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
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…