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Analysis of Biologically-Derived Small Particles—Searching for Geometry Correction Factors Using Monte Carlo Simulation

  • Grzegorz Tylko (a1)

Abstract

A Monte Carlo simulation was used to determine geometry correction factors that increase accuracy of quantitative X-ray microanalysis of laterally semithick biological materials. A model composed of cellulose with homogeneously distributed biological elements and lateral dimensions between 0.5–25 μm was chosen. The specimen was exposed to 5, 10, and 15 keV electrons, the net intensities of characteristic X-rays registered for the elements, and presented as a function of the lateral dimensions of the model. This showed the double decay exponential function fitted the distribution of X-ray intensities in relation to the model size. The applicability of the function as a correction method was successfully tested for 30 specimens with varying composition and dimensions. The value of relative error decreased from ±60% to ±5% when the correction was applied. Moreover, the minimal lateral size of the material was defined, below which the correction is not required. The simulation also revealed that the difference of the weighted sum of Z 2/A between the unknown and the standard could reach 25% without significant influence on the quantitative results. The correction method could be helpful for accurate assessment of elemental composition in biological or organic matrices, when their lateral dimensions are smaller than the distribution range.

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* Corresponding author. E-mail: grzegorz.tylko@uj.edu.pl

References

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Anderson, C.A. & Hasler, M.F. (1966). Extension of electron microprobe techniques to biochemistry by the use of long wavelength X-rays. In Proceedings of the 4th International Conference on X-ray Optics and Microanalysis, Castaing, R., Deschamps, P. & Philibert, J. (Eds.), pp. 310327. Paris, France: Herman.
Armigliato, A. & Rosa, R. (2009). X-ray microanalysis combined with Monte Carlo simulation for the analysis of layered thin films: The case of carbon contamination. Microsc Microanal 15, 99105.
Armstrong, J.T. (1991). Electron Probe Quantification. New York: Plenum Press.
Armstrong, J.T. & Buseck, P.R. (1975). Methods of quantitative analysis of individual microparticles using electron microprobe: Theoretical. Anal Chem 47, 21782192.
Casnati, E., Tartari, A. & Baraldi, C. (1989). An empirical approach to K-shell ionization cross section by electrons. J Phys B 15, 155167.
Choël, M., Deboudt, K., Osán, J., Flament, P. & Van Grieken, R. (2005). Quantitative determination of low-Z number elements in single atmospheric particles on boron substrates by automated scanning electron microscopy—Energy-dispersive X-ray spectrometry. Anal Chem 77, 56865692.
Czyzewski, Z., MacCallum, D.O., Romig, A. & Joy, D.C. (1990). Calculations of Mott scattering cross sections. J Appl Phys 68, 30663072.
Demers, H. & Gauvin, R. (2004). X-ray microanalysis of a coated nonconductive specimen: Monte Carlo simulation. Microsc Microanal 10, 776782.
Gao, D., Kumar, G., Co, C. & Ho, C-C. (2008). Formation of capillary tube-like structures on micropatterned biomaterials. Adv Exp Med Biol 614, 199205.
Gauvin, R. (2007). A universal equation for the emission range of X rays from bulk specimens. Microsc Microanal 13, 354357.
Gauvin, R. & Lifshin, E. (2000). Simulation of X-ray emission from rough surfaces. Mikrochim Acta 132, 201204.
Gauvin, R., Lifshin, E., Demers, H., Horny, P. & Campbell, H. (2006). Win X-ray: A new Monte Carlo program that computes X-ray spectra obtained with a scanning electron microscope. Microsc Microanal 12, 4964.
Goldstein, J.I., Lyman, C.E., Newbury, D.E., Lifshin, E., Echlin, P., Sawyer, L., Joy, D.C. & Michael, J.R. (2003). Scanning Electron Microscopy and X-Ray Microanalysis. New York: Kluwer Academic/Plenum Publishers.
