Park, S. J.; Han, H. N.; Oh, K. H.; Raabe, D.; Kim, J. K.: Finite element simulation of grain interaction and orientation fragmentation during plastic deformation of BCC metals. Proc. ICOTOM 13, pp. 371 - 376 (2002)
Raabe, D.: Cellular automata in materials science with particular reference to recrystallization simulation. Annual Review of Materials Research 32, pp. 53 - 76 (2002)
Raabe, D.; Roters, F.; Zhao, Z.: Texture component crystal plasticity finite element method for physically-based metal forming simulations including texture update. Proc. 8th Int. Conf. on Aluminium Alloys, pp. 31 - 36 (2002)
Raabe, D.; Zhao, Z.; Mao, W.: On the dependence of in-grain subdivision and deformation texture of aluminium on grain interaction. Acta Materialia 50, pp. 4379 - 4394 (2002)
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)
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
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…