Rusitzka, A. K.; Stephenson, L.; Gremer, L.; Raabe, D.; Willbold, D.; Gault, B.: Getting insights to Alzheimer‘s disease by atom probe tomography. 6th International caesar conference, Overcoming Barriers — atomic-resolution and beyond: advances in molecular electron microscopy, Bonn, Germany (2017)
Konijnenberg, P. J.; An, D.; Stechmann, G.; Zaefferer, S.; Raabe, D.: Recent Developments in the Analysis of Microstructures by 3D-EBSD. Symposium: 3D materials characterization at all length scales and its applications to iron and steel, Düsseldorf, Germany (2017)
Peng, Z.; Gault, B.; Raabe, D.: On the Multiple Event Detection in Atom Probe Tomography. Microscopy & Microanalysis 2017 Conference, St. Louis, MO, USA (2017)
Li, Z.; Raabe, D.: Designing novel high-entropy alloys towards superior properties. Frontiers in Materials Processing Applications, Research and Technology (FiMPART'2017), Bordeaux, France (2017)
Liu, C.; Diehl, M.; Shanthraj, P.; Roters, F.; Raabe, D.; Sandlöbes, S.; Dong, J.: An integrated crystal plasticity-phase field approach to locally predict twin formation in magnesium. DGM Meeting, "Herausforderungen bei der skalenübergreifenden Modellierung von Werkstoffen ", Regensburg, Germany (2017)
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)
Max Planck team explains dendrite propagation, paving the way for safer and longer-lasting next-generation batteries. They publish their findings in the journal Nature.
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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