High-frequency dielectric characterization of electronic defect states in co-sputtered W-doped TiO2
Bibliographic record
Abstract
Tungsten-doped titanium dioxide (TiO2:W) has been reported to have increased photocatalytic performance as compared to undoped TiO2. The exact mechanism behind this has been debated. Consequently, the purpose of this work is twofold: (i) synthesize TiO2:W films with improved optoelectronic properties and (ii) refine the understanding of photocharge properties in tungsten-doped TiO2. An in situ radio frequency magnetron-sputtering deposition process was used to fabricate undoped (TiO2), oxygen deficient (TiO2-x), and tungsten-doped (TiO2:W) films with varying dopant levels. X-ray photoelectron spectroscopy measurements showed the presence of both WTi″ and WTix type dopants that led to significantly reduced oxygen vacancy (VO) densities. These observations were corroborated by X-ray diffraction analysis, which revealed that the improved stoichiometry resulted in a marked enhancement of the rutile phase as compared to the sub-stoichiometric (VO-doped) samples. Critically, high-frequency dielectric spectroscopy measurements revealed an optimal tungsten doping level of ∼2.5 at. %. This point showed the greatest tungsten induced reduction in the 2[TiIII]–[VO″] defect pair ɛ′ contribution, i.e., almost two orders of magnitude. Finally, this dielectrically observed reduction in VO was correlated to an increase in photocharge decay lifetimes. In other words, photocharge lifetimes increased in accordance with the reduction of VO defects brought on by tungsten doping.
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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".