Marx, V. M.; Kirchlechner, C.; Zizak, I.; Cordill, M. J.; Dehm, G.: Adhesion Behavior of Cu–Cr Thin Films on Polyimide Substrate. TMS 2013: 142nd Annual Meeting & Exhibition, San Antonio, TX, USA (2013)
Philippi, B.; Schießl, A.; Schingale, A.; Dehm, G.: Micromechanical investigation of solder joints for automotive microelectronics. Nano- and Micromechanical Testing in Materials Research and Development IV, Olhão Algarve, Portugal (2013)
Harzer, T. P.; Dehm, G.: Microstructural studies of Cu–Cr thin film structures grown by molecular beam epitaxy using advanced transmission electron microscopy. Macan Theromodynamics Workshop, Istanbul, Turkey (2012)
Marx, V. M.; Kirchlechner, C.; Zizak, I.; Dehm, G.; Cordill, M. J.: In-situ fracture study of thin Cu films on polyimide substrate. GDRi MECANO General Meeting 2012, Ecole de Mines, Paris, France (2012)
Eiper, E.; Martinschitz, K. J.; Dehm, G.; Kečkéš, J.: Size effect in metallic thin films characterized by low-temperature X-ray diffraction. Gordon Research Conference on thin film & smallscale mechanical behavior , Colby College Waterville, Maine, USA (2006)
Rester, M.; Kiener, D.; Kreuzer, H. G.M.; Dehm, G.; Motz, C.: Microstructural investigation of the deformation zone below nanoindents in copper, silver and nickel. Hysitron Workshop and Usermeeting, München, Germany (2006)
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.