Krein, R.; Palm, M.; Heilmaier, M.: Microstructure, Strength and Ductility of some Fe–Al–Ti–based Alloys. 5th Discussion Meeting on the Development of Innovative Iron Aluminium Alloys (FEAL 2009), Prague, Czech Republic (2009)
Riedel, J. L.; Kauffmann, A.; Nizamoglu, S.; Guth, S.; Best, J. P.; Lee, J. S.; Stein, F.; Heilmaier, M.: Application of a novel testing scheme for single-specimen brittle-to-ductile-transition temperature determination to Iron-Aluminides. MSE 2024, Darmstadt, Germany (2024)
Li, X.; Bottler, F.; Spatschek, R. P.; Scherf, A.; Heilmaier, M.; Stein, F.: Novel Lamellar in situ Composite Materials in the Al-Rich Part of the Fe-Al System. Int. Conf. The Materials Chain: From Discovery to Production, University Bochum, Bochum, Germany (2016)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. 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. With this project, we aim to…