Classification of Pottery Fragments Described by Concentration of Chemical Elements

Zanaboni, Anna Maria; Malchiodi, Dario; Bonizzoni, Letizia; Ruschioni, Giulia

doi:10.1007/978-3-031-13321-3_13

Cited by 1 publication

(1 citation statement)

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“…Previous studies that included bucchero chemical composition measurements identified many of the elements identified in our study although with some variation depending on analytical technique, most commonly XRF, 25,26 and research focus such as trace elements only. 27 Considering some elements identified in these Orvieto bucchero sherds, namely Si, Al, Mg, K, and O, are more challenging or impossible to detect using XRF, this LIBS-based study adds a new view to prior published work in the field.…”

Section: Resultsmentioning

confidence: 74%

Handheld Laser-Induced Breakdown Spectroscopy for Field Archaeology: Characterization of Roman Wall Mortars and Etruscan Ceramics

Donais

Douglass

Ramundt

et al. 2023

Applied Spectroscopy Practica

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Handheld laser-induced breakdown spectroscopy (LIBS) was applied to two studies of archaeological material at excavation sites in the Orvieto (Umbria), Italy geographic region. The short analysis times and wide range of detectable elements, covering both metals and nonmetals, achievable via LIBS played a central role in successfully exploring research questions specific to the analyzed artifacts. For one study, associations among Roman terraced walls at the Coriglia excavation site were established through comparisons among lime mortar elemental compositions measured in situ. New conclusions regarding construction phases were achieved, and agreement between handheld LIBS and handheld X-ray fluorescence (XRF) spectrometry results was established. Secondly, Etruscan bucchero pottery was examined to explore relationships among fabric color (gray and black), excavation site (Cavità 254 and Crocifisso del Tufo), and elemental composition. Differences were found and are discussed as they relate to ceramic production and object purpose. Principal component analysis was applied for data analysis in both studies.

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Section: Resultsmentioning

confidence: 74%