Effect of Nanoclay Addition on the Morphology, Fiber Size Distribution and Pore Size of Electrospun Polyvinylpyrrolidone (PVP) Composite Fibers for Air Filter Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The fabrication of Polyvinylpyrrolidone (PVP) electrospun layers for air filter applications is the target of this study. Solutions of 10% PVP containing 0, 3, 10 and 25 wt% nanoclay were used to fabricate electrospun fibers. Scanning electron microscopy showed that the fibers’ roughness increased by increasing the nanoclay content, and it was maximum at the nanoclay concentration of 25 wt%. Concurrently, nanoclay decreased the pore size considerably and increased the range of the fibers’ size distribution up to 100%. In addition, as the nanoclay concentration increased, the frequency distribution decreased abruptly for the larger fiber sizes and increased dramatically for the small fiber sizes. This phenomenon was correlated to the effect of nanoclay concentration on the conductivity of the solution. The solution’s conductivity increased from 1.7 ± 0.05 µS/cm for the PVP solution without nanoclay to 62.7 ± 0.19 µS/cm for the solution containing 25 wt% nanoclay and destabilized the electrospun jet, increasing the range of fiber size distribution. Therefore, the PVP solution containing 25 wt% nanoclay has potential characteristics suitable for air-filter applications, owing to its rougher fibers and combination of fine and thicker fibers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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 it