Characterisation And Classification Of Automotive Clear Coats With Raman Spectroscopy And Chemometrics For Forensic Purposes

Keywords

automotive clear coats; forensic science; linear discriminant analysis; principal component analysis; Raman spectroscopy

Abstract

The clear coats from a collection of automotive paint samples of 139 vehicles, covering a range of Australian and international vehicle manufacturers and sold in Western Australia, were characterised using FT-Raman spectroscopy. Principal component analysis (PCA) revealed 19 distinct classes that were associated with the vehicles' manufacturer and model, and in the case of Australian manufacturers, the years of manufacture. Linear discriminant analysis based on the PCA groupings gave excellent discrimination between the groups with 96.9% of the calibration set and 97.6% of the validation set being correctly classified. Although the sample set comprised only vehicles available in Australia, the methodology used is universal and hence applicable in any jurisdiction that is willing and able to generate a statistically significant data set and maintain and update it as new vehicles appear on the market. A FT-Raman spectroscopy-based database would rapidly provide information regarding vehicle origin and manufacture and hence generate investigative leads for questioned paint samples found at incident sites. Copyright © 2016 John Wiley & Sons, Ltd.

Publication Date

8-1-2016

Publication Title

Journal of Raman Spectroscopy

Volume

47

Issue

8

Number of Pages

948-955

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1002/jrs.4925

Socpus ID

84963858663 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84963858663

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