Constructing S-scheme 3D Zn3In2S6/ReS2 heterojunction photocatalyst for simultaneous organic pollutants degradation and hydrogen production
Bibliographic record
Abstract
Controlling efficient interfacial charge transfer is crucial for developing advanced photocatalysts. This study successfully developed a bifunctional photocatalyst with an S-scheme heterojunction by incorporating ReS 2 into the Zn 3 In 2 S 6 (ZIS) nanoflower structure, enabling the organic pollutants degradation and synergistic hydrogen production. The optimized ZIS/ReS 2 -1% exhibited exceptional photocatalytic efficiency, reaching a 97.7% degradation rate of ibuprofen (IBP) within 2 h, along with a hydrogen generation rate of 1.84 mmol/g/h. The degradation efficiency and hydrogen generation rate were 1.78 and 5.75 times greater than those of Zn 3 In 2 S 6 , respectively. Moreover, ZIS/ReS 2 -1% demonstrated excellent catalytic degradation abilities for various organic pollutants such as ciprofloxacin, amoxicillin, norfloxacin, levofloxacin, ofloxacin, sulfamethoxazole, and tetracycline, while also showing good synergistic hydrogen production efficiency. Electron spin resonance and radical scavenging experiments verified that h + , ·O 2− , and ·OH were the primary reactive species responsible for IBP degradation. The superior photocatalytic performance of the ZIS/ReS 2 -1% was mainly attributed to its broad and intense absorption of visible light, effective separation of charge carriers, and enhanced redox capabilities. The degradation pathway of IBP was unveiled through Fukui function and liquid chromatography-mass spectrometry, and the toxicity of the degradation intermediates was also examined. In-situ XPS and density functional theory (DFT) calculations confirmed the existence of S-scheme heterojunction. This study provided a new pathway for simultaneously achieving organic pollutant treatment and energy conversion. The S-scheme heterojunction constructed from Zn 3 In 2 S 6 and ReS 2 achieves efficient charge carrier separation and enhanced redox capability, thereby facilitating the augmented synergistic effect of ibuprofen degradation and hydrogen generation. • Novel bifunctional ZIS/ReS 2 photocatalyst was successfully constructed. • The formed S-scheme heterojunction promoted efficient charge separation. • ZIS/ReS 2 exhibits enhanced photocatalytic activity for IBP degradation and H 2 generation. • The interface reaction mechanism and IBP degradation pathways were revealed.
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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) | 0.001 | 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".