In this review, topic modeling—an unsupervised machine learning tool—is employed to analyze research on pigments in cultural heritage published from 1999–2023. The review answers the following question: What are topics and time trends in the past three decades in the analytical study of pigments within cultural heritage (CH) assets? In total, 932 articles are reviewed, ten topics are identified and time trends in the share of these topics are revealed. Each topic is discussed in-depth to elucidate the community, purpose and tools involved in the topic. The time trend analysis shows that dominant topics over time include T1 (the spectroscopic and microscopic study of the stratigraphy of painted CH assets) and T5 (X-ray based techniques for CH, conservation science and archaeometry). However, both topics have experienced a decrease in attention in favor of other topics that more than doubled their topic share, enabled by new technologies and methods for imaging spectroscopy and imaging processing. These topics include T6 (spectral imaging techniques for chemical mapping of painting surfaces) and T10 (the technical study of the pigments and painting methods of historical and contemporary artists). Implications for the field are discussed in conclusion.

This review presents the computational method of topic modeling to identify core topics and time trends in research on X-ray fluorescence (XRF) and its application to cultural heritage. Topic modeling is an approach to text mining based on unsupervised machine learning, which helps to determine core topics within a vast body of text. Due to the large amount of published work on X-ray fluorescence in the area of cultural heritage, traditional literature review has become impractical, inefficient, time-consuming, and potentially less reliable. Therefore, it is important to take stock of which topics have been core to such research and whether specific time trends can be identified within them. Using topic modeling, this review aims to reveal core topics and trends in research on XRF analysis of painted heritage objects by examining 982 articles collected from Web of Science. Within this dataset of articles, ten topics have been identified. The identified topics can be clustered in three main categories: the methods used, the objects studied, and the specific materials studied. In terms of trends in topic share since 2010, it is especially noteworthy to see that the share of articles focused on the identification and study of painting materials and techniques has more than doubled. Similarly, another impressive increase can be observed for articles centered on advanced imaging spectroscopic techniques, such as macro X-ray fluorescence (MA-XRF) and reflectance hyperspectral imaging, for the study of easel paintings. The share of attention within XRF literature given to imaging spectroscopic techniques tripled between 2010 and 2017, though stabilizing in the subsequent years. Conversely, the share of articles which specifically deal with the development and improvement of energy dispersive X-ray fluorescence (ED-XRF) spectroscopic techniques (i.e., portable ED-XRF, confocal micro-XRF, micro-grazing exit XRF) for the elemental analysis (including elemental depth profiling) of painted heritage objects has declined sharply.

.The Archaeological Collection of Ghent University Museum hosts one of the most remarkable cork models representing the Pantheon of Rome, made by the master Antonio Chichi (1743-1816). Ghent University started a restoration campaign dedicated to the cork masterpiece, which has great artistic value. Next to macroscopic analysis, an extensive physicochemical campaign was organised in order to study and document the composition and the preservation state of the polychromic layers of Chichi's masterpiece. Portable and micro-Raman spectroscopy revealed the presence of materials such as carbon-based pigments, lead white, vermilion, chalk, gypsum, bassanite, Prussian blue and haematite on the exterior and interior of the cork model. A tin-containing layer was characterized on the exterior of the model. XRF instruments were employed to better understand the overall elemental composition of the model's polychromic layers, positively identifying Pb, Sn, Zn, Ca, Hg, Fe at the exterior surface. Stratigraphic analysis was performed, with both analytical techniques, when possible. The detailed information provided by archaeology, art history and applied sciences on the cork model of the Pantheon, will help the conservators to better understand and restore the Pantheon model which will be exhibited in the new museum of Ghent University.

The painting Saint Jerome, part of the collection of the Maagdenhuis Museum (Antwerp, Belgium), is attributed to the young Anthony van Dyck (1613–1621) with reservations. The painting displays remarkable compositional and iconographic similarities with two early Van Dyck works (1618–1620) now in Museum Boijmans van Beuningen (Rotterdam) and Nationalmuseum (Stockholm). Despite these similarities, previous art historical research did not result in a clear attribution to this master. In this study, the work’s authenticity as a young Van Dyck painting was assessed from a technical perspective by employing a twofold approach. First, technical information on Van Dyck’s materials and techniques, here identified as his fingerprint, were defined based on a literature review. Second, the materials and techniques of the questioned Saint Jerome painting were characterized by using complementary imaging techniques: infrared reflectography, X-ray radiography and macro X-ray fluorescence scanning. The insights from this non-invasive research were supplemented with analysis of a limited number of cross-sections by means of field emission scanning electron microscopy coupled with energy dispersive X-ray spectroscopy. The results demonstrated that the questioned painting’s materials and techniques deviate from Van Dyck’s fingerprint, thus making the authorship of this master very unlikely.

