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)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
In collaboration with Dr. Edgar Rauch, SIMAP laboratory, Grenoble, and Dr. Wolfgang Ludwig, MATEIS, INSA Lyon, we are developing a correlative scanning precession electron diffraction and atom probe tomography method to access the three-dimensional (3D) crystallographic character and compositional information of nanomaterials with unprecedented…
Adding 30 to 50 at.% aluminum to iron results in single-phase alloys with an ordered bcc-based crystal structure, so-called B2-ordered FeAl. Within the extended composition range of this intermetallic phase, the mechanical behavior varies in a very particular way.
The mechanical properties of bulk CrFeCoNi compositionally complex alloys (CCA) or high entropy alloys (HEA) are widely studied in literature [1]. Notably, these alloys show mechanical properties similar to the well studied quinary CrMnFeCoNi [2] . Nevertheless, little is known about the deformation mechanisms and the thermal behavior of these…