Machine learning-enabled pulse shape discrimination in YAP:Ce

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.