RESUMEN
Considering the existence of a large number and variety of metal-organic frameworks (MOFs) and ionic liquids (ILs), assessing the gas separation potential of all possible IL/MOF composites by purely experimental methods is not practical. In this work, we combined molecular simulations and machine learning (ML) algorithms to computationally design an IL/MOF composite. Molecular simulations were first performed to screen approximately 1000 different composites of 1-n-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]) with a large variety of MOFs for CO2 and N2 adsorption. The results of simulations were used to develop ML models that can accurately predict the adsorption and separation performances of [BMIM][BF4]/MOF composites. The most important features that affect the CO2/N2 selectivity of composites were extracted from ML and utilized to computationally generate an IL/MOF composite, [BMIM][BF4]/UiO-66, which was not present in the original material data set. This composite was finally synthesized, characterized, and tested for CO2/N2 separation. Experimentally measured CO2/N2 selectivity of the [BMIM][BF4]/UiO-66 composite matched well with the selectivity predicted by the ML model, and it was found to be comparable, if not higher than that of all previously synthesized [BMIM][BF4]/MOF composites reported in the literature. Our proposed approach of combining molecular simulations with ML models will be highly useful to accurately predict the CO2/N2 separation performances of any [BMIM][BF4]/MOF composite within seconds compared to the extensive time and effort requirements of purely experimental methods.
RESUMEN
Discovery of remarkable porous materials for CO2 capture from wet flue gas is of great significance to reduce the CO2 emissions, but elucidating the most critical structure features for boosting CO2 capture capabilities remains a great challenge. Here, machine-learning-assisted Monte Carlo computational screening on 516 experimental covalent organic frameworks (COFs) identifies the superior secondary building units (SBUs) for wet flue gas separation using COFs, which are tetraphenylporphyrin units for boosting CO2 adsorption uptake and functional groups for boosting CO2/N2 selectivity. Accordingly, 1233 COFs are assembled using the identified superior SBUs. Density functional theory calculation analysis on frontier orbitals, electrostatic potential, and binding energy reveals the influencing mechanism of the SBUs on the wet flue gas separation performance. The "electron-donating-induced vdW interaction" effect is discovered to construct the better-performing COFs, which can achieve high CO2 uptake of 4.4 mmol·g-1 with CO2/N2 selectivity of 104.8. Meanwhile, the "electron-withdrawing-induced vdW + electrostatic coupling interaction" effect is unearthed to construct the better-performing COFs with superior CO2/N2 selectivity, which can reach 277.6 with CO2 uptake of 2.2 mmol·g-1; in this case, H2O plays a positive contribution in improving CO2/N2 selectivity. This work provides useful guidelines for designing optimized two-dimensional-COF adsorbents for wet flue gas separation.
RESUMEN
The effect of thickness in multilayer thin-film composite membranes on gas permeation has received little attention to date, and the gas permeances of the organic polymer membranes are believed to increase by membrane thinning. Moreover, the performance of defect-free layers with known gas permeability can be effectively described using the classical resistance in series models to predict both permeance and selectivity of the composite membrane. In this work, we have investigated the Pebax®-MH1657/PDMS double layer membrane as a selective/gutter layer combination that has the potential to achieve sufficient CO2/N2 selectivity and permeance for efficient CO2 and N2 separation. CO2 and N2 transport through membranes with different thicknesses of two layers has been investigated both experimentally and with the utilization of resistance in series models. Model prediction for permeance/selectivity corresponded perfectly with experimental data for the thicker membranes. Surprisingly, a significant decrease from model predictions was observed when the thickness of the polydimethylsiloxane (PDMS) (gutter layer) became relatively small (below 2 µm thickness). Material properties changed at low thicknesses-surface treatments and influence of porous support are discussed as possible reasons for observed deviations.
RESUMEN
Metal-organic frameworks (MOFs) are potential adsorbents for CO2 capture. Because thousands of MOFs exist, computational studies become very useful in identifying the top performing materials for target applications in a time-effective manner. In this study, molecular simulations were performed to screen the MOF database to identify the best materials for CO2 separation from flue gas (CO2/N2) and landfill gas (CO2/CH4) under realistic operating conditions. We validated the accuracy of our computational approach by comparing the simulation results for the CO2 uptakes, CO2/N2 and CO2/CH4 selectivities of various types of MOFs with the available experimental data. Binary CO2/N2 and CO2/CH4 mixture adsorption data were then calculated for the entire MOF database. These data were then used to predict selectivity, working capacity, regenerability, and separation potential of MOFs. The top performing MOF adsorbents that can separate CO2/N2 and CO2/CH4 with high performance were identified. Molecular simulations for the adsorption of a ternary CO2/N2/CH4 mixture were performed for these top materials to provide a more realistic performance assessment of MOF adsorbents. The structure-performance analysis showed that MOFs with Δ Qst0 > 30 kJ/mol, 3.8 Å < pore-limiting diameter < 5 Å, 5 Å < largest cavity diameter < 7.5 Å, 0.5 < Ï < 0.75, surface area < 1000 m2/g, and ρ > 1 g/cm3 are the best candidates for selective separation of CO2 from flue gas and landfill gas. This information will be very useful to design novel MOFs exhibiting high CO2 separation potentials. Finally, an online, freely accessible database https://cosmoserc.ku.edu.tr was established, for the first time in the literature, which reports all of the computed adsorbent metrics of 3816 MOFs for CO2/N2, CO2/CH4, and CO2/N2/CH4 separations in addition to various structural properties of MOFs.
RESUMEN
Ordered open channels found in two-dimensional covalent organic frameworks (2D COFs) could enable them to adsorb carbon dioxide. However, the frameworks' dense layer architecture results in low porosity that has thus far restricted their potential for carbon dioxide adsorption. Here we report a strategy for converting a conventional 2D COF into an outstanding platform for carbon dioxide capture through channel-wall functionalization. The dense layer structure enables the dense integration of functional groups on the channel walls, creating a new version of COFs with high capacity, reusability, selectivity, and separation productivity for flue gas. These results suggest that channel-wall functional engineering could be a facile and powerful strategy to develop 2D COFs for high-performance gas storage and separation.