A software package for the simulation of neutron activation spectra has been developed. The simulation of the 14 MeV neutron activation gamma ray spectra has been carried out both for cyclic and conventional modes. The simulation allows the prediction of the optimum parameters for a low level of detection. The parameters are irradiation, counting and decay times. The simulation was based on an accurate calculation of various parameters such as the photoelectric yield, detector efficiency and background estimation. Compton effect, single and double escape are also taken into account. This software was extensively tested using the IAEA certified material Sll lake sediment and AI(OH)3 chemical standard. A high agreement between the theoretical simulated spectra and those measured is obtained. The second part of the package implements the optimization of the timing parameters. The Monte Carlo method was used to search within a constrained time space for the optimum condition resulting in the lowest detection limit for a given reaction. In order to illustrate the validity of the optimisation routine, sodium is determined in SL1 using the reaction 23Na(n,u)20F

Idiri, Z

Khelifi, R

Tchantchane, A

English

Research Online

University of Wollongong Research Online University of Wollongong in Dubai - Papers University of Wollongong in Dubai 1996 Gamma ray spectra simulation and optimization in neutron activation analysis R Khelifi Centre de Developpement des Techniques Nucleaires, Algeria A Tchantchane University of Wollongong, tchantch@uow.edu.au Z Idiri Centre de Developpement des Techniques Nucleaires, Algeria Follow this and additional works at: https://ro.uow.edu.au/dubaipapers Recommended Citation Khelifi, R; Tchantchane, A; and Idiri, Z: Gamma ray spectra simulation and optimization in neutron activation analysis 1996, 99-102. https://ro.uow.edu.au/dubaipapers/152 Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: research-pubs@uow.edu.au Pergamon Vacuum/volume 48lnumber l/pages 99 to 10211997 Copyright Q 1996 Elsevier Science Ltd Printed in Great Britain. All rights reserved PII: SOO42-207X(96)00233-3 0042-207x/97 $17.00+.00 Gamma ray spectra simulation and optimization in neutron activation analysis R Khelifi, A Tchantchane and 2 Idiri, Centre de Developpement des Techniques Nucleaires, 2 Bd Frantz Fanon, B. P. 399, Alger Gare, Algeria received 78 February 1996; accepted in revised form 22 July 1996 A software package for the simulation of neutron activation spectra has been developed. The simulation of the 14 MeV neutron activation gamma ray spectra has been carried out both for cyclic and conventional modes. The simulation allows the prediction of the optimum parameters for a low level of detection. The parameters are irradiation, counting and decay times. The simulation was based on an accurate calculation of various parameters such as the photoelectric yield, detector efficiency and background estimation. Compton effect, single and double escape are also taken into account. This software was extensively tested using the IAEA certified material Sll lake sediment and AI( chemical standard. A high agreement between the theoretical simulated spectra and those measured is obtained. The second part of the package implements the optimization of the timing parameters. The Monte Carlo method was used to search within a constrained time space for the optimum condition resulting in the lowest detection limit for a given reaction. In order to illustrate the validity of the optimisation routine, sodium is determined in SL 1 using the reaction 23Na(n,u)20F. Copyright 0 1996 Elsevier Science Ltd Introduction The concept of simulation was initiated in Neutron Activation Analysis in order to predict and estimate some fundamental parameters such as detection limits. El Mugrabi and Guinn’x* have investigated this concept for sample analysis in thermal neutron activation. Several authors have given detection limits for elements with the assumption of zero background noise. Therefore these data cannot be reliable for our needs since the background noise is mostly generated from the activation of elements which are in the sample. Hence the detection limit of a given element may differ from one type of sample to another. A program for the simulation and optimisation of neutron activation analysis is developed in our laboratory. The detection limit is calculated from nuclear data contained in the library which includes neutron induced nuclear reactions, neutron beam intensity and sample composition. The detector response is also considered.’ First photoelectric peaks are modelled by gaussians of width u. The gaussian base is spread over + 3a and - 30. The Compton continuum described by Zykowski modeL4 both the Compton front and the backscatter peak are included in the spectrum. The simple and the double escape peaks are included in the simulated spectrum and treated in the same way as photoelectric peaks. The optimisation of the experimental time parameters (irradiation, counting and decay times) is based on a Monte Carlo approach:’ at each iteration, random values to the time parameters are generated and new elemental detection limits are calculated using the ratio of noise with respect to the intensity of the photoelectric peak. Time parameters giving a minimum detection limit for a given element are set to be the optimum experimental parameters for the analysis of that element. In order to test the reliability of the simulation, two samples, SLl and an aluminium chemical standard AI(O are irradiated with a 14 MeV neutron generator. Experimental and simulated spectra are compared and good agreement is obtained. Further, in order to illustrate the validity of the optimisation routine, sodium is determined in the IAEA reference material SLl where the reaction of interest is 23Na(n,a)20F (‘OF half life = 11 s) and the analytical peak energy is 1634 keV. Software description The simulation software was developed in Fortran 77 on an IBM personal computer. The program requires as input the sample composition, detector characteristics and the data library named ‘LIBRAPID’ (for 14 MeV neutrons) containing nuclear tables of elements’ isotope nuclear abundance, atomic masses, reaction cross sections, isotopic half life and gamma ray energies with their relative intensities. The time parameters (irradiation, decay and counting times) are also entered into the program. The simu- lated spectrum is visualised on the screen. Data related to photo- electric peak reactions, energy, area, resolution, detector efficiency, transmission factors, escape peak areas, Compton ratios and background noise are saved with the simulated spectra. 99 R Khelifi et al: Simulation and optimization in neutron activation analysis Table 1. SLI lake sediment composition used as input for the simulation Element symbol Concentraion (ppm) Element symbol Concentration Element symbol Concentration @mm) (ppm) Element Symbol Concentration (ppm) Sb CU Ag Xe Ge ;is SC Cl 1.31 Se 30.0 Th 0.08 Br 0.01 Hf 25.0 Rb 21.5 AU 5 170.0 V 17.30 Sr 10.0 Mg 2.90 Na 1720 14.0 P 831 6.82 K 15000 4.16 Pb 37.7 113.0 Zr 241 0.01 Ba 639 170.0 Se 117 80.0 Al 89000 29 000.0 Fe 67400 Y 85 Ga 24 Ca 2500 Si 200000 Cr 104 Mn 3400 B 39 Based on a Monte Carlo approach, optimisation of time par- ameters (irradiation, decay and counting) are determined for each element of interest. This method allows us to search for time parameters that give the minimum detection limit for a given element. At each iteration, the three time parameters values are randomly selected within a bounded interval and a new detection limit is calculated using the simulation program. In case the detection limit is improved these new values are kept as being optimum values otherwise they are ignored. The number of iter- ations may be set by the set user. Results and discussion In order to evaluate the performance of the simulation, an IAEA sediment standard ‘SLI lac’ is analysed. The sample (mass of 7.852 g) is irradiated for 600 s using a 14 MeV neutron generator of type SAMES 525. After the irradiation the activity in the sample was measured for 1800 s after letting it decay for 500 s. A hyperpure Germanium detector with a 2 keV resolution and a 20% relative efficiency for 1332 keV gamma energy is used. The detector is coupled to an ORTEC 7150 multichannel analyser. The energy calibration of the detection system is given by: E = 2.73 x channel + 87.70(keV) A neutron flux of 4.8 x IO’cm- s-’ is experimentally determined for the Al(q) Mg reaction having a 568 s half life and 844 KeV gamma ray (Table 1). The experimental parameters of the analysis are shown in Table 2. Figure 1 displays both the experimental gamma ray spectrum and the simulated one for the SLl sample. We note that the annihilation peaks at 5 11 KeV due to 0, + emitters are included in the experimental spectrum. This explains the difference in intensity between the two spectra in the region of 511 KeV. Over- all, the intensity of the simulated spectrum is slightly less than that of the experimental spectrum. This may be due to the fact that not all the possible reactions are included in the input library since part of the continuum background originates from these reactions. However, this difference does not affect very much the detection limit calculations. The marked peaks on spectra are defined in Table 3. The simulation program is further tested with a chemical stan- dard, Al(OH) having a weight of 8.73g. The neutron flux used was 3.1 x lO’cm~‘s- ’ during 180 s. The activity is measured experimental spectrum 19 channel simulated spectrum Figure 1. Experimental and simulated of the sediment IAEA certifies material SL 1. 