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                            Library & Multimedia
 Transmission Infrared Imaging Microscopy and Multivariate Curve Resolution Applied to the Forensic Examination of Automotive Paints
NCJ Number
              307457
Journal

*Talanta* Volume: 186 Dated: 15 August 2018 Pages: 662-669
Author(s)
          Francis Kwofie;
                        Undugodage Don Nuwan Perera;
                        Matthew D. Allen;
                        Barry K. Lavine
Date Published

August 2018
Length
              8 pages
Annotation
              This article presents an imaging approach to IR analysis of automotive paint using infrared (IR) spectroscopy that saves time and eliminates the need to analyze each layer separately, but also ensures that the final spectrum of each layer is “pure” and not a mixture.
Abstract
              This imaging approach to IR analysis of automotive paint using infrared (IR) spectroscopy not only saves time and eliminates the need to analyze each layer separately, but also ensures that the final spectrum of each layer is “pure” and not a mixture. In the forensic examination of automotive paint, each layer of paint is analyzed individually by IR spectroscopy. Laboratories in North America typically hand section each layer and present each separated layer to the spectrometer for analysis, which is time consuming. In addition, sampling too close to the boundary between adjacent layers can pose a problem as it produces an IR spectrum that is a mixture of the two layers. Not having a “pure” spectrum of each layer will prevent a meaningful comparison between each paint layer or in the situation of searching an automotive database will prevent the forensic paint examiner from developing an accurate hit list of potential suspects. These two problems can be addressed by collecting concatenated IR data from all paint layers in a single analysis by scanning across the cross sectioned layers of the paint sample using aFTIR imagingmicroscope. Decatenation of the IR data is achieved by multivariate curve resolution using a Varimax extended rotation to select the starting point (i.e., initial estimates of the reconstructed IR spectra of each layer) for the alternating least squares algorithm to obtain apureIR spectrum of each automotive paint layer. Comparing the reconstructed IR spectrum of each layer against the IR spectral library of the PDQ database demonstrated that it is possible to identify the correct model of the vehicle from these reconstructed spectra. (Published Abstract Provided)
      
  
          Additional Details
Grant Number(s)
        2014-DN-BX-K087


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Application of Infrared Imaging and Chemometrics to Facilitate the Forensic Examination of Automotive Paints
    
  
  
Date Published: August 1, 2018
    
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