Fluoride-capped nanoceria as a highly efficient oxidase-mimicking nanozyme: inhibiting product adsorption and increasing oxygen vacancies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nanozymes aim to mimic enzyme activities using nanomaterials. Nanoceria (CeO2 nanoparticles) is an important model nanozyme for its rich redox chemistry. In particular, its oxidase-like activity allows oxidation reactions without the need of unstable and toxic H2O2. Fluoride can significantly improve its oxidase-like activity, and this work aims to understand the mechanism of fluoride-promoted catalysis. First, fluoride can adsorb on CeO2 tighter than other halides, but not as strong as phosphate as characterized by isothermal titration calorimetry (ITC). FT-IR spectroscopy indicates adsorption of fluoride likely via exchange with surface hydroxide groups. Fluoride capping inverses the surface charge of CeO2, facilitating desorption of the ABTS oxidation product, significantly increasing the turnover number. The Raman, EPR and XPS spectroscopy results demonstrate that the concentration of Ce3+ and the accompanying oxygen vacancy significantly increased upon adding F-, which can explain the enhanced catalytic activity. Finally, the electron transfer properties of fluoride-capped CeO2 were more efficient than that of the bare CeO2 as determined by a direct electrochemical measurement on a glass carbon electrode. This study has provided new insight into nanoceria, and can also further confirm the role of nanoceria as a model for engineering the surface of nanozymes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it