EFFICIENCY SIMULATION OF A HPGE DETECTOR FOR THE ENVIRONMENTAL RADIOACTIVITY LABORATORY/CDTN USING A MCNP-GAMMAVISION METHOD

2011 International Nuclear Atlantic Conference - INAC 2011 Belo Horizonte,MG, Brazil, October 24-28, 2011 ASSOCIAÇÃO BRASILEIRA DE ENERGIA NUCLEAR - ABEN ISBN: 978-85-99141-04-5 EFFICIENCY SIMULATION OF A HPGE DETECTOR FOR THE ENVIRONMENTAL RADIOACTIVITY LABORATORY/CDTN USING A MCNP-GAMMAVISION METHOD Danilo C. Vasconcelos 1, Claubia Pereira 1, Sergio Gallardo 2, Zildete Rocha 3, Talita O. Santos 2 1 Departamento de Engenharia Nuclear Escola de Engenharia Universidade Federal de Minas Gerais Departamento de Engenharia Nuclear - PCA 1 - Anexo Engenharia, Av. Antônio Carlos, 6627 Campus UFMG CEP 31.270-901, Belo Horizonte, MG, Brazil 2 Departamento de Ingeniería Química y Nuclear Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, Spain 3 Centro de Desenvolvimento da Tecnologia Nuclear / Comissão Nacional de Energia Nuclear (CDTN/CNEN), Laboratório de Trítio, Caixa Postal 941,CEP 30123-970, Belo Horizonte, Minas Gerais, Brazil ABSTRACT A gamma spectrometer including an HPGe detector is commonly used for environmental radioactivity measurements. In this work, a systematic study of the efficiency simulation of an HPGe coaxial detector has been performed in the energy range between 50 and 1500 kev using the Monte Carlo code MCNP. With this aim, a detailed model of the HPGe detector and a Marinelli beaker containing a certified gamma source has been done. Once the Pulse Height Distribution (PHD) registered in the detector is simulated, the efficiency curve is obtained by calculating the net peak areas and taking into account the certified activity of the source. In order to avoid the uncertainty due to the net area calculation, the simulated PHD is treated using the GAMMAVISION program, which is also used in the experimental spectra processing. The simulated and experimental efficiency curves are compared observing a satisfactory agreement. 1. INTRODUCTION A gamma spectrometer including an HPGe (High Purity Germanium) detector is commonly used for environmental radioactivity measurements. The Environmental Radioactivity Laboratory at Tritium - CDTN (Centro de Desenvolvimento da Tecnologia Nuclear) in Belo Horizonte, Brazil undertakes experimental work using this detector for laboratory measurements. To obtain reliable measurements of the environmental radionuclide activity, the knowledge of the absolute peak efficiency of the detector is required. It can be obtained by employing known radioactive standard source homogenously distributed in a Marinelli beaker of same dimension and similar composition. In the present work, the Monte Carlo method was applied complementary for detector efficiency calibration using version 5 of the MCNP code [1]. Monte Carlo N-particles Transport Code (MCNP) is an extremely advanced Monte Carlo program, which contains all the necessary cross-section data for neutron, photon, and electron transport calculations. The use of Monte Carlo simulation of a detector s response to incident photons is becoming increasingly important. Some authors used the MCNP code for Full Energy Peak Efficiency (FEPE) determinations [2].

The version used is suitable for modelling the detector response, since it contains a tally (F8), which is specific for detector Pulse Height Distribution (PHD) determination. Thus, the detector geometry is modelled with MCNP code, which simulates the detection process to obtain spectrum peaks [2]. Marinelli beaker geometries have been considered as well as water containing the standards for the simulation. Results obtained from Monte Carlo simulation have been compared with experimental measurements in order to validate the model. In this kind of semiconductor detectors (HPGe), germanium dead layer extremely affects the efficiency of low-energy photons. For this purpose, the Monte Carlo simulations are very useful to know the effect of the dead layer thickness on the efficiency, due to the fact that this value is normally not well known in experimental measurements. 2.1. Experimental measurements 2. METHODOLOGY A High Purity Germanium coaxial detector system has been used for experimental measurements. The detector model is a Canberra GC1519, with a closed end coaxial geometry. The main performance specifications of the detector are as follows: relative efficiency at 1.33 MeV Co-60 is 18.7%, FWHM resolution of 1.78 kev, FWTM resolution of 3.29 kev both at 1.33 MeV Co-60, and the peak-to-compton ratio for Co-60 is 44.7:1. The crystal diameter is 61mm and the length is 25.5 mm. The core hole diameter is 8 mm, and the core hole length is 15.5 mm. The end cap to crystal distance is 5 mm. The cryostat window material is aluminium with 1.5 mm thickness. The crystal has also a layer composed by Mylar and Kapton in front of the cryostat window. The effective thickness of the dead layer is not well known a cause of the existence of a transition zone between the inactive layer and the active germanium in the crystal whose thickness is very difficult to be accurately estimated, but for this kind of detectors it has been assumed a dead layer of 1.5 mm thick (including the outer and inner electrode thickness). The source used for measurements was a calibration gamma cocktail solution, covering the energy range between 80 and 1400 kev. The radionuclides contained in the source solution are listed in Table 1 together with the main peak energy, the branching ratio and the certified activity. The uncertainty of the experimental efficiency was estimated using the ISO standard [3] from certified activities and counting results. All of the measured gamma spectra were analysed using the GAMMAVISION program [3]. The mixed gamma-ray standard contains the following radionuclides: Ba-133, Cs-134, Cs-137 and Co-60. From the measurement of calibration sources, the experimental efficiencies in the energy range between 80 and 1400 kev were calculated. The experimental efficiency at energy E γ for a given measuring condition is: (1) where N Ei is the net area under the full-energy peak corresponding to Eγ energy photons emitted by a radionuclide with a known activity, A, f is the emission probability, m is the sample mass and t is the counting time [4].

Table 1. Gamma standard properties. Energy Branching (kev) ratio Activity (Bq) Gamma/s Ba-133 81 0.3280 399.738 131.1143 Ba-133 276.4 0.0729 399.738 29.14095 Ba-133 302.9 0.1860 399.738 74.35141 Ba-133 356 0.6230 399.738 249.0372 Ba-133 383.9 0.0884 399.738 35.3369 Co-60 1173.2 0.9999 242.139 67.24008 Co-60 1332.5 0.9999 242.139 460.8927 Cs-134 604.7 0.9760 68.893 58.83507 Cs-134 795.8 0.8540 68.893 242.1392 Cs-137 661.6 0.8510 541.589 242.1392 2.2. The Monte Carlo model A MCNP model has been developed for the system defined by the HP Ge detector and the Marinelli beaker. The Marinelli beaker was filled with water containing the calibration gamma solution sit directly on top of the detector providing relatively high-efficiency geometry, as it can be seen in Figure 1. This figure has been obtained using the Sabrina program [5]. Marinelli beaker Air Gamma solution in water Ge detector Aluminum holder Figure 1. Representation of the Marinelli beaker and the Ge detector.

The F8 (Pulse Height Distribution) tally has been used for photons and electrons. A detailed physics treatment, including photoelectric effect with fluorescence production, incoherent scattering with form factors and pair production, has been considered in the energy range between 0.001 and 2.0 MeV. Simulating electron tracks requires large computation time, but it has been included in the model due to its influence on the spectrum. To decrease computing time, an energy cut off has been used: 30 kev for electron transport and 1 kev for photons. The number of histories has been set to 100 million in order to obtain a relative error less than 1% at every peak centroid. The use of the GEB (Gaussian Energy Broadening) card option provides a spectrum that can be compared with the experimental one in terms of resolution (FWHM and FWTM). The GEB card parameters have been chosen to reproduce the actual resolution calibration. Determination of peak efficiency from MCNP results has been performed applying the same method used by the GAMMAVISION program in experimental measurements. This program obtains the net area of each peak subtracting the background to the gross area of the peak. 3. RESULTS AND DISCUSSION The PHD obtained with MCNP corresponds to one-photon emitted by the source. In order to compare both experimental and simulated PHDs it is necessary to take into account the total number of gamma/s emitted by the source. For this purpose, the calculated PHD has been multiplied by the acquisition live time (86400 s) and by the total number of gamma/s emitted by the calibration gamma cocktail. The comparison of both PHDs is shown in Figure 2. As it can be seen in this figure, it has been achieved a satisfactory agreement between experimental and simulated measurements, even in the peak resolution (FWHM). Figure 2. Comparison of experimental and simulated Pulse Height Distribution.

