Particle Identification in Fast Inorganic Scintillators via Machine Learning

ORAL

Abstract

YAP:Ce is a fast, mechanically robust inorganic scintillator primarily used for X-ray and gamma-ray detection. Differences in scintillation kinetics for gamma rays and alpha particles in YAP:Ce have been reported, but particle identification capability through pulse shape discrimination has not previously been shown. Therefore, YAP:Ce has been paired with additional scintillation material such as ZnS(Ag) in mixed-field applications, but the slow decay time of the latter limits these applications to relatively low count rates. We highlight the limitations of traditional approaches to particle identification in YAP:Ce and showcase the efficacy of an approach based on machine learning. Through a proof-of-concept experiment, we demonstrate that YAP:Ce alone can discriminate between alpha particles and gamma rays in mixed-field radiation environments. We also show that this technique can potentially be extended to other fast inorganics such as YAG:Ce.

*This research was performed with support from ARPA-E under cooperative agreement DE-AR0001734.

Publication: E. Todd, V. Fondement, and I. Jovanovic, "Particle Identification in YAP:Ce," in prep, 2025

Presenters

  • Ethan Todd

    • University of Michigan - Ann Arbor

Authors

  • Ethan Todd

    • University of Michigan - Ann Arbor
  • Valentin Fondement

    • University of Michigan - Ann Arbor
  • Igor Jovanovic

    • University of Michigan