Neutron-gamma Discrimination Research Articles

Study on neutron-gamma discrimination methods based on GMM-KNN and LabVIEW implementation

Study on neutron-gamma discrimination methods based on GMM-KNN and LabVIEW implementation

Particle identification capability of a homogeneous calorimeter composed of oriented crystals

Recent studies have shown that the electromagnetic shower induced by a high-energy electron, positron or photon incident along the axis of an oriented crystal develops in a space more compact than the ordinary. On the other hand, the properties of the hadronic interactions are not affected by the lattice structure. This means that, inside an oriented crystal, the natural difference between the hadronic and the electromagnetic shower profile is strongly accentuated. Thus, a calorimeter composed of oriented crystals could be intrinsically capable of identifying more accurately the nature of the incident particles, with respect to a detector composed only of non-aligned crystals. Since no oriented calorimeter has ever been developed, this possibility remains largely unexplored and can be investigated only by means of numerical simulations. In this work, we report the first quantitative evaluation of the particle identification capability of such a calorimeter, focusing on the case of neutron-gamma discrimination. We demonstrate through Geant4 simulations that the use of oriented crystals significantly improves the performance of a Random Forest classifier trained on the detector data. This work is a proof that oriented calorimeters could be a viable option for all the environments where particle identification must be performed with a very high accuracy, such as future high-intensity particle physics experiments and satellite-based γ-ray telescopes.

250 μm Thick Detectors for Neutron Detection: Design, Electrical Characteristics, and Detector Performances

Solid State Detectors (SSD) are crucial for fast neutron detection and spectroscopy in tokamaks due to their solid structure, neutron-gamma discrimination, and magnetic field resistance. They provide high energy resolutions without external conversion stages, enabling compact array installations in the harsh environment of a tokamak. Research comparing diamond and 4H-SiC detectors highlights thickness as a key efficiency factor. A 250 μm SiC epilayer with low doping, grown using a high-growth-rate process, exhibits sharp interfaces and minimal defects, essential for neutron detectors. The study evaluates detector designs, and performance using a 4H-SiC substrate. Various detector designs, such as Schottky diodes and p/n diodes, are assessed via I-V and C-V measurements, addressing high depletion voltage challenges. Preliminary neutron irradiation tests validate detector functionality, energy resolution and confirming detector reliability.

Characterization of a novel polyurethane-based plastic scintillator for neutron and gamma detection in mixed radiation fields

We present studies of a novel plastic scintillator branded M600, which was developed and provided by Target Systemelektronik. This new material is, in contrast to other solid organic scintillators offered by commercial providers, based on a polyurethane matrix complemented with scintillating and wavelength-shifting additives. This paper covers measurements of absolute light output, LO, (photons per 1 MeV-γ), γ-non-proportionality (NP), light pulse shapes, and neutron-gamma (n/γ) discrimination. The measurements were carried out either using standard calibration gamma sources (LO, NP) or in a mixed field of neutron and γ radiation from an intense (∼4 × 105 neutrons/s/4π) AmBe source (n/γ discrimination). The measured light output was 9650 ± 1000 ph/MeV and the PSD's figure of merit (FoM) was found as 2.2 ± 0.1 at ∼1000 keVee for ∅2.54 cm × 2.54 cm M600 sample. The bigger sample (∅5.08 cm × 5.08 cm) exhibits about 25% lower LO and poorer FoM when compared to the ∅2.54 cm × 2.54 cm M600, due to self-absorption.

