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Macroscopic x‐ray fluorescence imaging spectroscopy (MA‐XRF) and reflectance imaging spectroscopy (RIS) are important tools in the analysis of cultural heritage objects, both for conservation and art historical research purposes. The elemental and molecular distributions provided by MA‐XRF and RIS respectively, are particularly useful for the identification and mapping of pigments in easel paintings. While MA‐XRF has relatively established data processing methods based on modeling of the underlying physics, RIS data cannot be modeled with sufficient precision and its processing has considerable room for improvements. This work seeks to improve RIS data processing workflows in the short wavelength infrared range (SWIR, 1000–2500 nm) with a novel method that fits Gaussian profiles to pigment‐specific absorption features, and we compare its performance to MA‐XRF for the task of semi‐quantitative pigment mapping, evaluating their limits of detection (LODs) and the matrix effects that affect their signals. Two pigments are considered in this work, lead white and blue verditer, which are mapped in SWIR RIS using the first overtone of OH stretching of their primary compounds, hydrocerussite (Pb3(CO3)2(OH)2) and azurite (Cu3(CO3)2(OH)2), at 1447 and 1497 nm respectively, and in MA‐XRF using the Pb‐L and Cu‐K fluorescence signals. The methods are evaluated using two sets of custom‐prepared paint samples, as well as a 16th‐century painting, discussing the identification, mapping, and semi‐quantitative analysis of the considered pigments. We found SWIR RIS to be a pigment‐specific method with a longer linear range but inferior LODs and penetration depth when compared to MA‐XRF, the latter is often not capable of discriminating between different pigments with identical elemental markers. We furthermore present a novel color scale that allows the simultaneous visualization of signals above and below a confidence limit. [ABSTRACT FROM AUTHOR]

This work introduces a novel method to multivariate analysis applied to fused hyperspectral datasets in the field of Cultural Heritage (CH). Hyperspectral Imaging is a well-established approach for the non-invasive examination of artworks, offering insights into their composition and conservation status. In CH field, a combination of hyperspectral techniques is usually employed to reach a comprehensive understanding of the artwork. To deal with hyperspectral data, multivariate statistical methods are essential due to the complexity of the data. The process involves factorizing the data matrix to highlight components and reduce dimensionality, with techniques such as Non-negative Matrix Factorization (NMF) gaining prominence. To maximize the synergies between multimodal datasets, the fusion of hyperspectral datasets can be coupled with multivariate analysis, with potential applications in CH. In this work, I will show examples of this approach with different combinations of datasets, including reflectance and transmittance spectral imaging, Fluorescence Lifetime Imaging and Time-Gated Hyperspectral Imaging, and Raman and fluorescence spectroscopy micro-mapping.

The material study of ancient Egyptian paintings began with the advent of Egyptology during the 19th century. By the 1930s, a lot had already been sampled and described. The limited palette for example has been analysed from actual painted surfaces but also from pigments and painting tools retrieved on site. However, most of these studies took place in museums while the painted surfaces, preserved in funerary chapels and temples, remained somewhat estranged from this primary physical understanding. The artistic process has been also reconstructed, mainly from the information presented by unfinished monuments, showing surfaces at different stages of completion. A lot of this modern and theoretical reconstruction is, however, based on the usual archaeological guessing game that aims at filling the remaining blanks. Our interdisciplinary project has decided to experiment on-site with state-of-the-art portable analysis tools, avoiding any physical sampling, to see if our knowledge of the work of the ancient Egyptian painters and draughtsmen could be taken at a further stage, while based on physical quantification that could be seen as a stronger and more reliable foundation for a redefined scientific hypothesis. The use of XRF mapping has, for instance, been applied to a known case of correction by surface repaint, something that is supposedly rare in the ancient Egyptian formal artistic process, while another fully unexpected one was discovered during the analytic exploration of a royal representation. In both cases, the precise and readable imaging of the physical composition of the painted surface offers a renewed visual approach based of chemistry, that can be shared through a multi- and interdisciplinary approach. However, this also leads to a more complex description of pigment mixtures that could have multiple meanings, where the practical often leads towards the symbolic, and from there hopefully to a renewed definition of the use of colours in complex sets of ancient Egyptian representations. At this stage, though the progress in this on-site material assessment of ancient works of art definitely means astonishing progress, one humbly has to face the fact that these ancient treasures shall still retain part of their defining mysteries. [ABSTRACT FROM AUTHOR]

