MOFs that were identified as promising for CO2 capture or DAC applications. The MLFF model was trained based on optimized configurations collected from the ODAC23 database (training and validation set). First, the lowest CO2 and H2O interaction energies (interaction energies in this case were calculated after geometry optimization of MOF+gas system) were gathered for MOFs using the IS2RE database from the ODAC23 database. MOFs that met the following two conditions were considered: (1) the lowest CO2 and H2O binding energy is smaller than -0.1 eV, and (2) the number of atoms is less than 250. Lastly, given that the top 20 most frequently appearing metal atoms in the ODAC23 database were provided in the original paper (see Supplementary Figure ), 3 MOFs were randomly selected from those containing each metal type. Therefore, 60 MOFs were considered, and 120 equilibrium configurations were collected from the ODAC23 database, considering both CO2 and H2O molecules. For the evaluation of the trained MLFF model, an additional database was constructed based on the equilibrium states obtained from the manually selected 26 MOFs. A single guest molecule was introduced into the framework, where it was allowed to relax while the framework remained fixed. Three to five different initial points were sampled, considering active adsorption sites for the guest molecules, and the configuration with the lowest energy was selected as the equilibrium state. In total, 52 equilibrium configurations were collected for both CO2 and H2O molecules. Further details and illustrations of these 26 MOFs are provided in Supplementary