In the following, we introduce a multi-scale, computational workflow to evaluate MOFs for CO 2 post-combustion capture with temperature-swing absorption (TSA) in natural gas combined cycle (NGCC) power plants. The workflow, see Figure , uses molecular-level simulations for characterizing MOFs with high CO 2 adsorption selectivity, which are shortlisted based on active learning cycles, and rank-ordered based on process simulations informed by molecular-scale, adsorption figuresof-merit. Finally, process optimizations at realistic operation conditions confirm each MOF's performance at process level. We demonstrate that inclusion of molecular kinetics improves the workflow's ability to discover false leads, which reduces computational costs significantly. Moreover, based on the TOP-20 MOF ranking results, we show for representative crystallite diameters how the inclusion of microscopic diffusivity affects process-level, CO 2 capture performance predictions. , leads to significant changes in CO 2 capture outcomes at process level: Recovery (higher is preferable), Productivity (higher is preferable) and Energy Cost (lower is preferable).