Electrospinning as an Important Tool for Fabrication of Nanofibers for Advanced Applications—a Brief Review
Bibliographic record
Abstract
Nanomaterials are attracting renewed interest due to their novel properties, which are not seen in their conventional micro state counterparts. They are used in advanced applications in the fields of catalysis, medicine, electronics, optics and membranes. Electrospinning is one of the simplest and cheapest methods to make nano-porous polymer membranes, and these offer a large surface area-to-volume ratio, high porosity and small pore size. These electrospun nonwoven mats could be employed in myriad applications ranging from filtration, sensors, electrode materials, drug delivery, cosmetics, and tissue scaffolding. This technique can introduce novel functional characteristics, and hence by changing the basic experimental set up, solvent, solution and polymer characteristics can alter the composition, morphology, and porosity of the processed material. The unique structural and functional characteristics inherited at submicron to nanoscale dimensions via electrospinning makes it an attractive technique for advanced industrial applications.
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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 | 0.000 |
| 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 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".