Dehm, G.: Atomic resolution interface study of VN and Cu films on MgO using Cs corrected TEM. Microscopy Conference MC 2013, Regensburg, Germany (2013)
Dehm, G.: Struktur und Nano-/Mikromechanik von Materialien. Vorstandssitzung des Stahlinstituts VDEh und der Wirtschaftsvereinigung Stahl, Düsseldorf, Germany (2013)
Kirchlechner, C.; Liegl, W.; Motz, C.; Dehm, G.: X-ray μLaue: A novel view on fatigue damage at the micron scale. ECI on Nanomechanical Testing 2013, Olhão (Algarve), Portugal (2013)
Kirchlechner, C.; Motz, C.; Dehm, G.: A novel view on fatigue damage at the micron scale by X-ray µLaue diffraction. GDRi CNRS MECANO General Meeting on the Mechanics of Nano-Objects, MPIE, Düsseldorf, Germany (2013)
Marx, V. M.; Kirchlechner, C.; Cordill, M. J.; Dehm, G.: Deformation behavior of a Cr interlayer buried under Cu films on polyimide. GDRi CNRS MECANO General Meeting on the Mechanics of Nano-Objects, MPIE, Düsseldorf, Germany (2013)
Dehm, G.: Prospects and experimental constraints of nano/micro-mechanical testing in materials science. GDRiCNRSMecano General Meeting, Ecole des Mines, Paris, France (2012)
Rashkova, B.; Moser, G.; Felber, H.; Grosinger, W.; Zhang, Z.; Motz, C.; Dehm, G.: A Novel Preparation Route to Obtain Micro-Bending Beams for In-situ TEM Studies. 9th Multinational Microscopy Conference 2009, Institute for Electron Microscopy Graz University of Technology , Graz, Austria (2009)
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
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.