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Determination of mass attenuation coefficient of low-Z dosimetric materials ab

bc

A.M. El-Khayatt , A.M. Ali , Vishwanath P. Singh

de

& N.M.

d

Badiger a

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Department of Physics, College of Science, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia b

Reactor Physics Department, NRC, Atomic Energy Authority, 13759 Cairo, Egypt c

Department of Physics, Faculty of Science, Jazan University, Jazan, Kingdom of Saudi Arabia d

Department of Physics, Karnatak University, Dharwad 580003, India e

Health Physics Section, Kaiga Atomic Power Station-3&4, NPCIL, Karwar 581400, India Published online: 18 Dec 2014.

To cite this article: A.M. El-Khayatt, A.M. Ali, Vishwanath P. Singh & N.M. Badiger (2014): Determination of mass attenuation coefficient of low-Z dosimetric materials, Radiation Effects and Defects in Solids: Incorporating Plasma Science and Plasma Technology, DOI: 10.1080/10420150.2014.988626 To link to this article: http://dx.doi.org/10.1080/10420150.2014.988626

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Radiation Effects & Defects in Solids, 2014 http://dx.doi.org/10.1080/10420150.2014.988626

Determination of mass attenuation coefficient of low-Z dosimetric materials

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A.M. El-Khayatta,b∗ , A.M. Alib,c , Vishwanath P. Singhd,e and N.M. Badigerd a Department of Physics, College of Science, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia; b Reactor Physics Department, NRC, Atomic Energy Authority, 13759 Cairo, Egypt; c Department of Physics, Faculty of Science, Jazan University, Jazan, Kingdom of Saudi Arabia; d Department of Physics, Karnatak University, Dharwad 580003, India; e Health Physics Section, Kaiga Atomic Power Station-3&4, NPCIL, Karwar 581400, India

(Received 13 September 2014; final version received 10 November 2014) The mass attenuation coefficients of some low-Z dosimetric materials with potential applications in dosimetry, medical and radiation protection have been investigated using the Monte Carlo simulation code Monte Carlo N-Particle (MCNP). Appreciable variations are noted for the mass attenuation coefficient by changing the photon energy. The MCNP-simulated parameters are compared with the experimental data wherever possible and theoretical values through the WinXcom program. The simulated results obtained by MCNP generally agree well with the experiment and WinXcom predictions for various low-Z dosimetric and tissue substitute materials. In addition, the mass attenuation coefficients around the k-edges for low-Z dosimetric materials estimated from the MCNP code agree very well with WinXcom prediction. Finally, the results indicate that this simulation process can be followed to determine the interaction parameters of gamma rays in such low-Z materials for which there are no satisfactory experimental values available. Keywords: dosimetry; gamma; MC simulate

1.

Introduction

Applications of dosimetric materials and tissue substitutes in radiological protection, medical, radiation physics and radiobiology are essential for exposure monitoring and estimation of the dose. The X- and γ -rays are being measured by different types of dosimeters which are required to be equivalent to human organ and tissues. The dosimeters are being tested for calibration on phantoms made of tissue-equivalent materials. Thermoluminescent dosimetric (TLD) materials are widely used for personnel dose estimation in nuclear reactors, medical and other radiation measurement purposes (1). The TLD are chosen for dose measurement whose radiological properties such as mass attenuation coefficients, effective atomic numbers or electron densities are equivalent to the human organs and tissues or tissue substitutes. A material that exhibits the same radiological properties same as tissue or organ is called tissue substitute or tissue-equivalent materials. The tissue-equivalent materials are being used to understand the radiation interaction properties for the actual human organs and tissues. Polymers are found to be the suitable tissue equivalent and substitute for human organs and phantoms (2). *Corresponding author. Emails: [email protected], [email protected] © 2014 Taylor & Francis

