Reliability Analysis of Gallium Nitride (GaN) Devices Using Data Analysis Methods

Gallium nitride (GaN) high-electron-mobility transistors (HEMTs) are good candidates to replace the traditional silicon-based transistors. Although these devices show superior performances compared to Si and SiC-based devices, they suffer from some reliability issues. The aim of this research project is to improve the performance of the GaN HEMTs and enhance their reliability by performing a data analysis technique. This analysis would result in better understanding of GaN HEMTs’ characteristics. Pattern recognition is one of the powerful data analysis techniques which can be helpful in diagnosing different patterns in the given dataset. The use of this technique will result in finding any direct and indirect correlations between different parameters of GaN HEMTs and their reliability. The outcomes of this analysis can help produce reliable GaN HEMTs devices, and would also benefit GaN Systems Inc. in improving the reliability of their products.

Intern: 
Sajjad Goudarzitaemeh
Faculty Supervisor: 
Majid Pahlevani
Province: 
Ontario
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