Extreme IR absorption in group IV-SiGeSn core-shell nanowires
Bibliographic record
Abstract
Sn-containing Si and Ge (Ge1-y-xSixSny) alloys are an emerging family of semiconductors with the potential to impact group IV material-based devices. These semiconductors provide the ability to independently engineer both the lattice parameter and bandgap, which holds the premise to develop enhanced or novel photonic and electronic devices. With this perspective, we present detailed investigations of the influence of Ge1-y-xSixSny layers on the optical properties of Si and Ge based heterostructures and nanowires. We found that by adding a thin Ge1-y-xSixSny capping layer on Si or Ge greatly enhances light absorption especially in the near infrared range, leading to an increase in short-circuit current density. For the Ge1-y-xSixSny structure at thicknesses below 30 nm, a 14-fold increase in the short-circuit current is observed with respect to bare Si. This enhancement decreases by reducing the capping layer thickness. Conversely, decreasing the shell thickness was found to improve the short-circuit current in Si/Ge1-y-xSixSny and Ge/Ge1-y-xSixSny core/shell nanowires. The optical absorption becomes very important by increasing the Sn content. Moreover, by exploiting an optical antenna effect, these nanowires show extreme light absorption, reaching an enhancement factor, with respect to Si or Ge nanowires, on the order of 104 in Si/Ge0.84Si0.04Sn0.12 and 12 in Ge/Ge0.84Si0.04Sn0.12. Furthermore, we analyzed the optical response after the addition of a dielectric layer of Si3N4 to the Si/Ge1-y-xSixSny core-shell nanowire and found approximatively a 50% increase in the short-circuit current density for a dielectric layer of thickness equal to 45 nm and both a core radius and a shell thickness greater than 40 nm. The core−shell optical antenna benefits from a multiplication of enhancements contributed by leaky mode resonances in the semiconductor part and antireflection effects in the dielectric part.
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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".