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Updated: Aug 6, 2025

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Geochemical ceramic composition dataset using neutron activation and statistical analyses.

Wael M Badawy1,2, Andrey Yu Dmitriev1, Vladimir Yu Koval3

  • 1Frank Neutron Physics Laboratory, Joint Institute for Nuclear Research, 6, Joliot Curie str. 141980 Dubna, Russian Federation.

Data in Brief
|March 23, 2023
PubMed
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This study presents geochemical data for archeological ceramics, using instrumental neutron activation analysis (INAA) to identify elemental fingerprints. These findings establish reference groups for medieval pottery provenance, aiding in the identification of unknown ceramic fragments.

Area of Science:

  • Archaeological Science
  • Geochemistry
  • Materials Analysis

Background:

  • Archeological ceramics provide crucial insights into past human activities and trade networks.
  • Understanding ceramic provenance is essential for reconstructing ancient settlement patterns and interactions.
  • Elemental composition analysis offers a powerful tool for tracing the origin of ceramic artifacts.

Purpose of the Study:

  • To establish comprehensive baseline geochemical data for archeological ceramics.
  • To develop reference groups for medieval pottery provenance using statistical and machine learning methods.
  • To identify key elemental fingerprints for distinguishing ceramic fragments.

Main Methods:

  • Instrumental Neutron Activation Analysis (INAA) to determine elemental composition (39 oxides and elements).
Keywords:
Archaeological ceramicsINAAMultivariate statistical analysisTrace elements

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  • Quality control using certified reference materials for analytical accuracy.
  • Univariate and multivariate statistical analyses, including Hierarchical Clustering (HC), Linear Discriminant Analysis (LDA), and Principal Component Analysis (PCA).
  • Machine learning (ML) methods to identify important elemental discriminators.

    • Main Results:

    • Detailed geochemical composition data (mass fractions in wt% and mg/kg) for 70 ceramic sherds.
    • Identification of chromium as a highly significant element for distinguishing ceramic fragments, alongside other key elements.
    • Establishment of statistically defined reference groups for medieval archeological pottery.

    Conclusions:

    • The generated baseline data and reference groups are crucial for classifying and identifying unknown ceramic sherds.
    • Geochemical analysis combined with statistical and ML approaches effectively deciphers ceramic provenance.
    • This study provides a robust framework for future archeological ceramic sourcing investigations.