Aymerich Armengol, R.; Cignoni, P.; Ebbinghaus, P.; Rabe, M.; Tschulik, K.; Scheu, C.; Lim, J.: Mechanism of coupled phase/morphology transformation of 2D manganese oxides through Fe galvanic exchange reaction. Chemistry Department Seminar, Kangwon National University, Chuncheon, South Korea (2022)
Vega Paredes, M.; Garzón-Manjón, A.; Rivas Rivas, N. A.; Berova, V.; Hengge, K. A.; Gänsler, T.; Jurinsky, T.; Scheu, C.: Ruthenium-Platinum Core-Shell Nanoparticles as durable, CO tolerant catalyst for Polymer Electrolyte Membrane Fuel Cells. 5th International Caparica Symposium on Nanoparticles/Nanomaterials and Applications (ISN2A), Online (accepted)
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)
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
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…
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…