Au/CeO <sub>2</sub> hollow nanospheres with enhanced catalytic activity for <scp>CO</scp> oxidation
Bibliographic record
Abstract
Abstract Au/CeO 2 hollow nanospheres were successfully synthesized by template method. Carbon spheres ( CS s) were employed as the sacrificial templates, which were fabricated by hydrothermal method, and the shell of CeO 2 precursor was formed on the surface of CS s through layer‐by‐layer self‐assembled approach. Then, Au nanoparticles were deposited on the shell. Finally, the templates were removed by calcination and Au/CeO 2 hollow spheres with hierarchically porous structure were obtained. The samples were characterized by XRD , SEM , TEM , TG ‐ DSC , and BET analysis. The diameters and thickness of the nanospheres were about 250 nm and 20 nm, respectively. Samples with different loading amounts of Au were prepared and noted as L‐Au/CeO 2 , M‐Au/CeO 2 , and H‐Au/CeO 2 , corresponding to the Au weight percentages of 1.8%, 4.2%, and 9.3%. The specific surface area of L‐Au/CeO 2 could reach 87.1 m 2 /g, higher than that of M‐Au/CeO 2 (77.8 m 2 /g), while M‐Au/CeO 2 showed the best catalytic activity that CO could be completely converted to CO 2 at 81°C. The CeO 2 , L‐Au/CeO 2 , and M‐Au/CeO 2 hollow nanospheres showed excellent catalytic stability. Moreover, this method can be easily extended to the synthesis of other metal oxide hollow nanospheres compounded with Au nanoparticles.
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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".