abstract: Gallium Nitride (GaN) based Current Aperture Vertical Electron Transistors (CAVETs) present many appealing qualities for applications in high power, high frequency devices. The wide bandgap, high carrier velocity of GaN make it ideal for withstanding high electric fields and supporting large currents. The vertical topology of the CAVET allows for more efficient die area utilization, breakdown scaling with the height of the device, and burying high electric fields in the bulk where they will not charge interface states that can lead to current collapse at higher frequency.
Though GaN CAVETs are promising new devices, they are expensive to develop due to new or exotic materials and processing steps. As a result, the accurate simulation of GaN CAVETs has become critical to the development of new devices. Using Silvaco Atlas 5.24.1.R, best practices were developed for GaN CAVET simulation by recreating the structure and results of the pGaN insulated gate CAVET presented in chapter 3 of [8].
From the results it was concluded that the best simulation setup for transfer characteristics, output characteristics, and breakdown included the following. For methods, the use of Gummel, Block, Newton, and Trap. For models, SRH, Fermi, Auger, and impact selb. For mobility, the use of GANSAT and manually specified saturation velocity and mobility (based on doping concentration). Additionally, parametric sweeps showed that, of those tested, critical CAVET parameters included channel mobility (and thus doping), channel thickness, Current Blocking Layer (CBL) doping, gate overlap, and aperture width in rectangular devices or diameter in cylindrical devices. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2019
Identifer | oai:union.ndltd.org:asu.edu/item:53600 |
Date | January 2019 |
Contributors | Warren, Andrew (Author), Vasileska, Dragica (Advisor), Goodnick, Stephen (Committee member), Zhao, Yuji (Committee member), Arizona State University (Publisher) |
Source Sets | Arizona State University |
Language | English |
Detected Language | English |
Type | Masters Thesis |
Format | 60 pages |
Rights | http://rightsstatements.org/vocab/InC/1.0/ |
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