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)
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
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
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.