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Water exhibits adequate suitability for tissue equivalence in radiation applications in medical science. The mass attenuation coefficient, µ/ρ, is defined for the photon interaction which is independent of the medium density. It is the fundamental γ -ray interaction parameter that is being used to derive other radiation interaction parameters such as effective atomic number and electron density, energy deposition and shielding effectiveness (3–7). The μ/ρ (cm2 /g) is usually determined empirically by a transmission experiment; using radiation sources with different energies. The μ/ρ experimental values of the dosimetric and tissue substitutes are available for limited energies. Also the experiment procedure is lengthy as it requires radiation sources to include several energies, adjusted fine beam experimental setup, spectrum acquisition system, data analysis and radiation exposure. Presently simulation of the experiment using the Monte Carlo code has been employed to standardize such experimental setups and simulation for different elements and low-Z materials at various energies. Monte Carlo simulations for mass attenuation coefficients of various concretes and heavy metal oxide glasses, recently, have been reported (7–11). Theoretical values for the μ/ρ of all elements and some compounds over wide photon energy range have been tabulated (12). Using such a table one can obtain the value for any compound and for any energy not listed in the table by employing the additivity rule and interpolation techniques. One can save a lot of manual work involved in such an approach, by using, instead, computer programs, such as XMuDat (13), NXcom ((14) and WinXCom (15) or its predecessor, XCOM (12) for calculating photon interaction cross-sections and mass attenuation coefficients for any element, compound or mixture at a wide range of energies. Monte Carlo N-Particle Transport (MCNP) 4 B (16) is a general-purpose Monte Carlo transport code that can track thousands of particles over large energy ranges (up to 100 MeV) and has been benchmarked for various applications. MCNP 4B was used to estimate μ/ρ at different photon energies. The simulation uses a typical fine beam setup for transmission experiments. The transmitted beam of photons is estimated for different thicknesses of the sample. In MCNP simulation, the energies of the photon can be chosen down to the very low region of the photoelectric absorption region. The accuracy of Monte Carlo simulations strongly depends on the accuracy in the probability functions and thus on the cross-section libraries used for photon transport calculations. In the present work, we have utilized the Monte Carlo simulation code MCNP for determination of mass attenuation coefficients of low-Z dosimetric and tissue substitute materials. First mass attenuation coefficients had been simulated for the selected materials and the results were compared with the theoretical values obtained by the WinXcom program and experimental data available in the literatures (17–19). The simulated results obtained by MCNP generally agree well with the experiment and WinXcom predictions for various low-Z dosimetric and tissue substitute materials. The experimental results were referred as 1, 2 and 3, respectively, for (17–19). When no experimental data are available, the present simulation method can be followed.

2.

Materials and methods

The TLD compounds and tissue substitute materials considered in the study are LiF, CaSO4 .2H2 O, CaCO3 , C4 H6 BaO4 , and 3CdSO4·8H2O, CaSO4 , SrSO4 , CdSO4 , BaSO4 , alanine, bakelite and Perspex. The weight fractions of these substances are given in Tables 1 (18,20). The atomic numbers of the elements of these materials vary from 1 to 56. The MCNP4B (16) has been employed for the simulations. Since the problem deals with photon interaction with the desired samples, the MCNP code is run in the photon transport mode only. In addition, it was executed for the mono-energetic isotropic point source in infinite

Radiation Effects & Defects in Solids Table 1.

Elemental composition (by weight). Density (g/cm3)

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Material LiF CaSO4 ·2 H2 O CaCO3 C4 H6 BaO4 3CdSO4 ·8 H2 O CaSO4 SrSO4 CdSO4 BaSO4 Alanine Bakelite Perspex

Figure 1.

3

2.64 2.31 2.71 2.46 3.1 2.32 3.96 4.69 4.5 1.42 1.36 1.18

H

Li

C

N

O

0.2676 0.0234 0.0237 0.0210

0.0792 0.0574 0.0805

F

S

Ca

Sr

Cd

Ba

0.7324 0.5576 0.1200 0.4796 0.1881 0.2506 0.4158 0.4701 0.3484 0.3070 0.2742 0.4044 0.1572 0.3592 0.7749 0.1680 0.5998 0.3196

0.1862 0.2328 0.4004 0.5377 0.1250 0.4382 0.2355 0.2944 0.1746 0.4770 0.1538 0.5392 0.1374 0.5884

The schematic arrangement of the experimental setup transmission method.

