Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-27T14:58:24.673Z Has data issue: false hasContentIssue false

The Impact of Chemical Bonding on Mass Absorption Coefficients of Soft X-rays

Published online by Cambridge University Press:  14 May 2020

Samantha Rudinsky
Affiliation:
Department of Mining and Materials Engineering, McGill University, 3610 University, Montreal, CanadaH2T 2X1
Nicholas C. Wilson
Affiliation:
CSIRO Mineral Resources, Bayview Avenue, Clayton3168, VIC, Australia
Colin M. MacRae
Affiliation:
CSIRO Mineral Resources, Bayview Avenue, Clayton3168, VIC, Australia
Yu Yuan
Affiliation:
Department of Mining and Materials Engineering, McGill University, 3610 University, Montreal, CanadaH2T 2X1
Hendrix Demers
Affiliation:
Hydro-Québec Center of Excellence in Transportation Electrification and Energy Storage, 1800 Boul. Lionel-Boulet, Varennes, CanadaJ3X 1S1
Mark A. Gibson
Affiliation:
CSIRO Manufacturing, Bayview Avenue, Clayton3168, VIC, Australia
Raynald Gauvin*
Affiliation:
Department of Mining and Materials Engineering, McGill University, 3610 University, Montreal, CanadaH2T 2X1
*
*Author for correspondence: Raynald Gauvin, E-mail: [email protected]
Get access

Abstract

Accurate elemental quantification of materials by X-ray detection techniques in electron microscopes or microprobes can only be carried out if the appropriate mass absorption coefficients (MACs) are known. With continuous advancements in experimental techniques, databases of MACs must be expanded in order to account for new detection limits. Soft X-ray emission spectroscopy (SXES) is a characterization technique that can detect emitted X-rays whose energies are in the range of 10 eV to 2 keV by using a varied-line-spaced grating. Transitions producing soft X-rays can be detected and accurate MACs are required for use in quantification. This work uses Monte Carlo modeling coupled with multivoltage SXES measurements in an electron probe micro-analyzer (EPMA) to compute MACs for the L2,3-M and Li Kα transitions in a variety of aluminum alloys. Electron depth distribution curves obtained by the software MC X-ray are used in a parametrized fitting equation. The MACs are calculated using a least-squares regression analysis. It is shown that X-ray distribution cross-sections at such low energies need to take into account additional contributions, such as Coster–Kronig transitions, Auger yields, and wave function effects in order to be accurate.

Type
Australian Microbeam Analysis Society Special Section AMAS XV 2019
Copyright
Copyright © Microscopy Society of America 2020

