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Quantum Sieving in Metal鈥揙rganic Frameworks: A Computational Study
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文摘
In this work, a systematic computational study was performed to investigate the quantum sieving in nine typical metal鈥搊rganic 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 鈥渜uantum effective pore size鈥?(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 77 K. This work indicates that MOFs are suitable candidates for the separation of hydrogen isotopes through quantum sieving.

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