22,613 research outputs found
AlN/GaN-based MOS-HEMT technology: processing and device results
No full textProcess development of AlN/GaN MOS-HEMTs is presented, along with issues and problems concerning the fabrication processes. The developed technology uses thermally grown Al<sub>2</sub>O<sub>3</sub> as a gate dielectric and surface passivation for devices. Significant improvement in device performance was observed using the following techniques: (1) Ohmic contact optimisation using Al wet etch prior to Ohmic metal deposition and (2) mesa sidewall passivation. DC and RF performance of the fabricated devices will be presented and discussed in this paper
Dynamic Transconductance Dispersion Characterization of Channel Hot-Carrier Stressed 0.25<i>μ</i>m AlGaN/GaN HEMTs
No full textUsing the dynamic transconductance frequency dispersion technique, we characterize unstressed and hot-electron stressed short-channel AlGaN/GaN high-electron-mobility transistors. The results reported in this letter demonstrate that the stress-induced degradation in dc and pulsed characteristics is unlikely to be ascribable to sizable trap generation at the AlGaN/GaN interface
Intentionally Carbon-Doped AlGaN/GaN HEMTs:Necessity for Vertical Leakage Paths
No full textDynamic ON-resistance (RON) in heavily carbon doped AlGaN/GaN high electron mobility transistors is shown to be associated with the semi-insulating carbon-doped buffer region. Using transient substrate bias, differences in RON dispersion between transistors fabricated on nominally identical epilayer structures were found to be due to the band-to-band leakage resistance between the buffer and the 2DEG. Contrary to normal expectations, suppression of dynamic RON dispersion in these devices requires a high density of active defects to increase reverse leakage current through the depletion region allowing the floating weakly p-type buffer to remain in equilibrium with the 2DEG
Behavioral modeling of GaN-based power amplifiers: impact of electrothermal feedback on the model accuracy and identification
No full textIn this article, we discuss the accuracy of behavioral models in simulating the intermodulation distortion (IMD) of microwave GaN-based high-power amplifiers in the presence of strong electrothermal (ET) feedback. Exploiting an accurate self-consistent ET model derived from measurements and thermal finite-element method simulations, we show that behavioral models are able to yield accurate results, provided that the model identification is carried out with signals with wide bandwidth and large dynamics
Remote temperature mapping of high-power InGaN/GaN MQW flip-chip design LEDs
No full textWe report on the study of heat 2D-distribution in InGaN LEDs with the stress made on local device overheating and
temperature gradients inside the structure. The MQW InGaN/GaN/sapphire blue LEDs are designed as bottom emitting
devices where light escapes the structure through the transparent GaN current spreading layer and sapphire substrate, whereas the LED structure with high-reflectivity Ni/Ag p-contact is bonded to the thermally conductive Si submount by a flip-chip method. The measurements are performed with an IR microscope operating in a time-resolved mode (3-5 μm spectral range, <20 μm spatial and 10 μs temporal resolution), while scanning a heat emission map through a transparent sapphire substrate. We show how current crowding (which is difficult to avoid) causes a local hot region near the n-contact pads and affects the performance of the device at a high injection level
LCT-GAN - Improving the efficiency of tabular data synthesis via latent embeddings
No full textIn the past decade data-driven approaches have been at the core of many business and research models. In critical domains such as healthcare and banking, data privacy issues are very stringent. Synthetic tabular data is an emerging solution to privacy guarantee concerns. Generative Adversarial Networks (GANs) are one of the emerging solutions for synthesizing data. However in order to capture all relevant relationships between columns, tabular data needs to be numerically encoded. As columns might be of different types, this is a challenging task as proven by recent approaches. Throughout this paper, we focus on the dimensionality explosion problem, which leads to high-dimensional datasets alongside computational overhead and increase in training time. We introduce a novel synthesis pipeline - LCT-GAN - an improvement to the current state-of-the-art in tabular data synthesis CTAB-GAN. Our approach addresses the dimensionality explosion problem by introducing a low-dimensional embedding step via an autoencoder prior to training. It is then combined with a novel conditional GAN architecture, operating in latent space. After thorough evaluation, we observe that our solution achieves more than 30\% improvement in certain statistical metrics in comparsion to CTAB-GAN, accompanied by 5 fold decrease in size and 150 times speedup in training time for a single epoch. We successfully show that it is possible to embed data using autoencoders, and that GANs are able to learn complex relationships in latent space in the context of tabular data.CSE3000 Research ProjectComputer Science and Engineerin
FCT-GAN: Fourier Neural Operator for Global Relation Enhancement in Tabular Data Synthesizing using Generative Adversarial Networks
