Scheu, C.; Zhang, S.: Hematite for light induced water splitting – improving efficiency by tuning distribution of Sn dopants at the atomic scale. Karlsruher Werkstoffkolloquium_Digital (2021)
Scheu, C.; Hengge, K. A.: Insights in the stability of Pt/Ru catalyst and the effect for polymer electrolyte membrane fuel cells. Thermec 2021, Online Conference (2021)
Aymerich Armengol, R.; Lim, J.; Ledendecker, M.; Scheu, C.: The devil is in the details: correlating SMSI catalyst encapsulation layers with electrochemical properties. ElecNano9 2020, online, Paris, France (2020)
Scheu, C.: Atomic-scale characterization of complex solid solution nanoparticles using TEM. Workshop on High Entropy Alloy and Complex Solid Solution Nanoparticles for Electrocatalysis, RUB, online, Bochum, Germany (2020)
Scheu, C.: Co-organizer of the International Seminar Series on the Microstructure of Materials (on-line). International Seminar Series on the Microstructure of Materials, online (2020)
Scheu, C.; Hieke, S. W.: How stable are thin Aluminium films: Dewetting phenomena observed by in-situ electron microscopy. Microscopy Conference 2019 (MC2019), Berlin, Germany (2019)
Scheu, C.; Hieke, S. W.: Fundamentals and Applications of Electron Energy-Loss Spectroscopy in a Scanning Transmission Electron Microscope. Universita' Roma Tre Colloquium, Roma, Italy (2019)
Scheu, C.: Materials for renewable energy applications. Metallurgical Engineering and Materials Science Department Colloquium, Indian Institute of Technology, Mumbai, India (2019)
Frank, A.; Changizi, R.; Scheu, C.: Preparative and analytical challenges in electron microscopic investigation of nanostructured CuInS2 thin films for energy applications. Microscience Microscopy Congress (MMC) 2019, Manchester, UK (2019)
Gänsler, T.; Frank, A.; Betzler, S. B.; Scheu, C.: Electron microscopy studies of Nb3O7(OH) nanostructured cubes - insights in the growth mechanism. Microscience Microscopy Congress MMC2019, Manchester, UK (2019)
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
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
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.