Advances in electrospinning techniques for synthesis of nanofibers loaded with herbal extracts and natural ingredients: A comprehensive review
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
Electrospinning offers a versatile method for the synthesis of polymeric nanofibers integrated with natural compounds such as medicinal extracts, antibacterial agents, and antioxidants (e.g., Aloe vera, honey, curcumin). These composite fibers exhibit diverse potential applications spanning wound dressing, tissue engineering, drug delivery, and the food industry. Tailoring nanofiber morphologies and loading techniques enables modulation of release kinetics and controlled diffusion of extracts tailored to specific applications. Recent literature showcases an array of studies exploring the electrospinning of various polymers, including natural ingredients, for biomedical and industrial purposes. This article aims to compile and review methodologies for combining and encapsulating natural extracts within polymers via electrospinning synthesis method, alongside their applications. Our review presents a comprehensive analysis of electrospun nanofibers containing extracts and natural ingredients, encompassing their architectural diversity and factors influencing release kinetics. As more people become interested in natural materials, we expect to see a huge increase in research efforts in this field in the years to come.
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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) | 0.002 | 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 it