Browsing by Subject "Computational"

Now showing 1 - 5 of 5
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    Comprehensive study of the chemical reactions resulting from the decomposition of chloroform in alkaline aqueous solution.
    (2009-11) Mews, Jorge Estevez
    Chloroform (CHCl3) is a volatile liquid, which has a rather slow rate of decomposition in ground water. It is a known carcinogen and one of the most common contaminants found at toxic waste sites. The dominant degradation process for chloroform in both the atmosphere and the groundwater is the reaction with the hydroxyl radical or hydroxide ion. This process triggers a sequence of reactions which ultimately yield carbon monoxide, hydrogen chloride, and formic acid. The rate of chloroform degradation is considerably larger in solution than that in the gas phase and it increases dramatically with increasing pH. However, only one of the viable reactions had been studied previously at a high level of theory in solution. It is of great interest to gain a deeper understanding of the decomposition reaction mechanism. Quantum mechanical methods are well suited for studying the mechanism of organic reactions. However, a full quantum mechanical treatment of the entire fluid system is not computationally feasible. In this work, combined quantum mechanical and molecular mechanical (QM/MM) methods are used for studying chemical reactions in condensed phases. In these calculations, the solute molecules are treated quantum mechanically (QM), whereas the solvent molecules are approximated by empirical (MM) potential energy functions. The use of quantum mechanics and statistical sampling simulation is necessary to determine the reaction free energy profile. In the present study, the ab initio Hartree-Fock theory along with the 3-21G basis set was used in the quantum mechanical calculations to elucidate the reaction pathways of chloroform decomposition, with a focus on basic reaction conditions. Statistical mechanical Monte Carlo approach was then applied in molecular mechanical simulations, employing the empirical TIP3P model for water. We employed state-of-the-art electronic structure methods to determine the gas-phase inter-nuclear potential energy profile for all the relevant reactions. Each gas-phase potential energy profile obtained at a high level of theory was used as a post-correction of the corresponding reaction free energy profile in aqueous solution. A detailed picture of the actual mechanism driving the decomposition pathway of chloroform has emerged from these simulations.
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    Computational Modeling of Gas Adsorption, Separation, and Reactivity within Coordinatively Unsaturated Metal-Organic Framework Materials
    (2015-03) Dzubak, Allison
    In this work, computational methodologies are used to investigate the behavior of Metal-Organic Frameworks (MOFs) that are of potential utility in gas separation ap- plications. MOFs are three-dimensional porous materials that are desirable due to their high porosity and internal surface area. Given the myriad of possible framework topologies, computational tools are necessary in order to aid and complement experimental efforts. The focus of this dissertation is specifically coordinatively unsaturated MOFs, a subclass of MOFs for which there are additional computational challenges in treating the exposed metal site. The collection of studies presented here are grouped into four categories: force field parameterization, gas reactivity within MOFs, nature of adsorbate-MOF bonding, and multireference treatment of metal-metal bonds. Ab initio force fields are parameterized for various MOF-gas interactions, where the the NonEmpirical Modeling (NEMO) philosophy is adopted. Wave-Function Theory (WFT) is used for the calculation of the reference energies of the intermolecular terms. Moller-Plesset Perturbation Theory to 2nd order (MP2) and Complete-Active Space Perturbation Theory to 2nd order (CASPT2) are applied for closed-shell and open-shell cases, respectively. These derived force fields are utilized in Grand Canonical Monte Carlo (GCMC) simulations for the MOF + adsorbate systems. Results from GCMC simulations include adsorption isotherms, Henry coefficients, and isosteric heats of adsorption that are compared with the available experimental data, demonstrating the predictive capabilities of this computational procedure. A reaction mechanism between CO2 and amines grafted within the pores of a MOF is proposed based on DFT results, and both DFT and CASPT2 results are utilized to elucidate the nature of a reactive Fe-Oxo intermediate at the exposed Fe site in the MOF. Coupled Cluster (CC), MP2, CASPT2, and DFT are all used to rationalize adsorbate-MOF bonding trends, and the Extended-Transition State Natural Orbitals for Chemical Valence (ETS-NOCV) is used as a comparative tool. Complete-Active Space Self-Consistent Field (CASSCF) and CASPT2 are used for the studies of metal-metal multiple bonded species, and compared with results from DFT.
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    Development of computational tools for modeling the biotransport of small organic molecules into the active site of broad-substrate specificity enzymes
    (2019-07) Escalante, Diego
    In this dissertation research, two new computational tools were developed to model the biotransport of small organic molecules into the active site of broad-substrate specificity (BSS) enzymes. The biological organism selected to develop, test and validate these tools were Rieske non-heme iron dioxygenases. Members of this family of enzymes are known to have biocatalytic activity on more than three hundred different substrates. The large diversity of substrates that can be acted upon makes these enzymes very attractive in biotechnological processes such as bioremediation. In addition, the highly specific chirality of the products obtained makes these enzymes attractive for the potential synthesis of pharmaceutical precursors. Currently, the most common way to identify new substrates requires formulating an educated guess followed by the arduous task of testing each possible compound individually. This slows down the pace at which new industrial processes can be formulated or current ones further developed. The tools presented in this research provide fundamental and practical scientific contributions. For the basic science studies of my dissertation, an all-atom and, a coarse-grained (CG) model of Rieske non-heme iron dioxygenases were used to investigate the factors that affect the biotransport of small organic molecules into their active sites. From the all-atom model I discovered a gating mechanism that allows aromatic substrates into the active site and blocks other compounds. The key to these gates are T-stacked pi-pi interactions between hydrophobic amino acids and the aromatic substrates. On the other hand, from the CG model I discovered that the shape of tunnel modulates the hydrophobicity level of the surface. As the tunnels become more concave, the hydrophobicity increases causing the formation of a water exclusion zone which increases the diffusivity of aromatic substrates. The CG models also revealed that convex tunnels prevent the adhesion of hydrophobic substrates to the tunnel walls; providing a possible explanation for the evolution of bottlenecks at the entrance of Rieske active sites. For the practical contributions of my dissertation, I developed two new computational tools for the prediction of Rieske substrates. The first tool is an all-atom algorithm that models the stochastic roto-translational movement of small organic molecules along the Rieske enzyme tunnels. This algorithm has a 92% prediction accuracy of Rieske substrates. In addition, it is capable of elucidating the location of high-energy barriers along the tunnel, allowing the formulation of possible protein engineering sites. The second tool is a CG non dimensional model of the Rieske enzyme tunnels. This algorithm has a 90% prediction accuracy of Rieske substrates. The processing time of 1ms/substrate combined with its high accuracy allows for the high-throughput screening of possible Rieske substrates.
