Pizzutilo, E.: Towards On-Site Production of Hydrogen Peroxide with Gold-Palladium catalysts in Electrocatalysis and Heterogeneous Catalysis. Dissertation, Ruhr-Universität Bochum, Bochum, Germany (2017)
Philippi, B.: Micromechanical characterization of lead-free solder and its individual microstructure elements. Dissertation, Fakultät für Maschnenbau, RUB, Bochum, Germany (2016)
Marx, V. M.: The mechanical behavior of thin metallic films on flexible polymer substrate. Dissertation, Ruhr-Universität Bochum, Bochum, Germany (2016)
Imrich, P. J.; Dehm, G.; Clemens, H. J.: TEM Investigations on Interactions of Dislocations with Boundaries. Dissertation, Department of Physical Metallurgy and Materials Testing, Montanuniversität Leoben, Franz-Josef Strasse 18, 8700 Leoben, Austria, Leoben, Austria (2015)
Völker, B.: Investigation of interface properties of barrier metals on dielectric substrates. Dissertation, Department of Physical Metallurgy and Materials Testing, Montanuniversität Leoben, Franz-Josef Strasse 18, 8700, Leoben, Austria (2014)
Wimmer, A. C.: Plasticity and fatigue of miniaturized Cu structures. Dissertation, Department of Physical Metallurgy and Materials Testing, Montanuniversität Leoben, Franz-Josef Strasse 18, 8700, Leoben, Austria (2014)
Wetegrove, M.; Duarte, M. J.; Taube, K.; Rohloff, M.; Gopalan, H.; Scheu, C.; Dehm, G.; Kruth, A.: Preventing Hydrogen Embrittlement: The Role of Barrier Coatings for the Hydrogen Economy, Hydrogen 4 (2 Ed.), pp. 307 - 322 (2023)
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 general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…
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…