Optimization of fast neutron and X-ray pulse shape discrimination (PSD) using an EJ276G scintillator in high radiation mixed conditions

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Organic crystalline, liquid, and plastic scintillators with low Z-number materials are commonly used in fast neutron detectors. Pulse shape discrimination (PSD) is used to distinguish neutrons from X-rays because these detectors are affected by X-rays due to Compton scattering during fast neutron measurement. PSD was performed with a 1 x 1 x 3 cm(3) EJ276G plastic scintillator, SiPM, and DAQ (10-bit resolution, 400 MHz) using the charge comparison method, which compares the total charge (Q(body)) and the delayed charge (Q(tail)) from the peak. Most studies have been conducted under laboratory conditions, such as with Cf-252 or Am-241-Be sources. This study will perform PSD in a 15 MeV electron accelerator with a total flux of 6.72 x 10(14) #/sec and an X-ray-to-neutron ratio of up to 4071:1. The PSD was optimized before the measurement in high flux conditions because it was difficult to perform PSD due to the pile-up effect in these conditions. Optimization focused on the figure of merit (FoM), which is an index of PSD performance. To distinguish neutrons from X-rays under these conditions, lead shielding is necessary to reduce the X-ray-to-neutron ratio. We performed Monte Carlo N-Particle Transport Code (MCNP6) simulations to determine the optimal shielding thickness. Fast neutrons interact with lead due to its high density, which results in small neutron energy loss and direction changes by scattering. This effect can affect other pixels as noise. We plan to evaluate the neutron images under high X-ray flux conditions by comparing the images of the MCNP6 simulation results and the measurement results.
Publisher
IOP Publishing Ltd
Issue Date
2022-03
Language
English
Article Type
Article; Proceedings Paper
Citation

JOURNAL OF INSTRUMENTATION, v.17, no.3

ISSN
1748-0221
DOI
10.1088/1748-0221/17/03/C03016
URI
http://hdl.handle.net/10203/296397
Appears in Collection
NE-Journal Papers(저널논문)
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