Bismuth Tungstate Nanoplates—Vis Responsive Photocatalyst for Water Oxidation
Bibliographic record
Abstract
The development of visible-light-responsive (VLR) semiconductor materials for effective water oxidation is significant for a sustainable and better future. Among various candidates, bismuth tungstate (Bi2WO6; BWO) has attracted extensive attention because of many advantages, including efficient light-absorption ability, appropriate redox properties (for O2 generation), adjustable morphology, low cost, and profitable chemical and optical characteristics. Accordingly, a facile solvothermal method has been proposed in this study to synthesize two-dimensional (2D) BWO nanoplates after considering the optimal preparation conditions (solvothermal reaction time: 10–40 h). To find the key factors of photocatalytic performance, various methods and techniques were used for samples’ characterization, including XRD, FE-SEM, STEM, TEM, HRTEM, BET-specific surface area measurements, UV/vis DRS, and PL spectroscopy, and photocatalytic activity was examined for water oxidation under UV and/or visible-light (vis) irradiation. Famous commercial photocatalyst–P25 was used as a reference sample. It was found that BWO crystals grew anisotropically along the {001} basal plane to form nanoplates, and all properties were controlled simultaneously by tuning the synthesis time. Interestingly, the most active sample (under both UV and vis), prepared during the 30 h solvothermal reaction at 433 K (BWO–30), was characterized by the smallest specific surface area and the largest crystals. Accordingly, it is proposed that improved crystallinity (which hindered charge carriers’ recombination, as confirmed by PL), efficient photoabsorption (using the smallest bandgap), and 2D mesoporous structure are responsible for the best photocatalytic performance of the BWO–30 sample. This report shows for the first time that 2D mesoporous BWO nanoplates might be successfully prepared through a facile template-free solvothermal approach. All the above-mentioned advantages suggest that nanostructured BWO is a prospective candidate for photocatalytic applications under natural solar irradiation.
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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".