Pulse Shape Discrimination Method Research Articles

Application of wavelet transform in anti-Compton phoswich detector for gamma spectrum

The response of an anti-Compton phoswich detector to gamma rays was investigated using Monte-Carlo method, and the pulses from different crystal cases, including gamma deposition only in the LaBr3(Ce) or CsI(Tl) crystal and coincidence in both crystals, were analyzed. A novel pulse discrimination method for gamma deposition events based on wavelet transform analysis, called SSD (Scale Shape Discrimination), was developed in this study. Compared to the traditional PSD (Pulse Shape Discrimination) method, SSD has the advantage of transforming one-dimensional pulses in the time-domain into two-dimensional time-frequency spectra, providing the more useful features for pulse discrimination. The performances of the Compton suppression and Full-energy peak loss using PSD and SSD methods was studied. The results show that the Compton suppression factor IPSD = 5.12 and ISSD = 5.32, and FEP loss factor PLPSD = 0.0554 and PLSSD = 0.0587. Meanwhile, the influences of the cutoff values for pulse discrimination on the results of I and PL with different method were analyzed.

Study on scintillation properties and proton-induced radiation damage of LaCl[formula omitted] crystals

A Cs2LiYCl6 (CLYC) scintillation crystal is a promising candidate for fast neutron spectroscopy due to its dual mode gamma/neutron capability and good energy resolution. Despite promising features, CLYC’s limited radiation tolerance and inability to separate alpha/proton particles using pulse shape discrimination (PSD) method restrict its applicability in fast neutron spectroscopy. The significant cross-sections for 35Cl(n,p)35S and 35Cl(n, α)32P reactions make 35Cl-containing crystals attractive candidates for fast neutron detection, prompting their development as a promising new solution. This study reports the growth of LaCl3 crystals via the Bridgman technique, enabling further exploration of their scintillation and material properties for fast neutron detection applications. The effects of the proton irradiation on LaCl3 crystals were investigated by irradiating them with a 100 MeV proton beam at the Korea Multi-purpose Accelerator Complex. The study quantified radiation damage by comparing the pre- and post-irradiation scintillation properties and PSD of the LaCl3 crystals. The results of the measurements demonstrate that LaCl3 crystals are promising candidates for applications in fast neutron identification, spectroscopy, and space mission, maintaining performance even under high-radiation environments.

Enabling pulse shape discrimination with commercial ASICs

Fast electronic readout for high-channel density scintillator-based systems is needed for radiation tracking and imaging in a wide range of applications, including nuclear physics, nuclear security and nonproliferation. Programmable electronics, like FPGAs and ASICs, provide a fast way of conditioning and processing the signal in real time. In this paper, we present a pulse shape discrimination (PSD) method based on the shaping circuit of a commercially available ASIC, the Citiroc1A by CAEN Technologies. We used two different shaping times per detector channel to calculate a shaping parameter that enables PSD. Using our new method, neutron and gamma-ray pulses detected by a d12-stilbene scintillator can be effectively discriminated at light output values greater than 0.15MeVee. While not achieving the PSD performance of traditional offline charge integration, our method does not require the transfer of data to a separate system for further processing and enables the direct deployment of high-channel density multi-particle detection systems. Moreover, the availability of a wider range of shaping times than those on the Citiroc1A can potentially further improve the PSD performance.

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.

Measurements of AmBe and PuC spectra using EJ309 and stilbene scintillators

Two organic scintillators (EJ309 and stilbene) with their different detection chains and elaborate software were used to measure neutron spectra of AmBe and PuC sources. Method of shadow cone ensures minimization of scattered neutron influence. To separate neutrons and γ, a modern method of pulse shape discrimination was employed using fast digitizers. Calibration was performed by γ sources and three different methods for the identification of the Compton edge. Spectrometric systems also used different light output functions and unfolding methods. The same spectra were calculated using the MCNP6 code and the JENDL-5 library. The measured and calculated results were mutually compared, and also with the published results available in the literature. Generally, the results agree on the main peaks of neutron spectra but differ in their abundance. The lower limit for the ability to distinguish between neutrons and γ in spectrometry with organic scintillators was found at about 1.5 MeV.

