Gold nanoparticle-functionalized niobium oxide perovskites as photocatalysts for visible light-induced aromatic alcohol oxidations
Bibliographic record
Abstract
Spherical gold nanoparticles have been supported onto the surface of potassium niobium oxide perovskites, an underdeveloped class of semiconductor in photocatalytic organic transformations. The nanoparticle dopants of 9.5 nm in diameter and surface plasmon absorption at 530 nm are examined as possible visible light induced catalysts using alcohol photooxidation as the probe reaction. The nanomaterial-induced photooxidation of a series of aromatic alcohols is examined, in the absence of solvent, as a function of base, H 2 O 2 , and catalyst concentrations, as well as using multiple visible light sources. This experimental methodology affords extremely selective photooxidation to the carbonyl products (>99%) in as little as 2 h. Using the results obtained from the substitution of the aromatic alcohol, the proposed photocatalytic mechanism is suggested to rely heavily on plasmon-initiated electron transfer from the gold nanoparticle surface to the potassium niobium oxide perovskite and subsequent reductive decomposition of H 2 O 2 . This photodegradation step is proposed to favor the formation of ketyl radical species, a key intermediate in the visible light induced mechanism that undergoes both an electron and proton transfer to facilitate formation of the final, carbonyl products. Furthermore, the gold nanoparticle – potassium niobium oxide catalyst exhibits moderate reusability, highly desired in the realm of heterogeneous catalysis.
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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".