<p dir="ltr">Rapid evolution in wireless technology and the increasing demand for high bandwidth communication for 5G/6G and the Internet of Things (IoT) have necessitated a growing number of components in radio front-end modules in an increasingly overcrowded radio frequency (RF) spectrum. Low-cost ad-hoc radios have drawn consumer interest, enabling new devices like microelectromechanical (MEMS) resonators for on-chip clocking, frequency-selective filters, RF signal processing, and spectral sensing for their small footprint and low power consumption. Gallium nitride (GaN) is an attractive electromechanical material due to its high coupling coefficient, acoustic velocity, and low viscoelastic losses. These benefits enable high-Q MEMS resonators in GaN monolithic microwave integrated circuits (MMICs) with scaling capability up to mm-wave frequencies, making this technology platform a contender for high-performance programmable radios in RF/mm-wave, sensors for harsh environments, and information processing in quantum systems.</p><p dir="ltr">The bias-dependent control mechanism of the 2D electron gas (2DEG) in GaN heterostructures can be exploited to design different switchable and tunable devices for reconfigurable MEMS components. This work presents, for the first time, a comprehensive study of the electromechanical performances of different transduction mechanisms in switchable GaN MEMS resonators. A unique OFF-state shunt design, where the 2DEG in an AlN/GaN heterostructure is utilized to control electromechanical transduction in Lamb mode resonators, is also experimentally demonstrated in this work. To make a valid comparison among switchable transducers, equivalent circuit models are developed to extract key parameters from the measurements by fitting them in both ON and OFF states. The switchable transducer with Ohmic interdigitated transducers (IDTs) and Schottky control gate shows superior performance among the designs under consideration with complete suppression of the mechanical mode in the OFF state and a maximum frequency-quality factor product of 5x10¹²s^-1 and a figure-of-merit of 5.18 at 1GHz in the ON state.</p><p dir="ltr">Over the past few years, there have been numerous efforts to scale the frequencies of MEMS devices in the GaN platform towards mm-wave frequencies. However, challenges remain due to the multi-layer thick buffer, typical in the growth of GaN epilayer on a substrate. This work presents the investigation of SweGaN QuanFINEbuffer-free and ultrathin GaN-on-SiC for the performance of surface acoustic wave (SAW) devices beyond 10GHz. Finite element analysis (FEA) is performed to find the range of frequencies for the Sezawa mode in the structure. Transmission lines and resonators are designed, fabricated, and characterized. Modified Mason circuit models are developed for each class of devices to extract critical performance metrics and benchmark with the state-of-the-art and theoretical limits for GaN. Sezawa modes are observed at frequencies up to 14.3GHz, achieving a record high in GaN MEMS to the best of our knowledge. A maximum piezoelectric coupling of 0.61% and frequency-quality factor product of 6x10¹²s^-1 are achieved for Sezawa resonators at 11GHz, with a minimum propagation loss of 0.26dB/λ for the two-port devices. The devices also exhibit high linearity with input third-order intercept points (IIP3) of 65dBm at 9GHz.</p><p dir="ltr">This work also investigates tunable acoustoelectric (AE) devices in the QuanFINE platform, leveraging its inherent 2DEG in the AlGaN/GaN heterostructure. Using 9.7GHz Sezawa mode acoustic delay lines, we report the highest frequency of AE in GaN to date. Active and passive AE devices are designed for voltage-dependent non-reciprocity and propagation loss without modification to the standard process for the High Electron Mobility Transistors (HEMTs) in MMICs. Drain/source Ohmic contacts control the drift velocity of the 2DEG, and the Schottky gate modulates 2DEG carrier concentration, resulting in a 30dB/cm separation between forward and reverse acoustic waves for a 2.56kV/cm lateral DC electric field and a maximum change in propagation loss of 50dB/cm for -5V DC at the control gate, respectively. The QuanFINEtechnology with AlGaN/GaN heterostructure enables a platform for switchable MEMS resonators and tunable acoustoelectric devices in MMICs for reconfigurable front end approaching mm-wave frequencies.</p>

