Promoting Influence of Doping Indium into BaCe <sub>0.5</sub> Zr <sub>0.3</sub> Y <sub>0.2</sub> O <sub>3‐δ</sub> as Solid Proton Conductor
Bibliographic record
Abstract
The influence of indium doping on chemical stability, sinterability, and electrical properties of BaCe 0.5 Zr 0.3 Y 0.2 O 3‐δ was investigated. The phase purity and the chemical stability of the powders in humid pure CO 2 were evaluated by XRD . The dense electrolyte pellets were formed after the calcination at 1450°C for 8 h. SEM images and shrinkage plot showed that the sinterability of the samples was apparently improved by doping indium. The electrical conductivity was measured by impedance test through two‐point method, at both low (200–350°C) and high temperature ranges (450–850°C) in different atmospheres. BaCe 0.4 Zr 0.3 In 0.1 Y 0.2 O 3‐δ has been proved to be the optimal composition which simultaneously maximized the chemical stability, sinterability, and electrical conductivity which reached 1.1 × 10 −2 S/cm in wet hydrogen at 700°C, comparing with the 1.3 × 10 −2 S/cm for original BaCe 0.5 Zr 0.3 Y 0.2 O 3‐δ . Anode support fuel cell with a thin BaCe 0.4 Zr 0.3 In 0.1 Y 0.2 O 3‐δ electrolyte (15 μm) was fabricated by spin coating method. Maximum power density of 0.651 W/cm 2 was obtained when operating at 700°C and fed by humid H 2 (containing H 2 O 3 vol%). The obtained fuel cell could efficiently run at 650°C for more than 100 h without any attenuation.
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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".