Unveiling the Invisible in Uffizi Gallery?s Drawing 8P by Leonardo with Non-Invasive Optical Techniques

Year: 2021

Authors: Dal Fovo Alice; Striova Jana; Pampaloni Enrico; Fontana Raffaella

Autors Affiliation: CNR, Natl Inst Opt CNR INO, Lgo E Fermi 6, I-50125 Florence, Italy.

Abstract: Until recently, the study of drawings by old masters has been confined to the art history conservation field. More specifically, scientific investigations of Leonardo?s drawings are still very few, possibly due to the latter?s extreme fragility and artistic value. However, analytical data are crucial to develop a solid knowledge base of the drawing materials and techniques used by artists in the past. In this work, we report on the application of non-invasive optical techniques on a double-sided drawing by Leonardo belonging to the Uffizi Gallery (8P). We used multispectral reflectography in the visible (Vis) and near-infrared (NIR) regions to obtain a spectral mapping of the drawing materials, to be subsequently integrated with technical information provided by art historians and conservators. Morphological analysis by microprofilometry allowed for the identification of the typical wave-like texture impressed in the paper during the sheet?s manufacture, as well as of further paper-impressed traits attributable to the drawing transfer method used by Leonardo. Optical coherence tomography revealed a set of micrometric engraved details in the blank background, which lack any trace of colored material, nor display any apparent relation to the drawn landscape. The disclosure of hidden technical features allowed us to offer new insights into Leonardo?s still under-investigated graphic practices.

Journal/Review: APPLIED SCIENCES-BASEL

Volume: 11 (17)      Pages from: 7995-1  to: 7995-12

More Information: This research was funded by Regione Toscana (POR FSE 2014-2020, “Giovanisi”, Intervention Program “CNR4C”, CUP B15J19001040004).
KeyWords: Leonardo da Vinci, drawing, multispectral reflectography, microprofilometry, optical coherence tomography
DOI: 10.3390/app11177995

ImpactFactor: 2.838
Citations: 5
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