Beyond Lambertian light trapping for large-area silicon solar cells: fabrication methods
Bibliographic record
Abstract
Light trapping photonic crystal (PhC) patterns on the surface of Si solar cells provides a novel opportunity to approach the theoretical efficiency limit of 32.3%, for light-to-electrical power conversion with a single junction cell. This is beyond the efficiency limit implied by the Lambertian limit of ray trapping ~ 29%. The interference and slow light effects are harnessed for collecting light even at the long wavelengths near the Si band-gap. We compare two different methods for surface patterning, that can be extended to large area surface patterning: 1) laser direct write and 2) step-&-repeat 5× reduction projection lithography. Large area throughput limitations of these methods are compared with the established electron beam lithography (EBL) route, which is conventionally utilised but much slower than the presented methods. Spectral characterisation of the PhC light trapping is compared for samples fabricated by different methods. Reflectance of Si etched via laser patterned mask was ~ 7% at visible wavelengths and was comparable with Si patterned via EBL made mask. The later pattern showed a stronger absorbance than the Lambertian limit. (M.-L. Hsieh et al., Sci. Rep. 10, 11857 (2020)).
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".