A comprehensive dataset of vibrational spectra of different natural organic binding media is presented and discussed. The binding media were applied on a glass substrate and analyzed after three months of natural ageing. The combination of Raman and FT-NIR spectroscopies allows for an improved identification of these materials as Raman technique is more informative about the skeletal vibrations, while FT-NIR spectroscopy is more sensitive to the substituents and polar groups. The experimental results are initially discussed in the framework of current spectral assignment. Then, multivariate analysis (PCA) is applied leading to differentiation among the samples.The two major principal components allow for a complete separation of the different classes of organic materials. Further differentiation within the same class is possible thanks to the secondary components. The loadings obtained from PCA are discussed on the basis of the spectral assignment leading to clear understanding of the physical basis of this differentiation process.

Vibrational Spectroscopies and Chemometry for Nondestructive Identification and Differentiation of Painting Binders / Carlesi, Serena; Becucci, Maurizio; Ricci, Marilena. - In: JOURNAL OF CHEMISTRY. - ISSN 2090-9063. - ELETTRONICO. - 2017:(2017), pp. 1-10. [10.1155/2017/3475659]

Vibrational Spectroscopies and Chemometry for Nondestructive Identification and Differentiation of Painting Binders

CARLESI, SERENA;BECUCCI, MAURIZIO;RICCI, MARILENA
2017

Abstract

A comprehensive dataset of vibrational spectra of different natural organic binding media is presented and discussed. The binding media were applied on a glass substrate and analyzed after three months of natural ageing. The combination of Raman and FT-NIR spectroscopies allows for an improved identification of these materials as Raman technique is more informative about the skeletal vibrations, while FT-NIR spectroscopy is more sensitive to the substituents and polar groups. The experimental results are initially discussed in the framework of current spectral assignment. Then, multivariate analysis (PCA) is applied leading to differentiation among the samples.The two major principal components allow for a complete separation of the different classes of organic materials. Further differentiation within the same class is possible thanks to the secondary components. The loadings obtained from PCA are discussed on the basis of the spectral assignment leading to clear understanding of the physical basis of this differentiation process.
2017
2017
1
10
Carlesi, Serena; Becucci, Maurizio; Ricci, Marilena
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1092262
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