Database for CO 2 Separation Performances of MOFs Based on Computational Materials Screening

Metal-organic frameworks (MOFs) are potential adsorbents for CO 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 CO separation from flue gas (CO /N ) and landfill gas (CO /CH ) under realistic operating conditions. We validated the accuracy of our computational approach by comparing the simulation results for the CO uptakes, CO /N and CO /CH selectivities of various types of MOFs with the available experimental data. Binary CO /N and CO /CH 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 CO /N and CO /CH with high performance were identified. Molecular simulations for the adsorption of a ternary CO /N /CH 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 Δ Q > 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 m /g, and ρ > 1 g/cm are the best candidates for selective separation of CO from flue gas and landfill gas. This information will be very useful to design novel MOFs exhibiting high CO 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 CO /N , CO /CH , and CO /N /CH separations in addition to various structural properties of MOFs.