Zhang, S.; Yu, Y.; Jung, C.; Mattlat, D. A.; Abdellaoui, L.; Scheu, C.: In situ STEM observation of thermoelectric materials under heating and biasing conditions. The 6th joint Sino-German workshop on advanced & correlative electron microscopy of catalysts, quantum phenomena & soft matter, Bad Honnef, Germany (2024)
Zhang, S.; Yu, Y.; Jung, C.; Wang, Z.; Mattlat, D. A.; Abdellaoui, L.; Scheu, C.: In situ microstructural observation and electrical transport measurements of PbTe thermoelectrics by transmission electron microscopy. International Conference on Thermoelectrics ICT, Krakow, Poland (2024)
Scheu, C.; Zhang, S.: Hematite for light induced water splitting – improving efficiency by tuning distribution of Sn dopants at the atomic scale. The International Symposium on Advanced Coatings for Energy – ISC4E 2023, Ben Guerir, Morocco (2023)
Zhang, S.: Electron microscopy: Resolution and imaging contrast. DMG/DGK-AK9 Summer School “Advanced methods for the characterization of applied materials”, MPI für Kohlenforschung, Mülheim (Ruhr), Germany (2023)
Zhang, S.; Kim, S.-H.; Mingers, A. M.; Gault, B.; Scheu, C.: Operando Study on the activation of hydrogen evolution electrocatalysts. NRF-DFG meeting “Electrodes for direct sea-water splitting and microstructure based stability analyses”, Korean Institute for Energy Research, Daejeon, South Korea (2023)
Jung, C.; Jang, K.; Zhang, S.; Bueno Villoro, R.; Choi, P.-P.; Scheu, C.: Sb-doping induced order to disorder transition enhances the thermal stability of NbCoSn1-xSbx half-Heusler semiconductors. The 20th International Microscopy Congress, PS-07.2. Microscopy of Semiconductor Materials and Devices, Busan, Republic of Korea (2023)
Zhang, S.; Yu, Y.; Jung, C.; Abdellaoui, L.; Scheu, C.: In situ TEM unveils dynamic doping behavior of thermoelectric materials – Microstructure and property evolution under heating and electric biasing. International Microscopy Conference IMC20, Busan, Korea (2023)
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.