Automated Scientific Discovery - Materials Science (RAISE pilot) (RIA)

Quel est l’objet de cet appel ?

The topic funds research and innovation projects that add an AI-driven decision layer to automated laboratories, enabling closed-loop experimentation. The initial focus is materials science.

Que finance cet appel ?

Scope

The topic supports safe and trustworthy closed-loop scientific experimentation systems that combine laboratory automation with AI-driven decision-making and robust data infrastructure. It targets laboratories that already have advanced automation and digitalisation, helping them build the intelligence layer that lets instruments plan, run and analyse experiments semi- or fully autonomously, without a complete redesign of existing equipment.

Possible research targets

• Adaptive AI systems, including agentic AI, connected to laboratory instruments and robotics within a validated safe pipeline.
• AI-managed robotic systems that automate diverse experiments on varied hardware.
• Networked automation enabling collaborative experimentation across several laboratories.
• Real-time data processing and analytics, interoperability standards, user interfaces and AI-driven predictive maintenance.
• Data management systems for secure collection, storage, processing and sharing of experimental data.

Focus and costs

The initial focus is on materials science, with possible impact areas including drug discovery, batteries, photovoltaics, carbon capture, water purification and sustainable fabrics. Proposals should show close collaboration between computer or AI scientists and domain scientists, and develop synergies with related Horizon Europe projects. The scope prioritises software development, but justified purchases of complementary equipment are not excluded. Proposals should incorporate human oversight and interaction to ensure accuracy, safety and ethical compliance. International collaboration is encouraged.

Expected outcomes

• Closed-loop experimentation systems in existing laboratories.
• Faster, more efficient and reproducible scientific discovery.
• Prototype demonstrators and best practices for laboratory automation.

Quelle est la date limite ?

2 février 2027 (89 jours)

2 February 2027 (single-stage).