Influence of Microstructure on Electrochemical Performance of Plasma Sprayed Ni‐YSZ Anodes for SOFCs
Bibliographic record
Abstract
Abstract The influence of anode microstructural parameters on the electrochemical performance of plasma sprayed solid oxide fuel cells with metal supports has been investigated. Electrochemical impedance spectroscopy (EIS) was used to correlate the measured polarization resistances associated with both the three‐phase boundary length density and gas diffusivity of porous nickel/yttria‐stabilized zirconia (YSZ) anodes. Each anode was deposited in atmospheric conditions using solution precursor plasma spraying (SPPS), dry‐powder plasma spraying (DPPS), or suspension plasma spraying (SPS). The high‐frequency (> 1 kHz) part of the impedance spectrum was found to correlate with the three‐phase boundary length per unit volume of each anode. The low‐frequency part of the impedance spectrum was found to correlate with diffusive transport of gases through the porous anode. Gas transport measurements in the context of the dusty gas model were used to extract microstructure‐dependent parameters that provided a quantitative comparison among the distinct microstructures obtained using the three plasma spray methods. These results were compared to measurements using Darcy's law, which yielded similar trends and provided an efficient method to more rapidly compare gas transport rates in porous electrodes having different structures.
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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 | 0.001 |
| 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 | 0.001 | 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".