medium. The source strength is assigned to unity to represent a normalized source. The photon weight factor is 1 in all cells and zero in the cutoff region (outside the boundary surface of the problem). F4 Tally (flux over detector cell) is concerned with the total cross-section. The geometry setup for our simulation is shown in Figure 1. The geometry setup for our simulation is shown in Figure 1. It is built up from a source and detector collimators separated by 13 cm. The collimators, which were made in a similar manner, are made of lead cylinders with an outer/inner diameter of 12/0.3 cm. The beam and source collimators were, respectively, 16 and 22 cm long. The studied samples have disk forms with different thicknesses and 8 cm diameter. The transmitted beam of photons was estimated for many thicknesses of each sample then the average value was calculated over all thicknesses. The elemental components of the samples were introduced to the MCNP4B code. The simulations have been performed for gamma photons of energies 26.34, 33.2, 59.54, 100, 279.2, 320.07, 514.0, 661.6, 1115.5, 1173.2, 1332.5 keV. MCNP 4B uses the mcplib22 cross-section data file for performing the calculations. Finally, the simulated results pass all statistical checks and have a relative error less than 0.1%.

2.1.

WinXcom program

The µ/ρ values of the selected tissue substitutes and dosimetric materials have been calculated by using WinXcom (15) which uses the Berger and Hubbell Tables (12). The interpolation procedures used for these tables are slightly different from those used by Berger and Hubbell (12).

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The uncertainties in µ/ρ values are about 1% for low-Z (1 < Z < 8) in the Compton region (30 keV to 100 MeV). Hubbell (20) estimated the uncertainties in the mass attenuation coefficients to be of the order of ± 5% below 5 keV and ± 2% up to 10 MeV. Also above 100 MeV photon energy, uncertainties in µ/ρ values may be 5–10% (20). The gamma sources of photon energies above 5 keV are being used in medical, biological, industrial, radioactive source transportation and other shielding applications. Hence, we concluded that our calculated mass attenuation values are accurate to within a few percentages at energies above 5 keV.

BaSO4

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Mas s at t en u at i o n c o ef f i c i en t (cm /g )

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Expt.(1) taken from Shivaling et al. (2004) Expt.(2) taken from Shivaramu et al. (1999)

8 6 4 2 0 -2

K-edge of Ba

C4H2BaO4

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Expt.(1) taken from Shivaling et al. (2004) 10

Expt.(2) taken from Shivaramu et al. (1999)

8 6 4 2 0

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CdSO4

K-edg of Cd

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MCNP WinXcom Expt. (1)

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Expt.(1) taken from Shivaling et al. (2004)

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K-edge of Cd

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Expt.(1) taken from Shivaling et al. (2004) Expt.(2) taken from Shivaramu et al. (1999)

8 6 4 2 0

-2 100

-2

1000

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E (keV) LiF 0.5

Expt.(1) taken from Shivaling et al. (2004)

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CaSO4.H2O 2.0

MCNP WinCom Expt. (1) Expt. (2)

2

2

(f)

MCNP WinXcom Expt. (1)

Mas s at t en u at i o n c o ef f i c i en t (cm /g )

(e) Mas s at t en u at i o n c o ef f i c i en t (cm /g )

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(b)

MCNP WinXcom Expt. (1) Expt. (2)

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0.4

0.3

0.2

0.1

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1.5

Expt.(1) taken from Shivaling et al. (2004) Expt.(2) taken from Shivaramu et al. (1999)

1.0

0.5

0.0

100

1000

E (keV)

100

1000

E (keV)

Figure 2. Mass attenuation coefficients of low-Z dosimetric using Monte Carlo simulation, WinXcom and experiments in photon energy range of 1–1500 keV.

