Sandim, M. J. R.; Tytko, D.; Kostka, A.; Choi, P.; Awaji, S.; Watanabe, K.; Raabe, D.: Grain boundary segregation in a bronze-route Nb3Sn superconducting wire studied by atom probe tomography. Superconductor Science and Technology 26, pp. 055008-1 - 055008-7 (2013)
Siboni, N. H.; Raabe, D.; Varnik, F.: Maintaining the equipartition theorem in small heterogeneous molecular dynamics ensembles. Physical Review E 87 (3), pp. 030101-1 - 030101-4 (2013)
Nematollahi, A.; von Pezold, J.; Neugebauer, J.; Raabe, D.: Thermodynamics of carbon solubility in ferrite and vacancy formation in cementite in strained pearlite. Acta Materialia 61 (5), pp. 1773 - 1784 (2013)
Seol, J.-B.; Raabe, D.; Choi, P.; Park, H. S.; Kwak, J. H.; Park, C. G.: Direct evidence for the formation of ordered carbides in a ferrite based low-density Fe–Mn–Al–C alloy studied by transmission electron microscopy and atom probe tomography. Scripta Materialia 68 (6), pp. 348 - 353 (2013)
Titrian, H.; Aydin, U.; Friák, M.; Ma, D.; Raabe, D.; Neugebauer, J.: Self-consistent scale-bridging approach to compute the elasticity of multi-phase polycrystalline materials. Materials Research Society Symposia Proceedings 1524, pp. 17 - 23 (2013)
Gutiérrez-Urrutia, I.; Raabe, D.: Influence of Al content and precipitation state on the mechanical behavior of austenitic high-Mn low-density steels. Scripta Materialia 68 (6), pp. 343 - 347 (2013)
Pinto de Siqueira, R.; Sandim, H. R. Z.; Raabe, D.: Particle Stimulated Nucleation in Coarse-Grained Ferritic Stainless Steel. Metallurgical and Materials Transactions A 44 (1), pp. 469 - 478 (2013)
Woldemedhin, M. T.; Raabe, D.; Hassel, A. W.: Characterization of thin anodic oxides of Ti–Nb alloys by electrochemical impedance spectroscopy. Electrochimica Acta 82, pp. 324 - 332 (2012)
Cojocaru-Mirédin, O.; Choi, P.; Wuerz, R.; Raabe, D.: Exploring the p-n junction region in Cu(In,Ga)Se2 thin-film solar cells at the nanometer-scale. Applied Physics Letters 101 (18), pp. 181603-1 - 181603-5 (2012)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
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.