Sachtleber, M.; Zhao, Z.; Raabe, D.: Experimental investigation of plastic grain interaction. Materials Science and Engineering A 336, pp. 81 - 87 (2002)
Juntunen, P.; Raabe, D.; Karjalainen, P.; Kopio, T.; Bolle, G.: Optimizing continuous annealing of IF steels for improving their deep drawability. Metallurgical and Materials Transactions A 32, pp. 1989 - 1995 (2001)
Roters, F.; Raabe, D.; Gottstein, G.: Work hardening in heterogeneous alloys - A microstructural approach based on three internal state variables. Acta Materialia 48 (17), pp. 4181 - 4189 (2000)
Raabe, D.; Becker, R. C.: Coupling of a crystal plasticity finite element model with a probabilistic cellular automaton for simulating primary static recrystallization in aluminum. Modelling and Simulation in Materials Science and Engineering 8, pp. 445 - 462 (2000)
Raabe, D.; Miyake, K.; Takahara, H.: Processing, microstructure, and properties of ternary high-strength Cu–Cr–Ag in situ composites. Material Science and Engineering A 291, pp. 186 - 197 (2000)
Raabe, D.; Mattissen, D.: Experimental investigation and Ginzburg-Landau modeling of the microstructure dependence of superconductivity in Cu–Ag–Nb wires. Acta Materialia 47 (3), pp. 769 - 777 (1999)
Mattissen, D.; Raabe, D.; Heringhaus, F.: Experimental investigation and modeling of the influence of microstructure on the resistive conductivity of a Cu–Ag–Nb in situ composite. Acta Materialia 47, pp. 1627 - 1634 (1999)
Marx, V.; Raabe, D.; Engler, O.; Gottstein, G.: Simulation of the texture evolution during annealing of cold rolled BCC and FCC matals using a cellular automation approach. Textures and Microstructures 28, pp. 211 - 218 (1997)
Raabe, D.: Texture simulation for hot rolling of aluminium by use of a Taylor model considering grain interactions. Acta Metallurgica et Materialia 43 (3), pp. 1023 - 1028 (1995)
Roters, F.; Eisenlohr, P.; Bieler, T. R.; Raabe, D.: Crystal Plasticity Finite Element Methods in Materials Science and Engineering. Wiley-VCH, Weinheim (2010), 197 pp.
Janssens, K. G. F.; Raabe, D.; Kozeschnik, E.; Miodownik, M. A.; Nestler, B.: Computational Materials Engineering – An Introduction to Microstructure Evolution. Academic Press, Elsevier, USA (2007), 360 pp.
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
Grain boundaries are one of the most prominent defects in engineering materials separating different crystallites, which determine their strength, corrosion resistance and failure. Typically, these interfaces are regarded as quasi two-dimensional defects and controlling their properties remains one of the most challenging tasks in materials…
Project A02 of the SFB1394 studies dislocations in crystallographic complex phases and investigates the effect of segregation on the structure and properties of defects in the Mg-Al-Ca System.
The aim of this project is to develop novel nanostructured Fe-Co-Ti-X (X = Si, Ge, Sn) compositionally complex alloys (CCAs) with adjustable magnetic properties by tailoring microstructure and phase constituents through compositional and process tuning. The key aspect of this work is to build a fundamental understanding of the correlation between…
In this project, we aim to achieve an atomic scale understanding about the structure and phase transformation process in the dual-phase high-entropy alloys (HEAs) with transformation induced plasticity (TRIP) effect. Aberration-corrected scanning transmission electron microscopy (TEM) techniques are being applied ...
Grain boundaries are one of the most important constituents of a polycrystalline material and play a crucial role in dictating the properties of a bulk material in service or under processing conditions. Bulk properties of a material like fatigue strength, corrosion, liquid metal embrittlement, and others strongly depend on grain boundary…
This project targets to exploit or develop new methodologies to not only visualize the 3D morphology but also measure chemical distribution of as-synthesized nanostructures using atom probe tomography.