Haghighat, S. M. H.; Welsch, E. D.; Gutiérrez-Urrutia, I.; Roters, F.; Raabe, D.: Mesoscale modeling of dislocation mechanisms and the effect of nano-sized carbide morphology on the strengthening of advanced lightweight high-Mn steels. MMM2014, 7th International Conference on Multiscale Materials Modeling
, Berkeley, CA, USA (2014)
Haghighat, S. M. H.; Welsch, E. D.; Gutiérrez-Urrutia, I.; Raabe, D.: Alloy design of advanced lightweight high-Mn steels by combined TEM and discrete dislocation dynamics simulations. 2nd International Conference on High Manganese Steels, Aachen, Germany (2014)
Welsch, E. D.; Haghighat, S. M. H.; Gutiérrez-Urrutia, I.; Raabe, D.: Investigation of nano-sized kappa carbide distribution in advanced austenitic lightweight high-Mn steels by coupled TEM and DDD simulations: Strengthening and dislocation-based mechanisms. 2nd International Conference on High Manganese Steels, Aachen, Germany (2014)
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
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…