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Neelakantan, L.; Eggeler, G. F.; Hassel, A. W.: Investigations to understand the mechanisms during electropolishing of NiTi. 6th International Symposium on Electrochemical Micro & Nanosystem Technologies, Bonn, Germany (2006)
Neelakantan, L.; Eggeler, G. F.; Hassel, A. W.: Electropolishing of NiTi - Insight its mechanism. 58th Annual Meeting of the International Society of Electrochemistry, Banff, Canada (2007)
Hariharan, A.: On the interfacial defect formation mechanism during laser additive manufac-turing of polycrystalline superalloys. Dissertation, Ruhr-Universität Bochum (2019)
Hariharan, A.: On the interfacial defect formation mechanism during laser additive manufacturing of polycrystalline superalloys. Dissertation, Ruhr-Universität Bochum (2019)
Luo, W.: Mechanical properties of the cubic and hexagonal NbCo2 Laves phases studied by micromechanical testing. Dissertation, Ruhr-Universität Bochum (2019)
Wu , X.: Elementary deformation processes during low temperature and high stress creep of Ni-base single crystal superalloys. Dissertation, Ruhr-University Bochum, Bochum, Germany (2016)
Aghajani, A.: Evolution of microstructure during long-term creep of a tempered martensite ferritic steel. Dissertation, Ruhr-University Bochum, Bochum (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
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…
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…
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…