High-Efficiency CMOS Charge Pump for Ultra-Low Power RF Energy Harvesting Applications
Bibliographic record
Abstract
This paper explicates the design and implementation of a switch capacitor DC-DC converter system for Radio Frequency (RF) energy harvesting applications for an input voltage in the sub-150mV range, using 180-nm CMOS triple-well BCD technology. The proposed system incorporates a charge pump architecture that employs an improvised Dynamic Gate Biasing (DGB), Forward and Reverse Body Bias technique (FRBB), along with a time axis symmetrical clocking scheme implemented using an advanced bootstrapped CMOS driver to enhance the overall drive capability of the system at low input voltages. Post-layout extracted simulations demonstrate that the proposed system achieves higher overall efficiency, delivering a peak Power Conversion Efficiency (PCE) of 85.8% at 125mV input voltage, outperforming other state-of-the-art architectures in similar voltage ranges. Moreover, the proposed system exhibits reliable operation even at input voltages as low as 85mV, while maintaining good overall efficiency.
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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 | 0.000 | 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".