Enhancing Solar‐Driven Water Splitting with Surface‐Engineered Nanostructures
Bibliographic record
Abstract
Functional nanoscale interfaces that promote the transport of photoexcited charge carriers are fundamental to efficient hydrogen production during photoelectrochemical (PEC) splitting of water. Here, the realization of a functional one‐dimensional nanostructure achieved through surface engineering of hematite (α‐Fe2O3) nanorods with a TiO2 overlayer is reported. The surface‐engineered hematite nanostructure exhibits significantly improved PEC performance as compared to untreated α‐Fe2O3, with an increase in the maximum incident photon‐to‐current efficiency (IPCE) of nearly 400% at 350 nm. While addition of the TiO2 overlayer did not alter the lifetime of photoexcited charge carriers, as evidenced from transient absorption spectroscopy, it is found that the presence of TiO2 could enhance oxygen electrocatalysis by interfacial electron enrichment, largely attributed to enhanced O(2p)−Fe(3d) hybridization. Moreover, the interfacial electronic structure revealed from XANES measurements of the α‐Fe2O3/TiO2 nanorods suggests that photoexcited holes in α‐Fe2O3 may efficiently transfer through the TiO2 overlayer to the electrolyte while electrons migrate to the external circuit along the one‐dimensional nanorods, thereby promoting charge separation and enhancing PEC splitting of 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".