Coupled Resonance Energy Transfer Over Gigahertz Frequency Range Using Ceramic Filled Cavity for Medical Implanted Sensors
Bibliographic record
Abstract
A wireless power transmission (WPT) system based on a magnetically coupled coil-based resonance is the predominating technology in most WPT applications. In the field of implantable medical devices, however, the energy transfer operation is highly limited by the size of the receiver and also the loss properties of dispersive human tissue. Since the low gigahertz range has been considered as the optimal transfer frequency, an alternative to the lossy coil resonator should be studied and developed. In this paper, an original transmitter solution is presented that considers the needs for strong magnetic dominant near-field and weak far-field radiation even at low gigahertz frequency. A half-closed partially ceramic-filled cavity resonator is described on the basis of an accurate, but analytical model. Design parameters are also studied using a full-wave simulation software package and measurement results of a resonator-to-resonator transfer scheme are presented, which show a good agreement with simulation results. An efficiency above 65% can be obtained within the distance comparable to the diameter of the resonator (60.5 mm) in this case study. Subsequently, energy transmission between the proposed cavity resonator and a small-sized copper coil of 3 mm of diameter is investigated. Measurement results show that the efficiency is above 34% within 20 mm and above 8.2% within 40 mm, which is much higher than the conventional coil-to-coil transmission scheme.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".