No description available.

No description available.

Power electronics plays an important role in many energy conversion applications in modern society including consumer electronics, data centers, electric vehicles, and power grids, etc. The key components of power electronic circuits are power semiconductor devices including diodes and transistors, which determine the performance of power electronics circuits. Traditional power devices are based on the semiconductor silicon (Si), which have already reached the silicon's material limit. Gallium nitride (GaN) is a wide bandgap semiconductor with high electron mobility and high critical electric field. GaN-based power devices promise superior device performance over the Si-based counterpart. The primary design target of a unipolar power device is to achieve low on-resistance and high breakdown voltage. Although GaN high electron mobility transistor (HEMT) is commercially available in a voltage class from 15 V to 900 V, the performance of GaN devices is still far below the GaN material limit, due to several reasons: 1) To achieve the normally-off operation in a GaN HEMT, the density of two-dimensional electron gas (2DEG) channel cannot be too high; this limits the on-resistance reduction in the access region. 2) The gate capacitance of GaN HEMT is usually low so that the carrier concentration in the channel underneath the gate is relatively low, limiting the on-resistance reduction in the gated channel region. 3) The electric-field distribution in the drift region is not uniform, resulting in a limited breakdown voltage. We proposed to use the junction-based structure in GaN power devices to address the above problems and fully exploit GaN's material properties. The first part of this dissertation characterizes nickel oxide (NiO) as a p-type material to construct the junction-based GaN power devices. Although the homogenous p-GaN/n-GaN junction is preferred in many devices, the selective-area, p-GaN regrowth can lead to excessive leakage current; in comparison, the p-NiO/n-GaN junction is stable without leakage. This section describes the optimization of NiO deposition as well as the NiO characterization. Although acceptor in NiO is not generated by impurity doping, the acceptor concentration modulation is realized by tuning the O2 partial pressure during the sputtering process. Practical breakdown electric field is also characterized and confirmed to be higher than GaN. These results provide the design guidelines for NiO-GaN junction-based power devices. The second part of this dissertation demonstrates the 3D NiO-GaN junction gate to improve the GaN HEMT's on-resistance. The 3D junction gate structure enables a high carrier concentration under the gate region in the device on-state. Meanwhile, the strong depletion effect of the junction-based gate allows for a robust normally-off operation; as a result, the GaN wafer with a higher 2DEG concentration can be used to achieve both normally-off and low on-state resistance in HEMT devices. Simulation is also performed to project the performance space of trigate GaN junction HEMTs using the p-GaN instead of NiO. The third part of this dissertation presents the application of the p-GaN/n-GaN junction in the drift region of the multi-channel lateral devices to achieve the high breakdown voltage. Here p-GaN is grown in-situ with the multi-channel AlGaN/GaN structure, and there is no leakage problem. The structure is designed to achieve charge balance between the acceptor in p-GaN and the net donor in the multichannel AlGaN/GaN. This design enables a uniform electric field distribution and breakdown voltage over 10 kV. The fourth part of this dissertation presents the application of the p-NiO/n-GaN junction in vertical superjunction (SJ) devices. We show the design and simulation of this heterojunction structure in a SJ and confirm the uniform electric field and high breakdown voltage under the charge balance. Then the device fabrication is presented in detail, which mainly comprises the deep GaN trench etch, NiO self-aligned lift off, and photoresist trench planarization. The optimized device shows a trade-off between its drift region specific on-resistance versus breakdown that exceeds the 1D GaN's limit. The last part of this dissertation is exploring the design and fabrication of p-GaN/n-GaN based SJ devices. First, the challenges in p-GaN regrowth especially the introduction of interface