A Novel Approach for Analysis of Rocking Curve X-Ray Diffraction Imaging Data (RC-XRDI) on 4H-SiC Using Cumulative Integrated Intensity (CII) Method
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This paper presents a novel method of using cumulative integrated intensity (CII) to analyse rocking curve x-ray diffraction imaging (RC-XRDI) data. This method overcomes several limitations of traditional complex non-ideal curve fitting, which often results in inaccurate peak detection and full width at half maximum (FWHM) extraction. These complex non-ideal rocking curves arise in cases where additional features are present, such as peak splitting and multiple peaks. The application of the method also avoids the need for curve fitting and time-consuming calculations, allowing the extraction of peak widths at various normalized height-intensities (FWxM) and revealing extra information about defects. By analysing the broadening and peak position of the rocking curves for different defects, RC-XRDI provides insights into the nature and distribution of these defects within the material. Applied to RC-XRDI of a 4H-SiC 10 μm-thick homo-epitaxial layer on a substrate, the CII method was used to detect shifts in peak position and generate maps of full width at 1%, 10%, and 50% of maximum intensity, offering a detailed view of defect-induced broadening. Our results demonstrate that the CII method provides improved accuracy and requires fewer computations compared to curve-fitting techniques, making it particularly useful where precise defect characterization is critical. Moreover, background intensity was detected pixel-by-pixel using cubic smoothing splines, and the CII method provided robust validation for the precision of this background detection.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- A Novel Approach for Analysis of Rocking Curve X-Ray Diffraction Imaging Data (RC-XRDI) on 4H-SiC Using Cumulative Integrated Intensity (CII) Method
- Date Crossref
- 09/05/2025
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
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