Browsing by Subject "Chemical kinetics"

Now showing 1 - 4 of 4
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    Canards, Black Swans and Control of Chemical Reactions
    (University of Minnesota. Institute for Mathematics and Its Applications, 2009-02) Sobolev, Vladimir; Shchepakina, Elena
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    Explicit, implicit and parametric invariant manifolds for model reduction in chemical kinetics
    (University of Minnesota. Institute for Mathematics and Its Applications, 2009-03) Sobolev, Vladimir; Shchepakina, Elena
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    Kinetics and mechanisms of methanol to hydrocarbons conversion over zeolite catalysts
    (2013-05) Hill, Ian Michael
    The methanol-to-hydrocarbons (MTH) process over zeolite catalysts is the final step in the synthesis of commodity chemicals and fuels from alternative carbon sources via synthesis gas intermediates. Emerging research has shown that olefins and aromatics are critical intermediates, acting as scaffolds for the addition of methyl groups from methanol or dimethyl ether (DME) in an indirect "hydrocarbon pool" mechanism. Outstanding questions in this research pertain to (i) the quantitation of reaction rates for C1 homologation and (ii) the mechanism of activating methanol or DME for the formation of carbon-carbon bonds. This research reports rate constants and activation energies of olefin and aromatic methylation steps over zeolites of different pore sizes and geometries from steady-state methylation reactions, as well as isotopic and post-reaction titration studies to determine mechanistic details regarding the structure of the active zeolite surface species. Specifically, isolated steady-state methylation of C2 to C4 olefins over zeolites at differential conditions have shown that reactions producing higher degrees of substitution of intermediate carbocations have rate constants that are an order of magnitude higher than less substituted intermediates. Benzene and toluene methylation reactions show similar kinetic behavior to propylene and linear butene, respectively, over H-ZSM-5. Pressure-dependent studies show a first-order rate dependence on olefin or aromatic pressures which is invariant of DME partial pressures, indicating a surface saturated in DME-derived species reacting with a gas phase co-reactant in the rate-limiting step. These surface species have been identified as methoxides, as observed using post-reaction titration and isotopic studies. The methylation of para- and ortho-xylene with DME at low conversions showed linear dependence of the reaction rate at low pressures of xylene, but the reaction rate became zero-order at higher xylene pressures over H-ZSM-5. The reaction rate remained zero-order in DME pressure, and when taken in conjunction with results from isotopic studies and surface titrations, indicates that the surface methoxides become saturated in adsorbed xylene isomers. A reduction in the critical diffusion length by a factor of >150 did not increase the reaction rate, indicating that the effect is adsorption and not one of transport limitations. Arguments based on derived rate equations modeling observed trends in kinetic, isotopic, and titration studies set a basis for building a microkinetic model for MTH reactions over H-ZSM-5, which can predict expected product distributions for a given set of reaction conditions.
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    Neural Network Potentials for Atomistic Simulations of Reactive Chemistry
    (2024-05) Gordon, Adrian
    Atomistic simulations play an important role in a wide range of chemical investigations, including studies of chemical kinetics. These simulations rely on accurate energies and forces, often obtained through expensive ab initio electronic structure calculations. Recently researchers have explored the use of machine learning models to provide analytical and differentiable potential energy surfaces for use in atomistic simulations. These ML models can provide energies at a fraction of the cost of ab initio methods and are also highly accurate within the chemical space represented in the training data. In this work, we explore methods for data sampling techniques for training datasets used to train ML potentials, specifically to calculate chemical kinetics of the OH+ CH4 hydrogen abstraction reaction. In addition, combined ML and molecular mechanics methods for condensed phase reactions is discussed.