Application of Raman spectroscopy to the differentiation of lipsticks for forensic purposes

Raman spectroscopy was applied to the forensic analysis and differentiation of lipstick samples. Spectra were obtained from 73 different lipstick samples. 11 % of the samples gave fluorescent spectra. 21.9% gave spectra that were unique to the individual lipstick. The remaining 67.1 % could be divid...

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Bibliographic Details
Main Author: Salahioglu, Fatma
Published: University of Kent 2012
Subjects:
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.593898
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Summary:Raman spectroscopy was applied to the forensic analysis and differentiation of lipstick samples. Spectra were obtained from 73 different lipstick samples. 11 % of the samples gave fluorescent spectra. 21.9% gave spectra that were unique to the individual lipstick. The remaining 67.1 % could be divided into seven groups, each of which could be differentiated from one another. Identification of the component dye peaks in the lipstick spectra allowed further classification of the samples within each group. A spectral library of lipstick samples was built. Effects of ageing on the Raman spectra of lipsticks were investigated. The majority of the spectra of deposited lipstick samples remained unchanged over a period of up to two years. In some of the aged lipstick spectra, the (C=C) band at 1655 em-l and the (=CH) band at 3011 em"\ were found to decrease in intensity and disappear over time. Trace amounts of lipstick smears deposited on textile fibres, cigarette butts and paper tissues were analysed. Differentiation of lipstick smears could be achieved with little or no interference from the underlying medium. Lipstick smears on glass slides, cigarette butts and tissues could also be analysed and identified in situ through evidence bags. Use of chemometrics for the characterisation of large numbers' of lipstick spectra was explored. Thirty spectra each from ten different lipsticks were analysed by Principal Components Analysis (PCA) and classified using the K-Nearest Neighbours (KNN) classifier. Up to 98.7% correct classification was achieved. Spectra from trace amounts of lipstick smears deposited on fibres were also analysed and classified using the same technique. 100% correct classification of these samples was achieved. This study has demonstrated that Raman spectroscopy is an invaluable tool for discriminating between lipstick samples under a range of forensically relevant situations. 11