Examination of Firearms Review: 2007 to 2010 - Interpol

of the more current studies involved analysis of artwork by multiple techniques in
conjunction, providing a greater amount of complementary information on a
single item than was previously possible.
This portion of the review will therefore describe key publications covering the
range of art and archaeological materials analysis from primarily single-technique
examinations to analysis by multiple techniques in combination. Singletechnique
analysis will be broken down into spectroscopic techniques (FTIR,
Raman, fluorescence), X-Ray-based techniques (SEM/EDS, XRF, XRD, PIXE),
laser-based atomic techniques (LA-ICP/MS, LIBS), and separation techniques
(GC/MS, CE).
14. Fourier transform infrared spectroscopy (FTIR)
With regard to FTIR analyses, two primary trends were noted in this review
period: analysis in reflectance mode and the use of multivariate statistics to aid in
data analysis. In fact, some research incorporated both trends. In Rosi et al.,
the strengths and limitations of reflectance mid-FTIR chemometric models for
binder identification were discussed, including how principal components
analysis (PCA) can be used as a data analysis tool.[178] Navas and coauthors
combined diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS)
with PCA to compare transmission FTIR to DRIFTS and found that the intensity
was improved in DRIFTS, making it more suitable for purposes of identification
and characterization of pigments.[179]
Several additional publications considering multivariate statistics were of note.
One included FTIR-ATR analysis of reference standards of polymeric resins to
evaluate multivariate statistics (hierarchical clustering, PCA, Linear Discriminant
Analysis (LDA).[180] LDA provided the best resolution for separating similar
resins. Gruchow and coauthors primarily investigated transmission FTIR
comparing univariate with multivariate statistics, demonstrating the usefulness of
cluster analysis and PCA.[181] Schäning et al. tried to facilitate classification of
organic pigments by partial least-squares discriminate analysis and concluded
that the “…application of the classification models to FTIR spectra of unknown
paint samples gained very similar results as obtained from experts.”[182]
Another example of the application of statistics to analytical datasets acquired in
paint examinations was reported by Latour et al.[183] In this study, diffuse
reflectance spectra of pigment mixtures were simulated from a database of
absorption and scattering coefficients of reference pigments typical of those used
in works of art.
Regarding additional reflectance studies, Poli and coworkers used mid-IR FORS
to analyze a work of art without sampling.[184] A simple method for enhancing
signals in sub-optimal conditions was successfully applied, and spectral
corrections were evaluated for comparing the reflectance spectra with reference
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