Material optimization in dual particle detectors by comparing advanced scintillating materials using two Monte Carlo codes

H. Al Hamrashdi*, D. Cheneler, S. D. Monk

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

5 اقتباسات (Scopus)

ملخص

A new generation of scintillating materials have been recently developed in the radiation-imaging field offering very promising dual particle detection abilities. Here, four different scintillating materials (Cs2LiYCl6:Ce (CLYC), 95% 6Li enriched Cs2LiYCl6:Ce (CLYC-6), natural Li-glass scintillator (GS10) and liquid scintillator EJ-309) have been characterized for their abilities to attenuate thermal neutrons, fast neutrons and gamma-rays. Recent studies regarding these materials overlook these fundamental characteristics, which can directly affect the design process of advanced imaging systems such as Compton cameras and dual particle imaging systems. The response of each featured material to these three types of radiation fields was simulated with two different Monte Carlo codes, MCNP6 and Geant4. The results indicated that among these four materials, natural Li-glass scintillator (GS10) has the highest thermal neutron detection efficiency and the highest elastic scattering efficiencies. However, the attenuation of fast neutrons was found to be the most severe in EJ-309 liquid scintillator. When gamma-rays are considered, it was found that the mass attenuation coefficient of CLYC and CLYC-6 is the highest of the four materials considered when energies lower than 1 MeV are incident. It is intended that this work will lead to the design and the build of an advanced prototype three stage Compton Camera which will be sensitive to both neutrons and Gamma rays.

اللغة الأصليةEnglish
الصفحات (من إلى)163-171
عدد الصفحات9
دوريةNuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
مستوى الصوت869
المعرِّفات الرقمية للأشياء
حالة النشرPublished - أكتوبر 11 2017

ASJC Scopus subject areas

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