Controlled-Source Electromagnetics (CSEM) is a method that has been used since the 1980’s in the marine environment for determining electrical properties of the subsurface. Receivers on the seafloor collect total electric and magnetic fields which are produced as a result of interaction of the transmitter generated primary fields with the seawater and subsurface. Badea et al. (2001) coded an existing algorithm for solving Maxwell’s equations. This finite element 3D forward modeling algorithm is used to simulate CSEM experiments. The objective of the present study is to model the changes in electromagnetic response for a resistive disk and a more geometrically complex structure, which are rough approximations of hydrocarbon reservoirs. The parameters that are varied in studying these subsurface structures are the disk radius, disk depth, the transmitter frequency, the transmitter location, and the structure orientation.The results showed that a disk of finite radius behaves similar to an infinite disk at short range and grades into double half-space behavior at longer ranges. The frequency of the transmitter must be tuned to the disk depth as certain frequencies will penetrate too shallow or too deep to probe the disk. Moving the transmitter away from the receivers causes a decrease in signal strength, but exhibits a greater capacity to distinguish between the double half-space and infinite disk scenarios. The disk was then replaced by a more complex structure. To determine if the 3D nature of the structure may be located a study was undertaken to probe the structure from different perspectives using different transmitter locations and azimuths. It is determined that the 3D nature of the structure could not be observed until the structure’s thickness is sufficiently large.The goal of the study is to better understand the effect of subsurface parameters on the total fields and show the usefulness of the 3D forward modeling code. Understanding the relationships between these parameters and the resulting signals is important in terms of setting up a real experiment. Marine CSEM studies are costly and using a valuable tool such as an accurate finite element 3D forward modeling algorithm may save time and money.

The kidneys and the eyes are sensitive to blood pressure changes. The kidney participates in blood pressure control and renal disease can cause arterial hypertension and be aggravated by hypertension, entering a vicious circle between both alterations. In human patients with hypertension, increased vascular resistance is observed in renal and ocular arteries. This increased vascular resistance can be measured with Doppler ultrasound by calculating resistive and pulsatility indices. Increased renal and ocular indices have been observed in human patients with hypertension, and a correlation between the indices and the systolic blood pressure and hypertensive damage has also been reported. The indices values in normal animals vary slightly among the studies and the technique, the operator and, the administration of sedative or anaesthetic drugs can cause variation of the indices. Then, obtaining your own reference values is necessary. The aim of this study is to determine if increased vascular resistance is found in dogs and cats with diseases that can cause hypertension and whether they are related with arterial blood pressure. Values were obtained in non-sedated healthy animals and the effect of a sedative protocol appropriated to be used in ill animals, if necessary, was evaluated. Then renal and ocular resistive and pulsatility indices and systolic blood pressure were obtained in dogs and cats with diseases that can cause hypertension, such as renal disease, diabetes mellitus, hyperadrenocorticism, and hepatic disease. Significant increased renal indices were found in the disease groups in comparison to healthy animals. Correlations with blood parameters and the indices were also found in different diseases. Correlation with blood pressure was not found in any of the groups. In conclusion, increased peripheral vascular resistance was found in the kidney in animals with these diseases, as well as certain degree of relationship with the severity of the disease (evaluated by means of blood parameters). However, no correlation with systolic blood pressure was observed.

A control method is proposed for exercising specific muscles of a human's lower body. This is accomplished using an exoskeleton that imposes active force feedback control. The proposed method involves a combined dynamic model of the musculoskeletal system of the lower-body with the dynamics of pneumatic actuators. The exoskeleton is designed to allow for individual control of mono-articular or bi-articular muscles to be exercised while not inhibiting the subject's range of motion. The control method has been implemented in a 1-Degree of Freedom (DOF) exoskeleton that is designed to resist the motion of the human knee by applying actuator forces in opposition to a specified muscle force profile. In this research, there is a discussion on the model of the human's lower body and how muscles are affected as a function of joint positions. Then it is discussed how to calculate for the forces needed by a pneumatic actuator to oppose the muscles to create the desired muscle force profile at a given joint angles. The proposed exoskeleton could be utilized either for rehabilitation purposes, to prevent muscle atrophy and bone loss of astronauts, or for muscle training in general.

