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Author |
Gestels, A.; Van der Snickt, G.; Caen, J.; Nuyts, G.; Legrand, S.; Vanmeert, F.; Detry, F.; Janssens, K.; Steenackers, G. |
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Title |
Combined MA-XRF, MA-XRPD and SEM-EDX analysis of a medieval stained-glass panel formerly from Notre Dame, Paris reveals its material history |
Type |
A1 Journal article |
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Year |
2022 |
Publication |
Microchemical journal |
Abbreviated Journal |
Microchem J |
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Volume |
177 |
Issue |
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Pages |
107304 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Art; Antwerp Cultural Heritage Sciences (ARCHES); Antwerp X-ray Imaging and Spectroscopy (AXIS) |
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Abstract |
As part of its conservation-restoration, the 13th century stained-glass panel ‘the Annunciation’, was examined at the micro- and macro level. This window, since 1898 in the collection of the Museum Mayer Van den Bergh (Antwerp, B), was formerly a part of the southern Rose window of the Notre Dame Cathedral (Paris, F). The insigths emerging from a first phase of the analysis, comprising non-invasive analysis techniques such as optical microscopy combined with macroscopic X-ray fluorescence (MA-XRF) and X-ray diffraction (MA-XRPD) mapping, were used to select sampling positions for the second phase of investigation that involved micro-invasive analysis, namely scanning-electron microscopy coupled to energy-dispersive X-ray analysis (SEM-EDX). The aim of the investigation was fourfold: (1) to assess the applicability of MA-XRF scanning for the characterisation of stained glass windows prior to any conservation or restoration procedure, (2) to assess the applicability of MA-XRPD scanning to identify the degradation products formed on the surface of stained glass windows, (3) to establish a method to limit the set of sampled glass fragments taken from a glass panel for quantititive analysis while maintaining sufficient representativeness and (4) to distinguish the original glass panes and grisaille paint from non-original glass panes that were inserted during various past interventions. Most of the panes in this window proved to consist of medieval potash glass, consistent with the 13th c. origin of the window while a limited number of panes were identified as non-original infills, with divergent glass compositional types and/or colorants. Most panes derive their color from the pot metal glass (i.e. homogenously colored) they were made of. Some of the panes that originally had a red flashed layer on their surface, completely or partially lost this layer due to weathering. Three main compositional glass families with similar color could be defined. With the exception of the yellow and orange panes, the chromophoric elements responsible for the dark(er) and light(er) blue (Co), green (Cu), purple (Mn) and red colors (Cu) were identified. Two different grisaille paints were encountered, part of which were restored during the 19th century. On the basis of this information, all missing pieces were replaced by glass panes with appropriate colors and the panel could be successfully conserved to its former glory. On the surface of several panes, typical glass degradation products such as calcite, syngenite and gypsum were identified, together with lead based degradation products such as anglesite and palmierite. In addition, the presence of hematite and melanotekite in the grisailles was observed; also the presence of Zn, uncorrelated to Cu, in the grissailes on the right side of the window became apparent. |
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Wos |
000850000900001 |
Publication Date |
2022-02-22 |
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ISSN |
0026-265x; 0026-265x |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
4.8 |
Times cited |
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Open Access |
OpenAccess |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
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Approved |
Most recent IF: 4.8 |
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Call Number |
UA @ admin @ c:irua:187493 |
Serial |
7138 |
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Author |
Vanmeert, F.; De Meyer, S.; Gestels, A.; Clerici, E.A.; Deleu, N.; Legrand, S.; Van Espen, P.; Van der Snickt, G.; Alfeld, M.; Dik, J.; Monico, L.; De Nolf, W.; Cotte, M.; Gonzalez, V.; Saverwyns, S.; Depuydt-Elbaum, L.; Janssens, K. |
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Title |
Non-invasive and non-destructive examination of artists’ pigments, paints and paintings by means of X-ray imaging methods |
Type |
H1 Book chapter |
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Year |
2022 |
Publication |
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Abbreviated Journal |
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Volume |
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Issue |
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Pages |
317-357 |
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Keywords |
H1 Book chapter; Art; Antwerp Cultural Heritage Sciences (ARCHES); Antwerp X-ray Imaging and Spectroscopy (AXIS) |
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Abstract |