impurities are discussed, followed by device simulation and modeling to optimize the SJ performance considering these interface impurities. The activation of regrown p-GaN in deep trenches is more difficult than planar p-GaN, and we present the characterization and physical model for the activation of the deep buried p-GaN. Last, the results of p-GaN filling regrowth and the acceptor concentration calibration in the lightly doped p-GaN are presented and discussed. In summary, our work combines experimental device fabrication and characterization, TCAD simulation, and device modeling to demonstrate the benefit of multi-dimensional, junction-based GaN power devices as compared to the traditional GaN power devices. The junction-based structure at gate region can provides stable normally-off operation and low on-resistance. When being applied to the drift region, the multidimensional junction structure can push the device specific on-resistance versus breakdown voltage trade-off near or even exceeding the material limit. These results will advance the performance and application spaces of GaN power devices. / Doctor of Philosophy / Power electronics plays an important role in many energy conversion applications in modern society including consumer electronics, data centers, electric vehicles, and power grids, etc. The key components of power electronic circuits are power semiconductor devices including diodes and transistors, which determine the performance of power electronics circuits. Traditional power devices are based on the semiconductor silicon (Si), which have already reached the silicon's material limit. Gallium nitride (GaN) is a wide bandgap semiconductor with high electron mobility and high critical electric field. GaN-based power devices promise superior device performance over the Si-based counterpart. Currently, GaN power devices performance is still far below its material limit due to several reasons: 1) To achieve normally-off operation, the carriers at gate region need to be fully depleted at zero bias. Due to a relatively limited depletion capability of the planar gate, the normally-off operation poses an upper limit on the channel carrier density, which increases the device on-resistance. 2) The electric field distribution is not uniform when the device is blocking off-state voltage, and the crowded electric field will cause the device premature breakdown. This work proposed to use multi-dimensional, p-n junction-based device structure to overcome the above challenges. The devices with diverse structures are fabricated, characterized, and compared with the commercially available devices. The multi-dimensional, junction-based gate structure provides strong electrostatic control to realize normally-off operation and allow for higher carrier concentration and lower on-resistance. The devices with multi-dimensional, junction-based drift region enables the uniform electric field distribution at the device off-state, allowing devices to block high voltage without compromising the on-state resistance. Examples of such devices investigated in this dissertation include the tri-gate junction transistors, reduced-surface-field (RESURF) diodes, and superjunction diodes. In summary, this work demonstrates the multi-dimensional, junction-based device structure to overcome the performance limitations of planar devices and fully exploit GaN's material benefits for power devices. The multi-dimensional, junction-based devices are experimentally fabricated and characterized, manifesting the superior performance over traditional GaN devices. This work will significantly boost the performance and application space of GaN power devices.

A presença que tem hoje a Medicina Nuclear como modalidade de obtenção de imagens médicas é muito importante e um dos principais procedimentos utilizados hoje nos centros de saúde, tendo como grande vantagem a capacidade de conseguir analisar o comportamento metabólico do paciente, fazendo possíveis diagnósticos precoces. Este projeto está baseado em imagens médicas obtidas através da modalidade PET (Positron Emission Tomography) a qual está tendo uma crescente difusão e aceitação. Para isso, temos desenvolvido uma estrutura integral de processamento de imagens tridimensionais PET, a qual está constituída por etapas consecutivas que se iniciam na obtenção das imagens padrões (gold standard), sendo utilizados volumes simulados ou phantoms do Ventrículo