Developments in computer vision has sought to design deep neural networks which trained on a large set of images are able to generate high quality artificial images which share semantic qualities with the original image set. A pivotal shift was made with the introduction of the generative adversarial network (GAN) by Goodfellow et al.. Building on the work by Goodfellow more advanced models using the same idea have shown great improvements in terms of both image quality and data diversity. GAN models generate images by feeding samples from a vector space into a generative neural network. The structure of these so called latent vector samples show to correspond to semantic similarities of their corresponding generated images. In this thesis the DCGAN model is trained on a novel data set consisting of image sequences of the growth process of basil plants from germination to harvest. We evaluate the trained model by comparing the DCGAN performance on benchmark data sets such as MNIST and CIFAR10 and conclude that the model trained on the basil plant data set achieved similar results compared to the MNIST data set and better results in comparison to the CIFAR10 data set. To argue for the potential of using more advanced GAN models we compare the results from the DCGAN model with the contemporary StyleGAN2 model. We also investigate the latent vector space produced by the DCGAN model and confirm that in accordance with previous research, namely that the DCGAN model is able to generate a latent space with data specific semantic structures. For the DCGAN model trained on the data set of basil plants, the latent space is able to distinguish between images of early stage basil plants from late stage plants in the growth phase. Furthermore, utilizing the sequential semantics of the basil plant data set, an attempt at generating an artificial growth sequence is made using linear interpolation. Finally we present an unsuccessful attempt at visualising the latent space produced by the DCGAN model using a rudimentary approach at inverting the generator network function. / Utvecklingen inom datorseende har syftat till att utforma djupa neurala nätverk som tränas på en stor mängd bilder och kan generera konstgjorda bilder av hög kvalitet med samma semantiska egenskaper som de ursprungliga bilderna. Ett avgörande skifte skedde när Goodfellow et al. introducerade det generativa adversariella nätverket (GAN). Med utgångspunkt i Goodfellows arbete har flera mer avancerade modeller som använder samma idé uppvisat stora förbättringar när det gäller både bildkvalitet och datamångfald. GAN-modeller genererar bilder genom att mata in vektorer från ett vektorrum till ett generativt neuralt nätverk. Strukturen hos dessa så kallade latenta vektorer visar sig motsvara semantiska likheter mellan motsvarande genererade bilder. I detta examensarbete har DCGAN-modellen tränats på en ny datamängd som består av bildsekvenser av basilikaplantors tillväxtprocess från groning till skörd. Vi utvärderar den tränade modellen genom att jämföra DCGAN-modellen mot referensdataset som MNIST och CIFAR10 och drar slutsatsen att DCGAN tränad på datasetet för basilikaväxter uppnår liknande resultat jämfört med MNIST-dataset och bättre resultat jämfört med CIFAR10-datasetet. För att påvisa potentialen av att använda mer avancerade GAN-modeller jämförs resultaten från DCGAN-modellen med den mer avancerade StyleGAN2-modellen. Vi undersöker också det latenta vektorrum som produceras av DCGAN-modellen och bekräftar att DCGAN-modellen i enlighet med tidigare forskning kan generera ett latent rum med dataspecifika semantiska strukturer. För DCGAN-modellen som tränats på datamängden med basilikaplantor lyckas det latenta rummet skilja mellan bilder av basilikaplantor i tidiga stadier och sena stadier av plantor i tillväxtprocessen. Med hjälp av den sekventiella semantiken i datamängden för basilikaväxter gjörs dessutom ett försök att generera en artificiell tillväxtsekvens med hjälp av linjär interpolation. Slutligen presenterar vi ett misslyckat försök att visualisera det latenta rummet som produceras av DCGAN-modellen med hjälp av ett rudimentärt tillvägagångssätt för att invertera den generativa nätverksfunktionen.

In this report the influence of the growth conditions on the surface morphology of AlGaN/GaN heterostructures grown on sapphire-based and bulk GaN substrates is nondestructively investigated with focus on the decoration of defects and the surface roughness. Under Ga-rich conditions specific types of dislocations are unintentionally decorated with shallow hillocks. In contrast, under Ga-lean conditions deep pits are inherently formed at these defect sites. The structural data show that the dislocation density of the substrate sets the limit for the density of dislocation-mediated surface structures after MBE overgrowth and no noticeable amount of surface defects is introduced during the MBE procedure. Moreover, the transfer of crystallographic information, e.g. the miscut of the substrate to the overgrown structure, is confirmed. The combination of our MBE overgrowth with the employed surface morphology analysis by atomic force microscopy (AFM) provides a unique possibility for a nondestructive, retrospective analysis of the original substrate defect density prior to device processing.

