Project Details
Projekt
Photonic Sintering of Ceramics as Novel sintering Approach for Data-driven Microstructure Investigation of Protonic Conductors
Applicant
Professor Dr.-Ing. Wolfgang Rheinheimer
Subject Area
Synthesis and Properties of Functional Materials
Term
since 2026
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 556363981
The project aims to replace conventional, time-consuming ceramic sintering methods with photonic sintering in order to enable fast, scalable, and data-driven optimization of proton-conducting ceramic materials. The focus lies on BaZrO3-based (BZY) and BaZrCeY-based (BZCY) ceramics, which are promising for electrochemical cells but remain difficult to process due to their poor sinterability and microstructure sensitivity. Photonic sintering uses high-intensity, short-wavelength light (e.g., blue laser or xenon flash lamps) to heat ceramic compacts at extremely high heating rates (>100 K/s), achieving full densification within minutes. This enables reaching the high sintering temperatures required for BZY/BZCY without the extended dwell times that lead to undesirable BaO loss. Moreover, it allows the simultaneous sintering of multiple samples and the in-situ monitoring of densification via video capture - offering valuable data for data-driven process optimization. Key research questions of this project include: 1. How do high heating rates affect microstructure evolution, particularly dopant distribution and segregation at grain boundaries? 2. Can grain boundary conductivity be enhanced by deliberate "grain boundary decoration" with nanoscale dopants to increase the grain boundary conductivity of the non-equilibrium grain boundaries after fast sintering? 3. What role do transient liquid phases (e.g., from NiO additives) play under ultrafast sintering conditions? 4. How do different rapid sintering techniques (UHS, PS, FAST/SPS) compare in terms of material performance and microstructural outcomes? To address these questions, partially calcined BZY powders will be systematically modified with sintering aids and dopants, followed by photonic sintering. The resulting samples will be comprehensively characterized (density, phase composition, microstructure, impedance spectroscopy), and all process and property data will be stored in a central research database. Together with other subprojects, a data-driven optimization loop will be established, supported by machine learning (ML) models that guide the design of optimized sintering protocols. The project contributes essential experimental data including: 1) Supplying base powders and sintered samples to other subprojects, 2) Conducting systematic high-throughput sintering experiments, 3) Performing multimodal sample characterization in close collaboration, 4) Supporting model validation and process optimization efforts. In the long term, it aims to establish a fundamental understanding of high heating rate sintering in proton-conducting ceramics and to develop energy-efficient, scalable processing routes for these materials.
DFG Programme
Research Units