FPGA implementation of 500-MHz high-count-rate high-time-resolution real-time digital neutron-gamma discrimination for fast liquid detectors

FPGA implementation of 500-MHz high-count-rate high-time-resolution real-time digital neutron-gamma discrimination for fast liquid detectors

Digital neutron-gamma discrimination algorithm using adaptive noise filter

Pulse shape discrimination of a liquid scintillator-based detector (BC501A) has been studied using a digital approach. The objective of this work is to develop a new neutron-gamma discrimination algorithm to improve the discrimination efficiency. The new approach is a combination of two parts. The first part uses an adaptive Sallen-Key filter to reduce noise in the pulse followed by traditional approaches of either charge comparison or time over threshold. The approach of adaptive Sallen-Key combined with time over threshold was found to have a much better capability to discriminate neutron events from that of gamma. The pulse shape discrimination performance obtained for a 5 inches by 5 inches (length by diameter) liquid scintillator detector using the combination of the adaptive Sallen-Key filter with time over threshold is found to be significantly higher compared to that obtained using traditional methods. Moreover, this combination has the potential for real-time hardware implementation.

Nanoparticle ZnS:Ag/6LiF—a new high count rate neutron scintillator with pulse shape discrimination

A neutron sensitive scintillator employing nanoparticles of ZnS:Ag has been developed for the first time. Pulse shape differences between neutron and gamma signals were observed in this material and neutron-gamma discrimination was applied. With initial signal processing parameters, gamma sensitivities of 8.5×10−6 to 60Co gammas were achieved. The average primary decay of neutron scintillation in nanoparticle ZnS:Ag/6LiF was measured to be 18ns, and afterglow was significantly suppressed in comparison to standard ZnS:Ag/6LiF scintillators that employ micron sized ZnS:Ag. Fast decay times and minimal afterglow indicate potential for use in high count rate capability applications. Prospective count rate capabilities were investigated here as proof of concept, with rates of 1.12Mcps measured for a single readout channel with less than 3.5% count loss. This is approximately 70 times greater than the count rate capability of the current standard ZnS:Ag/6LiF scintillation detectors. With improvements to signal processing and scintillator composition, nanoparticle ZnS:Ag/6LiF could be a promising candidate for future high rate capability neutron detectors.

Comparative Analysis of the Neutron–Gamma Discrimination Methods for Scintillators Based on Lithium Glass

Comparative Analysis of the Neutron–Gamma Discrimination Methods for Scintillators Based on Lithium Glass

Design and performance evaluation of a compact thermal and fast neutron spectrometer

Measurement of the space neutron radiation environment has put forward new requirements for the miniaturization and lightweight design of neutron spectrometers. In this paper, a compact broad-spectrum neutron spectrometer was designed, in which the fast neutron detector was based on the EJ-254 scintillator-coupled with SiPMs array, and the thermal and epithermal neutron detectors were based on the NaI(Tl + Li) (NaIL) scintillator coupled with SiPMs array encapsulated in Al and Cd shells, respectively. The overall weight of the neutron spectrometer was only 2.4 kg, and its dimensions were 154 mm × 123 mm × 115 mm. The fast neutron energy spectrum was obtained based on the capture-gated method and the Maximum Likelihood Expectation Maximization (MLEM) unfolding algorithm; the counts of thermal and epithermal neutrons were obtained based on the optimized frequency-domain Pulse Shape Discrimination (PSD) method and cadmium difference method. The proposed neutron spectrometer with all applied methods was tested as a whole system with a252Cf and a241Am–Be source. The spectrum result was compared to an ISO standard source. The accuracy of fast part of 0.5–10 MeV was 5.9% in definition of Relative Root Mean Squared Error (RRMSE). The thermal and epithermal neutron counts were far higher than standard spectrum, and we proved it being effected by laboratory introduced neutron scattering through a simulation, thus the thermal and epithermal flux measurements was believed to be decent. The Figure of Merit (FoM) of the NaIL's PSD neutron gamma discrimination were 2.57 and 2.90 respectively.

