A high-efficiency CMOS rectifier for low-power RFID tags
Bibliographic record
Abstract
In this paper, a high-efficiency highly sensitive CMOS rectifier for radio-frequency identification (RFID) tags is presented. Although the minimum RF input signal amplitude for which the rectifier operates properly is lower than the standard threshold voltage of the MOS transistors, the design uses only standard-threshold-voltage (standard-Vth) devices. Furthermore, two rectifier biasing schemes are proposed. The first biasing scheme is intended for semi-passive RFID tags and allows the tag rectifier to adjust the input power level at which the rectifier's maximum power efficiency is achieved, i.e., the rectifier circuit can be tuned to achieve its maximum power efficiency at any given input power. The second biasing scheme is for self-sufficient rectifiers used in passive tags and does not require any auxiliary power source. The rectifier is designed and laid out in a standard 0.13-¿m CMOS process and its performance is confirmed through post-layout simulations.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".