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With traditional neutron activation analysis, the increase of sample quality leads to some problems in both irradiation process and measurement process. These problems include the neutron flux gradient in the range of the sample, the decrease of the thermal neutron flux rate around the sample and the influence of self-shielding in the sample in the irradiation process, In the process of measurement, the self-attenuation of γ-ray in the sample and the geometric effect of the sample lead to the effect of the detector on the measurement of characteristic γ-ray emissivity due to the difference in the detection efficiency of each point of the sample. So the neutron activation analysis of mass sample needs to make some additional modifications. By using the neutron activation analysis technique, the content of 24Mg and 28Si in a large amount of flour can be detected, and the content of talc powder in the flour can be given, so that the quality of flour can be monitored. The flour mainly contains C, H, O, N, Ca, and F element, but the main chemical constituent of talc powder is Mg3[Si4010](OH)2. Therefore, the measured content of Si and Mg element can be used to judge whether the flour contains talcum powder and to determine its exact content. When the content of 24Mg and 28Si in flour are measured by the neutron activation analysis, the variation of neutron flux and energy with thickness in the measured sample and the effect of γ-ray self-absorption will have great influence on the measurement results. The relationship between the neutron flux and energy and the thickness of the sample is simulated by MCNP5 (Monte Carlo N-particle transport code system 5), and the neutron fluxes at different thickness of the sample are measured by a 3He proportional counter tube. The results show that the simulation results of MCNP5 are basically consistent with the experimental results. Using the simulation by MCNP5 and the measurements by a sodium iodide detector, the relationship between γ-ray self-absorption effect and sample thickness is studied, and the sample thickness is determined to be 6.6.cm that is adopted as an optimal experimental condition. Based on the simulated data, the function relationship between the counting of 1.779 MeV γ-ray and the thickness of the sample is obtained as follows: A = 1401 + 3815x – 720x2 + 64x3 – 2.8x4 + 0.05x5. The curve trend of the experimental results is basically the same as that of the simulation results.
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Keywords:
- neutron activation analysis /
- MCNP5 /
- gamma ray self-absorption /
- elemental content analysis
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图 1 MCNP模拟示意图
Figure 1. Simulation diagram by MCNP.
图 2 MCNP模拟不同厚度处中子通量
Figure 2. Neutron flux at different thicknesses simulated by MCNP.
图 3 MCNP模拟不同样品厚度处中子能谱
Figure 3. Neutron spectrum simulated by MCNP.
图 5 两条特征γ射线的出射率与样品的厚度的关系
Figure 5. The relation between count rate of radiation and thickness of samples.
图 6 中子通量与样品厚度的关系
Figure 6. The relationship between neutron flux and sample thickness.
图 8 碘化钠探测器测量不同样品γ能谱
Figure 8. Measurement of gamma energy spectra of different samplesby sodium iodide detector.