The Compton edges are well simulated as well as the contribution of each radionuclide. Regarding to the photo peaks, it is important to remark that the simulation slightly overestimates the height of all of them, and consequently the efficiency. Experimental and simulated PHDs have been analyzed with GAMMAVISON in order to obtain the efficiency curve for each case. In Table 2 and Table 3 it can be seen the results of analysis (background counts, net area counts, intensity counts, 1-sigma uncertainty, resolution (FWHM) and efficiency) for experimental and simulated PHDs respectively. In Table 4, the ratio between simulated and experimental efficiency is shown. As it can be seen in this table, the values obtained with MCNP-GAMMAVISION slightly overestimate the efficiency for almost all the energies considered. For the comparison between measured and calculated efficiencies, a method of uncertainty propagation was applied considering a normal distribution with K = 1, providing a confidence level equal to 0.63. In the MCNP calculations, the number of particles simulated has been chosen to achieve a relative error lower than 1% for each energy bin. Table 2. Experimental PHD analysis with GAMMAVISON. Energy (kev) g/s Background Counts Net Area Counts Intensity Counts/s Uncert 1 Sigma (%) FWHM (kev) Efficiency Ba-133 80.98 131.1143 65506 127812 1.479 0.55 1.210 0.011280 Ba-133 276.39 29.14095 23920 27593 0.319 1.00 1.522 0.010947 Ba-133 302.92 74.35141 32934 66324 0.768 0.80 1.517 0.010329 Ba-133 356.01 249.0372 33538 185221 2.144 0.29 1.654 0.008609 Ba-133 383.91 35.3369 18305 25919 0.3 0.96 1.703 0.008490 Cs-134 604.72 67.24008 11310 24544 0.284 1.00 2.142 0.004224 Cs-137 661.58 460.8927 10985 195215 2.259 0.25 2.226 0.004901 Cs-134 795.86 58.83507 6257 15961 0.185 1.06 2.409 0.003144 Co-60 1173.18 242.1392 4945 53259 0.616 0.64 2.990 0.002544 Co-60 1332.5 242.1392 938 47297 0.547 0.48 3.349 0.002259 Table 3. MCNP PHD analysis with GAMMAVISON. Net Energy Background Intensity g/s Area (kev) Counts Counts/s Counts Uncert 1 Sigma (%) FWHM (kev) Efficiency Ba-133 80.98 131.1143 59300 128306 1.485 0.54 1.525 0.011328 Ba-133 276.39 29.14095 23121 30467 0.353 1.2 1.514 0.012102 Ba-133 302.92 74.35141 23692 70458 0.815 0.62 1.404 0.010969 Ba-133 356.01 249.0372 16219 195623 2.264 0.26 1.441 0.009092 Ba-133 383.91 35.3369 17780 26739 0.309 1.27 1.392 0.008760 Cs-134 604.72 67.24008 6543 30457 0.353 0.85 1.59 0.005245 Cs-137 661.58 460.8927 3689 188923 2.187 0.23 1.561 0.004725 Cs-134 795.86 58.83507 3727 20202 0.204 0.82 1.639 0.003510 Co-60 1173.18 242.1392 1897 57576 0.666 0.43 1.837 0.002752 Co-60 1332.5 242.1392 74 51605 0.597 0.44 1.992 0.002467

Table 4. Experimental and simulated efficiency obtained with GAMMAVISION. Energy Experimental MCNP Ratio (kev) efficiency efficiency MCNP/Exp Ba-133 80.98 0.011280 0.011328 1.00 Ba-133 276.39 0.010947 0.012102 1.11 Ba-133 302.92 0.010329 0.010969 1.08 Ba-133 356.01 0.008609 0.009092 1.07 Ba-133 383.91 0.008490 0.008760 1.03 Cs-134 604.72 0.004224 0.005245 1.12 Cs-137 661.58 0.004901 0.004725 0.98 Cs-134 795.86 0.003144 0.003510 1.11 Co-60 1173.18 0.002544 0.002752 1.10 Co-60 1332.5 0.002259 0.002467 1.12 Figure 3 shows the efficiency curve as a function of energy, for the ten experimental and simulated peaks studied. The efficiency of the detector varies with the incident photon energy and their interactions with the active volume. The maximum ratio MCNP/experiment is 1.12 corresponding to Cs-134 and Co-60. Figure 3. Experimental and simulated efficiency. Experimental errors have been characterized considering the uncertainty of standard cocktail provided by manufacturer and errors due to the experimental measurements. MCNP error is less than 1% for every efficiency value, so error bars cannot be seen in figure.

