AlGaN/GaN high electron mobility transistors (HEMTs) have appeared as attractive candidates for high power, high frequency, and high temperature operation at microwave frequencies. In particular, these devices are being considered for use in the area of high RF power for microwave and millimeter wave communications transmitter applications at frequencies greater than 100 GHz and at temperatures greater than about 150 °C. However, there are concerns regarding the reliability of AlGaN/GaN HEMTs. First of all, thermal reliability is the chief concern since high channel temperatures significantly affect the lifetime of the devices. Therefore, it is necessary to find the solutions to decrease the temperature of AlGaN/GaN HEMTs. In this study, we explored the methods to reduce the channel temperature via high thermal conductivity diamond as substrates of GaN. Experimental verification of AlGaN/GaN HEMTs on diamond substrates was performed using micro-Raman spectroscopy, and investigation of the design space for devices was conducted using finite element analysis as well. In addition to the thermal impact on reliability, environmental effects can also play a role in device degradation. Using high density and pinhole free films deposited using atomic layer deposition, we also explore the use of ultra-thin barrier films for the protection of AlGaN/GaN HEMTs in high humidity and high temperature environments. The results show that it is possible to protect the devices from the effects of moisture under high negative gate bias stress testing, whereas devices, which were unprotected, failed under the same bias stress conditions. Thus, the use of the atomic layer deposition (ALD) coatings may provide added benefits in the protection and packaging of AlGaN/GaN HEMTs.

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Submitted by Karlla Delalibera Chagas null (karlladelalibera@gmail.com) on 2018-05-14T12:25:13Z No. of bitstreams: 1 dissertação - Karlla Delalibera.pdf: 2936984 bytes, checksum: 3d99ddd54b4c7d3230e5de9070915594 (MD5) / Approved for entry into archive by Claudia Adriana Spindola null (claudia@fct.unesp.br) on 2018-05-14T12:53:09Z (GMT) No. of bitstreams: 1 chagas_kd_me_prud.pdf: 2936984 bytes, checksum: 3d99ddd54b4c7d3230e5de9070915594 (MD5) / Made available in DSpace on 2018-05-14T12:53:09Z (GMT). No. of bitstreams: 1 chagas_kd_me_prud.pdf: 2936984 bytes, checksum: 3d99ddd54b4c7d3230e5de9070915594 (MD5) Previous issue date: 2018-04-16 / Pró-Reitoria de Pós-Graduação (PROPG UNESP) / Neste trabalho iremos realizar uma abordagem sobre a modelagem de dados que advém de um teste acelerado. Consideraremos o caso em que a carga de estresse aplicada foi do tipo "step-stress". Para a modelagem, utilizaremos os modelos step-stress simples e múltiplo sob censura tipo II e censura progressiva tipo II, e iremos supor que os tempos de vida dos itens em teste seguem uma distribuição Gama. Além disso, também será utilizado o modelo step-stress simples sob censura tipo II considerando a presença de riscos competitivos. Será realizada uma abordagem clássica, por meio do método de máxima verossimilhança e uma abordagem Bayesiana usando prioris não-informativas, para estimar os parâmetros dos modelos. Temos como objetivo realizar a comparação dessas duas abordagens por meio de simulações para diferentes tamanhos amostrais e utilizando diferentes funções de perda (Erro Quadrático, Linex, Entropia), e através de estatísticas verificaremos qual desses métodos se aproxima mais dos verdadeiros valores dos parâmetros. / In this work, we will perform an approach to data modeling that comes from an accelerated test. We will consider the case where the stress load applied was of the step-stress type. For the modeling, we will use the simple and multiple step-stress models under censorship type II and progressive censorship type II, and we will assume that the lifetimes of the items under test follow a Gamma distribution. In addition, the simple step-stress model under censorship type II will also be used considering the presence of competitive risks. A classical approach will be performed, using the maximum likelihood method and a Bayesian approach using non-informative prioris, to estimate the parameters of the models. We aim to compare these two approaches by simulations for different sample sizes and using different loss functions (Quadratic Error, Linex, Entropy), and through statistics, we will check which of these approaches is closer to the true values of the parameters.

Ce travail de thèse se concentre sur l'évaluation de la fiabilité des transistors à haute mobilité électronique (HEMT) AlGaN / GaN à grille ultra-courte sur substrat silicium dédiés aux applications de puissance à une fréquence supérieure à 40GHz. Il a été réalisé au sein des laboratoires IMS Bordeaux et IEMN Lille.Ce travail compare initialement les HEMT AlGaN / GaN réalisés par croissance MOCVD avec ceux obtenus par croissance MBE. En particulier, l'analyse électrique statique a permis d'étudier l'influence de la géométrie des dispositifs sur les performances des composants.Des tests de vieillissement accéléré ont été effectués pour évaluer la robustesse des transistors HEMTs en AlGaN/GaN à grille ultra-courte sur Si. Une méthodologie basée sur une séquence d'essais de vieillissement a été définie pour établir le diagnostic in-situ d’une dégradation statique et permanente et d’une dégradation qui se traduit par un transitoire de courant de drain au cours du chaque palier de la séquence de vieillissement. La valeur de la tension critique de dégradation à partir de laquelle le courant de drain commence à diminuer de façon significative dépend des conditions de polarisation du vieillissement, de la distance grille-drain et de la longueur de grille. De plus, l’aire de sécurité de fonctionnement de cette technologie a été déterminée. / This Ph.D. work focuses on the reliability assessment of ultra-short gate AlGaN/GaN high electron mobility transistor (HEMT) on silicon substrate dedicated to power applications at frequency above 40GHz. It was carried out within IMS Bordeaux and IEMN Lille laboratories.This work initially compares AlGaN/GaN HEMTs grown by MOCVD with those grown using MBE, through electrical characterization.In particular, the device geometry impact on the device performances has been studies by static electrical characterization.Step-stress experiments are performed to investigate reliability assessment of ultra-short gate AlGaN/GaN high electron mobility transistor (HEMT) on Si substrate. A methodology based on a sequence of step stress tests has been defined for in-situ diagnosis of a permanent degradation and of a degradation which is identified by a drain current transient occurring during each step of the ageing sequence . The same stress conditions were applied on HEMTs with different geometries. It is found no evolution of the drain current during non stressful steps. The value of the critical degradation voltage beyond which the stress drain current starts to decrease significantly is also found dependent on the stress bias conditions, the gate-drain distance and the gate length. Moreover, the safe operating area of this technology has been determined.

