Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-23T11:48:41.036Z Has data issue: false hasContentIssue false
  • English
  • Français

Monte Carlo Simulation of the X-Ray Fluorescence Spectra from Multielement Homogeneous and Heterogeneous Samples

Published online by Cambridge University Press:  06 March 2019

A. M. Yacout ,
R. P. Gardner  and
K. Verghese
A. M. Yacout
Affiliation:
Center for Engineering Applications of Radioisotopes, North Carolina State University, Raleigh, North Carolina 27695-7909
R. P. Gardner
Affiliation:
Center for Engineering Applications of Radioisotopes, North Carolina State University, Raleigh, North Carolina 27695-7909
K. Verghese
Affiliation:
Center for Engineering Applications of Radioisotopes, North Carolina State University, Raleigh, North Carolina 27695-7909
Get access

Abstract

A Monte Carlo model that predicts the entire photon, spectrum for energy-dispersive X-ray fluorescence (EDXRF) analyzers excited by radio-isotope sources from multielement homogeneous samples is developed and demonstrated. The components of the photon spectrum include: (1) the and Kα and Kβ characteristic primary, secondary and tertiary X rays from both the unscattered and scattered source photons, (2) the characteristic X rays excited by other characteristic X rays that have been scattered, and (3) the scattered source photons from single, double, and multiple scatters in the sample.

The computer code NCSMCXF based on this model has been developed. It is capable of handling up to 20 elements per sample and provides a detailed account of the intensities of the X rays and backscattered source photons per unit source decay as well as a summary of the relative intensities from all elements present in the sample. Cubic splines are used within the code for photoelectric and total scattering cross sections and two-variable cubic splines for angular coherent and incoherent scattering distributions for efficiency in both computation time and storage. The code also provides the pulse-height spectrum of the sample by using the appropriate Si(Li) detector response function. The Monte Carlo predictions for benchmark experimental results on two alloy samples of known composition indicate that the model is very accurate. This approach is capable of replacing most of the experimental work presently required in EDXRF quantitative analysis.

A previous Monte Carlo model that uses the simple assumption of spherical homogeneous particles to approximate sample heterogeneities has been modified to improve the computer execution time requirements for the heterogeneous sample case. A new technique for photon tracking in this medium is used and reduces the computation time requirement by half.

Type
III. XRF Fundamental Parameters and Data Analysis
Information
Advances in X-Ray Analysis , Volume 30: Thirty-Fifth Annual Conference on Applications of X-ray Analysis, August 4-8, 1986 , 1986 , pp. 121 - 132
Copyright
Copyright © International Centre for Diffraction Data 1986

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arinc, F., Wielo polski, L. and Gardner, R.P., 1977, Chapter 20, Linear least-squares analysis of X-ray fluorescence spectra of aerosol samples using pure element library standards and photon excitation, Dzubay, T.G.(ed.), Ann Arbor Science Publishers, Inc., Ann Arbor, Michigan, p. 277.Google Scholar
Berry, P.F., Furuta, T. and Rhodes, J.R., 1969, Particle size effects in radioisotope x-ray spectrometry, Advances in X-Ray Analysis, 12, 612.Google Scholar
Budesinsky, B.W., 1975, Theoretical correction of inter-element effects: system iron + nickel + chromium, X-Ray Spectroscopy, 4, 166— 170.Google Scholar
Criss, J.W. and Birks, L.S., 1968, Calculation methods for fluorescent X-ray spectrometry. Empirical coefficients vs. fundamental parameters, Analytical Chemistry, 40 (7), p p. 1080-1086.Google Scholar
Doster, J.M. and Gardner, R.P., 1982a, The complete spectral response for EDXRF.systems - calculation by Monte Carlo and analysis applications. 1. homogeneous samples, X-Ray Spectrometry, 11, (4), 173.Google Scholar
Doster, J.M. and Gardner, R.P., 1982b, The complete spectral response for EDXRF.systems - calculation by Monte Carlo and analysis applications. 2. heterogeneous samples, X-Ray Spectrometry, 11, (4), 181.Google Scholar
Duncanson, W.E. and Coulson, C.A., 1945, Theoretical shape of the Compton profile for atoms from H. o Ne, Proc. Phys. Soc. Lond., 57, 190.Google Scholar
Gardner, R.P., Betel, D. and Verghese, K., 1973, X-ray fluorescence analysis of heterogeneous material: effects of geometry and secondary fluorescence, International Journal of Applied Radiation and Isotopes, 24, 135.Google Scholar
Gardner, R.P. and Hawthorne, A.R., 1975, Monte Carlo simulation of Xray fluorescence from homogeneous samples including tertiary interelement effects, X-Ray Spectrometry, 4, 138.Google Scholar
Gardner, R.P. and Doster, J.M., 1982, Treatment of the Si(Li) detector response function as a probability density function, Nuclear Instruments and Methods in Physics Research, 198, 381.Google Scholar
Gardner, R.P., Choi, H.K., Mickael, M., Yacout, A.M. and Verghese, K., 1987, Algorithms for forcing scattered radiation to spherical, planar circular, and right cylindrical detectors for Monte Carlo simulation, accepted for publication in Nuclear Science and Engineering.Google Scholar
Sherman, J., 1955, The theoretical derivation of fluorescent X-ray intensities from mixtures, Spectrochimica Acta, 7, 283.Google Scholar
Quittner, P., 1972, “Gamma-Ray Spectroscopy with Particular Reference to Detector and Computer Evaluation Techniques”, Adam Hilger, Ltd., London.Google Scholar
Wielopolski, L. and Gardner, R.P., 1979, Development of the detector response function approach for the library least-squares analysis of energy-dispersive X-ray fluorescence spectra, Advances in X-ray Analysis, 22, pp. 317–323,Google Scholar
Yacout, A.M., Gardner, R.P. and Verghese, K., 1984, Cubic spline techniques for fitting X-ray cross sections, Nuclear Instruments and Methods in Physics Research, 220, 461.Google Scholar
Yacout, A.M., Gardner, R.P. and Verghese, K., 1986, A new mi-empirical model for the X-ray Si(Li) detector response function, “ Nuclear Instruments and Methods in Physics Research, A243, 121.Google Scholar
Yacout, A.M., Verghese, K. and Gardner, R.P., 1986, Cubic spline representation of the two-variable cumulative distribution functions for coherent and incoherent X-ray scattering, X-Ray Spectrometry (in press).Google Scholar
Yacout, A.M., 1986, unpublished Ph.D. thesis, Department of Nuclear Engineering, North Carolina State University, Raleigh, North Carolina.Google Scholar