Ponge, D.; Tarzimoghadam, Z.; Klöwer, J.; Raabe, D.: Hydrogen-assisted Failure in Ni-base Superalloy 718 Studied under In-situ Hydrogen Charging: The Role of Localized Deformation in Crack Propagation. TMS 2017 Annual Meeting & Exhibition, San Diego, CA, USA (2017)
Springer, H.; Raabe, D.; Belde, M. M.: Rapid Alloy Prototyping – High Throughput Bulk Metallurgy at the MPIE. Workshop on machine learning and data analytics in advanced metals processing, RollsRoyce Institute Manchester, Manchester, UK (2017)
Diehl, M.; Cereceda, D.; Wong, S. L.; Reuber, J. C.; Roters, F.; Raabe, D.: From Phenomenological Descriptions to Physics-based Constitutive Models EPSRC Workshop on Multiscale Mechanics of Deformation and Failure in Materials. EPSRC Workshop on Multiscale Mechanics of Deformation and Failure in Materials
, Aberdeen, Scotland (2016)
Ponge, D.; Kuzmina, M.; Herbig, M.; Sandlöbes, S.; Raabe, D.: Segregation and Austenite Reversion at Dislocations in a Binary Fe–9%Mn Steel Studied by Correlative TEM-atom Probe Tomography. The 3rd International Conference on High Manganese Steels, Chengdu, China (2016)
Marian, J.; Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.: Unraveling the temperature dependence of the yield strength of tungsten single crystals using atomistically-informed crystal plasticity. 8th International Conference on Multiscale Materials Modeling, MMM2016, Dijon, France (2016)
Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.; Marian, J.: Unraveling the temperature dependence of the yield strength in BCC metals from atomistically-informed crystal plasticity calculation. Dislocations 2016, Purdue University, West Lafayette, IN, USA (2016)
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.