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In this work, neutron spectra are unfolded using artificial neural networks (ANNs). The neutron response of the NE213 scintillator detector, characterized by the pulse height distribution, is calculated to obtain the necessary data for unfolding the energy spectrum. This is achieved using both analytical response functions and response functions generated by the MCNPX-PHOTRACK code. In this query, the Levenberg-Marquardt method (LMM), which has a high computational speed in the learning method, is used to train the network. The performance of the ANN for unfolding the neutron energy spectrum of the NE213 scintillation detector was evaluated by comparing its results to the established Gravel method. The ANN method consistently produced spectra with a single peak closely matching the incident energy, while the Gravel method showed additional peaks and distortions. Quantitative analysis revealed a lower relative energy peak difference (indicating higher accuracy) for the ANN method compared to Gravel, particularly when noise was introduced into the data. These results suggest that ANNs offer a more robust and accurate approach for neutron spectrum unfolding. • The neutron energy spectrum was unfolded using LMBP algorithm. • A two-layer neural network for energy spectrum unfolding was developed. • In the LMBP method, the time and cost of calculations are reduced considerably. • A comparison of LMBP with GRAVEL shows that both methods are very efficient. [ABSTRACT FROM AUTHOR]

Activity of 225Ac was measured by the digital anti-coincidence spectroscopy technique using a 4πα–γ detector configuration, composed of a sandwich type 4π plastic scintillator and Ge detectors. Ultrathin plastic scintillators were used for selective detection of α-particles emitted from 225Ac and its progenies, and the α-counting efficiencies of a 4π plastic scintillation detector for individual nuclides in the decay chain were determined as well. A list-mode multichannel analyzer was employed to record coincidence/anti-coincidence events for off-line analyses. The time difference distribution spectra revealed α-particle emission following 213Po decay without β-particle interference from 213Bi. • Selective α-particle detection using ultrathin plastic scintillators for 225Ac. • Individual α-efficiencies determined by 4πα(PS)–γ(Ge) anti-coincidence spectroscopy. • α-particles from short-lived 213Po(T 1/2 = 3.7 μs) detected without interference. • Effect of β-particle from 213Bi confirmed from γ–α/β time difference distribution. • Results were consistent with those obtained using the CN method with LSC. [ABSTRACT FROM AUTHOR]

We developed a multi-tasking deep learning model for simultaneous pulse height estimation and pulse shape discrimination for pile-up n/γ signals. Compared with single-tasking models, our model showed better spectral correction performance with higher recall for neutrons. Further, it achieved more stable neutron counting with less signal loss and a lower error rate in the predicted gamma ray spectra. Our model can be applied to a dual radiation scintillation detector to discriminatively reconstruct each radiation spectrum for radioisotope identification and quantitative analysis. • Multi-tasking deep learning model for piled-up n/γ signals. • Simultaneous pulse height estimation and pulse shape discrimination. • Better spectral correction performance with a higher recall of neutrons. • Stable neutron counting with low signal loss and low error in predicted gamma spectra. [ABSTRACT FROM AUTHOR]

Dose-rate monitoring instruments measure the ambient dose equivalent and hence are crucial for protecting workers from radiation exposure. Although plastic scintillation detectors (PSDs) are ideal equipment for dosimetry, they are rarely used owing to the lower detection efficiency than other scintillation detectors. In this study, we acquired ten types of G(E) functions to utilize a PSD in spectroscopic dosimetry using the least-square and first-order methods. The energy response of PSD was much improved in terms of dose evaluation. • Measurement of ambient dose equivalent using a plastic scintillation detector. • Detector with an EJ-276G plastic scintillator coupled to a silicon photomultiplier. • G(E) function obtained using the least-square and first-order methods. • Ensemble G(E) function showed the most stable and superior performance. [ABSTRACT FROM AUTHOR]

This manuscript deals with the possible utilization of plastic microspheres for radiation detection. The aim was to determine the suitability of microspheres for this application, factors that affect detection efficiency, and based on the evaluation of current state technology to design and test a constructional solution suitable for this use. Three detection cell variations and their configurations, which utilize plastic microspheres, were tested for their response to selected militarily important radionuclides during a series of static measurements. Based on the results of static measurements, the most structurally suitable cell variation was subsequently tested for flow scintillation analysis. Among the cells designed for flow scintillation counting in 2π geometry, the highest achieved detection efficiency for 241Am was 13.1 ± 0.7% using Cell #5, for 90Sr/Y was 71.2 ± 3.9% using Cell #10 and for 3H was 3.9 ± 0.2% using Cell #5 respectively. Cell #10 was evaluated to perform universally the best despite achieving slightly lower detection efficiencies for 241Am and 3H than Cell #5, as the results were easily replicable and due to the cell constructional simplicity, its application was problem-free. • Utilization of plastic microspheres for on/line radiation detection. • Can be satisfactorily used for mid and high energy beta emitters. • Moderate detection efficiency for alpha radionuclides. • Poor detection efficiency for low energy beta particles. [ABSTRACT FROM AUTHOR]

In this study, the unfolding of the plastic scintillator spectrum was undertaken using the artificial neural networks tools of MATLAB. To this purpose, the response matrix of the plastic scintillator was generated for 145 energy groups and in 512 pulse-height channels using the MCNPX2.6 code. The results confirmed that the relative error in the gamma-ray energy unfolding with artificial neural networks is less than 3.8%. • ANN tool of MATLAB was used for gamma-ray energy spectrum unfolding of plastic scintillator. • Response matrix was generated using MCNPX2.6 in 145 energy groups and 512 pulse-height channels. • Unfolding results of ANN confirmed that the relative error in this study is less than 3.8%. [ABSTRACT FROM AUTHOR]

New techniques for fabrication of optically clear structures (3D printing and casting) can be applied to fabrication of light guides, especially complex -shaped ones, for scintillation detectors. In this investigation, we explored the spectral transmissivity of sample light guides created with different fabrication methods and materials. A spectrophotometer was used to measure the transmissivity of the samples to determine their compatibility with a number of commonly used inorganic scintillators (NaI(Tl), BGO, LaBr 3 , LaCr 3 , CSI(Tl) and LYSO). These measurements showed that stereolithography with a Stratasys 3D printer using Somos WaterClear Ultra 10122® produced the most compatible light guide with common organic scintillators, especially LYSO (peak emission λ=420 nm) (a scintillator commonly used in positron emission tomography (PET) imaging). Additionally, Polytek Poly-Optic® 1730 clear urethane produced a cast light guide that was the most optically compatible with these scintillators. To demonstrate the ability to create a unique shaped scintillation detector using 3D-printing and casting methods, a small arc-shaped piece of LYSO was coupled to a 4 × 4 array of 4 mm2 silicon photomultipliers (SiPM) using light guides made from these materials. For comparative purposes, a light guide was also fabricated using standard acrylic, a material often used in current light guides. All detectors produced similar event position maps. The energy resolution for 18F (511 keV photopeak) was 13% for the acrylic light-guide-based detector, while it was 18% for the printed light-guide-based detector and 20% for the cast light-guide-based detector. Results from this study demonstrate that advanced fabrication methods have the potential to facilitate creation of light guides for scintillation detectors. Continued advancements in materials and methods will likely result in improved optical performance for 3D-printed structures. • Three-dimensional printing and casting techniques can be used to fabricate light guides for scintillation detectors. • The suitability of the most promising printing and casting materials for creation of light guides wereexplored. • Three sample light guides were produced and tested with a complex-shaped scintillator. [ABSTRACT FROM AUTHOR]