Sulfur-Doped Highly Ordered TiO<sub>2</sub> Nanotubular Arrays with Visible Light Response
Bibliographic record
Abstract
The future of TiO 2 -based photocatalysts strongly depends on their structural optimization so as to obtain high activity as well as visible light response. Recently we successfully fabricated sulfur-doped highly ordered TiO 2 nanotubular arrays by potentiostatic anodization of titanium foils, followed by annealing in a flow of H 2 S at 380 °C. The as-prepared arrays were characterized using field emission scanning electron microscopy, differential scanning calorimetry, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), ultraviolet−visible diffuse reflectance spectroscopy (UV−vis DRS), and photoelectrochemical measurements. The results clearly show that the vertically oriented nanotubular arrays are highly ordered with a wall thickness of 10 nm. After being annealed at 380 °C, the original TiO 2 nanotubular arrays were transformed from an amorphous structure to an anatase phase with a crystallization enthalpy of 324.6 J/g. With treatment in a H 2 S atmosphere, sulfur ions were incorporated into oxygen atom sites in the TiO 2 nanotubes to form O−Ti−S bonds, confirmed by high-resolution XPS of S2p and Ti2p and XRD analysis. The sulfur doping caused the absorption edge of TiO 2 to shift into the lower energy region, making the nanotubular arrays active under visible light irradiation up to 650 nm, demonstrated by UV−vis DRS and photocurrent measurements.
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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".