The modeling and simulation of advanced materials, which includes solids and fluids, provides the key to future generations of modern devices relying on physical effects on the micro, nano or quantum scale. Examples include organic LED displays, single-photon emitters, tunable nanopores, or lithium-ion batteries.
Truly predictive mathematical models typically involve coupled hierarchies of multiple scales and physical regimes. Efficient and reliable numerical simulations are typically based on sound thermodynamical models in combination with structure preservation in subsequent model reduction and discretization. The increasing availability of experimental and process data arising from modern measurement and storage opportunities allows for to complementing physics-based descriptions based on partial differential equations by novel data-driven modeling techniques. This opens the door to a new predictive quality of numerical simulations in a multitude of applications.
The current projects cover the following topics: hybrid electrothermal modeling for OLEDs, excitons in polymer chains, quantum-classical modeling for quantum-dot lasers, data-driven approximation of electronic band structures for nanodevices, electrocatalytic effects in solvents and their boundary layers, nonlinear behavior in suspension flows.
Scientists in Charge: Ralf Kornhuber, Alexander Mielke, Klaus-Robert Müller