Computational Modeling and Predictive Design of Metal-organic Frameworks for Catalysis and Adsorption

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Computational Modeling and Predictive Design of Metal-organic Frameworks for Catalysis and Adsorption

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2023-08

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Metal-organic frameworks (MOFs) are structurally well-defined nanoporous materials built from inorganic metal oxide nodes connected by organic linkers. The high porosity, surface area, and chemical and thermal stability of MOFs have attracted interest to use these materials in catalysis, gas adsorption and storage, and separation. Furthermore, the modularity of MOFs allows to tailor their nanoscale pore environment for enhanced performance in a desired application. This thesis utilizes different computational modeling techniques to provide fundamental mechanistic insights into catalysis and adsorption phenomena occurring in MOFs which can be used to design better-performing systems. Chapter 1 highlights the suitability of MOFs for catalysis and adsorption and briefly discusses the computational methods useful for modeling MOFs for these applications. In Chapter 2, the reactivity of CAU-1, an Al-based MOF, is investigated for the dehydration of methanol to dimethylether. Density functional theory (DFT) studies in conjuction with experimental reactivity measurements are used to elucidate the reaction mechanism occurring on active sites constituted by the nodes and linkers of the MOF. In Chapter 3 and Chapter 4, the catalytic activity of several single-atom transition metals deposited on the nodes of UiO-66 (a Zr-based MOF) through post-synthetic modifications (Mn+-UiO-66), is investigated for the dimerization of 1-butene to linear octenes. The Cossee-Arlmann reaction mechanism is found to be the energetically most favorable reaction mechanism occurring on the undercoordinated metal sites of Mn+-UiO-66 catalysts investigated with Ni-UiO-66 outperforming the other metalated catalysts. Chapter 5 and Chapter 6 demonstrate the use of Al-rod-based MOFs for adsorption-assisted atmospheric water harvesting (AWH). In Chapter 5, insights into the primary adsorption sites and water uptake mechanism in MOF-303 obtained from periodic DFT optimization and ab initio molecular dynamics (MD) simulations in concert with single crystal X-ray diffraction measurements are used to design a linker-variate analogue of MOF-303, MOF-333, with increased water throughput. Furthermore, the water adsorption behavior predicted in these MOFs using force-field-based Gibbs ensemble Monte Carlo (GEMC) simulations are shown to achieve good agreement with experimental data after a careful choice of the rigid framework structures and force field parameters used for the MOF. In Chapter 6, a novel linker extension strategy in MOFs is used to enhance the water harvesting characteristics of MOF-303. Remarkably, the new MOF, MOF-LA2-1, shows a 50% increase in the water uptake capacity compared to MOF-303. Finally, in Chapter 7, the effect of the structural flexibility of IRMOFs on the adsorption and self-diffusion behavior of DMF is investigated using GEMC and MD simulations in the constant-stress ensemble using flexible force fields for the MOF.

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University of Minnesota Ph.D. dissertation. August 2023. Major: Chemical Engineering. Advisors: Laura Gagliardi, J. Ilja Siepmann. 1 computer file (PDF); xlii, 443 pages.

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Chheda, Saumil. (2023). Computational Modeling and Predictive Design of Metal-organic Frameworks for Catalysis and Adsorption. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/269562.

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