The yielding of attractive gels of nanocrystal cellulose (CNC)
Bibliographic record
Abstract
The flow behavior of nanocrystalline cellulose (CNC) hydrogels in the presence of a monovalent electrolyte (NaCl) as a function of CNC and salt concentration is explored using a variety of linear and nonlinear rheological tests. We have first observed an apparent “slip yield stress” at small wall shear stress values that is mainly due to the onset of solidlike slippage of the hydrogels before their true yielding and deformation. This flow regime and the “slip yield stress” can be eliminated using a sandpaper of an optimum grit size. At higher wall shear stress values, two yielding points for the CNC/salt network are seen in strain sweep tests due to network disruption and cluster deformation that depend on the concentration of both CNC (1–5 wt. %) and electrolyte (0–100 mM). The first yield stress is due to yielding and flow of clusters, while the second one is due to breakage of clusters to small flocs and individual fibers. These yielding stresses were obtained by a variety of tests including strain amplitude sweep, creep, and steady shear, and their values are compared confirming their existence. Rheo-SALS (small angle light scattering) measurements confirmed structural changes as the scattering patterns change from isotropic to highly anisotropic with an increase of deformation and rate of deformation. Moreover, confocal laser scanning microscopy and polarized microscopy images confirm the gradual breakup of clusters to smaller ones and eventually to nearly individual fibers with an increase in the applied shear strain and rate.
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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) | 0.000 | 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".