Effects of metal support interaction on dry reforming of methane over Ni/<scp>Ce‐Al<sub>2</sub>O<sub>3</sub></scp>catalysts
Bibliographic record
Abstract
Abstract Dry (CO2) reforming of methane is conducted over two newly synthesized Ni20/Ce‐γAl2O3and Ni20/Ce‐meso‐Al2O3catalysts. The x‐ray diffraction (XRD) patterns indicated that Ni20/Ce‐meso‐Al2O3exhibits a better dispersion of nickel, while Ni20/Ce‐γAl2O3has larger amounts of nickel crystallites. The temperature programmed desorption (TPD) kinetics analysis indicated that Ni20/Ce‐meso‐Al2O3had a lesser metal‐support interaction than the Ni20/Ce‐γAl2O3. The thermal gravimetric analysis (TGA) indicated that the incorporation of ceria into the Al2O3matrix helps to stabilize Ni20/Ce‐meso‐Al2O3during dry reforming of methane. The temperature programmed reduction (TPR) indicated that the synthesized catalysts were sufficiently reducible below 750 °C. A fixed bed reactor evaluation (at 750 °C) showed that both catalysts can facilitate methane reforming to syngas with minimal coking throughout the 30 hours time‐on‐stream (TOS). However, Ni20/Ce‐meso‐Al2O3is more promising in terms of prolonged stability for dry reforming applications. Moreover, the syngas yield for Ni20/Ce‐γAl2O3is close to equilibrium prediction during the first 1 hour of reaction time.
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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".