Abstract
The use of large-area and multi-detector energy-dispersive X-ray spectrometer (EDXS) systems introduces a number of complex challenges with regard to the accuracy of EDXS quantification.
This is due to the increased absorption effects and variable shadowing across the detector surface that these detectors entail. The application of conventional techniques, such as specimen tilting to enhance the take-off angle, proves inadequate for ensuring accurate quantification in these circumstances. In order to address these issues, we developed a Python-based ray tracing simulation tool, edXTrace. This tool models energy-dependent X-ray absorption and shadowing effects with arbitrary detector geometries, sample holder and specimen shapes. Furthermore, a supplementary script for DigitalMicrograph is provided, which integrates the calculated absorption correction into the TEM workflow, thus enhancing the quantitative accuracy of large-area EDXS systems. This approach offers TEM operators a practical and adaptable solution for quantitative EDXS analysis, which is particularly beneficial in the context of complex specimen-detector geometries that are prevalent in modern TEM configurations. Using a NiO test specimen we demonstrate the use of edXTrace with respect to quantitative analysis results.
