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Multivariate data analysis using spectroscopic data of fluorocarbon alcohol mixtures / Nothnagel, C.

Pelchem, a commercial subsidiary of Necsa (South African Nuclear Energy Corporation), produces a range of commercial fluorocarbon products while driving research and development initiatives to support the fluorine product portfolio. One such initiative is to develop improved analytical techniques to analyse product composition during
development and to quality assure produce.
Generally the C–F type products produced by Necsa are in a solution of anhydrous HF, and cannot be directly analyzed with traditional techniques without derivatisation. A technique such as vibrational spectroscopy, that can analyze these products directly without further preparation, will have a distinct advantage. However, spectra of mixtures of similar compounds are complex and not suitable for traditional quantitative regression analysis.
Multivariate data analysis (MVA) can be used in such instances to exploit the complex nature of spectra to extract quantitative information on the composition of mixtures.
A selection of fluorocarbon alcohols was made to act as representatives for fluorocarbon compounds. Experimental design theory was used to create a calibration range of mixtures
of these compounds. Raman and infrared (NIR and ATR–IR) spectroscopy were used to
generate spectral data of the mixtures and this data was analyzed with MVA techniques by
the construction of regression and prediction models. Selected samples from the mixture
range were chosen to test the predictive ability of the models.
Analysis and regression models (PCR, PLS2 and PLS1) gave good model fits (R2 values larger
than 0.9). Raman spectroscopy was the most efficient technique and gave a high prediction
accuracy (at 10% accepted standard deviation), provided the minimum mass of a
component exceeded 16% of the total sample.
The infrared techniques also performed well in terms of fit and prediction. The NIR spectra were subjected to signal saturation as a result of using long path length sample cells. This was shown to be the main reason for the loss in efficiency of this technique compared to Raman and ATR–IR spectroscopy.
It was shown that multivariate data analysis of spectroscopic data of the selected
fluorocarbon compounds could be used to quantitatively analyse mixtures with the
possibility of further optimization of the method. The study was a representative study
indicating that the combination of MVA and spectroscopy can be used successfully in the
quantitative analysis of other fluorocarbon compound mixtures. / Thesis (M.Sc. (Chemistry))--North-West University, Potchefstroom Campus, 2012.

Identiferoai:union.ndltd.org:NWUBOLOKA1/oai:dspace.nwu.ac.za:10394/7064
Date January 2012
CreatorsNothnagel, Carien
PublisherNorth-West University
Source SetsNorth-West University
Detected LanguageEnglish
TypeThesis

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