Konrad, J.; Zaefferer, S.; Schneider, A.: Investigation of nucleation mechanisms of recrystallization in warm rolled Fe3Al base alloys. Materials Science Forum 467-470, pp. 75 - 80 (2004)
Zaefferer, S.; Konrad, J.; Raabe, D.: 3D-Orientation Microscopy in a Combined Focused Ion Beam (FIB) - Scanning Electron Microscope: A New Dimension of Microstructure Characterisation. Microscopy Conference 2005, Davos, Switzerland (2005)
Konrad, J.; Raabe, D.; Zaefferer, S.: Investigation of orientation gradients around particles and their influence on particle stimulated nucleation in a hot rolled Fe3Al based alloy by applying 3D EBSD. DPG Frühjahrstagung, Berlin, Germany (2005)
Konrad, J.; Raabe, D.; Zaefferer, S.: Investigation of Nucleation Mechanisms of Recrystallization in Warm Rolled Fe3Al Base Alloys. 2nd International Conference on Recrystallization and Grain Growth, Annecy, France (2004)
Konrad, J.: Hot Rolling Behaviour and Plastic Anisotropy of Fe3Al-based Alloys. Discussion Meeting on the Development of Innovative Iron Aluminium Alloys, MPIE Düsseldorf (2004)
Konrad, J.; Raabe, D.; Zaefferer, S.: Texturentwicklung beim Warmwalzen und bei der Rekristallisation von Fe3Al-Basislegierungen. Sitzung des DFG Fachausschuss Intermetallische Phasen, MPIE, Düsseldorf, Germany (2004)
Konrad, J.; Zaefferer, S.; Schneider, A.; Raabe, D.; Frommeyer, G.: Texturentwicklung beim Warmwalzen und bei der Rekristallisation von Fe3Al-Basislegierungen. Treffen des Fachausschusses Intermetallische Phasen, MPI Eisenforschung, Düsseldorf (2004)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.