Hovington, P., Drouin, D. & Gauvin, R. (1997). CASINO: A new Monte Carlo code in C language for electron beam interaction—Part I: Description of the program. Scanning 19, 114.
Janik, P., Tylko, G., Ostachowicz, B. & Turnau, K. (2010). Elemental composition of Physarum compressum Alb. et Schw. sporocarps and their structures cultivated on rabbit dung and agar substrates. Microsc Res Tech 73, 11341142.
Joy, D.C. & Luo, S. (1989). An empirical stopping power relationship for low-energy electrons. Scanning 11, 176180.
Król, E., Płachno, B., Adamec, L., Stolarz, M., Dziubińska, H. & Tręcz, K. (2012). Quite a few reasons for calling carnivores “the most wonderful plants in the world.” Annals Bot 109, 4764.
Laskin, A. & Cowin, J.P. (2001). Automated single-particle SEM/EDX analysis of submicrometer particles down to 0.1 μm. Anal Chem 73, 10231029.
McCarthy, J.J. (1980). Analysis of X-ray spectra by filtered least-squares fitting. Scan Elect Microsc II, 259270.
Orłowska, E., Przybyłowicz, W., Orłowski, D., Turnau, K. & Mesjasz-Przybyłowicz, J. (2011). The effect of mycorrhiza on the growth and elemental composition of Ni-hyperaccumulating plant Berkheya coddii Roessler. Environ Pollut 159, 37303738.
Pamula, E., Kokoszka, J., Cholewa-Kowalska, K., Łączka, M., Kantor, L., Niedzwiedzki, L., Reilly, G.C., Filipowska, J., Madej, W., Kołodziejczyk, M., Tylko, G. & Osyczka, A.M. (2011). Degradation, bioactivity, and osteogenic potential of composites made of PLGA and two different sol-gel bioactive glasses. Ann Biomed Eng 39, 21142129.
Ritchi, N.W.M. (2009). Spectrum simulation in DTSA-II. Microsc Microanal 15, 454468.
Ro, C., Osán, J., Szalóki, I., de Hoog, J., Worobiec, A. & Van Grieken, R. (2003). A Monte Carlo program for quantitative electron-induced X-ray analysis of individual particles. Anal Chem 75, 851859.
Roomans, G. (1988). Quantitative X-ray microanalysis of biological specimens. J Elect Microsc Tech 9, 1943.
Roomans, G. (1990). X-ray microanalysis. In Biophysical Electron Microscopy, Hawkes, P.W. & Valdrè, U. (Eds.), pp. 347412. London: Academic Press.
Rosenberg, N. & Morin, C.Z.J.P. (1999). Monte Carlo simulations of coaxial backscattered electrons in SEM. Ultramicroscopy 76, 97105.
Salvat, F., Fernández-Varea, J.M. & Sempau, J. (2008). PENELOPE, A code system for Monte Carlo simulation of electron and photon transport. Issy-les-Moulineaux. France: OECD/Nuclear Energy Agency.
Scott, K. & Ritchie, N.W.M. (2009). Analysis of 3D elemental mapping artifacts in biological specimens using Monte Carlo simulation. J Microsc 233, 331339.
Small, J.A. (2002). The analysis of particles at low accelerating voltages (≤10 keV) with energy—Dispersive X-ray spectroscopy (EDS). J Res Nat Inst Stand Tech 107, 555566.
Storms, H.M., Janssens, K.H., Török, S.B. & Van Grieken, R.E. (1989). Evaluation of the Armstrong-Buseck correction for automated electron probe X-ray microanalysis of particles. X-ray Spectr 18, 4552.
Tylko, G., Banach, Z. & Kilarski, W. (2004). PROZA and CALIBRATION CURVES for quantitative X-ray microanalysis of biological samples. Microchim Acta 144, 271276.
Tylko, G., Dubchak, S., Banach, Z. & Turnau, K. (2010). Monte Carlo simulation for an assessment of standard validity and quantitative X-ray microanalysis in plants. IOP Conf Series Mat Sci Eng 7, 012028.
Wang, M., Chen, L., Chen, S. & Ma, Y. (2012). Alleviation of cadmium-induced root growth inhibition in crop seedlings by nanoparticles. Ecotoxicol Environ Saf 79, 4854.
Warley, A. (1997). X-ray Microanalysis for Biologists. London: Portland Press Ltd.
Wróblewski, J., Müller, R.M., Wróblewski, R. & Roomans, G.M. (1983). Quantitative X-ray microanalysis of semi-thick cryosections. Histochem 77, 447463.
Zapotoczny, Sz., Jurkiewicz, A., Tylko, G., Anielska, T. & Turnau, K. (2007). Accumulation of copper by Acremonium pinkertoniae, a fungus isolated from industrial wastes. Microbiol Res 162, 219228.

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