Circuit4EU is a major European Union initiative to advance 10 different technologies to recover, reuse, and recycle critical raw materials found in old printed circuit boards, permanent magnets, and other electronic device components.
Publicly launched on 4 September, the 3.5-year project brings together 21 partners in 9 countries to support an EU target to derive 25 percent of annual rare-earth minerals from recycling by 2030. French engineering school Arts et Métiers ParisTech is leading the initiative.
The EU remains heavily reliant on foreign imports essential for green transition technologies like solar panels and electric vehicles, the advancement of new digital technologies, and defense, in part because recycling rates remain extremely low.
Among the ten technologies are AI-driven quality inspection, robotic disassembly, digital product passports, desoldering, and hydrometallurgical recycling. These technologies are being piloted across recycling efforts for laptops, Wi-Fi boxes, e-scooters, and dishwashers.
The Circuit4EU initiative aims to achieve a technology readiness level 7 with at least some of the pilot technologies. That’s equivalent to a live prototype in a factory environment. “We hope pilots will move from a research phase to industrial scale, being integrated directly by project partners and available as future technology on the market,” says Nicolas Perry, the project’s coordinator at Circuit4EU.
AI Quality Inspection for E‑Waste
Separating buried treasure from useless junk at scale will mean using AI to automate quality inspection. Trained AI models will help make decisions about the value of components in products such as an old laptop, a wheel from an e-scooter, or a printed circuit board, and whether it’s worth investing time and money to extract them. Circuit boards, for example, could be inspected to find functional components suitable for reuse, as well as defective or damaged components that could be recycled or refined instead.
Circuit4EU hasn’t settled on specific AI models yet, but it is exploring computer vision and machine learning options. A pilot at the University of Ljubljana in Slovenia to test AI inspection will involve e-waste recycling and repair companies including Arianee, EcoWise, GAD Elektronika, and Tech Take Back.
However, heavy reliance on computer vision to survey e-waste streams is not always the best option. According to Sebastian Pattinson, an associate professor at the University of Cambridge and co-founder of AI for manufacturing spin-out Matta, conventional visible-light imaging systems may not be able to see through a product’s external plastic casing to directly flag items like internal batteries or circuit boards, making alternative detection methods more appropriate.“If you really need to see inside a box, and you don’t have any additional information, then a different sensor technology may be more appropriate, such as X-ray inspection, although that could impact the economics,” says Pattinson.
The waste industry has conventionally deployed sensor fusion systems in commercial material recovery facilities to reveal components that would otherwise be concealed from view. These use machine learning and deep learning algorithms to combine data from multiple sensors, such as near-infrared spectroscopy, X-ray fluorescence, and hyperspectral imaging, to enhance the accuracy of material classification.
Robotic Disassembly of Laptops
Another Circuit4EU pilot—led by Tech Take Back working alongside Arts et Métiers spin-out AMValor and non-profit tech research centre Lortek in Spain—is testing robotic disassembly techniques. Circuit4EU’s workstream will focus on laptops and dishwashers. For laptops, for example, an industrial robotic arm would take them apart and remove motherboards or RAM.
A system of pressure contacts and internal sensors will enable the robot to adjust its position to reach the ideal position for disassembly. Printed circuit boards in dishwashers will be removed by hand before being worked on by a robot.
Here, AI computer vision may again play a role. Optical character recognition can scan text to help characterize the product, while other computer vision models would study the positions of chips, RAM, CPU, screws, connectors, and more.
The aim is to automate the process as much as possible, says Perry, to enable accurate unscrewing or desoldering, potentially even when there is zero data on a specific product.
José Saenz, who leads a separate e-waste automation initiative at Germany’s Fraunhofer Institute for Factory Operation and Automation, says a key challenge for robotic disassembly is understanding “how deep to go” when taking products apart.
“Are there potentially hazardous chemicals or materials, are there sharp corners, is it glued and is there a way to unscrew it without having to break it?” Saenz says. He says it’s important to have a database detailing historic product changes and any disassembly processes that failed to work, which can enable a system to make better decisions in the future.
The economics behind different disassembly pathways, for example, whether to unscrew, unglue, mill out screws, or rip apart the entire housing, are all aspects to consider when scaling up the system for factory operation.
Understanding factors such as the value of what’s inside, possible contamination, and the energy being put into the process by the robot “will help determine how to reach higher levels of technology readiness,” says Saenz.
Desoldering and Chemical Recycling
After the hardware is dismantled, the focus shifts to targeted desoldering and chemical recycling to extract the actual raw materials, alongside digital material tracking.
Circuit4EU will benchmark different desoldering technologies when developing an end effector tool for the robot arm, with image recognition and thermal measurement both likely to feature.
Data from quality inspection, robotic disassembly, and other processes will form the basis of a digital product passport—a virtual ID card for recovered rare-earth minerals–which Perry says could be linked to a digital twin providing detailed information on origin, quality, environmental footprint, and recycling options.
Beyond the technical concerns, Circuit4EU has been investigating the value chain for recovered components, including brokers, reusers, and remanufacturers, as well as potential knowledge sharing or synergies with other European projects tackling critical materials recovery.
EU Critical Raw Materials Policy
The shift to more advanced recycling isn’t happening in a vacuum: New EU policies are driving change. The EU’s Critical Raw Materials Act from 2024 introduces a non-binding commitment to obtain 25 percent of all CRMs needed for the energy transition via recycling by 2030.
Amendments to the regulation, slated for approval some time in 2027, would increase pressure on large companies by requiring them to map out full supply chains of components containing rare metals. It would also expand the recycling of permanent magnets in consumer electronics, such as hard disk drives and loudspeakers.
A related proposal to transform the EU Waste Electrical and Electronic Equipment (WEEE) Directive into binding legislation across all member states would oblige product manufacturers to create detailed Bill Of Material-level mapping of CRMs in products to support downstream recycling.
“All this is a reaction to very poor e-waste collection rates and insufficient recycling in Europe,” says Theresa Mörsen, the waste and resources policy manager at environmental NGO Zero Waste Europe, who argues that greater efforts should be made to improve the waste management system.
“Some member states have better systems than others, but essentially there’s a realisation at the EU level that it doesn’t work,” says Mörsen, “There are no real incentives to recycle e-waste, the right option is usually more of an effort and more costly for the end consumer, and there are no clear collection pathways.”