Database for CO2 separation performances of MOFs based on computational materials screening

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/N-2) 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/N-2 and CO2/CH4 selectivities of various types of MOFs with the available experimental data. Binary CO2/N-2 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/N-2 and CO2/CH4 with high performance were identified. Molecular simulations for the adsorption of a ternary CO2/N-2/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 Delta Q(st)(0) > 30 kJ/mol, 3.8 angstrom 1 g/cm(3) 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 https://cosmoserc.ku.edu.tr was established, for the first time in the literature, which reports all of the computed adsorbent metrics of 3816 MOFs for CO2/N-2, CO2/CH4, and CO2/N-2/CH4 separations in addition to various structural properties of MOFs.European Research Counci

Computational Screening of Metal–Organic Frameworks for Membrane-Based CO₂/N₂/H₂O Separations: Best Materials for Flue Gas Separation

It has become a significant challenge to select the best metal–organic frameworks (MOFs) for membrane-based gas separations because the number of synthesized MOFs is growing exceptionally fast. In this work, we used high-throughput computational screening to identify the top MOF membranes for flue gas separation. Grand canonical Monte Carlo and molecular dynamics simulations were performed to assess adsorption and diffusion properties of CO₂ and N₂ in 3806 different MOFs. Using these data, selectivities and permeabilities of MOF membranes were predicted and compared with those of conventional membranes, polymers, and zeolites. The best performing MOF membranes offering CO₂/N₂ selectivity > 350 and CO₂ permeability > 10⁶ Barrer were identified. Ternary CO₂/N₂/H₂O mixture simulations were then performed for the top MOFs to unlock their potential under industrial operating conditions, and results showed that the presence of water decreases CO₂/N₂ selectivity and CO₂ permeability of some MOF membranes. As a result of this stepwise screening procedure, the number of promising MOF membranes to be investigated for flue gas separation in future experimental studies was narrowed down from thousands to tens. We finally examined the structure–performance relations of MOFs to understand which properties lead to the greatest promise for flue gas separation and concluded that lanthanide-based MOFs with narrow pore openings (<4.5 Å), low porosities (<0.75), and low surface areas (<1000 m²/g) are the best materials for membrane-based CO₂/N₂ separations