Calcagnotto, M.; Ponge, D.; Adachi, Y.; Raabe, D.: Effect of grain refinement to 1 µm on deformation and fracture mechanisms in ferrite/martensite dual-phase steels. 2nd International Conference on Super-High Strength Steels SHSS, Peschiera del Garda, Italy (2010)
Dmitrieva, O.; Choi, P.; Ponge, D.; Raabe, D.; Gerstl, S. S. A.: Laser-pulsed atom probe studies of a complex maraging steel: Laser pulse energy variation and precipitate analysis. 52nd International Field Emission Symposium IFES 2010, Sydney, Australia (2010)
Ponge, D.; Raabe, D.: Nano-particles and filaments in steels: From understanding to materials design. 52nd International Field Emission Symposium IFES 2010, Sydney, Australia (2010)
Herrera, C.; Ponge, D.; Raabe, D.: Development of a high ductile lean duplex stainless steel. 2nd International Conference on Super-High Strength Steels SHSS, Peschiera del Garda, Italy (2009)
Calcagnotto, M.; Ponge, D.; Raabe, D.: Effect of grain refinement to 1µm on the mechanical properties of dual-phase steels. European Congress and Exhibition on Advanced Materials and Processes (EUROMAT 2009), Glasgow, UK (2009)
Herrera, C.; Ponge, D.; Raabe, D.: Hot workability of 1.4362 duplex stainless steel. Euromat 2009 (European Congress and Exhibition on Advanced Materials and Processes), Glasgow, Scotland, UK (2009)
Calcagnotto, M.; Ponge, D.; Demir, E.; Raabe, D.; Zaefferer, S.: 3D-EBSD Investigation on Orientation Gradients and Geometrically Necessary Dislocations Induced by the Martensitic Phase Transformation in Ultrafine Grained Dual-Phase Steels. Interdisciplinary Symposium on 3D Microscopy, Interlaken, Switzerland (2009)
Calcagnotto, M.; Ponge, D.; Raabe, D.: Mechanical properties of ultrafine and fine grained dual phase steels. MS&T 2008 (Materials Science and Technology), Pittsburgh, PA, USA (2008)
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…