One-Step Overall Water Splitting under Visible Light Using Multiband InGaN/GaN Nanowire Heterostructures
Bibliographic record
Abstract
The conversion of solar energy into hydrogen via water splitting process is one of the key sustainable technologies for future clean, storable, and renewable source of energy. Therefore, development of visible light-responsive and efficient photocatalyst material has been of immense interest, but with limited success. Here, we show that overall water splitting under visible-light irradiation can be achieved using a single photocatalyst material. Multiband InGaN/GaN nanowire heterostructures, decorated with rhodium (Rh)/chromium-oxide (Cr2O3) core-shell nanoparticles can lead to stable hydrogen production from pure (pH ∼ 7.0) water splitting under ultraviolet, blue and green-light irradiation (up to ∼560 nm), the longest wavelength ever reported. At ∼440-450 nm wavelengths, the internal quantum efficiency is estimated to be ∼13%, the highest value reported in the visible spectrum. The turnover number under visible light well exceeds 73 in 12 h. Detailed analysis further confirms the stable photocatalytic activity of the nanowire heterostructures. This work establishes the use of metal-nitrides as viable photocatalyst for solar-powered artificial photosynthesis for the production of hydrogen and other solar fuels.
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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".