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Combined micro X-ray absorption and fluorescence spectroscopy to map phases of complex systems: the case of sphalerite

Combining micro-X-ray absorption spectroscopy (μXAS) and micro-X-ray fluorescence spectroscopy (μXRF) is a promising approach for the investigation of complex multi-phase systems. In this work, we have employed this approach to investigate natural sphalerite, the most common form of Zinc Sulfide. Sp...

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Detalles Bibliográficos
Autores principales: Marini, Carlo, Rovira, Anna Maria Diaz, Ramanan, Nitya, Olszewski, Wojciech, Joseph, Boby, Simonelli, Laura
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906441/
https://www.ncbi.nlm.nih.gov/pubmed/31827165
http://dx.doi.org/10.1038/s41598-019-55347-9
Descripción
Sumario:Combining micro-X-ray absorption spectroscopy (μXAS) and micro-X-ray fluorescence spectroscopy (μXRF) is a promising approach for the investigation of complex multi-phase systems. In this work, we have employed this approach to investigate natural sphalerite, the most common form of Zinc Sulfide. Spatially resolved elemental distribution maps of common 3d metal atoms (Zn, Cu, Ni, Co, and Fe) are superimposed with chemical speciation and structural parameter maps in order to understand the sphaleriteore-formation process and metamorphosis. Chemical speciation and structural parameters have been obtained by analyzing the μXAS spectra collected in several representative points of the sample, after μXRF mapping. In the present case, this X-ray based approach has permitted to determine the spatial distribution of the Zn species in sphalerite. The presence of two main zincite and smithsonite inclusions has been established, with the latter located close to copper impurity center. Since copper is known to remarkably reduce the corrosion resistance of zinc, resulting in the formation of carbonate as the corrosion product, this implies a possible role of Cu in the growth of the carbonate inclusions. The results obtained highlight the efficiency of this method in univocally identifying the spatial distribution of phases in complex systems, thanks to the simultaneous access to complementary information.