Over the past decades, technical study of artworks proved valuable for addressing issues of attribution.[1] By revealing new information about painting materials and techniques, advanced imaging tools and chemical analyses (e.g. Infrared reflectography, Macroscopic X-ray fluorescence and XRF analysis), we challenge and broaden the current interpretative value of technical investigations of artworks.[2-3] However, despite the recurring introduction of improved diagnostic techniques for the study of paintings and the increasing knowledge of painters’ modus operandi, ‘advances in the methodology of attribution seemed to progress at a snail’s pace.’[4] Hence, the main problem in this research field is how to transform technical data into meaningful information favoring or opposing a specific attribution. This issue can be solved by identifying distinctive materials and techniques as markers in a set of reference artworks for a specific master, workshop, school or period.[5] In this study we assess how an object-based methodology can assist in addressing attribution problems. The method was applied to a case study, i.e. the painting Saint Jerome attributed to Anthony van Dyck [6] of the Antwerp Museum Maagdenhuis, which presented useful evidence on the issue of markers. For the painting Saint Jerome, in-depth art historical and archival research did not result in a clear attribution to Van Dyck. Limited information on the painting’s origin and history could be retraced as the earliest written document on the picture’s provenance dates from 1841. Therefore, Van Dyck’s working procedures were studied by systematically gathering available compositional data derived from a set of 37 reference paintings.[7-16] Additionally, the Antwerp painting’s origin, history, iconographic program, formal features, current condition, physical and technical aspects were examined. Hence, the obtained compositional data of the painting could be studied within a broader art historical and technical context to determine whether the identified painting materials and techniques could be used as markers. This holistic approach thus allowed us to simultaneously assess art historical and technical data to systematically refine our observations and conclusions. As such, the selected markers could be determined for the painting under study, allowing a comparison with the working procedures of Van Dyck. In what follows, we elaborate on the results of the proposed object-based methodology applied to the specific case. Based on the identified working procedures of Van Dyck, the layer build-up, chemical composition and microstructure of the painting were determined by chemical analysis and imaging techniques (e.g. IRR, XRR, Portable XRF, FE-SEM-EDX and MA-XRF scanning). From this working procedure, a set of 4markers could be identified opposing the painting’s current attribution to Van Dyck. First, the identified type of support of the painting Saint Jerome, which is plain-weave canvas with a low density, deviates from Van Dyck’s choice of canvas supports. More specifically, he preferred plain and tabby-weave canvas with a high density. Second, the picture is painted on top of a red chalk-based ground with a grey priming. This canvas preparation type differs from Van Dyck’s usage of white and pale colored chalk-based grounds with various types of primings. Third, the identified blue pigment employed in the painting Saint Jeromefor the depiction of the blue drapery is smalt. Van Dyck, however, favored the usage of the organic pigment indigo to construct blue draperies. Fourth, the identified complex method of paint application to depict the flesh tones in the painting Saint Jerome substantially diverges from Van Dyck’s art practice, who models the human flesh in a single layer. In conclusion, the materials and techniques used in the picture Saint Jeromeclearly deviate from Van Dyck’s working process. These findings thus led us to the conclusion that the painting is not by Anthony van Dyck. References: [1]M. W. Ainsworth.Getty Newsletter2005; 20.1: 4.[2]H.Verougstraete, J. Couvert. La Peinture Ancienne et ses Procedes. Copies, replique, pastiches, Peeters, Leuven, 2006.[3]K. Van der Stighelen, K. Janssens, G. Van der Snickt, M. Alfeld, B. Van Beneden, B. Demarsin, M. Proesmans, G. Marchal, J.Dik.Art Matters. International Journal for Technical Art History2014; 6: 21.[4]M. W. Ainsworth, in Recent Developments in the Technical Examination of Early Netherlandish Painting. Methodology, Limitations & Perspectives, (Eds: M. Faries, R. Spronk), Brepols, Turnhout, 2003, 137.[5]L. Sheldon, G. Macaro, in European Paintings 15th-18thcentury. Copying, Replicating and Emulating, (Ed: E. Hermens), Archetype Publications, London, 2014, 105-112.[6]L. Philippen, in Commissie van Openbare Onderstand Antwerpen. Bestuurlijk Verslag over het Dienstjaar 1931, Commissie van Openbare Onderstand, Antwerp, 1933, 182-189.[7]L. Alba, M. Jover, M. D. Goya, in The Young Van Dyck, (Eds: A. Vergara, F. Lammertse), Thames & Hudson, London, 2013, 337.[8]M. W. Ainsworth, J. Brealey, E. Haverkamp-Begemann, P. Meyers, Art and Autoradiography: Insights into the Genesis of Paintings by Rembrandt, Van Dyck and Vermeer, The Metropolitan Museum of Art,New York,1987.[9]C. Christensen, M. Palmer, M. Swicklik, in Anthony van Dyck, (Ed: J. Sweeney),National Gallery of Art, Washington, 1990-1991,45.[10]L. Depuydt-Elbaum, R. Ghys. Bulletin de l’Institut Royal du Patrimoine Artistique1999-2000; 28: 251.[11]D. Fend. Jahrbuch des Kunsthistorischen Museums Wien2001; 2: 263.[12]C. Fryklund, F. Lammertse, Masterpiece or Copy? Two Versions of Anthony van Dyck’s St Jerome with an Angel, Museum Boijmans van Beuningen, Rotterdam, 2009.[13]M. Grieser. Jahrbuch des Kunsthistorischen Museums Wien2001; 2: 266.[14]A. Roy. National Gallery Technical Bulletin1999; 20: 50.[15]N. Van Hout,in Looking Through Paintings,(Ed: A. Hermens), Archetype Publications,London1998, 199.[16] R. Woudhuysen-Keller, K. Groen. The Hamilton Kerr Institute Bulletin1988; 1: 119.

Four x-ray techniques: computed radiography, emission radiography, energy-resolved radiography and imaging x-ray fluorescence were compared using four mock-up panel paintings. The paintings have different stratigraphy and pigments and are representative for different historical periods. One of the paintings has a hidden underlying painting. The type of pigments used mainly influences the information obtained by both the emission and absorption measurements; high-Z white pigment and high-Z color pigments giving the best contrast. Each of the techniques revealed interesting aspects of the paintings, but none of them could reveal the hidden painting to a satisfactory level. Due to the statistical quality of the spectral data, x-ray fluorescence gives elemental images with high contrast. The radiographic images are better to reveal the internal structure. Imaging x-ray fluorescence and energy-resolved radiography measurements can be done simultaneously, and the combination has the highest potential for the study of complex multilayer paintings. Copyright (c) 2015 John Wiley & Sons, Ltd.