Bibliographic record
Abstract
The properties of spinel oxides were studied in an effort to identify a potential solid oxide fuel cell (SOFC) interconnect coating which can hinder chromium oxide growth and evaporation as well provide acceptable electrical conductivity. Transition metal spinels based on aluminum, chromium, manganese and iron were examined. The electrical conductivities were measured in air from 500 to 800°C by the standard four-probe DC method. Additionally, the thermal expansion coefficients of some samples were measured in air from room temperature to 1000°C. The stoichiometric aluminates, chromites and manganites have thermal expansion coefficients that lie consistently in the 7–9 ppm/K range. Thermal expansion coefficients of the ferrites are in the 11–13 ppm/K range, and their conductivities are generally 0.1–10 S/cm. Conductivities of the aluminates are all less than 10 −2 S/cm. Among the potential candidates for SOFC interconnect coatings, Co 2 MnO 4 has a conductivity of 55 S/cm at 800°C and a thermal expansion coefficient of 9.7 ppm/K and CuFe 2 O 4 has a conductivity of 9.1 S/cm at 800°C and a thermal expansion coefficient of 11.2 ppm/K. The ternary spinel oxides of CuMn 2−x Cr x O 4 (x = 0.2, 0.6, 0.8 and 1.0) and Co 2 Mn 0.5 Cr 0.5 O 4 are also acceptable in terms of their electrical conductivities and thermal expansion coefficients.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".