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The CREF was born with a dual soul: a research centre and a historical museum. Its aim is to preserve and disseminate the memory of Enrico Fermi and to promote the dissemination and communication of scientific culture.

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Unlocking Ancient Egyptian Metalworking Methods with Physics and AI

A recent study published in the Journal of Cultural Heritage reveals fascinating insights into the metalworking techniques used in ancient Egypt.

Researchers from CREF, CNR-ISPC, INFN, and the Museo Egizio (Turin)  joined forces to analyze 12 copper-alloy objects from the undisturbed tomb of Kha and Merit (TT8), dating back to the mid-18th Dynasty (circa 1425-1352 BCE). This remarkable tomb, discovered in 1906, is a treasure trove of well-preserved artifacts, offering a unique opportunity to study ancient Egyptian craftsmanship.

The team employed a novel approach, combining non-destructive X-ray fluorescence (XRF) and X-ray diffraction (XRD) with the power of machine learning. XRF provided the elemental composition of the objects, revealing them to be low-tin bronze with traces of lead. XRD, on the other hand, offered insights into the microscopic structure of the metal. This is where the machine learning magic came in. By analyzing the complex XRD patterns with machine learning algorithms, the researchers were able to identify four distinct groups of objects based on their metalworking techniques.

These groups ranged from objects with highly homogeneous microstructures, indicative of extensive heat treatment like annealing, to those with extremely non-homogeneous structures, suggesting cold working methods. Intriguingly, this microscopic classification aligned perfectly with a macroscopic classification based on the objects’ shapes. This demonstrates a clear connection between the intended design and the specific metalworking techniques employed, highlighting the sophisticated understanding of materials science possessed by ancient Egyptian artisans.

“This innovative study not only sheds light on the manufacturing processes of these specific objects” said Dr. Giulia Festa  (CREF) – “but also establishes a new methodology for investigating ancient metal artifacts. By combining traditional analytical techniques with cutting-edge machine learning, we can now delve deeper into the secrets of ancient craftsmanship, gaining a richer understanding of the technological and artistic achievements of past civilizations. “

Title: Studying ancient Egyptian copper-alloy objects via X-ray diffraction and Machine Learning
Authors: G. Festa (CREF), C. Caliri (CNR – Istituto di Scienze del Patrimonio Culturale, Catania) M. Botticelli (CNR – Istituto di Scienze del Patrimonio Culturale, Catania), C.G. Fatuzzo (CNR – Istituto di Scienze del Patrimonio Culturale, INFN, Laboratori Nazionali del Sud, Catania), E. Ferraris (Fondazione Museo delle Antichità Egizie di Torino) , J. Auenmüller (Fondazione Museo delle Antichità Egizie di Torino), D.P. Pavone (CNR – Istituto di Scienze del Patrimonio Culturale, Catania), G. Privitera (CNR – Istituto di Scienze del Patrimonio Culturale, INFN, Laboratori Nazionali del Sud, Catania), C. Scatigno (CREF), C. Miliani (CNR – Istituto di Scienze del Patrimonio Culturale, Catania), F.P. Romano (CNR – Istituto di Scienze del Patrimonio Culturale, Catania – CREF)
https://doi.org/10.1016/j.culher.2025.01.002
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