Author
Listed:
- Riccardo Zito
(XGLAB—Bruker Nano Analytics, Via Conte Rosso 23, 20134 Milano, Italy)
- Letizia Bonizzoni
(Department of Physics A. Pontremoli, State University of Milano Italy, Via Celoria 16, 20133 Milano, Italy)
- Nicola Ludwig
(Department of Physics A. Pontremoli, State University of Milano Italy, Via Celoria 16, 20133 Milano, Italy)
Abstract
Even though X-ray fluorescence (XRF) is strictly an atomic method, this technique has been developed mostly at research centers for nuclear physics. One of its most valuable variations is the mapping mode that allows it to shift XRF from a punctual to an image technique. Macro X-ray Fluorescence (MA-XRF) is a widespread analytical technique applied in cultural heritage for characterizing the elemental composition of pigments with a non-destructive, rapid and green approach. When dealing with cultural heritage materials, the sustainability of the applied techniques is directly linked to the limited impact on the work of art. MA-XRF can reveal hidden sub-surface layers or restorations, but, nonetheless, it is hardly adopted for estimating the thickness of layers without resorting to complex Monte Carlo simulations or without combining information from other techniques. Exploiting the recurrent presence of lead white under pictorial layers in historical artworks, we perform a calibration on stand-alone layers produced ad hoc for the relative absorption of Pb L fluorescence lines, and then, their ratio is successfully used to estimate the thickness of azurite and ultramarine blue layers over lead white. The final result is rendered as a heatmap, easy to present to non-technical personnel frequently involved in the cultural heritage field. The new proposed procedure for calculating layer thickness extends the concept of non-invasive applications, paving the way to the possibility of performing stratigraphy without sampling.
Suggested Citation
Riccardo Zito & Letizia Bonizzoni & Nicola Ludwig, 2024.
"Application of Macro X-ray Fluorescence Fast Mapping to Thickness Estimation of Layered Pigments,"
Sustainability, MDPI, vol. 16(6), pages 1-17, March.
Handle:
RePEc:gam:jsusta:v:16:y:2024:i:6:p:2467-:d:1358017
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