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Issue 18, 2018
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What's underneath? A non-destructive depth profile of painted stratigraphies by synchrotron grazing incidence X-ray diffraction

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Abstract

Many works of art are complex systems consisting of a core completed by the overlapping of several painted layers. In this work, we apply an innovative method based on grazing incidence X-ray diffraction (GIXRD) with synchrotron radiation (SR) to investigate polychrome stratigraphies with a completely non-destructive approach. The SR-GIXRD measurements provided direct and unambiguous compositional and stratigraphic information of the crystalline species lying in different layers. The investigations performed on a small fragment sampled from a painted terracotta statue allowed the identification of pigments, fillers, aggregates of the matrix and newly formed decay salts in micrometric-thin paint layers. Furthermore, the great potentiality of this study is the feasibility of depth profile investigations on multi-layered painted samples from cultural heritage objects without resorting to cross sectional analyses. Currently, the method is non-destructive but it can be potentially non-invasive in situations where small moveable artworks can be placed into the measurement chamber of the SR-XRD beamlines. The overall study paves the way to a new scenario of artwork investigations, shedding light on new unexplored approaches for non-destructive studies of cultural heritage objects, their conservation history and their interaction with the environment.

Graphical abstract: What's underneath? A non-destructive depth profile of painted stratigraphies by synchrotron grazing incidence X-ray diffraction

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Publication details

The article was received on 15 May 2018, accepted on 15 Jul 2018 and first published on 08 Aug 2018


Article type: Paper
DOI: 10.1039/C8AN00901E
Citation: Analyst, 2018,143, 4290-4297
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    What's underneath? A non-destructive depth profile of painted stratigraphies by synchrotron grazing incidence X-ray diffraction

    E. Possenti, C. Colombo, C. Conti, L. Gigli, M. Merlini, J. R. Plaisier, M. Realini and G. D. Gatta, Analyst, 2018, 143, 4290
    DOI: 10.1039/C8AN00901E

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