Cyril Muehlethaler

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm(-1) and 2730-3600 cm(-1), provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.

Towards a validation of surface-enhanced Raman scattering (SERS) for use in forensic science: repeatability and reproducibility experiments.

In order for a new analytical technique such as surface-enhanced Raman scattering (SERS) to be used in a routine manner, data and studies on the validation of the method are required. In that context, we performed a systematic study of the variability observed at different levels of the analytical procedure (i.e. respectively measurement, sampling, colloids aliquots, colloids batches, laboratories). Our goal is to provide data towards a qualitative validation of the technique for identification purposes. Three molecules of forensic interest were used as probes, respectively crystal violet, methamphetamine and 2,4,6-trinitrotoluene (TNT). We demonstrate that the method is repeatable with RSD and multivariate techniques (PCA). The % RSD at the different analytical stages vary between the molecules and the peaks considered. The repeatability is on the order of 2-6% for crystal violet, and 5-16% for TNT. Methamphetamine binds very weakly to the silver colloids giving much greater variability in the measurements (5-29%). We show that spectra measured in the same conditions (e.g. same laboratory and instrument), even a few days apart, are comparable and stable. The largest source of variation has been identified to be the measurement conditions and the associated random fluctuations in intensity (i.e. Brownian motion of the particles, solvent evaporation and concentration). The influence of the substrate is confirmed to be negligible. However, the reproducibility between different laboratories and different instruments introduced the largest source of variability (∼ 10-70%). Despite these factors, we demonstrate that qualitative identification of the species under analysis by measurement and comparison of peaks position is always successful even though quantitative analysis is, at present, difficult. Regardless of the amount of variability determined, the molecules could always be successfully identified, even on different instruments from different laboratories by utilizing the criterion proposed in the literature (i.e. 3:1 signal-to-noise ratio).

Influence of the shaking time on the forensic analysis of FTIR and Raman spectra of spray paints

In order to decide if replicated measurements of a trace fall within the intra-variability expected for reference paint samples, a forensic scientist has to understand and integrate all reasonable sources of variation. The origins of such variation in spectra can be various, but mainly include differences in components distribution (homogeneity of spraying) or differences originating from the manufacturing process (production batches). Instrumental variation can also be problematic for non-successive measurements. Infrared and Raman spectra were collected to study the homogeneity of the paint distribution after shaking a spray can for times of 0, 1, 2, 3, 4 and 5min. The results confirm that differences arise in both the spectroscopic techniques used in this study. Mainly, this survey shows that the problematic of shaking is particularly important when the pigment content can be detected from spray paint samples within the infrared domain. In these situations, the signal from the pigment might produce strong absorptions that vary with shaking time, leading to differences in relative intensities with respect to those attributed to the binder. For Raman spectroscopy, it has been shown that a gradient of pigment concentration is observable in some samples depending on the shaking time. The proportion of the signal due to the pigment increases with shaking times from 0 to 1min and diminishes afterwards, to finally reach stabilization around 3min of shaking. Not all samples are affected by these differences and it should always be evaluated on a case-by-case basis. From a statistical point-of-view, principal component analyses of the replicates show that the spectra are reproducible after 3min of shaking.

Discrimination and classification of FTIR spectra of red, blue and green spray paints using a multivariate statistical approach

The use of multivariate techniques was investigated in a forensic paint analysis context. The data set consisted of the infrared spectra of 74 spray paint cans, corresponding to three colors code, respectively red, green and blue. Two aspects of the forensic procedure are studied, respectively, the discrimination of paints coming from a market study through exploratory techniques, and the source prediction of unknown samples in database using classifiers. The exploratory discrimination capabilities of principal component analysis (PCA) and hierarchical clusters analysis (HCA) were compared to a visual comparison of the spectra. Iterative PCA was found to be the most adapted solution for exploratory analysis of the samples. Very few differences were found compared to a visual comparison of the samples and the statistical foundations behind the method ensure that no errors are due to a misclassification of the samples. Market studies and joint PCA also represent a significant gain of time. Following that, classification and prediction of future samples were evaluated by means of supervised techniques of classification such as linear/quadratic discriminant analysis (LDA/QDA), support vector machines (SVM), soft independent modeling of classes analogies (SIMCA) and partial least squares discriminant analysis (PLS-DA). SIMCA was the preferred method, as it provided the smallest false negative rates together with a correct classification rate of about 95%. From an investigative point-of-view the presence of false positives was considered acceptable, as it is preferable to have a longer list of possible sources but have confidence that the true source belongs to it.

