Stabilization of Ni-YSZ Nanocomposite Anodes by Deposition of a Thin YSZ Overlayer
Bibliographic record
Abstract
Micro solid oxide fuel cells (μ-SOFCs) are energy conversion devices that are being considered for portable devices, such as laptop computers and mobile phones. As the low operating temperatures of μ-SOFCs (600 °C) result in high electrode resistances, one solution to this is to increase the triple phase boundary (TPB) length. In order to achieve this goal, ethylene glycol-based polymeric precursors of the Ni and YSZ components, which allow atomic level mixing of ions, were used to form nanocomposite Ni-YSZ thin films in this work. This, in turn, resulted in Ni-YSZ anode layers with an average grain size of ca. 25 nm, producing a very high TPB length (in comparison to conventional Ni-YSZ anodes) and hence a low electrode polarization resistance of 0.64 Ω.cm2 at 550 °C in humidified H2. It has been reported that Ni-YSZ thin films, prepared by pulsed laser deposition (PLD), exhibit Ni grain growth at operating temperatures (400-600 °C), resulting in a deleterious effect on the long-term stability of the electrode performance [1]. Although the YSZ network within the composite films constrained Ni grain growth to some extent, significant grain growth at the outer surface of the film could not be inhibited [1]. To overcome this problem for the polymeric precursor-deposited Ni-YSZ films developed here, we deposited a thin, porous YSZ layer (ca. 100 nm in thickness) on top of the Ni-YSZ film. This led to a decrease in the polarization resistance degradation rate, from 3.7% per hour at 550 °C in Ni-YSZ thin films to only 0.39 % per hour at the same temperature.The results obtained in this study show that atomic level mixing, resulting from the use of polymeric precursors, yields very good electrode performances that can be stabilized by the application of additional layers. This will allow for significantly lower μ-SOFC cost as a result of the increase in power density and improved robustness. Acknowledgements: The authors gratefully acknowledge the Eyes High PDF Program at the University of Calgary and Alberta Innovates – Technology Futures (AITF) for the support of AB, as well as the Natural Sciences and Engineering Research Council of Canada (NSERC) for the overall financial support of this work. References: U. P. Muecke, K. Akiba, A. Infortuna, T. Salkus, N. V. Stus and L. J. Gauckler, Solid State Ionics, 178 (2008) 1762.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".