Raabe, D.; Ponge, D.; Kuzmina, M.; Sandlöbes, S.: Phase transformations at dislocations. Workshop Possibilities and Limitations of Quantitative Materials Modeling and Characterization, Bernkastel, Germany (2015)
Morsdorf, L.; Tasan, C. C.; Ponge, D.; Raabe, D.: Lath martensite transformation, µ-plasticity and tempering reactions: potential TEM aids. Seminar at Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany (2015)
Kuzmina, M.; Herbig, M.; Ponge, D.; Sandlöbes, S.; Raabe, D.: Linear Complexions: Confined Chemical and Structural States at Dislocations in Metallic Alloys. MRS Fall Meeting & Exhibit, Boston, MA, USA (2015)
Tarzimoghadam, Z.; Ponge, D.: Hydrogen Embrittlement and Sour Gas Corrosion in Oil and Gas Industry. Workshop: Hydrogen Embrittlement and Sour Gas Corrosion, Max-Planck-Institut für Eisenforschung, Düsseldorf, Germany (2015)
Herbig, M.; Ponge, D.; Gault, B.; Borchers, C.; Raabe, D.: Segregation and phase transformation at dislocations during aging in a Fe-9%Mn steel studied by correlative TEM-atom probe tomography. MSE 2014, Darmstadt, Germany (2014)
Li, Y.; Ponge, D.; Choi, P.-P.; Raabe, D.: Segregation of boron at prior austenite grain boundaries in a quenched steel studied by atom probe tomography. Atom Probe Tomography & Microscopy 2014, Stuttgart, Germany (2014)
Kuzmina, M.; Ponge, D.; Bleskov, I.; Raabe, D.: Study of equilibrium segregation of Mn and reversion of austenite in tempered medium Mn steels and its influence on impact toughness. 2nd International Conference on High Manganese Steels - HMnS 2014, Aachen, Germany (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)
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.
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…