Wide-angle, wide-band, polarization-insensitive metamaterial absorber for thermal energy harvesting
Bibliographic record
Abstract
We propose a wide-band metamaterial perfect absorber (MPA), using the coupling in the near-field of a quadruple split-ring resonator concentric with crossed ellipses. We designed the MPA with a metal-insulator-metal (MIM) structure for use in thermal energy harvesting. A gradient-based optimization approach was carried out to maximize the absorption of infrared (IR) radiation around 10 μm. Owing to the near-field coupling of resonators with optimal design parameters, the peaks of the absorption responses approach each other, thus broadening the overall bandwidth with almost unity absorptivity. The proposed design has a resonance at 10 μm resulting from magnetic polaritons (MPs) and thus maintains high absorption above 99% up to a range of incident-angles greater than 60° and exhibits a polarization-free behavior due to symmetry. When the optimal design was numerically examined to fabrication tolerances, it showed negligible sensitivities in the absorptivity with respect to design parameters. The strong electric field enhancement inside the split-ring gaps and between the ends of the cross arms and the surrounding ring enables designing MIM diodes to rectify the harvested thermal radiations at 288 K. MIM diodes can be built by the deposition of thin insulators to sit in these gaps. The MIM diode and MPA work together to harvest and rectify the incident IR radiation in a manner similar to the operation of rectennas. The MPA outperforms the traditional nano-antennas in impedance matching efficiency because of its higher resistance. Also, its dual-polarization reception capability doubles the rectenna efficiency. Our proposed MPA retained absorptivity more than 99% when coupled with MIM diodes whose resistances are in the range of 500 Ω-1 MΩ.
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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".