4.7 Article

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

期刊

JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY
卷 27, 期 9, 页码 1413-1422

出版社

ROYAL SOC CHEMISTRY
DOI: 10.1039/c2ja30093a

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资金

  1. ESR Scholarship
  2. University of Waikato Research Scholarship
  3. New Zealand Federation of Graduate Women Charitable Trust Award
  4. Todd Foundation Award for Excellence
  5. Bonded Merit Scholarship
  6. University of Waikato Master Fees Award

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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, Delta 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.

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