Integrated Material and Process Evaluation of Metal-Organic Frameworks Database for Energy-efficient SF6/N2 Separation

In this work, we proposed multi-scale screening, which employs both molecular and process-level models, to identify high-performing MOFs for energy-efficient separation of SF6 from SF₆ and N₂ mixture. Grand canonical Monte Carlo (GCMC) simulations were combined with ideal adsorption process simulation to computationally screen 14,000 metal-organic frameworks (MOFs) for adsorptive separation of SF6/N₂. More than 150 high-performing MOFs were identified based on the results from GCMC simulations at the pressure and vacuum swing conditions, and subsequently evaluated using the ideal adsorption process simulation. High-performing MOFs selected for the VSA conditions are able to achieve the 90% target purity level of SF6 but none of the selected MOFs for PSA conditions could. Cascade PSA configuration was proposed and adopted to improve the purity level of the separated SF6. In the pump efficiency scenarios of 80, 20, and 10%, the VSA and cascade PSA cases were compared, which concluded 10% scenario prefers the PSA case whereas the VSA case is favored in the others. Top-performing MOFs identified from the multi-scale computational approach were found to be able to produce 90% purity SF₆ with 0.10 - 0.4 and 0.5 - 1.4 MJ per kg of SF6 for VSA and PSA, respectively.