Raacke, J.; Giza, M.; Grundmeier, G.: Combination of FTIR reflection absorption spectroscopy and work function measurement for in-situ studies of plasma modification of polymer and metal surfaces. Surface and Coatings Technology 200 (1-4), pp. 280 - 283 (2005)
Giza, M.; Raacke, J.; Grundmeier, G.: Surface analysis of plasma induced reactions on organic model substrates. 17th International Symposium on Plasma Chemistry, Toronto, Canada, August 07, 2005 - August 12, 2005. (2005)
Giza, M.; Raacke, J.; Grundmeier, G.: Surface analysis of plasma induced reactions on metallic and organic model substrates. 17th International Symposium on Plasma Chemistry, Toronto, Canada (2005)
Raacke, J.; Giza, M.; Grundmeier, G.: In-situ IR-spectroscopic and Kelvin probe investigations of plasma modified model substrates. Ninth International Conference on Plasma Surface Engineering, Garmisch-Partenkirchen, Germany (2004)
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.