Macroscopic X-ray Powder Diffraction Scanning, a New Method for Highly Selective Chemical Imaging of Works of Art: Instrument Optimization

High-resolution compound-specific mapping in works of art via data fusion of MA-XRPD with hyperspectral data (part 1: Method evaluation)

BACKGROUND

Hyperspectral imaging techniques have emerged as powerful tools for non-invasive investigation of artworks. This paper employs either reflectance imaging spectroscopy (RIS) or macroscopic X-ray fluorescence (MA-XRF) imaging in combination with macroscopic X-ray powder diffraction (MA-XRPD) for state-of-the-art chemical imaging of painted cultural heritage artefacts. While RIS can provide molecular information and MA-XRF can offer elemental distribution maps of paintings of high lateral resolution, the unique advantage of MA-XRPD lies in its ability to visualize the distributions of specific pigments and estimate in a quantitative manner the relative concentrations of the crystalline phases at the surface of artworks. However, MA-XRPD is more time-consuming and offers a lower lateral resolution than RIS and MA-XRF.

RESULTS

This study introduces a machine learning (ML) approach to obtain the distribution of specific compounds on the surface of artworks with a resolution that is comparable to that of RIS and MA-XRF data but with the compound specificity of MA-XRPD. The general aim is to expedite non-destructive artwork imaging analysis by fusing data from different imaging modalities via machine learning models. The effect of preprocessing techniques to enhance the predictive accuracy of the models is explored. The paper demonstrates the method's efficacy on a 16th-century illuminated manuscript, showcasing the feasibility of predicting compound-specific distribution maps. Three evaluation methods-visual examination of the predicted distribution, root mean square errors (RMSE), and feature permutation importance (FPI)-are employed to assess model performance. Fusing MA-XRF with MA-XRPD led to the best RMSE scores overall. However, fusing the RIS and MA-XRPD data blocks also yield very satisfactory and easily interpretable high-resolution compound maps.

SIGNIFICANCE

While MA-XRPD allows for highly specific imaging of artworks, its time-consuming nature and limited resolution presents a bottleneck during non-invasive imaging of painted works of art. By integrating data from more time-efficient hyperspectral techniques such as MA-XRF and RIS, and employing machine learning, we expedite the process without compromising accuracy. The fusion process can also denoise the distribution maps, improving their readability for heritage professionals and art historical scholars.

Exploring high-throughput synchrotron X-Ray powder diffraction for the structural analysis of pharmaceuticals

Synchrotron radiation offers a host of advanced properties, surpassing conventional laboratory sources with its high brightness, tunable phonon energy, photon beam coherence for advanced X-ray imaging, and a structured time profile, ideal for capturing dynamic atomic and molecular processes. However, these benefits come at the cost of operational complexity and expenses. Three decades ago, synchrotron radiation facilities, while technically open to all scientists, primarily served a limited community. Despite substantial accessibility improvements over the past two decades, synchrotron measurements still do not qualify as routine analyses. The intrinsic complexity of synchrotron science means experiments are pursued only when no alternatives suffice. In recent years, strides have been made in technology transfer offices, intermediate synchrotron-based analytical service companies, and the development of high-throughput synchrotron systems at various facilities, reshaping the perception of synchrotron science. This article investigates the practical application of synchrotron X-Ray Powder Diffraction (s-XRPD) techniques in pharmaceutical analysis. By utilizing concrete examples, we demonstrate how high-throughput systems have the potential to revolutionize s-XRPD applications in the pharmaceutical industry, rapidly generating XRPD patterns of comparable or superior quality to those obtained in state-of-the-art laboratory XRPD, all in less than 5 s. Additional cases featuring well-established pharmaceutical active ingredients (API) and excipients substantiate the concept of high throughput in pharmaceuticals, affirming data quality through structural refinements aligned with literature-derived unit cell parameters. Synchrotron data need not always be state-of-the-art to compete with lab-XRPD data. The key lies in ensuring user-friendliness, reproducibility, accessibility, cost-effectiveness, and the streamlined efforts associated with synchrotron instrumentation to remain highly competitive with their laboratory counterparts.

