Rheology of nanocrystalline cellulose (CNC) gels: Thixotropy, yielding, wall slip, and shear banding
Bibliographic record
Abstract
This study focuses on the rheological behavior of a cellulose nanocrystal gel. This system [5 wt. % cellulose nanocrystal (CNC) + 20 mM NaCl] is proved to be thixotropic, and the detected shear force tightly depends on the growth and break-up of the aggregates of CNC rods. From strain-controlled experiments, a nonmonotonic steady-state flow curve with a minimum stress value of ≈33 Pa is found, and the negative slope of stress versus shear rate suggests the existence of shear bands. From stress-controlled experiments (creep), the “static yield stress” is determined to be 67.5 ± 2.5 Pa. This difference proves that the local minimum stress of the flow curve does not coincide with the “static yield stress” determined by creep tests. However, this minimum stress can maintain flow provided that the material is already in a yielded state. At nominal shear rates below about 100 s−1, shearing is suggested to be localized in a shear band rather than over the whole material. The “dynamic yield stress” is found as “the minimum stress to maintain flow,” or the onset of shear banding. Moreover, wall slip also occurs at low nominal shear rates which is related to the interaction between the dynamic microstructure of the CNC gel and the wall: it is hypothesized that the low shear rates allow the CNC aggregates to extensively grow and, thus, the oversized CNC aggregates detach from the asperities of the wall. Our finding of the robust connection between yielding, thixotropy, wall slip, and shear banding shall shed new light on the nature of the nonmonotonic flow curves of yield stress and thixotropic materials.
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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) | 0.000 | 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 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".