AI-driven Digital Twins for waste-to-value technologies
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AI-driven Digital Twins for waste-to-value technologies


AIM is one of the eight projects funded under the EIC Pathfinder Challenge on Waste-to-Value, which has awarded a combined EU contribution of around 30.5 million Euros. Together, the projects are exploring different ways to turn difficult-to-recycle waste into useful products, from breaking down mixed plastics and recovering materials from desalination brines to treating wastewater and converting CO₂ into chemicals.

Digital twins allow to test ideas virtually

Within this portfolio, AIM has a specific role: it is the only project developing digital twins. Using artificial intelligence and computational simulations, the project will create virtual models that link processes at the atomic level with the behaviour of a complete device. These models will provide computational support to the other projects, helping their teams understand how their technologies work and explore how different materials or operating conditions could affect their performance.

Digital twins will allow researchers to test ideas virtually, compare different approaches and identify potential problems before building or scaling up a device. This could reduce the need for costly physical trials and help researchers make better-informed decisions about which solutions to investigate before moving to real-world testing.

This project comes at a time when Europe is pushing to reduce waste, cut emissions, and rely less on fossil resources. On its way to defossilisation, energy systems and industries are developing solutions to replace fossil inputs with alternative carbon-based raw materials, including waste.

Understand the system as a whole

However, working with waste is currently challenging as these materials are often contaminated or contain substances that make conventional recycling difficult. Additionally, in these recycling processes many things happen at once and at very different scales: reactions take place at the level of atoms, but at the same time materials change, transport processes occur and the full device operates under complex conditions. Today, these levels of complexity are often studied separately, which makes it hard to connect detailed knowledge with real performance.

“In AIM, we want to understand these systems as a whole, not as separate pieces. By combining artificial intelligence with multiscale simulations, we can connect what happens at the smallest level with the performance of the full device. This will help us design better and more realistic waste-to-value technologies,” says Núria López, project coordinator.

At the heart of RC FEMS

AIM’s goals closely match the research agenda of RC FEMS. The centre brings together researchers from Ruhr University Bochum, TU Dortmund University and the University of Duisburg-Essen to develop materials and systems for a sustainable energy future. A central idea of RC FEMS is that better energy technologies need an understanding that runs from the atomic scale to the working device, combining simulation, data-driven methods and experiment. That is exactly the bridge AIM’s digital twins are meant to build.

“Turning waste into fuels, chemicals and materials depends on how materials behave at the atomic level, and on how that behaviour carries through to the performance of a real device,” says Silvana Botti. “This question is at the core of RC FEMS. With AIM, the simulation methods we develop in Bochum feed directly into a European network of waste-to-value technologies.”

Cooperation partners

The project brings together a consortium with complementary expertise. Fundamental simulation methods will be developed by the University of Jyväskylä (Finland) and Ruhr University Bochum (Germany), through its Research Center Future Energy Materials and Systems (RC FEMS), while multiscale modelling will be led by EPFL – École Polytechnique Fédérale de Lausanne (Switzerland). Artificial intelligence tools will be contributed by Matgenix (Belgium) and Digital Twin Architecture development and validation will be supported by the Dutch Institute for Fundamental Energy Research – DIFFER (Netherlands). Alongside its coordination role, ICIQ (Spain) will focus on data integration across experimental and computational methods, ensuring consistency across scales, while AGATA (United Kingdom) will lead communication and dissemination activities.

The project is aligned with key European initiatives such as the European Green Deal, REPowerEU and the Fit for 55 package, which highlights the importance of combining digital tools with sustainable solutions.

Funding

The European Innovation Council (EIC) has been established under the EU Horizon Europe programme. It has a budget of €10.1 billion to support game changing innovations throughout the lifecycle from early stage research, to proof of concept, technology transfer, and the financing and scale up of start-ups and SMEs.

The AI-Multiscale Integration for Waste-to-Value Digital Twins – AIM project has received funding from the European Union’s Horizon Europe, Grant Agreement No. 101306664.

Attached files
  • From left to right: Guido Petretto (Matgenix), Nicolas Tancogne-Dejean (RUB), Gian-Marco Rignanese (Matgenix), Karoliina Honala (JYU), Daan van Uffelen (DIFFER), Silvana Botti (RUB), Etienne Boutin (EPFL), Lulu Li (ICIQ-CERCA), Nuria López (ICIQ-CERCA), Silvia Planella (ICIQ-CERCA), Camilla Lo Conte (ICIQ-CERCA), Javier Heras (ICIQ-CERCA/UB), Jennifer Greggs (Agata), Pol Sanz (ICIQ-CERCA), Yuncheng Mao (RUB), Fernando Gomollón (Agata), Patricia An Peña Hernández (AGATA). © Raquel Puras / AGATAThe image may only be used in the context of the press release "AI-driven Digital Twins for waste-to-value technologies" published by RUB on November 9, 2026.
Regions: Europe, Germany, Belgium, Finland, Netherlands, Spain, Switzerland, United Kingdom, North America, United States
Keywords: Applied science, Engineering, Artificial Intelligence, Technology

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