Ma, D.; Friák, M.; von Pezold, J.; Raabe, D.; Neugebauer, J.: Computationally efficient and quantitatively accurate multiscale simulation of solid-solution strengthening by ab initio calculation. Acta Materialia 85, S. 53 - 66 (2015)
Tytko, D.; Choi, P.-P.; Raabe, D.: Thermal dissolution mechanisms of AlN/CrN hard coating superlattices studied by atom probe tomography and transmission electron microscopy. Acta Materialia 85, S. 32 - 41 (2015)
Li, Y.; Ponge, D.; Choi, P.-P.; Raabe, D.: Segregation of boron at prior austenite grain boundaries in a quenched martensitic steel studied by atom probe tomography. Scripta Materialia 96, S. 13 - 16 (2015)
Kim, J.-K.; Sandlöbes, S.; Raabe, D.: On the room temperature deformation mechanisms of a Mg–Y–Zn alloy with long period stacking ordered structures. Acta Materialia 82, S. 414 - 423 (2015)
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), S. 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), S. 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, S. 198 - 210 (2014)
Wissenschaftler des Max-Planck-Instituts für Eisenforschung entwickeln ein neues maschinelles Lernmodell für korrosionsresistente Legierungen. Und veröffentlichen ihre Ergebnisse in der Fachzeitschrift Science Advances
Düsseldorfer Max-Planck-Wissenschaftler diskutieren den Einsatz künstlicher Intelligenz in der Materialwissenschaft und veröffentlichen Review-Artikel in der Fachzeitschrift Nature Computational Science