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The process of MA-XRF data for spectroscopy imaging in cultural heritage

Authors: Huseynli, Fakhriyya;

The process of MA-XRF data for spectroscopy imaging in cultural heritage

Abstract

Scanning macro-X-ray fluorescence analysis (MA-XRF) is rapidly being established as a technique for the investigation of historical paintings. The elemental distribution images acquired by this method allow the visualization of hidden paint layers and thus, provide insight into the artist's creative process and the painting's conservation history. As a non-destructive instrument MA-XRF and analyzing software PyMca will be used to identify, also to study painting from private collection in Italy. The use of MA-XRF to tentatively predict pigments has an important advantage, its application provides the undamaged and low cost survey of large areas in the painting. The method was proved powerful and useful, capable of efficiently determining the composition and structure of the investigated object in a total safe approach. Nevertheless, for a more throughout evaluation and a better estimation of the pigment composition, it has been demonstrated that, the use of complementary analytical techniques is required

Country
Portugal
Related Organizations
Keywords

Painting, Synchrotron radiation, PyMca, XRF, MA-XRF

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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