Researchers conduct life testing on objects of interest in an attempt to determine their life distribution as a means of studying their reliability (or survivability). Determining the life distribution of the objects under study helps manufacturers to identify potential faults, and to improve quality. Researchers sometimes conduct accelerated life tests (ALTs) to ensure that failure among the tested units is earlier than what could result under normal operating (or environmental) conditions. Moreover, such experiments allow the experimenters to examine the effects of high levels of one or more stress factors on the lifetimes of experimental units. Examples of stress factors include, but not limited to, cycling rate, dosage, humidity, load, pressure, temperature, vibration, voltage, etc. A special class of ALT is step-stress accelerated life testing. In this type of experiments, the study sample is tested at initial stresses for a given period of time. Afterwards, the levels of the stress factors are increased in agreement with prefixed points of time called stress-change times. In practice, time and resources are limited; thus, any experiment is expected to be constrained to a deadline which is called a termination time. Hence, the observed information may be subjected to Type-I censoring. This study discusses maximum likelihood inferential methods for the parameters of multiple step-stress models from a generalized Birnbaum-Saunders distribution under time constraint alongside other inference-related problems. A couple of general inference frameworks are studied; namely, the observed likelihood (OL) framework, and the expectation-maximization (EM) framework. The last-mentioned framework is considered since there is a possibility that Type-I censored data are obtained. In the first framework, the scoring algorithm is used to get the maximum likelihood estimators (MLEs) for the model parameters. In the second framework, EM-based algorithms are utilized to determine the required MLEs. Obtaining observed information matrices under both frameworks is also discussed. Accordingly, asymptotic and bootstrap-based interval estimators for the model parameters are derived. Model discrimination within the considered generalized Birnbaum-Saunders distribution is carried out by likelihood ratio test as well as by information-based criteria. The discussed step-stress models are illustrated by analyzing three real-life datasets. Accordingly, establishing optimal multiple step-stress test plans based on cost considerations and three optimality criteria is discussed. Since maximum likelihood estimators are obtained by numerical optimization that involves maximizing some objective functions, optimization methods used, and their software implementations in R are discussed. Because of the computational aspects are in focus in this study, the benefits of parallel computing in R, as a high-performance computational approach, are briefly addressed. Numerical examples and Monte Carlo simulations are used to illustrate and to evaluate the methods presented in this thesis. / Thesis / Doctor of Science (PhD)

In this thesis, we investigate several inferential issues regarding the lifetime data from exponential distribution under different censoring schemes. For reasons of time constraint and cost reduction, censored sampling is commonly employed in practice, especially in reliability engineering. Among various censoring schemes, progressive Type-I censoring provides not only the practical advantage of known termination time but also greater flexibility to the experimenter in the design stage by allowing for the removal of test units at non-terminal time points. Hence, we first consider the inference for a progressively Type-I censored life-testing experiment with k uniformly spaced intervals. For small to moderate sample sizes, a practical modification is proposed to the censoring scheme in order to guarantee a feasible life-test under progressive Type-I censoring. Under this setup, we obtain the maximum likelihood estimator (MLE) of the unknown mean parameter and derive the exact sampling distribution of the MLE through the use of conditional moment generating function under the condition that the existence of the MLE is ensured. Using the exact distribution of the MLE as well as its asymptotic distribution and the parametric bootstrap method, we discuss the construction of confidence intervals for the mean parameter and their performance is then assessed through Monte Carlo simulations. Next, we consider a special class of accelerated life tests, known as step-stress tests in reliability testing. In a step-stress test, the stress levels increase discretely at pre-fixed time points and this allows the experimenter to obtain information on the parameters of the lifetime distributions more quickly than under normal operating conditions. Here, we consider a k-step-stress accelerated life testing experiment with an equal step duration τ. In particular, the case of progressively Type-I censored data with a single stress variable is investigated. For small to moderate sample sizes, we introduce another practical modification to the model for a feasible k-step-stress test under progressive censoring, and the optimal τ is searched using the modified model. Next, we seek the optimal τ under the condition that the step-stress test proceeds to the k-th stress level, and the efficiency of this conditional inference is compared to the preceding models. In all cases, censoring is allowed at each change stress point iτ, i = 1, 2, ... , k, and the problem of selecting the optimal Tis discussed using C-optimality, D-optimality, and A-optimality criteria. Moreover, when a test unit fails, there are often more than one fatal cause for the failure, such as mechanical or electrical. Thus, we also consider the simple stepstress models under Type-I and Type-II censoring situations when the lifetime distributions corresponding to the different risk factors are independently exponentially distributed. Under this setup, we derive the MLEs of the unknown mean parameters of the different causes under the assumption of a cumulative exposure model. The exact distributions of the MLEs of the parameters are then derived through the use of conditional moment generating functions. Using these exact distributions as well as the asymptotic distributions and the parametric bootstrap method, we discuss the construction of confidence intervals for the parameters and then assess their performance through Monte Carlo simulations. / Thesis / Doctor of Philosophy (PhD)