Discovery of remarkable porous materials for CO2 capture
from wet flue gas is of great significance to reduce the CO2 emissions, but elucidating the most critical structure features
for boosting CO2 capture capabilities remains a great challenge.
Here, machine-learning-assisted Monte Carlo computational screening
on 516 experimental covalent organic frameworks (COFs) identifies
the superior secondary building units (SBUs) for wet flue gas separation
using COFs, which are tetraphenylporphyrin units for boosting CO2 adsorption uptake and functional groups for boosting CO2/N2 selectivity. Accordingly, 1233 COFs are assembled
using the identified superior SBUs. Density functional theory calculation
analysis on frontier orbitals, electrostatic potential, and binding
energy reveals the influencing mechanism of the SBUs on the wet flue
gas separation performance. The “electron-donating-induced
vdW interaction” effect is discovered to construct the better-performing
COFs, which can achieve high CO2 uptake of 4.4 mmol·g–1 with CO2/N2 selectivity of
104.8. Meanwhile, the “electron-withdrawing-induced vdW + electrostatic
coupling interaction” effect is unearthed to construct the
better-performing COFs with superior CO2/N2 selectivity,
which can reach 277.6 with CO2 uptake of 2.2 mmol·g–1; in this case, H2O plays a positive contribution
in improving CO2/N2 selectivity. This work provides
useful guidelines for designing optimized two-dimensional-COF adsorbents
for wet flue gas separation.