Optimization of pulse shape discrimination based on frequency domain for SiPM-based NaIL scintillator detector

Frequency gradient analysis (FGA) neutron-gamma pulse shape discrimination (PSD) based on Fourier transform has proved to be an effective method for discrimination between two types of pulses by simply constructing a discrimination parameter by subtracting the amplitude of the 1st frequency component from the 0th frequency component. However, the discrimination parameter constructed by the above method could not meet the requirements at some lower sample rates, and the dark noise caused using optoelectronic devices such as miniaturized SiPMs array further erodes the difference between the two frequency components. This paper proposes a new discrimination parameter construction method based on FGA for neutron-gamma discrimination, which is referred as mFGA (modified FGA). This discrimination parameter uses the 0th frequency component and other frequency components to enhance the discrimination performance. A neutron detector module consisting of a 25.4 mm× 25.4 mm× 50.8 mm NaI:Tl,6Li (NaIL) scintillator and an array of 8 × 8 SiPMs was established to verify the method of mFGA. The module measured a 252Cf neutron source under three shielding conditions: no shield, 5 cm high-density polyethylene (HDPE), and 10 cm lead brick. The proposed mFGA method was used to calculate the figure of merit (FoM) under each shielding condition and compared to the traditional frequency gradient method (FGA) and the traditional charge comparison method (CCM). The results show that the discrimination performance with the mFGA method is significantly improved. Taking the HDPE shielding group as an example, the performances of the three methods are FoM-FGA =1.14, FoM-mFGA =2.75, FoM-CCM =0.92. At the same time, with the increase of energy, due to the neutron gamma pulse becoming similar, and the discrimination performance of FGA and CCM decrease significantly. The discrimination performance of the mFGA method is relatively stable in all energy regions. Therefore, the proposed method is superior to the traditional FGA of the 0th frequency minus the 1st frequency and has a good application prospect for neutron-gamma discrimination with detectors of poor signal quality.

Optimization of digital neutron-gamma discrimination methods in time and frequency domain

Four digital methods are investigated for neutron-gamma discrimination in organic scintillation detectors. A fast-digital pulse processing system has been used to optimize the PSD methods and to investigate a mixed radiation field with light output in the range of 100 keV to 5 MeV from an Am-Be source. The methods used for pulse shape discrimination are the charge comparison, the simplified digital charge collection, the frequency gradient analysis, and the discrete wavelet transform method. The performance of each of these methods has been assessed by calculating the figure-of-merit and the probability of misclassification. It has been found that the frequency-domain algorithms perform more effectively for low-energy pulses and require a smaller processing gate width than the time-domain methods. They are therefore more suited to environments with high count rates where pulse pileup is a common attribute of data. In addition, frequency-domain methods are more resistant to random noise present in the dataset compared to time-domain methods.

Neutron-gamma discrimination with broaden the lower limit of energy threshold using BP neural network

Neutron-gamma discrimination is a tough and significative in experimental neutrons measurements procedure, especially for low-energy neutrons signal discrimination. In this work, based on the Pulse Shape Discrimination (PSD) and Back-Propagation (BP) artificial neural networks, a neutron-gamma discrimination method is developed to broaden the lower limit of energy threshold with the hidden layer of 20 neurons. Compared with neutron-gamma discrimination method based on PSD only, the developed neutron-gamma discrimination method based on the PSD and BP-ANN can discriminate neutron and gamma-ray signals with low energy threshold, which can discriminate signals up to 99.93%. Moreover, this work can reduce the energy threshold from 350 keV to 70 keV, as well as the acquired data utilization increased from 60% to more than 99.9%, which overcome the hardware limitations and distinguish neutron and gamma-ray signals, effectively. The developed neutron-gamma discrimination method and the trained neural network can be directly used to other experimental neutrons measurements.

Towards the next generation of detectors for n-γ capture reactions at n_TOF (CERN)

Benzene-d6 has been the scintillation material of choice for performing most of the neutron-capture cross-section measurements at CERN n_TOF for more than 20 years. Recently a revamping of solidstate Stilbene scintillators has been justified by their good timing performances, lack of toxicity and excellent neutron-gamma discrimination by Pulse-Shape Analysis. Consequently, several measurements were recently performed at the n_TOF facility at CERN and INFN-Catania to characterize their performance. We benchmarked both regular and deuterated stilbene scintillation crystals in EAR2@CERN. Based on these results, we are developing and designing a new generation of detectors with enhanced detection sensitivity and improved safety and maintenance conditions.

