Molecular beam epitaxial growth, fabrication, and characterization of InN/Si nanowire heterojunction solar cells
Bibliographic record
Abstract
We report on the molecular beam epitaxial growth, fabrication, and characterization of InN/Si nanowire heterojunction solar cells. Vertically aligned <i>p</i>-doped-intrinsic-<i>n</i>-doped (<i>p-i-n</i>) InN nanowires spontaneously formed on <i>n</i>-type Si(111) substrates as well as <i>n-i</i> InN nanowires spontaneously formed on <i>p</i>-Si(111) were demonstrated. With the use of an <i>in situ</i> deposited In seeding layer, such InN nanowires exhibit non-tapered morphology. InN nanowire solar cells display a rectifying ratio of larger than 1,000 under dark, which provides a strong evidence of successful <i>p</i>-doping of InN nanowires. We measured a short-circuit current density of ~ 85 mA/cm<sup>2</sup> and a power conversion efficiency of ~ 1.62% under AM 1.5G illumination at approximately 100 mW/cm<sup>2</sup>. Further improvement in the device performance is being investigated by optimizing the growth and fabrication process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".