Recent studies in which X-ray beams of (sub)micrometre to millimetre dimensions have been used for non-destructive analysis and characterization of pigments, minute paint samples and/or entire paintings from fifteenth to twentieth century artists are discussed. The overview presented encompasses the use of laboratory and synchrotron radiation-based instrumentation and deals with the use of several variants of X-ray fluorescence (XRF) as a method of elemental analysis and imaging as well as with the combined use with X-ray diffraction (XRD). Microscopic XRF (μ-XRF) is a variant of the XRF method able to visualize the elemental distribution of key elements, mostly metals, on the scale from 1 μm to 100 μm present inside multi-layered micro samples taken from paintings. In the context of the characterization of artists’ pigments subjected to natural degradation, in many cases the use of methods limited to elemental analysis or imaging does not suffice to elucidate the chemical transformations that have taken place. However, at synchrotron facilities, combinations of μ-XRF with related methods such as μ-XAS (microscopic X-ray absorption spectroscopy) and μ-XRD have proven themselves to be very suitable for such studies. Since microscopic investigation of a relatively limited number of minute paint samples may not yield representative information about the complete artefact they were taken from, several methods for macroscopic, non-invasive imaging have recently been developed. Combined macroscopic XRF/XRD scanning is able to provide a fairly complete overview of the inorganic pigments employed to create a work of art, to answer questions about ongoing degradation phenomena and about its authenticity. As such these newly developed non-invasive and highly specific imaging methods are of interest for many cultural heritage stakeholders. |
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Wos |
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Publication Date |
2022-09-08 |
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978-3-030-86864-2 |
Additional Links |
UA library record |
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Not_Open_Access |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
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Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:190777 |
Serial |
7183 |
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Author |
Gonzalez, V.; Fazlic, I.; Cotte, M.; Vanmeert, F.; Gestels, A.; De Meyer, S.; Broers, F.; Hermans, J.; van Loon, A.; Janssens, K.; Noble, P.; Keune, K. |
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Title |
Lead(II) formate in Rembrandt's Night Watch : detection and distribution from the macro- to the micro-scale |
Type |
A1 Journal article |
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Year |
2023 |
Publication |
Angewandte Chemie: international edition in English |
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Pages |
1-9 |
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Keywords |
A1 Journal article; Art; Antwerp X-ray Imaging and Spectroscopy (AXIS) |
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Abstract |
The Night Watch, painted in 1642 and on view in the Rijksmuseum in Amsterdam, is considered Rembrandt's most famous work. X-ray powder diffraction (XRPD) mapping at multiple length scales revealed the unusual presence of lead(II) formate, Pb(HCOO)(2), in several areas of the painting. Until now, this compound was never reported in historical oil paints. In order to get insights into this phenomenon, one possible chemical pathway was explored thanks to the preparation and micro-analysis of model oil paint media prepared by heating linseed oil and lead(II) oxide (PbO) drier as described in 17(th) century recipes. Synchrotron radiation based micro-XRPD (SR-mu-XRPD) and infrared microscopy were combined to identify and map at the micro-scale various neo-formed lead-based compounds in these model samples. Both lead(II) formate and lead(II) formate hydroxide Pb(HCOO)(OH) were detected and mapped, providing new clues regarding the reactivity of lead driers in oil matrices in historical paintings. |
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000920584500001 |
Publication Date |
2023-01-02 |
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ISSN |
1433-7851; 0570-0833 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
16.6 |
Times cited |
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Open Access |
OpenAccess |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
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Approved |
Most recent IF: 16.6; 2023 IF: 11.994 |
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Call Number |
UA @ admin @ c:irua:194279 |
Serial |
7318 |
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Permanent link to this record |
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Author |
De Kerf, T.; Gestels, A.; Janssens, K.; Scheunders, P.; Steenackers, G.; Vanlanduit, S. |
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Title |
Quantitative detection of corrosion minerals in carbon steel using shortwave infrared hyperspectral imaging |
Type |
A1 Journal article |
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Year |
2022 |
Publication |
RSC advances |
Abbreviated Journal |
Rsc Adv |
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Volume |
12 |
Issue |
50 |
Pages |
32775-32783 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Vision lab; Antwerp X-ray Imaging and Spectroscopy (AXIS) |
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Abstract |
This study presents a novel method for the detection and quantification of atmospheric corrosion products on carbon steel. Using hyperspectral imaging (HSI) in the short-wave infrared range (SWIR) (900-1700 nm), we are able to identify the most common corrosion minerals such as: alpha-FeO(OH) (goethite), gamma-FeO(OH) (lepidocrocite), and gamma-Fe2O3 (maghemite). Six carbon steel samples were artificially corroded in a salt spray chamber, each sample with a different duration (between 1 h and 120 hours). These samples were analysed by scanning X-ray diffraction (XRD) and also using a SWIR HSI system. The XRD data is used as baseline data. A random forest regression algorithm is used for training on the combined XRD and HSI data set. Using the trained model, we can predict the abundance map based on the HSI images alone. Several image correlation metrics are used to assess the similarity between the original XRD images and the HSI images. The overall abundance is also calculated and compared for XRD and HSI images. The analysis results show that we are able to obtain visually similar images, with error rates ranging from 3.27 to 13.37%. This suggests that hyperspectral imaging could be a viable tool for the study of corrosion minerals. |
