Effects of non-solvents and electrolytes on the formation and properties of cellulose I filaments
Bibliographic record
Abstract
Abstract Coagulation is a critical process in the assembly of cellulose nanofibrils into filaments by wet spinning; however, so far, the role of the coagulation solvent has not been systematically elucidated in this context. This work considers organic non-solvents (ethanol, acetone) and aqueous electrolyte solutions (NaCl(aq), HCl(aq), CaCl 2 (aq)) for the coagulation of negatively charged cellulose nanofibrils via wet spinning. The associated mechanisms of coagulation with such non-solvents resulted in different spinnability, coagulation and drying time. The properties of the achieved filaments varied depending strongly on the coagulant used: filaments obtained from electrolytes (using Ca 2+ and H + as counterions) demonstrated better water/moisture stability and thermomechanical properties. In contrast, the filaments formed from organic non-solvents (with Na + as counterions) showed high moisture sorption and low hornification when subjected to cycles of high and low humidity (dynamic vapor sorption experiments) and swelled extensively upon immersion in water. Our observations highlight the critical role of counter-ions and non-solvents in filament formation and performance. Some of the fundamental aspects are further revealed by using quartz crystal microgravimetry with model films of nanocelluloses subjected to the respective solvent exchange.
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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 | 0.000 |
| 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) | 0.000 | 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".