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
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization as in micropillar compression. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one.…
Because of their excellent corrosion resistance, high wear resistance and comparable low density, Fe–Al-based alloys are an interesting alternative for replacing stainless steels and possibly even Ni-base superalloys. Recent progress in increasing strength at high temperatures has evoked interest by industries to evaluate possibilities to employ…
The goal of this project is to optimize the orientation mapping technique using four-dimensional scanning transmission electron microscopy (4D STEM) in conjunction with precession electron diffraction (PED). The development of complementary metal oxide semiconductor (CMOS)-based cameras has revolutionized the capabilities in data acquisition due to…
Grain boundaries (GBs) affect many macroscopic properties of materials. In the case of metals grain growth, Hall–Petch hardening, diffusion, and electrical conductivity, for example, are influenced or caused by GBs. The goal of this project is to investigate the different GB phases (also called complexions) that can occur in tilt boundaries of fcc…