The effect of PPO concentration on the scintillation properties of a polystyrene based plastic scintillator

Abstract Plastic scintillator detectors are widely used in industry, medicine, nuclear research, and fundamental particle research. Numerous studies worldwide aim to gain better insight into and optimize this detector. In this study, polystyrene-based plastic scintillators were fabricated through thermal polymerization without initiator and with different wt% of PPO (2, 5, 10, 15, and 30 wt%) to examine the effect of PPO on scintillation properties and pulse shape discrimination. The features of these scintillators were compared and investigated. The results showed an optimal light yield at 15 wt% PPO. However, the neutron-gamma discrimination was directly related to the PPO concentration, so that for 30 wt% PPO, FOM and peak-to-valley ratio were 1.57 and 4.6 respectively. The aging test of plastic scintillators has shown an inverse relationship between the concentration of PPO and their lifespan.

Improving Neutron-gamma discrimination in CLYC with Gaussian mixture model

Neutron and gamma discrimination is a common issue in neutron detection. Cs 2 LiYCl 6:Ce (CLYC) crystal, with its unique core-to-valence luminescence (CVL) mechanism for gamma rays, has excellent capability for neutron-gamma discrimination. This paper proposes a new preprocessing method called constant fraction alignment (CFA), based on the fast rise and slow decay characteristics of CLYC, to effectively improve discrimination performance. Unsupervised classification methods that do not require training data have a great advantage since pure neutron sources are difficult to obtain. As an unsupervised clustering method, Gaussian mixture model (GMM) is used to achieve neutron-gamma discrimination of data detected by CLYC, and the impact of different parameters on GMM results is studied. When the input dimension is high, GMM not only requires significantly more time but also reduces precision, so dimensionality reduction is necessary. Principal component analysis (PCA) is a commonly used dimensionality reduction method, and through analysis, it is found that using the first three components of PCA as inputs achieves the best performance. In the GMM solving process, selecting different covariance matrices based on data types can reduce running time while maintaining high accuracy. Diagonal mode is the most suitable according to comparison. Based on the same dataset, the accuracy of GMM is higher than that of charge comparison method and k-means++, with an accuracy of 99.96% for 252 Cf source and a false alarm rate as low as 0.01% for 137 Cs source.

A low-power neutron and gamma-ray detector for environmental radiation monitoring using CLYC scintillator

This paper describes a low-power neutron and gamma-ray detector based on a CLYC scintillator enriched with 96% 6Li for environmental radiation monitoring. The detector is designed in compliance with the IP66 standard having water and dust release capability. The power consumption of the detector is 3.5 W, and the operating temperature is from -15° to +40°. The energy response range for gamma rays is 40 keV to 3 MeV, while the energy resolution of the detector is 4.8% (662 keV). A standard figure of merit (FOM) is used to evaluate neutron-gamma discrimination, achieving a value of 3.42. The mixed neutron-gamma environment was simulated at the Back-n neutron beam of the China Spallation Neutron Source (CSNS). The test results show that the detector can detect the changes in the gamma dose and neutron count rates when the beam is turned on and off in real-time. The proposed detector is suitable for the application of long-term environmental radiation monitoring for nuclear facilities or buildings housing radioactive sources.

Study on neutron–gamma discrimination method based on the KPCA-GMM

Neutron–gamma discrimination plays a fundamental role in the fields of radiation protection and nuclide identification. In this paper, the neutron–gamma discrimination algorithm based on the combination of the kernel principal component analysis (KPCA) and the gaussian mixture model (GMM) was studied. The EJ309 liquid scintillation detector was used to detect two radioisotope neutron sources (252Cf and 241Am-Be). KPCA was used to reduce the dimension of the characteristic value of the pulse signal, GMM was used to cluster the dimensionality reduction results. The suitability of silhouette coefficient (S) as a discriminating index of traditional method and machine learning method was studied. The KPCA-GMM was compared with charge comparison method (CCM) and frequency gradient method (FGA) by using silhouette coefficient. The results show that the KPCA-GMM has higher discrimination accuracy. In the radiation field of 252Cf and 241Am-Be, the S of the KPCA-GMM reached 0.91 and 0.93, which were higher than those of CCM (0.86 and 0.86) and FGA (0.85 and 0.84). Therefore, the KPCA-GMM has good generalization ability and can be used for neutron–gamma discrimination.

