Research Project: Computational Simulations of MOFs for Gas Separations
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Contributors
Funders
ID
EC.00105
Authors
Keskin, Seda
Faculty Member
Publications
Computational screening of MOFs for acetylene separation
(Frontiers, 2018) Azar, Ayda Nemati Vesali; Keskin, Seda; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; Yes; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
Efficient separation of acetylene (C2H2) from CO2 and CH4 is important to meet the requirement of high-purity acetylene in various industrial applications. Metal organic frameworks (MOFs) are great candidates for adsorption-based C2H2/CO2 and C2H2/CH4 separations due to their unique properties such as wide range of pore sizes and tunable chemistries. Experimental studies on the limited number of MOFs revealed that MOFs offer remarkable C2H2/CO2 and C2H2/CH4 selectivities based on single-component adsorption data. We performed the first large-scale molecular simulation study to investigate separation performances of 174 different MOF structures for C2H2/CO2 and C2H2/CH4 mixtures. Using the results of molecular simulations, several adsorbent performance evaluation metrics, such as selectivity, working capacity, adsorbent performance score, sorbent selection parameter, and regenerability were computed for each MOF. Based on these metrics, the best adsorbent candidates were identified for both separations. Results showed that the top three most promising MOF adsorbents exhibit C2H2/CO2 selectivities of 49, 47, 24 and C2H2/CH4 selectivities of 824, 684, 638 at 1 bar, 298 K and these are the highest C2H2 selectivities reported to date in the literature. Structure-performance analysis revealed that the best MOF adsorbents have pore sizes between 4 and 11 angstrom surface areas in the range of 600-1,200 m(2)/g and porosities between 0.4 and 0.6 for selective separation of C2H2 from CO2 and CH4. These results will guide the future studies for the design of new MOFs with high CC2H2 separation potentials.
Combining machine learning and molecular simulations to unlock gas separation potentials of MOF membranes and MOF/polymer MMMs
(American Chemical Society (ACS), 2022) Harman, Hilal Dağlar; Keskin, Seda; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; Yes; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
Due to the enormous increase in the number of metal-organic frameworks (MOFs), combining molecular simulations with machine learning (ML) would be a very useful approach for the accurate and rapid assessment of the separation performances of thousands of materials. In this work, we combined these two powerful approaches, molecular simulations and ML, to evaluate MOF membranes and MOF/polymer mixed matrix membranes (MMMs) for six different gas separations: He/H-2, He/N-2, He/CH4, H-2/N-2, H-2/CH4, and N-2/CH4. Single-component gas uptakes and diffusivities were computed by grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations, respectively, and these simulation results were used to assess gas permeabilities and selectivities of MOF membranes. Physical, chemical, and energetic features of MOFs were used as descriptors, and eight different ML models were developed to predict gas adsorption and diffusion properties of MOFs. Gas permeabilities and membrane selectivities of 5249 MOFs and 31,494 MOF/polymer MMMs were predicted using these ML models. To examine the transferability of the ML models, we also focused on computer-generated, hypothetical MOFs (hMOFs) and predicted the gas permeability and selectivity of 1000 hMOF/polymer MMMs. The ML models that we developed accurately predict the uptake and diffusion properties of He, H-2, N-2, and CH(4 )gases in MOFs and will significantly accelerate the assessment of separation performances of MOF membranes and MOF/polymer MMIMs. These models will also be useful to direct the extensive experimental efforts and computationally demanding molecular simulations to the fabrication and analysis of membrane materials offering high performance for a target gas separation.
Evaluating charge equilibration methods to generate electrostatic fields in nanoporous materials
(American Chemical Society (ACS), 2019) Kadıoğlu, Özge; Keskin, Seda; Ongari, Daniele; Boyd, Peter G.; Mace, Amber K.; Smit, Berend; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; Yes; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
Charge equilibration (Qeq) methods can estimate the electrostatic potential of molecules and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute density functional (DFT)-derived charges. This makes possible, for example, the computational screening of thousands of microporous structures to assess their performance for the adsorption of polar molecules. Recently, different variants of the original Qeq scheme were proposed to improve the quality of the computed point charges. One focus of this research was to improve the gas adsorption predictions in metal-organic frameworks (MOFs), for which many different structures are available. In this work, we review the evolution of the method from the original Qeq scheme, understanding the role of the different modifications on the final output. We evaluated the result of combining different protocols and set of parameters, by comparing the Qeq charges with high quality DFT-derived DDEC charges for 2338 MOF structures. We focused on the systematic errors that are attributable to specific atom types to quantify the final precision that one can expect from Qeq methods in the context of gas adsorption where the electrostatic potential plays a significant role, namely, CO2 and H2S adsorption. In conclusion, both the type of algorithm and the input parameters have a large impact on the resulting charges, and we draw some guidelines to help the user to choose the proper combination of the two for obtaining a meaningful set of charges. We show that, considering this set of MOFs, the accuracy of the original Qeq scheme is often still comparable with the most recent variants, even if it clearly fails in the presence of certain atom types, such as alkali metals.
Recent advances in simulating gas permeation through MOF membranes
(Royal Society of Chemistry (RSC), 2021) Harman, Hilal Dağlar; Keskin, Seda; Eruçar, İlknur; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; Yes; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
In the last two decades, metal organic frameworks (MOFs) have gained increasing attention in membrane-based gas separations due to their tunable structural properties. Computational methods play a critical role in providing molecular-level information about the membrane properties and identifying the most promising MOF membranes for various gas separations. In this review, we discuss the current state-of-the-art in molecular modeling methods to simulate gas permeation through MOF membranes and review the recent advancements. We finally address current opportunities and challenges of simulating gas permeation through MOF membranes to guide the development of high-performance MOF membranes in the future.
Computer simulations of 4240 MOF membranes for H-2/CH4 separations: insights into structure-performance relations
(Royal Society of Chemistry (RSC), 2018) Altıntaş, Çiğdem; Avcı, Gökay; Harman, Hilal Dağlar; Keskin, Seda; Gülçay, Ezgi; Eruçar, İlknur; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; Yes; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
Design of new membranes having high H-2/CH4 selectivity and high H-2 permeability is strongly desired to reduce the energy demand for H-2 production. Metal organic frameworks (MOFs) offer a great promise for membrane-based gas separations due to their tunable physical and chemical properties. We performed a high-throughput computational screening study to examine membrane-based H-2/CH4 separation potentials of 4240 MOFs. Grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations were used to compute adsorption and diffusion of H-2 and CH4 in MOFs. Simulation results were then used to predict adsorption selectivity, diffusion selectivity, gas permeability and membrane selectivity of MOFs. A large number of MOF membranes was found to outperform traditional polymer and zeolite membranes by exceeding the Robeson's upper bound for selective separation of H-2 from CH4. Structure-performance analysis was carried out to understand the relations between MOF membranes' selectivities and their pore sizes, surface areas, porosities, densities, lattice systems, and metal types. Results showed that MOFs with pore limiting diameters between 3.8 and 6 angstrom, the largest cavity diameters between 6 and 12 angstrom, surface areas less than 1000 m(2) g(-1), porosities between 0.5 and 0.75, and densities between 1 and 1.5 g cm(-3) are the most promising membranes leading to H-2 selectivities > 10 and H-2 permeabilities > 10(4) Barrer. Our results suggest that monoclinic MOFs having copper metals are the best membrane candidates for H-2/CH4 separations. This study represents the first high-throughput computational screening of the most recent MOF database for membrane-based H-2/CH4 separation and microscopic insight provided from molecular simulations will be highly useful for the future design of new MOFs having extraordinarily high H-2 selectivities.
