: A selection of historical textile fragments from the Venetian art dealer Moisè Michelangelo Guggenheim collection, ranging from XV to XVIII century, has been investigated by means of non-invasive techniques in order to reveal the coloring materials. Imaging was preliminarily used to visually investigate the selected artwork fragments in order to investigate their structure and conservation conditions; Fiber Optics Reflectance Spectroscopy (FORS) allowed recognizing the main natural dyestuffs, such as indigotin and anthraquinones-based compounds, except the yellow ones, difficultly identifiable when using this non-invasive technique. Collected spectroscopic data have been also elaborated by using a clustering algorithm that permitted to group collected spectra on the basis of similar properties and evidencing their inflection point wavelength as the most influencing feature.
de Ferri, L., Tripodi, R., Martignon, A., Ferrari, E.S., Lagrutta-Diaz, A.C., Vallotto, D., et al. (2018). Non-invasive study of natural dyes on historical textiles from the collection of Michelangelo Guggenheim. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 204, 548-567 [10.1016/j.saa.2018.06.026].
Non-invasive study of natural dyes on historical textiles from the collection of Michelangelo Guggenheim
Tripodi, R;
2018
Abstract
: A selection of historical textile fragments from the Venetian art dealer Moisè Michelangelo Guggenheim collection, ranging from XV to XVIII century, has been investigated by means of non-invasive techniques in order to reveal the coloring materials. Imaging was preliminarily used to visually investigate the selected artwork fragments in order to investigate their structure and conservation conditions; Fiber Optics Reflectance Spectroscopy (FORS) allowed recognizing the main natural dyestuffs, such as indigotin and anthraquinones-based compounds, except the yellow ones, difficultly identifiable when using this non-invasive technique. Collected spectroscopic data have been also elaborated by using a clustering algorithm that permitted to group collected spectra on the basis of similar properties and evidencing their inflection point wavelength as the most influencing feature.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
