Boosting photoelectrochemical efficiency by near-infrared-active lattice-matched morphological heterojunctions
Bibliographic record
Abstract
Photoelectrochemical catalysis is an attractive way to provide direct hydrogen production from solar energy. However, solar conversion efficiencies are hindered by the fact that light harvesting has so far been of limited efficiency in the near-infrared region as compared to that in the visible and ultraviolet regions. Here we introduce near-infrared-active photoanodes that feature lattice-matched morphological hetero-nanostructures, a strategy that improves energy conversion efficiency by increasing light-harvesting spectral range and charge separation efficiency simultaneously. Specifically, we demonstrate a near-infrared-active morphological heterojunction comprised of BiSeTe ternary alloy nanotubes and ultrathin nanosheets. The heterojunction's hierarchical nanostructure separates charges at the lattice-matched interface of the two morphological components, preventing further carrier recombination. As a result, the photoanodes achieve an incident photon-to-current conversion efficiency of 36% at 800 nm in an electrolyte solution containing hole scavengers without a co-catalyst.
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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".