Thermodynamic exploration of xenon/krypton separation based on a high-throughput screening

Abstract

Nanoporous framework materials are a promising class of materials for energy-efficient technology of xenon/krypton separation by physisorption. Many studies on Xe/Kr separation by adsorption have focused on the determination of...

Computational investigation of multifunctional MOFs for adsorption and membrane-based separation of CF4/CH4, CH4/H2, CH4/N2, and N2/H2 mixtures

“…While one can typically expect selectivity to drop at higher pressure due to weaker host–guest interactions, it is also possible to observe a cooperative effect between sorbates enhancing the selectivity. 59 Thus, such comparisons should preferably be made after obtaining selectivities at the same pressure conditions.…”

Concluding remarks: current and next generation MOFs

“…[160][161][162] Such computational screening methods have recently witnessed a rapid expansion due to several factors such as (1) the growth of the open public databases, (2) the advances in methods for hypothetical structural construction, and (3) the development of artificial intelligence techniques. [163][164][165] In fact, machine learning techniques have now shown great promise in MOF science because it is not feasible to experimentally single out top-performing structures from the vast and ever-growing MOF library, which now exceeds >70,000 MOF structures. In this Faraday discussion, high-throughput computational screening of MOF in applying xenon/krypton separation, 165 methane storage, 166 and biogas purification 167 were discussed.…”

“…[163][164][165] In fact, machine learning techniques have now shown great promise in MOF science because it is not feasible to experimentally single out top-performing structures from the vast and ever-growing MOF library, which now exceeds >70,000 MOF structures. In this Faraday discussion, high-throughput computational screening of MOF in applying xenon/krypton separation, 165 methane storage, 166 and biogas purification 167 were discussed. They demonstrated that their methods provide the best candidates and a better comprehension of the structure-property relationships in the target application.…”

Computational Predictions for Effective Separation of Xenon/Krypton Gas Mixtures in the MFM Family of Metal–Organic Frameworks

“…Computational studies can be invaluable in directing experimental efforts efficiently toward promising MOFs. On a particularly large scale, the diverse chemical space occupied by MOFs makes them a prime target for high-throughput computational screenings. ,,− Large data sets of structures can be studied using relatively cheap computational methods, as in Glover and Besley’s search of nearly 7,000 MOFs for biogas upgrading properties. Promising MOFs identified by computational screenings are often the subject of detailed investigations using more intensive computational methods, which remain significantly faster than experimental studies.…”