Interfacial Properties and the Response of the Transverse Acoustic Wave Device in Electrolytes
Bibliographic record
Abstract
An analysis of electrical effects associated with the operation of thickness-shear-mode acoustic wave sensors in liquid is presented. A frequent observation found for this system is that the magnitude and the sign of frequency changes cannot be explained by the previously developed mass- and the viscous-loading formulations. These discrepancies are attributed, in part, to the electric properties of the liquid layers in the vicinity of the device electrode. Using network analysis, the resonance frequencies and the equivalent circuit parameters of the device were monitored for a variety of electrolytes in the concentration range 1 to 3000 mM. A nonlinear and periodic dependence was found between both the series resonance frequency and the motional resistance parameter of the device with respect to concentration of electrolyte. Unlike the case of viscous-loading of the sensor, which is known to exhibit a linear and inversely proportional relationship between frequency change and motional resistance, the electrolyte loading of the device yields an unexpected spiral dependence of the two quantities. The spiral dependence provides further proof for the periodicity of the dependence of the series resonance frequency and motional resistance parameter on electrolyte concentration. This finding has important implications for the development of acoustic wave biosensors, since solutions of biochemical species usually involve electrolytes of variable composition, which may affect the electrical double layer structure and, in turn, the response of the sensor.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".