation of CH4/N2 mixtures.

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In an attempt to bridge the gap between computational and experimental studies, coarse-grained simulations are used to study nematic Liquid Crystal (LC) nanodroplets dispersed in water. A LC phase diagram is generated as a function of droplet size and temperature, and the effect of adding surfactants is quantified.