12-23 October 2020
GMT timezone

A Novel Spectroscope with Machine Learning at the Edge for Real-Time Position Sensitivity in Thick LaBr3 Crystal

14 Oct 2020, 16:08
Mini Oral and Poster Real Time System Architectures and Intelligent Signal Processing Poster session C-01


Mr DI VITA, Davide (Politecnico di Milano)


We present a 144-channel detection module for gamma spectroscopy that couples a SiPM detectors array to a thick LaBr3 scintillation crystal. The module features custom front-end electronics, state-of-the-art energy resolution (2.9% at 662keV), 80kHz monolithic acquisition rate and embedded, real-time imaging capabilities. The relatively large number of independent channels allows to achieve a large energy range (up to 20MeV) and spatial resolution in photon-interaction position reconstruction (aiming at relativistic Doppler effect correction in accelerator-based nuclear physics experiments), without sacrificing state-of-the-art energy resolution, thanks to the 84dB dynamic range GAMMA ASIC. The experimental results, obtained in real-time, edge computing of coordinates and energy per scintillation event on the FPGA device with sub-µs processing time, suggest an innovative approach in instrumentation development for nuclear science.

Minioral Yes
IEEE Member Yes
Are you a student? Yes

Primary authors

Mr DI VITA, Davide (Politecnico di Milano) Mr BUONANNO, Luca (Politecnico di Milano) Prof. CARMINATI, Marco (Politecnico di Milano) Prof. CAMERA, Franco (Università Statale degli Studi di Milano) Mr FIORINI, Carlo (Politecnico di Milano)

Presentation materials