Intriguing type-II g-GeC/AlN bilayer heterostructure for photocatalytic water decomposition and hydrogen production
Bibliographic record
Abstract
Abstract Adapting two-dimensional (2D) van der Walls bilayer heterostructure is an efficient technique for realizing fascinating properties and playing a key role in solar energy-driven water decomposition schemes. By means of first-principles calculations, this study reveals the intriguing potential of a novel 2D van der Walls hetero-bilayer consisting of GeC and AlN layer in the photocatalytic water splitting method to generate hydrogen. The GeC/AlN heterostructure has an appropriate band gap of 2.05 eV, wherein the band edges are in proper energetic positions to provoke the water redox reaction to generate hydrogen and oxygen. The type-II band alignment of the bilayer facilitates the real-space spontaneous separation of the photogenerated electrons and holes in the different layers, improving the photocatalytic activity significantly. Analysis of the electrostatic potential and the charge density difference unravels the build-up of an inherent electric field at the interface, preventing electron–hole recombination. The ample absorption spectrum of the bilayer from the ultra-violet to the near-infrared region, reaching up to 8.71 × 10 5 /cm, combined with the resiliency to the biaxial strain, points out the excellent photocatalytic performance of the bilayer heterostructure. On top of rendering useful information on the key features of the GeC/AlN hetero-bilayer, the study offers informative details on the experimental design of the van der Walls bilayer heterostructure for solar-to-hydrogen conversion applications.
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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) | 0.001 | 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".