Temperature Compensated Dielectric Constant Sensor Using Dual-Mode Triangular Structure
Bibliographic record
Abstract
An aperture-coupled dual-mode triangular resonator (DMTR) sensor is presented for measuring sample under test (SUT) dielectric constant in real-time. Using this structure, it is possible to compensate for temperature variations without adding any components or circuits to the main resonator. With a specially designed slot in the middle, the proposed triangular resonator can provide two separate resonance frequencies: the lower frequency (${F}{2}$) is used for sensing, while the upper frequency (${F}{1}$) can be used for calibration purposes and temperature compensation. Changing the material in contact with the slot only affects${F}{2}$, while${F}{1}$remains the same. A sample structure is designed and fabricated to evaluate the performance of the proposed DMTR sensor. The measurement results indicate negligible changes at${F}{1}$equal to 2.425 GHz, providing an acceptable calibration frequency in the industrial, scientific and medical (ISM) band. In contrast, the sample-dependent band around 2.36 GHz shifts frequency by 1.6 MHz per unit dielectric constant for samples with permittivity ranging from 1.0 to 6.15. Loss tangents of up to 0.01 are also found to have no significant effect on frequency response. Temperature analysis reveals the sensor’s compensation capability. The frequency difference between${F}{1}$and${F}{2}$for any SUT remains constant over a wide temperature range from$- 40\,\,^{\circ} \text{C}$to$140 ^{\circ} \text{C}$. As a result, the frequency difference variations depend solely on the dielectric constant of the SUT at any given operating temperature.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".