A new research project called TRACE AI has just received funding from the Swedish research agency Formas. The grant is SEK 3 million and the project is set to run for 18 months starting November 2025. The University of Gothenburg leads it via FRAM and Centre for Future Chemical Risk Assessment and Management.
Its mission is to improve access to reliable information about chemical hazards in materials. Many substances used in manufacturing or recycling today lack complete data about their toxicity or long-term risks. Without that information, recycled materials may unintentionally perpetuate harmful chemicals.
Why chemical safety is crucial
A circular economy depends on the safe reuse of materials. If recycled goods carry toxic elements, they undermine trust and harm human health and ecosystems. EU initiatives such as the Ecodesign for Sustainable Products Regulation (ESPR) are raising demands for better traceability of hazardous substances.
Current chemical safety databases are fragmented and inconsistent. Information is scattered between regulatory lists, safety data sheets, research articles, and proprietary databases. For decision makers in industry and government, synthesizing that data is slow, error-prone, and resource intensive. TRACE AI aims to automate and streamline that process.
How TRACE AI works
The team will apply machine learning, natural language processing, and generative models to collect, organize, and interpret chemical data from multiple sources. They will connect databases, regulatory frameworks, scientific literature, and supplier reports to build a unified, trustworthy data system.
Project partners include University of Gothenburg, Chalmers University of Technology, Stockholm University, RISE Research Institutes of Sweden, and ChemSec (the International Chemical Secretariat). Together they bring expertise in toxicology, life cycle analysis, chemistry, AI, and policy.
Use cases and expected impact
TRACE AI will pilot cases in plastics, textiles and food-contact materials sectors. The goal is to demonstrate how AI tools can enable safer material loops, guide product design, and support regulatory compliance. The project also intends to explore how these tools can assist lower-income regions, where chemical data is especially scarce.
If successful, TRACE AI may help prevent hazardous substances from reentering recycling streams. It could boost confidence in recycled products, reduce health and environmental risks, and accelerate adoption of circular industry practices.
Challenges and future outlook
Significant challenges remain. Data gaps are large. Linking chemical records across entire supply chains is technically and legally complex. Regulatory frameworks differ among jurisdictions. Social acceptance and stakeholder trust are essential. TRACE AI is a preparatory step: it will map those obstacles and propose a shared research agenda.
If TRACE AI succeeds, it may become a critical foundation for transparent, chemically safe circular economy systems. Its tools could influence future regulations, industrial practices, and public confidence in sustainability.
