In the following sections, we report the results obtained by applying the computational workflow that integrates structure selection by active-learning, molecular simulation and process-level optimization. As reference database for our study, we have selected the non-disordered, all solvent removed (ASR) portion of CoRE-MOF-2019 (v1.1.2) . From the initial dataset of 10,143 structures, we have removed 3,659 spurious MOF structures using mofchecker . Within the remaining 6,484 MOFs, we have identified those providing the best balance between energy cost, productivity, and recovery with a purity of at least 95% as required for CO 2 capture applications at NGCC power plants.