In this work, we introduce a MLFF that is both accurate for DAC applications and transferable across a wide range of MOFs, as shown in Figure . By including configurations of MOFs interacting with CO2 and H2O gas molecules contained in our curated GoldDAC dataset, we finetune a foundation model that was pretrained on diverse crystalline compounds. To deploy this model, we have developed the DAC-SIM package, which combines our MLFF with the statistical Widom insertion method , molecular dynamics, and structure optimization. We use DAC-SIM to conduct high-throughput screening of 8,131 experimental MOFs in the CoRE MOF database . Comparison of the distributions in CO2 adsorption and selectivity highlights several limitations in the traditional screening approach and we identify several novel candidates and design principles.