MOF‐Derived In<sub>2</sub>O<sub>3</sub>/CuO p‐n Heterojunction Photoanode Incorporating Graphene Nanoribbons for Solar Hydrogen Generation
Bibliographic record
Abstract
Abstract Solar‐driven photoelectrochemical (PEC) water splitting is a promising approach toward sustainable hydrogen (H 2 ) generation. However, the design and synthesis of efficient semiconductor photocatalysts via a facile method remains a significant challenge, especially p‐n heterojunctions based on composite metal oxides. Herein, a MOF‐on‐MOF (metal‐organic framework) template is employed as the precursor to synthesize In 2 O 3 /CuO p‐n heterojunction composite. After incorporation of small amounts of graphene nanoribbons (GNRs), the optimized PEC devices exhibited a maximum current density of 1.51 mA cm −2 (at 1.6 V vs RHE) under one sun illumination (AM 1.5G, 100 mW cm −2 ), which is approximately four times higher than that of the reference device based on only In 2 O 3 photoanodes. The improvement in the performance of these hybrid anodes is attributed to the presence of a p‐n heterojunction that enhances the separation efficiency of photogenerated electron‐hole pairs and suppresses charge recombination, as well as the presence of GNRs that can increase the conductivity by offering better path for electron transport, thus reducing the charge transfer resistance. The proposed MOF‐derived In 2 O 3 /CuO p‐n heterojunction composite is used to demonstrate a high‐performance PEC device for hydrogen generation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".