To expedite the identification and design of promising MOFs for CO2 capture, large-scale screening has been widely applied. These are typically based on classical molecular simulations with force fields, such as universal force fields (UFFs) with point charges (e.g. Qeq, EQeq, and DDEC ). For CO2 capture, Boyd et al., designed new MOFs suitable for flue gas CO2 capture by introducing CO2 responsive pockets acquired from screening results. Findley et al. screened the CoRE MOF database to evaluate whether MOFs are suitable for DAC application. While these methods are time-efficient, they struggle to accurately describe the interaction between the MOF frameworks and the gas molecules such as CO2 and H2O, due to the diversity of chemical environments and the complexity of the short-range potential energy landscape. While ab initio calculations offer a more accurate alternative by explicitly accounting for electron density distributions, the computational cost increases substantially and are impractical for large-scale screening or extensive data accumulation for porous solids.