Maximum Likelihood Spectrum Decomposition for Isotope Identification and Quantification

J. T. Matta, A. J. Rowe,M. P. Dion,M. J. Willis,A. D. Nicholson, D. E. Archer, H. H. Wightman

IEEE Transactions on Nuclear Science(2022)

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摘要
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 ( 241 Am, 109 Cd, 137 Cs, and 60 Co), the deviations from the certificate values were generally no more than 6% with a few outliers as high as 10%. For 57 Co, 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.
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关键词
Gamma-ray detection,gamma-ray detectors,gamma-ray spectroscopy,isotope identification,maximum likelihood expectation maximization (MLEM),Monte Carlo methods,nuclear measurements,nuclide identification,radioactive decay,semiconductor radiation detectors,spectral analysis,spectral decomposition
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