PDMS-Gold Nanocomposite Platforms with Enhanced Sensing Properties
Bibliographic record
Abstract
Gold-poly(dimethyl siloxoxane) (Au-PDMS) nanocomposite films with a high elasticity were fabricated for sensing experiments. The nanocomposite was prepared by a novel in-situ method by using the ethanol solution of the chloroauric acid. The high rate of permeation of ethanol in the polymer film, compared to an aqueous solution, allows the introduction of the gold precursor into the polymer network with a higher rate and, thus the reduction reaction is accelerated. The strong hydrophobicity of the as-prepared films precludes the diffusion of aqueous solutions of biomolecules in the polymer network, essential for sensing purposes. In order to modify the morphology and the surface properties of the samples, they have been heat-treated and the polymer network has been expanded mechanically by repeated swellings and shrinkages. As a result, the free volume of the polymer is increased substantially and thus, the biosensing capability of the material is improved. The effect of gold nanoparticles on the porosity and the mechanical properties of the material has been studied. The highest value of the sensitivity (around 70 nm/RIU) has been obtained for the samples that were annealed and, subsequently swollen in toluene. Biosensing experiments involving antigen-antibody interactions showed a high sensitivity. The results of this work are relevant for sensing in a microfluidic environment.
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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 | 0.000 | 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 | 0.001 |
| 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".