Simulation methods have become a vital pillar in the understanding, optimization, and development of new energy materials. Often, a single length or time scale is not sufficient, as microscopic effects can influence mesoscopic and macroscopic behavior - and vice versa. To capture these interdependent phenomena, we pursue a comprehensive, multiscale approach and develop problem-specific methods to effectively link different scales. Our strategy integrates computer simulations with analytical techniques, machine learning and quantum computing, enabling the creation of advanced, predictive models.

At the micro- and mesoscopic scale, we use ab initio and phase-field methods to investigate mechanical and electrochemical properties, as well as microstructural evolution in materials like steels. At the macroscopic scale, we model friction and decohesion processes using coarse-grained approaches, with applications ranging from energy systems to geological phenomena.