Parri, M C (2014) New Methods for Quantifying X-ray Spectra in a Transmission Electron Microscope. PhD thesis, University of Sheffield.
Abstract
In an effort to develop new methods of analysis and improving quantification accuracy in the
transmission electron microscope (TEM) while using energy-dispersive X-ray spectroscopy (EDXS), several methods have been explored. Some of these methods have been applied to a sample that has a thin layer of some material embedded within a matrix of another material, while others can be applied to any sample that is homogeneous in chemical composition or nearly so.
For those methods that are applied to a thin layer embedded within a matrix, several conclusion can be drawn. While each of these methods works in simulations, only two ('absorption matching') provide reasonable results for experimental data. Unfortunately, these results differ considerably for the same sample. The other methods either prove to be so sensitive that the data scatter is too large to draw meaningful conclusions from, or so insensitive that any change of a useful magnitude would not be detected.
The remaining methods were found to give good results, particularly when used together. The X-ray intensity ratio from a pair of X-rays from a single spectrum (generally from the same element) can be used to calculate the sample thickness for that spectrum. The second method was a means of plotting a function of the Cliff-Lorimer k-factor as a function of thickness in order to better calculate the effect of absorption. Combined, these two methods can give considerably superior quantification of the chemical composition than when used alone.
Metadata
Supervisors: | Walther, Thomas |
---|---|
Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Electronic and Electrical Engineering (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.634332 |
Depositing User: | Mr M C Parri |
Date Deposited: | 22 Jan 2015 15:49 |
Last Modified: | 03 Oct 2016 12:09 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:7771 |
Download
Thesis
Filename: Thesis.pdf
Licence:
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 2.5 License
Export
Statistics
You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.