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Suitable classification of mortars from ancient Roman and Renaissance frescoes using thermal analysis and chemometrics

Overview of attention for article published in BMC Chemistry, April 2015
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Title
Suitable classification of mortars from ancient Roman and Renaissance frescoes using thermal analysis and chemometrics
Published in
BMC Chemistry, April 2015
DOI 10.1186/s13065-015-0098-z
Pubmed ID
Authors

Mauro Tomassetti, Federico Marini, Luigi Campanella, Matteo Positano, Francesco Marinucci

Abstract

Literature on mortars has mainly focused on the identification and characterization of their components in order to assign them to a specific historical period, after accurate classification. For this purpose, different analytical techniques have been proposed. Aim of the present study was to verify whether the combination of thermal analysis and chemometric methods could be used to obtain a fast but correct classification of ancient mortar samples of different ages (Roman era and Renaissance). Ancient Roman frescoes from Museo Nazionale Romano (Terme di Diocleziano, Rome, Italy) and Renaissance frescoes from Sistine Chapel and Old Vatican Rooms (Vatican City) were analyzed by thermogravimetry (TG) and differential thermal analysis (DTA). Principal Component analysis (PCA) on the main thermal data evidenced the presence of two clusters, ascribable to the two different ages. Inspection of the loadings allowed to interpret the observed differences in terms of the experimental variables. PCA allowed differentiating the two kinds of mortars (Roman and Renaissance frescoes), and evidenced how the ancient Roman samples are richer in binder (calcium carbonate) and contain less filler (aggregate) than the Renaissance ones. It was also demonstrated how the coupling of thermoanalytical techniques and chemometric processing proves to be particularly advantageous when a rapid and correct differentiation and classification of cultural heritage samples of various kinds or ages has to be carried out. Graphical abstractPCA analysis of TG data allows differentiating mortar samples from different ages (Roman era and Renaissance).

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Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 21%
Student > Master 3 21%
Other 2 14%
Researcher 2 14%
Professor 1 7%
Other 2 14%
Unknown 1 7%
Readers by discipline Count As %
Arts and Humanities 4 29%
Chemistry 3 21%
Physics and Astronomy 1 7%
Agricultural and Biological Sciences 1 7%
Earth and Planetary Sciences 1 7%
Other 1 7%
Unknown 3 21%