Physical Properties of Polyacrylamide/Polyvinylalcohol Silica Nanocomposites
Bibliographic record
Abstract
In this paper, samples of Polyacrylamide (PAAm) nanosilica nanocomposites were prepared having different concentration of nanosilica (0.125, 0.25, and 0.5). Polyacrylamide (PAAm) and poly (vinyl alcohol) (PVA) were blended with different ratio (3/1, 1/1, 1/3) using solution-cast technique. The prepared films were characterized by Fourier transform infrared (FTIR), X-ray diffractions (XRD) and scanning electron microscopy (SEM). FTIR spectra showed the presence of hydrogen bonding between–CONH2 groups in PAAm and –OH group in PVA and confirm the hydrophilic nature of the blends. X-ray diffractions shows the presence of a strong broad peak centered at 22º (2θ) confirms the amorphous nature of silica which is supposed to be the characteristic of SiO2. The results obtained from different experimental techniques were supported by SEM image analysis. The thermal stability of the nanocomposites enhanced by increasing the silica content in the blend. The DC electrical conductivity was studied for all prepared samples. It was found that the conductivity increase by increasing silica content as well as, increased by increasing the wt% of PVA.
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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".