Controlled-Source Electromagnetics (CSEM) is a method that has been used since the 1980’s in the marine environment for determining electrical properties of the subsurface. Receivers on the seafloor collect total electric and magnetic fields which are produced as a result of interaction of the transmitter generated primary fields with the seawater and subsurface. Badea et al. (2001) coded an existing algorithm for solving Maxwell’s equations. This finite element 3D forward modeling algorithm is used to simulate CSEM experiments. The objective of the present study is to model the changes in electromagnetic response for a resistive disk and a more geometrically complex structure, which are rough approximations of hydrocarbon reservoirs. The parameters that are varied in studying these subsurface structures are the disk radius, disk depth, the transmitter frequency, the transmitter location, and the structure orientation.The results showed that a disk of finite radius behaves similar to an infinite disk at short range and grades into double half-space behavior at longer ranges. The frequency of the transmitter must be tuned to the disk depth as certain frequencies will penetrate too shallow or too deep to probe the disk. Moving the transmitter away from the receivers causes a decrease in signal strength, but exhibits a greater capacity to distinguish between the double half-space and infinite disk scenarios. The disk was then replaced by a more complex structure. To determine if the 3D nature of the structure may be located a study was undertaken to probe the structure from different perspectives using different transmitter locations and azimuths. It is determined that the 3D nature of the structure could not be observed until the structure’s thickness is sufficiently large.The goal of the study is to better understand the effect of subsurface parameters on the total fields and show the usefulness of the 3D forward modeling code. Understanding the relationships between these parameters and the resulting signals is important in terms of setting up a real experiment. Marine CSEM studies are costly and using a valuable tool such as an accurate finite element 3D forward modeling algorithm may save time and money.

<p>Isolationsdiagnostik är ett redskap som är av stor betydelse för underhållsoptimering av elektriska anläggningar. Ett av de möjliga mått på isolationsförsämring som kan användas i diagnosticeringssyfte är partiella urladdningar. Det här examensarbetet beskriver ett modelleringsförsök av ett resistivt-kapacitivt nätverk för simulering av partiella yturladdningar i Matlab. Tyvärr blev försöket misslyckat på grund av ett oväntat stort beroende av högspänningskapacitanser på ytresistiviteten. Ytterligare ett försök genomfördes i COMSOL Multiphysics, ett program baserat på finita elementmetoden ämnat för simuleringar av fysikaliska processer. Den huvudsakliga nackdelen med COMSOL Multiphysics modellen är långa simuleringstider. Det visade sig vara möjligt att simulera urladdningar i COMSOL Multiphysics. Här modellerades ytresistansen med hjälp av ett resistivt skikt. Yturladdningar simulerades genom att ändra det resistiva skiktets konduktivitet. Här upptäcks ytterligare ett problem: mycket långa simuleringstider vid användandet av olinjära konduktivitetsuttryck som beror på det elektriska fältet.</p><p>Alla simuleringar, både i Matlab och COMSOL Multiphysics, utfördes på en dator med Intel dual-core processor: 2.13 GHz, 0.99 GB of RAM.</p> / <p>Insulation diagnostics is a very important tool in optimization of electric installations’ maintenance. One of the possible measures of insulation deterioration that can be used for diagnostic purposes are partial discharges. This thesis work describes an attempt to model a resistive-capacitive network for simulating partial surface discharges in Matlab. Unfortunately this attempt proved to be a failure due to an unexpectedly considerable dependency of high voltage capacitances on surface resistivity. Another attempt described here was performed in COMSOL Multiphysics, a finite-element based program for simulation of physical processes. The main drawback with COMSOL Multiphysics model is long simulation times. It proved to be possible to simulate discharges in COMSOL Multiphysics. Here surface resistance was modeled with the help of a resistive layer. Discharges were simulated by changing conductivity of the mentioned layer. Here another problem was discovered: very long simulation times when using non-linear, electric field dependent expressions for conductivity.</p><p>All the simulations, both in Matlab and COMSOL Multiphysics, were performed on a computer with Intel dual-core processor: 2.13 GHz, 0.99 GB of RAM.</p>

CdS/CdTe solar cell performance and reproducibility can be improved by integrating a ZTO buffer layer, which interdiffuses into the CdS layer during device fabrication. Reducing the thickness of CdS layer improves the QE in the blue spectral region without affecting the device performance. This buffer layer is expected to prevent the formation of localized TCO/CdTe junction during high temperature processing.The CdS/CdTe Solar Cell was modified by introducing ZTO as a buffer layer between the window layer (CdS) and the absorber layer (CdTe). Studies were performed on different varying ZTO processing parameters like (a) Zn/Sn atomic ratios during sputtering process, (b) ZTO thickness, (c) ZTO heat treatment temperature, and (d) ZTO heat treatment ambient.

Quick evaluation of reservoir performance is a main concern in decision making. Time-consuming input data preparation and computing, along with data uncertainty tend to inhibit the use of numerical reservoir simulators. New analytical solutions are developed for capacitance-resistive models (CRMs) as fast predictive techniques, and their application in history-matching, optimization, and evaluating reservoir uncertainty for water/CO₂ floods are demonstrated. Because the CRM circumvents reservoir geologic modeling and saturation-matching issues, and only uses injection/production rate and bottomhole pressure data, it lends itself to rapid and frequent reservoir performance evaluation. This study presents analytical solutions for the continuity equation using superposition in time and space for three different reservoir-control volumes: 1) entire field volume, 2) volume drained by each producer, and 3) drainage volume between an injector/producer pair. These analytical solutions allow rapid estimation of the CRM unknown parameters: the interwell connectivity and production response time constant. The calibrated model is then combined with oil fractional-flow models for water/CO₂ floods to match the oil production history. Thereafter, the CRM is used for prediction, optimization, flood performance evaluation, and reservoir uncertainty quantification. Reservoir uncertainty quantification is directly obtained from several equiprobable history-matched solutions (EPHMS) of the CRM. We validated CRM's capabilities with numerical flow-simulation results and tested its applicability in several field case studies involving water/CO₂ floods. Development and application of fast, simple and yet powerful analytic tools, like CRMs that only rely on injection and production data, enable rapid reservoir performance evaluation with an acceptable accuracy. Field engineers can quickly obtain significant insights about flood efficiency by estimating interwell connectivities and use the CRM to manage and optimize real time reservoir performance. Frequent usage of the CRM enables evaluation of numerous sets of the EPHMS and consequently quantification of reservoir uncertainty. The EPHMS sets provide good sampling domains and reasonable guidelines for selecting appropriate input data for full-field numerical modeling by evaluating the range and proper combination of uncertain reservoir parameters. Significant engineering and computing time can be saved by limiting numerical simulation input data to the EPHMS sets obtained from the CRMs. / text

In den Manganaten können kleine Änderungen von externen Feldern die elektronischen, magnetischen und strukturellen Eigenschaften drastisch beeinflussen. In dieser Arbeit wird der Einfluss von elektrischen Feldern und Licht auf den elektrischen Transport in Manganatschichten analysiert. Durch elektrische Feldern können die Widerstände des Manganats remanent und reversibel zwischen verschiedenen Widerstandsniveaus in Abhängigkeit von der Polarität und der Größe des elektrischen Feldes eingestellt werden. Dieser, auch als bipolares Widerstandsschalten bezeichnete Effekt, wird in nanokolumnaren Lanthan und Strontium dotierten Manganatschichten mittels leitfähiger Rasterkraftmikroskopie und in mittels Elektronenstrahllithographie präparierten Mikrostrukturen studiert. Des Weiteren wird der Einfluss von Laseranregungen auf die erste und dritte harmonische Spannung in einer Lanthan und Barium dotierten Manganatschicht untersucht.

Le but de cette thèse était de caractériser et d’aider au développement des premières mémoires résistives verticales (VRRAM) fabriquées au LETI. Parmi les mémoires émergentes, les mémoires résistives (ReRAM) semblent prometteuses en termes de miniaturisation, de vitesse de commutation, de coût et de simplicité d’intégration. Comme pour les mémoires FLASH, qui ont déjà atteint leur limite physique en terme de miniaturisation, les mémoires résistives ont déjà été étudiées dans une géométrie verticale pour proposer des solutions qui maximisent la densité. Au début de ce travail on a étudié des échantillons 1R pour avoir une compréhension générale du fonctionnement et faire un balayage des matériaux et des épaisseurs. Une fois identifiées les configurations optimales, les mémoires ont été intégrées dans des structures 1T-1R pour pouvoir les étudier d’une manière plus industrielle. Les mémoires 1R ont été intégrées dans des structures MESA et celles 1T-1R ont été intégrées dans des structures MESA et VIA. Dans les deux cas le point mémoire se trouve dans les flancs de la structure ; il était particulièrement compliqué de déposer l’électrode supérieure. Les dispositifs ont été caractérisés électriquement afin d’obtenir les informations suivantes : résistance initiale, tension de formation, set et reset, temps de commutation, états de haute et basse résistivité, endurance et temps de rétention. Ces informations ont permis d’évaluer les VRRAM comme un possible candidat de mémoire non-volatile. Les dispositifs ont démontré une endurance de 107 cycles pour un courant de SET de 300µA, plus de 105s de temps de rétention pour un courant de SET de 100µA à 200 C et un temps de commutation de 20ns. Le courant de SET a été réduit jusqu’à 7µA, les mémoires montrant alors une capacité de commutation. Pour des courants si faibles les tests de data rétention ont démontré que le filament conducteur (CF) n’est pas stable. Les résultats expérimentaux étaient en accord avec ceux obtenus sur une technologie planaire en démontrant que la géométrie verticale n’a pas d’effet majeur sur le fonctionnement des mémoires. Ensuite des mémoires à 2 niveaux ont été fabriquées. Ces dispositifs étaient importants pour faire des tests qui donnaient des informations utiles pour une future intégration à haute densité. Les structures à 2 niveaux ont été comparées en termes de tensions de commutation et de résistance pour vérifier la reproductibilité de la technologie sur les flancs de la structure verticale. Des tests de « disturb » ont été également effectués pour vérifier que le cyclage sur un niveau n’influence pas le niveau non sélectionné. Une autre partie de la thèse était dédiée à l’étude physique du comportement du CF pendant le cyclage. Cette étude a montré qu’il y a une corrélation parmi les résistances pendant le cyclage. Pour expliquer ce phénomène des modèles analytique et physique ont été développés. Les deux modèles sont basés sur l’hypothèse que pendant le cyclage il y a un paramètre qui dépend des valeurs aux cycles précédents. Pour le modèle analytique le paramètre était la résistance même, alors que pour le modèle physique le paramètre était le gap du CF (LGAP). Les deux modèles montrent un bon accord avec les données expérimentales en indiquant que la morphologie du CF à un cycle donné dépend de la morphologie des cycles précédents. Une autre partie du travail était dédiée à l’étude pour les applications haute densité : en partant des résultats électriques sur les dispositifs à 2 niveaux et en supposant avoir un sélecteur intégré, on a calculé la taille maximum des matrices qu’on peut obtenir en fonction des différents paramètres d’intégration. Enfin on a travaillé sur les applications neuromorphiques où un pilier de VRRAM a été proposé comme émulateur de synapse. Les VRRAM peuvent émuler les synapses de 2 manières, soit en utilisant la probabilité intrinsèque des ReRAM ou en programmant chaque cellule du pilier avec un circuit extérieur. / The scope of the thesis was to characterize and help further development of the first LETI-fabricated vertical resistive RAM (VRRAM). Among emerging memories Resistive RAMs (ReRAM) seems promising in terms of scalability, switching speed, fabrication costs and ease of production. As in the case of FLASH devices, which are attaining their physical limits in terms of scalability, resistive memories are already being studied in vertical geometry in order to propose solutions that maximize memory density. This work proceeded as follows: at first 1 Resistor (1R) devices were characterized to gain a general understanding of the memory cells functioning and to perform the first screening in terms of stack composition and thicknesses. Once the best configurations were identified 1 Transistor- 1 Resistor (1T-1R) devices were integrated in order to assess memory performances in an industrial-like fashion. 1R devices were integrated in a MESA structure while 1T-1R devices were integrated in both MESA and VIA architectures. In both architectures the memory cell is found on the sidewall of the structure; particularly challenging was the deposition of the top electrode. Devices were electrically characterized to extract the following information: initial resistance, forming, set and reset voltages, switching times, high and low resistance states (HRS and LRS) resistances, endurance characteristics and data retention times. This set of measurements allowed to extensively study the capability of VRRAM as a non-volatile memory candidate. It was shown that HfO2-based VRRAM have 107 endurance capability for a set current (ISET) of 300 [µA], more than 105 [s] data retention for a SET current of 100 [µA] at 200 [˚C] backing temperature and down to 20 [ns] switching time. ISET was also reduced down to 7 [µA] and memory cell showed switching capability although the conductive filament (CF) resulted unstable after data retention tests. Experimental results obtained were in accordance with previous studies conducted on planar devices showing that vertical geometry did not have a significant effect on memory behavior. Finally 2-level memory devices were fabricated. These samples were really useful to perform important tests for future high density integration: the 2 level devices were compared in terms of switching voltages and resistances to verify the reproducibility of the integration along the sidewall of the structure. Disturb tests were carried out to be sure that write/erase operations on one level did not influence the state of the un-selected level. Another part of the thesis was dedicated to the physical investigation of the conducting filament behavior during cycling. This study showed that a correlation exists among resistances while cycling. In order to explain these measurements both analytical and physical models were proposed. Both rely on the assumption that there is a parameter during cycling that is related to its previous values; in the case of the analytical model this parameter is simply the resistance while in the physical model the parameter is the CF gap (LGAP). Both models show good fit with experimental data suggesting therefore that at any given cycle the morphology of the conductive filament is dependent on the morphology during the previous cycles. Another part of the thesis was also dedicated to a study on high density applications:starting from the electrical results obtained on 2-level VRRAM and supposing to work with an integrated selector the maximum array size attainable was calculated as a function of various parameters such as the node half pitch, the plane thicknesses and the number of integrated levels. Finally neuromorphic applications were investigated and a VRRAM pillar was proposed as a synapse emulator. VRRAMs can act as synapses in two ways: using the intrinsic probability of the ReRAM technology or programming each VRRAM cell in the pillar with a probability given from an external circuit.

