High-efficiency CMOS rectifier dedicated for multi-band ambient RF energy harvesting
Bibliographic record
Abstract
Several rectifier topologies dedicated for radio frequency (RF) energy harvesting have been proposed, but only a few have been reported to be able to harvest RF energy at low input power (LIP) levels. In this paper, we are focusing on fully gate cross-coupled (FGCC) rectifier structure, which gives good performance at LIP levels. In order to get an enough high output DC voltage, a 3-stage FGCC rectifier using low-threshold-voltage (LTV) transistors is designed. According to simulation results, with 850MHz input AC signal, the designed rectifier has power conversion efficiency (PCE) of 70% at 20μW (-17.0dBm) input power with 100kOhms load. Also, a multi-band RF energy harvesting topology is proposed. Simulation results show that PCE of the tri-channel rectifier achieves 66.3% at 4.8μW (-23.2dBm) input power per channel and 1V DC output voltage is generated at 5.1μW (-22.9dBm) input power per channel with only 100kOhms load, showing both high-efficiency and sensitivity.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".