FT-NIR Spectroscopy for the Non-Invasive Study of Binders and Multi-Layered Structures in Ancient Paintings: Artworks of the Lombard Renaissance as Case Studies.


Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
06 Mar 2022
Historique:
received: 30 12 2021
revised: 02 03 2022
accepted: 04 03 2022
entrez: 10 3 2022
pubmed: 11 3 2022
medline: 15 3 2022
Statut: epublish

Résumé

This work deals with the identification of natural binders and the study of the complex stratigraphy in paintings using reflection FT-IR spectroscopy, a common diagnostic tool for cultural heritage materials thanks to its non-invasiveness. In particular, the potential of the near-infrared (NIR) spectral region, dominated by the absorption bands due to CH, CO, OH and NH functional groups, is successfully exploited to distinguish a lipid binder from a proteinaceous one, as well as the coexistence of the two media in laboratory-made model samples that simulate the complex multi-layered structure of a painting. The combination with multivariate analysis methods or with the calculation of indicative ratios between the intensity values of characteristic absorption bands is proposed to facilitate the interpretation of the spectral data. Furthermore, the greater penetration depth of NIR radiation is exploited to obtain information about the inner layers of the paintings, focusing in particular on the preparatory coatings of the supports. Finally, as proof of concept, FT-NIR analyses were also carried out on six paintings by artists working in Lombardy at the end of the 15th century, that exemplify different pictorial techniques.

Identifiants

pubmed: 35271199
pii: s22052052
doi: 10.3390/s22052052
pmc: PMC8914679
pii:
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Margherita Longoni (M)

Dipartimento di Chimica, Università degli Studi di Milano, Via C. Golgi, 19, 20133 Milan, Italy.

Beatrice Genova (B)

Dipartimento di Chimica, Università degli Studi di Milano, Via C. Golgi, 19, 20133 Milan, Italy.

Alessia Marzanni (A)

Dipartimento di Chimica, Università degli Studi di Milano, Via C. Golgi, 19, 20133 Milan, Italy.

Daniela Melfi (D)

Dipartimento di Chimica, Università degli Studi di Milano, Via C. Golgi, 19, 20133 Milan, Italy.

Carlotta Beccaria (C)

Beccaria Carlotta & C. Studio Di Restauro, Via Conservatorio, 30, 20122 Milan, Italy.

Silvia Bruni (S)

Dipartimento di Chimica, Università degli Studi di Milano, Via C. Golgi, 19, 20133 Milan, Italy.

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Classifications MeSH