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                            Library & Multimedia
 Signal-to-noise ratios in forensic glass analysis by micro X-ray fluorescence spectrometry
NCJ Number
              304172

Author(s)
          T. Ernst;
                        et al
Date Published

2012
Length
              9 pages
Annotation
              This article reports on a project that demonstrated a practical method for applying the concepts of signal-to-noise ratio (SNR), limits of detection, and limits of quantitation to μ-XRF generated EDS-based spectra; and it discusses the implications of such determinations, addresses spectral features that must be considered when making the calculations, and illustrates the application of these concepts to forensic examination and comparison of glass samples.
Abstract
              Micro X-ray fluorescence (μ-XRF) spectrometry using an energy dispersive X-ray (EDS) detector is capable of detecting certain major, minor, and trace elements that permit potential discrimination of glass fragments in forensic cases on the basis of differences in elemental composition. Often, elements used for discrimination are present at concentrations near the detection limit of the EDS system, and the decision whether to use these minor peaks in a comparative analysis has generally been left to the discretion of the examiner. The use of signal-to-noise ratios (SNRs) of spectral peaks provides additional objectivity in peak identification/label decisions and in the selection of elements in semiquantitative ratio comparisons. In addition, the use of SNRs enables calculations of limits of detection and limits of quantitation, as well as the monitoring of instrument performance. It also facilitates performance comparisons of different μ-XRF configurations. (publisher abstract modified)
      
  
          Additional Details
Grant Number(s)
        2009-DN-BX-K252


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Significance of Elemental Analysis from Trace Evidence
    
  
  
Date Published: January 1, 2012
    
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