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Computational investigation of degradation processes in historical paintings using DFT and AI

Project description

The environmental impact on painting degradation

Preserving historical paintings is a complex task that requires a deep understanding of the processes behind painting degradation, the types of paints used, and the environmental conditions in which the artworks are stored. Unfortunately, obtaining this information can be challenging due to the influence of factors such as humidity, pollutants, and temperature. Supported by the Marie Skłodowska-Curie Actions programme, the REPAINT project aims to enhance our understanding of pigment degradation in 19th- and 20th-century paintings caused by environmental exposure. The project will integrate ab initio molecular dynamics simulations, AI, density functional theory, and advanced computational techniques to analyse the properties of pigments and investigate how they are affected by varying environmental conditions.

Objective

This project focuses on understanding of pigment degradation in 19th to 20th-century paintings caused by environmental factors such as humidity, temperature, and pollutants. By integrating advanced computational techniques, density functional theory (DFT), ab initio molecular dynamics (AIMD) simulations, and artificial intelligence (AI), the research aims to provide a detailed understanding of how these factors affect the chemical stability and degradation pathways of historical pigments at a molecular level. Static DFT calculations will be used to explore the electronic and optical properties of pigments, while AIMD simulations will examine how environmental conditions affect their degradation by revealing the structural changes. Using these computational results, AI models will be developed to predict how pigments degrade based on their composition and environmental conditions by capturing changes over time that static methods can't fully show. This approach will include a comparative study of pigments from different artworks to enhance the robustness of predictive models. The project aims to advance materials science and conservation by creating a comprehensive database that will offer data-driven guidelines to help extend the life of valuable historical artworks. This interdisciplinary approach aims to benefit both the scientific community and conservation professionals by representing an important step forward in the preservation of cultural heritage for future generations.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

BILKENT UNIVERSITESI ULUSAL NANOTEKNOLOJI ARASTIRMA MERKEZI - UNAM
Net EU contribution
€ 165 205,20
Address
ULUSAL NANOTEKNOLOJI ARASTIRMA MERKEZI
06800 ANKARA
Türkiye
Region
Batı Anadolu Ankara Ankara
Activity type
Research Organisations
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Total cost
No data

Partners (1)