Fabrication of oriented electrospun cellulose nanocrystals–polystyrene composite fibers on a rotating drum
Bibliographic record
Abstract
ABSTRACT Nitrobenzene (CNC‐1), trifluoromethyl benzene (CNC‐2) modified and polystyrene‐grafted (CNC‐ g ) cellulose nanocrystals in polystyrene (PS)‐ N , N dimethylformamide (DMF) solutions were electrospun and collected as stretched and aligned fibers on a rotating drum. Scanning electron microscope pictures showed significant alignment in the case of unmodified and nitrobenzene‐modified CNC‐1/PS nanocomposite fibers once the linear speed of rotor reached to 15 m s −1 . Fiber diameter decrease was more strong with rotor speed increase in the case of trifluoromethyl benzene modified (CNC‐2) and polystyrene‐grafted (CNC‐ g ) cellulose nanocrystals/PS systems. Dynamic mechanical analysis including storage and elastic modulus of electrospun‐oriented fibers were performed on surface‐modified and polymer‐grafted CNC/PS samples. According to α transition peak, the increase in the glass‐transition temperature with filler concentration was the highest in polymer‐grafted CNC‐ g /PS composite fibers. It was due to the interpenetration of grafted polymer brushes and free polymer chains in continuous phase and resulted in restrictions of motions of polymer chains in the PS matrix. The elastic moduli of nitrobenzene (CNC‐1) and trifluoromethyl benzene (CNC‐2)‐modified CNC‐filled PS composite fibers agreed well with percolation model, which indicates the CNC–CNC interactions and network formation with an increase in concentration. Magnitude of the elastic modulus of polymer grafted CNC‐ g at 0.33 vol % in PS was significantly higher than the prediction from percolation theory. It was due the immobilized polymer chains around CNC‐ g particles. However, grafted polymer chains, at higher CNC concentrations acted like stickers among CNC particles and caused CNC agglomerates with entrapped free polystyrene from the matrix, thus caused a decrease in the elastic modulus. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137 , 48942.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".