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)
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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.