Steinmetz, D.: A constitutive model of twin nucleation and deformation twinning in High-Manganese Austenitic TWIP steels. Dissertation, RWTH Aachen, Aachen, Germany (2013)
Takahashi, T.: On the growth and mechanical properties of non-oxide perovskites and the spontaneous growth of soft metal nanowhiskers. Dissertation, RWTH Aachen, Aachen, Germany (2013)
Hostert, C.: Towards designing elastic and magnetic properties of Co-based thin film metallic glasses. Dissertation, RWTH Aachen, Aachen, Germany (2012)
Britton, B.: Measurement of residual elastic strain and lattice rotations with high resolution electron backscatter diffraction. Dissertation, Oxford University, Oxford, UK (2011)
Song, J.: Microstructure and properties of interfaces formed by explosion cladding of Titanium to low Carbon steel. Dissertation, Ruhr-University Bochum, Bochum, Germany (2011)
Voß, S.: Mechanische Eigenschaften von Laves-Phasen in Abhängigkeit von Kristallstruktur und Zusammensetzung am Beispiel der Systeme Fe–Nb–Al und Co–Nb. Dissertation, RWTH Aachen, Aachen, Germany (2011)
Springer, H.: Fundamental Research into the Role of Intermetallic Phases in Joining of Aluminium Alloys to Steel. Dissertation, Ruhr-University Bochum, Bochum, Germany (2011)
Demir, E.: Constitutive modeling of fcc single crystals and experimental study of mechanical size effects. Dissertation, RWTH Aachen, Aachen, Germany (2010)
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…
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.
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.