Frank, A.; Wochnik, A. S.; Bein, T.; Scheu, C.: A biomolecule-assisted, cost-efficient route for growing tunable CuInS2 films for green energy application. RSC Advances 7 (33), pp. 20219 - 20230 (2017)
Frank, A.; Folger, A.; Betzler, S. B.; Wochnik, A. S.; Wisnet, A.; Scheu, C.: Low-cost synthesis of semiconducting nanostructures used in energy applications. 61. Metallkunde-Kolloquium - Werkstoffforschung für Wirtschaft und Gesellschaft, Lech am Arlberg, Austria (2015)
Frank, A.; Wochnik, A. S.; Scheu, C.: Electron microscopy study of CuInS2 solvothermally synthesized with l-Cysteine. Microscopy Conference, Göttingen, Germany (2015)
Frank, A.; Wochnik, A. S.; Betzler, S. B.; Scheu, C.: Copper indium disulfide films synthesized with L-cysteine. Autumn School on Microstructural Characterization and Modelling of Thin-Film Solar Cells, Werder, Potsdam, Germany (2014)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
“Smaller is stronger” is well known in micromechanics, but the properties far from the quasi-static regime and the nominal temperatures remain unexplored. This research will bridge this gap on how materials behave under the extreme conditions of strain rate and temperature, to enhance fundamental understanding of their deformation mechanisms. The…
The precipitation of intermetallic phases from a supersaturated Co(Nb) solid solution is studied in a cooperation with the Hokkaido University of Science, Sapporo.
In this project, we employ atomistic computer simulations to study grain boundaries. Primarily, molecular dynamics simulations are used to explore their energetics and mobility in Cu- and Al-based systems in close collaboration with experimental works in the GB-CORRELATE project.
This project is a joint project of the De Magnete group and the Atom Probe Tomography group, and was initiated by MPIE’s participation in the CRC TR 270 HOMMAGE. We also benefit from additional collaborations with the “Machine-learning based data extraction from APT” project and the Defect Chemistry and Spectroscopy group.