Peranio, N.; Schulz, S.; Li, Y. J.; Roters, F.; Raabe, D.; Masimov, M.; Springub, G.: Processing of dual-phase steel for automotive applications: Microstructure and texture evolution during annealing and numerical simulation by cellular automata. Euromat 2009 (European Congress and Exhibition on Advanced Materials and Processes), Glasgow, UK (2009)
Butz, A.; Rist, T.; Springub, B.; Roters, F.; Schulz, S.; Peranio, N.; Lossau, S.: From Cold Rolling to Deep Drawing - Microstructure Based Modeling of a Dual Phase Steel. NUMISHEET 2008, Interlaken, Switzerland (2008)
Springub, G.; Masimov, M.; Peranio, N.; Li, Y. J.; Roters, F.; Raabe, D.: Study of substructure and texture development in dual phase steels due to thermo-mechanical treatment. ITAP3, 3d International Conference on Texture and Anisotropy in Polycrystals, Göttingen, Germany (2009)
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
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
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.