Recently, a variety of machine learning techniques have been applied to different healthcare sectors, and the results appear to be promising. One such sector is healthcare planning, in which patient data is used to produce statistical models for predicting the load on different units of the healthcare system. This research introduces an attempt to design and implement a privacy-preserving synthetic data generation method adapted explicitly to patients’ health data and for healthcare planning. A Privacy-preserving Conditional Generative Adversarial Network (PPCGAN) is used to generate synthetic data of Healthcare events, where a well-designed noise is added to the gradients in the training process. The concept of differential privacy is used to ensure that adversaries cannot reveal the exact training samples from the trained model. Notably, the goal is to produce digital patients and model their journey through the healthcare system. / Nyligen har en mängd olika maskininlärningstekniker tillämpats på olika hälso- och sjukvårdssektorer, och resultaten verkar lovande. En sådan sektor är vårdplanering, där patientdata används för att ta fram statistiska modeller för att förutsäga belastningen på olika enheter i sjukvården. Denna forskning introducerar ett försök att utforma och implementera en sekretessbevarande syntetisk datagenereringsmetod som uttryckligen anpassas till patienters hälsodata och för vårdplanering. Ett sekretessbevarande villkorligt generativt kontradiktoriskt nätverk (PPCGAN) används för att generera syntetisk data från hälsovårdshändelser, där ett väl utformat brus läggs till gradienterna i träningsprocessen. Begreppet differentiell integritet används för att säkerställa att motståndare inte kan avslöja de exakta träningsproven från den tränade modellen. Målet är särskilt att producera digitala patienter och modellera deras resa genom sjukvården.

The incorporation of Gallium Nitride (GaN) Power Amplifiers (PAs) into future high power aperture radar systems is certain; however, the introduction of this technology into multifunction radar systems will present new challenges to radar engineers. This dissertation describes a broad investigation into amplitude and phase transients produced by GaN PAs when they are excited with multifunction radar waveforms. These transients are the result of self-heating electrothermal memory effects and are manifested as interpulse instabilities that can negatively impact the coherent processing of multiple pulses. A behavioral model based on a Foster network topology has been developed to replicate the measured amplitude and phase transients accurately. This model has been used to develop a digital predistortion technique that successfully mitigates the impact of the transients. The Moving Target Indicator (MTI) Improvement Factor and the Root Mean Square (RMS) Pulse-to-Pulse Stability are used as metrics to assess the impact of the transients on radar system performance and to test the effectiveness of a novel digital predistortion concept. / Ph. D.

Doctor of Philosophy / Department of Physics / Jingyu Lin / Time-resolved deep ultraviolet (DUV) Photoluminescence (PL) spectroscopy system has been employed to systematically monitor crystalline quality, identify the defects and impurities, and investigate the light emission mechanism in III-nitride semiconducting materials and photonic structures. A time correlated single photon counting system and streak camera with corresponding time resolutions of 20 and 2 ps, respectively, were utilized to study the carrier excitation and recombination dynamics. A closed cycle He-flow cryogenic system was employed for temperature dependent measurements. This system is able to handle sample temperatures in a wide range (from 10 to 900 K). Structural, electrical, and morphological properties of the material were monitored by x-ray diffraction (XRD), Hall-effect measurement, and atomic force microscopy (AFM), respectively. Most of the samples studied here were synthesized in our laboratory by metal organic chemical vapor deposition (MOCVD). Some samples were bulk AlN synthesized by our collaborators, which were also employed as substrates for homoepilayer growth. High quality AlN epilayers with (0002) XRD linewidth as narrow as 50 arcsec and screw type dislocation density as low as 5x10[superscript]6 cm[superscript]-2 were grown on sapphire substrates. Free exciton transitions related to all valence bands (A, B, and C) were observed in AlN directly by PL, which allowed the evaluation of crystal field (Δ[subscript]CF) and spin-orbit (Δ[subscript]SO) splitting parameters exerimentally. Large negative Δ[subscript]CF and, consequently, the difficulties of light extraction from AlN and Al-rich AlGaN based emitters due to their unique optical polarization properties have been further confirmed with these new experimental data. Due to the ionic nature of III-nitrides, exciton-LO phonon Frohlich interaction is strong in these materials, which is manifested by the appearance of phonon replicas accompanying the excitonic emission lines in their PL spectra. The strength of the exciton-phonon interactions in AlN has been investigated by measuring the Huang-Rhys factor. It compares the intensity of the zero phonon (exciton emission) line relative to its phonon replica. AlN bulk single crystals, being promising native substrate for growing nitride based high quality device structures with much lower dislocation densities (<10[superscript]4 cm[superscript]-2), are also expected to be transparent in visible to UV region. However, available bulk AlN crystals always appear with an undesirable yellow or dark color. The mechanism of such undesired coloration has been investigated. MOCVD was utilized to deposit ~0.5 μm thick AlN layer on top of bulk crystal. The band gap of strain free AlN homoepilayers was 6.100 eV, which is ~30 meV lower compared to hetero-epitaxial layers on sapphire possessing compressive strain. Impurity incorporation was much lower in non-polar m-plane growth mode and the detected PL signal at 10 K was about an order of magnitude higher from a-plane homo-epilayers compared to that from polar c-plane epilayers. The feasibility of using Be as an alternate p-type dopant in AlN has been studied. Preliminary studies indicate that the Be acceptor level in AlN is ~330 meV, which is about 200 meV shallower than the Mg level in AlN. Understanding the optical and electronic properties of native point defects is the key to achieving good quality material and improving overall device performance. A more complete picture of optical transitions in AlN and GaN has been reported, which supplements the understanding of impurity transitions in AlGaN alloys described in previous reports.

