MCMarco Colombo

Marco Colombo

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Marco Colombo has a total of 6 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Application of mobile-macroscale scanning X-ray fluorescence (mobile-MA-XRF) imaging in paleontology: analyses of vertebrate fossil specimens from Messel conserved in different solid and liquid media

    by Marco Colombo, Thomas Lehmann, Wolfgang Ensinger, Valentina Rossi

    Cutting-edge analytical instrumentation is increasingly being developed and applied to the analysis of fossils. X-ray fluorescence (XRF) imaging spectroscopy is a powerful tool to resolve the elemental chemistry of fossil specimens. Most of the XRF application to study fossils is carried out at dedicated synchrotron radiation XRF beamlines. Recent studies used laboratory scanners, i.e. stationary instruments with a measurement chamber or mobile ones to tackle paleontological questions. The application of these new XRF systems on fossils is still relatively limited and clear protocols for the acquisition and processing of the XRF data are currently lacking. Here, we present the use of mobile-macroscale scanning XRF (mobile-MA-XRF) imaging for the in situ analyses of the elemental chemistry of fossil vertebrates from the Messel biota (∼48 Ma, Eocene), including amphibians, reptiles, mammals and birds. We investigate the usefulness of mobile-MA-XRF to detect tissue-specific elemental signatures in fossils preserved in solid resin, liquid glycerin and water. We found remarkable tissue-specific chemical signatures preserved in almost all specimens analyzed. Hair and feathers are associated with S and Ti, abdominal tissues with Cu and Zn and stomach contents, e.g., seeds, are associated with Ni, Cu, and Zn. We provide a detailed protocol for acquisition and processing of MA-XRF data and a critical discussion of the application of this approach to paleontological research. Our work sets the foundation for applying MA-XRF to the analyses of those fossils that cannot be measured at synchrotron facilities and/or with stationary laboratory scanners due to their dimensions, weights and conservation mode.


  • Open Access

    Scanning macro x‐ray fluorescence spectroscopy maps for matching 17th century paintings color areas to different earth pigments uses and for investigating attribution issues

    by Marco Colombo, Falk Münch, Peter Hoffmann, Jochen Sander, Wolfgang Ensinger

    Fe and/or Mn‐containing yellow ochre, red ochre, and umber earth pigments are omnipresent in 17th century paintings. Less common in the materials used in historical paintings of this period is the Fe and Mn‐rich earth pigment sienna. Different uses of historical pigments in one painting by Georg Flegel (1566–1638) and another version of the same painting but of disputed attribution were recently uncovered by means of macro‐x‐ray fluorescence (MA‐XRF) scanning and other non‐invasive analytical techniques. In this paper, an approach solely based upon the correlation of Fe and Mn MA‐XRF maps with the optical image of the painting is compared to the use of Mn/Fe correlation plots. The identification of clusters within a plot of the Fe counts vs. the Mn counts can aid to infer whether an area with a certain color matches with the use of the earth pigments found in the two paintings and to ultimately shed light on the different usage of these pigments. The analytical thresholds found in the Mn/Fe correlation plots allowed to identify clusters differing in composition, which matched an area of a certain color with the earth pigments used therein. This highlighted the differences and similarities between the two paintings, ultimately ascertaining the lower value of the painting of disputed attribution. The analysis of single‐pixel spectra allowed refining the interpretation of specific Mn/Fe correlation plots. The purpose of these data evaluation steps is presented and the limitations of the proposed methodology are also discussed.