Literature DB >> 25127604

Towards a non-invasive quantitative analysis of the organic components in museum objects varnishes by vibrational spectroscopies: methodological approach.

Céline Daher1, Vanessa Pimenta2, Ludovic Bellot-Gurlet2.   

Abstract

The compositions of ancient varnishes are mainly determined destructively by separation methods coupled to mass spectrometry. In this study, a methodology for non-invasive quantitative analyses of varnishes by vibrational spectroscopies is proposed. For that, experimental simplified varnishes of colophony and linseed oil were prepared according to 18th century traditional recipes with an increasing mass concentration ratio of colophony/linseed oil. FT-Raman and IR analyses using ATR and non-invasive reflectance modes were done on the "pure" materials and on the different mixtures. Then, a new approach involving spectral decomposition calculation was developed considering the mixture spectra as a linear combination of the pure materials ones, and giving a relative amount of each component. Specific spectral regions were treated and the obtained results show a good accuracy between the prepared and calculated amounts of the two compounds. We were thus able to detect and quantify from 10% to 50% of colophony in linseed oil using non-invasive techniques that can also be conducted in situ with portable instruments when it comes to museum varnished objects and artifacts.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  FT-Raman; IR-reflectance; Museum objects; Non-invasive quantification; Spectral decomposition; Varnish

Year:  2014        PMID: 25127604     DOI: 10.1016/j.talanta.2014.05.059

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  1 in total

1.  Mid and Near-Infrared Reflection Spectral Database of Natural Organic Materials in the Cultural Heritage Field.

Authors:  Claudia Invernizzi; Tommaso Rovetta; Maurizio Licchelli; Marco Malagodi
Journal:  Int J Anal Chem       Date:  2018-10-01       Impact factor: 1.885

  1 in total

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