Characterization of Automotive Paint Clear Coats by Ultraviolet Absorption Microspectrophotometry with Subsequent Chemometric Analysis

Abstract

Clear coats have been a staple in automobile paints for almost thirty years and are of forensic interest when comparing transferred and native paints. However, the ultraviolet (UV) absorbers in these paint layers are not typically characterized using UV microspectrophotometry, nor are the results studied using multivariate statistical methods. In this study, measurements were carried out by UV microspectrophotometry on 71 samples from American and Australian automobiles, with subsequent chemometric analysis of the absorbance spectra. Sample preparation proved to be vital in obtaining accurate absorbance spectra and a method involving peeling the clear coat layer and not using a mounting medium was preferred. Agglomerative hierarchical clustering indicated three main groups of spectra, corresponding to spectra with one, two, and three maxima. Principal components analysis confirmed this clustering and the factor loadings indicated that a substantial proportion of the variance in the data set originated from specific spectral regions (230-265 nm, 275-285 nm, and 300-370 nm). The three classes were well differentiated using discriminant analysis, where the cross-validation accuracy was 91.6% and the external validation accuracy was 81.1%. However, results showed no correlation between the make, model, and year of the automobiles.

Chemometrics

“…Association and classification of paint samples using HCA, PCA, and discriminant analysis has also been demonstrated (Liszewski et al, 2010;Muehlethaler et al, 2011;Maric et al, 2014). Maric et al analyzed the primer surface layer in automotive paints using synchrotron FTIR (Maric et al, 2014).…”

The effect of environmental degradation on the characterisation of automotive clear coats by infrared spectroscopy

“…Recent studies by Liszewski [12] and Mendlein [13] found that clear coats could be differentiated into broad classes based on their UV microspectrophotometry or micro Raman spectra with chemometric analysis, although they were unable to correlate the separation of samples with the make, model or year of vehicle manufacture. Several publications by Lavine [14][15][16][17][18][19][20].…”

Assessing the effect of data pretreatment procedures for principal components analysis of chromatographic data

“…[1] Since publication of this report, there has been increasing interest in applying multivariate statistical procedures to forensically relevant chromatographic and spectral data. For example, principal components analysis (PCA), cluster analysis, and discriminant analysis have been applied in the analysis of fire debris [2][3][4][5], explosives [6], controlled substances [7][8][9], and various trace evidence types including hair [10], soil [11], electrical tape [12], and paint [13][14][15]. Forensic research in this area has conclusively demonstrated the potential of these procedures for case work.…”