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Innovative directional detector with 360° source localization coverage

Localization and identification of radioactive sources is a key issue for operators in nuclear facilities and homeland security. We propose a γ-ray detection system without moving parts, based on a scintillator crystal read out by an array of silicon …

Isotope Spectrum Builder: An Application for Modeling Gamma-Ray Spectra of Common Isotopes Using Monte Carlo Pools and Experimental Backgrounds

The Isotope Spectrum Builder is an open-source software framework for generating realistic gamma-ray spectra by combining physics-based Monte Carlo signal event pools with experimentally derived background radiation data. Signal events are generated …

Introducing CdZnTe Detectors into Measuring 222Rn Concentrations in Water

Radon (222Rn) is a noble, radioactive gas and tends to be accumulated in poorly ventilated enclosed spaces. Mainly due to its radioactive daughters and the α-particles emitted, 222Rn poses a risk of cancer and therefore its concentration in air and …

Strengthening Nuclear Security with ML, Full-Spectrum 137Cs Burial Depth Estimation

The non-intrusive characterization of buried radioactive sources is a critical capability for thwarting illicit trafficking, mitigating orphan‑source hazards, and safeguarding civilian populations against radiological threats. Depth estimation, in …

Anomaly Detection in Gamma-Ray Spectra Using Autoencoders with Small Form Factor CZT Detectors

The detection of weak radioactive sources in fluctuating background environments is a critical task for nuclear security, environmental monitoring, and emergency response. Compact gamma-ray detectors, such as small-volume CdZnTe (CZT) crystals, are …

Deep Learning-Based Isotope Identification for Radiological Crime Scene Investigations Using Convolutional Neural Networks

We address on-scene nuclear forensics with a portable NaI 3 inch detector by training a convolutional neural network on spectra synthesized from Geant4 event level pools with bootstrap resampling, mixed with measured background, and regularized via …

Detection of Buried Landmines using a Convolutional Autoencoder trained on Simulated prompt Gamma Spectra

The detection of buried landmines remains a persistent challenge in security and humanitarian demining. In this work, we present an indirect detection methodology based on the analysis of prompt gamma-ray emissions induced by 14 MeV neutron …

Deep learning on simulated gamma spectra for explosives detection using a NaI detector

The detection of explosives and contraband materials using neutron activation analysis (NAA) is a critical component of modern security systems. This study investigates the feasibility of identifying explosive materials using a simple sodium iodide …

Spectrum analysis for identification of nuclides at radiological crime scene

Gamma-ray spectroscopy is an essential technique for identifying the composition of radioactive materials. This work presents a detailed algorithm for analysing gamma-ray spectra, focusing on peak detection, energy calibration, efficiency calibration …

Simulated near-field radioactive source localization in 3D with Coded Aperture and Convolutional Neural Networks

Coded Aperture γ-cameras have been extensively used in applications ranging from astrophysics to nuclear medicine for imaging radioactive source distributions. These devices allow the identification of the direction of γ-emitters by analyzing the …