Composites of La0.4Sr0.6Co0.8Fe0.2O3−d (LSCF) with samarium doped ceria (SDC) have been extensively used as cathodes
for solid oxide fuel cells (SOFCs) to lower its operation temperature. The ability to visualize three-dimensional (3D)
microstructural changes in LSCF-SDC composite cathodes can help elucidate the impact of microstructure on cathode
performance. This study reports that we utilize the nano-computed tomography (nano-CT) technique to image the 3D
microstructures of La0.4Sr0.6Co0.2Fe0.8O3 (LSCF) - Ce0.8Sm0.2O1.9 (SDC) composite cathodes which were sintering at 800,
1000, and 1200°C, respectively, for 2 h based on the Fe K-absorption edge. Using the reconstructions of LSFC-SDC
composite cathodes submitted to different temperatures, the key microstructural properties, such as volume fraction of
each phase, connected volume fraction, surface area, triple-phase boundary length, and pore size were measured. The
effect of sintering temperature on the microstructure of LSFC-SDC cathodes was discussed and compared with
theoretical simulation. With increasing sintering temperature in the range from 800 to 1200°C LSFC-SDC composite
cathode microstructure was found that the volume fraction and grain size of LSCF material increased, while the volume
fraction of SDC decreased. Furthermore, the triple-phase boundary length per volume increased as the sintering
temperature increasing. This study had revealed that the nano-CT can provide a powerful tool to investigate the 3D
microstructure of energy materials and optimize its preparation condition to gain better functional performance.
Nano-CT has been considered as an important technique applied in analyzing inter-structures of nanomaterials and
biological cell. However, maximum rotation angle of the sample stage is limited by sample space; meanwhile, the scan
time is exorbitantly large to get enough projections in some cases. Therefore, it is difficult to acquire nano-CT images
with high quality by using conventional Fourier reconstruction methods based on limited-angle or few-view projections.
In this paper, we utilized the total variation (TV) iterative reconstruction to carry out numerical image and nano-CT
image reconstruction with limited-angle and few-view data. The results indicated that better quality images had been
achieved.
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