Publication
Title
Revealing hidden paint layers in oil paintings by means of scanning macro-XRF : a mock-up study based on Rembrandt's "An old man in military costume"
Author
Abstract
Over the past several decades the oeuvre of Rembrandt has been the subject of extensive art historical and scientific investigations. One of the most striking features to emerge is his frequent re-use of canvases and panels. The painting An Old Man in Military Costume (78.PB.246), in the collection of the J. Paul Getty Museum, is an example of such a re-used panel. Conventional imaging techniques revealed the presence of a second portrait under the surface portrait, but the details of this hidden portrait have not yet been revealed. Vermilion (HgS) has been identified to have been used nearly exclusively in the flesh tones of the lower painting, suggesting that element-specific XRF imaging might successfully image the hidden portrait. To test this hypothesis, a full-scale mock-up of the painting was created, including a "free impression" of the hidden portrait, reproducing as closely as possible the pigments and paint stratigraphy of the original painting. XRF imaging of the mock-up painting was conducted using three different XRF imaging systems: a mobile X-ray tube based system and two synchrotron-based setups (one equipped with multiple SDDs and one equipped with a Maia detector). The sensitivity, limits of detection and imaging capabilities of each system under the chosen experimental conditions are evaluated and compared. The results indicate that an investigation of the original painting by this method would have an excellent chance of success.
Language
English
Source (journal)
Journal of analytical atomic spectrometry. - London
Publication
London : 2013
ISSN
0267-9477
Volume/pages
28:1(2013), p. 40-51
ISI
000314903400003
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 30.04.2013
Last edited 04.09.2017
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