Real-Time Microwave Sensing with Engineered Electromagnetic Passive Tag Coupled to UWB Antenna
Bibliographic record
Abstract
This study introduces a novel passive microwave sensor integrated with an ultra-wideband (UWB) coplanar antenna for real-time sensing. The passive tag consists of a twolayer structure interconnected by vias, where the bottom layer operates as a non-resonant surface, and the top layer serves as a resonator. This unique design enhances sensing performance by enabling precise manipulation of the electric field and sensing region, while also extending the operating distance by increasing the absorbance rate of the passive tag. Simulations reveal that the proposed design for small amounts of material changes achieves a frequency shift of 104 MHz and a maximum effective coupling distance of 18 mm, outperforming conventional designs with a frequency shift of 24 MHz and a coupling distance of 7 mm. Measurements on a fabricated prototype further validate its high sensitivity, with the sensor demonstrating a 2.125 MHz frequency shift when detecting a$250 \mu \mathrm{L}$sample of deionized water compared to acetone, highlighting the potential of the proposed design for biomedical scenarios requiring minimal sample quantities.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".