Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.661039
Title: Characterisation of HFC-134a by gas chromatography-mass spectrometry and chemometrics
Author: Reilly, Michael Anthony
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 1999
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Abstract:
1,1,1,2-tetrafluoroethane (HFC 134a) is one of the major replacement compounds for chlorofluorocarbons and is therefore of great industrial importance. This work describes a method of characterisation for HFC 134a. The method profiled the levels of synthesis by-products present in samples of HFC 134a using gas chromatography (GC) with detection by flame ionisation detector (FID) or electron capture detector (ECD). The principal method for identification of the by-products was EI GC-mass spectrometry. The multi-variate data produced by the profiling of samples were analysed using chemometric techniques. A training set of samples of HFC 134a, with known origins of production, was analysed by both GC-FID and GC-ECD. This training data set was used to investigate the different methods of chemometric analysis as applied to the raw data, normalised data and principal component analysed data. K-means clustering and Hierarchical clustering were investigated to find the optimum methods for the identification of samples' origins of production based on their chromatographic profiles. The FID chromatographic traces could be correctly identified by applying a two step principal component analysis (PCA) using a hierarchical clustering method to classify the samples. The ECD chromatographic data could be correctly identified by applying a PCA followed by classification using a hierarchical clustering method. The two classification techniques were used to identify further samples of HFC 134a into clusters belonging to the known origins of production or into new clusters representing samples of unknown origin. Classification of samples using the ECD data required the least amount of operator interpretation and provided the least amount of ambiguity in sample identification.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.661039  DOI: Not available
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