图 9 γ射线的计数与质量分数10%样品厚度的关系
Figure 9. The relation between count rate of radiation and thickness of quality score 10% sample
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[1] 德·索埃特著 (伍任 译) 1978 中子活化分析 (北京: 原子能出版社) 第1−2页
de Soete D (translated by Wu R) 1978 Neutron Activation Analysis (Beijing: Atomic Energy Press) pp1−2 (in Chinese)
[2] 张兰芝, 倪邦发, 田伟之, 黄东辉, 张桂英, 刘存兄, 王平生, 刘立坤, 李德红 2005 原子能科学技术 3 282
Google Scholar
Zhang L Z, Ni B F, Tian W Z, Huang D H, Zhang G Y, Liu C X, Wang P S, Liu L K, Li D H 2005 Atom. Energy Sci. Technol. 3 282
Google Scholar
[3] 贾文宝, 黑大千, 徐爱国, 陈晓文, 李安民 2011 原子能科学技术 45 1011
Jia W B, Hei D Q, Xu A G, Chen X W, Li A M 2011 Atom. Energy Sc. Technol. 45 1011
[4] Paul R L, Lindstrom R M 2000 J. Radioanalyt. Nucl. Chem. 243 181
Google Scholar
[5] 田永顺, 胡志良, 童剑飞, 陈俊阳, 彭向阳, 梁天娇 2018 物理学报 67 142801
Google Scholar
Tian Y S, Hu Z L, Tong J F, Chen J Y, Peng X Y, Liang T J 2018 Acta Phys. Sin. 67 142801
Google Scholar
[6] 李欣年, 郭俊鹏, 罗文芸, 王传珊, 方晓明, 虞太六 2008 原子能科学技术 42 343
Li X N, Guo J P, Luo W Y, Wang C S, Fang X M, Yu T L 2008 Atom. Energy Sc. Technol. 42 343
[7] 何雄英, 郑世平, 卢小龙, 姚泽恩 2013 强激光与粒子束 25 253
He X Y, Zheng S P, Lu X L, Yao Z E 2013 High Power Laser and Particle Beams 25 253
[8] Lu Y S, Zhao H 2013 Nucl. Electron. Detect. Technol. 33 1527
[9] Rick L P, Dagistan S, Jeremy C C, Christoph B, Richard M L 2015 J. Radioanalyt. Nucl. Chem. 304 189
Google Scholar
[10] 王兴华, 孙洪超, 姚永刚, 肖才锦, 张贵英, 金象春, 华龙, 周四春 2014 同位素 27 251
Google Scholar
Wang X H, Sun H C, Yao Y G, Xiao C J, Zhang G Y, Jin X C, Hua L, Zhou S C 2014 J. Isotopes 27 251
Google Scholar
[11] 张海青, 秦亚丽, 倪邦发, 田伟之, 王平生, 黄东辉, 张贵英, 刘存兄, 肖才锦, 孙洪超, 聂鹏, 陈喆 2010 原子能科学技术 10 1238
Zhang H Q, Qin Y L, Ni B F, Tian W Z, Wang P S, Huang D H, Zhang G Y, Liu C X, Xiao C J, Sun H C, Nie P, Chen Z 2010 Atom. Energy Sci. Technol. 10 1238
[12] 严小松, 刘荣, 鹿心鑫, 蒋励, 王玫, 林菊芳 2012 物理学报 61 102801
Google Scholar
Yan X S, Liu R, Lu X X, Jiang L, Wang M, Lin J F 2012 Acta Phys. Sin. 61 102801
Google Scholar
[13] 李德红, 苏桐龄 2005 大学物理 24 56
Google Scholar
Li D H, Su T L 2005 Univ. Phys. 24 56
Google Scholar
[14] 曹传儒 1981分析化学 3 335
Cao C R 1981 Analyt. Chem. 3 335
[15] 程璨, 贾文宝, 黑大千, 单卿, 凌永生, 张焱 2014 原子能科学技术 48 802
Cheng C, Jia W B, Hei D Q, Shan Q, Ling Y S, Zhang Y 2014 Atom.Energy Sci. Technol. 48 802
[16] 贾文宝, 徐忠锋, 苏桐龄, 张晓民 1999 兰州大学学报 35 89
Google Scholar
Jia W B, Xu Z F, Su T L, Zhang X M 1999 J. Lanzhou Univ. 35 89
Google Scholar
[17] 张海青, 肖才锦, 聂鹏, 秦亚丽, 陈喆, 倪邦发 2008 中国原子能科学研究院年报 2008 151
Zhang H Q, Xiao C J, Nie P, Qin Y L, Chen Z, Ni B F 2008 Annual Report of China Institute of Atomic Energy 2008 151
[18] 孙洪超, 袁国军, 肖才锦, 张紫竹, 杨伟, 金象春, 张贵英, 王平生, 倪邦发 2012 中国原子能科学研究院年报 2012 118
Sun H C, Yuan G J, Xiao C J, Zhang Z Z, Yang W, Jin X C, Zhang G Y, Wang P S, Ni B F 2012 Annual Report of China Institute of Atomic Energy 2012 118
[19] 陈念年, 蔡勇, 张建生, 张建华 2010 计算机工程与应用 46 208
Google Scholar
Chen N N, Cai Y, Zhang J S, Zhang J H 2010 Comput. Engin. Appl. 46 208
Google Scholar
[20] Evaluated Nuclear Data File (ENDF) https://www.nndc.bnl.gov/exfor/servlet/E4sMakeE4 [2019-2-1]
[21] Evaluated Nuclear Data File (ENDF) https://www.nndc.bnl.gov/exfor/endf00.jsp [2018-5-11]
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