Elkot, M.; Sun, B.; Ponge, D.; Raabe, D.: Tackling hydrogen embrittlement sensitivity and poor low-temperature toughness of austenitic high manganese lightweight steel. Thermec 2023 - International Conference on PROCESSING & MANUFACTURING OF ADVANCED MATERIALS, Vienna, Austria (2023)
Elkot, M.; Sun, B.; Ponge, D.; Raabe, D.: The deceit of steel strength ductility diagrams: A case study on high manganese lightweight steel. 7th International Conference of Engineering Against Failure ICEAF 2023, Spetses, Greece (2023)
Elkot, M.; Sun, B.; Zhou, X.; Ponge, D.; Raabe, D.: Grain boundary κ-carbides in high manganese lightweight steel: degradation assessment and potential solutions. 5th International High Manganese Steel Conference 2022, online, Linz, Austria (2022)
Liu, C.; Roters, F.; Raabe, D.: Finite strain crystal plasticity-phase field modeling of deformation twinning and dislocation slip interaction in hexagonal materials. 18th European Mechanics of Materials Conference, online, Oxford, UK (2022)
Ma, Y.; Villanova, J.; Requena, G.; Raabe, D.: Understanding the physical-chemical phenomena in green steel production using synchrotron X-ray techniques. European Synchrotron Radiation Facility User Meeting 2022, Online (2022)
Liu, C.; Roters, F.; Raabe, D.: Finite strain crystal plasticity-phase field modeling of twin, dislocation, and grain boundary interactions. 19th International Conference on Strength of Materials ICSMA, Metz, France (2022)
Liu, C.; Shanthraj, P.; Davis, A.; Fellowes, J.; Prangnell, P.; Raabe, D.: Chemo-mechanical phase-field model for two-sublattice phases: phase precipitation in Al–Zn–Mg–Cu alloys. 19th International Conference on Strength of Materials ICSMA, Metz, France (2022)
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
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
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…