Broadband high-efficiency dielectric metasurfaces for the visible spectrum
Bibliographic record
Abstract
Metasurfaces are planar optical elements that hold promise for overcoming the limitations of refractive and conventional diffractive optics. Original dielectric metasurfaces are limited to transparency windows at infrared wavelengths because of significant optical absorption and loss at visible wavelengths. Thus, it is critical that new materials and nanofabrication techniques be developed to extend dielectric metasurfaces across the visible spectrum and to enable applications such as high numerical aperture lenses, color holograms, and wearable optics. Here, we demonstrate high performance dielectric metasurfaces in the form of holograms for red, green, and blue wavelengths with record absolute efficiency (>78%). We use atomic layer deposition of amorphous titanium dioxide with surface roughness less than 1 nm and negligible optical loss. We use a process for fabricating dielectric metasurfaces that allows us to produce anisotropic, subwavelength-spaced dielectric nanostructures with shape birefringence. This process is capable of realizing any high-efficiency metasurface optical element, e.g., metalenses and axicons.
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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) | 0.001 | 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".