Maximum Likelihood Spectrum Decomposition for Isotope Identification and Quantification

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Abstract

A spectral decomposition method has been implemented to identify and quantify isotopic source terms in high-resolution gamma-ray spectroscopy in static geometry and shielding scenarios. Monte Carlo simulations were used to build the response matrix of a shielded high-purity germanium detector monitoring an effluent stream with a Marinelli configuration. The decomposition technique was applied to a series of calibration spectra taken with the detector using a multi-nuclide standard. These results are compared with decay-corrected values from the calibration certificate. For most nuclei in the standard (241Am, 109Cd, 137Cs, and 60Co), the deviations from the certificate values were generally no more than 6% with a few outliers as high as 10%. For 57Co, the radionuclide with the lowest activity, the deviations from the standard reached as high as 25%, driven by the meager statistics in the calibration spectra. In addition, a complete treatment of error propagation for the technique is presented.

Original languageEnglish
Pages (from-to)1212-1224
Number of pages13
JournalIEEE Transactions on Nuclear Science
Volume69
Issue number6
DOIs
StatePublished - Jun 1 2022

Keywords

  • Gamma-ray detection
  • Monte Carlo methods
  • gamma-ray detectors
  • gamma-ray spectroscopy
  • isotope identification
  • maximum likelihood expectation maximization (MLEM)
  • nuclear measurements
  • nuclide identification
  • radioactive decay
  • semiconductor radiation detectors
  • spectral analysis
  • spectral decomposition

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