Measurement of the electric permittivity using Bleustein–Gulyaev wave sensor
Bibliographic record
Abstract
Abstract We present a novel compact electric permittivity sensor that exploits Bleustein–Gulyaev waves propagating along the surface of shear-poled piezoelectrics. We formulate the dynamic nonlinear electromechanical partial differential equations of motion governing wave propagation under electromagnetically quasistatic conditions. The permittivity of the medium-under-test was found to influence the sensor eigenvalues, enabling the implementation of a frequency-shift permittivity sensor. Solution of the equations of motion demonstrates resonance of the first and third modes when excited using an interdigitated transducer. We fabricated two sensor prototypes on shear-poled PZT4 and LiNbO 3 substrates and used a Vector Network Analyzer to observe the shift in their fundamental natural frequency in the presence of various media-under-test. S 11 measurements show deterministic and repeatable shifts in the resonant frequency of the first mode of the LiNbO 3 sensor measured at <?CDATA $\Delta f_1 = 3.51$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi mathvariant="normal">Δ</mml:mi> <mml:msub> <mml:mi>f</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>=</mml:mo> <mml:mn>3.51</mml:mn> </mml:math> MHz for ethanol and <?CDATA $\Delta f_1 = 7.49$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi mathvariant="normal">Δ</mml:mi> <mml:msub> <mml:mi>f</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>=</mml:mo> <mml:mn>7.49</mml:mn> </mml:math> MHz for deionized water where the bare surface frequency was initially at <?CDATA $f_1 = 25.27$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mi>f</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>=</mml:mo> <mml:mn>25.27</mml:mn> </mml:math> MHz.
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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 | 0.000 | 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".