abstract: The field of flexible displays and electronics gained a big momentum within the recent years due to their ruggedness, thinness, and flexibility as well as low cost large area manufacturability. Amorphous silicon has been the dominant material used in the thin film transistor industry which could only utilize it as N type thin film transistors (TFT). Amorphous silicon is an unstable material for low temperature manufacturing process and having only one kind of transistor means high power consumption for circuit operations. This thesis covers the three major researches done on flexible TFTs and flexible electronic circuits. First the characterization of both amorphous silicon TFTs and newly emerging mixed oxide TFTs were performed and the stability of these two materials is compared. During the research, both TFTs were stress tested under various biasing conditions and the threshold voltage was extracted to observe the shift in the threshold which shows the degradation of the material. Secondly, the design of the first flexible CMOS TFTs and CMOS gates were covered. The circuits were built using both inorganic and organic components (for nMOS and pMOS transistors respectively) and functionality tests were performed on basic gates like inverter, NAND and NOR gates and the working results are documented. Thirdly, a novel large area sensor structure is demonstrated under the Electronic Textile project section. This project is based on the concept that all the flexible electronics are flexible in only one direction and can not be used for conforming irregular shaped objects or create an electronic cloth for various applications like display or sensing. A laser detector sensor array is designed for proof of concept and is laid in strips that can be cut after manufacturing and weaved to each other to create a real flexible electronic textile. The circuit designed uses a unique architecture that pushes the data in a single line and reads the data from the same line and compares the signal to the original state to determine a sensor excitation. This architecture enables 2 dimensional addressing through an external controller while eliminating the need for 2 dimensional active matrix style electrical connections between the fibers. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

abstract: The work presented in this manuscript has the overarching theme of radiation. The two forms of radiation of interest are neutrons, i.e. nuclear, and electric fields. The ability to detect such forms of radiation have significant security implications that could also be extended to very practical industrial applications. The goal is therefore to detect, and even image, such radiation sources. The method to do so revolved around the concept of building large-area sensor arrays. By covering a large area, we can increase the probability of detection and gather more data to build a more complete and clearer view of the environment. Large-area circuitry can be achieved cost-effectively by leveraging the thin-film transistor process of the display industry. With production of displays increasing with the explosion of mobile devices and continued growth in sales of flat panel monitors and television, the cost to build a unit continues to decrease. Using a thin-film process also allows for flexible electronics, which could be taken advantage of in-house at the Flexible Electronics and Display Center. Flexible electronics implies new form factors and applications that would not otherwise be possible with their single crystal counterparts. To be able to effectively use thin-film technology, novel ways of overcoming the drawbacks of the thin-film process, namely the lower performance scale. The two deliverable devices that underwent development are a preamplifier used in an active pixel sensor for neutron detection and a passive electric field imaging array. This thesis will cover the theory and process behind realizing these devices. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015

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Les réseaux de capteurs corporels représentent un enjeu sociétal important en permettant des soins de meilleure qualité avec un coût réduit. Ces derniers sont utilisés pour détecter des anomalies dès leur apparition et ainsi intervenir au plus vite. Les capteurs sont soumis à de nombreuses contraintes de fiabilité, robustesse, taille et consommation. Dans cette thèse, les différentes opérations réalisées par les réseaux de capteurs corporels sont analysées. La consommation de chacune d'elles est évaluée afin de guider les axes de recherche pour améliorer l'autonomie énergétique des capteurs. Un capteur pour la détection d'arythmie sur des signaux cardiaques est proposé. Il intègre un traitement du signal via l'utilisation d'un réseau de neurone à cliques. Le système proposé est simulé et offre une exactitude de classification de 95 % pour la détection de trois types d'arythmie. Le prototypage du système via la fabrication d'un circuit mixte analogique/numérique en CMOS 65 nm montre une consommation du capteur de l'ordre de 1,4 μJ. Pour réduire encore plus l'énergie, une nouvelle méthode d'acquisition est utilisée. Une architecture de convertisseur est proposée pour l'acquisition et le traitement de signaux cardiaques. Cette dernière laisse espérer une consommation de l'ordre de 1,18 nJ pour acquérir les paramètres tout en offrant une exactitude de classification proche de 98 %. Cette étude permet d'ouvrir la voie vers la mise en place de capteurs très basse consommation pouvant durer toute une vie avec une simple pile. / Body area sensor networks gained great focused through the promiseof better quality and cheaper medical care system. They are used todetect anomalies and treat them as soon as they arise. Sensors are under heavy constraints such as reliability, sturdiness, size and power consumption. This thesis analyzes the operations perform by a body area sensor network. The different energy requirements are evaluated in order to choose the focus of the research to improve the battery life of the sensors. A sensor for arrhythmia detection is proposed. It includes some signal processing through a clique-based neural network. The system simulations allow a classification between three types of arrhythmia with 95 % accuracy. The prototype, based on a 65 nm CMOS mixed signal circuit, requires only 1.4 μJ. To further reduce energy consumption, a new sensing method is used. A converter architecture is proposed for heart beat acquisition. Simulations and estimation show a 1.18 nJ energy requirement for parameter acquisition while offering 98 % classification accuracy. This work leads the way to the development of low energy sensor with a lifetime battery life.