Radiation Effects & Defects in Solids

(g) 3.0

(h)

MCNP WinXcom Expt. (1)

CaCO3

Mas s at t en u at i o n c o ef f i c i en t (cm /g )

2

Expt.(1) taken from Shivaling et al. (2004)

2

CaSO4

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Expt.(1) taken from Shivaling et al. (2004)

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1.0

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0.0

0.0

100

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1000

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(i)18

SrSO4

2

MCNP WinXcom Expt. (1) Expt. (2)

(j)

Expt.(1) taken from Shivaling et al. (2004) Expt.(2) taken from Shivaramu et al. (1999)

ALANINE

0.40

0.35

10 8 6 4 2 0

Expt.(3) taken from Shivaramu et al. (2001)

0.30

0.25

0.20

0.15

0.10

0.05

-2 100

1000

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1000

E (keV) BAKELITE

0.30

(l)

MCNP WinXcom Expt. (3)

PERPEX

0.35

Expt.(3) taken from Shivaramu et al. (2001)

0.25

0.20

0.15

0.10

0.05

MCNP WinXcom Expt. (3)

Expt.(3) taken from Shivaramu et al. (2001) 0.30

0.25

0.20

0.15

0.10

0.05

100

1000

E (keV)

Figure 2.

0.40

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Mas s at t en u at i o n c o ef f i c i en t (cm /g )

0.35

E (keV)

Mas s at t en u at i o n c o ef f i c i en t (cm /g )

(k)

3.

MCNP WinXcom Expt. (3)

2

Mas s at t en u at i o n c o ef f i c i en t (cm /g )

Mas s at t en u at i o n c o ef f i c i en t (cm /g )

16

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Continued.

Results and discussion

The variation of mass attenuation coefficients, μ/ρ, of the selected low-Z dosimetric and tissue substitute materials with photon energy ranging from 1 to 1500 keV is shown in Figure 2. Experimental data and MCNP simulation results of μ/ρ of the low-Z dosimetric and tissue substitute materials at 26.34, 33.2, 59.54, 100, 279.2, 320.07, 514.0, 661.6, 1115.5, 1173.2, 1332.5 keV are also shown in the graph along with WinXcom predictions. From Figure 2, one can find that the MCNP simulation results agree remarkably well with the experiment and WinXcom predictions. It is also observed that the μ/ρ values of the selected dosimetric and tissue substitute materials

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are small when low-Z elements are predominant as shown in Figure 2(j)–(l), whereas large for high-Z as shown in Figure 2(a)–(i). It is known that the μ/ρ is a chemical composition-dependent parameter. Figure 2(a)–(d) presents, respectively, theoretical and simulated values of μ/ρ at 37.44 keV (K-edge of barium), and at very close energy (33.2 keV). As well as Figure 2(h) and 2(e) shows the WinXcom predication at 26.67 keV (K-edge of cadmium) and the simulated value at nearly the same photon energy (26.6 keV). From these figures, good agreement was recorded between the results of the MCNP code and WinXcom program. Hence, we can conclude that the mass attenuation coefficients around the K-edges for low Z-materials estimated from the MCNP code agree very well with WinXcom prediction. A significant deviation between the simulated results and WinXcom predictions was noticed for alanine, bakelite and perpex especially in the energy region 100–500 keV as shown in Figure 2(j)–(l). This deviation can be attributed to different natures of the two employed techniques and the expected differences between the respective databases that were considered for each method. Moreover, it should be noted that these materials only have a low Z-constituents (1 ≤ Z ≤ 8), as shown in Table 1, and this may lead to magnification of the differences.

4.

Conclusions

The Monte Carlo simulation code MCNP was used to calculate mass attenuation coefficients of low-Z dosimetric and tissue substitute materials in the 26.34–1332.5 keV photon energy range. Generally, our simulation results agree remarkably well with experiment and WinXcom predictions. This validates and standardizes our experimental setup for MCNP simulation of gamma photon with low-Z dosimetric materials. Using a suitable value for sample thickness, this setup can be employed to estimate mass attenuation coefficients of the low-Z dosimetric materials for additional energies where experimental results may not be available. Also the study showed that the mass attenuation coefficients around the k-edges for the selected low Z-materials estimated from MCNP code agree very well with WinXcom prediction. Acknowledgements The authors would like to thank cyclotron project, Exp. Nuclear Physics department, Nuclear Research Centre, Atomic Energy Authority, for using MCNP4B code. The authors would like to thank Prof. L. Gerward, Department of Physics, Denmark Technical University for providing WinXCom software.

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