Hengge, K. A.; Scheu, C.: Novel electrodes for polymer based fuel cells. The 18th Israel Materials Engineering Conference (IMEC18), Dead Sea, Israel (2018)
Scheu, C.: 3D Nb3O7(OH) Nanoarrays – Structure, Stability and Functional Properties. Talk at Felix-Bloch-Institut für Festkörperphysik, Universität Leipzig, Leipzig, Germany (2018)
Hieke, S. W.; Willinger, M. G.; Wang, Z.-J.; Richter, G.; Dehm, G.; Scheu, C.: Evolution of faceted voids and fingering instabilities in a model thin film system - Insights by in-situ environmental scanning electron microscopy. Symposium - In situ Microscopy with Electrons, X‐rays and Scanning Probes, Universität Erlangen‐Nürnberg, Erlangen, Germany (2017)
Scheu, C.: Thermal stability and phase transformation of nanostructured Nb3O7(OH) photocatalyst. Material Science & Technology (MST), Salt Lake City, UT, USA (2017)
Zhang, S.; Diehl, L.; Lotsch, B. V.; Scheu, C.: In-situ heating study on the growth of NiOx nanoparticles on photocatalytic supports. International GRK 1896 Satellite Symposium “In Situ Microscopy with Electrons, X-rays and Scanning Probes, Erlangen, Germany (2017)
Betzler, S. B.; Scheu, C.: Nb3O7(OH) – a promising candidate for photocatalyst: synthesis, nanostructure and functionality. International Conference on Functional Nanomaterials and Nanodevices, Budapest, Hungary (2017)
Garzón-Manjón, A.; Zahn, G.; Kuchshaus, C.; Ludwig, A.; Scheu, C.: Observation of the Structural Transformation of Multinary Nanoparticles by In-situ Transmission Electron Microscopy. 13th Multinational Congress on Microscopy (MCM2017), Rovinj, Croatia (2017)
Scheu, C.: Structural and functional properties of Nb3O7(OH) nanoarrays and their modification via doping and thermal annealing. Talk at Institut für Werkstofftechnik, Technische Universität Ilmenau, Ilmenau, Gemany (2017)
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.
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.