Muehlethaler Cyril, Cheng Yin Pak, Islam Syed K, Lombardi John R
University of Quebec at Trois-Rivières, Department of Chemistry, Biochemistry and Physics, Canada; Laboratoire de Recherche en Criminalistique, Trois-Rivières, Canada.
Department of Chemistry, City College of New York, USA.
Forensic Sci Int. 2018 Jun;287:98-107. doi: 10.1016/j.forsciint.2018.03.036. Epub 2018 Mar 31.
Although ubiquitous on accident scenes, the polymers from headlight optics are often neglected in hit-and-run cases, and their evidential value restrained to direct comparison once a corresponding vehicle is found. Multilayered automotive paint fragments are preferred for their access to corresponding databases (PDQ, EUCAP) to infer models and brands of cars. The potential of polymers headlights for providing forensic intelligence has never been exploited, principally due to the lack of diversity, of appropriate databases, and of case examples. The motives are very simple however. Headlight polymers suffer from a lack of differentiation, and about 90% of them are composed of polymethylmethacrylate (PMMA). The discriminating powers using techniques in sequence typically range from 30 to 60%. In this paper, we take advantage of the extreme sensitivity of Surface Enhanced Raman Spectroscopy (SERS) to analyze the dye composition of the polymer headlights. The measurements by standard Raman spectroscopy at 488, 633, and 785nm permits us to identify the polymer type with relative ease. 51 out of 53 samples are composed of PMMA, the two remaining being either Polycarbonate or Polybutylene terephthalate. Additionally, using SERS with silver colloids at 488 and 633nm, provides enhanced spectra of the dyes used in the composition with an extreme sensitivity and specificity. With SERS we are able to differentiate the majority of the headlights with a remarkable 90-100% discriminating power. Solvent Orange 60, Solvent Red 52 and Solvent Red 111 were successfully identified as dyes used in the manufacture of the headlights. These results demonstrate that a combined Raman-SERS approach has the potential to replace an otherwise lengthy sequence of many different analytical techniques. With one single instrument, we offer the possibility to combine an analysis of the polymer type, and of the dye components with high discriminating capabilities. These results open up new opportunities for exploiting headlight plastics in road accidents investigations. It has the potential to help in source attribution, and/or database building in a forensic intelligence perspective.