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)
Tsybenko, H.; Dehm, G.; Brinckmann, S.: Deformation and chemical evolution during tribology in cementite. Materials Science and Engineering Congress (MSE) 2020, online, Darmstadt, Germany (2020)
Hosseinabadi, R.; Dehm, G.; Kirchlechner, C.: Size effect in bi-crystalline Cu micropillars with a coherent twin boundary. DGM Arbeitskreistreffen Rasterkraftmikroskopie und nanomechanische Methoden, online (2020)
Duarte, M. J.; Fang, X.; Rao, J.; Dehm, G.: Hydrogen-microstructure interactions at small scale by in-situ nanoindentation during hydrogen charging. Nanobrücken 2020: A nanomechanical Testing Conference, Düsseldorf, Germany (2020)
Dehm, G.: Probing the mechanics of dislocation - grain boundary interactions: Lessons learned from in situ microcompression experiments. 14th International Conference on Local Mechanical Properties 2019 (plenary), Prague, Czech Republic (2019)
Jeong, J.; Dehm, G.; Liebscher, C.: Advances in automatic TEM based orientation mapping with precession electron diffraction. KSM Annual Fall Conference 2019, Gyeongju, South Korea (2019)
Stein, F.; Luo, W.; Kirchlechner, C.; Dehm, G.: Micromechanics of Laves Phases: Strength, Fracture Toughness, and Hardness as Function of Composition and Crystal Structure. Joint EPRI-123 HiMAT Conference on Advances in High Temperature Materials, Nagasaki, Japan (2019)
Dehm, G.: Do we understand the microstructure and properties of materials: New insights by advanced microscopy techniques. Metallurgical Engineering and Materials Science Department, Indian Institute of Technology, Mumbai, India (2019)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
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.