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Comparison of Cliff–Lorimer-Based Methods of Scanning Transmission Electron Microscopy (STEM) Quantitative X-Ray Microanalysis for Application to Silicon Oxycarbides Thin Films

Published online by Cambridge University Press:  31 May 2018

Andrea Parisini Open the ORCID record for Andrea Parisini [Opens in a new window] ,
Stefano Frabboni ,
Gian Carlo Gazzadi ,
Rodolfo Rosa  and
Aldo Armigliato
Andrea Parisini*
Affiliation:
CNR-IMM Sezione di Bologna, via P. Gobetti 101, 40129 Bologna, Italy
Stefano Frabboni
Affiliation:
Dipartimento di Fisica, Informatica e Matematica, Università di Modena e Reggio Emilia, via G. Campi 213/A, 41100 Modena, Italy CNR-Istituto di Nanoscienze-S3, via G. Campi 213/a, 41100 Modena, Italy
Gian Carlo Gazzadi
Affiliation:
CNR-Istituto di Nanoscienze-S3, via G. Campi 213/a, 41100 Modena, Italy
Rodolfo Rosa
Affiliation:
CNR-IMM Sezione di Bologna, via P. Gobetti 101, 40129 Bologna, Italy
Aldo Armigliato
Affiliation:
CNR-IMM Sezione di Bologna, via P. Gobetti 101, 40129 Bologna, Italy
*
* Author for correspondence: Andrea Parisini, E-mail: parisini@bo.imm.cnr.it
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Abstract

In this work, we compare the results of different Cliff–Lorimer (Cliff & Lorimer 1975) based methods in the case of a quantitative energy dispersive spectrometry investigation of light elements in ternary C–O–Si thin films. To determine the Cliff–Lorimer (C–L) k-factors, we fabricated, by focused ion beam, a standard consisting of a wedge lamella with a truncated tip, composed of two parallel SiO2 and 4H-SiC stripes. In 4H-SiC, it was not possible to obtain reliable k-factors from standard extrapolation methods owing to the strong CK-photon absorption. To overcome this problem, an extrapolation method exploiting the shape of the truncated tip of the lamella is proposed herein. The k-factors thus determined, were then used in an application of the C–L quantification procedure to a defect found at the SiO2/4H-SiC interface in the channel region of a metal-oxide field-effect-transistor device. As in this procedure, the sample thickness is required, a method to determine this quantity from the averaged and normalized scanning transmission electron microscopy intensity is also detailed. Monte Carlo simulations were used to investigate the discrepancy between experimental and theoretical k-factors and to bridge the gap between the k-factor and the Watanabe and Williams ζ-factor methods (Watanabe & Williams, 2006).

Keywords

FIB lamellaanalytical electron microscopyscanning transmission electron microscopysilicon carbidesilicon oxide
Type
Materials Science Applications
Information
Microscopy and Microanalysis , Volume 24 , Issue 3 , June 2018 , pp. 193 - 206
Copyright
© Microscopy Society of America 2018 

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Footnotes

Cite this article: Parisini A, Frabboni S, Gazzadi GC, Rosa R and Armigliato A (2018) Comparison of Cliff–Lorimer-Based Methods of Scanning Transmission Electron Microscopy (STEM) Quantitative X-Ray Microanalysis for Application to Silicon Oxycarbides Thin Films. Microsc Microanal. 24(3): 193ȓ206 doi: 10.1017/S1431927618000259

References

Amari, H, Kappers, MJ, Humphreys, CJ, Chèze, C and Walther, T (2012) Measurement of Al content in AlGaN epitaxial layers by combined energy-dispersive X-ray and electron energy-loss spectroscopy in a transmission electron microscope. Phys Status Solidi C 9, 1079–1082.CrossRefGoogle Scholar
Armigliato, A, Frabboni, S, Gazzadi, GC and Rosa, R (2013) FIB preparation of a NiO wedge-lamella and STEM X-ray microanalysis for the determination of the experimental k(O-Ni) Cliff-Lorimer Coefficients. Microsc Microanal 19, 79–84.Google Scholar
Armigliato, A and Rosa, R (2009) X-ray microanalysis combined with Monte Carlo simulations for the analysis of layered thin films: The case of carbon contamination. Microsc Microanal 15, 99–105.Google Scholar
Cliff, G and Lorimer, G (1975) The quantitative analysis of thin specimens. J Microsc 103, 203–207.CrossRefGoogle Scholar
FEI Company (now Thermo Fisher Scientific) (2008) TEM Imaging & Analysis, TIA. Eindhoven, The Netherlands: FEI Company.Google Scholar
Fladisher, S and Grogger, W (2014) Quantitative EDXS analysis of organic materials using the ζ-factor method. Ultramicroscopy 136, 26–30.Google Scholar
Giannuzzi, LA, Drown, JL, Brown, SR, Irwin, RB and Stevie, FA (1997) Focused ion beam milling and micromanipulation lift-out for site specific cross-section TEM specimen preparation. Mat Res Soc Proc 480, 19.Google Scholar
Goldstein, JI, Costley, JL, Lorimer, GW and Reed, SJB (1977) Quantitative X-ray analysis in the electron microscope. In Scanning Electron Microscopy 1977, vol. 1, Johari O (Ed.), pp. 315–324. Chicago, IL: IITRI.Google Scholar
Heinrich, KFJ (1987) Mass absorption coefficients for electron probe microanalysis. In Proceedings of the 11th International Congress on X-ray Optics and Microanalysis, Brown JD and Packwood RH (Eds.), pp. 67–377. London, ON: University of Western Ontario.Google Scholar
Hopman, TL, Heirwegh, CM, Campbell, JL, Krumreyb, M and Scholzeb, F (2012) An accurate determination of the K-shell X-ray fluorescence yield of silicon. X-ray Spectrom 41, 164–171.Google Scholar
Horita, Z, Sano, T and Nemoto, M (1986) An extrapolation method for the determination of Cliff-Lorimer k AB factors at zero foil thickness. J Microsc 143, 215–231.Google Scholar
Jones, L (2016) Quantitative ADF-STEM: Acquisition, analysis and interpretation. Mat Sci and Eng 109, 012008.Google Scholar
Krause, MO (1979) Atomic radiative and radiationless yields for K and L shells. J Phys Chem Ref Data 8, 307–327.CrossRefGoogle Scholar
Longo, DM, Howe, JM and Johnson, WC (1999) Experimental method for determining Cliff-Lorimer factors in transmission electron microscopy (TEM) utilizing stepped wedge-shaped specimens prepared by focused ion beam (FIB) thinning. Ultramicroscopy 80, 85–97.Google Scholar
Parisini, A, Frabboni, S, Gazzadi, GC, Armigliato, A and Rosa, R (2017) Thickness and orientation dependence of the average HAADF STEM normalized intensity: A comparison with Monte Carlo and Multislice simulations. In Proceedings of the 13th Multinational Congress on Microscopy, September 24–29, Gajovic A, Weber I, Kovačević G, Čadež V, Šegota S, Peharec Štefanić P and Vidoš A (Eds.), pp. 167–169. Zagreb, Croatia: Ruder Bošković Institute and Croatian Microscopy Society.Google Scholar
Poggi, A, Moscatelli, F, Solmi, S, Armigliato, A, Belsito, L and Nipoti, R (2010) Effect of N implantation at the SiO2/SiC interface on the electron mobility and free carrier density in 4H-SiC MOSFET channel. J Appl Phys 107, 044506.CrossRefGoogle Scholar
Powell, CJ (1976) Cross sections for ionization of inner shell electrons. Rev Mod Phys 48, 33–47.Google Scholar
Rosa, R and Armigliato, A (1989) Monte Carlo simulation of thin-film X-ray microanalysis at high energies. X-Ray Spectrom 18, 19–23.Google Scholar
Schlossmacher, P, Klenov, DO, Freitag, B and von Harrach, HS (2010) Enhanced detection sensitivity with a new windowless XEDS system for AEM based on silicon drift detector technology. Microsc Today 18, 14–20.Google Scholar
Schreiber, TP and Wims, AM (1982) Relative intensity factors for K, L and M shell X-ray lines. X-ray Spectrom 11, 42–45.Google Scholar
Van Cappellen, E (1990) The parameterless correction method in X-ray microanalysis. Micro Microanal Microstruct 1, 1–22.Google Scholar
Van Cappellen, E (2004) Energy dispersive X-ray microanalysis in STEM and TEM. In X-Ray Spectrometry: Recent Technological Advances, Tsuji K, Injuk J and Van Grieken R (Eds.), pp. 387–404. West Sussex, UK: John Wiley & Sons, Ltd.Google Scholar
Van den Broek, W, Rosenauer, A, Goris, B, Martinez, GT, Bals, S, Van Aert, S and Van Dyck, D (2012) Correction of non-linear thickness effects in HAADF STEM electron tomography. Ultramicroscopy 116, 8–12.Google Scholar
Ware, NG and Reed, SJB (1973) Background corrections for quantitative electron microprobe analysis using a lithium drifted silicon X-ray detector. J Phys E 6, 286–288.Google Scholar
Watanabe, M (2016) Practical aspects and advanced applications of XEDS. In Transmission Electron Microscopy: Diffraction, Imaging, and Spectrometry, Carter CB and Williams DB (Eds.), chap. 17. Berlin, Heidelberg: Springer-Verlag GmbH.Google Scholar
Watanabe, M and Williams, DB (2006) The quantitative analysis of thin specimes: A review of progress from the Cliff-Lorimer to the new ζ-factor methods. J Microsc 221, 89–109.Google Scholar
Williams, DB and Carter, CB (2009 a) Transmission Electron Microscopy, 2nd ed. New York: Springer. pp. 639–662.Google Scholar
Williams, DB and Carter, CB (2009 b) Transmission Electron Microscopy, 2nd ed. New York: Springer. pp. 378–381.Google Scholar
Zaluzec, NJ (1981) On the geometry of the absorption correction for analytical electron microscopy. In Microbeam Analysis, Geiss RH (Ed.), pp. 325–328. San Francisco, CA: San Francisco Press.Google Scholar