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)
Ahmad, S.; Liebscher, C.; Dehm, G.: To decipher the novel atomic structure of [111] tilt grain boundaries in Al. Material Science and Engineering Congress - MSE 2020, virtual, Darmstadt, Germany (2020)
Devulapalli, V.; Dehm, G.; Liebscher, C.: Unravelling grain boundary structures in Ti thin films using aberration-corrected transmission electron microscopy. MSE Darmdtadt (Virtual), Darmstadt, Germany (2020)
Saood, S.; Liebscher, C.; Dehm, G.: Observing the atomic structure of high angle [111] tilt grain boundaries in Al. Materials Science and Engineering Congress MSE 2020, virtual (2020)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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.