Mixed X-Ray Image Separation for Artworks With Concealed Designs

In this paper, we focus on X-ray images (X-radiographs) of paintings with concealed sub-surface designs (e.g., deriving from reuse of the painting support or revision of a composition by the artist), which therefore include contributions from both the surface painting and the concealed features. In particular, we propose a self-supervised deep learning-based image separation approach that can be applied to the X-ray images from such paintings to separate them into two hypothetical X-ray images. One of these reconstructed images is related to the X-ray image of the concealed painting, while the second one contains only information related to the X-ray image of the visible painting. The proposed separation network consists of two components: the analysis and the synthesis sub-networks. The analysis sub-network is based on learned coupled iterative shrinkage thresholding algorithms (LCISTA) designed using algorithm unrolling techniques, and the synthesis sub-network consists of several linear mappings. The learning algorithm operates in a totally self-supervised fashion without requiring a sample set that contains both the mixed X-ray images and the separated ones. The proposed method is demonstrated on a real painting with concealed content, Do na Isabel de Porcel by Francisco de Goya, to show its effectiveness.

Novel optical photothermal infrared (O-PTIR) spectroscopy for the noninvasive characterization of heritage glass-metal objects

Optical photothermal infrared (O-PTIR) is a recently developed molecular spectroscopy technique that allows to noninvasively obtain chemical information on organic and inorganic samples at a submicrometric scale. The high spatial resolution (≈450 nm), lack of sample preparation, and comparability of the spectral results to traditional Fourier transform infrared spectroscopy make it a promising candidate for the analysis of cultural heritage. In this work, the potential of O-PTIR for the noninvasive characterization of small heritage objects (few cubic centimeters) is demonstrated on a series of degraded 16th century brass and glass decorative elements. These small and challenging samples, typically encountering limitations with existing noninvasive methods such as macroscopic x-ray powder diffraction and μRaman, were successfully characterized by O-PTIR, ultimately identifying the markers of glass-induced metal corrosion processes. The results clearly demonstrate how O-PTIR can be easily implemented in a noninvasive multianalytical strategy for the study of heritage materials, making it a fundamental tool for cultural heritage analyses.

Antimony and Nickel Impurities in Blue and Green Copper Pigments

Impurities in paint layers executed with green and blue copper pigments, although relatively common, have been studied only little to date. Yet, their proper identification is a powerful tool for classification of paintings, and, potentially, for future provenance studies. In this paper, we present analyses of copper pigments layers from wall paintings situated in the vicinity of copper ore deposits (the palace in Kielce, the palace in Ciechanowice, and the parish church in Chotków) located within the contemporary borders of Poland. We compare the results with the analyses of copper minerals from three deposits, two local, and one historically important for the supply of copper in Europe, i.e., Miedzianka in the Holy Cross Mountains, Miedzianka in the Sudetes, and, as a reference, Špania Dolina in the Slovakian Low Tatra. Optical (OM) and electron microscopy (SEM-EDS), Raman spectroscopy, and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) have been used for a detailed investigation of the minute grains. Special attention has been devoted to antimony and nickel phases, as more unusual than the commonly described iron oxides. Analyses of minerals from the deposits helped to interpret the results obtained from the paint samples. For the first time, quantitative analyses of copper pigments’ impurities have been described.

Reflectance Imaging Spectroscopy (RIS) for Operation Night Watch: Challenges and Achievements of Imaging Rembrandt's Masterpiece in the Glass Chamber at the Rijksmuseum

Visible and infrared reflectance imaging spectroscopy is one of the several non-invasive techniques used during Operation Night Watch for the study of Rembrandt’s iconic masterpiece The Night Watch (1642). The goals of this project include the identification and mapping of the artists’ materials, providing information about the painting technique used as well as documenting the painting’s current state and ultimately determining the possible conservation plan. The large size of the painting (3.78 m by 4.53 m) and the diversity of the technical investigations being performed make Operation Night Watch the largest research project ever undertaken at the Rijksmuseum. To construct a complete reflectance image cube at a high spatial resolution (168 µm²) and spectral resolution (2.54 to 6 nm), the painting was imaged with two high-sensitivity line scanning hyperspectral cameras (VNIR 400 to 1000 nm, 2.54 nm, and SWIR 900 to 2500 nm, 6 nm). Given the large size of the painting, a custom computer-controlled 3-D imaging frame was constructed to move each camera, along with lights, across the painting surface. A third axis, normal to the painting, was added along with a distance-sensing system which kept the cameras in focus during the scanning. A total of 200 hyperspectral image swaths were collected, mosaicked and registered to a high-resolution color image to sub-pixel accuracy using a novel registration algorithm. The preliminary analysis of the VNIR and SWIR reflectance images has identified many of the pigments used and their distribution across the painting. The SWIR, in particular, has provided an improved visualization of the preparatory sketches and changes in the painted composition. These data sets, when combined with the results from the other spectral imaging modalities and paint sample analyses, will provide the most complete understanding of the materials and painting techniques used by Rembrandt in The Night Watch.

