Non-invasive identification of synthetic organic pigments in contemporary art paints by visible–excited spectrofluorimetry and visible reflectance spectroscopy
El presente estudio da a conocer los resultados de los análisisno invasivosde colorimetría y espectroscopía de reflectancia visible llevados a cabo por primera vez sobre cinco ejemplos de escultura románica en mármol del Museo Arqueológico Nacional (Madrid) de procedencia gallega y leonesa. En concreto se han analizado dos columnas de San Paio de Antealtares (Santiago de Compostela), un parteluz de Vigo, y dos ejemplos procedentes del monasterio de San Benito de Sahagún (León).The present study reveals the results of the non-invasive analysis of colorimetry and visible reflectance spectroscopy, carried out for the first time to five examples of Spanish Romanesque marble sculpture from the National Archaeological Museum (Madrid, Spain) of Galician and Leonese origin. Specifically, two columns of San Paio de Antealtares (Santiago de Compostela), a mullion from Vigo, and two examples from the monastery of San Benito de Sahagún (León) have been analyzed.
Two paintings, made on aluminium support by Silvio Pasotti (among the major exponents of 1960s Italian pop art) were investigated in a totally non-invasive manner to identify the materials used by the artist. Raman spectroscopy, Fourier-transform infrared spectroscopy (FTIR), visible reflectance spectroscopy, and spectrofluorimetry with visible excitation were exploited as molecular analysis techniques, which are particularly suitable to recognise also synthetic organic materials, such as pigments and binders. The effectiveness of this multi-analytical approach was demonstrated, leading to the identification of several synthetic organic pigments, both conventional and “special effect” ones, introduced during the first half of the 20th century, as well as some well-established inorganic ones. Combining FTIR results both in the medium and near IR ranges, considerations regarding the binders employed by the artist could also be made, suggesting the use of both nitrocellulose and acrylic paints. Imaging techniques, such as IR reflectography, false colour IR, UV induced fluorescence, and portable microscopy, were also used to achieve a better knowledge of the painting practice.
AbstractA series of synthetic organic pigments (SOP’s) with azo-containing linkages have been synthesized and characterized by Fourier transform infrared (FTIR) and Raman spectroscopies and laser desorption ionization mass spectrometry (LDI-MS). These pigments include representatives of the chemical classes arylide (Hansa) yellow, diarylide yellow and oranges, and Naphthol AS. Certain of these (PR7, PR10, PR11, PR18, PR19, PO14, PO15, PO16, PY49, PY98, PY106, PY113, PY124, PY203) are historical pigments, that is they were manufactured but subsequently were removed from production. Of these, some have been brought back into limited production. In addition to the above-mentioned pigments, 18 products of azo-linkage reactions formed between N,N′-bis(acetoacetyl)-o-toluidine and substituted anilines have been synthesized and characterized by the methods listed above as well as by visible reflectance spectroscopy. While not commercially available azo pigments, these colorants will serve as model systems to study substituent effects on pigment color.
The objective of this study was to determine if visible reflectance spectroscopy and quantitative colorimetry represent viable approaches to classifying the heat treatment state of silcrete. Silcrete is a soil duricrust that has been used as toolstone since at least the Middle Stone Age. The ancient practice of heat treating silcrete prior to knapping is of considerable interest to paleolithic archaeologists because of its implications for early modern human complex cognition generally and the ability to manipulate the material properties of stone specifically. Here, we demonstrate that our quantitative, non-invasive, and portable approach to measuring color, used in conjunction with k-Nearest Neighbors “lazy” machine learning, is a highly promising method for heat treatment detection. Traditional, expert human analyst approaches typically rely upon subjective assessments of color and lustre and comparison to experimental reference collections. This strongly visual method can prove quite accurate, if difficult to reproduce between different analysts. It is thus surprising that until now, no published study has sought to exploit an instrumental approach to measuring color for classifying heat treatment state in silcrete. In this work, we measured percent reflectance for the visible spectrum (1018 variables) and tristimulus color values (CIEL*a*b*) in unheated and experimentally heat treated silcrete specimens from three sources in South Africa. k-NN classification proved highly effective with both the spectroscopy and colorimetry data sets. An important innovation was using the heat treatment state predicted by the k-NN model for the majority of replicate observations of a single specimen to predict the heat treatment state for the specimen overall. When this majority voting approach was applied to the 746 individual observations in this study, associated with 94 discrete silcrete flakes, both spectroscopy and colorimetry k-NN models yielded 0% test set misclassification rates at the specimen level.
«Opus artificum universa» estudio colorimétrico de la escultura románica en mármol del Museo Arqueológico Nacional: ejemplos de Galicia y León = «Opus Artificum Universa» Colorimetric Study of the Marble Romanesque Sculpture in the Museo Arqueológico Nacional: Examples from Galicia and León