X-ray fluorescence spectroscopy (XRF) plays an important role for elemental analysis in a wide range of scientific fields, especially in cultural heritage. XRF imaging, which uses a raster scan to acquire spectra pixel-wise across artworks, provides the opportunity for spatial analysis of pigment distributions based on their elemental composition. However, conventional XRF-based pigment identification relies on time-consuming elemental mapping facilitated by the interpretation of measured spectra by experts. To reduce the reliance on manual work, recent studies have applied machine learning techniques to cluster similar XRF spectra in data analysis and to identify the most likely pigments. Nevertheless, it is still challenging to implement automatic pigment identification strategies to directly tackle the complex structure of real paintings, e.g. pigment mixtures and layered pigments. In addition, pigment identification based on XRF on a pixel-by-pixel basis remains an obstacle due to the high noise level. Therefore, we developed a deep-learning based pigment identification framework to fully automate the process. In particular, this method offers high sensitivity to the underlying pigments and to the pigments present in low concentrations, therefore enabling robust mapping of pigments based on single-pixel XRF spectra. As case studies, we applied our framework to lab-prepared mock-up paintings and two 19th-century paintings: Paul Gauguin's Poεave;mes Barbares (1896) that contains layered pigments with an underlying painting, and Paul Cezanne's The Bathers (1899–1904). The pigment identification results demonstrated that our model achieved comparable results to the analysis by elemental mapping, suggesting the generalizability and stability of our model. [ABSTRACT FROM AUTHOR]

X-ray fluorescence (XRF) spectroscopy is a common technique in the field of heritage science. However, data processing and data interpretation remain a challenge as they are time consuming and often require a priori knowledge of the composition of the materials present in the analyzed objects. For this reason, we developed an open-source, unsupervised dictionary learning algorithm reducing the complexity of large datasets containing 10s of thousands of spectra and identifying patterns. The algorithm runs in Julia, a programming language that allows for faster data processing compared to Python and R. This approach quickly reduces the number of variables and creates correlated elemental maps, characteristic for pigments containing various elements or for pigment mixtures. This alternative approach creates an overcomplete dictionary which is learned from the input data itself, therefore reducing the a priori user knowledge. The feasibility of this method was first confirmed by applying it to a mock-up board containing various known pigment mixtures. The algorithm was then applied to a macro XRF (MA-XRF) data set obtained on an 18th century Mexican painting, and positively identified smalt (pigment characterized by the co-occurrence of cobalt, arsenic, bismuth, nickel, and potassium), mixtures of vermilion and lead white, and two complex conservation materials/interventions. Moreover, the algorithm identified correlated elements that were not identified using the traditional elemental maps approach without image processing. This approach proved very useful as it yielded the same conclusions as the traditional elemental maps approach followed by elemental maps comparison but with a much faster data processing time. Furthermore, no image processing or user manipulation was required to understand elemental correlation. This open-source, open-access, and thus freely available code running in a platform allowing faster processing and larger data sets represents a useful resource to understand better the pigments and mixtures used in historical paintings and their possible various conservation campaigns. [ABSTRACT FROM AUTHOR]

The nonplanar shape of a painting as well as practical constraints often result in the painting's surface not being parallel to the plane in that the measurement head of a MA‐XRF scanner is being moved. Changing the working distance affects the measurement geometry, so that the sensitivity for the same element may vary throughout the investigated area and induce visible artifacts. These artifacts are especially visible when different scans of the same painting are stitched together. In this article, we present an approach to correct for the variation of the measurement distance. We explored using an intrinsic part of the XRF data set, the Ar signal from the air, to estimate the distance between surface and instrument. The model is developed based on fundamental parameter calculations and a measurement of a NIST 610 standard and is verified on a set of scans of Rembrandt's 'Portrait of Oopjen Coppit (1611–1689)'. [ABSTRACT FROM AUTHOR]

