30 Million Euros for Catalyst Research Using AI-Controlled Laboratories
ASCEND is leveraging automated learning loops and 3D thin-film catalysts to develop industrially viable drop-in substitutes.
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Six partners from research and industry, including Helmholtz-Zentrum Berlin (HZB), the Fritz-Haber-Institute of the Max Planck Society (FHI), BASF, Dunia Innovations, Siemens Energy, and the Technical University Berlin are launching a joint project to accelerate the catalyst discovery. The German Federal Ministry for Science, Technology and Space (BMFTR) is providing €30 million in funding for ASCEND. The research initiative targets the defossilisation of energy-intensive industries while safeguarding industrial competitiveness, with a focus on the chemical sector. The five-year project will start on 1st April 2026.
ASCEND (Accelerated Solutions for Catalysis using Emerging Nanotechnology and Digital Innovation) aims to accelerate the development of next-generation catalysts, a cornerstone of sustainable chemical manufacturing, by bringing together two breakthrough approaches: Digital Catalysis and thin-film catalyst technologies. Digital Catalysis uses artificial intelligence (AI), simulations, and self-driving laboratories (SDLs) to speed up the discovery of high-performance materials, while thin-film catalysts reduce material use and improve efficiency. Combined with 3D structures, these catalysts enhance surface area and reaction control, towards the goal of providing sustainable syn-fuels and base chemicals as drop-in substitutes in industry.
AI-accelerated material discovery
At the heart of ASCEND’s approach is AI, which, together with automation and robotics, powers SDLs to accelerate scientific experiments. The AI autonomously builds and updates digital twins of the systems under study and bases its design decisions on these models. It designs experiments that are carried out by automated systems in iterative learning loops, using each result to improve the next step. While AI significantly speeds up planning and efficiency, humans remain essential for guiding the overall approach and defining the scientific questions.
The project builds on the long-term successful partnership between the Fritz Haber Institute and Helmholtz-Zentrum Berlin to drive forward catalysis research.
The scientific project coordinators emphasise the strategic importance of the funding: "The AI-driven approach of ASCEND allows us to explore vast material spaces that were previously inaccessible” says project leader Karsten Reuter, FHI. His co-project lead Michelle Browne, HZB adds "It fundamentally changes how fast the science can deliver the solutions chemical industry urgently needs."
The goal is not autonomous experimentation for its own sake, but industrially trustworthy results. In ASCEND, by combining AI with physical synthesis and stress testing under manufacturing-relevant conditions, Dunia accelerates learning while maintaining confidence at scale,” says Marcus Tze-Kiat Ng, Chief Technology Officer of Dunia Innovations.
From research to industrial application: Strengthening technology leadership
By accelerating catalyst development cycles, ASCEND aims to unlock the performance breakthroughs needed for commercially viable, large-scale deployment of green hydrogen and sustainable chemicals. This is an important prerequisite for the industry to become independent of coal and oil products.
"This project allows us to validate new catalyst materials at an early stage, which is critical for moving promising research into technological application," says Wolfram Stichert, Senior Vice President at BASF SE.
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