Design of rectenna series‐association circuits for radio frequency energy harvesting in CMOS FD‐SOI 28 nm
Bibliographic record
Abstract
Series‐connected rectenna associations are proposed to improve the harvesting performance of conventional rectenna circuits by recovering power from different directions. With an available input power of −20 dBm, post‐layout simulations evaluated the total output power of four series‐connected rectennas designed in Complementary Metal Oxide Semiconductor Fully Depleted Silicon On Insulator (CMOS FD‐SOI) 28 nm technology, to 14 µW at maximum power point (MPP), while the post‐layout simulation of a single rectenna yields 5 µW at the same input power level. However, the rectenna association performance may be significantly degraded when dealing with different input power levels among rectennas. Therefore, a passive bypass circuit has been added at the output of the series association to short‐circuit the weakest rectenna. The proposed design is cost‐effective since there is a negligible silicon penalty and no additional power losses. In the designed four series‐connected rectenna association, the total output power is 7 µW at MPP with the bypass circuit when the strongest and the weakest rectennas receive −20 and −35 dBm, respectively. Also, thanks to the bypass circuit, the efficiency of the rectenna association and the ratio of maximum achieved power are improved by, respectively, 10 and 20%.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".