Electrospinning Biopolymers from Ionic Liquids Requires Control of Different Solution Properties than Volatile Organic Solvents
Bibliographic record
Abstract
Abstract We report the correlation between key solution properties and spinability of chitin from the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]) and the similarities and differences to electrospinning solutions of nonionic polymers in volatile organic compounds (VOCs). We found that when electrospinning is conducted from ILs, conductivity and surface tension are not the key parameters regulating spinability, while solution viscosity and polymer concentration are. Contrarily, for electrospinning of polymers from VOCs, solution conductivity and viscosity have been reported to be among some of the most important factors controlling fiber formation. For chitin electrospun from [C2mim][OAc], we found both a critical chitin concentration required for continuous fiber formation (>0.20 wt %) and a required viscosity for the spinning solution (between ca. 450–1500 cP). The high viscosities of the biopolymer–IL solutions made it possible to electrospin solutions with low, less than 1 wt %, polymer concentration and produce thin fibers without the need to adjust the electrospinning parameters. These results suggest new prospects for the control of fiber architecture in nonwoven mats, which is crucial for materials performance.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".