For the energy range considered, one of the most important parameter on the detection efficiency is the dead layer thickness. In order to analyze its effect, different MCNP models have been developed varying the dead layer (0.5, 1.0, 1.25 and 1.50 mm). When the dead layer increases, the low-energy efficiency decreases due to the fact that the low-energy photons do not reach the active detection volume. As it can be seen in the Figure 4 and Table 5, the effect is more evident for Ba-133, as expected. Normally, the precise dead layer value is not well known, and this kind of analysis can be useful for understanding its effect. When the dead layer thickness is increased from 0.5 to 1.5 mm, the ratio MCNP/Experiment is reduced from 2.11 to 1.0 in the case of Ba-133 (80.99 kev). This effect is also important in the higher energy range. In this case, the ratio MCNP/Experiment varies from 1.44 to 1.12 for Co-60 1.33 MeV. Figure 4. Dead layer thickness effect on detection efficiency. However, in the case of Co-60, there is also another effect to be considered: the true coincidence effect. The effect of coincidence summing on efficiency calibration has been taken into account dividing experimental efficiencies by the correction factors (0.93 and 0.932 for each Co-60 gamma line). It is important to remark that these factors are only valid for aqueous solutions [6]. True coincidence is not taken into account in MCNP.

Table 5. Dead layer thickness effect on detection efficiency. Ratio MCNP/Experiment. Energy Ratio model 1 Ratio model 2 Ratio model 3 Ratio model 4 (kev) /Experimental /Experimental /Experimental /Experimental Ba-133 80.99 1.00 1.17 1.43 2.11 Ba-133 276.48 1.11 1.18 1.27 1.42 Ba-133 302.73 1.08 1.15 1.21 1.37 Ba-133 355.98 1.07 1.16 1.24 1.36 Ba-133 383.76 1.03 1.11 1.17 1.31 Cs-134 604.4 1.12 1.19 1.28 1.45 Cs-137 661.48 0.98 1.04 1.12 1.26 Cs-134 795.64 1.30 1.40 1.51 1.66 Co-60 1173.22 1.10 1.17 1.25 1.42 Co-60 1331.85 1.12 1.19 1.27 1.44 Model 1: 1.5 mm; Model 2: 1.25 mm; Model 3: 1.0 mm and Model 4: 0.5 mm. The active volume of the detector also determines de efficiency of detection. If the geometrical dimensions of the crystal are fixed and dead layer is supposed to be known, then the only parameter affecting to the active volume is the core hole of the crystal. In order to test the importance of this hole, some MCNP models have been performed varying the diameter of the core hole (3, 4 and 5 mm). In Figure 5, it is represented the detector efficiency when the core hole diameter varies. It can be seen, that the effect is almost negligible for this energy range. It can be stated that the most important parameter affecting the detector efficiency is the dead layer thickness. Figure 5. Core hole diameter effect on detection efficiency.

4. CONCLUSIONS The MCNP code, based on the Monte Carlo method, is a useful tool to calibrate in efficiency an HP Ge detector as those commonly used in Environmental Radioactivity laboratories. The combined method MCNP-GAMMAVISION permits to compare the efficiency curve obtained by simulation with the experimental curve, avoiding errors and deviations due to the calculation method of the net peak area. The agreement between simulated and experimental efficiencies is satisfactory and allows studying relevant design parameters of this kind of detectors. Dead layer thickness is one of the most important parameter affecting the efficiency of the detection system. The effect of this parameter is more important at lowenergy range (below 400 kev), but it is not negligible for the high-energy range (up to Co- 60). It is stated that, for these conditions, the variation of the equivalent volume of the inner core hole is not relevant for the detection efficiency. ACKNOWLEDGMENTS The authors thank to the Centro de Desenvolvimento da Tecnologia Nuclear CDTN/CNEN, where this study was carried out. The authors also are grateful to FAPEMIG, CNPq and CAPES for financial assistance. REFERENCES 1. Briesmeister, J.F., MCNP A general Monte Carlo code for neutron and photon transport, version 5, Los Alamos National Laboratory, Report LA-12625-M, 2003. 2. Ródenas, J.; Gallardo, S.; Ballester, S.; Primault, V.; Ortiz, J. Application of the Monte Carlo method to the analysis of measurement geometries for the calibration of a HP Ge detector in an environmental radioactivity laboratory. Nuclear Instruments and Methods in Physics Research B 263, 144 148, 2007. 3. GammaVision, Gamma-ray Spectrum Analysis and MCA Emulation for MS Windows, Software User s Manual, version 32, V5.10. 4. Debertin, K., Helmer, R.G. Gamma and X-Ray Spectrometry with Semiconductor Detectors. North-Holland, Amsterdam, 1988. 5. K. A. Van Riper, Sabrina User s Guide Windows version, ed. White Rock Science, White Rock, NM, USA 2003. 6. D. Arnold, O. Sima, Extension of the efficiency calibration of germanium detectors using the GESPECOR software, Appl. Radiat. Isotopes 61 (2004) 117.