Rao, J.: Hydrogen effects on the mechanical behaviour of FeCr alloys investigated by in-situ nanoindentation. Dissertation, Ruhr-Universität Bochum (2023)
Jentner, R.: Phase identification and micromechanical characterization of an advanced high-strength low-alloy steel. Dissertation, Ruhr-Universität Bochum (2023)
Ahmad, S.; Mayer, J.: Fundamental investigation of the atomic structures of [111] tilt grain boundaries, their defects and segregation behaviour in pure and alloyed Al. Dissertation, Ruhr-Universität Bochum (2023)
Oellers, T.: Development of combinatorial methods to tailor electrical and mechanical properties of Cu-based thin-film structures. Dissertation, Ruhr-Universität Bochum (2022)
Distl, B.: Phase equilibria and phase transformations of Ti–Al–X (X=Nb, Mo, W) alloys for high-temperature structural applications between 700 and 1300 °C. Dissertation, Ruhr-Universität Bochum, Fakultät für Maschinenbau, Germany (2022)
Wolff-Goodrich, S.: Development of AlCrFeNiTi Compositionally Complex Alloys for High Temperature Structural Applications. Dissertation, Ruhr-Universität Bochum (2021)
Tian, C.: On the damage initiation in dual phase steels: Quantitative insights from in situ micromechanics. Dissertation, Ruhr-Universität Bochum (2021)
Evertz, S.: Quantum mechanically guided design of mechanical properties and topology of metallic glasses. Dissertation, Fakultät für Georessourcen und Materialtechnik, RWTH Aachen (2020)
Li, J.: Probing dislocation nucleation in grains and at Ʃ3 twin boundaries of Cu alloys by nanoindentation. Dissertation, Ruhr-Universität Bochum (2020)
Arigela, V. G.: Development and application of a high-temperature micromechanics stage with a novel temperature measurement approach. Dissertation, Ruhr-Universität Bochum (2020)
Luo, W.: Mechanical properties of the cubic and hexagonal NbCo2 Laves phases studied by micromechanical testing. Dissertation, Ruhr-Universität Bochum (2019)
Pizzutilo, E.: Towards On-Site Production of Hydrogen Peroxide with Gold-Palladium catalysts in Electrocatalysis and Heterogeneous Catalysis. Dissertation, Ruhr-Universität Bochum, Bochum, Germany (2017)
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
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…
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.