Fluorophosphate glasses doped with Eu3+ and Dy3+ for X-ray radiography

The borosilica, a very common PMT window and envelope material, contains 5% Boron (1% 10 B). The high cross section for 10 B capturing thermal neutrons (3980 barn), is a con- cern for LHC experiments using borosilica window PMTs. This study investigates the rate and the size of the signals generated by thermal neutron boron interaction in borosilica window PMTs; Hamamatsu R7525-HA and R7600U-200-M4. Although virtuallyall of the thermal neutrons inci- dent on the borosilicate glass are absorbed, probability of generating a PMT signal was measured to be 3 × 10 −4 and 3 × 10 −6 for R7525-HA and R7600U-200-M4 PMTs, respectively. For these signals the average pulse size was found to be between 20-30 photoelectrons. We also discuss that four anode PMTs allow the elimination of these events with an offline algorithm.

https://absimage.aps.org/image/APR11/MWS_APR11-2011-000842.pdf

Boron and thermal neutron interactions on borosilica window photomultiplier tubes

The glass system (50NaPO3–20BaF2–10CaF2–20GdF3)-xTbCl3 with x = 0.3, 1, 3, 5, and 10 wt % was investigated. We successfully produced transparent glass ceramic (GC) scintillators with x = 1 through a melt-quenching process followed by thermal treatment. The luminescence and crystallization characteristics of these materials were thoroughly examined using various analytical methods. The nanocrystallization of Tb3+-doped Na5Gd9F32 within the doped fluoride-phosphate glasses resulted in enhanced photoluminescence (PL) and radioluminescence (RL) of the Tb3+ ions. The GC exhibited an internal PL quantum yield of 33 % and the integrated RL intensity across the UV-visible range was 36 % of that reported for the commercial BGO powder scintillator. This research showcases that Tb-doped fluoride-phosphate GCs containing nanocrystalline Na5Gd9F32 have the potential to serve as efficient scintillators while having lower melting temperature compared to traditional silicate and germanate glasses. 

Photoluminescence and X-ray induced scintillation in Gd3+-Tb3+ co-doped fluoride-phosphate glasses, and derived glass-ceramics containing NaGdF4 nanocrystals

—The high cost and low image quality tradition-ally associated with proton computed tomography (pCT) have prevented it from seeing signiﬁcant use in clinical settings. A cheap, compact, high-density scintillating glass detector capable of being attached to existing proton therapy gantries may help address these concerns. The design of the detector allows for use in conjunction with single-proton counting reconstruction algorithms, as well as beam-based algorithms that do not resolve individual protons within an accelerator bunch. This study presents quantitative reconstructed images of proton stopping power from Monte Carlo generated pCT scans using the radiation transport code MCNP6, demonstrating the feasibility of proton imaging using this detector design. Relative error and contrast have been examined and compared for images reconstructed using two reconstruction algorithms: a standard ﬁltered backprojection algorithm to act as a benchmark, and a variant of a pCT algorithm which utilizes the concept of distance- driven binning.

Reconstructed pCT Images Using Monte Carlo Simulations of a Scintillating Glass Detector

High-purity germanium radiation detectors, reknowned for their exceptional gamma-ray spectroscopy capabilities, are associated with high costs and require cooling below 77°K for optimal operation. This study introduces an innovative approach to construct high-resolution gamma-ray spectra for high-purity germanium detectors using more affordable, lower-resolution thallium-activated sodium iodide detectors. A Fully Connected Neural Network was proposed to create a mapping function for this transformation. A dataset consisting of 7200 diverse spectra was generated using measurements from single radioisotopes for both thallium-activated sodium iodide and high purity germanium detectors. The model's performance was assessed on datasets with low counts and overlapping peaks. Experimental validation was performed on 26 multiple spectra, yielding errors of 3.83% and 5.82% and accuracies of 0.998 and 0.971 for the generated and measured test data, respectively. Despite being trained solely on generated data, the model effectively converted the broad thallium-activated sodium iodide spectra into sharp high-purity germanium spectra. 

Utilizing artificial neural networks to convert gamma-ray spectra from NaI(Tl) detectors to HPGe detector gamma-ray spectra

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.

A glass neutron detector with machine learning capabilities

Post-Situ neutron and gamma radiation damage studies performed on seven types of quartz fibers are reported. All fibers contained quartz cores, some of which were UV enhanced. The fiber cladding was either polymer or quartz, while the buffer was either polymide or acrylite. Previous studies with electron and proton irradiation on numerous types of quartz fibers have shown different optical degradation levels. However, neutron and gamma irradiation has not been investigated for similar quartz fibers before. After 17.6 × 104 Gray of neutron and 73.5 × 104 Gray of gamma radiation, wavelength specific damage to each type of fibers was determined. It is seen that the FBP type quartz fiber by Polymicro shows the least damage due to neutron and gamma radiations.

https://iopscience.iop.org/article/10.1088/1748-0221/11/10/T10006/pdf

Post Situ neutron and gamma radiation damage tests on different quartz types

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A glass neutron detector with machine learning capabilities

Post Situ neutron and gamma radiation damage tests on different quartz types