Electrode modification and the response of the acoustic shear wave device operating in liquids
Bibliographic record
Abstract
The effect of electrode polarity, geometry, and stray capacitance on the performance of the thickness-shear mode acoustic wave sensor operating in electrolytes and solutions of biomolecules has been studied. In contrast to the well-known mass-based response of the device operating in the gas phase, the response in a liquid is governed by several factors including acoustoelectric and fringing field effects, which are known to be active at the edges of the electrodes. In order to investigate and utilize these effects, we modified the electrode geometry to increase the edge length, which, in turn, raises the sensitivity of the device. These changes which constituted either complete coverage of the back of the device with electrode material, or the removal of disks and lines from the electrode surface, resulted in a two to three times enhancement of sensor response. Such modifications that extend device sensitivity beyond the electrode area to the quartz region of the sensing structure also provide a better surface for the immobilization of various probes. We verified the enhancing ability of the modified electrodes for the case of adsorption of the protein avidin and neutravidin, followed by their affinity reactions with biotinylated biomolecules. It was found that the active electrode in contact with electrolyte exhibits a sensitivity of about twice that of the grounded electrode. The existence of stray capacitance around the cell was confirmed by shielding the cell assembly with a bath of concentrated KCl solution. This shielding effect was measured to be about 25-60 Hz in series resonant frequency and -1000 Hz in parallel resonant frequency.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".