Pulse shape discrimination for the CONUS experiment in the keV and sub-keV regime

Point-contact p-type high-purity germanium detectors (PPC HPGe) are particularly suited for detection of sub-keV nuclear recoils from coherent elastic scattering of neutrinos or light dark matter particles. While these particles are expected to interact homogeneously in the entire detector volume, specific classes of external background radiation preferably deposit their energy close to the semi-active detector surface, in which diffusion processes dominate that subsequently lead to slower rising pulses compared to the ones from the fully active bulk volume. Dedicated studies of their shape are therefore highly beneficial for the understanding and the rejection of these unwanted events. This article reports about the development of a data-driven pulse shape discrimination (PSD) method for the four 1 kg size PPC HPGe detectors of the Conus experiment in the keV and sub-keV regime down to 210 eVee.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{ee}.$$\\end{document} The impact of the electronic noise at such low energies is carefully examined. It is shown that for an acceptance of 90% of the faster signal-like pulses from the bulk volume, approx. 50% of the surface events can be rejected at the energy threshold and that their contribution is fully suppressed above 800 eVee.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{ee}.$$\\end{document} Applied to the Conus background data, such a PSD rejection cut allows to achieve an overall (15-25)%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(15{-}25)\\%$$\\end{document} reduction of the total background budget. The new method allows to improve the sensitivity of future Conus analyses and to refine the corresponding background model in the sub-keV energy region.

A Self-Organizing feature Map neural network for compton suppression in phoswich detector

Scintillation phoswich detectors can be used for particle discrimination and Compton suppression, and their function is based on pulse shape discrimination (PSD) methods. The conventional PSD methods mainly including Rise Time Discrimination (RTD), Rise and Decay time discrimination (R&D), Constant Time Discrimination (CTD), etc., but linear PSD methods have their limitations in processing pulse signals. Neural network tools can achieve nonlinear output by adjusting the weights between neurons during the training, which are suitable for identifying nonlinear signals generated by detectors. The self-organizing feature mapping (SOM) is the most commonly used clustering neural network, which can cluster signals based on their similarity through competitive training of neural networks without prior data. In this study, 3 SOM networks with different size are trained, and after comparison with the single LaBr3:Ce detector, the total accuracy of the phoswich detector using the SOM neural network for discrimination reaches over 99.5%, which is a 7.59% increase in accuracy compared to the RTD method, and the peak-to-total ratio (P/T) is improved by 1.07%.

CLYC as a neutron detector in low background conditions

We report on the thermal neutron flux measurements carried out at the Laboratorio Subterráneo de Canfranc (LSC) with two commercial 2″×2″\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2^{\\prime \\prime } \ imes 2^{\\prime \\prime }$$\\end{document} CLYC detectors. The measurements were performed as part of an experimental campaign at LSC with 3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{3}$$\\end{document}He detectors, for establishing the sensitivity limits and use of CLYCs in low background conditions. A careful characterization of the intrinsic α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} and γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document}-ray background in the detectors was required and done with dedicated measurements. It was found that the α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} activities in the two CLYC crystals differ by a factor of three, and the use of Monte Carlo simulations and a Bayesian unfolding method allowed us to determine the specific α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} activities from the 238\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{238}$$\\end{document}U and 232\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{232}$$\\end{document}Th decay chains. The simulations and unfolding also revealed that the γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document}-ray background registered in the detectors is dominated by the intrinsic activity of the components of the detector such as the aluminum housing and photo-multiplier and that the activity within the crystal is low in comparison. The data from the neutron flux measurements with the two detectors were analyzed with different methodologies: one based on an innovative α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}/neutron pulse shape discrimination method and one based on the subtraction of the intrinsic α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} background that masks the neutron signals in the region of interest. The neutron sensitivity of the CLYCs was calculated by Monte Carlo simulations with MCNP6 and GEANT4. The resulting thermal neutron fluxes are in good agreement with complementary flux measurement performed with 3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{3}$$\\end{document}He detectors, but close to the detection limit imposed by the intrinsic α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} activity.

