Novel synthesis method of oxygen vacancy <scp>WO<sub>3</sub></scp> and its photocatalytic performance for degradation of rhodamine B
Bibliographic record
Abstract
Abstract BACKGROUND Photocatalytic degradation of organic pollution as a ‘green’ treatment technology has been a broad concern in water treatment. This work proposed a simple method for introducing oxygen vacancies into WO 3 and enhancing the degradation of WO 3 for rhodamine B under simulated solar light. RESULTS In this work, titanium power was used as an oxygen absorber to introduce oxygen vacancies into WO 3 . The degradation of organic dyes by semiconductor materials is significantly improved by the presence of oxygen vacancies. After 4 h of simulated sunlight irradiation, 100% degradation efficiency of rhodamine B by WO 3 with vacancies was achieved, compared to about 60% by WO 3 . Combined with liquid chromatography–mass spectrometry and total organic carbon analysis results, we speculated the degradation path of rhodamine B degraded by WO 3 ‐2. CONCLUSION There exist three reasons for the enhanced photocatalytic performance of oxygen‐containing vacancy WO 3 : (i) the introduction of vacancies generates an energy level of the donor that can reduce the band gap; (ii) the presence of oxygen vacancies can effectively prevent the electron–hole complexation process; and (iii) oxygen vacancies increase the adsorption capacity of the catalyst. It is expected that this method of oxygen vacancy introduction can be extended to other semiconductor systems to achieve higher performance in pollutant degradation and water remediation. © 2023 Society of Chemical Industry (SCI).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 teacher head, 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".