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Three-Dimensional X-Ray Photoelectron Tomography on the Nanoscale: Limits of Data Processing by Principal Component Analysis

Published online by Cambridge University Press:  19 April 2013

Shaaker Hajati ,
John Walton  and
Sven Tougaard
Shaaker Hajati*
Affiliation:
Department of Physics, Yasouj University, Yasouj 75918-74831, Iran
John Walton
Affiliation:
School of Materials, The University of Manchester, Manchester M13 9PL, UK
Sven Tougaard
Affiliation:
Department of Physics, Chemistry, and Pharmacy, University of Southern Denmark, DK-5230 Odense M, Denmark
*
*Corresponding author. E-mail: [email protected]
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Abstract

In a previous article, we studied the influence of spectral noise on a new method for three-dimensional X-ray photoelectron spectroscopy (3D XPS) imaging, which is based on analysis of the XPS peak shape [Hajati, S., Tougaard, S., Walton, J. & Fairley, N. (2008). Surf Sci602, 3064–3070]. Here, we study in more detail the influence of noise reduction by principal component analysis (PCA) on 3D XPS images of carbon contamination of a patterned oxidized silicon sample and on 3D XPS images of Ag covered by a nanoscale patterned octadiene layer. PCA is very efficient for noise reduction, and using only the three most significant PCA factors to reconstruct the spectra restores essentially all physical information in both the intensity and shape of the XPS spectra. The corresponding signal-to-noise improvement was estimated to be equivalent to a reduction by a factor of 200 in the required data acquisition time. A small additional amount of information is obtained by using up to five PCA factors, but due to the increased noise level, this information can only be extracted if the intensity of the start and end points for each spectrum are obtained as averages over several energy points.

Keywords

nondestructive analysis3D XPS imagingXPS peak shape analysisPCA noise reduction
Type
Equipment and Techniques Development: Materials
Information
Microscopy and Microanalysis , Volume 19 , Issue 3 , June 2013 , pp. 751 - 760
Copyright
Copyright © Microscopy Society of America 2013 

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References

Alexander, M.R., Wittle, J.D., Barton, D. & Short, R.D. (2004). Plasma polymer chemical gradients for evaluation of surface reactivity: Epoxide reaction with carboxylic acid surface groups. J Mater Chem 14, 408–412.CrossRefGoogle Scholar
Artyushkova, K. & Fulghum, J.E. (2005). Angle resolved imaging of polymer blend systems: From images to a 3D volume of material morphology. J Electron Spectrosc Relat Phenom 149, 51–60.CrossRefGoogle Scholar
Briggs, D. & Grant, J.T. (2003). Surface Analysis by Auger and Photoelectron Spectroscopy. Chichester, UK: IM Publications.Google Scholar
Browning, R. (1993). Multi-spectral imaging in materials microanalysis. Surf Interface Anal 20, 495–502.CrossRefGoogle Scholar
d'Agostino, R. (1990). Plasma Deposition, Treatment, and Etching of Polymers. London: Academic Press.Google Scholar
Dench, W.A., Hazell, L.B. & Seah, M.P. (1988). VAMAS surface chemical analysis standard data transfer format with skeleton decoding programs. Surf Interface Anal 13, 63–122.CrossRefGoogle Scholar
Fairley, N. (2008). CasaXPS Version 2.3.14: Software package for data processing. Available at http://www.casaxps.com.Google Scholar
Geladi, P. & Grahn, H. (1996). Multivariate Image Analysis. Chichester, UK: Wiley.Google Scholar
Hajati, S., Coultas, S., Blomfield, C. & Tougaard, S. (2006). XPS imaging of depth profiles and amount of substance based on Tougaard's algorithm. Surf Sci 600, 3015–3021.CrossRefGoogle Scholar
Hajati, S., Coultas, S., Blomfield, C. & Tougaard, S. (2008a). Nondestructive quantitative XPS imaging of depth distribution of atoms on the nanoscale. Surf Interface Anal 40, 688–691.CrossRefGoogle Scholar
Hajati, S. & Tougaard, S. (2006). What nano-physical properties can be determined by analysis of elastic peak accompanied by its inelastic background tail in XPS and AES spectra? J Surf Anal 13, 148–155.Google Scholar
Hajati, S. & Tougaard, S. (2010). XPS for non-destructive depth profiling and 3D imaging of surface nanostructures. Anal Bioanal Chem 396, 2741–2755.CrossRefGoogle ScholarPubMed
Hajati, S., Tougaard, S., Walton, J. & Fairley, N. (2008b). Noise reduction procedures applied to XPS imaging of depth distribution of atoms on the nanoscale. Surf Sci 602, 3064–3070.CrossRefGoogle Scholar
Hajati, S., Zaporojtchenko, V., Faupel, F. & Tougaard, S. (2007). Characterization of Au nano-cluster formation on and diffusion in polystyrene using XPS peak shape analysis. Surf Sci 601, 3261–3267.CrossRefGoogle Scholar
Jolliffe, I.T. (2002). Principal Component Analysis, 2nd ed. New York: Springer-Verlag.Google Scholar
López-Santos, M.C., Yubero, F., Espinós, J.P. & González-Elipe, A.R. (2010). Non-destructive depth compositional profiles by XPS peak-shape analysis. Anal Bioanal Chem 396, 2757–2768.CrossRefGoogle ScholarPubMed
Malinowski, E.R. & Howery, D.G. (1980). Factor Analysis in Chemistry. New York: Wiley.Google Scholar
Payne, B.P., Grosvenor, A.P., Biesinger, M.C., Kobe, B.A. & McIntyre, N.S. (2007). Structure and growth of oxides on polycrystalline nickel surfaces. Surf Interface Anal 39, 582–592.CrossRefGoogle Scholar
Savitzky, A. & Golay, M.J.E. (1964). Smoothing and differentiation of data by simplified least squares procedures. Anal Chem 36, 1627–1639.CrossRefGoogle Scholar
Smith, E.F., Briggs, D. & Fairley, N. (2006). Further developments in quantitative X-ray photoelectron spectromicroscopy: Preliminary results from the study of germanium corrosion. Surf Interface Anal 38, 69–75.CrossRefGoogle Scholar
Tanuma, S., Powell, C.J. & Penn, D.R. (1994). Calculations of electron inelastic mean free paths. V. Data for 14 organic compounds over the 50–2000 eV range. Surf Interface Anal 21, 165–176.CrossRefGoogle Scholar
Tougaard, S. (1987). X-ray photoelectron spectroscopy peak shape analysis for the extraction of in-depth composition information. J Vac Sci Technol A 5, 1275–1278.CrossRefGoogle Scholar
Tougaard, S. (1990a). Formalism for quantitative surface analysis by electron spectroscopy. J Vac Sci Technol A 8, 2197–2203.CrossRefGoogle Scholar
Tougaard, S. (1990b). Inelastic background correction and quantitative surface analysis. J Electron Spectrosc Relat Phenom 52, 243–271.CrossRefGoogle Scholar
Tougaard, S. (1996). Surface nanostructure determination by X-ray photoemission spectroscopy peak shape analysis. J Vac Sci Technol A 14, 1415–1423.CrossRefGoogle Scholar
Tougaard, S. (1997). Universality classes of inelastic electron scattering cross-section. Surf Interface Anal 15, 137–154.3.0.CO;2-L>CrossRefGoogle Scholar
Tougaard, S. (1998). Accuracy of the non-destructive surface nanostructure quantification technique based on analysis of the XPS or AES peak shape. Surf Interface Anal 26, 249–269.3.0.CO;2-A>CrossRefGoogle Scholar
Tougaard, S. (2003). Quantitative X-ray photoelectron spectroscopy: Simple algorithm to determine the amount of atoms in the outermost few nanometers. J Vac Sci Technol A 21, 1081–1086.CrossRefGoogle Scholar
Tougaard, S. (2005). Algorithm for automatic X-ray photoelectron spectroscopy data processing and X-ray photoelectron spectroscopy imaging. J Vac Sci Technol A 23(4), 741–745.CrossRefGoogle Scholar
Tougaard, S. (2013). Validity of automated X-ray photoelectron spectroscopy algorithm to determine the amount of substance and the depth distribution of atoms. J Vac Sci Technol A 31, 031502-1–6.CrossRefGoogle Scholar
Tougaard, S. & Hansen, H.S. (1989). Non-destructive depth profiling through quantitative analysis of surface electron spectra. Surf Interface Anal 14, 730–738.CrossRefGoogle Scholar
Walton, J. & Fairley, N. (2005). Noise reduction in X-ray photoelectron spectromicroscopy by a singular value decomposition sorting procedure. J Electron Spectrosc Relat Phenom 148, 29–40.CrossRefGoogle Scholar
Walton, J. & Fairley, N. (2006). Characterisation of the Kratos Axis Ultra with spherical mirror analyser for XPS imaging. Surf Interface Anal 38, 1230–1235.CrossRefGoogle Scholar