Scheu, C.: Grain growth and dewetting of thin Al films on (0001) Al2O3 substrates. 3 Phase, Interface, Component Systems (PICS), Centre Interdisciplinaire de Nanoscience de Marseille (CINaM), Marseille, France (accepted)
Scheu, C.: In-situ Transmission Electron Microscopy Observation of Heat-Induced Structural Changes of 3D Nb3O(OH) Networks. Electronic Materials and Applications 2017 (EMA), Orlando, FL, USA (2017)
Scheu, C.: Insights into structural and functional properties of Nb3O7(OH) and TiO2 nanoarrays. European Materials Research Society’s (EMRS) Fall Meeting, Warsaw, Poland (2016)
Scheu, C.: Transmission electron microscopy – a versatile tool to study the microstructure of HT-PEMFC. Materials Science 2016, Atlanta, GA, USA (2016)
Scheu, C.: Insights into structural and functional properties of nano-structured electrodes for energy and fuel generating devices. Talk at Helmholtz‐Zentrum Geesthacht, Geesthacht, Germany (2016)
Scheu, C.: Correlative STEM & Atom Probe Tomography (ATP): Insights in the k-carbide/austenite interface. Workshop on “New trends in electron microscopy”, Ringberg Castle, Kreuth am Tegernsee, Germany (2016)
Hengge, K.; Heinzl, C.; Perchthaler, M.; Scheu, C.: Insights into degradation processes in WO3-x based anodes of HT-PEMFCs via electron microscopic techniques. Fuel Cells Science and Technology 2016 , Glasgow, Scotland, UK (2016)
Folger, A.; Wisnet, A.; Scheu, C.: Defects in as-grown vs. annealed rutile titania nanowires and their effect on properties. EMC 2016, 16th European Microscopy Congress, Lyon, France (2016)
Hengge, K.; Heinzl, C.; Perchthaler, M.; Welsch, M. T.; Scheu, C.: Template-free synthesized high surface area 3D networks of Pt on WO3-x – a promising alternative for H2 oxidation in fuel cell application. 2016 MRS Fall Meeting, Boston, MA, USA (2016)
Hieke, S. W.; Dehm, G.; Scheu, C.: Investigation of solid state dewetting phenomena of epitaxial Al thin films on sapphire using electron microscopy. The 16th European Microscopy Congress (EMC 2016), Lyon, France (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
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…
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.