Multisensor hyperspectral imaging approach for the microchemical analysis of ultramarine blue pigments

This work presents a multisensor hyperspectral approach for the characterization of ultramarine blue, a valuable historical pigment, at the microscopic scale combining the information of four analytical techniques at the elemental and molecular levels. The hyperspectral images collected were combined in a single hypercube, where the pixels of the various spectral components are aligned on top of each other. Selected spectral descriptors have been defined to reduce data dimensionality before applying unsupervised chemometric data analysis approaches. Lazurite, responsible for the blue color of the pigment, was detected as the major mineral phase present in synthetic and good quality pigments. Impurities like pyrite were detected in lower quality samples, although the clear identification of other mineral phases with silicate basis was more difficult. There is no correlation between the spatial distribution of the bands arising in the Raman spectra of natural samples in the region 1200-1850 cm(-1) and any of the transition metals or rare earth elements (REE). With this information, the previous hypothesis (based on bulk analysis) attributing these bands to luminescence emissions due to impurities of these elements must be revised. We propose the consideration of CO2 molecules trapped in the cages of the aluminosilicate structure of sodalite-type. Additionally, correlation between certain Raman features and the combined presence of Ca, P, and REE, in particular Nd, was detected for the lowest quality pigment. Our results highlight the usefulness of fusing chemical images obtained via different imaging techniques to obtain relevant information on chemical structure and properties.

Automated summary

This work presents a multisensor hyperspectral approach for the characterization of ultramarine blue, a valuable historical pigment, at the microscopic scale combining the information of four analytical techniques at the elemental and molecular levels. The hyperspectral images collected were combined in a single hypercube, where the pixels of the various spectral components are aligned on top of each other. Selected spectral descriptors have been defined to reduce data dimensionality before applying unsupervised chemometric data analysis approaches. Lazurite, responsible for the blue color of the pigment, was detected as the major mineral phase present in synthetic and good quality pigments. Impurities like pyrite were detected in lower quality samples, although the clear identification of other mineral phases with silicate basis was more difficult. There is no correlation between the spatial distribution of the bands arising in the Raman spectra of natural samples in the region 1200-1850 cm(-1) and any of the transition metals or rare earth elements (REE). With this information, the previous hypothesis (based on bulk analysis) attributing these bands to luminescence emissions due to impurities of these elements must be revised. We propose the consideration of CO2 molecules trapped in the cages of the aluminosilicate structure of sodalite-type. Additionally, correlation between certain Raman features and the combined presence of Ca, P, and REE, in particular Nd, was detected for the lowest quality pigment. Our results highlight the usefulness of fusing chemical images obtained via different imaging techniques to obtain relevant information on chemical structure and properties.