A Neutron Sensitive Detector Using 3D-Printed Scintillators
Adam Barr, Cinzia da Vià, Mosst Tasnim Binte Shawkat, Stephen Watts, John Allison, Gabriele D'Amen, Tianqi Gao
TL;DR
This study demonstrates a scalable route to neutron-sensitive detectors by fabricating polystyrene-based scintillators via FDM, doped with p-terphenyl and POPOP and loaded with $^6$Li via LiF to enable neutron sensitivity. The printed scintillators are integrated with a TimePix3-based detector and an image intensifier, enabling high-resolution spatial and temporal readout; a cluster-based discrimination algorithm leverages TimePix3 data to separate neutron events from gamma backgrounds in mixed fields. Geant4 simulations guide design and interpretation, and experiments show a light yield of $30 \pm 5$ photons/MeV, with Li-loaded designs enhancing neutron detection relative to non-loaded geometries, though commercial EJ-420 remains more sensitive. The work highlights a flexible, low-cost path for customizing neutron-sensitive detectors, with future improvements anticipated from dopant innovations such as perovskites to increase light output while maintaining fast decay times.
Abstract
This work reports on the performance of a novel neutron-sensitive scintillating detector fabricated using Fused-Deposition Modelling (FDM) additive manufacturing. FDM is a cost-effective 3D-printing method employing flexible plastic filaments to create custom-shaped components. Scintillating filaments, based on polystyrene doped with \emph{p}-terphenyl and 1,4-bis (5-phenyloxazol-2-yl) benzene, and enriched with $^6$LiF to enable neutron sensitivity were manufactured in house and achieved visible scintillation with a light output of 30$\pm$5~photons per MeV. Printed scintillators were then integrated into a detector system consisting of an image intensified TimePix3 camera, offering high spatial and temporal resolution. The detector performance was compared with Geant4 simulations of the scintillating sensor's response to electrons, gamma-rays, and thermal neutrons. A novel event discrimination algorithm, using the properties of the TimePix3 camera, enabled the separation of neutron signatures from the gamma-ray background.
