Etan ve metan saflaştırma süreçlerinde kullanılmak üzere metal-organik gözenekli yapılarin gaz ayırma performansının kapsamlı hesaplamalı taraması

Ethane purification and natural gas purification are two energy-intensive processes which can advantage from better separation techniques. Metal organic frameworks (MOFs) are a recent group of nanoporous materials which can be obtained through the combination of metal nodes and organic linkers on different topologies. Considering the large number of available MOFs, it is not possible to fabricate and test the gas separation performance of every single MOF adsorbents and membranes using purely experimental manners. Therefore, the C2H6/C2H4, C2H6/CH4, and CO2/CH4 separation performances of MOFs were investigated using high-throughput computational screening methods in this thesis. In the first part, molecular simulations were used to assess membrane-based C2H6/C2H4 and C2H6/CH4 separation performances of 175 different MOF structures. Results showed that a significant number of MOF membranes is C2H6 selective for C2H6/C2H4 separation in contrast to the traditional nanoporous materials. Several MOFs were identified to exceed the upper bound established for polymeric membranes and many MOF membranes exhibited higher gas permeabilities than zeolites and carbon molecular sieves. In the second part, a multi-level high-throughput computational screening methodology was used to examine the most recent MOF database for membrane-based CO2/CH4 separation. 8 promising MOF membranes offering the best combination of CO2 permeability (>106 Barrer) and CO2/CH4 selectivity (>80) were identified by combining grand canonical Monte Carlo (GCMC) and equilibrium molecular dynamics (EMD) simulations. Permeabilities and selectivities of the mixed matrix membranes (MMM) in which the best MOF candidates were incorporated as filler particles were also investigated. Many MOF membranes could outperform polymeric membranes for CO2/CH4 separation and MOF-based MMMs can have significantly higher CO2 permeabilities and moderately higher selectivities than pure polymers. Computational identification of the promising MOF candidates for CO2 separation depends on the accurate description of electrostatic interactions between CO2 molecules and MOFs. In the last part, role of partial charge assignment methods in high-throughput computational screening of MOFs for CO2/CH4 separation was examined. A quantum based, density-derived electrostatic and chemical charge method (DDEC) and an approximate charge equilibration method (Qeq) were used to compute the adsorption of CO2/CH4 mixture in 1500 MOFs at two different operating conditions. Results showed that the identity of the best performing MOF candidates, which were selected based on the regenerability and adsorbent performance score of MOFs, can change based on the type of the charge assignment method used in simulations. Overall, results showed that high-throughput screening approaches introduced in this thesis can be used to predict gas separation performance of MOF adsorbents and membranes and MOFs can perform better than commercially used materials. The results of this thesis will be useful to guide the experiments to the most promising MOF candidates and to accelerate the development of new MOFs with high performances.