Measurement of 6Li burn-up reaction rate using a single crystal CVD diamond detector under fast neutron irradiation environment

The study aimed to develop a technique for measuring the 6Li burn-up rate using a single crystal diamond (SCD) detector (SDD) made by chemical vapor deposition (CVD) with a thin lithium fluoride foil. The method relied on pulse shape discrimination (PSD) to separate pulses by nuclear reaction products of 6Li from pulses due to fast neutrons and gamma-rays.By applying the PSD method, the rectangular shape pulses induced by events occurred at the specific depth positions of the SCD, i.e., the incident surface, the ballistic center region (BCR), and the rear surface, were extracted. Thereafter, pulses occurred each specific depth position of the SCD were discriminated according to the pulse width.Due to a short range of nuclear reaction products in the SCD, pulses at the incident surface should be induced by both fast neutrons and nuclear reaction products, although pulses at the BCR are caused by fast neutron only. The study demonstrated that quantitative measurements of nuclear reaction products in the 6Li burn-up reaction under fast neutron irradiation can be achieved using only one SDD by analyzing event rates at the incident surface and in the BCR region.

Optimization and first electronic implementation of the Constant-Fraction Time-Over-Threshold pulse shape discrimination method

In this contribution we report on further investigations of the recently-evaluated Constant-Fraction Time-over-Threshold (CF-ToT) method for neutron/gamma-ray Pulse Shape Discrimination (PSD). The superiority of the CF-ToT PSD method over the constant-threshold (CT-ToT) method was previously demonstrated, down to low neutron energy thresholds of 100 keVee. Here, we report on a quantitative comparison between the traditionally used Charge Comparison (CC) method and the CF-ToT method using a stilbene scintillator coupled to a silicon photomultiplier, implementing an offline analysis of recorded fast-neutron and gamma-ray waveforms. An optimization of the constant fraction value indicates that a 20%-fraction yields the optimum figure-of-merit (FOM) and gamma-ray peak-to-valley (P/V) ratio. The results obtained for a particle energy threshold of 100 keVee (kilo electron Volt electron equivalent) show that the FOM and P/V values achieved with the CF-ToT method are superior to those obtained using the standard CC method. In addition, a first electronic implementation of the CF-ToT method was performed using simple circuitry suitable for multichannel architecture. Initial results obtained with this circuit prototype are presented.

Determination of radioactivity concentration in a LaBr3(Ce) scintillator

Herein, we determined the radioactivity concentration of isotopes in a ϕ1.5′′×1.5′′ LaBr3(Ce) crystal through a series of measurement experiments involving independent analytic approaches based on a single experimental setup. Experimental data was collected under self-triggering and double-coincidence modes operations inside a shielded chamber. During the self-triggering mode operation, the radioactivity concentration of 227Ac was estimated to be 0.00694 ± 0.00003 Bq/cm3 from the measurement of alpha particles using a pulse-shape discrimination method. During the double-coincidence mode operation, the radioactivity concentration of 138La was calculated from the double-coincidence measurement of electron capture and β-decay processes. The radioactivity concentration of 138La in the LaBr3(Ce) crystal was estimated to be 1.394 ± 0.008 Bq/cm3.

Research on the application of pulse shape discrimination method in (n, lcp) reaction cross-section measurements

The China Spallation Neutron Source Back-n white neutron source supplies neutrons with a wide energy range for nuclear data measurements and nuclear techniques. In cross-section measurements of neutron induced light charged-particle emission (n, lcp) reactions at Back-n, the identification of charged particles are usually achieved with the ΔE-E method or a two-dimensional spectrum of the signal amplitude of the particles deposited in the detector and the corresponding neutron energies derived from the time of flight, called amplitude-En method. Nevertheless, a deficiency still exists in the measurement range and the identification performance with these methods. The pulse shape discrimination (PSD) method with a silicon detector is supposed to be a supplement to the amplitude-En and ΔE-E methods. With silicon detectors, experiments have been performed to compare the performance of the amplitude-En and the PSD methods. The PSD method shows a good performance in identifying light charged particles in the MeV neutron energy region. Alphas and tritons emitted from 6Li(n, t) reaction can be identified with the low energy threshold around 2.5 MeV. This provides an effective method for the cross-section measurement of (n, lcp) reactions at Back-n.

