Identifying the grain boundary character distribution in ceramics using scanning electron nanobeam diffraction (SEND)- A case study on Solid Oxide Electrolysis Cells (SOEC) for sustainable hydrogen generation.

Grain and inter-phase boundaries are important defects within the engineering materials microstructure, critically affecting material properties linked to mechanical strength, corrosion and diffusion, just to name a few. Introducing the right type of GB’s into the microstructure can increase the overall corrosion resistance by a factor of two or fracture toughness by orders of magnitude. The established routes into grain boundary character distribution (GBCD) determination are either through electron back-scattered diffraction (EBSD) of bulk specimens in an SEM or high-resolution TEM or STEM of isolated grain boundaries. The former technique is limited to grains larger than ~100-200 nm. The latter approach lacks the number of grain boundary observations needed for statistical analysis. 
Non-special boundaries are more frequent compared to special GBs, and consequently the non-special GB have a large effect on the materials properties. Yet most HR-TEM studies are focused on special Σ-GB's, which are rarely the dominant type of grain boundaries in ceramics. Importantly these non-special grain boundaries are the ones with the most flexible structures, sensitive to small variations in processing and consequently they are engineerable. We aim to enable high resolution structure analysis across the full variability of grain boundaries in misorientation space by using scanning electron nano-beam diffraction (SEND) to collect scanning diffraction data from large areas of the sample. From this we implement automated segmentation and crystal orientation mapping routines, enabling us to obtain structural information across the whole misorientation space and draw a statistically sound picture of the grain boundary character landscape of ceramics. 

The PhD project:
We will be building on the developments based on SEND at ePSIC and automated microscope control using the python API PyJEM. The new workflow will enable the collection of large data-sets automatically, allowing orientation mapping across identified grain boundaries. The resulting data will be analyzed to extract the GBCD and identify the most frequent grain boundaries in SOEC.

Example of SEND data across multiple grains

Example of SEND data across multiple grains with (A) virtual annular DF image, (B) segmented signal based on the diffraction signal, highlighting the grains, and (C) and (D) identified diffraction spots to be used for ACOM.


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