Chemically Accurate Prediction of CO ₂ Adsorption Thermodynamics in Metal–Organic Framework CALF‐20: Complementary Ab Initio Modeling and Grand Canonical Monte Carlo Simulations

Carbon dioxide adsorption thermodynamics in the metal–organic framework CALF‐20, a hydrothermally stable candidate for carbon capture, are predicted using two complementary approaches. An analytical ab initio thermodynamics method combines periodic density functional theory + dispersion interactions (DFT + D) with MP2 corrections for adsorption energies, local sampling of the potential energy surface, and a nonisolated‐site term to capture nonlocal effects. Grand Canonical Monte Carlo (GCMC) simulations using a newly developed force field enable comprehensive sampling of global configurations. Both methods reproduce experimental adsorption isotherms and heats of adsorption within chemical accuracy (±4 kJ mol −1 ). Dispersion dominates CO 2 binding (>80%), while quantum effects on nuclear motion (zero‐point vibrational energy) contribute up to 5.4 kJ mol −1 to adsorption thermodynamics—impacting both adsorption enthalpies and Gibbs free energies. Nonlocal effects reduce entropy penalties by ≳7 kJ mol −1 , yielding adsorption Gibbs free energies that reveal a two‐step pore filling mechanism: initial single occupancy of cages followed by intracage pairing. Triple cross‐validation across ab initio, GCMC, and experiment confirms this cooperative two‐step mechanism and reinforces the reliability of the thermodynamic dataset. This transferable strategy enables predictive modeling of adsorption thermodynamics in nanoporous materials for next‐generation carbon‐capture applications.