abstract: This work analyzes and develops a point-of-load (PoL) synchronous buck converter using enhancement-mode Gallium Nitride (e-GaN), with emphasis on optimizing reverse conduction loss by using a well-known technique of placing an anti-parallel Schottky diode across the synchronous power device. This work develops an improved analytical switching model for the GaN-based converter with the Schottky diode using piecewise linear approximations. To avoid a shoot-through between the power switches of the buck converter, a small dead-time is inserted between gate drive switching transitions. Despite optimum dead-time management for a power converter, optimum dead-times vary for different load conditions. These variations become considerably large for PoL applications, which demand high output current with low output voltages. At high switching frequencies, these variations translate into losses that contribute significantly to the total loss of the converter. To understand and quantify power loss in a hard-switching buck converter that uses a GaN power device in parallel with a Schottky diode, piecewise transitions are used to develop an analytical switching model that quantifies the contribution of reverse conduction loss of GaN during dead-time. The effects of parasitic elements on the dynamics of the switching converter are investigated during one switching cycle of the converter. A designed prototype of a buck converter is correlated to the predicted model to determine the accuracy of the model. This comparison is presented using simulations and measurements at 400 kHz and 2 MHz converter switching speeds for load (1A) condition and fixed dead-time values. Furthermore, performance of the buck converter with and without the Schottky diode is also measured and compared to demonstrate and quantify the enhanced performance when using an anti-parallel diode. The developed power converter achieves peak efficiencies of 91.7% and 93.86% for 2 MHz and 400 KHz switching frequencies, respectively, and drives load currents up to 6A for a voltage conversion from 12V input to 3.3V output. In addition, various industry Schottky diodes have been categorized based on their packaging and electrical characteristics and the developed analytical model provides analytical expressions relating the diode characteristics to power stage performance parameters. The performance of these diodes has been characterized for different buck converter voltage step-down ratios that are typically used in industry applications and different switching frequencies ranging from 400 KHz to 2 MHz. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2020

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This dissertation tackles the problem of entanglement in Generative Adversarial Networks (GANs). The key insight is that disentanglement in GANs can be improved by differentiating between the content, and the operations performed on that content. For example, the identity of a generated face can be thought of as the content, while the lighting conditions can be thought of as the operations. We examine disentanglement in several kinds of deep networks. We examine image-to-image translation GANs, unconditional GANs, and sketch extraction networks. The task in image-to-image translation GANs is to translate images from one domain to another. It is immediately clear that disentanglement is necessary in this case. The network must maintain the core contents of the image while changing the stylistic appearance to match the target domain. We propose latent filter scaling to achieve multimodality and disentanglement. Previous methods require complicated network architectures to enforce that disentanglement. Our approach, on the other hand, maintains the traditional GAN loss with a minor change in architecture. Unlike image-to-image GANs, unconditional GANs are generally entangled. Unconditional GANs offer one method of changing the generated output which is changing the input noise code. Therefore, it is very difficult to resample only some parts of the generated images. We propose structured noise injection to achieve disentanglement in unconditional GANs. We propose using two input codes: one to specify spatially-variable details, and one to specify spatially-invariable details. In addition to the ability to change content and style independently, it also allows users to change the content only at certain locations. Combining our previous findings, we improve the performance of sketch-to-image translation networks. A crucial problem is how to correct input sketches before feeding them to the generator. By extracting sketches in an unsupervised way only from the spatially-variable branch of the image, we are able to produce sketches that show the content in many different styles. Those sketches can serve as a dataset to train a sketch-to-image translation GAN.

3D-aware image synthesis has attracted increasing interest as it models the 3D nature of our real world. However, performing realistic object-level editing of the generated images in the multi-object scenario still remains a challenge. Recently, a 2D GAN termed BlobGAN has demonstrated great multi-object editing capabilities on real-world indoor scene datasets. In this work, we propose BlobGAN-3D, which is a 3D-aware improvement of the original 2D BlobGAN. We enable explicit camera pose control while maintaining the disentanglement for individual objects in the scene by extending the 2D blobs into 3D blobs. We keep the object-level editing capabilities of BlobGAN and in addition allow flexible control over the 3D location of the objects in the scene. We test our method on real-world indoor datasets and show that our method can achieve comparable image quality compared to the 2D BlobGAN and other 3D-aware GAN baselines while being the first to enable camera pose control and object-level editing in the challenging multi-object real-world scenarios.

The study of impurity diffusion in semiconductor hosts is an important field that has both fundamental appeal and practical applications. Ion implantation is a good technique to introduce impurities deep into the semiconductor substrates at relatively low temperature and is not limited by the solubility of the dopants in the host. However ion implantation creates defects and damages to the substrate. Annealing process was used to heal these damages and to activate the dopants. In this study, we introduced several species such as alkali metals (Li, Na, K), alkali earth metals (Be, Ca,), transition metals (Ti, V, Cr, Mn) and other metals (Ga, Ge) into semiconductor substrates using ion implantation. The implantation energy varies form 70 keV to 200 keV and the dosages vary between ~ 1.0x1012 and ~5.0x1015 atoms/cm2. The samples are annealed at different temperatures from 300°C to 1000°C and for different time intervals. The redistribution behaviors of the implanted ions are studied experimentally using secondary ion mass spectrometry (SIMS). We observed some complex distribution behaviors due to the defects created during the process of ion implantation. The diffusivities of some impurities are calculated and compared to previous data. It was found that the diffusivities of implanted impurities is related to the dosages, annealing temperatures and the defects and damages caused by ion implantation. Additionally, as we go from one type of semiconductor to another, the diffusion behavior of the impurities shows a different trend.

This work has analyzed the complex interfaces of GaN and InGaN grown by sputter deposition and GaN grown by metal-organic chemical vapor deposition (MOCVD) with CdTe and CdS. First, the GaN and InGaN films were characterized by AFM and XRD, and it has been shown that the MOCVD samples have a very smooth surface and are single crystalline with growth in the (002) direction. On the other hand, the sputter deposited samples have rougher surfaces and are polycrystalline. Furthermore, complete interface studies have been performed using in-situ XPS and deposition between GaN grown by sputter deposition and MOCVD and CdTe and CdS to determine the band alignments, conduction and valence band offsets, and Fermi level positions. These interface studies will help determine basic properties to see if these GaN films can be incorporated in a CdTe solar cell to improve its efficiency. It was determined that all the interfaces between the sputtered GaN/InGaN and CdTe/CdS have small conduction band offsets of less than 0.1 eV that do not significantly prevent electron flow across the interface. However, the valence band offsets were much more significant, as they ranged from 0.43 eV to over 1.8 eV. For purposes of the desired positions of the GaN in the CdTe solar cell, the conduction band offsets are much more crucial, and very small conduction band offsets are desired. An interesting effect was that the interfaces between InGaN/CdTe and InGaN/CdS showed In migration into the CdTe and CdS, causing a rise in the Fermi level for the CdTe and CdS, which has been known to worsen the performance of the CdTe solar cell. The MOCVD GaN/CdTe and CdS interfaces showed a slightly higher conduction band offset of about 0.15 eV, but this barrier still should not significantly prevent current flow. / Master of Science

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