DTU – DANMARKS TEKNISKE UNIVERSITET
DESCRIPTION
The section for Autonomous Materials Discovery (AMD) at DTU Energy focuses on developing theoretical and experimental methodologies to accelerate the discovery of novel materials. Our core competences include atomistic and multiscale materials modelling, machine learning models, self-driving laboratories. We apply these methods to a broad portfolio of energy technologies, e.g., batteries and catalysis.
ROLE IN THE PROJECT
Within DECODE, we are working on the integration of theoretical and experimental models for predicting materials properties. Moreover, we will contribute to the definition of new modelling tools based on AI-accelerated ab-initio molecular dynamics simulations to realistically model the electrochemical interface. In addition, thanks to our expertise in research data management, we will contribute to link DECODE with other EU initiatives, such as BIG-MAP and BATTERY 2030+, which focus on accelerating the discovery of next generation batteries.