In this group, lithium-ion batteries and next-generation batteries are investigated at the cell level. The goal is to optimize future batteries in terms of capacity, performance, lifetime and safety through a detailed understanding of physical and chemical processes. One focus is on characterizing systems as close to reality as possible by using non-invasive methods. This group also focuses on the investigation and development of sustainable material alternatives. Tailor-made mathematical models using different platforms are used as support. As a member of the Battery LabFactory Braunschweig (BLB), an active contribution is made to the further development of batteries and their production and diagnosis.
We research and develop sustainable battery materials and non-invasive characterization methods for battery applications. These methods include cyclic voltammetry, electrochemical impedance spectroscopy, gas analysis (DEMS, GC/MS), X-ray tomography, acoustic emissions, and ultrasonic examination. The application of these methods allows us to observe and distinguish processes within the battery cell under realistic conditions. This is used to attribute changes in electrode structure or cell chemistry due to production or aging to individual processes. Based on these time-resolved and often imaging methods, production and cell construction can be optimized as well as operating conditions can be adapted to the respective cell chemistry and application.
Mathematical models link phenomena to physical and chemical causes. In our models, transport processes as well as chemical and electrochemical reaction kinetics are mathematically represented to enable the simulation of battery performance and degradation processes. Furthermore, the development of innovative coupling algorithms allows us to perform multiphysical (thermal, electrical and chemical) and multiscale (atomistic and macroscopic) simulations. Based on these new models, we mathematically represent physical processes and their complex interaction in batteries.
While purely experimental methods often do not allow a clear physical explanation, purely theoretical models often do not provide quantitative statements for real systems. For this reason, the combination of mathematical models and non-invasive in operando experiments is crucial to analyze and optimize batteries.