No full textSince the regularization of data privacy (e.g., GDPR), the effectiveness of data sharing has decreased. A promising technique to circumvent this problem is tabular data synthesis (i.e., the generation of fake tabular data that statistically resembles the original data). However, the state-of-the-art tabular data synthesis model, CTAB-GAN, fails at robustly imitating global data dependencies and underperforms when column orders get permuted. CTAB-GAN internally uses Convolutional Neural Networks (CNN) which limits the model’s performance due to a strictly non-global data perspective during iterative training phases. To address this limitation, this paper proposes FCT-GAN which leverages the Fourier Neural Operator to learn global dependencies in the frequency domain. Specifically, it enhances CTAB-GAN by replacing the CNN of the discriminator with a four-layered two-dimensional Fourier Neural Operator. As a consequence of FCT-GAN’s global nature and cross-column relation robustness, it outperforms CTAB-GAN and additionally offers the column permutation invariant property. The evaluation of FCT-GAN on five datasets shows that the generated data, remarkably resembles the real data and reveals an increase in accuracy, by up to 19% for five machine learning algorithms independent of data column order, compared to CTAB-GAN.CSE3000 Research ProjectComputer Science and Engineerin
Coincident electron channeling and cathodoluminescence studies of threading dislocations in GaN
No full textWe combine two scanning electron microscopy techniques to investigate the influence of dislocations on the light emission from nitride semiconductors. Combining electron channeling contrast imaging and cathodoluminescence imaging enables both the structural and luminescence properties of a sample to be investigated without structural damage to the sample. The electron channeling contrast image is very sensitive to distortions of the crystal lattice, resulting in individual threading dislocations appearing as spots with black–white contrast. Dislocations giving rise to nonradiative recombination are observed as black spots in the cathodoluminescence image. Comparison of the images from exactly the same micron-scale region of a sample demonstrates a one-to-one correlation between the presence of single threading dislocations and resolved dark spots in the cathodoluminescence image. In addition, we have also obtained an atomic force microscopy image from the same region of the sample, which confirms that both pure edge dislocations and those with a screw component (i.e., screw and mixed dislocations) act as nonradiative recombination centers for the Si-doped c-plane GaN thin film investigated
Band offsets of non-polar A-plane GaN/AlN and AlN/GaN heterostructures measured by X-ray photoemission spectroscopy
No full textThe band offsets of non-polar A-plane GaN/AlN and AlN/GaN heterojunctions are measured by X-ray photoemission spectroscopy. A large forward-backward asymmetry is observed in the non-polar GaN/AlN and AlN/GaN heterojunctions. The valence-band offsets in the non-polar A-plane GaN/AlN and AlN/GaN heterojunctions are determined to be 1.33 +/- 0.16 and 0.73 +/- 0.16 eV, respectively. The large valence-band offset difference of 0.6 eV between the non-polar GaN/AlN and AlN/GaN heterojunctions is considered to be due to piezoelectric strain effect in the non-polar heterojunction overlayers.Nanoscience & NanotechnologyMaterials Science, MultidisciplinaryPhysics, AppliedSCI(E)[email protected]; [email protected]
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Multi-scale modelling of III-nitrides: from dislocations to the electronic structure
No full textGallium nitride and its alloys are direct band gap semiconductors with a wide variety of applications. Of particular importance are light emitting diodes and laser diodes. Due to the lack of suitable lattice-matched substrates, epitaxial layers contain a high density of defects such as dislocations. To reduce their number and to design a device with desired specifications, multilayered systems with varying composition (and thus material properties) are grown. Theoretical modelling is a useful tool for gaining understanding of various phenomena and materials properties.
The scope of the present work is wide. It ranges from a continuum theory of dislocations treated within the linear elasticity theory, connects the continuum and atomistic level modelling for the case of the critical thickness of thin epitaxial layers, and covers some issues of simulating the electronic structure of III-nitride alloys by means of the first principle methods.
The first part of this work discusses several topics involving dislocation theory. The objectives were: (i) to apply general elasticity approaches known from the literature to the specific case of wurtzite materials, (ii) to extend and summarise theoretical studies of the critical thickness in heteroepitaxy. Subsequently, (iii) to develop an improved geometrical model for threading dislocation density reduction during the growth of thick GaN films.
The second part of this thesis employs first principles techniques (iv) to investigate the electronic structure of binary compounds (GaN, AlN, InN) and correlate these with experimentally available N K-edge electron energy loss near edge structure (ELNES) data, (v) to apply the special quasi-random structures method to ternary III-nitride wurtzite alloys aiming to develop a methodology for modelling wurtzite alloys and to get quantitative agreement with experimental N K-edge ELNES structures, and (vi) to theoretically study strain effects on ELNES spectra
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