Nuclear analytical techniques that use, e.g., X-rays, ions and neutrons as probes are very versatile tools to identify the elemental and molecular composition near the surface, in the sub-surface and within the bulk. They allow 2D and 3D high-resolution imaging (with micrometer or sub-micrometer resolution) what is a primary importance for the analysis of cultural heritage objects. Furthermore, their main advantage is that they provide analytical information with multi-elemental sensitivity and low detection limits.
Scientific research nowadays is undergoing a significant transformation with the rise of Open Science policy and Explainable Artificial Intelligence (Explainable AI). Open Science promotes transparency, collaboration, and accessibility in research, while Explainable AI enhances the capacity to collect, process, analyse and interpret vast amount of data.
The purpose of this research project is to develop and apply innovative Nuclear Analytical approaches supported by Explainable AI and Open Science policy for the provenance of heritage objects to study their interrelation with people.
Key activities of the project will include:
Development and application of machine learning algorithms specifically designed for nuclear analytical data evaluation, imaging and pattern recognition for the provenance of materials and study of their interrelation with people;
Minimizing radiation effects with the support of Explainable AI systems that can predict optimal measurement parameters based on object characteristics, desired quality and level of analytical information with real-time feedback to the data acquisition and scanning systems;
Establishing a framework for a comprehensive digital platform: “Irradiation Passport for Art” specifically designed for sharing analytical data and measurement parameters belonging to a specific heritage object.
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