We present a systematic non-invasive investigation of a large corpus of early printed books, exploiting multiple techniques. This work is part of a broader project - Argeia - aiming to study early printing technologies, their evolution and, potentially, the identification of physical/chemical fingerprints of different manufactures and/or printing dates. We analyzed sixty volumes, part of the important collection of the Ateneo Veneto in Venice (Italy), printed between the 15th and the 17th centuries in the main European manufacturing centers. We present here the results of the imaging analysis of the entire corpus and the X-Ray Fluorescence (XRF) investigation performed, focusing on the XRF data and their statistical treatment using a combination of Principal Component Analysis (PCA) and Logistic Regression. Thanks to the broad XRF investigation - more than 200 data points - and to the multidisciplinary approach, we were able to discriminate the provenances of the paper - in particular for the German and Venetian volumes - and we potentially identified a chemical fingerprint of Venetian papers.

Printing materials and technologies in the 15 th − 17 th century book production: an undervalued research field

Balliana, E.
Writing – Review & Editing
;
Pizzol, G.
;
Zendri, E.
Supervision
;
Raines, D.
2017-01-01

Abstract

We present a systematic non-invasive investigation of a large corpus of early printed books, exploiting multiple techniques. This work is part of a broader project - Argeia - aiming to study early printing technologies, their evolution and, potentially, the identification of physical/chemical fingerprints of different manufactures and/or printing dates. We analyzed sixty volumes, part of the important collection of the Ateneo Veneto in Venice (Italy), printed between the 15th and the 17th centuries in the main European manufacturing centers. We present here the results of the imaging analysis of the entire corpus and the X-Ray Fluorescence (XRF) investigation performed, focusing on the XRF data and their statistical treatment using a combination of Principal Component Analysis (PCA) and Logistic Regression. Thanks to the broad XRF investigation - more than 200 data points - and to the multidisciplinary approach, we were able to discriminate the provenances of the paper - in particular for the German and Venetian volumes - and we potentially identified a chemical fingerprint of Venetian papers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3695256
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