Non-invasive identification of organic materials in wall paintings by fiber optic reflectance infrared spectroscopy: a statistical multivariate approach.
ABSTRACT The aim of this study is to develop a method for the non-invasive and in situ identification of organic binders in wall paintings by fiber optic mid-FTIR reflectance spectroscopy. The non-invasive point analysis methodology was set-up working on a wide set of wall painting replicas of known composition and using statistical multivariate methods, in particular principal component analysis (PCA), for the interpretation, understanding, and management of data acquired with reflectance mid-FTIR spectroscopy. Results show that PCA can be helpful in managing and preliminary sorting of the large amount of spectra typically collected during non-invasive measurement campaigns and highlight further avenues for research. The developed PCA model was finally applied to the case of a Renaissance wall painting by Perugino assessing it predictability as compared to the interpretation of the single spectrum.
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ABSTRACT: Natural organic substances are involved in many aspects of the cultural heritage field. Their presence in different forms (raw, heated, mixed), with various conservation states, constitutes a real challenge regarding their recognition and discrimination. Their characterization usually involves the use of separative techniques which imply destructive sampling and specific analytical preparations. Here we propose a non destructive approach using FT-Raman and infrared spectroscopies for the identification and differentiation of natural organic substances. Because of their related functional groups, they usually present similar vibrational signatures. Nevertheless the use of appropriate signal treatment and statistical analysis was successfully carried out to overcome this limitation, then proposing new objective discriminating methodology to identify these substances. Spectral decomposition calculations were performed on the CH stretching region of a large set of reference materials such as resins, oils, animal glues, and gums. Multivariate analyses (Principal Component Analyses) were then performed on the fitting parameters, and new discriminating criteria were established. A set of previously characterized archeological resins, with different surface aspects or alteration states, was analyzed using the same methodology. These testing samples validate the efficiency of our discriminating criteria established on the reference corpus. Moreover, we proved that some alteration or ageing of organic materials is not an issue to their recognition.Talanta 10/2013; 115:540–547. · 3.50 Impact Factor
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ABSTRACT: We report a pyrolysis GC-MS method capable of analysing Indigenous Australian and European binders typically used in the manufacture of culturally important painted works. Eleven different traditional European binders and ten different Indigenous Australian binders were examined. The method allows discrimination between highly complex and impure lipid, resin, polysaccharide, wax, and protein-based binders. Each was found to have characteristic pyrolysis products that were unique to the binder material, demonstrating the potential for differentiation of these binders on Australian Aboriginal artworks towards identification and conservation of cultural heritage.Analytica chimica acta 11/2013; 803:194-203. · 4.31 Impact Factor
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ABSTRACT: MidIR fibre optic reflectance (MidIR-FORS) is a promising analytical technique in the field of science conservation, especially because it is non-destructive. Another advantage of MidIR-FORS is that the obtained information is representative, as a large amount of spectral data can be collected. Although the technique has a high potential and is almost routinely applied, its quality parameters have not been thoroughly studied in the specific application of analysis of artistic materials. The objective of this study is to evaluate the instrumental capabilities of MidIR-FORS for the analysis of artwork materials in terms of detection limit, reproducibility, and mixture characterisation. The study has been focused on oil easel painting and several paints of known composition have been analysed. Paint layers include blue pigments not only because of their important role along art history, but also because their physical and spectroscopic characteristics allow a better evaluation of the MidIR-FORS capabilities. The results of the analysis indicate that MidIR-FORS supplies a signal affected by different factors, such as the optical, morphological and physical properties of the surface, in addition to the composition of materials analysed. Consequently, the detection limits established are relatively high for artistic objects (Prussian blue - PB 2.1-6.5%; Phthalocyanine blue - Pht 6.3-10.2%; synthetic Ultramarine blue - UM 12.1%) and may therefore lead to an incomplete description of the artwork. Reproducibility of the technique over time and across surface has been determined. The results show that the major sources of dispersion are the heterogeneity of the pigments distribution, physical features, and band shape distortions. The total dispersion is around 4% for the most intense bands (oil) and increases up to 26% when weak or overlapped bands are considered (PB, Pht, UM). The application of different pre-treatments (cutoff of fibres absorption, Savizky-Golay smoothing algorithm, polynomial baseline offset, Standard Normal Variate algorithm - SNV) to the raw spectra allows improving these results to maximum values of 15%. Finally, the capabilities of PCA and MidIR-FORS to discriminate between binary mixtures were tested. The results demonstrate that it is possible to differentiate mixtures depending on the range of concentration of their components, within specific limits of detection.Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy 07/2013; 115C:617-628. · 1.98 Impact Factor