This the final report on the findings and methodology of a research project with the overall goal of improving the fundamental basis of elemental analysis and comparative analysis of paint by scanning electron microscopy coupled with energy dispersive x-ray spectrometry (SEM-EDS), a well-established technique for the microscopical and elemental analysis of macro- and microscopic materials.
This report is designed to provide an overview of project findings; however, the full extent of the findings and their interpretation in forensic analysis will be published in a series of articles currently being prepared. The layers selected as analogs were for common vehicle paints that may be seen in casework. SEM-EDS analysis for layered automotive paint samples was performed, and Monte Carlo simulation was used to examine the distance that must be kept to adjacent layers when elevating the area for analysis to avoid a mixed EDS signal. The consistency of the results is encouraging because this indicates it is possible to separate or exclude a signal from a sample adjacent to the analysis. A 5mm distance to an adjacent layer may prevent challenges when working with thin automotive paint layers. The results from the elemental analysis of the nearly 1,300 individual layers show significant elemental diversity among the layers. This report indicates that the elemental profiles of basecoats and primer layers hold the greatest potential for sample discrimination. The project team anticipates that the results of this research will benefit crime laboratories by improving the scientific basis for paint evidence, the overall significance of paint comparisons, and the investigative value of forensic paint samples provides more specific guidance on numerous aspects of the elemental analysis of paints. 1 table and 13 references
Downloads
Similar Publications
- GIS Application for Building a Nationally Representative Forensic Taphonomy Database
- Discrimination Between Human and Animal Blood Using Raman Spectroscopy and a Self-Reference Algorithm for Forensic Purposes: Method Expansion and Validation
- Enhancing Fault Ride-Through Capacity of DFIG-Based WPs by Adaptive Backstepping Command Using Parametric Estimation in Non-Linear Forward Power Controller Design