Core–Shell Structured PEO-Chitosan Nanofibers by Coaxial Electrospinning
Bibliographic record
Abstract
Core-shell structured PEO-chitosan nanofibers have been produced using a coaxial electrospinning setup. PEO and chitosan solutions, both in an aqueous acetic acid solvent, were used as the inner (core) and outer (shell) layer, respectively. Uniform-sized defect-free nanofibers of 150-190 nm diameter were produced. In addition, hollow nanofibers could be obtained subsequent to PEO washing of the membranes. The core-shell nanostructure and existence of chitosan on the shell layer were confirmed by TEM images obtained before and after washing the PEO content with water. The presence of chitosan on the surface of the composite nanofibers was further supported by XPS studies. The chitosan and PEO compositions in the nanofibrous mats were determined by TGA analysis, which were similar to their ratio in the feed solutions. The local compositional homogeneity of the membranes and the efficiency of the washing step to remove PEO were also verified by FTIR. In addition, DSC and XRD were used to characterize the crystalline structure and morphology of the co-electrospun nonwoven mats. The prepared coaxial nanofibers (hollow and solid) have several potential applications due to the presence of chitosan on their outer surfaces.
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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) | 0.001 | 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".