Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-12T21:40:54.143Z Has data issue: false hasContentIssue false
  • English
  • Français

Development of a New Quantitative X-Ray Microanalysis Method for Electron Microscopy

Published online by Cambridge University Press:  20 October 2010

Paula Horny ,
Eric Lifshin ,
Helen Campbell  and
Raynald Gauvin
Paula Horny*
Affiliation:
Department of Mining and Materials Engineering, McGill University, 3610 University Street, Montréal, Québec H3A 2B2, Canada Département de Génie des Mines, de la Métallurgie et des Matériaux, Université Laval, Québec G1K 7P4, Canada
Eric Lifshin
Affiliation:
College of Nanoscale Science and Engineering, University at Albany—State University of New York, 251 Fuller Road, Albany, NY 12203, USA
Helen Campbell
Affiliation:
Department of Mining and Materials Engineering, McGill University, 3610 University Street, Montréal, Québec H3A 2B2, Canada
Raynald Gauvin
Affiliation:
Department of Mining and Materials Engineering, McGill University, 3610 University Street, Montréal, Québec H3A 2B2, Canada
*
Corresponding author. E-mail: paula.horny@mail.mcgill.ca
Get access

Abstract

Quantitative X-ray microanalysis of thick samples is usually performed by measuring the characteristic X-ray intensities of each element in a sample and in corresponding standards. The ratio of the measured intensities from the unknown material to that from the standard is related to the concentration using the ZAF or ϕ(ρz) equations. Under optimal conditions, accuracies approaching 1% are possible. However, all the experimental conditions must remain the same during the sample and standard measurements. This is not possible with cold field emission scanning electron microscopes (FE-SEMs) where beam current can fluctuate around 5% in its stable regime. Very little work has been done on variable beam current conditions (Griffin, B.J. & Nockolds, C.E., Scanning13, 307–312, 1991), and none relating to cold FE-SEM applications. To address this issue, a new method was developed using a single spectral measurement. It is similar in approach to the Cliff-Lorimer method developed for the analytical transmission electron microscope. However, corrections are made for X rays generated from thick specimens using the ratio of the characteristic X-ray intensities of two elements in the same material. The proposed method utilizes the ratio of the intensity of a characteristic X-ray normalized by the sum of X-ray intensities of all the elements measured for the sample, which should also reduce the amplitude of error propagation. Uncertainties in the physical parameters of X-ray generation are corrected using a calibration factor that must be previously acquired or calculated. As an example, when this method was applied to the calculation of the composition of Au-Cu National Institute of Standards and Technology standards measured with a cold field emission source SEM, relative accuracies better than 5% were obtained.

Keywords

quantitative X-ray microanalysisMonte Carlo simulationfield emission scanning electron microscopestandardless microanalysis
Type
Instrumentation and Software Developments
Information
Microscopy and Microanalysis , Volume 16 , Issue 6 , December 2010 , pp. 821 - 830
Copyright
Copyright © Microscopy Society of America 2010

