No abstract

Forescattered electron detection (FED) was utilized to image surface depressions resulting from threading screw and edge dislocations in 4H-SiC epitaxial layers. These surface depressions, or growth pits, exhibited two morphology types. Screw and edge dislocations could be imaged by photoluminescence and differentiated by their interactions with propagating partial dislocations (PDs). Correlations between FED and photoluminescence showed that sharpapex pits 1 lm in size and strip-shaped pits 500 nm in size could be linked to individual screw and edge dislocations, respectively. Forescattered electron detection demonstrated sufficient sensitivity to image surface features previously resolvable only by atomic force microscopy. This new technique is nondestructive, noncontact, and capable of rapid, spatial mapping of growth pits resulting from threading screw and edge dislocations in SiC epitaxial layers.

To understand the nature of various extended defects and their impact on the electronic or optoelectronic characteristics of semiconductor devices, the investigation of spectral properties is required. However, electroluminescence spectroscopy does not provide spatial or structural information. The lack of such information can lead to incorrect assignment of a luminescence band and therefore misinterpretation of the nature of the emitting defect. Here we report on the collection and analysis of real-color and spectrally selective monochromatic electroluminescence (EL) images from 4H-SiC PiN diodes. The former provides the approximate spectral properties from the color of the various defects with high spatial resolution, while the latter enables simultaneous collection of both structural and spectral properties from extended defects, thereby assisting in providing the correct assignment of the various spectral features observed. This effort enabled the observation of the formation of a green EL emission located at C-core partial dislocations (PDs) that occurred during the stacking fault (SF) expansion process.