Reviving degraded colors of yellow flowers in 17th century still life paintings with macro- and microscale chemical imaging

Deep learning for enhanced spectral analysis of MA-XRF datasets of paintings

Recent advancements of noninvasive imaging techniques applied for the study and conservation of paintings have driven a rapid development of cutting-edge computational methods. Macro x-ray fluorescence (MA-XRF), a well-established tool in this domain, generates complex and voluminous datasets that pose analytical challenges. To address this, we have incorporated machine learning strategies specifically designed for the analysis as they allow for identification of nontrivial dependencies and classification within these high-dimensional data, thereby promising comprehensive interrogation. We introduce a deep learning algorithm trained on a synthetic dataset that allows for fast and accurate analysis of the XRF spectra in MA-XRF datasets. This approach successfully overcomes the limitations commonly associated with traditional deconvolution methods. Applying this methodology to a painting by Raphael, we demonstrate that our model not only achieves superior accuracy in quantifying the fluorescence line intensities but also effectively eliminates the artifacts typically observed in elemental maps generated through conventional analysis methods.

Combined macro X-ray fluorescence (MA-XRF) and pulse phase thermography (PPT) imaging for the technical study of panel paintings

Museum staff usually relies on a proven combination of X-ray radiography (XRR) and infrared reflectography (IRR) to study paintings in a non-destructive manner. In the last decades, however, the research toolbox of heritage scientists has expanded considerably, with a prime example being macro X-ray fluorescence (MA-XRF), producing element-specific images. The goal of this article is to illustrate the added value of augmenting MA-XRF with pulse phase thermography (PPT), a variant of active infrared thermographic imaging (IRT), which is an innovative diagnostic method that is able to reveal variations between or in materials, based on a different response to minor fluctuations in temperature when irradiated with optical radiation. By examining three 16th- and 17th-century panel paintings we assess the extent in which combined MA-XRF and PPT contributes to a better understanding of two commonly encountered interventions to panel paintings: (a) Anstückungen (enlargement of the panel) or (b) substitutions (replacement of part of the panel). Yielding information from different depths of the painting, these two techniques proved highly complementary with IRR and XRR, expanding the understanding of the build-up, genesis, and material history of the paintings. While MA-XRF documented the interventions to the wooden substrate indirectly by revealing variations in painting materials, paint handling and/or layer sequence between the original part and the extended or replaced planks, PPT proved beneficial for the study of the wooden support itself, by providing a clear image of the wood structure quasi-free of distortion by the superimposed paint or cradling. XRR, on the other hand, revealed other features from the wood structure, not visible with PPT, and allowed looking through the wooden panels, revealing e.g. the dowels used for joining the planks. Additionally, IRR visualised dissimilarities in the underdrawings. In this way, the results indicate that PPT has the potential to become an acknowledged add-on to the expanding set of imaging methods for paintings, especially when used in combination with MA-XRF, IRR and XRR.

Chemical Mapping of the Degradation of Geranium Lake in Paint Cross Sections by MALDI-MSI

Matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has become a powerful method to extract spatially resolved chemical information in complex materials. This study provides the first use of MALDI-MSI to define spatial-temporal changes in oil paints. Due to the highly heterogeneous nature of oil paints, the sample preparation had to be optimized to prevent molecules from delocalizing. Here, we present a new protocol for the layer-specific analysis of oil paint cross sections achieving a lateral resolution of 10 μm and without losing ionization efficiency due to topographic effects. The efficacy of this method was investigated in oil paint samples containing a mixture of two historic organic pigments, geranium lake and lead white, a mixture often employed in the work of painter Vincent Van Gogh. This methodology not only allows for spatial visualization of the molecules responsible for the pink hue of the paint but also helps to elucidate the chemical changes behind the discoloration of paintings with this composition. The results demonstrate that this approach provides valuable molecular compositional information about the degradation pathways of pigments in specific paint layers and their interaction with the binding medium and other paint components and with light over time. Since a spatial correlation between molecular species and the visual pattern of the discoloration pattern can be made, we expect that mass spectrometry imaging will become highly relevant in future degradation studies of many more historical pigments and paints.

Multidisciplinary approach to the study of large-format oil paintings

Cultural heritage has become a keystone for comprehending our society, as it represents and reflects our origins, passions, beliefs and traditions. Furthermore, it provides fundamental information about specific temporary spaces, materials' availability, technology, artist's intention, and site weather conditions. Our aim was to develop a multidisciplinary approach with a main focus on investigating two Italian large-format paintings located in highly diverse environments such as the National Theater of Costa Rica. We monitored environmental conditions and quantified fungal aerial spores. Then, we determined regions of possible biodeterioration with the software MicroorganismPattern and used the software PigmentArrangement to elucidate the apparent colour of the paintings based on distribution and arrangement of the pigment crystals. Finally, we characterized eight genera of calcareous nannofossils found in the ground layers of the artwork. The former Men's Canteen at the National Theater of Costa Rica presented a mean air temperature of 23.5 [Formula: see text]C, a relative humidity of 72.7% and a concentration of CO[Formula: see text] of 570 ppm. The fungal aerial concentration was 1776 spores/m[Formula: see text]. The software MicroorganismPattern identified 32 sampling regions, out of which 11 were positive for microbial contamination. The software PigmentArrangement determined that the blue crystals (ultramarine pigment) had the shortest distances between themselves (29 [Formula: see text]m). Finally, the nanofossils identified enabled us to restrict the age of the material to a biostratigraphic interval ranging from Coniacian to Maastricthian ages. By using a multidisciplinary approach we were able to explore the diptych, suggest a set of minimally invasive perspectives in tropical environments to be used worldwide and obtain key information about the artist's artistic process, materials used along with better understand its state of conservation.