Towards Analysis and Optimization of Electrospun PVP (Polyvinylpyrrolidone) Nanofibers
Bibliographic record
Abstract
In this study, the polymeric nanofibers of polyvinylpyrrolidone (PVP) were manufactured using the electrospinning technique. The electrospinning process parameters such as voltage, polymer concentration, rotational speed of the collecting drum, collecting distance, and flow rate were optimized to obtain the minimum fiber diameter for sound absorption applications. The effects of these parameters on the fiber diameter as output responses were investigated by analysis of variance (ANOVA) and Taguchi’s array design. Furthermore, a mathematical model was generated using response surface methodology (RSM) to model the electrospinning process. The high voltage and polymer concentration were observed to be the most significant parameters at 95% and 99% confidence level. The average model accuracy of 83.4% was observed for the predictive model of electrospinning which is considered acceptable as it is composed of complete experimental trials of 27 out of 243 runs. The experimental study offers a promising attempt in the open literature to carefully understand the effect of various electrospinning parameters when producing PVP nanofibers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".