Records |
Author |
Cagno, S.; van der Snickt, G.; Legrand, S.; Caen, J.; Patin, M.; Meulebroeck, W.; Dirkx, Y.; Hillen, M.; Steenackers, G.; Rousaki, A.; Vandenabeele, P.; Janssens, K. |
Title |
Comparison of four mobile, non‐invasive diagnostic techniques for differentiating glass types in historical leaded windows : MA‐XRF , UV–Vis–NIR, Raman spectroscopy and IRT |
Type |
A1 Journal article |
Year |
2020 |
Publication |
X-Ray Spectrometry |
Abbreviated Journal |
X-Ray Spectrom |
Volume |
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Issue |
|
Pages |
xrs.3185-17 |
Keywords |
A1 Journal article; Engineering sciences. Technology; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Antwerp Cultural Heritage Sciences (ARCHES) |
Abstract |
This paper critically compares the performance of four non-invasive techniques that match the accuracy, flexibility, time-efficiency, and transportability required for in situ characterization of leaded glass windows: macroscopic X-ray fluorescence imaging (MA-XRF), UV-Vis-NIR, Raman spectroscopy, and infrared thermography (IRT). In order to compare the techniques on equal grounds, all techniques were tested independently of each other by separate research groups on the same historical leaded window tentatively dated to the 17th century, without prior knowledge. The aim was to assess the ability of these techniques to document the conservation history of the window by classifying and grouping the colorless glass panes, based on differences in composition. IRT, MA-XRF and UV-Vis-NIR spectroscopy positively distinguished at least two glass groups, with MA-XRF providing the most detailed chemical information. In particular, based on the ratio between the network modifier (K) and network stabilizer (Ca) and on the level of colorants and decolorizers (Fe, Mn, As), the number of plausible glass families could be strongly reduced. In addition, UV-Vis-NIR detected cobalt at ppm level and gave more specific information on the chromophore Fe2+/Fe(3+)ratio. Raman spectroscopy was hampered by fluorescence caused by the metal ions of the decolorizer in most of the panes, but nevertheless identified one group as HLLA. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Wos |
000561869600001 |
Publication Date |
2020-08-24 |
Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume ![sorted by Series Volume (numeric) field, descending order (down)](img/sort_desc.gif) |
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Series Issue |
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Edition |
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ISSN |
0049-8246 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
Impact Factor |
1.2 |
Times cited |
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Open Access |
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Notes |
; Belgian Federal Science Policy Office, Grant/Award Number: BR/175/A3/FENESTRA; Fonds Wetenschappelijk Onderzoek, Grant/Award Number: 12X1919N; Baillet-Latour Fund ; |
Approved |
Most recent IF: 1.2; 2020 IF: 1.298 |
Call Number |
UA @ admin @ c:irua:170972 |
Serial |
6473 |
Permanent link to this record |
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Author |
Hillen, M.; Legrand, S.; Dirkx, Y.; Janssens, K.; van der Snickt, G.; Caen, J.; Steenackers, G. |
Title |
Cluster analysis of IR thermography data for differentiating glass types in historical leaded-glass windows |
Type |
A1 Journal article |
Year |
2020 |
Publication |
Applied Sciences-Basel |
Abbreviated Journal |
Appl Sci-Basel |
Volume |
10 |
Issue |
12 |
Pages |
4255-13 |
Keywords |
A1 Journal article; Engineering sciences. Technology; Antwerp Cultural Heritage Sciences (ARCHES); AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) |
Abstract |
Infrared thermography is a fast, non-destructive and contactless testing technique which is increasingly used in heritage science. The aim of this study was to assess the ability of infrared thermography, in combination with a data clustering approach, to differentiate between the different types of historical glass that were included in a colorless leaded-glass windows during previous restoration interventions. Inspection of the thermograms and the application of two data mining techniques on the thermal data, i.e., k-means clustering and hierarchical clustering, allowed identifying different groups of window panes that show a different thermal behavior. Both clustering approaches arrive at similar groupings of the glass with a clear separation of three types. However, the lead cames that hold the glass panes appear to have a substantial impact on the thermal behavior of the surrounding glass, thus preventing classification of the smallest glass panes. For the larger panes, this was not a critical issue as the center of the glass remained unaffected. Subtle visual color differences between panes, implying a variation in coloring metal ions, was not always distinguished by IRT. Nevertheless, data clustering assisted infrared thermography shows potential as an efficient and swift method for documenting the material intervention history of leaded-glass windows during or in preparation of conservation treatments. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Wos |
000549351800001 |
Publication Date |
2020-06-22 |
Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume ![sorted by Series Volume (numeric) field, descending order (down)](img/sort_desc.gif) |
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Series Issue |
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Edition |
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ISSN |
2076-3417 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
Impact Factor |
2.7 |
Times cited |
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Open Access |
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Notes |
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Approved |
Most recent IF: 2.7; 2020 IF: 1.679 |
Call Number |
UA @ admin @ c:irua:170012 |
Serial |
7674 |
Permanent link to this record |