Effects of Emulsion Droplet Size on the Structure of Electrospun Ultrafine Biocomposite Fibers with Cellulose Nanocrystals
Bibliographic record
Abstract
Electrospinning of cellulose nanocrystals (CNC)/poly(lactic acid) (PLA) emulsions has been demonstrated to be an effective dispersion and alignment method to control assembly of CNC into continuous composite ultrafine fibers. CNC-PLA nanocomposite random-fiber mats and aligned-fiber yarns were prepared by emulsion electrospinning. A dispersed phase of CNC aqueous suspension and an immiscible continuous phase of PLA solution comprised the CNC-PLA water-in-oil (W/O) emulsion system. Under a set of specific conditions, the as-spun composite ultrafine fibers assumed core-shell or hollow structures. In these structures, CNCs were aligned along the core in the core-shell case, or on the wall of the hollow cylinder in the hollow fiber case. CNCs act as nucleating agents influencing PLA crystallinity, and improve the strength and stiffness of electrospun composite fibers. The effects of emulsion droplet size on fiber structural formation and CNC distribution within the electrospun fibers have been carefully examined.
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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 | 0.001 |
| 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) | 0.001 | 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".