Survey on batch-to-batch variation in spray paints: A collaborative study

This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (CH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an experts opinion, will provide more objective criteria for decision making.

Forensic aspects of the weathering and ageing of spray paints

This paper presents a preliminary study on the degradation of spray paint samples, illustrated by Optical, FTIR and Raman measurements. As opposed to automotive paints which are specifically designed for improved outdoor exposure and protected using hindered amine light absorbers (HALS) and ultra-violet absorbers (UVA), the spray paints on their side are much simpler in composition and very likely to suffer more from joint effects of solar radiation, temperature and humidity. Six different spray paint were exposed to outdoor UV-radiation for a total period of three months and both FTIR and Raman measurements were taken systematically during this time. These results were later compared to an artificial degradation using a climate chamber. For infrared spectroscopy, degradation curves were plotted using the photo-oxidation index (POI), and could be successfully approximated with a logarithmic fitting (R(2)>0.8). The degradation can appear after the first few days of exposure and be important until 2 months, where it stabilizes and follow a more linear trend afterwards. One advantage is that the degradation products appeared almost exclusively at the far end (∼3000cm(-1)) of mid-infrared spectra, and that the fingerprint region of the spectra remained stable over the studied period of time. Raman results suggest that the pigments on the other side, are much more stable and have not shown any sign of degradation over the time of this study. Considering the forensic implications of this environmental degradation, care should be taken when comparing samples if weathering is an option (e.g. an exposed graffiti compared to the paint from a fresh spray paint can). Degradation issues should be kept in mind as they may induce significant differences between paint samples of common origin.

Forensic Paint Analysis

Paint is often encountered in criminal cases and its exploitation is done in accordance with specific analytical schemes. Depending on the circumstances of the case and the capabilities of the laboratory, specific techniques are applied. The choice of the analytical sequence relies not only on the presence/absence of control material but also on the nature of the samples recovered. Optical examination (stereomicroscopy and microscopy) is the first and most important step of the sequence. It allows rapid discrimination between paints of similar color and also helps in determining the nature of the traces (automotive or household paints). Then, analytical techniques, such as infrared spectroscopy, Raman spectroscopy, microspectrophotometry, pyrolysis–gas chromatography–mass spectrometry, or elemental analysis, offer possibilities to further differentiate and characterize the samples.

Contribution of Raman and Surface Enhanced Raman Spectroscopy (SERS) to the analysis of vehicle headlights: Dye(s) characterization

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.

EXPRESS: Competitive binding investigations and quantitation in surface enhanced Raman spectra of binary dye mixtures

This research presents a study in surface-enhanced Raman quantitation of dyes present in mixtures of alizarin and purpurin using standard calibration curves and Langmuir isotherm calibration models. Investigations of the nature of competitive adsorption onto silver nanoparticles by centrifugation indicates that both dyes in the mixture interact with the nanoparticles simultaneously, but only the stronger adsorbing one is seen to dominate the spectral characteristics. Calibration can be carried out by careful selection of peaks characteristic to each dye in the mixture. Comparisons of peak height and peak area calibrations reveal that peak heights, when selected by the maximum value and accounting for peak shifts, prove the better model for quantitation. It is also shown that the microwave nanoparticle synthesis method produces stable nanoparticles with a shelf-life of at least one year that give very little variation within and between uses.

Evaluation and Examination of a Possible Shoe-polish Trace in a Hold-up Case

In this article, we show how the Bayesian framework can be applied to a hold-up case involving a possible shoe-polish trace according to one of the parties. This article highlights the importance of interpreting data from the beginning of the examination through the preassessment steps. Once a set of alternative propositions in agreement with the information provided by the parties is chosen, one can establish what is needed in the case. Here, limited data were available to assign factors such as transfer and rarity of the traces. Consequently, we showed how specific case-tailored experiments provide meaningful data for evaluation. In this case, the police had observed a trace on the jacket of a person who reported to have been pushed with the offenders gun during the hold-up attempt. When the jacket was submitted to our laboratory, the exact nature of the trace was unknown. Particles from this trace were collected and analyzed by stereomicroscopy, microscopy, and infrared spectroscopy. The obtained results supported that this trace was waxy material. The literature dealing with the analysis of waxy materials generally uses solvent extraction-based methods. Here, as our analytical sequence allowed a good discrimination of different waxy products of known origin, we considered that this methodology was adequate. Moreover, it did not involve any extraction step that could lead to undesired compounds from the substrate (e.g., dyes and additives). This article therefore suggests an alternative analytical sequence for the analysis of such material in casework.