Grain and Grain Boundary Structure and Electric Fields in Protonic Ceramics by Electron Microscopy

• Applicant: Professorin Dr. Kerstin Volz
• Subject Area: Thermodynamics and Kinetics as well as Properties of Phases and Microstructure of Materials ; Synthesis and Properties of Functional Materials
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 556363981

In the project of the RU SynDiPET we will use electron microscopic methods to clarify the real-space as well as electronic structure of the proton conducting ceramics sintered in the RU with innovative approaches such as UHS, PS, as well as - for comparison - FAST/SPS, at length scales ranging from atomic scales to several micrometers. We will also develop electron microscopic methods further, especially to image space charge layers at interfaces and to perform in-situ studies. These will be applied to investigate the structural and electronic changes of BZCY in water vapor at elevated temperatures. The data we provide will be used by the partners to inform and validate multiscale simulations and to train machine learning (ML) models to optimize the synthesis conditions aiming for optimized performance of the materials. We will moreover – also together with the partner projects in the RU - develop ML methods to evaluate electron diffraction data faster and more reliably and use ML to provide a higher amount of three-dimensional microstructural data from 2-dimensional micrographs. In detail we plan to: 1) determine the grain (boundary) and pore structure, phases and morphology on submicron to micrometer length scales, 2) quantify the structure and composition of and the bonding at GBs at atomic length scales, also comparing scattering data to image simulations, 3) develop and apply methods to image the space charge region across GBs and quantify space charge potentials, 4) develop in-situ experiments for BZCY and understand the structural and electronic changes of BZCY in water by in-situ experiments, 5) provide structural and electronic data to the partner projects for validation of extended simulations and train ML models and to optimize the synthesis conditions with regard to materials' performance, 6) develop ML methods to evaluate electron diffraction data, 7) use ML to retrieve the three-dimensional grain (boundary) and pore structure from two-dimensional measurements.

• DFG Programme: Research Units
• Subproject of: FOR 5966: Synergistic Design of Proton Conducting Ceramics for Energy Technology (SynDiPET)
• Co-Investigator: Dr. Andreas Beyer