Roters, F.; Wong, S. L.; Shanthraj, P.; Diehl, M.; Raabe, D.: Thermo mechanically coupled simulation of high manganese TRIP/TWIP Steel. 5th International Conference on Material Modeling, ICMM 5, Rome, Italy (2017)
Raabe, D.; Gault, B.; Yao, M.; Scheu, C.; Liebscher, C.; Herbig, M.: Correlated and simulated electron microscopy and atom probe tomography. Workshop on Possibilities and Limitations of Quantitative Materials Modeling and Characterization 2017, Bernkastel, Germany (2017)
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)
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
Water electrolysis has the potential to become the major technology for the production of the high amount of green hydrogen that is necessary for its widespread application in a decarbonized economy. The bottleneck of this electrochemical reaction is the anodic partial reaction, the oxygen evolution reaction (OER), which is sluggish and hence…