Esquerdo do Coração criadas como parte do projeto, assim como geradas a partir do software NCAT-4D. A seguir, nos volumes simulados, é introduzido ruído quântico tipo Poisson que é o ruído característico das imagens PET e feita uma análise que busca certificar que o ruído utilizado corresponde efetivamente ao ruído Poisson. Em sequência é executada a parte de pré-processamento, utilizando para este fim, um conjunto de filtros tais como o filtro da mediana, o filtro da Gaussiana ponderada e o filtro que mistura os conceitos da Transformada de Anscombe e o filtro pontual de Wiener. Posteriormente é aplicada a etapa de segmentação que é considerada a parte central da sequência de processamento. O processo de segmentação é baseado na teoria de Conectividade Fuzzy e para isso temos implementado quatro diferentes abordagens: Algoritmo Genérico, Algoritmo LIFO, Algoritmo kTetaFOEMS e o Algoritmo utilizando Pesos Dinâmicos. Sendo que os três primeiros algoritmos utilizam pesos específicos selecionados pelo usuário, foi preciso efetuar uma análise para determinar os melhores pesos de segmentação que se reflitam numa segmentação mais eficiente. Finalmente, para terminar a estrutura de processamento, um procedimento de avaliação foi utilizado como métrica para obter quantitativamente três parâmetros (Verdadeiro Positivo, Falso Positivo e Máxima Distância) que permitiram conhecer o nível de eficiência e precisão de nosso processo e do projeto em geral. Constatamos que os algoritmos implementados (filtros e algoritmos de segmentação) são bastante robustos e atingem ótimos resultados chegando-se a obter, para o caso do volume do Ventrículo Esquerdo simulado, taxas de VP e FP na ordem de 98.49 ± 0.27% e 2,19 ± 0.19%, respectivamente. Com o conjunto de procedimentos e escolhas feitas ao longo da estrutura de processamento, encerramos o projeto com a análise de um grupo de volumes produto de um exame PET real, obtendo a quantificação destes volumes. / The usefulness of Nuclear medicine nowadays as a modality to obtain medical images is very important, and it has turned into one of the main procedures utilized in Health Care Centers. Its great advantage is to analyze the metabolic behavior of the patient, by allowing early diagnosis. This project is based on medical images obtained by the PET modality (Positron Emission Tomography), which has won wide acceptance. Thus, we have developed an integral framework for processing Nuclear Medicine three-dimensional images of the PET modality, which is composed of consecutive steps that start with the generation of standard images (gold standard) by using simulated images or phantoms of the Left Ventricular Heart that were generated in this project, such as the ones obtained from the NCAT-4D software. Then Poisson quantum noise is introduced into the whole volume to simulate the characteristic noises in PET images and an analysis is performed in order to certify that the utilized noise is the Poisson noise effectively. Subsequently, the pre-processing is executed by using specific filters, such as the median filter, the weighted Gaussian filter, and the filter that joins the concepts of Anscombe Transformation and the Wiener filter. Then the segmentation, which is considered the most important and central part of the whole process, is implemented. The segmentation process is based on the Fuzzy Connectedness theory and for that purpose four different approaches were implemented: Generic algorithm, LIFO algorithm, kTetaFOEMS algorithm, and Dynamic Weight algorithm. Since the first three algorithms used specific weights that were selected by the user, an extra analysis was performed to determine the best segmentation constants that would reflect an accurate segmentation. Finally, at the end of the processing structure, an assessment procedure was used as a measurement tool to quantify some parameters that determined the level of efficiency and precision of our process and project. We have verified that the implemented algorithms (filters and segmentation algorithms) are fairly robust and achieve optimal results, assist to obtain, in the case of the Left Ventricular simulated, TP and FP rates in the order of 98.49 ± 0.27% and 2.19 ± 0.19%, respectively. With the set of procedures and choices made along of the processing structure, the project was concluded with the analysis of a volumes group from a real PET exam, obtaining the quantification of the volumes.