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

Achkar, AJ, Regier, TZ, Monkman, EJ, Shen, KM & Hawthorn, DG (2011 a). Determination of total X-ray absorption coefficient using non-resonant X-ray emission. Sci Rep 1, 182.CrossRefGoogle ScholarPubMed
Achkar, AJ, Regier, TZ, Wadati, H, Kim, Y-J, Zhang, H & Hawthorn, DG (2011 b). Bulk sensitive X-ray absorption spectroscopy free of self-absorption effects. Phys Rev B 83, 081106.CrossRefGoogle Scholar
Allison, JW (1961). Gamma radiation absorption coefficients of various materials allowing for bremsstrahlung and other secondary radiations. Aust J Phys 14, 443.Google Scholar
Bambynek, W, Crasemann, B, Fink, RW, Freud, HU, Mark, H, Swift, CD, Price, RE & Venugopala Rao, P (1972). X-ray fluorescence yields, auger, and Coster-Kronig transition probabilities. Rev Mod Phys 44, 716813.CrossRefGoogle Scholar
Bastin, GF & Heijligers, HJM (1990). Quantitative electron probe microanalysis of ultralight elements (boron-oxygen). Scanning 12, 225236.CrossRefGoogle Scholar
Bote, D, Salvat, F, Jablonski, A & Powell, CJ (2009). Cross sections for ionization of K, L and M shells of atoms by impact of electrons and positrons with energies up to 1 GeV: Analytical formulas. At Data Nucl Data Tables 95, 871909.CrossRefGoogle Scholar
Campbell, JL (2003). Fluorescence yields and Coster-Kronig probabilities for the atomic L subshells. At Data Nucl Data Tables 85, 291315.CrossRefGoogle Scholar
Chantler, CT, Olsen, K, Dragoset, RA, Chang, J, Kishore, AR, Kotochigova, SA & Zucker, DS (2005). X-Ray Form Factor, Attenuation and Scattering Tables (version 2.1). Gaithersburg, MD: National Institute of Standards and Technology. [Online] Available: http://physics.nist.gov/ffastGoogle Scholar
Chantler, CT, Tran, CQ, Barnea, Z, Paterson, D, Cookson, DJ & Balaic, DX (2001). Measurement of the X-ray mass attenuation coefficient of copper using 8.85–20 kev synchrotron radiation. Phys Rev A 64, 062506.CrossRefGoogle Scholar
Cullen, DE, Hubbell, JH & Kissel, L (1997). Epdl97: The evaluated photo data library ’97 version. Technical report.Google Scholar
Demers, H, MacRae, CM, Wilson, NC, Hovington, P, Timoshevskii, V, Gauvin, R & Zaghib, K (2016). Determination of soft X-ray emission spectroscopy parameters using experimental data for quantitative microanalysis. Microsc Microanal S22, 408409.CrossRefGoogle Scholar
Egerton, RF (2013). Electron Energy-Loss Spectroscopy in the Electron Microscope. Boston: Springer US.Google Scholar
Elam, WT, Ravel, BD & Sieber, JR (2002). A new atomic database for X-ray spectroscopic calculations. Radiat Phys Chem 63, 121128.Google Scholar
Elmahroug, Y, Tellili, B & Souga, C (2015). Determination of total mass attenuation coefficients, effective atomic numbers and electron densities for different shielding materials. Ann Nucl Energy 75, 268274.CrossRefGoogle Scholar
Gauvin, R (2012). What remains to be done to allow quantitative X-ray microanalysis performed with EDS to become a true characterization technique? Microsc Microanal 18, 915940.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Gauvin, R & Michaud, P (2009). MC X-ray, a new Monte Carlo program for quantitative X-ray microanalysis of real materials. Microsc Microanal 15, 488489.CrossRefGoogle Scholar
Goldstein, J (2003). Scanning Electron Microscopy and X-ray Microanalysis, 3rd ed. New York: Plenum.CrossRefGoogle Scholar
Hall, CR (1966). On the production of characteristic X-rays in thin metal crystals. Proc R Soc Lond A: Math Phys Eng Sci 295, 140163.Google Scholar
Heinrich, KFJ (1987). Mass absorption coefficients for electron probe microanalysis. In 11th International Congress on X-ray Optics and Microanalysis: ICXOM 11, pp. 67–71.Google Scholar
Heinrich, KFJ & Newbury, D (1991). Electron Probe Quantitation. Springer US.CrossRefGoogle Scholar
Henke, BL, Gullikson, EM & Davis, JC (1993). X-ray interactions: Photoabsorption, scattering, transmission, and reflection at E = 50 − −30, 000 eV, Z = 1 − −92. At Data Nucl Data Tables 54, 181342.CrossRefGoogle Scholar
Hlil, E, Baudoing-Savois, R, Moraweck, B & Renouprez, AJ (1996). X-ray absorption edges in platinum-based alloys. 2. Influence of ordering and of the nature of the second metal. J Phys Chem 100, 31023107.CrossRefGoogle Scholar
Horny, P, Lifshin, E, Campbell, H & Gauvin, R (2010). Development of a new quantitative X-ray microanalysis method for electron microscopy. Microsc Microanal 16, 821830.Google ScholarPubMed
