A multivariate approach to the study of orichalcum ingots from the underwater Gela's archaeological site

Abstract

In this work a careful ICP-OES and ICP-MS investigation of 38 ancient ingots has been performed to determine both major components and trace elements content to find a correlation between the observed different features and the composition. The ingots, recovered in an underwater archaeological site of various finds near Gela (CL, Italy), were previously investigated by X-Ray Fluorescence (XRF) spectroscopy to know the composition of the alloy and it was found that the major elements were copper and zinc, in a ratio compatible with the famous orichalcum similar to the contemporary brass that was considered a precious metal in ancient times. The discovery of huge amount this alloy is extraordinary. Following a chemometric approach at first, the use of Principal Component Analysis (PCA) and Cluster Analysis (CA) allowed us to highlight three well-defined groups of ingots and to point out three ingots that appeared outlier with respect to the whole sample set. Linear Discriminant Analysis (LDA) and Soft Independent Modeling of Class Analogy (SIMCA) enabled us to confirm the difference between the hypothesized groups. The prediction power of the variables computed by SIMCA allowed us pointing out some elements able to differentiate each group. The three well-defined groups of ingots resulting from the chemometric analysis were in agreement with the observations of some morphological parameters such as ingot shape, width, and length and weight and by the presence of different kind of patina. The appearance of three distinctive families of ingots can indicate different geographical location of the furnace, different technology stages and/or different raw material used in melting process and the morphology is indicative of cast diverse technologies. These findings can signify the starting point for giving important insights in the archaeometric study of the orichalcum ingots regarding the provenience and the manufacture technologies.