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    Experimental and Computational Mechanics of Arteries in Health and Disease: An Exploration of Complex Structures and Simple Mathematical Models
    (2021-05) Mahutga, Ryan
    Aortic aneurysm, or dilatation of the aorta, is a clinically significant pathology as the risk of potentially fatal rupture (through-thickness failure) or dissection (delamination of the layers) is the fifteenth leading cause of death in the U.S. [1], with just under 10,000 deaths occurring in 2017 [2]. Current diagnostics for assessing aneurysm risk are aortic size and growth rate [1, 3]. These criteria correlate with aneurysm risk but are not direct measures of tissue strength. These criteria are especially inadequate for rare disorders involving genetic anomalies, where population sizes are relatively small and disease severity can vary widely between individuals. Therefore, it is important that we recognize and understand the underlying pathology that makes one aneurysm different from another, especially in terms of mechanics as this is what dictates aneurysm rupture risk. In this thesis I explore several testing methods for assessing aortic properties in animal models of health and disease. I evaluate the simple ring pull test as a high-throughput mechanical testbed for circumferential mechanics and explore the use of ultrasound for the assessment of complex aortic structures including vessel bifurcations and the aortic arch. These techniques offer unique insights as screening tools for understanding mechanics and for evaluating therapeutics. In order to further understand how the different mechanics in healthy and diseased tissues arise, I created a novel micromechanical model of pathophysiologic remodeling. Using this model, I was able to show pathological differences in mechanical properties despite similar clinical growth parameters. I further developed a technique to model more complex geometries using a multiscale coupling to finite element models. These methods create a unique and useful tool for evaluating remodeling with complex geometries utilizing complex microstructural remodeling scenarios leading to improved understanding of the mechanics of healthy and diseased tissues, as well as being a convenient way to assess tissue-engineered therapies.
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    Thermal modeling and design of a solar non-stoichiometric redox reactor with heat recovery
    (2013-08) Lapp, Justin L.
    A promising new technology for sustainable fuel production is the splitting of water and carbon dioxide by the non-stoichiometric two-step metal oxide redox cycle. Development of oxide materials and reactors to realize the cycle is currently in infancy, with significant room for improvement over previous demonstrations. Research efforts have gone into developing and characterizing reactive metal oxide materials for the cycle, while less literature is devoted to the design and understanding of non-stoichiometric redox reactors. The work presented attempts to close the gap by exploring multiple levels of modeling analysis to determine the important considerations for designing a reactor to perform high efficiency non-stoichiometric redox cycling. Cerium oxide (ceria) is considered as the reactive material for reactors in this work. A reactor for non-stoichiometric redox cycling should allow for continuous use of the solar input and should implement heat recovery. In the first stage of the research, thermodynamic analysis is carried out on a model reactor system to quantify the potential efficiency benefits of heat recovery and to determine the effects of the reduction temperature and sweep gas flow rate. Heat recovery is found to improve reactor efficiency from 4% to 16%. The selection of reduction temperature is important to high efficiency. For many cases the heating of gases is a major source of heat loss, indicating that heat recovery should be applied to the gas flows as well as the solid metal oxide. In the second stage of the research, a reactor is presented which incorporates continuous redox cycling of ceria and heat recovery from the solid ceria by using counter-rotating hollow cylinders of ceria and inert material. Heat transfer modeling is applied to this concept to explore its performance potential and identify the important design factors for effective heat recovery. Energy conservation is applied using a finite volume method with detailed modeling of radiative heat transfer by the Monte Carlo method and the Rosseland diffusion approximation. A simplified model of the rotating cylinders and a more complete model of the full reactor geometry are applied. It is determined that the proposed design can recover over 50% of the heat from the ceria, and provide a temperature differential of 400 K between the reaction steps. Geometric and material parameters are varied in a parametric study to determine which are important forheat recovery. The important parameters for heat recovery and chemical utilization of the material are those which define the heat transport across the ceria cylinder wall. Temperatures, heat transfer rates, heat fluxes, and the chemical state of the material are predicted. Using the heat transfer model results and other analysis, values of thermal design parameters for a prototype reactor are selected as part of an effort leading to a prototype reactor to be built and tested at the University of Minnesota. Heat recovery is found to be a path with great potential for improving the efficiency of solar-driven non-stoichiometric redox cycles. The prototype reactor described has the potential to demonstrate high levels of heat recovery and unprecedented efficiency. However, a careful understanding of the properties of the reactive material and the geometric parameters of the reactor is needed to ensure that heat which is input or removed is effectively transported across the cylinder wall for heat recovery. The models described here account for the important effects and explore the complexity needed to investigate the problem. Primary future improvements to the modeling work will include coupling of heat transfer and fluid mechanics, implementation of chemical rate expressions, and the addition of high-temperature and spectral material properties as they become available.