Caspar David Friedrich (1774–1840), one of the most famous German 19th c. painters, created paintings throughout his artistic life using different paint palettes, including many new pigments from the turn from the 18th to the 19th century. In that regard especially blue and yellow pigments are the focus of this non‐invasive chemical study using X‐ray fluorescence imaging, as these are a landscape painter's major colours. Four paintings from the collection of the Alte Nationalgalerie, Staatliche Museen zu Berlin‐Stiftung Preußischer Kulturbesitz, spanning over two important decades of Friedrich's artistic career, were investigated in situ to determine the chemical composition of the blue pigments used in the sky and the yellow hues used in the sunsets and moonlight. The results indicate the use of iron based yellow pigments as well as smalt based blue pigments in Friedrich's early works, while chromium‐based yellow pigments and cobalt blue are used in later paintings. The finding of cadmium sulphide in a painting dated in 1817, probably as a historical retouching, is interesting and requires further research. This in situ non‐invasive imaging study, although limited to one analytical technique, shows Friedrich's introduction of new synthetic pigments into his paint palette, which varies over the time. These results are important to better understand the painting technique of Caspar David Friedrich and his contemporaries. [ABSTRACT FROM AUTHOR]

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The pigment use in the Tomb of the Reliefs (fourth century BC) and four other tombs (seventh to fourth century BC) in the Etruscan Banditaccia Necropolis near Cerveteri, Italy, has been investigated. We made use of X‐ray fluorescence (XRF) and Raman spot analysis, XRF imaging, infrared luminescence and photography supported by Dstretch contrast enhancement. We identified the use of haematite, goethite, calcite, carbon black, manganese oxide, Tyrian purple, and Egyptian blue, with the last three only found under the central burial place of the Tomb of the Reliefs. The tuff in which these tombs were cut proved to be a significant challenge for XRF analysis as the signals of Ca, Mn, and Fe vary strongly due to the heterogeneity of the stone, so that it is difficult to distinguish between signals from the tuff and the pigments. Finally, we show that lightweight instruments transported in check‐in luggage may not answer all questions on pigment use but do provide additional insights. [ABSTRACT FROM AUTHOR]

Of the once colourful decoration of antique Greek statues only few traces remain today. But these allow one to reconstruct part of the polychromy, based on visual and microscopic inspection and spot analysis with spectroscopic methods. For the first time we used mobile hyperspectral reflectance imaging in the visible and near infrared range and scanning macro XRF imaging for the investigation of remnants of antique polychromy on a stationary object. With this method of analysis we were able to reveal previously unknown traces of ancient paint on the Frieze of the Siphnian Treasury (around 525 BCE). This illustrates the capabilities of this techniques to obtain new insights in a well-described and investigated object. Further, we gained insight into the painting technique, involving an earth based preparation layer. Finally, we present an alternative way to the treatment of the hyperspectral reflectance data in order to obtain easily readable pigment distribution images in case of heterogeneous illumination. [ABSTRACT FROM AUTHOR]

The colorful decoration of statues and buildings in antique times is commonly described by the term antique polychromy. It is well-known among scholars but less so to the general public, and its exact form is the subject of research. In this paper we discuss results obtained from the frieze of the Siphnian Treasury in the Sanctuary of Delphi (Greece). We will present the first application of a mobile instrument for macro-XRF imaging for the in situ investigation of antique polychromy and show that it allows one to identify significant traces not visible to the naked eye and not detectable by XRF spot measurements or any other mobile, noninvasive method. These findings allow for a partial reconstruction of the polychromy. Furthermore, we present a novel approach enabling the correct interpretation of artifacts resulting from changes of the detection geometry in the investigation of complexly shaped samples by XRF imaging. This approach is based on the 3D surface model acquired by photogrammetry and fundamental parameter calculations. [ABSTRACT FROM AUTHOR]

