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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*
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: Hajati@mail.yu.ac.ir

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.

Type
Equipment and Techniques Development: Materials
Copyright
Copyright © Microscopy Society of America 2013 

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