News

Work Package 5 (WP5) of the FIREFLY Horizon Europe project, conducted by INLECOM focuses on the development and validation of an AI-based prediction tool for the RES-powered electrochemical toolbox. The primary objective is to create a user-friendly digital tool that leverages artificial intelligence (AI) to support decision-making in enhanced metal recycling and catalyst synthesis processes.

The AI-based prediction tool developed in WP5 is expected to improve the way industries approach metal recycling and catalyst synthesis. The tool will not just provide accurate predictions and insights but it will also predict the optimal combination of different electrochemical technologies to achieve user defined criteria like:

• minimising the energy consumption
• maximising the recycled catalyst thus enabling more efficient and sustainable processes
• reducing waste and improving resource utilisation.

This innovation is anticipated to have a significant impact on the chemical industry, contributing to the European Union’s goals of sustainability and circular economy.

Updates of the AI/ML-based digital tool reported at month 18 (M18)

So far, WP5 has achieved several key milestones. The design of the user interface (UI) for the AI/ML-based digital tool has been developed and the team at INLE has already conducted a preliminary validation with project partners. This initial validation is expected to provide valuable feedback, which will be used to refine and further improve the UI.

Machine Learning (ML) algorithms trained with data from the electrochemical processes developed in FIREFLY have been integrated within the tool to ensure accurate and reliable predictions. The results obtained so far are very promising, indicating that the tool can effectively support decision-making in metal recycling and catalyst synthesis processes.

In conclusion, WP5 is on track to deliver a game-changing AI-based prediction tool that will enhance the efficiency and sustainability of metal recycling and catalyst synthesis.