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Nuclear resonance fluorescence (NRF) is a promising technique for non-destructive testing (NDT) of isotopic compositions, where a nucleus is excited by absorbing a specific quantum of energy and then de-excites by emitting one or more gamma rays. Recent advancements in gamma-ray sources, particularly inverse Compton scattering (ICS) sources, have enhanced the application of NRF in isotopic analysis. This paper presents the design and optimization of an isotope identification system based on ICS sources and NRF, and provides a quantitative analysis of the system’s detection capabilities. A Monte Carlo simulation code based on Geant4 is developed to model and optimize the system. The optimized system can resolve a 1% mass change in the target material.

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Design and Optimization of an Isotope Identification System Based on Inverse Compton Scattering Source and Nuclear Resonance Fluorescence for Non-destructive Testing

  • 会议论文

  • 发表日期：

    2026年

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  • Hongze Zhang,
  • Zhijun Chi,
  • Yingchao Du,
  • Wenhui Huang,
  • Chuanxiang Tang

摘要

Nuclear resonance fluorescence (NRF) is a promising technique for non-destructive testing (NDT) of isotopic compositions, where a nucleus is excited by absorbing a specific quantum of energy and then de-excites by emitting one or more gamma rays. Recent advancements in gamma-ray sources, particularly inverse Compton scattering (ICS) sources, have enhanced the application of NRF in isotopic analysis. This paper presents the design and optimization of an isotope identification system based on ICS sources and NRF, and provides a quantitative analysis of the system’s detection capabilities. A Monte Carlo simulation code based on Geant4 is developed to model and optimize the system. The optimized system can resolve a 1% mass change in the target material.