A 32-mV Supply Ring Oscillator Composed of Modified Schmitt Trigger Delay Cells for Integrated Start-Up Circuits in DC Energy Harvesting Systems
Bibliographic record
Abstract
Implementing fully integrated start-up energy harvesting (EH) systems is very challenging. The most popular start-up circuit implementations use a low-voltage ring oscillator (RO). The characteristics of this RO rapidly deteriorate at VDD values below the transistor’s threshold voltage. A novel delay cell based on a Schmitt trigger (ST) inverter leveraging dynamic body biasing (DBB) is proposed to mitigate this deterioration. The RO of the proposed cell, implemented in a 22 nm FD-SOI CMOS technology, is compared against conventional and state-of-the-art circuits implemented in the same technology. Simulated results show the proposed RO achieves the highest output swing and DC gain within the 40 to 100 mV supply voltage range. A prototype chip comprising a 27-stage RO was fabricated and tested in a 22 nm FD-SOI CMOS technology. When fed by a 50 mV supply voltage, this RO produces an output swing of$\mathbf {80\%}$of that voltage while oscillating at a 0.8 kHz clock frequency and consuming 300 pW. In reported experiments, oscillations started with VDD as low as 32 mV. To the authors’ knowledge, the proposed CMOS RO operates with the second-lowest ever reported supply voltage. Combining its low power and low area, this RO is most suitable for EH systems with restricted power and area budget.
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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) | 0.003 | 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".