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

REFERENCES

Bambynek, W., Crasemann, B., Fink, R.W., Freund, H.-U., Mark, H., Swift, C.D., Price, R.E. & Rao, P.V. (1972). X-ray fluorescence yields, auger, and Coster-Kronig transition probabilities. Rev Mod Phys 44(4), 716–813.CrossRefGoogle Scholar
Bastin, G.F., Heijligers, H.J.M. & Vanloo, F.J.J. (1984). The performance of the modified phi(rho-Z) approach as compared to the Love and Scott, Ruste and standard Zaf correction procedures in quantitative electron-probe microanalysis. Scanning 6(2), 58–68.CrossRefGoogle Scholar
Berger, M.J., Hubbell, J.H., Seltzer, S.M., Chang, J., Coursey, J.S., Sukumar, R. & Zucker, D.S. (2005). XCOM: Photon cross sections database. Available at www.physics.nist.gov/PhysRefData/Xcom/Text/XCOM.html.Google Scholar
Bethe, H.A. (1930). Zur theorie des durchgangs schneller korpuskularstrahlen durch materie. Ann Phys 5, 325–400.CrossRefGoogle Scholar
Bote, D. & Salvat, F. (2008). Calculations of inner-shell ionization by electron impact with the distorted-wave and plane-wave Born approximations. Phys Rev A 77(4), 042701-01/24.CrossRefGoogle Scholar
Campbell, J.L. (2003). Fluorescence yields and Coster-Kronig probabilities for the atomic L subshells. At Data Nucl Data Tables 82, 291–315.CrossRefGoogle Scholar
Casnati, E., Tartari, A. & Baraldi, C. (1982). An empirical approach for K-shell ionisation cross-section by electrons. J Phys B 15, 155–167.CrossRefGoogle Scholar
Castaing, R. (1952). Application des sondes électroniques à une méthode d'analyse ponctuell chimique et cristallographique. Thèse de doctorate d'état. Paris: University of Paris, Publication O.N.E.R.A.Google Scholar
Chen, M.H. & Crasemann, B. (1974). M X-ray emission rates in Dirac-Fock approximations. Phys Rev A 30(1), 170–176.CrossRefGoogle Scholar
Chen, M.H. & Crasemann, B. (1983). Radiationless transitions to atomic M1,2,3 shells results of relativistic theory. Phys Rev A 27(6), 1989–1994.CrossRefGoogle Scholar
Cliff, G. & Lorimer, G.W. (1975). The quantitative analysis of thin specimen. J Microsc Oxford 103, 203–207.CrossRefGoogle Scholar
Drouin, D., Hovington, P. & Gauvin, R. (1997). CASINO: A new Monte Carlo code in C language for electron beam interaction—part II: Tabulated values of Mott cross section. Scanning 19, 20–28.CrossRefGoogle Scholar
Duncumb, P. (1957). Microanalysis with a scanning X-ray microscope. In X-ray Microscopy and Microradiography, Cosslet, V.E., Engstrom, A. & Pattee, H.H. (Eds.), pp. 617–625. New York: Academic Press.Google Scholar
Duncumb, P. & Reed, S.J.B. (1968). The electron microprobe microanalysis. NBS Special Publication 298.Washington, DC: National Bureau of Standards, U.S. Department of Commerce.Google Scholar
Duncumb, P. & Shields, P.K. (1966). Effect of critical excitation potential on the absorption correction in X-ray microanalysis. In The Electron Microprobe, McKinley, T.D., Heinrich, K.F.J. & Wittry, D.B. (Eds.), pp. 284–295. New York: Wiley.Google Scholar
Gauvin, R. (1990). Analyse Chimique Quantitative en Microscopie Électronique. Montreal, Canada: École Polytechnique de Montréal.Google Scholar
Gauvin, R., Lifshin, E., Demers, H., Horny, P. & Campbell, H. (2006). Win X-ray, a new Monte Carlo program that computes X-ray spectrum obtained with a scanning electron microscope. Microsc Microanal 12, 49–64.CrossRefGoogle Scholar
Goldstein, J.I., Newbury, D.E., Joy, D.C., Lyman, C.E., Echlin, P., Lifshin, E., Sawyer, L.C. & Michael, J.R. (2003). Scanning Electron Microscopy and X-Ray Microanalysis. New York: Plemum Press.CrossRefGoogle Scholar
Griffin, B.J. & Nockolds, C.E. (1991). A routine correction for electron beam intensity variation during quantitative EDS microanalysis using continuum radiation. Scanning 13, 307–312.CrossRefGoogle Scholar
Heinrich, K.F.J. (1969). Present state of the classical theory of quantitative electron probe microanalysis. NBS Technical Note 521. Washington, DC: National Bureau of Standards, U.S. Department of Commerce.Google Scholar
Heinrich, K.F.J., Myklebust, R.L., Rasberry, S.D. & Michaelis, R.E. (1971). Standard reference materials: Preparation and evaluation of SRM's 481 and 482 gold-silver and gold-copper alloys for microanalysis. Washington, D.C.: National Bureau of Standards.Google Scholar
Henke, B.L., Gullikson, E.M. & Davis, J.C. (1993). X-ray interactions: Photoabsorption, scattering, transmission, and reflection at E = 50–30,000 eV, Z = 1–92. At Data Nucl Data Tables 54, 181–342.CrossRefGoogle Scholar
Henoc, J. (1968). Quantitative electron probe microanalysis. NBS Special Publication 298.Washington, DC: National Bureau of Standards, U.S. Department of Commerce.Google Scholar
