Temperature-Stable Low-Power RF-to-DC Dickson Charge Pump Rectifiers for Battery-Free Sensing and IoT Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Temperature variation poses a significant challenge for battery-free sensors and Internet of Things (IoT) systems, mainly due to the absence of built-in temperature compensation modules. This work presents a strategy to identify Schottky diodes for low-power RF-to-dc Dickson charge pump (DCP) rectifiers to enhance temperature stability. Theoretical analysis pinpoints that performance degradation in dynamic temperatures results from the mismatch loss between diode nonlinear junction resistance and load resistance. The analytical method is implemented to synthesize the optimum number of stages and identify suitable Schottky diodes for low-power RF-to-dc DCP rectifiers. Experimental measurements demonstrate that the SMS7621-based 3-stage RF-to-dc DCP rectifier maintains a wide matched operating temperature range from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$- 32.5~^{\circ }$ </tex-math></inline-formula>C to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$70~^{\circ }$ </tex-math></inline-formula>C. Further experiments show that its dc output voltage remains above 3.2 V across a wide temperature range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$- 40~^{\circ }$ </tex-math></inline-formula>C to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$80~^{\circ }$ </tex-math></inline-formula>C when the RF input is −8 dBm, which can drive a commercial wireless sensor board. This work aims to serve as a benchmark for developing reliable low-power RF-to-dc DCP rectifiers that meet various operating temperature requirements of battery-free IoT sensors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it