Le système nerveux central humain est un système de traitement de l'information stupéfiant en termes de capacités, de polyvalence, d’adaptabilité et de faible consommation d'énergie. Sa structure complexe se compose de milliards de neurones, interconnectés par plusieurs trillions de synapses, formant des grappes spécialisées. Récemment, l'imitation de ces paradigmes a suscité un intérêt croissant en raison de la nécessité d'approches informatiques avancées pour s'attaquer aux défis liés à la génération de quantités massives de données complexes dans l'ère de l’Internet des Objets (IoT). Ceci a mené à un nouveau domaine de recherche, connu sous le nom d’informatique cognitive ou d'ingénierie neuromorphique, qui repose sur les architectures dites non-von-Neumann (inspirées du cerveau) en opposition aux architectures von-Neumann (ordinateurs classiques). Dans cette thèse, nous examinons l'utilisation des technologies de mémoire résistive telles que les mémoires à accès aléatoires à base de lacunes d’oxygène (OxRAM) et les mémoires à pont conducteur (CBRAM) pour la conception de synapses artificielles, composants de base indispensables des réseaux neuromorphiques. De plus, nous développons un réseau de neurones impulsionnels artificiel (SNN), utilisant des synapses OxRAM, pour l'analyse de données impulsionnelles provenant du cerveau humain en vue du traitement de troubles neurologiques, en connectant la sortie du SNN à une interface cerveau-ordinateur (BCI). L'impact des problèmes de fiabilité, caractéristiques des OxRAMs, sur les performances du système est étudié en détail et les moyens possibles pour atténuer les pénalités liées aux incertitudes des dispositifs seuls sont démontrés. En plus de l’implémentation avec des OxRAMs et CBRAMs de la bien connue plasticité fonction du temps d’occurrence des impulsions (STDP), qui constitue une forme de plasticité à long terme (LTP), les dispositifs OxRAM ont également été utilisés pour imiter la plasticité à court terme (STP). Les fonctionnalités fondamentalement différentes de la LTP et STP sont mises en évidence. / The central nervous system of humankind is an astonishing information processing system in terms of its capabilities, versatility, adaptability and low energy consumption. Its complex structure consists of billions of neurons interconnected by trillions of synapses forming specialized clusters. Recently, mimicking those paradigms has attracted a strongly growing interest, triggered by the need for advanced computing approaches to tackle challenges related to the generation of massive amounts of complex data in the Internet of Things (IoT) era. This has led to a new research field, known as cognitive computing or neuromorphic engineering, which relies on the so-called non-von-Neumann architectures (brain-inspired) in contrary to von-Neumann architectures (conventional computers). In this thesis, we explore the use of resistive memory technologies such as oxide vacancy based random access memory (OxRAM) and conductive bridge RAM (CBRAM) for the design of artificial synapses that are a basic building block for neuromorphic networks. Moreover, we develop an artificial spiking neural network (SNN) based on OxRAM synapses dedicated to the analysis of spiking data recorded from the human brain with the goal of using the output of the SNN in a brain-computer interface (BCI) for the treatment of neurological disorders. The impact of reliability issues characteristic to OxRAM on the system performance is studied in detail and potential ways to mitigate penalties related to single device uncertainties are demonstrated. Besides the already well-known spike-timing-dependent plasticity (STDP) implementation with OxRAM and CBRAM which constitutes a form of long term plasticity (LTP), OxRAM devices were also used to mimic short term plasticity (STP). The fundamentally different functionalities of LTP and STP are put in evidence.