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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".