The high brilliance of third-generation synchrotron sources increases the demand for faster detectors to utilize the available flux. The Maia detector is an advanced imaging scheme for energy-dispersive detection realising dwell times per image-pixel as low as 50 µs and count rates higher than 10 × 106 s−1. In this article the integration of such a Maia detector in the Microprobe setup of beamline P06 at the storage ring PETRA III at the Deutsches Elektronen-Synchrotron (DESY) in Hamburg, Germany, is described. The analytical performance of the complete system in terms of rate-dependent energy resolution, scanning-speed-dependent spatial resolution and lower limits of detection is characterized. The potential of the Maia-based setup is demonstrated by key applications from materials science and chemistry, as well as environmental science with geological applications and biological questions that have been investigated at the P06 beamline. [ABSTRACT FROM AUTHOR]

Elemental distribution images acquired by imaging X-ray fluorescence analysis can contain high degrees of redundancy and weakly discernible correlations. In this article near real-time non-negative matrix factorization (NMF) is described for the analysis of a number of data sets acquired from samples of a bi-modal α+β Ti-6Al-6V-2Sn alloy. NMF was used for the first time to reveal absorption artefacts in the elemental distribution images of the samples, where two phases of the alloy, namely α and β, were in superposition. The findings and interpretation of the NMF results were confirmed by Monte Carlo simulation of the layered alloy system. Furthermore, it is shown how the simultaneous factorization of several stacks of elemental distribution images provides uniform basis vectors and consequently simplifies the interpretation of the representation. [ABSTRACT FROM AUTHOR]

L'utilisation des techniques d'imagerie chimique pour l'étude des peintures d'art est en plein essor. Ces techniques non invasives et mobiles permettent l'acquisition d'un grand nombre de données spatiales et spectrales, dont l'interprétation ouvre de nombreuses perspectives pour regarder autrement les oeuvres d'art. Nous présentons ici les concepts et les applications de deux techniques : l'imagerie par spectrométrie de fluorescence X et l'imagerie hyperspectrale en lumière visible et proche infrarouge. [ABSTRACT FROM AUTHOR]

Iron (Fe) sources available for plants in the rhizospheric solution are mainly a mixture of complexes between Fe and organic ligands, including phytosiderophores (PS) and water-extractable humic substances (WEHS). In comparison with the other Fe sources, Fe-WEHS are more efficiently used by plants, and experimental evidences show that Fe translocation contributes to this better response. On the other hand, very little is known on the mechanisms involved in Fe allocation in leaves. In this work, physiological and molecular processes involved in Fe distribution in leaves of Fe-deficient Cucumis sativus supplied with Fe-PS or Fe-WEHS up to 5 days were studied combining different techniques, such as radiochemical experiments, synchrotron micro X-ray fluorescence, real-time reverse transcription polymerase chain reaction and in situ hybridization. In Fe-WEHS-fed plants, Fe was rapidly (1 day) allocated into the leaf veins, and after 5 days, Fe was completely transferred into interveinal cells; moreover, the amount of accumulated Fe was much higher than with Fe-PS. This redistribution in Fe-WEHS plants was associated with an upregulation of genes encoding a ferricIII-chelate reductase (FRO), a Fe2+ transporter (IRT1) and a natural resistance-associated macrophage protein (NRAMP). The localization of FRO and IRT1 transcripts next to the midveins, beside that of NRAMP in the interveinal area, may suggest a rapid and efficient response induced by the presence of Fe-WEHS in the extra-radical solution for the allocation in leaves of high amounts of Fe. In conclusion, Fe is more efficiently used when chelated to WEHS than PS and seems to involve Fe distribution and gene regulation of Fe acquisition mechanisms operating in leaves. [ABSTRACT FROM AUTHOR]

