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“Visualizing the 17th century underpainting in Portrait of an Old Man by Rembrandt van Rijn using synchrotron-based scanning macro-XRF”. Alfeld M, Siddons DP, Janssens K, Dik J, Woll A, Kirkham R, van de Wetering E, Applied physics A : materials science &, processing 111, 157 (2013). http://doi.org/10.1007/S00339-012-7490-5
Abstract: In 17th century Old Master Paintings, the underpainting generally refers to the first sketch of a composition. The underpainting is applied to a prepared ground using a monochrome, brown oil paint to roughly indicate light, shade and contours. So far, methods to visualize the underpainting-other than in localized cross-sections-have been very limited. Neither infrared reflectography nor neutron induced autoradiography have proven to be practical, adequate visualization tools. Thus, although of fundamental interest in the understanding of a painting's genesis, the underpainting has virtually escaped all imaging efforts. In this contribution we will show that 17th century underpainting may consist of a highly heterogeneous mixture of pigments, including copper pigments. We suggest that this brown pigment mixture is actually the recycled left-over of a palette scraping. With copper as the heaviest exclusive elemental component, we will hence show in a case study on a Portrait of an Old Man attributed to Rembrandt van Rijn how scanning macro-XRF can be used to efficiently visualize the underpainting below the surface painting and how this information can contribute to the discussion of the painting's authenticity.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
Impact Factor: 1.455
Times cited: 26
DOI: 10.1007/S00339-012-7490-5
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“Spatially resolved (semi)quantitative determination of iron (Fe) in plants by means of synchrotron micro X-ray fluorescence”. Terzano R, Alfeld M, Janssens K, Vekemans B, Schoonjans T, Vincze L, Tomasi N, Pinton R, Cesco S, Analytical and bioanalytical chemistry 405, 3341 (2013). http://doi.org/10.1007/S00216-013-6768-6
Abstract: Iron (Fe) is an essential element for plant growth and development; hence determining Fe distribution and concentration inside plant organs at the microscopic level is of great relevance to better understand its metabolism and bioavailability through the food chain. Among the available microanalytical techniques, synchrotron mu-XRF methods can provide a powerful and versatile array of analytical tools to study Fe distribution within plant samples. In the last years, the implementation of new algorithms and detection technologies has opened the way to more accurate (semi)quantitative analyses of complex matrices like plant materials. In this paper, for the first time the distribution of Fe within tomato roots has been imaged and quantified by means of confocal mu-XRF and exploiting a recently developed fundamental parameter-based algorithm. With this approach, Fe concentrations ranging from few hundreds of ppb to several hundreds of ppm can be determined at the microscopic level without cutting sections. Furthermore, Fe (semi)quantitative distribution maps were obtained for the first time by using two opposing detectors to collect simultaneously the XRF radiation emerging from both sides of an intact cucumber leaf.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
Impact Factor: 3.431
Times cited: 27
DOI: 10.1007/S00216-013-6768-6
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“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””. Alfeld M, de Nolf W, Cagno S, Janssens K, et al, Journal of analytical atomic spectrometry 28, 40 (2013). http://doi.org/10.1039/C2JA30119A
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.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
Impact Factor: 3.379
DOI: 10.1039/C2JA30119A
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“Restoration of X-ray fluorescence images of hidden paintings”. Anitha A, Brasoveanu A, Duarte M, Hughes S, Daubechies I, Dik J, Janssens K, Alfeld M, Signal processing 93, 592 (2013). http://doi.org/10.1016/J.SIGPRO.2012.09.027
Abstract: This paper describes our methods for repairing and restoring images of hidden paintings (paintings that have been painted over and are now covered by a new surface painting) that have been obtained via noninvasive X-ray fluorescence imaging of their canvases. This recently developed imaging technique measures the concentrations of various chemical elements at each two-dimensional spatial location across the canvas. These concentrations in turn result from pigments present both in the surface painting and in the hidden painting beneath. These X-ray fluorescence images provide the best available data from which to noninvasively study a hidden painting. However, they are typically marred by artifacts of the imaging process, features of the surface painting, and areas of information loss. Repairing and restoring these images thus consists of three stages: (1) repairing acquisition artifacts in the dataset, (2) removal of features in the images that result from the surface painting rather than the hidden painting, and (3) identification and repair of areas of information loss. We describe methods we have developed to address each of these stages: a total-variation minimization approach to artifact correction, a novel method for underdetermined blind source separation with multimodal side information to address surface feature removal, and two application-specific new methods for automatically identifying particularly thick or X-ray absorbent surface features in the painting. Finally, we demonstrate the results of our methods on a hidden painting by the artist Vincent van Gogh. (C) 2012 Elsevier B.V. All rights reserved.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
Impact Factor: 3.11
Times cited: 13
DOI: 10.1016/J.SIGPRO.2012.09.027
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