Interface Engineering between Photocatalyst and Cocatalyst: A Strategy for Enhancing Interfacial Charge Transfer and Water Oxidation of Layered Oxyhalides
Bibliographic record
Abstract
Loading cocatalysts on photocatalysts is essential to enhance photocatalytic activity; however, the charge transfer from the photocatalyst to cocatalyst often governs the overall efficiency of the reactions. Nevertheless, their interface remains elusive and poses challenges for proactive control. The current study addresses the interface engineering to improve the O 2 evolution activity of oxyhalide photocatalysts by leveraging the unique band structures. Utilizing an oxyhalide Bi 4 NbO 8 Cl as a model photocatalyst, in which DFT calculations showed electrons and holes tend to accumulate in the fluorite and perovskite layer, respectively, we combined the exposure of the perovskite layer via acid treatment with the loading of water oxidation cocatalyst Ir species (hereafter denoted as IrO 2 ). This approach resulted in a 17-fold enhancement in the rate of evolution of the O 2 compared to unmodified pristine Bi 4 NbO 8 Cl. The observed O 2 evolution rate was markedly higher than that of the reported oxyhalide photocatalysts, with an apparent quantum efficiency reaching 16%. Various characterizations, including transient absorption spectroscopy, demonstrated that the significantly enhanced O 2 evolution was due to the efficient hole transfer between Bi 4 NbO 8 Cl and IrO 2, resulting from loading IrO 2 onto the perovskite layer (the hole accumulation layer) exposed through the acid treatment. By employing the surface-modified Bi 4 NbO 8 Cl as an O 2 evolution photocatalyst, we have achieved interparticle Z-scheme water splitting without any electron mediators. This research paves the way for rational control of photocatalyst-cocatalyst interface structures to improve the photocatalytic activities of various materials.
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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) | 0.001 | 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 | 0.001 |
| 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".