Work

Machine learning-enabled pulse shape discrimination in YAP:Ce

Year: 2026

Type: article

Abstract: YAP:Ce is a fast, mechanically robust inorganic scintillator primarily used to detect X-rays and gamma rays. 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. This work highlights the limitations of traditional approaches to particle identification in YAP:Ce and demonstrates the efficacy of a machine-learning-based approach. Through a proof-of-concept experiment, we show that this approach offers a possible path towards using YAP:Ce alone to discriminate between alpha particles and gamma rays in mixed-field radiation environments.

Source: Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment

DOI: 10.1016/j.nima.2026.171883

Authors: Ethan Todd, Valentin Fondement, Igor Jovanovic

Institutions: University of Michigan, University of California, Berkeley

Language: English

Topic: Radiation Detection and Scintillator Technologies

Subfield: Radiation

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,620

Funders: Advanced Research Projects Agency - Energy, Advanced Research Projects Agency, Lawrence Berkeley National Laboratory