Data, AI and material innovations for the industry of tomorrow

At the heart of the Fraunhofer trade fair presentation is the question of how industrial systems can be made not only more efficient, but above all more robust and flexible with the help of data, artificial intelligence and new materials. The exhibits make it clear that resilience today arises from the intelligent interaction of data ecosystems, automated processes and sustainable technologies.

At the joint Fraunhofer stand (Hall 11, Stand D33), the latest scientific findings will be combined with innovative technological solutions for industrial needs. The diversity of the projects demonstrates the interdisciplinary strength of Fraunhofer - from virtual AI avatars in the metaverse and strategic production planning to battery recycling and the recovery of critical raw materials through to high-performance electronic systems.

With a view to the partner country of Hannover Messe 2026 Brazil, the Fraunhofer Liaison Office Brazil presents successful international cooperation projects and emphasizes the importance of global innovation networks for industrial transformation.

Another focus is on contributions to the hydrogen economy: at the Hydrogen Island (Hall 11, Stand E9-E11), Fraunhofer Institutes will be showcasing technologies along the entire value chain, from production, storage and transportation to industrial applications.

Highlight exhibits

Collaborative Powerwall and virtual AI avatars: What will tomorrow's industrial collaboration look like and what role will the metaverse play? Researchers show new forms and potentials of engineering, service development and human-machine interaction - with immersive visualizations, AI avatars and digital twins.

High-performance packaging technology: Using a demonstrator, researchers present solutions from the APECS pilot line within the framework of the EU Chips Act for chip integration, cooling and reliable packaging, which enable developers and manufacturers to realize complex high-performance electronics in a particularly space-saving and cost-efficient manner.

Tailor-made and bio-based fertilizer: Over-fertilization in agriculture harms plants, soil and drinking water. An alternative fertilizer that is completely biodegradable supplies plants exclusively with necessary nutrients and thus avoids overfertilization. At the Hannover Messe, the researchers will present the results of the test series with the self-fertilized plants.

Battery recycling and recovery of critical raw materials: For the battery recycling industry and water treatment companies, a newly developed, chemical-free electrochemical process enables the efficient recovery of critical raw materials. Operation at room temperature and ambient pressure can significantly reduce investment and operating costs.

Strategic production planning with mathematics: Better decisions are no coincidence, but can be calculated and are even a competitive advantage. By using mathematical optimization, those responsible in production and logistics can reliably meet complex, multidimensional challenges in production planning in order to reduce costs, increase throughput and secure delivery dates.

Safe "unlearning" in distributed AI models: What happens when an actor leaves a decentralized AI ecosystem and its data needs to be unlearned? Together with Fujitsu, Fraunhofer shows how secure "unlearning" can be achieved without major loss of accuracy. For operators of data rooms such as Manufacturing-X, this enables data sovereign and GDPR-compliant use of distributed AI models.

Conversion of biogenic residues into fuels and chemical intermediates: For the energy, chemical, agricultural and waste industries, 'TCR' (Thermo-Catalytic Reforming) technology converts biogenic residues simultaneously into three valuable, storable products - synthesis gas, biocrude oil and biochar - thus promoting a circular economy and independence from fossil resources.

Smart data pipelines as a trustworthy basis for AI applications: The smart data pipelines shown create a trustworthy foundation for AI applications in data-driven companies and organizations by ensuring a transparent process for quality-assured data collection, secure exchange and traceable AI training.