ABSTRACT
Alternate least squares (ALS) reconstructions of the infrared (IR) spectra of the individual layers from original automotive paint were analyzed using machine learning methods to improve both the accuracy and speed of a forensic automotive paint examination. Twenty-six original equipment manufacturer (OEM) paints from vehicles sold in North America between 2000 and 2006 served as a test bed to validate the ALS procedure developed in a previous study for the spectral reconstruction of each layer from IR line maps of cross-sectioned OEM paint samples. An examination of the IR spectra from an in-house library (collected with a high-pressure transmission diamond cell) and the ALS reconstructed IR spectra of the same paint samples (obtained at ambient pressure using an IR transmission microscope equipped with a BaF2 cell) showed large peak shifts (approximately 10 cm-1) with some vibrational modes in many samples comprising the cohort. These peak shifts are attributed to differences in the residual polarization of the IR beam of the transmission IR microscope and the IR spectrometer used to collect the in-house IR spectral library. To solve the problem of frequency shifts encountered with some vibrational modes, IR spectra from the in-house spectral library and the IR microscope were transformed using a correction algorithm previously developed by our laboratory to simulate ATR spectra collected on an iS-50 FT-IR spectrometer. Applying this correction algorithm to both the ALS reconstructed spectra and in-house IR library spectra, the large peak shifts previously encountered with some vibrational modes were successfully mitigated. Using machine learning methods to identify the manufacturer and the assembly plant of the vehicle from which the OEM paint sample originated, each of the twenty-six cross-sectioned automotive paint samples was correctly classified as to the "make" and model of the vehicle and was also matched to the correct paint sample in the in-house IR spectral library.
ABSTRACT
A previously published study featuring an attenuated total reflection (ATR) simulation algorithm that mitigated distortions in ATR spectra was further investigated to evaluate its efficacy to enhance searching of infrared (IR) transmission libraries. In the present study, search prefilters were developed from transformed ATR spectra to identify the assembly plant of a vehicle from ATR spectra of the clear coat layer. A total of 456 IR transmission spectra from the Paint Data Query (PDQ) database that spanned 22 General Motors assembly plants and served as a training set cohort were transformed into ATR spectra by the simulation algorithm. These search prefilters were formulated using the fingerprint region (1500 cm-1 to 500 cm-1). Both the transformed ATR spectra (training set) and the experimental ATR spectra (validation set) were preprocessed for pattern recognition analysis using the discrete wavelet transform, which increased the signal-to-noise of the ATR spectra by concentrating the signal in specific wavelet coefficients. Attenuated total reflection spectra of 14 clear coat samples (validation set) measured with a Nicolet iS50 Fourier transform IR spectrometer were correctly classified as to assembly plant(s) of the automotive vehicle from which the paint sample originated using search prefilters developed from 456 simulated ATR spectra. The ATR simulation (transformation) algorithm successfully facilitated spectral library matching of ATR spectra against IR transmission spectra of automotive clear coats in the PDQ database.
ABSTRACT
Attenuated total reflection (ATR) is a widely used sampling technique in infrared (IR) spectroscopy because minimal sample preparation is required. Since the penetration depth of the ATR analysis beam is quite shallow, the outer layers of a laminate or multilayered paint sample can be preferentially analyzed with the entire sample intact. For this reason, forensic laboratories are taking advantage of ATR to collect IR spectra of automotive paint systems that may consist of three or more layers. However, the IR spectrum of a paint sample obtained by ATR will exhibit distortions, e.g., band broadening and lower relative intensities at higher wavenumbers, compared with its transmission counterpart. This hinders library searching because most library spectra are measured in transmission mode. Furthermore, the angle of incidence for the internal reflection element, the refractive index of the clear coat, and surface contamination due to inorganic contaminants can profoundly influence the quality of the ATR spectrum obtained for automotive paints. A correction algorithm to allow ATR spectra to be searched using IR transmission spectra of the paint data query (PDQ) automotive database is presented. The proposed correction algorithm to convert transmission spectra from the PDQ library to ATR spectra is able to address distortion issues such as the relative intensities and broadening of the bands, and the introduction of wavelength shifts at lower frequencies, which prevent library searching of ATR spectra using archived IR transmission data.
ABSTRACT
Attenuated total reflection (ATR) spectroscopy is now the most popular sampling technique for the measurement of infrared spectra of condensed phase samples. Most practitioners of ATR spectroscopy use the equation for depth of penetration, d(p), to estimate the path length of the evanescent wave through the sample. However, the effective path length, d(e), of the evanescent wave in an ATR measurement, i.e., the equivalent path length in a transmission measurement that would lead to an absorption band of the same intensity, is a more accurate metric than d(p). In measurements designed to obtain the absorptivity of bands in the spectrum of a strongly absorbing viscous liquid, we have shown that the refractive index used in the expressions for d(e) must be modified to take into account the effect of anomalous dispersion before accurate effective path lengths and band absorptivities can be measured.
ABSTRACT
During measurements of open-path Fourier transform infrared spectra, airborne dust may be present in the infrared beam. We have investigated the feasibility of identifying and quantifying the airborne particulate matter from spectra measured in this way. Although the results showed that analysis of the particulate matter was not able to be performed from these spectra, insight into the size and wavelength dependence of the Christiansen effect at wavelengths where the particles absorb strongly was obtained. Airborne particles larger than or equal to the wavelength of the incident radiation give rise to asymmetrical features in the spectrum caused by the Christiansen effect. However, the transmittance at wavelengths where the refractive index of the particles equals that of the atmosphere never reaches 1.0 because of absorption by the particles. As the particle size becomes much smaller than the wavelength of the incident radiation, the Christiansen effect becomes less pronounced and eventually is not exhibited.
ABSTRACT
Dynamic compression modulation attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopic methods have been developed in this paper for characterizing polymer films. To obtain dynamic compression polarized ATR spectra, internal reflection element (IRE) secure assemblies made of tungsten carbide with very high hardness (Knoop hardness of > 1000 kgf/mm(2)) have been designed. These assemblies are mounted on the Harrick Seagull ATR attachment and measured by step-scan FT-IR spectroscopy. The effect of static compression, air gaps, and refractive index changes were examined. Experimental and simulated results showed that the effect of air gaps between the sample and IRE and refractive index changes of the sample and IRE are negligible at values larger than a static torque of 40 cN m and good signal-to-noise ratios (SNR) and reproducible data can be obtained. Uniaxially and biaxially drawn poly(ethylene terephthalate) films were measured by the presented method. Both bipolar and unipolar bands were observed in the dynamic in-phase ATR spectra, which can be associated with their micro-structural environmental changes. This technique shows promise in evaluating various polymer film materials, including biaxially oriented films, multilayer coated film surfaces, and molecular interactions between polymer-polymer and polymer-additives at the film surface.
