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.