Wavelength-selective emitters with pyramid nanogratings enhanced by multiple resonance modes
Bibliographic record
Abstract
Binary gratings with high or low metal filling ratios in a grating region have been demonstrated as successful candidates in enhancing the emittance of emitters for thermophotovoltaics since they could support surface plasmons (SPs), the Rayleigh-Wood anomaly (RWA), or cavity resonance (CR) within their geometries. This work shows that combining a tungsten binary grating with a low and high filling ratio to form a pyramid grating can significantly increase the emittance, which is nearly perfect in the wavelength region from 0.6 to 1.72 μm, while being 0.1 at wavelengths longer than 2.5 μm. Moreover, the emittance spectrum of the hybrid tungsten grating is insensitive to the angle of incidence. The enhancement demonstrated by magnetic field and Poynting vector patterns is due to the interplay between SPs and RWA modes at short wavelengths, and CR at long wavelengths. Furthermore, a combined grating made of nickel is also proposed providing enhanced emittance in a wide angle of incidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".