Springer, H.; Tasan, C. C.; Raabe, D.: A novel roll-bonding methodology for the cross-scale analysis of phase properties and interactions in multiphase structural materials. International Journal of Materials Research 106 (1), pp. 3 - 14 (2015)
Jägle, E. A.; Choi, P.-P.; Raabe, D.: The maximum separation cluster analysis algorithm for atom-probe tomography: Parameter determination and accuracy. Microscopy and Microanalysis 20 (6), pp. 1662 - 1671 (2014)
Tasan, C. C.; Hoefnagels, J. P.M.; Diehl, M.; Yan, D.; Roters, F.; Raabe, D.: Strain localization and damage in dual phase steels investigated by coupled in-situ deformation experiments and crystal plasticity simulations. International Journal of Plasticity 63, pp. 198 - 210 (2014)
Zhang, H.; Pradeep, K. G.; Mandal, S.; Ponge, D.; Raabe, D.: New insights into the austenitization process of low-alloyed hypereutectoid steels: Nucleation analysis of strain-induced austenite formation. Acta Materialia 80, pp. 296 - 308 (2014)
Wang, M.; Tasan, C. C.; Ponge, D.; Kostka, A.; Raabe, D.: Smaller is less stable: Size effects on twinning vs. transformation of reverted austenite in TRIP-maraging steels. Acta Materialia 79, pp. 268 - 281 (2014)
Jägle, E. A.; Choi, P.-P.; Van Humbeeck, J.; Raabe, D.: Precipitation and austenite reversion behavior of a maraging steel produced by selective laser melting. Journal of Materials Research 29 (17), pp. 2072 - 2079 (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
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.