A presença que tem hoje a Medicina Nuclear como modalidade de obtenção de imagens médicas é muito importante e um dos principais procedimentos utilizados hoje nos centros de saúde, tendo como grande vantagem a capacidade de conseguir analisar o comportamento metabólico do paciente, fazendo possíveis diagnósticos precoces. Este projeto está baseado em imagens médicas obtidas através da modalidade PET (Positron Emission Tomography) a qual está tendo uma crescente difusão e aceitação. Para isso, temos desenvolvido uma estrutura integral de processamento de imagens tridimensionais PET, a qual está constituída por etapas consecutivas que se iniciam na obtenção das imagens padrões (gold standard), sendo utilizados volumes simulados ou phantoms do Ventrículo Esquerdo do Coração criadas como parte do projeto, assim como geradas a partir do software NCAT-4D. A seguir, nos volumes simulados, é introduzido ruído quântico tipo Poisson que é o ruído característico das imagens PET e feita uma análise que busca certificar que o ruído utilizado corresponde efetivamente ao ruído Poisson. Em sequência é executada a parte de pré-processamento, utilizando para este fim, um conjunto de filtros tais como o filtro da mediana, o filtro da Gaussiana ponderada e o filtro que mistura os conceitos da Transformada de Anscombe e o filtro pontual de Wiener. Posteriormente é aplicada a etapa de segmentação que é considerada a parte central da sequência de processamento. O processo de segmentação é baseado na teoria de Conectividade Fuzzy e para isso temos implementado quatro diferentes abordagens: Algoritmo Genérico, Algoritmo LIFO, Algoritmo kTetaFOEMS e o Algoritmo utilizando Pesos Dinâmicos. Sendo que os três primeiros algoritmos utilizam pesos específicos selecionados pelo usuário, foi preciso efetuar uma análise para determinar os melhores pesos de segmentação que se reflitam numa segmentação mais eficiente. Finalmente, para terminar a estrutura de processamento, um procedimento de avaliação foi utilizado como métrica para obter quantitativamente três parâmetros (Verdadeiro Positivo, Falso Positivo e Máxima Distância) que permitiram conhecer o nível de eficiência e precisão de nosso processo e do projeto em geral. Constatamos que os algoritmos implementados (filtros e algoritmos de segmentação) são bastante robustos e atingem ótimos resultados chegando-se a obter, para o caso do volume do Ventrículo Esquerdo simulado, taxas de VP e FP na ordem de 98.49 ± 0.27% e 2,19 ± 0.19%, respectivamente. Com o conjunto de procedimentos e escolhas feitas ao longo da estrutura de processamento, encerramos o projeto com a análise de um grupo de volumes produto de um exame PET real, obtendo a quantificação destes volumes. / The usefulness of Nuclear medicine nowadays as a modality to obtain medical images is very important, and it has turned into one of the main procedures utilized in Health Care Centers. Its great advantage is to analyze the metabolic behavior of the patient, by allowing early diagnosis. This project is based on medical images obtained by the PET modality (Positron Emission Tomography), which has won wide acceptance. Thus, we have developed an integral framework for processing Nuclear Medicine three-dimensional images of the PET modality, which is composed of consecutive steps that start with the generation of standard images (gold standard) by using simulated images or phantoms of the Left Ventricular Heart that were generated in this project, such as the ones obtained from the NCAT-4D software. Then Poisson quantum noise is introduced into the whole volume to simulate the characteristic noises in PET images and an analysis is performed in order to certify that the utilized noise is the Poisson noise effectively. Subsequently, the pre-processing is executed by using specific filters, such as the median filter, the weighted Gaussian filter, and the filter that joins the concepts of Anscombe Transformation and the Wiener filter. Then the segmentation, which is considered the most important and central part of the whole process, is implemented. The segmentation process is based on the Fuzzy Connectedness theory and for that purpose four different approaches were implemented: Generic algorithm, LIFO algorithm, kTetaFOEMS algorithm, and Dynamic Weight algorithm. Since the first three algorithms used specific weights that were selected by the user, an extra analysis was performed to determine the best segmentation constants that would reflect an accurate segmentation. Finally, at the end of the processing structure, an assessment procedure was used as a measurement tool to quantify some parameters that determined the level of efficiency and precision of our process and project. We have verified that the implemented algorithms (filters and segmentation algorithms) are fairly robust and achieve optimal results, assist to obtain, in the case of the Left Ventricular simulated, TP and FP rates in the order of 98.49 ± 0.27% and 2.19 ± 0.19%, respectively. With the set of procedures and choices made along of the processing structure, the project was concluded with the analysis of a volumes group from a real PET exam, obtaining the quantification of the volumes.

