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)
Dehm, G.: Mechanische Eigenschaften in kleinen Dimensionen. Lecture: Vorlesung (3LP), SS 2015, Ruhr-Universität Bochum, Bochum, Germany, May 18, 2015 - May 22, 2015
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
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…
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.
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…