Schlaich group

Semiconducting polymers are a special class of materials that combine the electrical properties of semiconductors with the mechanical flexibility and processing advantages of polymers. One prominent example is PEDOT:PSS, a complex where positively charged poly(3,4-ethylenedioxythiophene) chains are balanced by negatively charged poly(styrenesulfonate), chains, which is commonly used as a conductive polymer in organic electronics. Oxidation removes electrons from the PEDOT backbone, generating positive charges (polarons or bipolarons) on PEDOT, increasing its electrical conductivity drastically.

In this project, we aim at subsequent scale-bridging for such materials by combining machine-learned interatomic potentials and grand-canonical simulation approaches to study the oxidation dynamics and subsequent counter-ion uptake with coarse-grained descriptions of the polymers and solute/solvent dynamics on a lattice. This will allow for humidity- or potential-dependent study of the dynamical and mechanical properties of such soft functional materials in close contact with the experimental groups in the RTG.

Applicants should have a background in physics, theoretical chemistry, nano- or materials science, especially invoking knowledge in machine learning, soft matter and statistical mechanics, but elementary knowledge of fluid mechanics is also beneficial.