Processing of Ce<sub>1-x</sub>Gd<sub>x</sub>O<sub>2-δ</sub> (GDC) Thin Films from Precursors for Application in Solid Oxide Fuel Cells
Bibliographic record
Abstract
Extensive interfacial reactions are known to occur between Fe-Co based perovskite cathode materials and the standard solid oxide fuel cell (SOFC) yttria stabilized zirconia (YSZ) electrolyte. Thin films of gadolinia doped ceria (GDC) could be used as a diffusion barrier between the cathode and the electrolyte. The present work investigates spin coating thin diffusion reaction inhibiting films onto SOFC electrolytes. The chemical and structural evolution of ethylene glycol based precursor solution is studied by means of rheology, x-ray diffraction (XRD), high temperature XRD (HT-XRD), Fourier-transformed infrared spectroscopy (FTIR) and differential thermal analysis (DTA). The studies show that cerium formate is formed as an intermediate resin. Thin films, up to 500 nm thick, of gadolinia doped ceria (GDC) are successfully produced by multiple spin coating of polymerized ethylene glycol derived solutions on 200 1m thick YSZ tapes. The GDC and YSZ interfacial surface morphology and film thickness are studied by scanning electron microscopy (SEM) and atomic force microscopy (AFM). These films are shown to successfully prevent the creation of non-conducting reaction phases at the cathode-electrolyte interface by blocking interdiffusion.
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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) | 0.001 | 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".