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An Improved STEM/EDX Quantitative Method for Dopant Profiling at the Nanoscale

Published online by Cambridge University Press:  10 January 2020

Raghda Makarem ,
Filadelfo Cristiano ,
Dominique Muller  and
Pier Francesco Fazzini Open the ORCID record for Pier Francesco Fazzini [Opens in a new window]
Raghda Makarem
Affiliation:
LPCNO, Université de Toulouse INSA, CNRS, UPS 135, Avenue de Rangueil, 31077Toulouse, France
Filadelfo Cristiano
Affiliation:
LAAS-CNRS, Université de Toulouse, CNRS, 7 Avenue du Colonel Roche, F-31400Toulouse, France
Dominique Muller
Affiliation:
ICube Laboratory, Université de Strasbourg and CNRS, B.P. 20, 67037Strasbourg Cedex, France
Pier Francesco Fazzini*
Affiliation:
LPCNO, Université de Toulouse INSA, CNRS, UPS 135, Avenue de Rangueil, 31077Toulouse, France
*
*Author for correspondence: Pier Francesco Fazzini, E-mail: fazzini@insa-toulouse.fr
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Abstract

In this paper, an improved quantification technique for STEM/EDX measurements of 1D dopant profiles based on the Cliff-Lorimer equation is presented. The technique uses an iterative absorption correction procedure based on density models correlating the local mass density and composition of the specimen. Moreover, a calibration and error estimation procedure based on linear regression and error propagation is proposed in order to estimate the total measurement error in the dopant density. The proposed approach is applied to the measurement of the As profile in a nanodevice test structure. For the calibration, two crystalline Si specimens implanted with different As doses have been used, and the calibration of the Cliff-Lorimer coefficients has been carried out using Rutherford Back Scattering measurements. The As profile measurement has been carried out on an FinFET test structure, showing that quantitative results can be obtained in the nanometer scale and for dopant atomic densities lower than 1%. Using the proposed approach, the measurement error and detection limit for our experimental setup are calculated and the possibility to improve this limit by increasing the observation time is discussed.

Keywords

dopant profilingEDXnanodevicesquantification methodsSTEM
Type
Materials Science Applications
Information
Microscopy and Microanalysis , Volume 26 , Issue 1 , February 2020 , pp. 76 - 85
Copyright
Copyright © Microscopy Society of America 2020

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References

Alvisi, M, Blome, M, Griepentrog, M, Hodoroaba, VD, Karduck, P, Mostert, M, Nacucchi, M, Procop, M, Rohde, M, Scholze, F, Statham, P, Terborg, R & Thiot, JF (2006). The determination of the efficiency of energy dispersive X-ray spectrometers by a new reference material. Microsc Microanal 12, 406–415.CrossRefGoogle ScholarPubMed
Chu, WK (1978) Backscattering Spectrometry, Chu W-K, Mayer JW & Nicolet M-A (Eds.). Cambridge, USA: Academic Press.CrossRefGoogle Scholar
Cliff, G & Lorimer, GW (1975). The quantitative analysis of thin specimens. J Microsc 103, 203–207.CrossRefGoogle Scholar
Colinge, JP (Ed.) (2008) FinFETs and Other Multi-Gate Transistors, Integrated Circuits and Systems. New York: Springer.CrossRefGoogle Scholar
Custer, JS, Thompson, MO, Jacobson, DC, Poate, JM, Roorda, S, Sinke, WC & Spaepen, F (1994). Density of amorphous Si. Appl Phys Lett 64, 437–439.CrossRefGoogle Scholar
Eibl, O (1993). New method for absorption correction in high-accuracy, quantitative EDX microanalysis in the TEM including low-energy x-ray lines. Ultramicroscopy 50, 179–188.CrossRefGoogle Scholar
Goldstein, JI, Newbury, DE, Michael, JR, Ritchie, NWM, Scott, JHJ, Joy, DC (2018). Scanning Electron Microscopy and X-Ray Microanalysis, 4th ed. New York: Springer-Verlag.CrossRefGoogle Scholar
Greaves, GN, Elliott, SR & Davis, EA (1979). Amorphous arsenic. Adv Phys 28, 49–141.CrossRefGoogle Scholar
Heinrich, KFJ (1986) Mass absorption coefficients for electron probe microanalysis. In Proc 11th Int Congr on X-Ray Optics and Microanalysis, London (Canada), pp. 67–119.Google Scholar
Kasper, E, Schuh, A, Bauer, G, Holländer, B & Kibbel, H (1995). Test of Vegard's law in thin epitaxial SiGe layers. J Cryst Growth 157, 68–72.CrossRefGoogle Scholar
Ke, X, Bals, S, Romo Negreira, A, Hantschel, T, Bender, H & Van Tendeloo, G (2009). TEM sample preparation by FIB for carbon nanotube interconnects. Ultramicroscopy 109, 1353–1359.CrossRefGoogle ScholarPubMed
Kothleitner, G, Neish, MJ, Lugg, NR, Findlay, SD, Grogger, W, Hofer, F & Allen, LJ (2014). Quantitative elemental mapping at atomic resolution using X-ray spectroscopy. Phys Rev Lett 112, 085501.CrossRefGoogle Scholar
MacArthur, KE, Slater, TJA, Haigh, SJ, Ozkaya, D, Nellist, PD & Lozano-Perez, S (2016). Quantitative energy-dispersive X-ray analysis of catalyst nanoparticles using a partial cross section approach. Microsc Microanal 22, 71–81.CrossRefGoogle ScholarPubMed
MacLaren, I, Schierholz, R, Trusty, PA & Ponton, CB (2007). Silica glass segregation in 3 wt% LiF-doped hot-pressed ${\rm Y}_2{\rm Si}_2{\rm O}_7$. J Am Ceram Soc 90, 3307–3310.CrossRefGoogle Scholar
Malis, T, Cheng, SC & Egerton, RF (1988). EELS log-ratio technique for specimen-thickness measurement in the TEM. J Electron Microsc Tech 8, 193–200.CrossRefGoogle ScholarPubMed
Morris, PL, Ball, M & Statham, P (1979). Proceedings EMAG '79 Brighton. UK Inst. Phys. Conf. Ser. 52, 413.Google Scholar
Pichler, P (2004). Intrinsic Point Defects, Impurities, Their Diffusion in Silicon. Computational Microelectronics. Wien: Springer-Verlag. Available at https://www.springer.com/gp/book/9783211206874.CrossRefGoogle Scholar
Qiu, Y, Nguyen, VH, Dobbie, A, Myronov, M & Walther, T (2013). Calibration of thickness-dependentk-factors for germanium X-ray lines to improve energy-dispersive X-ray spectroscopy of SiGe layers in analytical transmission electron microscopy. J Phys: Conf Ser 471, 012031.Google Scholar
Stachurski, Z (2015) Fundamentals of Amorphous Solids: Structure and Properties. Weinheim, Germany: Wiley VCH.Google Scholar
Taylor, JR (1997) Introduction To Error Analysis: The Study of Uncertainties in Physical Measurements. Sausalito, USA: University Science Books.Google Scholar
Vandervorst, W, Schulze, A, Kambham, AK, Mody, J, Gilbert, M & Eyben, P (2014). Dopant/carrier profiling for 3d-structures. Phys Status Solidi C 11, 121–129.CrossRefGoogle Scholar
Wasserman, L (2006) All of Nonparametric Statistics, 1st ed., 3rd print ed. Springer Texts in Statistics. New York, NY: Springer, oCLC: 69992043.Google Scholar
Watanabe, M, Horita, Z & Nemoto, M (1996). Absorption correction and thickness determination using the ζ-factor in quantitative X-ray microanalysis. Ultramicroscopy 65, 187–198.CrossRefGoogle Scholar
Watanabe, M & Williams, DB (2006). The quantitative analysis of thin specimens: A review of progress from the Cliff-Lorimer to the new ζ-factor methods. J Microsc 221, 89–109.CrossRefGoogle ScholarPubMed
Williams, DB & Carter, CB (2009) Transmission Electron Microscopy: A Textbook for Materials Science. Springer Science and Business Media.CrossRefGoogle Scholar
Ziegler, JF & Biersack, JP (1985) The stopping and range of ions. In Treatise on Heavy-Ion Science: Volume 6: Astrophysics, Chemistry, and Condensed Matter, Bromley MDA (Ed.), pp. 93–129. Boston, MA: Springer US.CrossRefGoogle Scholar