X-ray computed microtomography: A non-invasive and time-efficient method for identifying and screening Roman copper-based coins
Source abstract
Abstract
This study utilises X-ray Computed Micro-Tomography (μXCT) as a non-destructive and non-invasive method to recover the original surface features and reveal the characteristics of encrusted, illegible Roman copper-based coins before any physical cleaning process is performed. The coins were retrieved from the topsoil during an archaeological survey in the countryside of the ancient city of Aquileia, Italy, and were severely degraded, covered with accumulated matter and pronounced encrustations developed over centuries of aging buried in soil. Despite their condition, most of the coins were identified from a numismatic standpoint using tomographic data alone, with the aid of reference images. They were subsequently cleaned using traditional manual methods and the results compared with μXCT. X-ray Fluorescence (XRF) analysis of the coins after the physical cleaning confirmed their numismatic attribution and revealed information regarding the influence of different alloy compositions on the applicability of the μXCT method, as well as on the corrosion process of the coins. This study showcases how the application of μXCT on fragile corroded metal artifacts prior to any intrusive manual procedures can expedite the identification process, mitigating the risk of information loss caused by physical handling and cleaning. This approach proves particularly valuable when dealing with large numbers of coins that would typically require restoration for identification purposes. It also emphasises the numerous advantages of using μXCT for coin identification, provenance determination, dating, virtual restoration, digitisation, and long-term preservation.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Cultural Heritage Materials Analysis · Nuclear Physics and Applications · Currency Recognition and Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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