Non-invasive mapping methods for pigments analysis of Roman mural paintings

Anno: 2020

Autori: Dal Fovo A., Mazzinghi A., Omarini S., Pampaloni E., Ruberto C., Striova J., Fontana R.

Affiliazione autori: CNR INO Ist Nazl Ott, Largo E Fermi 6, I-50125 Florence, IT, Italy;‎ INFN Ist Nazl Fis Nucl, Via B Rossi 1, I-50019 Sesto Fiorentino, IT, Italy; Univ Firenze, Dept Phys & Astron, Via G Sansone 1, I-50019 Sesto Fiorentino, IT, Italy

Abstract: The analysis of archaeological mural paintings may provide relevant information on the artistic techniques and the pictorial materials used in the past, expanding the knowledge of customs and technologies of ancient societies. Given their location, fragility and value, it is generally required to analyze mural paintings in situ, avoiding contact measurements, sampling or pre-treatments.
In this work, a number of polychrome fragments from two recently discovered Roman villas have been studied with three non-invasive techniques, making use of transportable devices: Macro X-ray Fluorescence (MA-XRF) elemental mapping, multispectral scanning reflectography, and Fibre Optics Reflectance Spectroscopy (FORS). Specifically, the MA-XRF elemental maps were compared with the spectral correlation maps (SCM) computed from the Vis-NIR images acquired with the multispectral scanner, with the aim of displaying the distributions of the different pictorial materials, while assessing the chemical composition of the pigments present. The combined application of the two former mapping/imaging techniques represents a valid tool for the chemical and spectral characterization of archaeological paintings, providing easy-to-interpret data for the professionals involved in the conservation of Cultural Heritage. (C) 2019 Elsevier Masson SAS. All rights reserved

Giornale/Rivista: JOURNAL OF CULTURAL HERITAGE

Volume: 43      Da Pagina: 311  A: 318

Parole chiavi: Archaeological paintings; A secco paintings; MA-XRF; Multispectral scanning reflectography; Spectral correlation mapping
DOI: 10.1016/j.culher.2019.12.002

Citazioni: 10
dati da “WEB OF SCIENCE” (of Thomson Reuters) aggiornati al: 2022-08-07
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