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Wos |
000885554600001 |
Publication Date |
2022-11-15 |
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ISSN |
2046-2069 |
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Additional Links |
UA library record; WoS full record |
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Impact Factor |
3.9 |
Times cited |
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Open Access |
OpenAccess |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
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Approved |
Most recent IF: 3.9 |
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Call Number |
UA @ admin @ c:irua:192085 |
Serial |
7334 |
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Author |
Koirala, B.; Rasti, B.; Bnoulkacem, Z.; De Lima Ribeiro, A.; Madriz, Y.; Herrmann, E.; Gestels, A.; De Kerf, T.; Janssens, K.; Steenackers, G.; Gloaguen, R.; Scheunders, P. |
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Title |
An extensive multisensor hyperspectral benchmark datasets of intimate mixtures of mineral powders |
Type |
P1 Proceeding |
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Year |
2023 |
Publication |
IEEE International Geoscience and Remote Sensing Symposium proceedings
T2 – IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, 16-21 July 2023, Pasadena, CA, USA |
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Volume |
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Issue |
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Pages |
5890-5893
T2 - IGARSS 2023 - 2023 IEEE Internation |
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Keywords |
P1 Proceeding; Economics; Vision lab; Antwerp X-ray Imaging and Spectroscopy (AXIS) |
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Abstract |
Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain.In this work, we generated a comprehensive hyperspectral dataset of intimate mineral powder mixtures by homogeneously mixing five different clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide). In total 325 samples were prepared. Among the 325 samples, 60 mixtures were binary, 150 were ternary, 100 were quaternary, and 15 were quinary. For each mixture (and pure clay powder), reflectance spectra are acquired by 13 different sensors, with a broad wavelength range between the visible and the long-wavelength infrared regions (i.e., between 350 nm and 15385 nm) and with a large variation in sensor types, platforms, and acquisition conditions. We will make this dataset public, to be used by the community for the validation of nonlinear unmixing methodologies (https://github.com/VisionlabUA/Multisensor_datasets) |
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Wos |
001098971606002 |
Publication Date |
2023-10-20 |
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ISSN |
979-83-503-2010-7 |
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Additional Links |
UA library record; WoS full record |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
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Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:201596 |
Serial |
9035 |
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Author |
Koirala, B.; Rasti, B.; Bnoulkacem, Z.; de Lima Ribeiro, A.; Madriz, Y.; Herrmann, E.; Gestels, A.; De Kerf, T.; Lorenz, S.; Fuchs, M.; Janssens, K.; Steenackers, G.; Gloaguen, R.; Scheunders, P. |
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Title |
A multisensor hyperspectral benchmark dataset for unmixing of intimate mixtures |
Type |
A1 Journal article |
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Year |
2024 |
Publication |
IEEE sensors journal |
Abbreviated Journal |
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Volume |
24 |
Issue |
4 |
Pages |
4694-4710 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Vision lab; Antwerp X-ray Imaging and Spectroscopy (AXIS) |
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Abstract |
Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain. In this work, we generated a comprehensive laboratory ground truth dataset of intimately mixed mineral powders. For this, five clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide) were mixed homogeneously to prepare 325 samples of 60 binary, 150 ternary, 100 quaternary, and 15 quinary mixtures. Thirteen different hyperspectral sensors have been used to acquire the reflectance spectra of these mixtures in the visible, near, short, mid, and long-wavelength infrared regions (350-15385) nm. Overlaps in wavelength regions due to the operational ranges of each sensor and variations in acquisition conditions resulted in a large amount of spectral variability. Ground truth composition is given by construction, but to verify that the generated samples are sufficiently homogeneous, XRD and XRF elemental analysis is performed. We believe these data will be beneficial for validating advanced methods for nonlinear unmixing and material composition estimation, including studying spectral variability and training supervised unmixing approaches. The datasets can be downloaded from the following link: https://github.com/VisionlabHyperspectral/Multisensor_datasets. |
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Wos |
001173599400063 |
Publication Date |
2023-12-28 |
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Edition |
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ISSN |
1530-437x; 1558-1748 |
ISBN |
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Additional Links |
UA library record; WoS full record |
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Impact Factor |
4.3 |
Times cited |
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Open Access |
Not_Open_Access |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
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Approved |
Most recent IF: 4.3; 2024 IF: 2.512 |
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Call Number |
UA @ admin @ c:irua:203094 |
Serial |
9059 |
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Permanent link to this record |