Technical progress in the fields of X-ray sources, optics and detectors is constantly enhancing the pace of data acquisition in XRF imaging. This enlarges the size of the hyperspectral datasets and the number of their sub-parts. This paper describes the challenges in processing large XRF datasets featuring several million pixels/spectra and the strategies developed to overcome them. During the investigation of historical paintings by scanning macro-XRF the main challenges are the correct identification of all spectral features in a dataset and its timely processing. For the identification of spectral features different approaches are discussed, i.e. the use of sum spectra, maximum pixel spectra and of χr2 maps. For the time-efficient, artefact-free evaluation of XRF imaging data, different software packages are evaluated and intercompared (AXIL, PyMCA, GeoPIXE and the in-house written datamuncher). The process of data evaluation is illustrated on a large dataset (3.4 MPixels) acquired during the investigation of a version of Caravaggio's Supper at Emmaus (143 × 199.5 cm2). This 17th century painting is currently the largest object entirely scanned with macroscopic XRF. [ABSTRACT FROM AUTHOR]

A combination of synchrotron radiation (SR) micro X-ray fluorescence (μ-XRF) and XRF mode X-ray absorption near edge structure (XANES) measurements at the Cr K-edge already allowed us to establish that the photo-reduction of chromates to Cr(iii) compounds is the cause of darkening of chrome yellow pigments (PbCr1−xSxO4, 0 ≤x≤ 0.8) in a number of paintings by Vincent van Gogh and in corresponding artificially aged paint models. A silicon drift detector (SDD) was employed to record the Cr-K XRF radiation in these X-ray micro beam-based measurements. However, in view of the limited count rate capabilities and collection solid angle of a single device, μ-XRF and μ-XANES employing single element SDDs (or similar) are primarily suited for collection of spectral data from individual points. Additionally, collection of XRF maps via point-by-point scanning with relatively long dwell times per point is possible but is usually confined to small areas. The development of the 384 silicon-diode array Maia XRF detector has provided valuable solutions in terms of data acquisition rate, allowing for full spectral (FS) XANES imaging in XRF mode, i.e., where spectroscopic information is available at each pixel in the scanned map. In this paper, the possibilities of SR Cr K-edge FS-XANES imaging in XRF mode using the Maia detector are examined as a new data collection strategy to study the speciation and distribution of alteration products of lead chromate-based pigments in painting materials. The results collected from two micro-samples taken from two Van Gogh paintings and an aged paint model show the possibility to perform FS-XANES imaging in practical time frames (from several minutes to a few hours) by scanning regions of sample sizes of the same order (more than 500 μm). The sensitivity and capabilities of FS-XANES imaging in providing representative chemical speciation information at the microscale (spatial resolution from ∼2 to 0.6 μm) over the entire scanned area are demonstrated by the identification of Cr(OH)3, Cr(iii) sulfates and/or Cr(iii) organometallic compounds in the corresponding phase maps, as alteration products. Comparable Cr-speciation results were obtained by performing equivalent higher spatial resolution SR μ-XRF/single-point μ-XANES analysis using a more conventional SDD from smaller regions of interest of each sample. Thus, large-area XRF mode FS-XANES imaging (Maia detector) is here proposed as a valuable and complementary data collection strategy in relation to “zoomed-in” high-resolution μ-XRF mapping and single-point μ-XANES analysis (SDD). [ABSTRACT FROM AUTHOR]

In this paper we demonstrate that by means of scanning reflection FTIR spectroscopy, it is possible to record highly specific distribution maps of organic and inorganic compounds from flat, macroscopic objects with cultural heritage value in a non-invasive manner. Our previous work involved the recording of macroscopic distributions of chemical elements or crystal phases from painted works of art based on respectively macroscopic X-ray fluorescence or X-ray powder diffraction analysis. The use of infrared radiation instead of X-rays has the advantage that more specific information about the nature and distribution of the chemical compounds present can be gathered. This higher imaging specificity represents a clear advantage for the characterization of painting and artist materials. It allows the distribution of metallo-organic compounds to be visualized and permits distinguishing between pigmented materials containing the same key metal. The prototype instrument allows the recording of hyperspectral datacubes by scanning the surface of the artefact in a contactless and sequential single-point measuring mode, while recording the spectrum of reflected infrared radiation. After the acquisition, spectral line intensities of individual bands and chemical distribution maps can be extracted from the datacube to identify the compounds present and/or to highlight their spatial distribution. Not only is information gained on the surface of the investigated artefacts, but also images of overpainted paint layers and, if present, the underdrawing may be revealed in this manner. A current major limitation is the long scanning times required to record these maps. [ABSTRACT FROM AUTHOR]

