Self-absorption correction on 2D X-ray fluorescence maps

X-ray fluorescence mapping (XRF) is a highly efficient and non-invasive technique for quantifying material composition with micro and nanoscale spatial resolutions. Quantitative XRF analysis, however, confronts challenges from the long-lasting problem called self-absorption. Moreover, correcting two-dimensional XRF mapping datasets is particularly difficult because it is an ill-posed inverse problem. Here we report a semi-empirical method that can effectively correct 2D XRF mapping data. The correction error is generally less than 10% from a comprehensive evaluation of the accuracy in various configurations. The proposed method was applied to quantify the composition distribution around the grain boundaries in an electrochemically corroded stainless steel sample. Highly localized Cr enrichment was found around the crack sites, which was invisible before the absorption correction.

Automated summary

X-ray fluorescence mapping (XRF) is a non-invasive technique for analyzing material composition at micro and nanoscale resolutions. However, self-absorption poses a challenge to quantitative analysis. In this study, a semi-empirical method was developed to effectively correct 2D XRF mapping data, achieving an error rate of less than 10%. The method was applied to analyze the composition distribution around grain boundaries in corroded stainless steel, revealing localized chromium enrichment around crack sites previously invisible due to absorption.