Tailoring the Microstructure of a Solid Oxide Fuel Cell Anode Support by Calcination and Milling of YSZ
Bibliographic record
Abstract
In this study, the effects of calcination and milling of 8YSZ (8 mol% yttria stabilized zirconia) used in the nickel-YSZ anode on the performance of anode supported tubular fuel cells were investigated. For this purpose, two different types of cells were prepared based on a Ni-YSZ/YSZ/Nd2NiO4+δ-YSZ configuration. For the anode preparation, a suspension was prepared by mixing NiO and YSZ in a ratio of 65:35 wt% (Ni:YSZ 50:50 vol.%) with 30 vol.% graphite as the pore former. As received Tosoh YSZ or its calcined form (heated at 1500 °C for 3 hours) was used in the anode support as the YSZ source. Electrochemical results showed that optimization of the fuel electrode microstructure is essential for the optimal distribution of gas within the support of the cell, especially under electrolysis operation where the performance for an optimized cell (calcined YSZ) was enhanced by a factor of two. In comparison with a standard cell (containing as received YSZ), at 1.5 V and 800 °C the measured current density was -1380 mA cm(-2) and -690 mA cm(-2) for the cells containing calcined and as received YSZ, respectively. The present study suggests that the anode porosity for improved cell performance under SOEC is more critical than SOFC mode due to more complex gas diffusion under electrolysis mode where large amount of steam needs to be transfered into the cell.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".