Water-splitting photoelectrodes consisting of heterojunctions of carbon nitride with a <i>p</i> -type low bandgap double perovskite oxide
Bibliographic record
Abstract
Abstract Quinary and senary non-stoichiometric double perovskites such as Ba 2 Ca 0.66 Nb 1.34− x Fe x O 6− δ (BCNF) have been utilized for gas sensing, solid oxide fuel cells and thermochemical CO 2 reduction. Herein, we examined their potential as narrow bandgap semiconductors for use in solar energy harvesting. A cobalt co-doped BCNF, Ba 2 Ca 0.66 Nb 0.68 Fe 0.33 Co 0.33 O 6− δ (BCNFCo), exhibited an optical absorption edge at ∼800 nm, p -type conduction and a distinct photoresponse up to 640 nm while demonstrating high thermochemical stability. A nanocomposite of BCNFCo and g-C 3 N 4 (CN) was prepared via a facile solvent-assisted exfoliation/blending approach using dichlorobenzene and glycerol at a moderate temperature. The exfoliation of g-C 3 N 4 followed by wrapping on perovskite established an effective heterojunction between the materials for charge separation. The conjugated 2D sheets of CN enabled better charge migration resulting in increased photoelectrochemical performance. A blend composed of 40 wt% perovskites and CN performed optimally, whilst achieving a photocurrent density as high as 1.5 mA cm −2 for sunlight-driven water-splitting with a Faradaic efficiency as high as ∼88%.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".