Beatrice Pedretti, a student in the Ph.D. programme in Information Technology at the Department of Electronics, Information and Bioengineering, Politecnico di Milano, received the EXRS 2024 Best Poster Award for the poster ‘CASPER-AI: Machine Learning for Enhanced Active Collimation in Monolithic Arrays of SDDs.’
The poster, presented at the last European X-ray Spectrometry Conference (EXRS 2024), held in Athens from June 24 to 28, 2024, was co-written with Giacomo Borghi, Giacomo Ticchi, Marco Carminati and Carlo Fiorini from the Department of Electronics, Information and Bioengineering.
The poster discusses the challenges of charge sharing in X-ray fluorescence spectroscopy using Silicon Drift Detector (SDD) arrays, which can lead to crosstalk between detector pixels. Traditional mechanical collimation reduces this issue but decreases the active area and efficiency of the detectors. The study proposes using electronic collimation combined with machine learning to address this problem.
The approach promises to improve SDD-based spectroscopy by reclaiming useful events lost due to charge sharing and integrating them into the photopeak, thus enhancing the overall efficiency and effectiveness of the detectors.