16.8 nW Ultra-Low-Power Energy Harvester IC for Tiny Ingestible Sensors Sustained by Bio-Galvanic Energy Source
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Bibliographic record
Abstract
Herein, we present a 16.8 nW ultra-low-power (ULP) energy harvester integrated circuit (IC) for ingestible biomedical sensors. The energy harvester can be powered from the electro-galvanic operation inside a human body, which provides a sustainable and long-term energy source. The challenge of dealing with relatively high input impedance (~kΩ) of the bio-galvanic energy source is addressed by introducing two design techniques. The first technique is an adaptive V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MPP</sub> -controlled algorithm (AVCA) for a maximum power point tracking (MPPT) controller, and the second technique is a ULP delay-line-based zero current switching (ZCS) controller. Different from the conventional fractional open-circuit voltage (FOCV) method for MPPT, the proposed AVCA allows continuous source tracking without detachment of the harvester from the source. The ZCS operation is achieved using a delay-line controller without using either a comparator or an opamp. The proposed AVCA is realized using a 12.1 nW MPPT controller. Successful ZCS operation is achieved using a 2.1 nW delay controller. Overall power consumption of the IC is 16.8 nW. The converter has been fabricated in a 0.18 μm CMOS process with 2 μm thick top-metal option. The measured result shows that the converter achieves a peak efficiency of 72.1% to generate 507 nW output power. The ULP operation allows a significant reduction in electrode size down to the submillimeter scale (~0.4 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), demonstrating the good potential of the proposed energy harvester IC.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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