Bulk growth of unidirectional 1, 3, 5-Triphenylbenzene (TPB) single crystal for fast neutron detection by time of flight technique

The organic scintillator crystal 1,3,5-Triphenylbenzene (TPB) is a promising material for high-energy particle detection applications. The bulk size of unidirectional (<100> plane) TPB cylindrical crystal was grown by the unidirectional growth technique and their optical properties were analyzed to couple with a photomultiplier tube for detector device fabrications. The gamma retorts of the grown cylindrical crystal were tested with varying gamma energy sources ranging from 356 to 1275 keV. The Time of flight (TOF) experimental setup was constructed with a grown TPB crystal and Neutron-Gamma discrimination was demonstrated with a 252Cf fission source. The developed TPB crystal exhibits strong timing characteristics operates consistently and offers a great capability for discrimination over gamma radiations.

Discrimination of piled-up neutron-gamma pulses using charge comparison method and neural network for CLYC detectors

To realize neutron-gamma discrimination of piled-up pulses in high counting rate circumstances, the discrimination performance of the charge comparison method and three neural network models to actual piled-up pulses was studied in this paper. The neural network models, including a residual neural network (ResNet), a convolutional neural network (CNN) and a fully connected neural network (FCNN), were trained and tested by seven kinds of actual experimental data sets, which included the background signals (bg), non-piled-up neutron (n) and gamma (g) pulses as well as piled-up neutron + neutron (n + n), neutron + gamma (n + g), gamma + neutron (g + n), and gamma + gamma (g + g) pulses. The labels of the seven data sets were provided after discriminating by the charge comparison method. The results showed that the charge comparison method could be applied to discriminate piled-up neutron-gamma pulses with the Figure of Merit (FoM) value of 1.0. The integration length has been optimized to be different for piled-up and non-piled-up pulses, but follow the same criterion for neutron and gamma discrimination. The FoM values are worse than that of non-piled-up signals because the baseline fluctuation is very large under high counting rate conditions, which gives lots of interference to pulse shape discrimination. The ResNet model has the highest total prediction accuracy (93.85%) for the seven signal types, and through the comparison and analysis of the inconsistent events discriminated by the charge comparison method and the ResNet model, it is concluded that the discrimination result of the ResNet model is more accurate. These results indicate that both the charge comparison method and residual neural network can be used for complicated n/γ discrimination under high counting rate conditions, and the residual neural network works better.

Temperature Dependences and Gamma Radiation Stability of Liquid Scintillation Cocktails for n–γ Discrimination

To correctly use different devices, including liquid scintillators, operating parameters have to be known and be at disposal. Among many others, the temperature influence and radiation hardness play an important role. The liquid organic scintillators namely EJ-301, EJ-309 (both Eljen Technology), and new custom-made cocktails based on 1-Phenyl-3-(2,4,6-trimethylphenyl)-2-pyrazoline and 2,5-Bis(5-tert-butyl-benzoxazol-2-yl)thiophene fluors have been tested for temperature stability and radiation resistance. The temperature dependence, in terms of neutron-gamma discrimination, was found to be very weak with the temperature coefficient in order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> MeVee/°C. As far as the gamma radiation resistance of scintillators goes, THIO proved to give consistent results almost independently of the absorbed dose. The EJ-301 exhibited the second-best result. EJ-309 was mostly comparable with PYR except for isomerization, which was observed at an absorbed dose from gamma irradiation greater than 10 kGy. In addition, the color change of borosilicate glass, serving as the casing, was noticed causing decreasing in light yield.