Radiation from gamma-ray emitting radionuclides poses significant health risks due to its high penetrating power. Currently, no technique offers effective shielding against it. Nevertheless, the rapid increase in the production and application of radionuclides warrants efficient and reliable radionuclide-detection systems. Although conventional scintillation detectors that adopt spectral analysis are widely used for their cost-effectiveness and robustness, their performance can be hindered by factors such as radioactive statistical fluctuations and background radiation. Advanced spectral-processing techniques, including machine-learning approaches, offer improvements; however, they are generally computationally intensive and not suitable for rapid onsite applications. In this study, a novel analytical approach for radionuclide identification based on the ratio of scintillation light output from scintillators with different attenuation properties is proposed. The scintillator assembly comprises four cylindrical scintillators: bismuth germanate (BGO), cerium-doped gadolinium gallium garnet (GAGG:Ce), europium-doped calcium fluoride (CaF2:Eu), and polyvinyltoluene-based plastic scintillators. The deposited energy in each scintillator is simulated using the Monte Carlo N-Particle Transport (MCNP) code, and the amount of scintillation light output (SLO) is calculated by a mathematical light yield model of the scintillator. From the calculated light output, the light output ratios for different scintillator combinations are derived and their dependence on the energy of incident gamma rays is evaluated. This approach exploits a parameter called equivalent energy to estimate the gamma-ray energy, which is then used to identify gamma ray-emitting radionuclides by comparing the results with known intensity-weighted average energies. The proposed method is validated with both monoenergetic and polyenergetic gamma rays using standard gamma-ray data. The results demonstrate that SLO ratio-based approach can effectively identify radionuclides without relying on traditional spectral measurement techniques, offering a promising alternative for rapid and efficient gamma-ray detection and analysis.

中文翻译：

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基于闪烁光输出比的伽马射线发射放射性核素鉴定仿真研究


由于伽马射线发射放射性核素的辐射具有很高的穿透力，因此会对健康构成重大风险。目前，没有技术可以有效地屏蔽它。然而，放射性核素生产和应用的迅速增加保证了高效可靠的放射性核素检测系统。尽管采用光谱分析的传统闪烁探测器因其成本效益和稳健性而被广泛使用，但它们的性能可能会受到放射性统计波动和背景辐射等因素的阻碍。先进的光谱处理技术，包括机器学习方法，提供了改进;但是，它们通常是计算密集型的，不适合快速的现场应用程序。本研究提出了一种基于不同衰减特性闪烁体闪烁光输出比的放射性核素鉴定新分析方法。闪烁体组件包括四个圆柱形闪烁体：锗酸铋 （BGO）、铈掺杂钆镓石榴石 （GAGG：Ce）、铕掺杂氟化钙 （CaF2：Eu） 和聚乙烯基塑料闪烁体。使用蒙特卡洛 N 粒子传输 （MCNP） 代码模拟每个闪烁体中的沉积能量，并通过闪烁体的数学光产率模型计算闪烁光输出 （SLO） 的量。从计算出的光输出中，可以得出不同闪烁体组合的光输出比，并评估它们对入射伽马射线能量的依赖性。 这种方法利用一个称为等效能量的参数来估计伽马射线能量，然后通过将结果与已知的强度加权平均能量进行比较，该能量用于识别发射伽马射线的放射性核素。使用标准 γ 射线数据，在单能和多能 γ 射线中验证了所提出的方法。结果表明，基于 SLO 比率的方法可以在不依赖传统光谱测量技术的情况下有效识别放射性核素，为快速高效的伽马射线探测和分析提供了一种有前途的替代方案。