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Multi-imaging and multivariate statistics used for 3D characterization at surfaces

Prutton, M., Barkshire, I.R., Kenny, Peter G., Roberts, R.H., Wenham, M. (1996) Multi-imaging and multivariate statistics used for 3D characterization at surfaces. Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences., 354 (1719). pp. 2683-2695. ISSN 0261-0523. (doi:10.1098/rsta.1996.0123) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:21414)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1098/rsta.1996.0123

Abstract

Several microanalytical imaging techniques--energy dispersive X-ray detection, parallel electron energy loss spectroscopy, secondary ion mass spectroscopy, photoelectron spectroscopy and XPS) and scanning Auger microscopy--have reached the stage where they are capable of producing images of a surface with a section of a spectrum in each pixel. The resulting image-spectrum is a complex data structure which requires the use of special methodologies if the data are to be interpreted effectively. Appropriate methods have been developed for Earth satellite image processing and are directly applicable to surface microanalysis. The use of scatter diagrams, interactive correlation partitioning, factor and target factor analysis and principal component analysis are outlined in this paper and their application to semiconducting, catalytic and magnetic structures is illustrated. This field of endeavour can be thought of as being the beginning of an area of study which may be called surface chemometrics.

Item Type: Article
DOI/Identification number: 10.1098/rsta.1996.0123
Additional information: Invited paper at Royal Society Meeting on Three Dimensional Chemical Characterisation of Electronic Materials, London, June 1995
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 21 Aug 2009 10:49 UTC
Last Modified: 16 Nov 2021 09:59 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/21414 (The current URI for this page, for reference purposes)

University of Kent Author Information

Kenny, Peter G..

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