Maximum Likelihood Spectrum Decomposition for Isotope Identification and Quantification
IEEE Transactions on Nuclear Science(2022)
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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