The objective of this research has been the study of device properties for emerging wide-bandgap cubic-phase semiconductors. Though the wide-bandgap semiconductors have great potential as high-power microwave devices, many gaps remain in the knowledge about their properties. The simulations in this work are designed to give insight into the performance of microwave high-power devices constructed from the materials in question. The simulation are performed using a Monte Carlo simulator which was designed from the ground up to include accurate, numerical band structures derived from an empirical pseudo-potential model. Improvements that have been made to the simulator include the generalized device structure simulation, the fully numerical final state selector, and the inclusion of the overlap integrals in the final-state selection. The first comparison that is made among the materials is direct-current breakdown. The DC voltage at which breakdown occurs is a good indication of how much power a transistor can provide. It is found that GaAs has the smallest DC breakdown, with 3C-SiC and ZB-GaN being over 3 times higher. This follows what is expected and is discussed in detail in the work. The second comparison made is the radio-frequency breakdown of the transistors. When devices are used in high-frequency applications it is possible to operate them beyond DC breakdown levels. This phenomenon is caused by the reaction time of the carriers in the device. It is important to understand this effect if these materials are used in a high-frequency application, since this effect can cause a change in the ability of a material to produce high-power devices. MESFETs made from these materials are compared and the results are discussed in detail.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/7500 |
| Date | 06 October 2005 |
| Creators | Weber, Michael Thomas |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 2466283 bytes, application/pdf |
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