This European Partnership project involves both, ambitious scientific projects as well as contributions to the use and development of scientific infrastructures. The scientific projects in the fields of materials research, environmental chemistry, microbial technologies, and high-performance computing are not only selected with respect to state-of-the-art research. They also concern general aspects of fundamental importance for present research strategies and societal challenges. These aspects are (i) to integrate current developments from diverse research fields (e.g. life science and materials science) and to foster interdisciplinary research, (ii) to identify the scale-depending relationship between processes on the atomic level and their consequences on the material’s macroscopic properties, and, (iii) to use high-performance computing systems for the simulation of complex processes in order to provide quantitative predictability. Therefore, within these interdisciplinary oriented projects, we are crossing barriers between different research disciplines and length scales from the atomic level to the macroscopic world.

Our main task is to investigate the possibilities to implement a class method on graphical processor units (GPU) and the application of suitable machine-learning methods to significantly reduce the computing time. In real-world systems we often need to simulate the behaviour of multiple liquids/solids and interactions between them. The simulations can be arbitrarily complex by including different physical phenomena making the simulations more or less accurate.

bilateral DE-SI