Jentner, R.; Best, J. P.; Kirchlechner, C.; Dehm, G.: Challenges in the phase identification of steels using unsupervised clustering of nanoindentation data. Nanomechanical Testing in Materials Research and Development VIII, Split, Croatia (2022)
Pemma, S.; Brink, T.; Janisch, R.; Dehm, G.: Stress driven grain boundary migration for different complexions of a Cu tilt grain boundary. Materials Science and Engineering Congress 2022, Darmstadt, Germany (2022)
Dehm, G.: New insights on the atomic grain boundary structure in pure and alloyed Cu and Fe. 10th International Workshop on Interfaces, Santiago de Compostele, Spain (2022)
Dehm, G.: Structure and properties of tilt grain boundaries in Cu thin films. Graduiertenkollegs GRK1896 „In situ microsopy with electrons, X-rays and scanning probes: Abschlusssymposium, Erlangen, Germany (2022)
Dehm, G.: Grain Boundary Phases (Complexions) in Pure and Alloyed Cu: Insights from Advanced Electron Microscopy and Molecular Dynamics. Gordon Research Conference Structural Nanomaterials, Les Diablerets, Switzerland (2022)
Dehm, G.: Grain boundary phase transitions in pure and alloyed Cu. Possibilities and Limitations of Quantitative Materials Modeling and Characterization 2022, Berndkastel-Kues, Germany (2022)
Dehm, G.; Rao, J.; Duarte, M. J.: Impact of Hydrogen on Dislocation Nucleation and Strength in bcc Fe–Cr alloys. TMS 2022 Annual Meeting, Symposium “Mechanical Behavior at the Nanoscale VI”, Anaheim, CA, USA (2022)
Hosseinabadi, R.; Best, J. P.; Kirchlechner, C.; Dehm, G.: Impact of an incoherent twin boundary on the mechanical response of Cu bi-crystalline micropillars. 11th European Solid Mechanics Conference - ESMC 2022, Galway, Ireland (2022)
Pemma, S.; Janisch, R.; Dehm, G.; Brink, T.: Atomistic simulation study of grain boundary migration for different complexions in copper. DPG-Tagung, Virtual (2021)
Brognara, A.; Best, J. P.; Djemia, P.; Faurie, D.; Dehm, G.; Ghidelli, M.: Toward engineered thin film metallic glasses with large mechanical properties: effect of composition and nanostructure. Seminar at Laboratoire des Sciences des Procédés et des Matériaux (LSPM), Paris Nord University, Paris, France (2021)
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
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
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…