Metal–organic frameworks (MOFs) are potential adsorbents for CO2 capture. Because thousands of MOFs exist, computational studies become very useful in identifying the top performing materials for target applications in a time-effective manner. In this study, molecular simulations were performed to screen the MOF database to identify the best materials for CO2 separation from flue gas (CO2/N2) and landfill gas (CO2/CH4) under realistic operating conditions. We validated the accuracy of our computational approach by comparing the simulation results for the CO2 uptakes, CO2/N2 and CO2/CH4 selectivities of various types of MOFs with the available experimental data. Binary CO2/N2 and CO2/CH4 mixture adsorption data were then calculated for the entire MOF database. These data were then used to predict selectivity, working capacity, regenerability, and separation potential of MOFs. The top performing MOF adsorbents that can separate CO2/N2 and CO2/CH4 with high performance were identified. Molecular simulations for the adsorption of a ternary CO2/N2/CH4 mixture were performed for these top materials to provide a more realistic performance assessment of MOF adsorbents. The structure–performance analysis showed that MOFs with ΔQst0 > 30 kJ/mol, 3.8 Å < pore-limiting diameter < 5 Å, 5 Å < largest cavity diameter < 7.5 Å, 0.5 < ϕ < 0.75, surface area < 1000 m2/g, and ρ > 1 g/cm3 are the best candidates for selective separation of CO2 from flue gas and landfill gas. This information will be very useful to design novel MOFs exhibiting high CO2 separation potentials. Finally, an online, freely accessible database was established, for the first time in the literature, which reports all of the computed adsorbent metrics of 3816 MOFs for CO2/N2, CO2/CH4, and CO2/N2/CH4 separations in addition to various structural properties of MOFs.

An extensive comparative analysis of two computation-ready MOF databases was provided to study adsorption and separation of CH4 and H2.

Several thousands of metal organic frameworks (MOFs) have been reported to date, but the information on H2/N2 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 H2 permeability and H2/N2 selectivity of 3765 different types of MOF membranes. Results showed that MOF membranes offer very high H2 permeabilities, 2.5 × 103 to 1.7 × 106 Barrer, and moderate H2/N2 membrane selectivities up to 7. The top 20 MOF membranes that exceed the polymeric membranes’ upper bound for H2/N2 separation were identified based on the results of initial screening performed at infinite dilution condition. Molecular simulations were then carried out considering binary H2/N2 and quaternary H2/N2/CO2/CO mixtures to evaluate the separation performance of MOF membranes under industrial operating conditions. Lower H2 permeabilities and higher N2 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 H2 permeability and high H2/N2 selectivity. Results showed that the most promising MOF membranes generally have large pore sizes (>6 Å) as well as high surface areas (>3500 m2/g) and high pore volumes (>1 cm3/g). We finally examined H2/N2 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 H2 permeabilities and slightly enhances H2/N2 selectivities of polymer membranes, which can advance the current membrane technology for efficient H2 purification.

Efficient separation of acetylene (C2H2) from CO2 and CH4 is important to meet the requirement of high-purity acetylene in various industrial applications. Metal organic frameworks (MOFs) are great candidates for adsorption-based C2H2/CO2 and C2H2/CH4 separations due to their unique properties such as wide range of pore sizes and tunable chemistries. Experimental studies on the limited number of MOFs revealed that MOFs offer remarkable C2H2/CO2 and C2H2/CH4 selectivities based on single-component adsorption data. We performed the first large-scale molecular simulation study to investigate separation performances of 174 different MOF structures for C2H2/CO2 and C2H2/CH4 mixtures. Using the results of molecular simulations, several adsorbent performance evaluation metrics, such as selectivity, working capacity, adsorbent performance score, sorbent selection parameter, and regenerability were computed for each MOF. Based on these metrics, the best adsorbent candidates were identified for both separations. Results showed that the top three most promising MOF adsorbents exhibit C2H2/CO2 selectivities of 49, 47, 24 and C2H2/CH4 selectivities of 824, 684, 638 at 1 bar, 298 K and these are the highest C2H2 selectivities reported to date in the literature. Structure-performance analysis revealed that the best MOF adsorbents have pore sizes between 4 and 11 Å, surface areas in the range of 600–1,200 m2/g and porosities between 0.4 and 0.6 for selective separation of C2H2 from CO2 and CH4. These results will guide the future studies for the design of new MOFs with high C2H2 separation potentials.