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/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 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/N₂, CO₂/CH₄, and CO₂/N₂/CH₄ separations in addition to various structural properties of MOFs.