Intensity measurement of the surface muon beam of MELODY

A Muon station for science, technology and industry project will be constructed at China Spallation Neutron Source. The Phase I project will provide a surface muon beam with a pulse width of 130 ns at a rate over 105 µ+/pulse. Beam intensity is the key design parameter of this project. Accurate measurement of the intensity is also essential for the calibration of the µSR spectrometer. The key to the surface muon intensity measurement is to distinguish background positrons from muons. A double-stacked scintillator detector based on PMT readout scheme has been proposed, which can determine the intensity of muons and background positrons by using pulse shape discrimination method. Detailed description of the detector principle and simulated results will be presented.

Pulse shape discrimination using a convolutional neural network for organic liquid scintillator signals

A convolutional neural network (CNN) architecture is developed to improve the pulse shape discrimination (PSD) power of the gadolinium-loaded organic liquid scintillation detector to reduce the fast neutron background in the inverse beta decay candidate events of the NEOS-II data. A power spectrum of an event is constructed using a fast Fourier transform of the time domain raw waveforms and put into CNN. An early data set is evaluated by CNN after it is trained using low energy β and α events. The signal-to-background ratio averaged over 1–10 MeV visible energy range is enhanced by more than 20% in the result of the CNN method compared to that of an existing conventional PSD method, and the improvement is even higher in the low energy region.

Efficient pulse shape discrimination using scalogram image masking and decision tree

In radiation detectors, pulse shape discrimination (PSD) is essential for classifying radiation types. Designing efficient PSD method that has high discrimination accuracy and low time consumption is a challenging task. In this paper, an efficient approach is proposed to discriminate neutron and gamma pulses in radiation detectors, where high classification accuracy and low time consumption are presented. The proposed method is based on image processing through the Scalogram representation of the pulses, which is acquired using the continuous wavelet transform (CWT). From the grayscale Scalogram image, the higher energy density region is segmented, where lower effect of noise is located. Furthermore, a mask image is generated to select a portion from the segmented region, where the difference between the neutron and gamma pulses is significant. The discrimination factor is evaluated according to the number of white pixels in the masked image. Machine learning is utilized to provide a regression model for the designed method, where the discrimination time is significantly reduced. The decision tree regression model is used to predict the value of the discrimination factor according to the principal components of the pulse signal. To validate the effectiveness of the proposed method, a performance comparison is conducted with state-of-the art and traditional PSD techniques using synthetic data. Experimental results show that the proposed method outperforms other PSD methods in terms of the figure of merit and the classification accuracy. Moreover, the proposed method provides less time-consuming discrimination compared to recent methods.

Machine learning application for dark matter - background classification in JUNO experiment

Jiangmen underground neutrino observatory (JUNO) has a potential to indirectly detect dark matter (DM), observing neutrino events from annihilations of DM trapped by the gravitational force in the solar core. Weakly interacting massive particle (WIMP) DM candidate with mass > 4 GeV has significant solar capture rate. In this work, we simulate JUNO neutrino events from the most dominated WIMP annihilation channel, . Given the high-energy neutrinos from massive WIMPs, we extend the neutrino-nucleon interactions in the detector to include quasi-elastic (QE) and deep inelastic scatterings (DIS). The most challenging background events in the energy range above 100 MeV is the atmospheric neutrinos (atmo). The pulse shape discrimination (PSD) method is usually applied to distinguish between DM and atmo. In this work, we apply machine learning (ML) techniques to distinguish between the background (BG) atmo and DM neutrino events. We found that the random forest algorithm gives the best results. Using ML, the accuracy of DM-atmo events classification is 93.8% while similar f1-score could be achieved. On the other hand, only 78.1 % accuracy is obtained using conventional PSD with linear regression (LR). The upper limit for spin-dependent DM-proton cross-section with the applied ML is 5.84 × 10−40 cm2 for a 10 GeV WIMP DM which is an improvement over the sensitivity of the LR method of by a factor of ∼ 2.8x.