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, 1–14.CrossRefGoogle Scholar
Joy, D.C. (2001). Fundamental constants for quantitative X-ray microanalysis. Microsc Microanal 7, 159–167.CrossRefGoogle ScholarPubMed
Joy, D.C. & Luo, S. (1989). An empirical stopping power relationship for low-energy electrons. Scanning 11(4), 176–180.CrossRefGoogle Scholar
Kyser, D.F. & Murata, K. (1974). Quantitative electron-microprobe analysis of thin-films on substrates. IBM J Res Dev 18(4), 352–363.CrossRefGoogle Scholar
Llovet, X., Merlet, C. & Salvat, F. (2000). Measurements of K-shell ionization cross sections of Cr, Ni and Cu by impact of 6.5–40 keV electrons. J Phys B: At Mol Opt Phys 33(18), 3761–3772.CrossRefGoogle Scholar
Lund, M.W. (1995). Current trends in Si(Li) detector windows for light element analysis. In X-Ray Spectrometry in Electron Beam Instruments, Williams, D.B., Goldstein, J.I. & Newbury, D.E. (Eds.), pp. 21–31. New York: Plenum Press.CrossRefGoogle Scholar
McGuire, E.J. (1972). Atomic M-shell Coster-Kronig, auger, and radiative rates, and fluorescence yields for Ca-Th. Phys Rev A 5(3), 1043–1047.CrossRefGoogle Scholar
Merlet, C., Llovet, X. & Salvat, F. (2004). Measurements of absolute K-shell ionization cross sections and L-shell X-ray production cross-section of Ge by electron impact. Phys Rev A 69(3), 032708-1–032708-7.CrossRefGoogle Scholar
Newbury, D.E. & Myklebust, R.L. (1981). Analytical Electron Microscopy. San Francisco, CA: San Francisco Press.Google Scholar
Newbury, D.E., Swyt, C.R. & Myklebust, R.L. (1995). Standardless quantitative electron probe microanalysis with energy-dispersive X-ray spectrometry. Is it worth the risk? Anal Chem 67(11), 1866–1871.CrossRefGoogle ScholarPubMed
Nockolds, C., Cliff, G. & Lorimer, G.W. (1980). Characteristic X-ray fluorescence correction in thin film analysis. Micron 11(3–4), 325–326.Google Scholar
Packwood, R.H. & Brown, J.D. (1981). A Gaussian expression to describe φ(ρz) curves of quantitative electron-probe microanalysis. X-Ray Spectrom 10, 138–146.CrossRefGoogle Scholar
Philibert, J. (1963). A method for calculating the absorption correction in electron probe microanalysis. In X-Ray Optics and X-Ray Microanalysis, Proceedings of the 34rd International Symposium on X-Ray Optics and X-Ray Microanalysis, Pattee, H.H., Cosslett, V.E. & Engström, A. (Eds.), pp. 379–392. New York: Academic Press.Google Scholar
Pouchou, J.-L. & Pichoir, F. (1984). A new model for quantitative X-ray microanalysis 1. Application to the analysis of homogeneous samples. Recherche Aérospatiale 3, 167–192.Google Scholar
Reed, S.J.B. (1965). Characteristic fluorescence correction in electron-probe microanalysis. Brit J Appl Phys 16, 913–926.CrossRefGoogle Scholar
Salvat, F. & Fernandez-Varea, J.M. (2009). Overview of physical interaction models for photon and electron transport used in Monte Carlo codes. Metrologia 46(2), S112–S138.CrossRefGoogle Scholar
Salvat, F., Fernández-Varea, J.M., Acosta, E. & Sempau, J. (2001). PENELOPE—A Code System for Monte Carlo Simulation of Electron and Photon Transport. Barcelona, Spain: Facultat de Fisica (ECM), Universitat de Barcelona, Spain, Nuclear Energy Agency.Google Scholar
Salvat, F. & Mayol, R. (1993). Elastic scattering of electrons and positrons by atoms. Schrödinger and Dirac partial wave analysis. Comput Phys Comm 74, 358–374.CrossRefGoogle Scholar
Scholze, F. & Procop, M. (2005). Detection efficiency of energy-dispersive detectors with low-energy windows. X-Ray Spectrom 34(6), 473–476.CrossRefGoogle Scholar
Schreiber, T.P. & Wims, A.M. (1981). A quantitative X-ray microanalysis thin film method using K-, L- and M-lines. Ultramicroscopy 6(4), 323–334.CrossRefGoogle Scholar
Scofield, J.H. (1974). Hatree-Fock values of L X-ray emission rates. Phys Rev A 10(5), 1507–1510.CrossRefGoogle Scholar
Shimizu, R. (1974). Secondary electron yield with primary electron beam of kilo-electron volts. J Appl Phys 45(5), 2107–2111.CrossRefGoogle Scholar
Shimizu, R. & Ding, Z.J. (1992). Monte Carlo modelling of electron solid interaction. Rep Prog Phys 55(4), 487–531.CrossRefGoogle Scholar
Statham, P.J. (2002). Limitations to accuracy in extracting characteristic line intensities from XS-ray spectra. J Res Natl Inst Stand Technol 107(6), 531–546.CrossRefGoogle ScholarPubMed
Watanabe, M. & Williams, D.B. (2006). The quantitative analysis of thin specimens: A review of progress from the Cliff-Lorimer to the new zeta-factor methods. J Microsc-Oxford 221, 89–109.CrossRefGoogle Scholar