Doctor of Philosophy / Department of Agronomy / Ganga M. Hettiarachchi / The milling and mining operations of metal ores are one of the major sources of heavy metal contamination at earth’s surface. Due to historic mining activities conducted in the Tri-State mining district, large area of land covered with mine waste, and soils enriched with lead (Pb), zinc (Zn) and cadmium (Cd) remain void of vegetation influencing ecosystem and human health. It has been hypothesized that if these minewaste materials are disposed of in the flooded subsidence pits; metals can be transformed into their sulfide forms under reduced conditions limiting their mobility, and toxicity. These mine waste materials are high in pH, low in organic carbon (OC) and sulfur (S). The objective of this study was to examine the effect of OC and S addition on the biogeochemical transformations of Pb, Zn and Cd in submerged mine waste containing microcosms. Advanced molecular spectroscopic and microbiological techniques were used to obtain a detail, mechanistic, and molecular scale understanding of the effect of natural and stimulated redox conditions on biogeochemical transformation and dynamics of Pb, Zn and Cd essential for designing effective remediation and mitigation strategies. The results obtained from these column studies indicated that Pb, Zn and Cd were effectively immobilized upon medium (119-day) and long-term (252-day) submergence regardless of treatment. The OC plus S treatment enhanced sulfide formation as supported by scanning electron microscopy- energy dispersive X-ray technique, and synchrotron based bulk-, and micro-X-ray fluorescence and absorption spectroscopy analyses. Microbial community structure changed with OC and S addition with the enhancement sulfur reducing bacteria genes (dsrA/B), and decreased metal resistance genes over time. The long-term submergence of existing mine tailings with OC plus S addition reduced trace metals mobility most likely through dissimilatory sulfate reduction under stimulated reduced conditions. Colloidal assisted metal transportation (<1% of both Pb and Cd) occurred during initial submergence. Retention filters are suggested to avoid colloidal metal transport in order to meet the maximum concentration limit for Pb and Cd in surface and groundwater. This research enhances our understanding of the redox processes associated with the sequestration of non-redox sensitive metals through dissimilatory reduction of sulfates in mine waste materials and/or waste water and provides regulators with useful scientific evidence for optimizing remediation goals.

The reason for the study is that IT-enabled organizational change processes such as information system implementations have high costs and disappointing results. Studies to identify causes of the mentioned failures are mainly based on a variance approach. This study applies another approach which is not yet performed in this field of research and affects several themes. Based on a process approach data is compared with ideal-process theories to identify the generative mechanisms causing the unfolding of the process. Thus, the study identifies a recipe and not the ingredients.

Les algies pelviennes aigues constituent le premier motif de consultation aux urgences gynécologiques. Les étiologies possibles de ces algies pelviennes aigues sont nombreuses et incluent à la fois des affections gynécologiques et non gynécologiques. Certaines de ces affections peuvent, en l'absence de diagnostic précoce et d'un traitement adapté, avoir des conséquences très graves. Dans ce travail, nous avons développé un autoquestionnaire standardisé de manière qualitative dédié aux urgences gynécologiques par des entretiens structurés. Nous avons ensuite construit des modèles de prédiction clinique dédiés (i) au diagnostic de rupture tubaire chez les patientes porteuses de grossesses extra-utérines et (ii) au diagnostic de torsion d'annexe à partir de cet autoquestionnaire. Après avoir défini le concept d'urgence potentiellement à risque en gynécologie, nous avons proposé (iii) un modèle de prédiction clinique de celles-ci basé sur notre autoquestionnaire standardisé. A l'issue du développement de ces modèles, nous avons sélectionné certains items de l'autoquestionnaire standardisé afin d'en proposer une version simplifiée. L'utilisation de nos modèles pour le tri et le diagnostic des patientes aux urgences gynécologiques pourrait permettre d'optimiser la prise en charge des patientes. Dans les groupes à haut risque de pathologie, les patientes pourraient bénéficier d'une prise en charge plus rapide avec une éventuelle diminution de la morbidité secondaire à la pathologie. Pour les patientes classées à bas risque, une désescalade des examens complémentaires et des chirurgies inutiles pourrait aussi permettre une diminution de la morbidité d'origine iatrogène.

