Construction of Ultrathin BiVO<sub>4</sub>‐Au‐Cu<sub>2</sub>O Nanosheets with Multiple Charge Transfer Paths for Effective Visible‐Light‐Driven Photocatalytic Degradation of Tetracycline
Bibliographic record
Abstract
Abstract In this study, unique BiVO 4 ‐Au‐Cu 2 O nanosheets (NSs) are well designed and multiple charge transfer paths are consequently constructed. The X‐ray photoelectron spectroscopy measurement during a light off‐on‐off cycle and redox capability tests of the photo‐generated charge carriers confirmed the formation of Z‐scheme heterojunction, which can facilitate the charge carrier separation and transfer and maintain the original strong redox potentials of the respective component in the heterojunction. The ultrathin 2D structure of the BiVO 4 NSs provided sufficient surface area for the photocatalytic reaction. The local surface plasmon resonance (LSPR) effect of the electron mediator, Au NPs, enhanced the light absorption and promoted the excitation of hot electrons. The multiple charge transfer paths effectively promoted the separation and transfer of the charge carrier. The synergism of the abovementioned properties endowed the BiVO 4 ‐Au‐Cu 2 O NSs with satisfactory photocatalytic activity in the degradation of tetracycline (Tc) with a removal rate of ≈80% within 30 min under visible light irradiation. The degradation products during the photocatalysis are confirmed by using ultra‐high performance liquid chromatography‐mass spectrometry and the plausible degradation pathways of Tc are consequently proposed. This work paves a strategy for developing highly efficient visible‐light‐driven photocatalysts with multiple charge transfer paths for removing organic contaminants in water.
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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".