Artificial neural network algorithm for pulse shape discrimination in 2πα and 2πβ particle surface emission rate measurements

To enhance the accuracy of 2πα and 2πβ particle surface emission rate measurements and address the identification issues of nuclides in conventional methods, this study introduces two artificial neural network(ANN) algorithms: back-propagation(BP) and genetic algorithm-based back-propagation(GA-BP). These algorithms classify pulse signals from distinct α and β particles. Their discrimination efficacy is assessed by simulating standard pulse signals and those produced by contaminated sources, mixing α and β particles within the detector. This study initially showcases energy spectrum measurement outcomes, subsequently tests the ANNs on the measurement and validation datasets, and contrasts the pulse shape discrimination efficacy of both algorithms. Experimental findings reveal that the proportional counter's energy resolution is not ideal, thus rendering energy analysis insufficient for distinguishing between 2πα and 2πβ particles. The BP neural network realizes approximately 99% accuracy for 2πα particles and approximately 95% for 2πβ particles, thus surpassing the GA-BP's performance. Additionally, the results suggest enhancing β particle discrimination accuracy by increasing the digital acquisition card's threshold lower limit. This study offers an advanced solution for the 2πα and 2πβ surface emission rate measurement method, presenting superior adaptability and scalability over conventional techniques.

Conceptual design of a Cs2LiLaBr6 scintillator‑based neutron total cross section spectrometer on the back‑n beam line at CSNS

To reduce the experimental uncertainty in the 235 U resonance energy region and improve the detection efficiency for neutron total cross section measurements compared with those obtained with the neutron total cross section spectrometer(NTOX), a dedicated lithium-containing scintillation detector has been developed on the Back-n beam line at the China Spallation Neutron Source. The Fast Scintillator-based Neutron Total Cross Section(FAST) spectrometer has been designed based on a Cs2Li La Br6(CLLB) scintillator considering the γ-ray flash and neutron environment on the Back-n beam line. The response of the CLLB scintillator to neutrons and γ-rays was evaluated with different 6Li/7 Li abundance ratios using Geant4. The neutron-γdiscrimination performance of the CLLB has been simulated considering different scintillation parameters, physical designs,and light readout modes. A cubic 6Li-enriched( > 90%) CLLB scintillator, which has a thickness of 4-9 mm and side length of no less than 50 mm to cover the Φ 50 mm neutron beam at the spectrometer position, has been proposed coupling to a side readout SiPM array to construct the FAST spectrometer. The developed simulation techniques for neutron-γ discrimination performance could provide technical support for other neutron-induced reaction measurements on the Back-n beam line.

Anti-noise performance of the pulse coupled neural network applied in discrimination of neutron and gamma-ray

In this study,the anti-noise performance of a pulse-coupled neural network(PCNN)was investigated in the neutron and gamma-ray(n-γ)discrimination field.The experiments were conducted in two groups.In the first group,radiation pulse signals were pre-processed using a Fourier filter to reduce the original noise in the signals,whereas in the second group,the original noise was left untouched to simulate an extremely high-noise scenario.For each part,artificial Gaussian noise with different intensity levels was added to the signals prior to the discrimination process.In the aforementioned conditions,the performance of the PCNN was evaluated and compared with five other commonly used methods of n-γdiscrimination:(1)zero crossing,(2)charge comparison,(3)vector projection,(4)falling edge percentage slope,and(5)frequency gradient analysis.The experimental results showed that the PCNN method significantly outperforms other methods with outstanding FoM-value at all noise levels.Furthermore,the fluctuations in FoM-value of PCNN were significantly better than those obtained via other methods at most noise levels and only slightly worse than those obtained via the charge comparison and zerocrossing methods under extreme noise conditions.Additionally,the changing patterns and fluctuations of the FoMvalue were evaluated under different noise conditions.Hence,based on the results,the parameter selection strategy of the PCNN was presented.In conclusion,the PCNN method is suitable for use in high-noise application scenarios for n-γdiscrimination because of its stability and remarkable discrimination performance.It does not rely on strict parameter settings and can realize satisfactory performance over a wide parameter range.

Timing properties and pulse shape discrimination of LAB-based liquid scintillator

Linear Alkyl Benzene （LAB） is a promising liquid scintillator solvent in neutrino experiments because it has many appealing properties. The timing properties of LAB-based liquid scintillator have been studied through ultraviolet and ionization excitation in this study. The decay time of LAB, PPO and bis-MSB is found to be 48.6 ns, 1.55 ns and 1.5 ns, respectively. A model can describe the absorption and re-emission process between PPO and bis-MSB perfectly. The energy transfer time between LAB and PPO with different concentrations can be obtained via another model. We also show that the LAB-based liquid scintillator has good （n, γ） and （α, γ） discrimination power.

Trapezoidal pulse shaping for pile-up pulse identification in X-ray spectrometry

Energy resolution is affected by the intrinsic energy resolution of the detector, ballistic deficit, pileup pulses and noise. Pile-up pulses become the dominant factor that degrades energy resolution after the system is established, so pile-up rejection is often applied to obtain good energy resolution by discarding pulses that are expected to be contaminated by pile-up. However, pile-up rejection can reduce count rates and thus lower the measurement precision. In order to improve count rates and maintain energy resolution, a new method of pile-up pulse identification based on trapezoidal pulse shaping is presented. Combined with pulse width discrimination, this method is implemented by recording pulses that are not seriously piled up. Some experimental tests with a Cu-Pb alloy sample are carried out to verify the performance of this method in X-ray spectrometry. The results show that the method can significantly improve count rates without degrading energy resolution.

Novel liquid scintillator radon detector

Purpose Radon is a noble gas,which endangers our health.The liquid scintillator is one of the detector materials used to measure radon in the environment.But there are challenges in measuring radon using a liquid scintillator,such as independent manual operation and long measurement periods.Methods and Results We propose a liquid scintillator detector for the rapid measurement of radon,which is composed of a breathable liquid scintillator probe and photomultiplier tube.Cascade decay recognition and pulse shape discrimination(PSD)were used to select radon events.241 Am4(α)and 90Sr(β)source calibration was used to optimize the PSDfigure of merit of the liquid scintillator,and a 232Th(220Rn)diffusion source was used to verify the function of this novel detector for measuring radon.Conclusion The detector had an integrated design for sampling and measurement,which simplified the measurement steps.Thus,this novel liquid scintillator detector demonstrated promise for use in radon-detection systems.