Tasan, C. C.; Diehl, M.; Yan, D.; Zambaldi, C.; Shanthraj, P.; Roters, F.; Raabe, D.: Integrated experimental and simulation analysis of stress and strain partitioning in dual phase steel. 17th U.S. National Congress on Theoretical and Applied Mechanics Michigan State University, East Lansing, MI, USA (2014)
Tasan, C. C.; Jeannin, O.; Barbier, D.; Morsdorf, L.; Wang, M.; Ponge, D.; Raabe, D.: In-situ characterization of martensite plasticity by high resolution microstructure and microstrain mapping. ICOMAT 2014, International Conference on Martensitic Transformations 2014, Bilbao, Spain (2014)
Wang, M.; Tasan, C. C.; Ponge, D.; Kostka, A.; Raabe, D.: Deformation micro-mechanisms in medium-Mn TRIP-maraging steel. 2nd International Conference on High Manganese Steel, HMnS 2014, Aachen, Germany (2014)
Springer, H.; Belde, M.; Raabe, D.: Bulk combinatorial design of high strength martensitic steels utilising austenite reversion and cryogenic strengthening. Thermec Conference, Las Vegas, NV, USA (2013)
Tasan, C. C.; Springer, H.; Lai, M.; Zhang, J.-I.; Raabe, D.: Influence of oxygen on the deformation behavior of Ti–Nb–Ta–Zr alloys. Thermec 2013, Las Vegas, NV, USA (2013)
Haghighat, S. M. H.; Eggeler, G.; Raabe, D.: Discrete Dislocation Dynamics Study of Creep Anisotropy in Single Crystal Ni Base Superalloys. MRS Fall Meeting, Bosten, USA (2013)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
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.
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…