Abstract: Hidden, sub-surface paint layers and features contain valuable information for the art-historical investigation of a painting's past and for its conservation for coming generations. The number of techniques available for the study of these features has been considerably extended in the last decades and established techniques have been refined. This review focuses on mobile non-destructive subsurface imaging and depth profiling techniques, which allow for the in-situ investigation of easel paintings, i.e. paintings on a portable support. Among the techniques discussed are: X-ray radiography and infrared reflectography, which are long established methods and are in use for several decades. Their capabilities of element/species specific imaging have been extended by the introduction of energy/wavelength resolved measurements. Scanning macro-X-ray fluorescence analysis made it for the first time possible to acquire elemental distribution images in-situ and optical coherence tomography allows for the non-destructive study the surface paint layers in virtual cross-sections. These techniques and their variants are presented next to other techniques, such as Terahertz imaging, Nuclear Magnetic Resonance depth profiling and established techniques for non destructive testing (thermography, ultrasonic imaging and laser based interference methods) applied in the conservation of historical paintings. Next to selected case studies the capabilities and limitations of the techniques are discussed. [Copyright &y& Elsevier]

In this study, P and other low Z elements were determined in aerosol particulates from ambient air using synchrotron radiation-induced total-reflection X-ray fluorescence analysis. Atmospheric transport of nutrients such as P or Si to the oceans is a key factor to marine plankton growth. Concentration of these elements in marine air masses is generally low (P < 10 ng/m3). Therefore, analytical procedures enabling for low detection limits are of interest. Because particle size is strongly correlated to its origin and sedimentation, the aerosols were collected with the aid of a low-pressure Berner impactor, which separates the aerosol particulates in nine size fractions with the smallest fraction from 15 to 30 nm. To be able to determine low Z elements, measurements were performed under vacuum conditions at the FLUO beamline at the ANKA synchrotron. An excitation energy of 3.5 keV near the P K-edge but below the Ca K absorption edge was chosen to avoid interferences of the P K-line with the detector escape artifact of the Ca-K α line. The result showed P was present in concentration from 2 to 180 ng/m3. Detection limits were found to be generally 0.2-0.3 ng/m3 for a collecting time of 1 h for the aerosols, which is an improvement to detection limits reported in other studies. Other elements such as S, Cl, and Si were determined as well. Si like P is a nutrient for marine plankton (diatoms). S and Cl play an important role in cloud formation, e.g. polar stratospheric clouds. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Scanning macro-X-ray fluorescence analysis (MA-XRF) is rapidly being established as a technique for the investigation of historical paintings. The elemental distribution images acquired by this method allow for the visualization of hidden paint layers and thus provide insight into the artist's creative process and the painting's conservation history. Due to the lack of a dedicated, commercially available instrument the application of the technique was limited to a few groups that constructed their own instruments. We present the first commercially available XRF scanner for paintings, consisting of an X-ray tube mounted with a Silicon-Drift (SD) detector on a motorized stage to be moved in front of a painting. The scanner is capable of imaging the distribution of the main constituents of surface and sub-surface paint layers in an area of 80 by 60 square centimeters with dwell times below 10 ms and a lateral resolution below 100 μm. The scanner features for a broad range of elements between Ti (Z = 22) and Mo (Z = 42) a count rate of more than 1000 counts per second (cps)/mass percent and detection limits of 100 ppm for measurements of 1 s duration. Next to a presentation of spectrometric figures of merit, the value of the technique is illustrated through a case study of a painting by Rembrandt's student Govert Flinck (1615–1660). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]