Surface properties and electromagnetic excitation of a piezoelectric gallium phosphate biosensor
Bibliographic record
Abstract
The surface properties of GaPO4 have been studied by secondary ion mass spectrometry, X-ray photoelectron spectroscopy and electromagnetic acoustic wave excitation in order to explore the potential of this relatively new piezoelectric material as a biosensor. The X-ray photoelectron spectrum of the substrate shows a Ga-rich surface (Ga:P = 1.4), while the negative secondary ion mass spectrum is similar to that of other phosphates, with PO3- and PO2- being the main fragments derived from the substrate. Surface analysis reveals that the linker protein for biotinylated moieties, neutravidin, is both readily chemisorbed to bare gallium phosphate at pH 7.5 and attached to p-hydroxy benzaldehyde-treated devices, establishing the possibility to exploit the surface chemistry of the phosphate for the fabrication of an electrode-free acoustic wave biosensor. Preliminary results regarding the detection of the adsorption of neutravidin with an electromagnetic field-excited GaPO4 device incorporated in a FIA configuration showed comparable results with those obtained with a quartz-sensor equivalent. The frequency shift for the adsorbed protein layer at the device fundamental frequency was 200 Hz and the noise was routinely around 13 Hz. The possibility to use the electrodeless acoustic GaPO4 device at higher harmonics in the liquid phase has also been confirmed.
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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 | 0.000 |
| 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 | 0.000 |
| 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".