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Classification and discrimination of automotive glass using LA-ICP-MS

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Show simple item record Grainger, Megan Nicole Clare Manley-Harris, Merilyn Coulson, Sally 2012-11-08T20:15:11Z 2012-11-08T20:15:11Z 2012 2012
dc.identifier.citation Grainger, M. N. C., Manley-Harris, M., & Coulson, S. (2012). Classification and discrimination of automotive glass using LA-ICP-MS. Journal of Analytical Atomic Spectrometry, 27(9), 1413-1422. en_NZ
dc.identifier.issn 0267-9477
dc.description.abstract Glass is one of the most common types of trace evidence found at crime scenes and on suspects. The elemental analysis of float glass has become increasingly important as the range in values of refractive index has substantially narrowed due to increased quality control in glass manufacture. The purpose of this research was to investigate the variation of elements in automotive float glass relevant to New Zealand for the purpose of classifying and discriminating samples. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used to analyse the elemental composition of 243 automotive glass samples. An intact side window (tempered pane) and an intact windscreen (laminated pane) were analysed to investigate the spatial trend of elements in automotive glass. Most elements displayed no spatial variation over the panes. Pb had the largest variation in the windscreen and was also found to have a large variation in the database. Most samples were able to be classified into the vehicles' country of origin using a multiclass classifier. However, this was not possible for all samples, due to the origin of glass differing from the origin of the vehicle in some cases. The elemental composition of Australian and Northern Hemisphere samples differed greatly making them easy to separate; however, there was little variation within the Australian samples, making it hard to discriminate between different samples. A three step method, which combined the use of elemental composition, △RI and RI, was used to discriminate database samples. The method distinguished 84% (172/204) of samples in the database. When Australian samples were removed from the analysis, the discrimination increased to 95% (148/156). The type II errors were reduced by using both elemental composition and RI measurement. en_NZ
dc.language.iso en
dc.publisher Royal Society of Chemistry en_NZ
dc.relation.ispartof Journal of Analytical Atomic Spectrometry
dc.subject automotive glass en_NZ
dc.subject crime scenes en_NZ
dc.subject elemental compositions en_NZ
dc.subject float glass en_NZ
dc.subject LA-ICP-MS en_NZ
dc.subject laser-ablation inductively-coupled plasma mass spectrometry en_NZ
dc.subject multi-class classifier en_NZ
dc.subject New Zealand en_NZ
dc.subject Northern Hemispheres en_NZ
dc.subject spatial trends en_NZ
dc.subject spatial variations en_NZ
dc.title Classification and discrimination of automotive glass using LA-ICP-MS en_NZ
dc.type Journal Article en_NZ
dc.identifier.doi 10.1039/c2ja30093a en_NZ
pubs.elements-id 37810

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