Future work remains to address these limitations of our study. First, we wish to test the separation performance of Ni(PyC-m-NH 2 ) 2 with a column breakthrough experiment. In this more practically relevant test, we pass air contaminated with a known, dilute concentration of Xe and Kr through a column packed with the MOF and measure the composition of the gas at the exit of the column [ ]. More, we wish to assess the impact of humidity (competitive adsorption) on the separation performance. For applications in SNF reprocessing, we wish to study the stability of Ni(PyC-m-NH 2 ) 2 under radiation . Second, in our molecular simulations, we wish to include competing gases such as CO 2 present in the capture of Xe from air and model the flexibility of the MOF structure . To increase the throughput of the virtual screening, we could train a supervised machine learning model or devise an evolutionary search strategy to predict or guide how to functionalize a MOF structure to enhance its selectivity for a gas. Third, we wish to screen, for Xe/Kr separations, Ni(PyC) 2 analogues constructed with different metal centers; changing the metal of a "lead" MOF is another way to tune its adsorption properties [ ]. Fourth, we wish to incorporate predictions of water-stability of the MOFs [ , ] in our virtual screening (e.g., as in Ref. [ ]).