Planar Sensing Platform Based on Split Ring Resonators and Microstrip Yagi-Uda Antennas
Bibliographic record
Abstract
Exciting microwave split ring resonators (SRRs) with an adjacent transmission line (TL) can put additional loading effect on the resonant characteristics and compromise the selectivity and resolution of SRR sensors. This work presents an alternative approach that reduces the near-field coupling of SRRs (to TL probes), by positioning them in Fresnel zone of two printed Yagi-Uda antennas, leading to a reduction in the loading effects of external coupling/probing circuitry. Therefore, the need for TLs is eliminated and the impact of external circuitry on the sensing performance is reduced. To achieve a small footprint, the overall sensing platform, including the SRRs, antennas, and director elements, was designed at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K} _{u}$ </tex-math></inline-formula> band and integrated on a single substrate of size <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$151\times 60\times0.7$ </tex-math></inline-formula> mm3. Experimental results indicated that for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6\times6$ </tex-math></inline-formula> mm solid samples, the sensitivity of the resonant frequency to permittivity variations was 69.19 MHz/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\varepsilon }^{\prime }$ </tex-math></inline-formula> . For liquid samples (0%–95% v/v aqueous-ethanol mixtures), the highest monitored sensitivity of the resonant amplitude was <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula> 1.6 dB/% of change in the ethanol concentration. These measurements demonstrated the dependency of the sensor’s <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\vert {S}_{{21}}\vert $ </tex-math></inline-formula> (dB) parameters on the dielectric properties of the samples. The proposed method proves advantageous for implementing a low profile, planar sensing platform, with an excitation mechanism that eliminates TL coupling (to resonators).
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".