Gallium Nitride (GaN) high electron mobility transistors (HEMT) have superior performance characteristics compared to Silicon (Si) and Gallium Arsenide (GaAs) based transistors. GaN is a wide bandgap semiconductor which allows it to operate at higher breakdown voltages and power. Unlike traditional semiconductor devices, the GaN HEMT channel region is undoped and relies on the piezoelectric effect created at the GaN and Aluminum Gallium Nitride (AlGaN) heterojunction to create a conduction channel in the form of a quantum well known as the two dimensional electron gas (2DEG). Because the GaN HEMTs are undoped, these devices have higher electron mobility crucial for high frequency operation. However, over time and use these devices degrade in a manner that is not well understood. This research utilizes low frequency noise (LFN) as a method for analyzing changes and degradation mechanisms in GaN-on-Si devices due to gate stress. LFN is a useful tool for probing different regions of the device that cannot be measured through direct means. LFN generation in GaN HEMTs is based on the carrier fluctuation theory of 1/f noise generation which states fluctuations in the number of charge carriers results in conductance fluctuations that produce a Lorentzian noise spectrum. The summing Lorentzian noise spectra from multiple traps leads to 1/f and random telegraph signal (RTS) noise. The primary cause of carrier fluctuations are electron traps near the 2DEG and in the AlGaN bulk. These traps occur naturally due to dislocations and impurities in the manufacturing process, but new traps can be generated by the inverse-piezoelectric effect during gate stress. This thesis introduces noise and presents a circuit to bias the devices and measure gate and drain LFN simultaneously. Three measurements are performed before and after gate DC stress at three different temperatures: DC characterization, capacitance-voltage (C-V) measurements, and LFN measurements. The DC characteristics show an increase in gate leakage after stress caused by an increase in traps after degradation consistent with trap assisted tunneling. However, the leakage current on the drain and source side differ before and after stress leading to the conclusion that the source side of the gate is more sensitive to gate stress. Gate leakage current on the drain side is also sensitive to temperature due to thermionic trap assisted tunneling. Hooge parameter calculations agree with previous research. The LFN results show an increase in gate and drain noise power, SIg(f) and SId(f), in accordance with increased gate leakage current under cutoff bias. RTS noise is also observed to increase in frequency with increased temperature. Activation energies for RTS noise are extracted and qualitatively linked to trap depth based on the McWhorter trap model.

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"L’industrie nano repousse constamment les limites de la miniaturisation. Pour les systèmes CMOS à mémoires non-volatiles, des phénomènes qui étaient négligeables autrefois sont à présent incontournables et nécessitent des modèles de plus en plus complexes pour décrire, analyser et prédire le comportement électrique de ces dispositifs.Le but de cette thèse est de répondre aux besoins de l’industriel, afin d’optimiser au mieux les performances des produits avant et après les étapes de production. Cette étude propose des solutions, comme des méthodes de test innovantes pour des technologies telles que les mémoires non-volatiles EEPROM embarquées.La première méthode proposée, consiste à extraire la densité de pièges (NiT) générée, au cours du cyclage, dans l’oxyde tunnel de cellules EEPROM, à partir d’une Macro cellule de test reprenant toutes les caractéristiques d’un produit fini. Les résultats expérimentaux sont ensuite injectés dans un modèle analytique décrivant le phénomène de SILC (Stress Induced Leakage Current) qui est le principal effet issu de ces pièges. La densité de pièges en fonction du nombre de cycles est ensuite extraite par interpolation entre les courbes expérimentales et les courbes simulées par le modèleLa seconde méthode propose une étude de corrélation statistique entre le test traditionnel de mise en rétention et le test de stress électrique aux bornes de l’oxyde tunnel, proposant des temps d’exécution bien plus courts. Cette étude se base sur les populations de cellules défaillantes à l’issue des deux tests. C’est en comparant les distributions sur ces populations qu’une loi de corrélation apparaît sur la tendance comportementale des cellules." / The nano industry constantly extends the size limits, especially for CMOS devices with embedded non-volatile memories. Each size reduction step always induces new challenges caused by phenomenon which were previously negligible. As a result, more complex models are required to describe, analyze and predict as well as possible the electrical behaviors. The main goal of this thesis is to propose solutions to the industry in term of test, to optimize the performances before and after the whole process steps. Thus, this study proposes two innovative methodologies dedicated to embedded non-volatile EEPROM memories based devices.The first of them consists in to extract the post-cycling generated tunnel oxide traps density (NiT), directly from a macro cell. The experimental results are then used to be compared with an analytical model calculation which perfectly describes the Stress Induced Current phenomena (SILC). This electrical current directly comes from the generated traps inside the cells tunnel oxide. An interpolation is then done between the model and the experimental resulting curves, to extract the tunnel oxide traps density.The second study proposes a method of statistical correlation between the traditional retention test and testing of electrical stress across the tunnel oxide which has shorter execution time. This study is based on cell populations after failing both tests. By comparing the distributions of these populations a correlation law appears between the cells behavioral tendencies. Following this study the replacement of long retention tests by shorter electrical stress tests may be considered.