Hovington, P, Timoshevskii, V, Burgess, S, Demers, H, Statham, P, Gauvin, R & Zaghib, K (2016). Can we detect Li K X-ray in lithium compounds using energy dispersive spectroscopy? Scanning 38, 571578.CrossRefGoogle Scholar
Hubbell, JH (1982). Photon mass attenuation and energy-absorption coefficients. Int J Appl Radiat Isot 33, 12691290.CrossRefGoogle Scholar
Kita, T, Harada, T, Nakano, N & Kuroda, H (1983). Mechanically ruled aberration-corrected concave gratings for a flat-field grazing-incidence spectrograph. Appl Opt 22, 512513.CrossRefGoogle ScholarPubMed
Krause, MO (1979). Atomic radiative and radiationless yields for K and L shells. J Phys Chem Ref Data 8, 307327.CrossRefGoogle Scholar
Leapman, RD, Rez, P & Mayers, DF (1980). K, L, and M shell generalized oscillator strengths and ionization cross sections for fast electron collisions. J Chem Phys 72, 12321243.CrossRefGoogle Scholar
MacRae, CM, Hughes, AE, Laird, JS, Glenn, AM, Wilson, NC, Torpy, A, Gibson, MA, Zhou, X, Birbilis, N & Thompson, GE (2018 b). An examination of the composition and microstructure of coarse intermetallic particles in AA2099-T8, including Li detection. Microsc Microanal 24, 325341.CrossRefGoogle ScholarPubMed
MacRae, CM, Wilson, NC, Torpy, A & Delle Piane, C (2018 a). Soft X-ray and cathodoluminescence measurement, optimisation and analysis at liquid nitrogen temperatures. IOP Conf Ser: Mater Sci Eng 304, 012010.CrossRefGoogle Scholar
Merlet, C, Llovet, X & Salvat, F (2004). Measurements of absolute K-shell ionization cross sections and L-shell X-ray production cross sections of Ge by electron impact. Phys Rev A 69, 032708.CrossRefGoogle Scholar
Moraweck, B, Renouprez, AJ, Hlil, EK & Baudoing-Savois, R (1993). Alloying effects on x-ray absorption edges in nickel-platinum single crystals. J Phys Chem 97, 42884292.CrossRefGoogle Scholar
Pouchou, JL & Pichoir, F (1987). Basic expression of PAP computation for quantitative EPMA. In Proceedings of the 11th ICXOM, pp. 249–253.Google Scholar
Prasad, NE, Gokhale, A & Wanhill, RJH (2013). Aluminum-Lithium Alloys: Processing, Properties, and Applications. Oxford: Elsevier Science.Google Scholar
Sabbatucci, L & Salvat, F (2016). Theory and calculation of the atomic photoeffect. Radiat Phys Chem 121, 122140.CrossRefGoogle Scholar
Sarkadi, L & Mukoyama, T (1984). Higher order processes in L-shell ionization. Nucl Instrum Methods Phys Res B 4, 296302.CrossRefGoogle Scholar
Scofield, JH (1978). K- and L-shell ionization of atoms by relativistic electrons. Phys Rev A 18, 963970.CrossRefGoogle Scholar
Seltzer, SM (1993). Calculation of photon mass energy-transfer and mass energy-absorption coefficients. Radiat Res 136, 147170.CrossRefGoogle ScholarPubMed
Shandiz, MA, Guinel, MJ-F, Ahmadi, M & Gauvin, R (2016). Monte Carlo simulations of electron energy-loss spectra with the addition of fine structure from density functional theory calculations. Microsc Microanal 22, 219229.CrossRefGoogle Scholar
Takahashi, H, Murano, T, Takakura, M, Asahina, S, Terauchi, M, Koike, M, Imazono, T, Koeda, M & Nagano, T (2016). Development of soft X-ray emission spectrometer for EPMA/SEM and its application. IOP Conf Ser: Mater Sci Eng 109, 012017.CrossRefGoogle Scholar
Terauchi, M & Kawana, M (2006). Soft X-ray emission spectroscopy based on TEM-toward a total electronic structure analysis. Ultramicroscopy 106, 10691075. Proceedings of the International Workshop on Enhanced Data Generated by Electrons.CrossRefGoogle ScholarPubMed
Terauchi, M, Koike, M, Fukushima, K & Kimura, A (2010). Development of wavelength-dispersive soft X-ray emission spectrometers for transmission electron microscopes-an introduction of valence electron spectroscopy for transmission electron microscopy. J Electron Microsc (Tokyo) 59, 251261.CrossRefGoogle ScholarPubMed
Terauchi, M, Takahashi, H, Handa, N, Murano, T, Koike, M, Kawachi, T, Imazono, T, Koeda, M, Nagano, T, Sasai, H, Oue, Y, Yonezawa, Z & Kuramoto, S (2011). Ultrasoft-X-ray emission spectroscopy using a newly designed wavelength-dispersive spectrometer attached to a transmission electron microscope. J Electron Microsc (Tokyo) 61, 18.CrossRefGoogle Scholar
Tran, CQ, Chantler, CT, Barnea, Z, Paterson, D & Cookson, DJ (2003). Measurement of the x-ray mass attenuation coefficient and the imaginary part of the form factor of silicon using synchrotron radiation. Phys Rev A 67, 042716.CrossRefGoogle Scholar
Victoreen, JA (1949). The calculation of X-ray mass absorption coefficients. J Appl Phys 20, 11411147.CrossRefGoogle Scholar