Zhang, S.; Kim, S.-H.; Mingers, A. M.; Gault, B.; Scheu, C.: Operando Study on the corrosion of photo-electrocatalysts. NRF-DFG meeting “Electrodes for direct sea-water splitting and microstructure based stability analyses”, Kangwon National University, Chuncheon-si, South Korea (2023)
Zhang, S.: Microstructure design in thermoelectric materials: in situ observation of doping behavior and role of grain boundary phases. Colloqium, Ruhr-Universität Bochum, Bochum, Germany (2023)
Zhang, S.: Microstructure design in thermoelectric materials: Decoupling the transport properties and in situ observation at operation conditions. Colloqium, TU Darmstadt, Darmstadt, Germany (2023)
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)
Zhang, S.: Electron Microscopy. DGK-AK20 Summer School “Synthesis and characterization of inorganic functional materials”, Mülheim (Ruhr), Germany (2019)
Scheu, C.; Zhang, S.: Effect of interfaces on the photoelectrochemical performance of functional oxides. PICS3 2019 Meeting, Centre Interdisciplinaire de Nanoscience de Marseille, Marseille, France (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
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…