A 3-D dosimeter fills the need for treatment plan and delivery verification required by every modern radiation-therapy method used today. This report summarizes a proof-of-concept study to develop a water-equivalent solid 3-D dosimeter that is based on novel radiation-hard scintillating material. The active material of the prototype dosimeter is a blend of radiation-hard peroxide-cured polysiloxane plastic doped with scintillating agent P-Terphenyl and wavelength-shifter BisMSB. The prototype detector was tested with 6 MV and 10 MV x-ray beams at Ohio State University’s Comprehensive Cancer Center. A 3-D dose distribution was successfully reconstructed by a neural network specifically trained for this prototype. This report summarizes the material production procedure, the material’s water equivalency investigation, the design of the prototype dosimeter and its beam tests, as well as the details of the utilized machine learning approach and the reconstructed 3-D dose distributions.

The detection of neutrons above background levels is an indication of nuclear materials, creating significant applications for handheld neutron detectors in homeland security. For such applications, a 10B and 6Li enriched, scintillating glass neutron detector was designed. The model is compact enough to be used as a handheld detector and is equipped with machine learning capabilities to determine the location of the source and discriminate a neutron from a gamma. Lithium Borosilicate glass samples, with up to 70% 10B and 6Li content, and doped with Tb and Eu, were engineered to optimize the performance of the detector. The scintillation properties and neutron/gamma detection capabilities of the glass samples were tested. The model detector's performance was simulated in Geant4 and the simulation data was utilized for machine learning to predict the location of the source with an Artificial Neural Network (ANN). The reported handheld neutron detector design with the implemented artificial intelligence capability can achieve 99.9% accuracy in neutron/gamma discrimination, 8.9% error in radial angle estimates, and 2.9% error in azimuthal angle estimates.