0D–2D Quantum Dot: Metal Dichalcogenide Nanocomposite Photocatalyst Achieves Efficient Hydrogen Generation
Bibliographic record
Abstract
Hydrogen generation via photocatalysis‐driven water splitting provides a convenient approach to turn solar energy into chemical fuel. The development of photocatalysis system that can effectively harvest visible light for hydrogen generation is an essential task in order to utilize this technology. Herein, a kind of cadmium free Zn–Ag–In–S (ZAIS) colloidal quantum dots (CQDs) that shows remarkably photocatalytic efficiency in the visible region is developed. More importantly, a nanocomposite based on the combination of 0D ZAIS CQDs and 2D MoS2 nanosheet is developed. This can leverage the strong light harvesting capability of CQDs and catalytic performance of MoS2 simultaneously. As a result, an excellent external quantum efficiency of 40.8% at 400 nm is achieved for CQD‐based hydrogen generation catalyst. This work presents a new platform for the development of high‐efficiency photocatalyst based on 0D–2D nanocomposite.
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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".