Viscous Rheological Behavior of Nanosuspensions of Fumed Silica Nanoparticles and Cellulose Nanocrystals
Bibliographic record
Abstract
The viscous rheological behavior of suspensions of mixtures of fumed silica nanoparticles (N20) and rod-shaped cellulose nanocrystals (NCC) were studied experimentally. The fumed silica concentration varied from 2 to 11.3 wt% and the NCC concentration varied from 0.99 to 6.73 wt%. The suspensions of pure fumed silica, pure NCC, and mixtures of N20 and NCC were non-Newtonian shear-thinning in nature. The viscosity versus shear rate data of all suspensions of pure and mixed additives could be described satisfactorily by a power-law model. The consistency and flow behavior indices of the suspensions were strongly dependent on the concentrations of both N20 and NCC. While the consistency index increased sharply with the increases in additive (N20 and NCC) concentrations, the flow behavior index generally decreased with the increases in N20 and NCC concentrations. