ePrints

Multivariate Auger Feature Imaging (MAFI) - a new approach towards chemical state identification of novel carbons in XPS imaging

Lookup NU author(s): Dr Anders Barlow, Dr Naoko Sano, Professor Peter Cumpson

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

The clear identification of allotropes and similar chemical states of carbon in XPS imaging can be made difficult because of the subtle differences observed in spectra, particularly when varying from sp(2) to sp(3) hybridised carbon. By shifting focus from the commonly analysed C1s region in XPS spectra to the often ignored C KVV region, we utilise the so-called D-Parameter to identify different forms of carbon in a surface. When this methodology is applied to XPS imaging, the result is a powerful and unambiguous tool for the chemical state identification of carbon in XPS images. Further enhancement by multivariate statistics improves XPS spectral and image quality, and we call this technique Multivariate Auger Feature Imaging. Herein, we have applied this technique to clearly identify in XPS imaging a graphite film mounted on carbon tape. Copyright (c) 2015 John Wiley & Sons, Ltd.

Publication metadata

Author(s): Barlow AJ, Scott O, Sano N, Cumpson PJ

Publication type: Article

Publication status: Published

Journal: Surface and Interface Analysis

Year: 2015

Volume: 47

Issue: 2

Pages: 173-175

Print publication date: 01/02/2015

Online publication date: 20/01/2015

Acceptance date: 26/11/2014

ISSN (print): 0142-2421

ISSN (electronic): 1096-9918

Publisher: John Wiley & Sons, Ltd.

URL: http://dx.doi.org/10.1002/sia.5738

DOI: 10.1002/sia.5738

Altmetrics

Share