Kanjilal, A.; Rehman, U.; Best, J. P.; Dehm, G.: Role of temperature on micromechanical fracture behavior of Laves phase in Mg–Al–Ca ternary alloy. FEMS Euromat 2023, Frankfurt am Main, Germany (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)
Dehm, G.: Grain boundary phases in metallic materials: Structure, stability and properties. MiFuN III - Microstructural Functionality at the Nanoscale, Venice, Italy (2023)
Dehm, G.: On the interplay between grain boundary complexions and chemical composition for fcc metals. Possibilities and Limitations of Quantitative Materials Modeling and Characterization 2023, Bernkastel-Kues, Germany (2023)
Brink, T.; Bhat, M. K.; Best, J. P.; Dehm, G.: Grain-boundary segregation effects on bicrystal Cu pillar compression. DPG Spring Meeting, Dresden, Germany (2023)
Kanjilal, A.; Rehman, U.; Best, J. P.; Dehm, G.: Microscale fracture behavior of Laves phases in the Mg–Ca–Al ternary alloy system. 86. Annual Meeting of DPG and DPG-Frühjahrstagung (DPG Spring Meeting) of the Matter and Cosmos Section (SMuK), Dresden, Germany (2023)
Kanjilal, A.; Rehman, U.; Best, J. P.; Dehm, G.: Microscale fracture behavior of Laves phases in the Mg–Ca–Al ternary alloy system. DPG-Frühjahrstagung (DPG Spring Meeting) of the Condensed Matter Section (SKM), Dresden, Germany (2023)
Pemma, S.; Janisch, R.; Dehm, G.; Brink, T.: Deformation mechanism of complexions in a Cu grain boundary under shear. FEMS EUROMAT 2023, Frankfurt am Main, Germany (2023)
Pemma, S.; Janisch, R.; Dehm, G.; Brink, T.: Disconnection activation in complexions of a Cu grain boundary under shear. 19th International Conference on Diffusion in Solids and Liquids (DSL-2023), Heraklion, Greece (2023)
Brognara, A.; Best, J. P.; Djemia, P.; Faurie, D.; Dehm, G.; Ghidelli, M.: Effect of composition and nanolayering on mechanical properties of Zr100-xCux thin film metallic glasses. Talk at Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium (2022)
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.