Selective etching of dislocations in GaN and quantitative SEM analysis with shape-reconstruction method

Area of Science:

• Materials Science
• Crystallography
• Surface Science

Background:

• Dislocation density determination is crucial for understanding material properties.
• Chemical etching reveals dislocations as etch pits, but quantifying types remains challenging.
• Existing methods for dislocation analysis can be complex and time-consuming.

Purpose of the Study:

• To develop and validate a novel shape-from-shading method for estimating etch-pit depth distributions.
• To determine dislocation densities based on etch-pit morphology and depth.
• To compare results with established transmission electron microscopy techniques.

Main Methods:

• Utilizing shape-from-shading algorithms based on image brightness and surface slope.
• Applying the method to Gallium Nitride (GaN) surfaces etched in a KOH-NaOH eutectic mixture.
• Analyzing scanning electron microscopy (SEM) micrographs to derive etch-pit depth distributions.

Main Results:

• The shape-from-shading method successfully estimated etch-pit depth distributions.
• Dislocation densities were correlated with specific etch-pit types and depths.
• Results showed good agreement with dislocation densities determined by transmission electron microscopy (TEM).

Conclusions:

• Chemical etching combined with shape-from-shading offers a viable approach for type-specific dislocation density determination.
• This method provides a more detailed analysis of dislocations compared to traditional etch-pit counting.
• The technique holds potential for advancing materials characterization in semiconductor research.