Few-Atomic-Layers Iron for Hydrogen Evolution from Water by Photoelectrocatalysis
Bibliographic record
Abstract
The carbon-free production of hydrogen from water splitting holds grand promise for the critical energy and environmental challenges. Herein, few-atomic-layers iron (Fe FAL ) anchored on GaN nanowire arrays (NWs) is demonstrated as a highly active hydrogen evolution reaction catalyst, attributing to the spatial confinement and the nitrogen-terminated surface of GaN NWs. Based on density functional theory calculations, the hydrogen adsorption on Fe FAL :GaN NWs is found to exhibit a significantly low free energy of −0.13 eV, indicative of high activity. Meanwhile, its outstanding optoelectronic properties are realized by the strong electronic coupling between atomic iron layers and GaN(10ī0) together with the nearly defect-free GaN NWs. As a result, Fe FAL :GaN NWs/n + -p Si exhibits a prominent current density of ∼ −30 mA cm −2 at an overpotential of ∼0.2 V versus reversible hydrogen electrode with a decent onset potential of +0.35 V and 98% Faradaic efficiency in 0.5 mol/L KHCO 3 aqueous solution under standard one-sun illumination.
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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 | 0.001 |
| 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".