Achieving an Accurate Surface Profile of a Photonic Crystal for Near-Unity Solar Absorption in a Super Thin-Film Architecture
Bibliographic record
Abstract
In this work, a teepee-like photonic crystal (PC) structure on crystalline silicon (c-Si) is experimentally demonstrated, which fulfills two critical criteria in solar energy harvesting by (i) its Gaussian-type gradient-index profile for excellent antireflection and (ii) near-orthogonal energy flow and vortex-like field concentration via the parallel-to-interface refraction effect inside the structure for enhanced light trapping. For the PC structure on 500-μm-thick c-Si, the average reflection is only ∼0.7% for λ = 400-1000 nm. For the same structure on a much thinner c-Si ( t = 10 μm), the absorption is near unity (A ∼ 99%) for visible wavelengths, while the absorption in the weakly absorbing range (λ ∼ 1000 nm) is significantly increased to 79%, comparing to only 6% absorption for a 10-μm-thick planar c-Si. In addition, the average absorption (∼94.7%) of the PC structure on 10 μm c-Si for λ = 400-1000 nm is only ∼3.8% less than the average absorption (∼98.5%) of the PC structure on 500 μm c-Si, while the equivalent silicon solid content is reduced by 50 times. Furthermore, the angular dependence measurements show that the high absorption is sustained over a wide angle range (θinc = 0-60°) for teepee-like PC structure on both 500 and 10-μm-thick c-Si.
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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 | 0.001 |
| 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".