Rheology of Nanocrystalline Cellulose Aqueous Suspensions
Bibliographic record
Abstract
The rheological properties and microstructure of nanocrystalline cellulose (NCC) aqueous suspensions have been investigated at different concentrations. The suspension is isotropic up to 3 wt %, and phase separates to liquid crystalline and isotropic domains at higher concentrations where the samples exhibit a fingerprint texture and the viscosity profile shows a three-region behavior, typical of liquid crystals. The suspension behaves as a rheological gel at even higher concentrations where the viscosity profile shows a single shear thinning behavior over the whole range of shear rates investigated. The effects of ultrasound energy and temperature on the rheological properties and structure of these suspensions were studied using polarized optical microscopy and rheometry. Our results indicate that the amount of applied ultrasound energy affects the microstructure of the suspensions and the pitch of the chiral nematic domains. The viscosity profile is changed significantly at low shear rates, whereas the viscosity of biphasic suspensions at intermediate and high shear rates decreased with increasing temperature. This suggests that, between 30 and 40 °C, structural rearrangement takes place. At higher concentrations of about 10 wt %, the temperature has no significant effect on viscosity; however, a marked increase in viscosity has been observed at around 50 °C. Finally, the Cox-Merz rule was found to fail after a critical concentration, thereby implying significant structural formation. This critical concentration is much higher for sonicated compared to unsonicated suspensions.
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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 | 0.001 |
| 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".