Polar coordinate-based background removal algorithm for 2D x-ray scattering data

During the data collection of x-ray diffraction experiments with various detectors, background signals are often unavoidable along with the sample signal. Addressing the background during post-data analysis is not a straightforward task. In this work, we introduced an algorithm specifically designed to handle centrally symmetric two-dimensional x-ray diffraction data and processed the data using the Python programming language. The two-dimensional data are first transformed from Cartesian coordinates to polar coordinates. Second, utilizing existing background processing algorithms, one-dimensional background curves are identified for each azimuth angle. These background data are then merged to generate two-dimensional background data. Finally, by subtracting the background from the original data, we obtain the clear diffraction signal. The algorithm can effectively remove the background from x-ray diffraction data and exhibits the ability to handle backgrounds with high intensity and irregular shapes, and the discernibility of the weak signal is significantly enhanced. Moreover, researchers have the flexibility to choose whether to preserve or eliminate the signals from additional amorphous components based on their needs. This algorithm will provide researchers with the possibility for further data analysis.