Dehm, G.; Liebscher, C.: In situ TEM study of deformation and phase transformation mechanisms in chemically complex alloys. Symposium In-situ & Environmental Microscopy, 20th International Microscopy Congress, Busan, Korea (2023)
Brink, T.; Langenohl, L.; Ahmad, S.; Liebscher, C.; Dehm, G.: Atomistic Modeling of the Thermodynamics of Grain Boundaries in fcc Metals. 19th International Conference on Diffusion in Solids and Liquids, Crete, Greece (2023)
Brink, T.; Frommeyer, L.; Freitas, R.; Frolov, T.; Pemma, S.; Liebscher, C.; Dehm, G.: Diffusionless congruent grain boundary phase transitions in metals: Simulation and experimental imaging. 2021 Fall Meeting of the European Materials Research
Society
, Virtual (2021)
Frommeyer, L.; Brink, T.; Freitas, R.; Frolov, T.; Dehm, G.; Liebscher, C.: Congruent grain boundary phase transformations revealed by STEM in pure copper. Microscopy conference Joint Meeting of Dreiländertagungn & Multinational Congress on Microscopy MC 2021, virtual, Vienna, Austria (2021)
Liebscher, C.: How do grain boundaries transform in metallic alloys? Institute of Material Physics, Westfälische Wilhelms-Universität Münster, Online Colloqium, Münster, Germany (2021)
Liebscher, C.; Lu, W.; Dehm, G.; Raabe, D.; Li, Z.: Complex phase transformation pathways in high entropy alloys explored by in situ S/TEM. Third International Conference on High Entropy Materials, Berlin, Germany (2020)
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.