Printed Fractal Folded Coplanar-strips-fed Array Rectenna for IoE Applications
Bibliographic record
Abstract
This paper presents a low-cost antenna integrable to a large set of indoor common building materials.Employing the printing technology on thin transparent polyethylene terephthalate material and using available building materials not only leads to a low-cost environmentally friendly solution for the expected massive sensor deployment but also eliminates the dispersive behavior of the materials that are interacting with them.A coplanar-strips fed fractal folded antenna element was designed and validated experimentally with four different materials including gypsum, plywood, and plexiglass.The aesthetically viable ground-free antenna achieves wideband performance and radiates in the broadside plane perpendicularly to the wall.The single antenna element covers the frequency band of 2.18-3.96GHz with a gain of 1 dBi at 2.4 GHz.To take advantage of the large available surface, a high efficiency 2.4 GHz array rectenna for powering electronic devices intended for IoE technology is proposed.The proposed array rectenna has a dimension of 384 × 354 × 6.475 mm 3 and employs a single diode as the rectifier element.The measured results for the presented array rectenna reveal an AC-DC powerconversion-efficiency (PCE) of more than 20% for input powers as low as 0.025 µW/cm 2 with a peak PCE of 61.3% at 4.03 µW/cm 2 .
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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".