Le nitrure de gallium (GaN) est un matériau en plein essor depuis le début des années 1990 pour des applications dans le domaine de l'optoélectronique telles que les diodes électroluminescentes (DELs) bleues ou blanches, les diodes lasers (DLs) bleues ou les détecteurs ultra-violets. L'activité épitaxie de GaN par la technique de croissance HVPE (Epitaxie en phase vapeur par la méthode aux hydrures), a vu le jour au LASMEA en 1998. Les premières études expérimentales et de modélisation réalisées sur des échantillons de faibles dimensions (surface d'environ 1 à 3 cm2) ont conduit à la mise en évidence des mécanismes de croissance et à la maîtrise du procédé. Le développement de ce matériau à l'échelle industrielle a nécessité de travailler sur des surfaces de dimension plus grandes de l'ordre de deux pouces. Un nouveau dispositif expérimantal HVPE a été conçu dans ce sens, mis en place au sein du laboratoire et le procédé a été validé. De nouvelles investigations ont été menées sur l'étude de l'épitaxie sélective de GaN pour la réalisation de structures périodiques de faible dimensionnalité à morphologies contrôlées. Des structures de morphologies poutres et pyramidales de GaN de 1 à 2 µm de large ont ainsi pu être épitaxiées par la technique HVPE. Une analyse systématique de la variation des conditions de croissance est effectuée, visant à maîtriser l'ensemble des paramètres qui influent sur les morphologies et les dimensions des structures. Cette étude est couplée à la compréhension des mécanismes de croissance mis en jeu au cours de l'épitaxie sélective de GaN.

Dans le domaine des semi-conducteurs, la technologie silicium (principalement l’architecture CMOS) répond à la majorité des besoins du marché et, de ce fait, elle est abondamment utilisée. Ce semi-conducteur profite d’une part, de son abondance dans la nature et par conséquent de son faible coût, et d’autre part de la grande maturité de sa technologie qui est étudiée depuis un demi-siècle. Cependant, le silicium (Si) souffre de plus en plus de ses propriétés électriques limitées qui l’excluent de certains domaines dans lesquels les technologies à base de matériaux III-V sont les plus utilisées. Bien que la technologie à base de matériaux III-V, notamment les hétérostructures à base de nitrure de gallium (GaN), soit très performante par rapport à celle à base du matériau historique (le silicium), cette nouvelle technologie est toujours limitée aux applications utilisant des circuits de moyennes voire faibles densités d’intégration. Ceci limite l’utilisation de cette technologie pour la réalisation de produits à très grande valeur ajoutée. Pour s’affranchir de cette limitation, plusieurs sujets de recherche ont été entrepris ces dernières années pour intégrer au sein du même circuit des composants à base de silicium et de matériaux III-V. En effet, la possibilité d’allier les bonnes performances dynamiques de la filière GaN/III-V et la grande densité d’intégration de la technologie Si dans le même circuit constitue une avancée importante avec un potentiel d’impact majeur pour ces deux filières technologiques. L’objectif ciblé par cette nouvelle technologie est la réalisation, sur substrat Si, d’un circuit à base d’hétérostructures GaN de haute performance assurant entre autres, la détection ou l’amplification du signal via des composants III-V tandis que la partie traitement du signal sera réalisée par les circuits CMOS Si. Ce projet de recherche de doctorat s’inscrit directement dans le cadre de l’intégration monolithique d’une technologie HEMT (High Electron Mobility Transistor) à base de matériaux GaN sur CMOS. L’objectif est de développer des architectures compatibles avec la stratégie d’intégration monolithique de transistors HEMTs GaN sur Si, en prenant en compte les exigences des différentes filières, circuits CMOS et croissance/fabrication de structures HEMTs GaN.