Experimental Study on the Link between Optical Emission, Crystal Defects and Photocatalytic Activity of Artist Pigments Based on Zinc Oxide

The historical knowledge inherited from house paint documents and the experimental research on synthetic pigments show that production methods have an important role in the performance of paint. In this regard, this work investigates the links existing between the optical emission, crystal defects and photocatalytic activity of zinc white pigment from different contemporary factories, with the aim of elucidating the effects of these characteristics onto the tendency of the pigment to induce paint failures. The analysed samples display highly similar crystallite structure, domain size, and specific surface area, whilst white pigments differ from pure ZnO in regards to the presence of zinc carbonate hydrate that is found as a foreign compound. In contrast, the photoluminescence measurements categorize the analysed samples into two groups, which display different trap-assisted emissions ascribed to point crystal defects introduced during the synthesis process, and associated to Zn or O displacement. The photocatalytic degradation tests infer that the emerged defective structure and specific surface area of ZnO-based samples influence their tendency to oxidize organic molecules under light irradiation. In particular, the results indicate that the zinc interstitial defects may be able to promote the photogenerated electron-hole couples separation with a consequent increase of the overall ZnO photocatalytic activity, negatively affecting the binding medium stability. This groundwork paves the way for further studies on the link between the photoluminescence emission of the zinc white pigment and its tendency to decompose organic components contained in the binding medium.

X-ray Diffraction Mapping for Cultural Heritage Science: a Review of Experimental Configurations and Applications

X-ray diffraction (XRD) mapping consists in the acquisition of XRD patterns at each pixel (or voxel) of an area (or volume). The spatial resolution ranges from the micrometer (μXRD) to the millimeter (MA-XRD) scale, making the technique relevant for tiny samples up to large objects. Although XRD is primarily used for the identification of different materials in (complex) mixtures, additional information regarding the crystallite size, their orientation, and their in-depth distribution can also be obtained. Through mapping, these different types of information can be located on the studied sample/object. Cultural heritage objects are usually highly heterogeneous, and contain both original and later (degradation, conservation) materials. Their structural characterization is required both to determine ancient manufacturing processes and to evaluate their conservation state. Together with other mapping techniques, XRD mapping is increasingly used for these purposes. Here, the authors review applications as well as the various configurations for XRD mapping (synchrotron/laboratory X-ray source, poly-/monochromatic beam, micro/macro beam, 2D/3D, transmission/reflection mode). On-going hardware and software developments will further establish the technique as a key tool in heritage science.

Macroscopic x-ray powder diffraction imaging reveals Vermeer's discriminating use of lead white pigments in Girl with a Pearl Earring

Until the 19th century, lead white was the most important white pigment used in oil paintings. Lead white is typically composed of two crystalline lead carbonates: hydrocerussite [2PbCO₃·Pb(OH)₂] and cerussite (PbCO₃). Depending on the ratio between hydrocerussite and cerussite, lead white can be classified into different subtypes, each with different optical properties. Current methods to investigate and differentiate between lead white subtypes involve invasive sampling on a microscopic scale, introducing problems of paint damage and representativeness. In this study, a 17th century painting Girl with a Pearl Earring (by Johannes Vermeer, c. 1665, collection of the Mauritshuis, NL) was analyzed with a recently developed mobile and noninvasive macroscopic x-ray powder diffraction (MA-XRPD) scanner within the project Girl in the Spotlight. Four different subtypes of lead white were identified using XRPD imaging at the macroscopic and microscopic scale, implying that Vermeer was highly discriminatory in his use of lead white.

Mixed lead carboxylates relevant to soap formation in oil and tempera paintings: the study of the crystal structure by complementary XRPD and ssNMR

The crystal structure of mixed lead carboxylates consisting of both palmitate and stearate anions was revealed by complementary XRPD and ssNMR.