Öffentliche Seminare

Block copolymers are known for their elaborate microphase separating capabilities. Due to the many tuning parameters a predictive modelling approach is required. Molecular dynamics for such large system sizes is expensive. On the other hand, self-consistent field theory is capable of simulating much larger systems, but its mean-field based approximation only becomes correct when the chain density becomes unrealistically high. As a result some experimental effects such as a first order order-to-disorder phase transition are not reproduced. Field-theoretic simulations, where fields are not constrained to their mean field value but allowed to fluctuate, bridge the gap between these methods. I will give an introduction into this method, with some of the associated phenomena such as the ultraviolet divergence, and successful applications in symmetric block copolymers and block copolymer-homopolymer blends. [mehr]

Innovative solar system missions must become increasingly innovative and elaborate since "the low-hanging fruits have already been picked." Solar sails, which are propelled solely by solar radiation pressure, are among the key technologies for the future exploration of the solar system because they make missions possible that would otherwise be infeasible due to their immense propellant requirements. The optimization of solar sail trajectories, however, is a difficult task. In the talk, a method is presented that is based on machine learning, fusing artificial neural networks and evolutionary algorithms. Such optimization methods may also be applied for subsurface ice melting probes, as they are required to explore Jupiter's and Saturn's icy moons, which may harbor life in the oceans beneath their thick ice crusts. Such ice melting probes have been developed at FH Aachen and successfully tested in Antarctic ice. It will be interesting to discuss whether those methods can also be applied in polymer research. [mehr]