A Comprehensive Review on the Boosted Effects of Anion Vacancy in the Photocatalytic Solar Water Splitting: Focus on Sulfur Vacancy
Bibliographic record
Abstract
In recent decades, a great interest in photocatalytic water splitting has been due to the importance of sunlight water splitting hydrogen production as a renewable energy source to reduce global warming effects. The photocatalytic water splitting applications of metal sulfide semiconductors photocatalysts, as chalcogenide compounds, with advantages of the wide range for light harvesting and tunable bandgap, may be restricted by the limited active sites, poor conductivity, photo corrosion, and charge recombination. The sulfur vacancy (SV) effectively addresses these issues and generates H 2 and O 2 by attaining adequate water-splitting because of the improved optoelectronic features. This review article aims to comprehensively highlight the synergistic roles of SV in metal sulfides for amended overall water-splitting activity. The SV-modulated metal sulfides’ photocatalytic features are deliberated, followed by different advanced synthetic techniques for effectual vacancy defect generation. The specific SV aspects in refining the optical harvesting range, dynamics of charge carrier, and photoinduced surface chemical reactions are deeply described for overall water splitting applications. Finally, summarized vouchsafing outlooks and opportunities confronting the S-vacancy engineered metal sulfides-based photocatalysts are elucidated. It would be expected and hoped that this review will help researchers design/fabricate better metal sulfide-based photocatalytic systems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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; both teacher heads agree on what is shown here.
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".