Malgré de nombreux travaux, il apparaît que les outils d'Analyse Typologiques ne permettent pas de réduire les délais d'implantation de la Technologie de Groupe. Cette démarche de rationalisation du système de production pose un problème général de classification que nous baptiserons ACCI. Il s'agit de construire sur un domaine de connaissance peu formalisé, une classification jugée pertinente par les experts du domaine. En terme d'Acquisition de Connaissances, l'ACCI a pour objectif de représenter l'activité d'un groupe d'expert à l'aide d'un modèle dit de classification simple. Les outils susceptibles de contribuer à résoudre ce problème proviennent de domaines variés : l'Analyse Typologique, la Classification Conceptuelle, les réseaux de Neurones et les Algorithmes Génétiques mais reposent sur un principe commun qui défini le concept d'Outils de Classification Automatique (OCA). Dans le cadre de l'ACCI, ces outils présentent des limites intrinsèques. La plupart des travaux menés pour y remédier, proposent des approchent interactives qui aident les experts à reformuler leurs connaissances en fonction de l'OCA utilisé. C'est à dire, sous la forme d'attributs descriptifs des objets tels qu'il devient possible d'en déduire des classes par des opérations de comparaison simples. Nous proposons une approche interactive qui a pour vocation de s'adapter aux experts en intégrant directement dans le processus de classification, les connaissances qu'ils sont à même de formuler naturellement lorsqu'ils valident une partition des objets du domaine. Cette approche a été testé sur un cas réel à l'aide d'un prototype informatique. Elle contribue à résoudre le problème de l'utilisation des outils d'Analyse Typologique pour réduire les délais d'implantation de la TG, et s'applique potentiellement à d'autre domaine, car les connaissances manipulées par le système ne sont pas liées au domaine d'application, mais à la structure recherchée (une partition).

We investigate several aspects of the numerical solution of the radiative transfer equation in the context of coal combustion: the parallel efficiency of two commonly used opacity models, the sensitivity of turbulent radiation interaction (TRI) effects to the presence of coal particulate, and an improvement of the order of temporal convergence using the coarse mesh finite difference (CMFD) method. There are four opacity models commonly employed to evaluate the radiative transfer equation in combustion applications; line-by-line (LBL), multigroup, band, and global. Most of these models have been rigorously evaluated for serial computations of a spectrum of problem types [1]. Studies of these models for parallel computations [2] are limited. We assessed the performance of the Spectral-Line- Based weighted sum of gray gasses (SLW) model, a global method related to K-distribution methods [1], and the LBL model. The LBL model directly interpolates opacity information from large data tables. The LBL model outperforms the SLW model in almost all cases, as suggested by Wang et al. [3]. The SLW model, however, shows superior parallel scaling performance and a decreased sensitivity to load imbalancing, suggesting that for some problems, global methods such as the SLW model, could outperform the LBL model. Turbulent radiation interaction (TRI) effects are associated with the differences in the time scales of the fluid dynamic equations and the radiative transfer equations. Solving on the fluid dynamic time step size produces large changes in the radiation field over the time step. We have modifed the statistically homogeneous, non-premixed flame problem of Deshmukh et al. [4] to include coal-type particulate. The addition of low mass loadings of particulate minimally impacts the TRI effects. Observed differences in the TRI effects from variations in the packing fractions and Stokes numbers are difficult to analyze because of the significant effect of variations in problem initialization. The TRI effects are very sensitive to the initialization of the turbulence in the system. The TRI parameters are somewhat sensitive to the treatment of particulate temperature and the particulate optical thickness, and this effect are amplified by increased particulate loading. Monte Carlo radiative heat transfer simulations of time-dependent combustion processes generally involve an explicit evaluation of emission source because of the expense of the transport solver. Recently, Park et al. [5] have applied quasidiffusion with Monte Carlo in high energy density radiative transfer applications. We employ a Crank-Nicholson temporal integration scheme in conjunction with the coarse mesh finite difference (CMFD) method, in an effort to improve the temporal accuracy of the Monte Carlo solver. Our results show that this CMFD-CN method is an improvement over Monte Carlo with CMFD time-differenced via Backward Euler, and Implicit Monte Carlo [6] (IMC). The increase in accuracy involves very little increase in computational cost, and the figure of merit for the CMFD-CN scheme is greater than IMC. / Graduation date: 2012