Le domaine du spectre électromagnétique correspondant aux fréquences térahertz est encore peu exploité, pourtant, les applications nécessitant la génération, l’amplification ou la détection d’un signal térahertz sont nombreuses et intéressantes. Dans ce travail, nous nous intéressons tout particulièrement au détecteurs plasmoniques, qui constituent une alternative prometteuse à la montée en fréquence des capteurs électroniques et à l’utilisation de capteurs thermiques pour les photons de faible énergie. Les capteurs plasmoniques fonctionnent grâce au couplage entre le photon térahertz et un plasmon au sein d’un gaz d’électrons bidimensionnel (2DEG). Le plasmon-polariton est ensuite transformé en un signal continu et détectable. Nous utilisons pour cela le 2DEG présent dans l’hétérostructure AlGaN/GaN. Le couplage entre le photon et le plasmon-polariton est réalisé par un réseau métallique déposé sur la structure semi-conductrice. Tout d’abord, l’étude du couplage photon/plasmon par des simulations électromagnétiques nous a permis de connaître les fréquences de résonance des plasmons-polaritons en fonction des dimensions du réseau. Le motif de réseau composé de deux bandes de métal de largeurs différentes a été plus particulièrement étudié. Ce motif permettant aux détecteurs d’atteindre une très haute sensibilité [Coquillat et al., 2010] et n’avait pas encore été étudié du point de vue de son efficacité de couplage. Des détecteurs, dimensionnés pour notre montage de test à 0,65 THz, ont ensuite été fabriqués puis mesurés avec un réseau non-polarisé, à température ambiante et refroidis à l’azote. La correspondance entre la variation de la sensibilité en fonction de la fréquence et les spectres d’absorption mesurés au spectromètre infrarouge à transformée de Fourier (FTIR) montre l’importance de l’étape de couplage dans le processus de détection. Contrôler la densité électronique dans le 2DEG permet de modifier la fréquence de résonance des plasmons-polaritons et d’augmenter la sensibilité des détecteurs. Nous avons mené des développements technologiques de manière à pouvoir contrôler la densité électronique du 2DEG en appliquant une tension sur le réseau. Cette étape constitue un défi technologique compte tenu de la surface très étendue des réseaux (plusieurs mm²). Nous avons finalement fabriqué des détecteurs pour lesquels la fréquence de résonance de couplage peut être contrôlée grâce à la tension appliquée sur le réseau. / Abstract: The objectives of this thesis were the fabrication, the measurement and the study of gallium nitride THz detectors. These detectors are working as follows : first the incident THz photon is coupled to a plasmon in the quantum well at the interface AlGaN/GaN. This plasmon is then turned into a continuous measurable current. One of the key-components in this type of detectors is the grating coupling the incident photon and the plasmon. Electromagnetic simulations have been made to determine the dimensions of the grating depending on the detection frequency. Detectors were then fabricated using the precendently calculated grating patterns. Their working frequency depending on their dimensions were measured with a good agreement with the previously led simulations. The grating is not used only as coupling element, but can be used to monitor the electron density in the quatum well as well, what should allow an exaltation of the rectification phenomenon and a frequency tunability. A technological development was needed to achieve grating actually monitoring the electron density over a wide range. It was a real challenge to fabricate such wide grating (36 mm²) with such small periods (about one micrometer) using epitaxies developped for devices with a much smaller area.

In this dissertation, I present that at a vacuum of 3×10-7 Torr, residual O2, CO2, H2 and Ar exposure do not significantly degrade the field emission (FE) properties of ZnO nanorods, but N2 exposure significantly does. I propose that this could be due to the dissociation of N2 into atomic nitrogen species and the reaction of such species with ZnO. I also present the effects of O2, CO2, H2O, N2, H2, and Ar residual gas exposure on the FE properties of GaN and ZnS nanostructure. A brief review of growth of ZnO, GaN and ZnS is provided. In addition, Cs deposition on GaN nanostructures at ultra-high vacuum results in 30% decrease in turn-on voltage and 60% in work function. The improvement in FE properties could be due to a Cs-induced space-charge layer at the surface that reduces the barrier for FE and lowers the work function. I describe a new phenomenon, in which the resistivity of CVD-grown graphene increases to a higher saturated value under light exposure, and depends on the wavelength of the light—the shorter the wavelength, the higher the resistivity. First-principle calculations and theoretical analysis based on density functional theory show that (1) a water molecule close to a graphene defect is easier to be split than that of the case of no defect existing and (2) there are a series of meta-stable partially disassociated states for an interfacial water molecule. Calculated disassociation energies are from 2.5 eV to 4.6 eV, that match the experimental observation range of light wavelength from visible to 254 nm UV light under which the resistivity of CVD-grown graphene is increased.