Pyrolysis (Py) with in situ derivatisation with hexamethyldisilazane–gas chromatography–mass spectrometry (GC–MS) and a gas chromatography–mass spectrometry procedure based on microwave-assisted saponification were used to identify the organic components in small sized beeswax samples. With the latter procedure quantitative recoveries can be made and hydrocarbons, alcohols and ω-1-diols in the neutral fraction, and fatty acids and ω-1-hydroxy acids in the acidic fraction can be efficiently separated and detected. Both procedures were used to characterise a wax anatomic sculpture “The Plague” (1691–1694) by Gaetano Zumbo, resulting in the identification of beeswax and a Pinaceae resin. The GC–MS analysis brought to light some essential differences in beeswax composition between the raw material and the old modelled wax thus giving some clear indications about the recipe used by the sculptor.

The characterization of beeswax in works of art by gas chromatography-mass spectrometry and pyrolysis-gas chromatography-mass spectrometry procedures

BONADUCE, ILARIA;COLOMBINI, MARIA PERLA
2004

Abstract

Pyrolysis (Py) with in situ derivatisation with hexamethyldisilazane–gas chromatography–mass spectrometry (GC–MS) and a gas chromatography–mass spectrometry procedure based on microwave-assisted saponification were used to identify the organic components in small sized beeswax samples. With the latter procedure quantitative recoveries can be made and hydrocarbons, alcohols and ω-1-diols in the neutral fraction, and fatty acids and ω-1-hydroxy acids in the acidic fraction can be efficiently separated and detected. Both procedures were used to characterise a wax anatomic sculpture “The Plague” (1691–1694) by Gaetano Zumbo, resulting in the identification of beeswax and a Pinaceae resin. The GC–MS analysis brought to light some essential differences in beeswax composition between the raw material and the old modelled wax thus giving some clear indications about the recipe used by the sculptor.
Bonaduce, Ilaria; Colombini, MARIA PERLA
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/187742
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