New method for optimizing the detection of low-energy soft X-rays (200–300 eV) in a CMOS detector

Complementary metal-oxide semiconductor (CMOS) sensors have been widely used as soft X-ray detectors in several fields owing to their recent developments and unique advantages. The CMOS detector parameters have been extensively studied and evaluated. However, the methods for discriminating signals and dark noise have not been sufficiently studied, particularly for low-energy soft X-rays. Setting a threshold, which is widely used for discrimination, is not suitable for low-energy soft X-rays because of the crossing of the energy bands of dark noise and signals. In this study, we analyzed the charge correlation of the CMOS detector GSENSE2020BSI (G2020BSI) and proposed a new two-dimensional segmentation method to optimize the discrimination of signals according to the charge correlation. The effectiveness of the method used to discriminate low-energy soft X-rays on the G2020BSI detector was qualitatively evaluated. The optimal feature parameters used in the two-dimensional segmentation method were investigated for G2020BSI. However, the two-dimensional segmentation method is insensitive to feature parameters.