A Novel Approach for Analysis of Rocking Curve X-Ray Diffraction Imaging Data (RC-XRDI) on 4H-SiC Using Cumulative...

Area of Science:

• Materials Science
• Crystallography
• Solid State Physics

Background:

• Rocking curve X-ray diffraction imaging (RC-XRDI) is crucial for material defect analysis.
• Traditional curve fitting methods struggle with complex, non-ideal rocking curves, leading to inaccurate peak detection and width extraction (FWHM).
• Complex curves often exhibit peak splitting and multiple peaks, complicating analysis.

Purpose of the Study:

• To introduce a novel cumulative integrated intensity (CII) method for analyzing RC-XRDI data.
• To overcome limitations of traditional curve fitting in extracting peak parameters and characterizing defects.
• To provide a more accurate, computationally efficient alternative for defect analysis in materials.

Main Methods:

• Developed and applied the cumulative integrated intensity (CII) method to RC-XRDI data.
• Analyzed peak broadening and position variations to understand defect nature and distribution.
• Utilized cubic smoothing splines for pixel-by-pixel background intensity detection.
• Extracted peak widths at various normalized height-intensities (FWxM).

Main Results:

• The CII method accurately analyzes RC-XRDI data, overcoming limitations of traditional curve fitting.
• Demonstrated improved accuracy and reduced computational requirements compared to curve-fitting techniques.
• Successfully applied to a 4H-SiC homo-epitaxial layer, mapping defect-induced broadening.
• Generated maps of full width at 1%, 10%, and 50% of maximum intensity, revealing detailed defect information.
• Validated the precision of background detection through robust CII analysis.

Conclusions:

• The CII method offers a superior approach for analyzing RC-XRDI data, particularly for complex, non-ideal curves.
• This technique provides enhanced accuracy and efficiency in defect characterization, crucial for material science applications.
• The method's ability to extract detailed defect information makes it valuable for precise material analysis.