PARC is an EU-wide research and innovation partnership programme to support EU and national chemical risk assessment and risk management bodies with new data, knowledge, methods, networks and skills to address current, emerging and novel chemical safety challenges.

This Polish-Chinese project aims to develop an innovative in silico methodology that integrates molecular mechanics (MM) with machine learning (ML) to design nanoparticle-based drug delivery systems for the brain. By evaluating over 10,000 nanoparticle structural variations and correlating their physicochemical properties with efficacy in receptor-mediated transcytosis, the approach overcomes the limitations of classic physics-based methods. Leveraging the ML expertise of the Polish partner and the MM experience of the Chinese partner, the project will generate a quantitative model to optimize nanocarrier design for improved safety and efficiency in brain drug delivery.

CompSafeNano is a convergence science project that truly integrates existing nanoinformatics and nanomaterials governance projects, and bridge gaps in methodologies and approaches as proposed by the EU 2030 Nanoinformatics Roadmap, by fostering mutual learning, innovative collaborations, and a trans-disciplinary and trans-sectoral language and knowledge integration.

The project aims to develop a new class of photocatalysts based on covalent organic frameworks (COFs) modified with quantum dots, enabling efficient hydrogen production and degradation of toxic pollutants using visible light. The research will focus on pore engineering and appropriate functionalization of COFs to broaden light absorption and enhance charge carrier separation. The obtained materials will be comprehensively characterized, allowing for the creation of a quantitative model correlating the structure with the photocatalytic properties.

The EU-funded NOUVEAU project will develop advanced solid oxide cells using recyclable, sustainable materials free from lanthanum and PMGs. It focuses on novel electrode materials, interconnects, and solid electrolytes. The contribution includes molecular modeling and computational aspects to ensure efficiency.

Nanotechnology holds vast potential but poses health and environmental risks. The EU-funded DIAGONAL project aims to support industries using advanced nanomaterials (MCNMs) and high aspect ratio nanomaterials (HARNs) by studying hazards, exposure, and lifecycle impacts. Its results will enhance safety and risk management strategies

NanoSolveIT aspires to introduce a ground-breaking in silico Integrated Approach to Testing and Assessment (IATA) for the environmental health and safety of Nanomaterials (NM), implemented through a decision support system packaged as both a stand-alone open software and via a Cloud platform.

NanoInformaTIX project is developing a multiscale modelling framework integrating numerous databases and models in one to optimise the assessment of exposure and toxicity associated with engineered nanomaterials.

PATROLS project provide an innovative and effective set of laboratory techniques and computational tools to more reliably predict potential human and environmental hazards resulting from engineered nanomaterial (ENM) exposures. These tools will minimise the necessity of animal testing and will support future categorisation of ENMs in order to support safety frameworks.

The project focuses on developing new photoactive materials based on quantum dots that are more stable, efficient, and activated by visible light, enhancing their application in environmental protection and energy conversion. The research will analyze excitation mechanisms and photochemical reactions to improve the efficiency of pollutant degradation, hydrogen generation, and CO₂ conversion into useful hydrocarbons. Additionally, the use of chemoinformatics and computational modeling will enable advanced nanomaterial design while reducing experimental research costs.

The project aims to understand the excitation mechanism of lanthanide-doped TiO₂ and develop a theoretical model linking electronic and surface properties of RE-TiO₂ with photocatalytic activity. By integrating modeling with experimental data, it will establish relationships between band structure, surface properties, and photocatalytic performance. The final model will guide the preparation of samples to validate its predictions, following the “build-by-design” approach.

​

The project focuses on developing new photoactive materials based on quantum dots that are stable, efficient, and activated by visible light for environmental protection and energy conversion. It aims to enhance pollutant degradation, hydrogen generation, and CO₂ conversion by studying excitation mechanisms and photochemical reactions. Additionally, computational modeling and chemoinformatics will aid in designing advanced nanomaterials while reducing experimental costs.

NanoPuzzles project aim is to create new computational methods for comprehensive modelling the relationships between the structure, properties, molecular interactions and toxicity of engineered nanoparticles. The methods will be based on the Quantitative Structure - Activity Relationship approach, chemical category formation and read-across techniques.

The project is aimed at creating a worldwide network of research partnerships, including various types of research organizations from EU and third countries, with different profiles (computational and empirical risk assessors), focused on the development of new tools for computational risk assessment of engineered nanoparticles (NPs).