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
A novel design with independent tip and sample heating is developed to characterize materials at high temperatures. This design is realized by modifying a displacement controlled room temperature micro straining rig with addition of two miniature hot stages.
Many important phenomena occurring in polycrystalline materials under large plastic strain, like microstructure, deformation localization and in-grain texture evolution can be predicted by high-resolution modeling of crystals. Unfortunately, the simulation mesh gets distorted during the deformation because of the heterogeneity of the plastic…
In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial…
The project HyWay aims to promote the design of advanced materials that maintain outstanding mechanical properties while mitigating the impact of hydrogen by developing flexible, efficient tools for multiscale material modelling and characterization. These efficient material assessment suites integrate data-driven approaches, advanced…
The Atom Probe Tomography group in the Microstructure Physics and Alloy Design department is developing integrated protocols for ultra-high vacuum cryogenic specimen transfer between platforms without exposure to atmospheric contamination.
Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials.