Quantum Sieving in Metal-Organic Frameworks: A Computational Study

In this work, a systematic computational study was performed to investigate the quantum sieving in nine typical metal organic frameworks (MOFs) for the separation of hydrogen isotope mixtures, The results show that Cu(F-pymo)(2) and CPL-1 exhibit exceptional selectivity that is higher than other MOFs as well as other nanoporous materials such as carbon nanotubes, slit-shaped graphites, and zeolites studied so far. A concept named quantum effective pore size (QEPS) was proposed in this work, which can incorporate the effects of quantum sieving, and thus is temperature-dependent. On the basis of the new pore size, good correlations between pore size and selectivity can be established for the MOFs considered; particularly, they can explain the different selectivity performance of the two MOFs with highest selectivity at 40 and 77K. This work indicates that MOFs are suitable candidates for the separation of hydrogen isotopes through quantum sieving.