An inversion decomposition test based on Monte Carlo response matrix on the γ-ray spectra from NaI(Tl) scintillation detector
Autor: | Jianping Cheng, Fang Fang, Qi-Fan Wu, Jin-Hui Qu, Yao-Zong Yang, He Jianfeng |
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Rok vydání: | 2016 |
Předmět: |
Physics
Nuclear and High Energy Physics Photon Physics::Instrumentation and Detectors business.industry Monte Carlo method Detector 020206 networking & telecommunications Inversion (meteorology) 02 engineering and technology Scintillator Spectral line 030218 nuclear medicine & medical imaging Computational physics 03 medical and health sciences 0302 clinical medicine Optics Nuclear Energy and Engineering 0202 electrical engineering electronic engineering information engineering Nuclide business Response spectrum |
Zdroj: | Nuclear Science and Techniques. 27 |
ISSN: | 2210-3147 1001-8042 |
DOI: | 10.1007/s41365-016-0104-8 |
Popis: | The NaI(Tl) scintillation detector has a number of unique advantages, including wide use, high light yield, and its low price. It is difficult to obtain the decomposition of instrument response spectrum because of limitations associated with the NaI(Tl) scintillation detector’s energy resolution. This paper, based on the physical process of γ photons released from decay nuclides, generating an instrument response spectrum, uses the Monte Carlo method to simulate γ photons with NaI(Tl) scintillation detector interaction. The Monte Carlo response matrix is established by different single energy γ-rays with detector effects. The Gold and the improved Boosted-Gold iterative algorithms have also been used in this paper to solve the response matrix parameters through decomposing tests, such as simulating a multi-characteristic energy γ-ray spectrum and simulating synthesized overlapping peaks γ-ray spectrum. An inversion decomposition of the γ instrument response spectrum for measured samples (U series, Th series and U–Th mixed sources, among others) can be achieved under the response matrix. The decomposing spectrum can be better distinguished between the similar energy characteristic peaks, which improve the error levels of activity analysis caused by the overlapping peak with significant effects. |
Databáze: | OpenAIRE |
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