We now compare the process-level CO 2 capture productivity for two scenarios: a constant, material-independent K eff , equivalent to setting R µ = 0 in Equation 2, thus neglecting microscopic diffusivity limitations, as well as a structure-dependent K eff accounting for microscopic diffusivity. In both cases, we have assumed a crystallite diameter of R µ = 10 µm and a CO 2 purity of 95%. The resulting productivity values are indicated by color shades in Figure . For the group of select MOFs, the plot reveals a correlation between CO 2 affinity, CO 2 /N 2 selectivity, and capture productivity. Most MOFs in our selection have a low CO 2 affinity, as evidenced by a small ∆H CO 2 -∆H N 2 difference. Due to the high concentration of N 2 in the feed stream, their separation performance is low. Therefore, we focus our analysis on the right-hand side of the graphs. As a key result of the comparison, 14% of high-productivity MOFs, i.e., ≳ 1 kg day.L , fail to sustain high productivity once molecular diffusivity is taken into account by means of a structure-dependent K eff . From a computational screening perspective, we consider these structures as "false positives" that can be effectively removed from the performance-based MOF rank-order.