Zinc oxide/graphene‐like tungsten disulphide nanosheet photocatalysts: Synthesis and enhanced photocatalytic activity under visible‐light irradiation
Bibliographic record
Abstract
A highly efficient zinc oxide/graphene‐like tungsten disulphide nanosheet (ZnO/WS2) was synthesized by a facile two‐step method and characterized via XRD, SEM, TEM, XPS, BET, UV‐Vis DRS, PL, etc. The photocatalytic activity of the ZnO/WS2 photocatalyst was estimated via the degradation of Rhodamine B (RhB) dye under 500 W tungsten lamp radiation. Compared with ZnO, ZnO/WS2 photocatalyst presented a high degradation efficiency (95.71 %) within 120 min under visible‐light irradiation, indicating that ZnO/WS2 photocatalyst had excellent photocatalytic activity. Photocatalytic reaction followed the first‐order model kinetics, and ZnO/WS2 photocatalyst remained a relatively higher photocatalytic activity after four successive recycles, which verified that the structure of ZnO/WS2 photocatalyst was stable and had potential applications in the removal of dye wastewater. At last, the possible mechanism for the photocatalytic degradation of dyes over ZnO/WS2 photocatalysts was also discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".