Kobayashi, S.; Zaefferer, S.; Schneider, A.; Raabe, D.; Frommeyer, G.: Slip system determination by rolling texture measurements around the strength peak temperature in a Fe3Al-based alloy. Materials Science and Engineering A 387–389, pp. 950 - 954 (2004)
Ma, A.; Roters, F.; Raabe, D.: Numerical study of textures and Lankford values for FCC polycrystals by use of a modified Taylor model. Computational Materials Science 29, 3, pp. 259 - 395 (2004)
Raabe, D.: Overview on the Lattice Boltzmann Method for Nano- and Microscale Fluid Dynamics in Materials Science and Engineering. Modelling and Simulation in Materials Science and Engineering 12, pp. R13 - R46 (2004)
Raabe, D.; Ge, J.: Experimental study on the thermal stability of Cr filaments in a Cu–Cr–Ag in situ composite. Scripta Materialia 51, pp. 915 - 920 (2004)
Raabe, D.; Roters, F.: Using texture components in crystal plasticity finite element simulations. International Journal of Plasticity 20, pp. 339 - 361 (2004)
Sandim, H. R. Z.; Sandim, M. J. R.; Bernardi, H. H.; Lins, J. F. C.; Raabe, D.: Annealing effects on the microstructure and texture of a multifilamentary Cu–Nb composite wire. Scripta Materialia 51, pp. 1099 - 1104 (2004)
Lima, E. B. F.; Pyzalla, A. R.; Reimers, W.; Kuo, J.-C.; Raabe, D.: Mosaic Size Distributions in an Aluminum Bi-crystal Deformed by Channel Die Plane Strain Compression. Journal of Neutron Research 11 (4), pp. 209 - 214 (2003)
Zaefferer, S.; Kuo, J. C.; Zhao, Z.; Winning, M.; Raabe, D.: On the influence of the grain boundary misorientation on the plastic deformation of aluminum bicrystals. Acta Materialia 51, pp. 4719 - 4735 (2003)
Raabe, D.: Don’t trust your simulation - Computational materials science on its way to maturity? Advanced Engineering Materials 4 (5), pp. 255 - 267 (2002)
Raabe, D.; Zhao, Z.; Park, S. J.; Roters, F.: Theory of orientation gradients in plastically strained crystals. Acta Materialia 50 (2), pp. 421 - 440 (2002)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science