Silicon carbide (SiC) is a semiconductor with attractive properties, such as a wide bandgap (3. 26 eV), high dielectric strength, and high thermal conductivity that make it suitable for high power, highspeed electronic devices. A major roadblock to its wider application is the presence of defects, particularly micropipes and dislocations, in SiC wafers produced today and decreasing density of these defects is the most important challenge of the industry. The goal of this thesis was to design, build and test a system for detection and analysis of the defects in SiC wafers. The system is based on the reflection optical microscopy of the surface of wafers etched with Potassium Hydroxide (KOH). Etching in molten KOH at 450ºC enhances the defects and allows distinguishing micropipes and dislocation in dark field or bright field microscopic images, depending on the semiconductor doping level. Computer image analysis of the microscopic images, which included threshold filtering, dilation, and erosion, resulted in creation of wafer maps of micropipes and dislocation defects. The process was automated and the duration for scanning wafers, 5 cm in diameter, and generating defect maps is typically four hours.
The ability to generate defect maps of SiC wafers will help to reveal the conditions under which micropipes are formed, and may ultimately lead to developing methods of their reduction. Since there is a well established theory that screw dislocations play a role in the generation of micropipes, the correlation between micropipes and dislocations maps will further help to confirm this hypothesis.
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