Tailored Interfaces of the Bulk Silicon Nanowire/TiO<sub>2</sub>Heterojunction Promoting Enhanced Photovoltaic Performances
Bibliographic record
Abstract
thin film atop vertically aligned silicon nanowire arrays obtained by facile metal-assisted wet electroless chemical etching of a bulk highly doped n-type silicon wafer. As we show here, chemical treatment of the nanowire arrays prior to depositing the sol-gel precursor has dramatic consequences on the device performance. While hydrofluoric treatment to remove the native oxide already improves significantly the device performances, hydrobromic (HBr) treatment consistently yields by far the best device performances with power conversion efficiencies ranging between 4.2 and 6.2% with fill factors up to 60% under AM 1.5G illumination. In addition to yield high-quality and easy to produce solar cell devices, these findings regarding the surface treatment of silicon nanowires with HBr suggest that HBr could contribute to the enhancement of the device performance not only for solar cells but also for other optoelectronics devices based on semiconductor nanostructures.
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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".