<p> There is only one unambiguous report in the literature of anchimeric assistance by the π-bond in a free radical reaction. It was the purpose of this work to investigate the possibility of such acceleration in the thermal homolysis of 7-norbornene peresters. Two such t-butyl peresters, the isomeric syn- and anti-7-norbornene percarboxylates as well as t-butyl 7-norbornane percarboxylate, were prepared and their decomposition was studied by kinetic methods and product analysis.</p> <p> The homolysis of 7-norbornene peresters is shown to occur with rate-determining perester O-O bond rupture, the transition state of which may be a hybrid of radical and polar structures. A low order of anchimeric acceleration may also assist the decomposition of the syn compound.</p> <p> The pKa values for syn- and anti- 7-norbornene- and 7-norbornane- carboxylic acid are reported.</p> / Thesis / Doctor of Philosophy (PhD)

The price fluctuation and depletion of crude oil have led to the fervent interest in finding alternatives that can satisfy our increasing need for energy. In the past decades, two primary approaches are seen as promising ways to remedy our dependence on crude oil: first, the use of natural gas, primarily methane, to produce high-value hydrocarbons, and second, the use of ammonia as a hydrogen carrier. In this dissertation, we used density functional theory (DFT) calculation and kinetic modeling to investigate methane activation and C-C coupling on WC as well as the ammonia decomposition over the CoNi alloy surface. From our methane conversion project, we investigated the reactivity of W-terminated WC(0001) and WC(112 ̅0) surface toward methane activation and conversion to produce C2 moieties using DFT. We first calculate the intermediates binding energies and activation and reaction energies of methane dissociation. We found that WC(112 ̅0) is better at dissociating the first C–H bond than WC(0001). Our results also indicate that the surface is likely populated by (CH)ads species. The mobility of (CH)ads species on both surfaces allows the possibility of C-C coupling, resulting in a precursor for higher hydrocarbon formation. Our results also demonstrate that the WC(0001) surface favors the production of the (C2H2)ads species, whereas the WC(112 ̅0) surface dissociates CHx completely, resulting in coke formation. Thus, methane dissociates readily on the WC surfaces whereas the formation of the C2 species is sensitive to the surface structure. The DFT study on ammonia decomposition has been performed in close collaboration with the experimental study. A highly active catalyst consisting of CoNi alloy nanoparticles well-dispersed on a MgO–CeO2–SrO mixed oxide support with potassium promotion exhibited a performance matching that of the Ru-based catalysts. Extensive characterization in combination with the DFT results revealed that the CoNi alloy surface and metal/oxide interfaces are the active sites for catalytic decomposition of ammonia. Moreover, the much improved catalytic activity stems mainly from the presence of interface where the recombinative desorption of nitrogen has been greatly enhanced. These have been demonstrated by examining the detailed elementary steps of ammonia decomposition on the Co, Ni, Co2Ni, CoNi2 (111) surfaces and at the CeO2/Co2Ni interface. We calculated the binding energies of intermediates and the activation energies of each elementary step in ammonia decomposition. We found that on the Co, Ni, Co2Ni, CoNi2 surfaces, N–N bond formation is the rate-determining step, with the CoNi alloy surfaces having a lower activation energy than the pure metal surfaces. Over the CeO2/Co2Ni interface, however, N–H bond dissociation becomes rate-determining. The high catalytic activity at the CeO2/Co2Ni interface originates from the localized charge polarization due to alloying and the presence of the oxide which drastically facilitates N2* formation. We then integrated the DFT-calculated adsorption and activation energies in the microkinetic modeling of ammonia decomposition on the Co, Co2Ni, CoNi2, and Ni surfaces, focusing on the alloying effect. Two cases were investigated: ammonia decomposition in the 1) absence and 2) presence of product re-adsorption. In both cases, we determined the turnover frequencies, the apparent activation energies, the steady-state coverages, the degree of rate control, and the reaction orders. Our results show that in both cases, the alloys have higher catalytic performance than the pure metals. We also found that as the temperature increases, ammonia decomposition switches from being limited by N–N (and N–NH) bond formation to N–H bond dissociation. This change of mechanism is predicted to occur at lower temperatures on the alloy surfaces. In the case of hydrogen re-absorption, the surface H* adatom retards the last N–H bond-breaking step, resulting in the high coverage of NH* species on the surfaces, making N–NH coupling an alternative pathway for N2 formation. Furthermore, our microkinetic results show that alloying Ni with Co reduces the effect of hydrogen inhibition at high hydrogen partial pressures. In summary, this dissertation provides information for the design of efficient catalysts toward methane conversion and ammonia decomposition.

Information retrieval is the process of fulfilling a user?s need for information by locating items in a data collection that are similar to a complex query that is often posed in natural language. Latent Semantic Indexing (LSI) was the predominant technique employed at the National Institute of Standards and Technology?s Text Retrieval Conference for many years until limitations of its scalability to large data sets were discovered. This thesis describes SCRIBE, a modification of LSI with improved scalability. SCRIBE clusters its semantic index into discrete volumes described by high-dimensional extensions to computer graphics data structures. SCRIBE?s clustering strategy limits the number of items that must be searched and provides for sub-linear time complexity in the number of documents. Experimental results with a large, natural language document collection demonstrate that SCRIBE achieves retrieval accuracy similar to LSI but requires 1/10 the time.

