Plasma catalysis offers a sustainable route to convert CO₂ into valuable chemicals using renewable electricity. Researchers used VSC’s computational resources to model plasma–catalyst interactions and reaction kinetics on glass and transition metal surfaces. Their findings reveal how catalyst choice and reaction conditions influence CO₂ splitting efficiency and product formation, advancing understanding of plasma-driven CO₂ conversion.

Researchers from KU Leuven and UHasselt demonstrated that personalized federated learning (PFL) can significantly improve predictions of disability progression in Multiple Sclerosis (MS). Using data from over 26,000 patients, the team developed novel approaches like AdaptiveDualBranchNet, balancing global collaboration with local adaptation. The work was made possible by the VSC’s high-performance infrastructure, enabling large-scale federated experiments.

Reading is shaped not only by word length and frequency but also by how predictable a word is in context. Using Dutch language models, researchers show that smaller models often predict reading times better and that predictability follows a logarithmic effect. With VSC’s computing power, large-scale analyses became possible, revealing new insights into how humans and machines process language.

Researchers from Ghent University have developed a new computational method that accurately predicts the exotic properties of strongly correlated materials, such as high-temperature superconductors. By combining downfolding techniques with tensor networks, and using the power of VSC supercomputing, the team achieved highly precise simulations of electronic structures—opening new paths for quantum devices and next-generation electronics.