Recent Advances in the Design of Plasmonic Au/TiO2 Nanostructures for Enhanced Photocatalytic Water Splitting
Bibliographic record
Abstract
Plasmonic nanostructures have played a key role in extending the activity of photocatalysts to the visible light spectrum, preventing the electron–hole combination and providing with hot electrons to the photocatalysts, a crucial step towards efficient broadband photocatalysis. One plasmonic photocatalyst, Au/TiO2, is of a particular interest because it combines chemical stability, suitable electronic structure, and photoactivity for a wide range of catalytic reactions such as water splitting. In this review, we describe key mechanisms involving plasmonics to enhance photocatalytic properties leading to efficient water splitting such as production and transport of hot electrons through advanced analytical techniques used to probe the photoactivity of plasmonics in engineered Au/TiO2 devices. This work also discusses the emerging strategies to better design plasmonic photocatalysts and understand the underlying mechanisms behind the enhanced photoactivity of plasmon-assisted catalysts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".