Correlation of Elongational Fluid Properties to Fiber Diameter in Electrospinning of Softwood Kraft Lignin Solutions
Bibliographic record
Abstract
Viscoelastic properties of N, N -dimethylformamide (DMF) solutions of softwood kraft lignin (SKL) containing small amounts of poly(ethylene oxide) (PEO) were investigated. Of interest is the relationship between viscoelastic properties of the spinning solutions and their corresponding electrospinning behavior. Although it is well established that fiber diameter is critical in determining the material properties of nanofibers, lignin solutions have been observed to display poor electrospinnability in many instances. Thus, the motivation behind this work was to understand and exert control over the relevant fluid properties that control the fiber diameter of SKL/PEO fibers, The results of dynamic shear and capillary breakup extensional rheometry (CaBER) experiments indicated that SKL solutions were weakly elastic in shear and Newtonian in elongational flow. SKL solutions were not electrospinnable at concentrations of 25–45 wt % but form fibers at 50 wt % concentration. The addition of PEO to SKL solutions led to an increase in shear moduli and pronounced strain hardening in elongational flow. The characteristic time scales of tensile stress growth (λ) measured with CaBER were dependent on the SKL concentration, PEO concentration, and PEO molecular weight. In contrast to SKL solutions, SKL/PEO solutions are electrospinnable over the concentration range of 25–45 wt % SKL depending on the combination of SKL concentration, PEO concentration, and PEO molecular weight. Correlation between the fiber diameters obtained during electrospinning and the measured value of λ are discussed.
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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".