Multispectral absorptance from large-diameter InAsSb nanowire arrays in a single epitaxial growth on silicon
Bibliographic record
Abstract
Abstract Vertical III-V nanowires are capable of resonant absorption at specific wavelengths by tuning the nanowire diameter, thereby exceeding the absorption of equivalent thin films. These properties may be exploited to fabricate multispectral infrared (IR) photodetectors, directly integrated with Si, without the need for spectral filters or vertical stacking of heterostructures as required in thin film devices. In this study, multiple InAsSb nanowire arrays were grown simultaneously on Si by molecular beam epitaxy with nanowire diameter controlled by the nanowire period (spacing between nanowires). This is the first such study of patterned InAsSb nanowires where control of nanowire diameter and multispectral absorption are demonstrated. The antimony flux was used to control axial and radial growth rates using a selective-area catalyst-free growth method, achieving large diameters, spanning 440–520 nm, which are necessary for optimum IR absorption. Fourier transform IR spectroscopy revealed IR absorptance peaks due to the HE 11 resonance of the nanowire arrays in agreement with optical simulations. Due to the dependence of the HE 11 resonance absorption on nanowire diameter, multispectral absorption was demonstrated in a single material system and a single epitaxial growth step without the need for bandgap tuning. This work demonstrates the potential of InAsSb nanowires for multispectral photodetectors and sensor arrays in the short-wavelength IR region.
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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) | 0.000 | 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 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".