Synthesis and Surface Modification of Poly (dimethylsiloxane) - Gold Nanocomposite Films for Biosensing Applications
Bibliographic record
Abstract
Gold - poly(dimethylsiloxane) (Au - PDMS) nanocomposite freestanding films were prepared and used to study the binding of Human Serum Albumin (HSA) to polyclonal anti-HSA. A new method of synthesis was developed for sensing application when most of the gold nanoparticles have to be localized in the surface layer. The localized surface plasmon resonance band in gold nanoparticles is used to monitor the binding reaction. SEM and AFM images as well as the UV- Visible spectrum have shown that incubating the PDMS film in a diluted solution of chloroauric acid for 18 hours results in a good dispersion of gold nanoparticles on the polymer surface, without aggregation. The kinetics of the formation of Au-PDMS is studied by UV-Visible spectroscopy. Biosensing experiments carried out with the Au-PDMS composite showed a good sensitivity allowing the detection of 2.5 mg of antigen. Compared to the previous methods of fabrication, the present technique has the advantage of simplicity; the structures can be prepared under mild conditions and without using an external capping agent. The method is suitable for microfluidic sensing applications for a variety of biomolecules.
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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".