Pulse Shape Discrimination For Background Rejection In Germanium Gamma-Ray Detectors

1989 ◽  
Author(s):  
P. T. Feffer ◽  
D. M. Smith ◽  
R. D. Campbell ◽  
J. H. Primbsch ◽  
R. P. Lin ◽  
...  
Keyword(s):  
Pulse Shape ◽  
Gamma Ray ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination ◽  
Background Rejection ◽  
Gamma Ray Detectors

Solar Flare Energetic Neutral Emission Measurements in the Project Coronas-I

1994 ◽  
Vol 144 ◽  
pp. 635-639
Author(s):  
J. Baláž ◽  
A. V. Dmitriev ◽  
M. A. Kovalevskaya ◽  
K. Kudela ◽  
S. N. Kuznetsov ◽  
...  
Keyword(s):  
Solar Flare ◽  
Energy Range ◽  
Gamma Rays ◽  
Pulse Shape ◽  
Gamma Ray ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination ◽  
Solar Neutron ◽  
Low Altitude

AbstractThe experiment SONG (SOlar Neutron and Gamma rays) for the low altitude satellite CORONAS-I is described. The instrument is capable to provide gamma-ray line and continuum detection in the energy range 0.1 – 100 MeV as well as detection of neutrons with energies above 30 MeV. As a by-product, the electrons in the range 11 – 108 MeV will be measured too. The pulse shape discrimination technique (PSD) is used.

A pulse-shape discrimination method for improving Gamma-ray spectrometry based on a new digital shaping filter

2018 ◽  
Vol 145 ◽  
pp. 193-201 ◽  
Author(s):  
Zhang-jian Qin ◽  
Chuan Chen ◽  
Jun-song Luo ◽  
Xing-hong Xie ◽  
Liang-quan Ge ◽  
...  
Keyword(s):  
Pulse Shape ◽  
Gamma Ray ◽  
Pulse Shape Discrimination ◽  
Gamma Ray Spectrometry ◽  
Shape Discrimination ◽  
Shaping Filter ◽  
Discrimination Method

Polysiloxane scintillators for neutron and gamma-ray pulse shape discrimination

2020 ◽  
Author(s):  
Allison Lim ◽  
Jonathan Arrue ◽  
Paul B. Rose ◽  
Alan Sellinger ◽  
Anna Erickson
Keyword(s):  
Pulse Shape ◽  
Gamma Ray ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination

scholarly journals Application of artificial neural network in neutron/gamma pulse shape discrimination for EJ301 scintillation detector

2021 ◽  
Vol 4 (2) ◽  
pp. first
Author(s):  
Chuân Văn Phan ◽  
Hải Xuân Nguyễn ◽  
Anh Ngọc Nguyễn ◽  
Hải Xuân Phạm ◽  
Phong Xuân Mai ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Energy Region ◽  
Pulse Shape ◽  
Gamma Ray ◽  
Pulse Shape Discrimination ◽  
Shape Discrimination ◽  
Neuron Network ◽  
Neutron Measurement ◽  
Artificial Neural

The scintilator detectors are sensitive to both neutron and gamma radiation. Therefore, right identification of the pulses which generated by neutrons or gamma ray from these detectors plays an important role in neutron measurement by using scintilator detector. In order to improve the ability to pulse shape discrimination (PSD), many PSD techniques have been studied, developed and applied. In this work, we use a basic configuration of a Fully connected Neural network (Fc- Net) where the number of elements of the network is minimum, and each element corresponds to identified specification of neutron or gamma pulses measured by using EJ-301 scintilator detector. The minimum of error principle has been applied for neuron network design; therefore, the accuracy of recognitions did not affect by this reduced network. The obtained results show that the identify accuracy of FcNet is higher than those of digital charge integration (DCI) method. Being tested using 60Co radioactive source, it is shown that, with the application of the FcNet, the accuracy of the gamma pulses discrimination acquires 98.60% in the energy region from 50 to 2000 keV electron equivalent energy (keVee), and 95.59% in the energy region from 50 to 150 keVee. In general, the obtained results indicate that the artificial neural network method can be applied to build neutron/gamma spectrometers with limited hardware.

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