Archie, F. M. F.: Damage nucleation in DP-steels: experimental characterization of the contributing microstructural parameters. Dissertation, Fakultät für Georessourcen und Materialtechnik, RWTH Aachen (2018)
Choi, W. S.: Deformation mechanisms and the role of interfaces in face-centered cubic Fe-Mn-C micro-pillars. Dissertation, RWTH Aachen, Aachen, Germany (2018)
Elhami, N. N.: Influence of strain path changes during cup drawing on the twinning activity in TWIP steels investigated by ECCI. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Morsdorf, L.: Fundamentals of ferrous low-carbon lath martensite: from the as-quenched, to tempered and deformed states. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Stechmann, G.: A Study on the Microstructure Formation Mechanisms and Functional Properties of CdTe Thin Film Solar Cells Using Correlative Electron Microscopy and Atomistic Simulations. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Stricker, M.: Die Übertragung von mikrostrukturellen Eigenschaften aus der diskreten Versetzungsdynamik in Kontinuumsbeschreibungen. Dissertation, KIT, Karlsruhe, Karlsruhe, Germany (2017)
Bowden, D. J.: Assessment of Co-free hardfacing stainless steel alloys for nuclear applications. Dissertation, University Manchester, Manchester, UK (2017)
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)
Lai, M.: Experimental-theoretical study of the interplay between deformation mechanisms and secondary phases in metastable β titanium alloys. Dissertation, RWTH Aachen, Aachen, Germany (2016)
Neddermann, P.: Martensitic Stainless Steel: Evolution of Austenite during Low Temperature Annealing and Design of Press Hardening Alloys. Dissertation, RWTH Aachen, Aachen, Germany (2016)
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…
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…
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.