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Counting-type neutron imaging detectors of the energy-resolved neutron imaging system RADEN at the J-PARC/MLF

机译:能量分辨中子成像系统RADEN的J-PARC / MLF计数型中子成像探测器

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The recently commissioned Energy-Resolved Neutron Imaging System, RADEN, located at the J-PARC Materials and Life Science Experimental Facility (MLF), is the world's first dedicated high-intensity, pulsed neutron imaging instrument. In addition to conventional radiography and tomography, the wide bandwidth and accurate measurement of neutron energy by time-of-flight is utilized to perform energy-resolved neutron imaging. Such techniques allow direct imaging of the macroscopic distribution of microscopic properties of materials in situ, including crystallographic structure and internal strain, nuclide-specific density and temperature distributions, and internal/external magnetic fields. To carry out such measurements in the high-rate, high-background environment at RADEN, we use cutting-edge detector systems, recently developed in Japan, employing micro-pattern detectors or fast Li-glass scintillators with high-speed, Field Programmable Gate Array-based data acquisition. These counting-type detectors offer sub-μs time resolution, high neutron count rates, and event-by-event gamma rejection. The available detectors offer a range of spatial resolutions from 0.3 to 3 mm and counting rates from 0.6 to 8 Mcps. In the present paper, we show the performance of these detectors as measured at RADEN. We also consider planned improvements to the detector systems that will allow us to achieve finer spatial resolutions by several factors and order-of-magnitude higher count rates.
机译:位于J-PARC材料与生命科学实验设施(MLF)上的最近启用的能量分辨中子成像系统RADEN是世界上第一台专用的高强度脉冲中子成像仪。除了常规的射线照相和断层扫描,还利用宽带宽和通过飞行时间对中子能量进行精确测量,以进行能量分辨的中子成像。这样的技术可以直接对材料的微观特性的宏观分布进行直接成像,包括晶体结构和内部应变,核素比密度和温度分布以及内部/外部磁场。为了在RADEN的高速率,高背景环境中进行此类测量,我们使用了日本最新开发的尖端检测器系统,该系统采用了具有高速,现场可编程门的微模式检测器或快速锂玻璃闪烁体基于数组的数据采集。这些计数型探测器提供了亚微秒级的时间分辨率,高中子计数率以及逐事件伽马抑制。可用的探测器提供0.3到3 mm的空间分辨率范围和0.6到8 Mcps的计数率。在本文中,我们显示了在RADEN处测量的这些检测器的性能。我们还考虑了对探测器系统的计划改进,这将使我们能够通过几个因素实现更高的空间分辨率,并获得更高数量级的数量级。

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