Kontis, P.; Raabe, D.; Gault, B.: The role of systematic characterization on the development of new nickel-based superalloys. Industrial Colloquium - SFB/TR 103 „From Atoms to Turbine Blades“ , Fürth, Germany (2018)
Kürnsteiner, P.; Wilms, M. B.; Weisheit, A.; Jägle, E. A.; Raabe, D.: Preventing the Coarsening of Al3Sc Precipitates by the Formation of a Zr-rich Shell During Laser Metal Deposition. TMS2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Kwiatkowski da Silva, A.; Inden, G.; Ponge, D.; Gault, B.; Raabe, D.: Precipitation of CFCC-TmC Carbides during Tempering at 450°C of a Medium Mn Steel: A Thermodynamic and Kinetic Study Followed by Atom Probe Tomography. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Li, Z.; Raabe, D.: Tuning Phase Transformation in Compositionally Complex Alloys for Superior Mechanical Properties. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Oh, H. S.; Li, Z.; Kim, J. Y.; Ryu, C. W.; Meyer, A.; Tsuchiya, K.; Raabe, D.; Park, E. S.: Phase Stabilization of High Entropy Alloy under Dynamic Forcing Condition. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
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. DPG-Frühjahrstagung der Sektion Kondensierte Materie, Berlin, Germany (2018)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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.