Surface-Driven Electron Localization and Defect Heterogeneity in Ceria
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The exceptional performance of ceria (CeO 2 ) in catalysis and energy conversion is fundamentally governed by its defect chemistry, particularly oxygen vacancies. The formation of each oxygen vacancy (V O •• ) is assumed to be compensated by two localized electrons on cations (Ce 3+ ). Here, we show by combining theory with experiment that while this 1 V O ••: 2Ce 3+ ratio accounts for the global charge compensation, it does not apply at the local scale, particularly in nanoparticles. Hybrid quantum mechanical/molecular mechanical (QM/MM) defect calculations, together with synchrotron X-ray photoelectron spectroscopy (XPS) measurements, show that electrons have a strong preference to localize and segregate on surfaces, which can overcome the trapping force from the V O •• sites in the bulk. At a given Fermi level, the surface V O •• tends to trap more electrons than those in bulk, resulting in a higher Ce 3+ to V O •• ratio on surfaces than that in the bulk, driven by the preferential localization of electrons and enhanced V O •• –Ce 3+ coupling. Large-scale unbiased Monte Carlo simulations on ceria nanoparticles confirmed this trend and further show that the surface segregation of electrons is more pronounced at low reduction levels and in smaller nanoparticles. In highly reduced ceria nanoparticles, however, the enhanced repulsive interactions lead to a less significant extent of defect heterogeneity or even reverse the location preference of defects in some nanoparticles. Our findings underscore the need to consider both the overall nonstoichiometry and local defect behavior in easily reducible oxides, with direct relevance to their performance in catalytic and energy applications.
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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 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".