Deep learning-based alpha particles spectroscopy with solid-state nuclear track detector CR-39

A novel approach for alpha particles energy spectroscopy utilizing a sophisticated deep learning machine learning algorithm is introduced. The approach we employ classifies the alpha particles trajectories on a CR-39 detector into six discrete energy levels: 0.5 MeV, 1.5 MeV, 2.5 MeV, 3.5 MeV, 4.5 MeV, and 5.4 MeV. Some 57 different CR-39 detectors were exposed to alpha particles of the stated energy levels using a²⁴¹Am source.