The interfacial heat transfer coefficient is an important variable regarding the subject of metal castings. The error associated with the experimental temperature data must be dealt with appropriately so that they do not significantly affect the resulting interfacial heat transfer coefficient. The systematic and random errors are addressed using a combination of three-dimensional finite element modeling and the matrix transform method, respectively. Experimentally obtained A356 permanent mold casting data was used to estimate the interfacial heat transfer coefficient corresponding to common industrial mold coatings.

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We prove convergence of the Adomian Decomposition Method (ADM) by using the Cauchy-Kovalevskaya theorem for differential equations with analytic vector fields, and obtain a new result on the convergence rate of the ADM. Picard's iterative method is considered for the same class of equations in comparison with the decomposition method. We outline some substantial differences between the two methods and show that the decomposition method converges faster than the Picard method. Several nonlinear differential equations are considered for illustrative purposes and the numerical approximations of their solutions are obtained using MATLAB. The numerical results show how the decomposition method is more effective than the standard ODE solvers. Moreover, we prove convergence of the ADM for the partial differential equations and apply it to the cubic nonlinear Schrodinger equation with a localized potential. / Thesis / Master of Science (MSc)

In this thesis, first we propose a new approach to solve Semi Infinite Linear Optimization Problems (SILP). The new algorithm uses the idea of adding violated cut or cuts at each iteration. Our proposed algorithm distinguishes itself from Luo, Roos, and Terlaky's logarithmic barrier decomposition method, in three aspects: First, the violated cuts are added at their original locations. Second, we extend the analysis to the case where multiple violated cuts are added simultaneously, instead of adding only one constraint at a time. Finally, at each iteration we update the barrier parameter and the feasible set in the same step. In terms of complexity, we also show that a good approximation of an optimal solution will be guaranteed after finite number of iterations. Our focus in this thesis is mainly on the implementation of our algorithm to approximate an optimal solution of the SILP. Our numerical experiences show that unlike other SILP solvers which are suffering from the lack of accuracy, our algorithm can reach high accuracy in a competitive time. We discuss the linear algebra involved in efficient implementation and describe the software that was developed. Our test problem set includes large scale second order conic optimization problems. / Thesis / Master of Applied Science (MASc)

<p> EEG is a noninvasive technique useful for the human brain mapping and for the estimation of neural electrical activities in human brain. A goal of processing EEG signals of a subject is the localization of neural current sources in human brain known as dipoles. Although this location estimation problem can be modeled as a particular kind of parameter estimation problem as in array signal processing, the nonlinear structure of an EEG electrode array, which is much more complicated than a traditional sensor array, makes the problem more difficult. </p> <p> In this thesis, we formulate the inverse problem of the forward model on computing the scalp EEG at a finite set of sensors from multiple dipole sources. It is observed that the geometric structure of the EEG array plays a crucial role in ensuring a unique solution for this problem. We first present a necessary and sufficient condition in the model of a single rotating dipole, that guarantees its location to be uniquely determined, when the second-order statistic of the EEG observation is available. In addition, for a single rotating dipole, a closed-form solution to uniquely determine its position is obtained by exploiting the geometrical structure of the EEG array. </p> <p> In the case of multiple dipoles, we suggest the use of the Maximum Likelihood (ML) estimator, which is often considered optimum in parameter estimation. We propose an efficient localization algorithm based on QR decomposition. Depending on whether or not the probability density functions of the dipole amplitude and the noise are available, we utilize the non-coherent ML or the LS as the criterion to develop a unified successive localization algorithm, so that solving the original multi-dipole optimization problem can be approximated by successively solving a series of single-dipole optimization problems. Numerical simulations show that our methods have much smaller estimation errors than the existing RAP-MUSIC method under non-ideal situations such as low SNR with small number of EEG sensors. </p> / Thesis / Master of Applied Science (MASc)

This dissertation explores the persistent gap between rural and urban areas in the percentage of households that access the Internet at home (a discrepancy commonly known as the "digital divide"). The theoretical framework underlying a household's Internet adoption decision is examined, with emphasis on the roles that household characteristics, network externalities, and digital communication technology (DCT) infrastructure potentially play. This framework is transferred into a statistical model of household Internet access, where non-linear decomposition techniques are employed to estimate the contributions of these variables to the digital divide in a given year. Differences in Internet access rates between years are also analyzed to understand the importance of temporal resistance to the continuing digital divide. The increasing prevalence of "high-speed" or broadband access is also taken into account by modeling a decision process where households that choose to have Internet access must decide between dial-up and high-speed access. This nested process is also decomposed in order to estimate the contributions of household characteristics, network externalities, DCT infrastructure, and temporal resistance to the high-speed digital divide. The results suggest that public policies designed to alleviate digital divides in both general and high-speed access should focus more on the broader income and education inequities between rural and urban areas. The results also imply that the current policy environment of encouraging DCT infrastructure investment in rural areas may not be the most effective way to close the digital divide in both general and high-speed Internet access. / Ph. D.