High resolution mapping of surface reduction in ceria nanoparticles
Bibliographic record
Abstract
Surface reduction of ceria nano octahedra with predominant {111} and {100} type surfaces is studied using a combination of aberration-corrected Transmission Electron Microscopy (TEM) and spatially resolved electron energy-loss spectroscopy (EELS) at high energy resolution and atomic spatial resolution. The valency of cerium ions at the surface of the nanoparticles is mapped using the fine structure of the Ce M(4,5) edge as a fingerprint. The valency of the surface cerium ions is found to change from 4+ to 3+ owing to oxygen deficiency (vacancies) close to the surface. The thickness of this Ce(3+) shell is measured using atomic-resolution Scanning Transmission Electron Microscopy (STEM)-EELS mapping over a {111} surface (the predominant facet for this ceria morphology), {111} type surface island steps and {100} terminating planes. For the {111} facets and for {111} surface islands, the reduction shell is found to extend over a single fully reduced surface plane and 1-2 underlying mixed valency planes. For the {100} facets the reduction shell extends over a larger area of 5-6 oxygen vacancy-rich planes. This finding provides a plausible explanation for the higher catalytic activity of the {100} surface facets in ceria.
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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".