Ponge, D.: Warmumformbarkeit von Stahl. Lecture: Kontaktstudium Werkstofftechnik Stahl, Teil III, Technologische Eigenschaften, Werkstoffausschuss im Stahlinstitut VDEh, Technische Universität Dortmund, June 22, 2008
Calcagnotto, M.; Ponge, D.; Raabe, D.: Fabrication of ultrafine grained dual phase steels. Lecture: National Institute for Materials Science (NIMS), Tsukuba, Japan, October 22, 2007
Storojeva, L.; Ponge, D.; Raabe, D.: Halbwarmwalzen als ein neues Produktionskonzept für Kohlenstoffstähle. Lecture: Max-Planck Hot Forming Conference, MPI für Eisenforschung GmbH, Düsseldorf, Germany, December 05, 2002
Sam, H. C.: Role of microstructure and environment on delayed fracture in a novel lightweight medium manganese steel. Master, Augsburg University (2019)
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
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.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…