Abstract
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.
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References
B. Tang, L.Q. Ge, F. Fang et al., The principle of measurement on nuclear radiation (Harbin Engineering University Press, Harbin, 2010), pp. 161–215
R.L. Heath, Scintillation spectrometry Gamma-ray spectrum catalogue, γ-ray spectrometry center Idaho national engineering and environmental laboratory, 2nd edn, vol. 1 (Rev). (1997). doi:10.2172/4033555
C. Mertens, F. Tondeur, C.D. Lellis, P.V. Put, MCNP simulation and spectrum unfolding for an NaI monitor of radioactivity in aquatic systems. Nucl. Instrum. Methods A 580, 118–122 (2007). doi:10.1016/j.nima.2007.05.049
L. Chen, Y.X. Wei, Monte Carlo simulation of γ-ray spectra using a LaBr 3 detector. Nucl. Technol. 32, 142–145 (2009). doi:10.3321/j.issn:0253-3219.2009.02.016
M. Jandel, M. Morháč, J. Kliman et al., Decomposition of continuum γ-ray spectra using synthesized response matrix. Nucl. Instrum. Methods A 516, 172–183 (2004). doi:10.1016/j.nima.2003.07.047
M. Guttormsen, T.S. Tveter, L. Bergholt et al., The unfolding of continuum γ-ray spectra. Nucl. Instrum. Methods A 374, 371–376 (1996). doi:10.1016/0168-9002(96)00197-0
J.L. Zheng, Q.X. Ying, W.L. Yang, Signals and systems (Higher Education Press, Beijing, 2011), pp. 28–130
M. Morháč, J. Kliman, V. Matoušek, M. Veselský et al., Background elimination methods for multidimensional coincidence γ-ray spectra. Nucl. Instrum. Methods A. 401, 113–132 (1997). doi:10.1016/S0168-9002(97)01023-1
P. Bandzuch, M. Morhac, J. Kristiak, Study of the Van Cittert and Gold iterative methods of deconvolutionn and their applicationin the deconvolution of experimental spectra of positron annihilation. Nucl. Instrum. Methods A 384, 506–515 (1997). doi:10.1016/S0168-9002(96)00874-1
R. Vlastou, N.I. Th, M. Kokkoris et al., Monte Carlo simulation of gamma-ray spectra from natural radionuclides recorded by a NaI detector in the marine environment. Appl. Radiat. Isot. 64, 116–123 (2006). doi:10.1016/j.apradiso.2005.07.011
S. Hurtado, M. GarciA-Leon, R. GarciA-Tenorio, Monte Carlo simulation of the response of a germanium detector for low-level spectrometry measurements using GEANT4. Appl. Radiat. Isot. 61, 139–143 (2004). doi:10.1016/j.apradiso.2004.03.035
N. Qian, D.Z. Wang, C. Wang et al., Collimated LaBr 3 detector response function in radioactivity analysis of nuclear waste drums. Nucl. Sci. Technol. 24, 26–31 (2013). doi:10.13538/j.1001-8042/nst.2013.06.006
O. Kadri, F. Gharbi, K. Farah et al., Monte Carlo studies of the Tunisian gamma irradiation facility using GEANT4 code. Appl. Radiat. Isot. 64, 170–177 (2006). doi:10.1016/j.apradiso.2005.07.009
P.H.V. Cittert, Zum Einfluß der Spaltbreite auf die Intensitätsverteilung in Spektrallinien II. Zeitschrift für Physik A Hadrons and Nuclei. 69, 298–308 (1931). doi:10.1007/BF01391351
R. Gold, An iterative unfolding method for response matrices, AEC Research and Development Report ANL-6984, Argonne National Laboratories, Argo. III. (1964). doi:10.2172/4634295
M. Morha’C, V. Matousek, J. Kliman, Efficient algorithm of multidimensional deconvolution and its application to nuclear data processing. Digit. Signal Process. 13, 144–171 (2003). doi:10.1016/S1051-2004(02)00011-8
M.S. Rahman, G. Cho, Unfolding low-energy gamma-ray spectrum obtained with NaI(Tl) in air using matrix inversion method. J. Sci. Res. 2, 221–226 (2010). doi:10.3329/jsr.v2i2.4372
L. Li, X.G. Tuo, M.Z. Liu, High-resolution boosted reconstruction of γ-ray spectra. Nucl. Sci. Tech. 25, 18–24 (2014). doi:10.13538/j.1001-8042/nst.25.050202
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This work is supported by National Natural Science Foundation of China (No. 11365001), National Major Scientific Equipment Development Projects (No. 041514065), Natural Science Foundation of Jiangxi (No. 20161BAB201035), and Fundamental Science on Radioactive Geology and Exploration Technology Laboratory, East China Institute of Technology (No. RGET1316).
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He, JF., Wu, QF., Cheng, JP. et al. An inversion decomposition test based on Monte Carlo response matrix on the γ-ray spectra from NaI(Tl) scintillation detector. NUCL SCI TECH 27, 101 (2016). https://doi.org/10.1007/s41365-016-0104-8
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DOI: https://doi.org/10.1007/s41365-016-0104-8