Scheu, C.: Designing the functional properties of thermoelectric materials by grain boundary engineering. Workshop on New Horizons in Materials Design, MPIE, Düsseldorf, Germany (2023)
Vega-Paredes, M.; Arenas Esteban, D.; Garzón-Manjón, A.; Scheu, C.: How can electron tomography be used for studying the catalyst degradation of fuel cells. Advanced Electron Nanoscopy Group – Institut Catala de Nanociencia I Nanotecnologia, Bellaterra, Spain (2022)
Aymerich Armengol, R.; Cignoni, P.; Ebbinghaus, P.; Linnemann, J.; Rabe, M.; Tschulik, K.; Scheu, C.; Lim, J.: Electron microscopy insights on the mechanism of morphology/phase transformations in manganese oxides. Institut de Nanociència i Nanotecnologia (ICN2), Bellaterra, Spain (2022)
Scheu, C.: Unravelling secrets of interfaces in renewable energy application. 10th International Workshop on Interfaces, Santiago de Compostela, Spain (2022)
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)
Scheu, C.: Insight in the structure and stability of (photo)catalysts. Graduiertenkollegs GRK1896 „In situ microsopy with electrons, X-rays and scanning probes: Abschlusssymposium, Erlangen, Germany (2022)
Scheu, C.: Tracing impurities and structural defects in energy materials using advanced scanning transmission electron microscopy and atom probe tomography. Retreat Lotsch Group, Schloss Fürstenried, München, Germany (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)
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
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…