Model-Based Deep Learning Algorithm for Pulse Shape Discrimination in High Event Rates

Pulse shape discrimination (PSD) is at the core of radioactive particles monitoring. Conventional PSD methods are geared towards low event rates, and struggle in the presence of pileups resulting from high rate. In this work we develop a PSD algorithm that combines classic approaches with deep learning techniques, that is highly suitable for coping with the dramatic challenges associated with classifying pulses in high event rates. Common PSD algorithms for high event rates limit their research to two piled-up pulses. Our algorithm is designed and tested under severe pileup conditions, where three or more pulses were piled-up. We tested the algorithm on simulated data based on Cs2LiYCl6:Ce (CLYC) based detector pulse shapes and compare its performance to both traditional PSD algorithms and data-driven deep neural network (DNN) based algorithms. In high event rates, ranging up to 10 Mcps, the algorithm demonstrates up to 8 times fewer miss-classifications than the traditional normalized cross-correlation (NCC) approach, and up to 1.7 times fewer miss-classifications than a purely data-driven DNN-aided method.

A phoswich alpha/beta detector for monitoring in the site of Fukushima Daiichi Nuclear Power Station

Alpha contamination and high concentrations of beta contamination can be found inside the reactor buildings at the Fukushima Daiichi Nuclear Power Station (FDNPS). This study proposes a newly developed phoswich alpha/beta detector that can discriminate alpha and beta particles emitted from the alpha and beta contaminations in the FDNPS site. The phoswich alpha/beta detector is made up of two layers of scintillators that detect alpha and beta particles. The first layer is an octagonal, 50 mm diameter, 40-μm-thick plastic scintillator that measures alpha particles, while the second layer is an octagonal, 50 mm diameter, 50-μm-thick Gd₂Si₂O₇ (GPS) scintillator that measures beta particles. The combination of the two scintillators improves the ability to distinguish between alpha and beta particles. The two layers of scintillators were optically coupled to an 8 × 8 multianode photomultiplier tube (MA-PMT) with 50 mm × 50 mm through a 3-mm-thick light guide (glass plate). An eight-channel 14-bit 500 MS/s digitizer was fed with four output signals. Python programming was used to analyze the collected voltage waveforms. The pulse shape discrimination (PSD) method was used to detect alpha particles in high beta particle and high gamma-ray (comparable to gamma-ray dose rate near the FDNPS reactor building) environments. Due to a 23.3% full width at half maximum (FWHM) energy resolution for alpha particles, the detector can be used to distinguish between nuclear fuel materials such as plutonium and its radon progeny (Po-214). Moreover, the detector could distinguish alpha particles from 137Cs gamma rays with a dose rate background up to 9.0 mSv/h. It is the first to demonstrate that the developed phoswich detector can be used to discriminate and measure alpha and beta particles of the actual contaminated FDNPS samples. As a result, this detector will be effective as an air monitoring device for alpha and beta radionuclide contamination measurement in real time.

Study on the Possibility of Neutron Gamma Discrimination in GAGG Crystal

The scintillators capable of neutron detection are being the research hotspot recently. In this manuscript, we investigated the possibility of cerium-doped gadolinium aluminium gallium garnet (GAGG: Ce) crystal to achieve neutron gamma discrimination through pulse shape discrimination (PSD) method. PSD is a method based on the principle that the waveforms of scintillation light differ for different particles. The experiments show that it’s hard for single GAGG crystal to distinguish the neutron from the gamma-ray. Therefore, a composite crystal made of gamma-sensitive crystal and GAGG crystal was furtherly developed. Using the 252Cf neutron source, the composite is proven to be capable of discriminating the neutrons from the gamma-ray and the corresponding FOM is 3.33.

Development of EJ-260/CsI(Tl) phoswich detector for [formula omitted]–[formula omitted] discrimination

To realize the discrimination of β particles and γ photons in complex environments, a phoswich detector based on the pulse shape discrimination method was designed. The scintillators EJ-260 and CsI(Tl) are selected for deposition of β particles and γ photons, respectively. The size of the detector was determined by simulating the detector by the Monte Carlo program Geant4. The detector was assembled for testing, and the pulses were collected using a high-frequency digital capture card. After smoothing the pulse and correcting the rise time, the respective energy spectra of β particles and γ photons in the mixed environment were obtained. The figure of merit value of phoswich detector was 6.35, which can effectively discriminate β particles and γ photons. Results indicate the phoswich detector can be used for the β−γ discrimination in the mixed fields and obtain the respective energy spectrum.