The winning teams have been found among two of the world's leading research environments in the field: Filippo Bigi and Cesare Malosso from the COSMO group of Prof. Michele Ceriotti, École Polytechnique Fédérale de Lausanne (EPFL) and Ilyes Batatia from the group of Prof. Gábor Csányi, Cambridge University, and the Max Planck Institute for Polymer Research (MPIP).
They will now be onboarded on the Danish DCAI NVIDIA GPU supercomputer Gefion for second phase of the competition (Stage 2). There, they will gain access to unique computational and experimental datasets to further develop and train their models to predict experimentally observable outcomes in nanoparticle synthesis from synchrotron experiments. This will be the first time machine learning models are optimized to directly predict experimental nanoparticle synthesis conditions.
"To achieve CAPeX's goals of delivering scalable solutions for Power‑to‑X, we need to develop much faster and more accurate machine learning models, and for this, we need to collaborate with the very best researchers worldwide. A competition like the AIS25 AI4Materials NP Challenge is an opportunity for doing just that. By combining an AI‑driven approach with large FAIR dataset and research infrastructure across borders, we can shorten the time from discovery to industrial uptake and reduce the cost of discovering new advanced materials. In doing so, we strengthen both Europe's green transition and competitiveness," says Tejs Vegge, Director of CAPeX.
