Brink, T.; Milanese, E.; Frérot, L.; Molinari, J.-F.: Simulation of adhesive wear mechanisms at the nanoscale and an approach towards mesoscale models. MSE Congress, Darmstadt, Germany (2022)
Frommeyer, L.; Brink, T.; Dehm, G.; Liebscher, C.: Atomic scale observations of Ag segregation in a high angle grain boundary in Cu. PICO 2022, Kasteel Vaalsbroek, The Netherlands (2022)
Frommeyer, L.; Brink, T.; Freitas, R.; Frolov, T.; Dehm, G.; Liebscher, C.: Characterization of the atomic structure of grain boundary phases in pure Cu. Sixth Conference on Frontiers of Aberration Corrected Electron Microscopy PICO 2021, vitual, Kasteel Vaalsbroek, The Netherlands (2021)
Brink, T.: Thermodynamics. Lecture: Lecture on Thermodynamics, Max Planck Institut für Eisenforschung (demnächst Max Planck Institute for Sustainable Materials), 4 lectures à 2 h, Düsseldorf, Germany, May 14, 2024 - June 11, 2024
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.