100 R Khelifi et al: Simulation and optimization in neutron activation analysis Table 2. Experimental conditions Energy = 2.14 x Channel+ 87.36 Resolution = 0.002 Energy+0.2 Solid angle = 1.6467 sr Sample mass = 7.852 g Number of cycles = 1 during 600s after a decay time of 180s. Both the experimental and the simulated spectra obtained are shown, respectively in Figure 2. Since the sample contains essentially Al (34.5%), only the nuclear reactions induced on this element appear on the spectra. The simulated spectrum shows a perfect similarity with the experimental spectrum. The photoelectric peak areas are the same in the two spectra. This software is used to predict the timing parameters for the minimum detection limit of sodium using the 1634 keV analytical peak. As shown in Figure 1, the sodium analytical peak is not The minimum detection limits and the corresponding time parameters are given in Table 4 for SLl. For each element, the execution of the software which is developed on the VAX 785 had taken up to 3 and 34 min where the number of iterations was set to tens of thousands. observed because of the random choice of the timing parameters. Other random timing parameters and number of cycles simulated spectra are displayed in Figure 3(a) and (b). The detection limits obtained are 2523 ppm and 3696ppm, respectively. Whereas the detection limit corresponding to the optimal parameters as determined by the optimisation routine is improved to 1017 ppm. The simulated spectra corresponding to the optimal parameters is illustrated in Figure 3(c). This test demonstrates both the val- idity of the optimisation routine and the utility of the spectra simulation. Conclusions Simulated and experimental spectra are shown to be in good This developed software may be extended to radiative capture agreement and we think that including the Bremstrahlung con- using instead of ‘LIBRAPID’ a different library concerning ther- tribution and the 511 keV annihilation peaks to the simulation induces an increase in the software execution time without improving significantly the simulated spectra. The spectra simu- mal neutron reactions. lation and the optimisation routine together are used to inves- tigate detection limits for a given element of interest as a function of the timing parameters and to determine the optimal ones. Table 3. Peaks’ identification as marked on spectra N’ Energy 1 511 2 757 3 844 4 IO10 5 1014 6 1273 7 1369 Radio N’ Energy Radio NZ Energy Radio. .- annih. 8 1460 K40 15 2167 K38 Esc.2 9 1733 Esc.2 16 2235 Est. 1 Mg27 10 1736 Esc.2 17 2247 Est. 1 Mg27 II 1779 Al28 18 2425 Est. Mg27 I2 1810 Mn56 19 2754 Na24 A129+ Esc.1 13 2029 Est. 20 2758 Na24 Na24 14 2125 P34 experimental spectrum simulated spectrum Figure 2. Experimental and simulated Al(OH), sample 101 R Khelifi et a/: Simulation and optimization in neutron activation analysis Table 4. Results of optimisation: minimum detection limits in SLI Element symbol Al Fe Si Ba Rb Na Ca K Mg F P Mn N Sr Ce Se SC Ti Hf Ag As Half life (s) _. 568 9290 394 153 1220 11 1330 458 53900 27 135 225 598 10100 56 17 18 18 18 44 18 Energy (keV) 844 1810 I273 662 248 1634 1157 2168 1369 197 1779 1434 511 388 757 162 142 142 214 93 142 Irradiation Decay time time (s) (s) ~. 895 9x 1192 505 617 180 559 60 1785 245 33 3 1785 491 1796 60 1790 467 87 3 299 4 589 9 1780 98 2385 494 148 3 49 3 44 3 65 3 44 3 149 3 140 3 Counting Number of Detection limit time (s) cycles (ppm) 1145 I 497 2357 I 1611 139 I 300 557 1 398 2357 1 59 39 I5 1017 3514 I 33977 2159 1 2701 7165 1 782 176 20 288 524 7 717 875 4 3298 2300 I 369 7028 I 121 176 I 134 44 20 214 43 1 479 40 20 4505 43 I 307 132 20 2084 147 20 2054 14cmo - klmbtbn 10 set imdLbicn 60 set decay 3 sac (al decay 10 set (W lrnooo -. carbhp 10 skc mlnulng So set rofcydss: 10 IOfcyCkSlO looom -. 1634 keV (cl 1634 keV I 0 200 400 SO0 SW0 2oo 4oo elm 800 0 200 4oo coo Figure 3. Illustration of spectra corresponding to random timing parameter (a) and (b) vs optimals (c) as determined by the optimization code. 8m References 3. Khelifi, R., Idiri, Z. and Tobbeche, S., Biological Trace Element Resenrch. Humana Press Inc, Vol. 43/44, 1994. 1. Guinn, V.P., Leslie, _I. and Nakazawa, L., J. Radioanal. Chem., 1982, 70,513. 2. Al-Mugrabi, M.A. and Spyrou, N.M., J. Radioanal. and Nucl. Chem. Articles, 1987, 1 lO( 1). 67-77. 4. Zikowsky, L. and Schweikert, E.A., Nucl. Instrum. and Meth., 1978, 155,279-284. S. Press, W.H., Teukolsky, S.A., Vettering, W.T. and Flannery, B.P., Numerical recipes in FORTRAN, 2 edn. Cambridge University Press, 1992, p. 266. 102 

Gamma ray spectra simulation and optimization in neutron activation analysis

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Gamma ray spectra simulation and optimization in neutron activation analysis

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