The Buffering Activity of Ceria toward Reactive Oxygen Species: A Density Functional Theory Perspective
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Nanocrystalline ceria exhibits nanozymatic activities, which are strongly affected by surface composition and surface Ce 3+ concentration. Here, we use density functional theory to perform a scan of the compositional landscape of the most important {111}, {110}, and {100} ceria nanoparticle surfaces and their buffering activity toward reactive oxygen species (ROS) involved in the superoxide dismutase (SOD) and catalase (CAT) enzymatic mimetic activity of ceria. This study displays that pristine and surface sublayer oxygen-deficient surfaces can perform catalytic activities, whereas surface layer oxygen-deficient surfaces can only perform noncatalytic reactions as the oxygen vacancy is healed by ROS changing surface stoichiometry. Our findings corroborate conventional literature that higher concentrations of Ce 3+ favor SOD, whereas Ce 4+ favors CAT while also highlighting contributions of specific subprocess reactions. {111} surfaces perform best as fully oxidized (CAT) and fully reduced (SOD), while this is not the case for the {110} and {100} surfaces. As we follow plausible reaction mechanisms of SOD and CAT, we depict a complex situation highly dependent on the surface composition, which clearly implies that it is vital to control subprocess reactions for optimal buffering, and the desorption of products is a critical step in all reactions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".