Y/Zr/NiO-Ceria/Silica Nanocomposite Anodic Cermets Support Direct Ethanol SOFC
Bibliographic record
Abstract
Several inherent challenges accompany direct conversion of primary fuels (e.g. ethanol) at elevated temperatures and these problems limit the applicability and efficiency of the solid oxide fuel cell (SOFC) technology. In fact, a pressing problem is the fuel dehydrogenation of standard nickel-based anode cermet. In the present study, the contribution of ceria/silica nanoparticles acting as dopants toward the stability of nickel oxide (NiO) functionalized anodic layer for direct ethanol SOFC was investigated. Two dopants were fabricated from fused molten nanocomposite consisting of combined ceria and silica nanoparticles (4:1 volume ratio) with 5 wt% Y or Zr bound to NiO. After synthesis, both nanocomposites were characterized using appropriate techniques (Scanning Electron Microscopy, SEM, X-ray Photoelectron Spectroscopy, XPS, and X-ray Diffraction, XRD, techniques). All tests were conducted in fixed bed reactors for ethanol fueled SOFC. The Zr containing dopant altered the catalytic properties of these modified ceria/silica supports toward ethanol steam reforming compared to Y, while changes in electronic transport properties were also observed for both Y/NiO and Zr/NiO ceria/silica nanocomposites. The dopant with Zr also exhibited significant oxygen storage capacity and electronic conductivity compared to Y. In summary, these ceria/silica-based cermets acted as novel and effective anode materials for ethanol steam reforming. Keywords: Solid oxide fuel cell (SOFC); Ceria dopants; Silica-based cermets; Direct ethanol SOFC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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; both teacher heads agree on what is shown here.
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".