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Atomistic modeling can provide mechanistic insights and improved design principles, but it is limited by the complexity of modern alloys that involve up to a dozen carefully tuned components.
This project will provide a molecular-level understanding of ZDDP tribofilm formation, driving the development of more environmentally friendly lubricant additives while advancing computational tribology.
Brain imaging techniques, particularly magnetic resonance imaging (MRI), play a crucial role in understanding the neurocognitive phenotype of Down syndrome (DS) and its associated challenges.
MXenes are a rapidly expanding class of two-dimensional transition-metal carbides, nitrides, and carbonitrides with exceptional tribological properties.
The project tackles one of the fundamental open questions in cosmology: the nature of dark matter. The project aims to redefine the standards of the field by simulating three cosmological volumes in multiple scenarios: cold, warm and three self-interacting dark matter models.
Velvet initiative aims to build a Multimodal Large Language Model to increase the European capacity and sovereignty in the field of Artificial Intelligence.
The functional properties of materials are systematically and often dramatically affected by the presence of defects and disorder.
This project proposes a video tokenizer based on Variational Autoencoders (VAEs) to address these challenges, incorporating spatio-temporal attention mechanisms and transformer-based architectures to manage long-range spatio-temporal dependencies and reduce artifacts.
The "Voice for Purpose" project represents an innovative approach to enabling communication for individuals with voice and movement impairments, in all European languages.
Propellers are by far the major device for marine propulsion. The improvement of their efficiency is critical for reducing fuel consumption, resulting in beneficial effects on the economic and environmental costs of shipping.