Winning, M.; Brahme, A.; Raabe, D.: Prediction of cold rolling textures of steels using an artificial neural network. Computational Materials Science 46, pp. 800 - 804 (2009)
Winning, M.; Raabe, D.; Brahme, A.: A texture component model for predicting recrystallization textures. Materials Science Forum 558 / 559, pp. 1035 - 1042 (2007)
Brahme, A.; Winning, M.; Raabe, D.: Texture Component Model for Predicting Recrystallization Textures. 15th International Conference on the Texture of Materials (ICOTOM 15), Pittsburgh, PA, USA (2008)
Brahme, A.: Brief Introduction to Cellular Automaton and Monte Carlo Method. MPIE inter-departmental tutorial day(s) 2008, MPI für Eisenforschung GmbH, Düsseldorf, Germany (2008)
Winning, M.; Raabe, D.; Brahme, A.: A texture component model for predicting recrystallization textures. The Third International Conference on Recrystallization and Grain Growth, Jeju Island, South Korea (2007)
Max Planck team explains dendrite propagation, paving the way for safer and longer-lasting next-generation batteries. They publish their findings in the journal Nature.
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
TiAl-based alloys currently mature into application. Sufficient strength at high temperatures and ductility at ambient temperatures are crucial issues for these novel light-weight materials. By generation of two-phase lamellar TiAl + Ti3Al microstructures, these issues can be successfully solved. Because oxidation resistance at high temperatures is…