Size-Selected TiO<sub>2</sub> Nanocluster Catalysts for Efficient Photoelectrochemical Water Splitting
Bibliographic record
Abstract
Nanoclusters (NCs) are of great interest because they provide the link between the distinct behavior of atoms and nanoparticles and that of bulk materials. Here, we report precisely controlled deposition of size-selected TiO2 NCs produced by gas-phase aggregation in a special magnetron sputtering system. Carefully optimized aggregation length and Ar gas flow are used to control the size distribution, while a quadrupole mass filter provides precise in situ size selection (from 2 to 15 nm). Transmission electron microscopy studies reveal that NCs larger than a critical size (∼8 nm) have a crystalline core with an amorphous shell, while those smaller than the critical size are all amorphous. The TiO2 NCs so produced exhibit remarkable photoelectrochemical water splitting performance in spite of a small amount of material loading. NCs of three different sizes (4, 6, and 8 nm) deposited on H-terminated Si(100) substrates are tested for the photoelectrochemical catalytic performance, and significant enhancement in photocurrent density (0.8 mA/cm(2)) with decreasing NC size is observed with a low saturation voltage of -0.22 V vs Ag/AgCl (0.78 V vs RHE). The enhanced photoconductivity could be attributed to the increase in the specific surface area and increase in the number of active (defect) sites in the amorphous NCs. The unique advantages of the present technique will be further exploited to develop applications based on tunable, size-selected NCs.
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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) | 0.000 | 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 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".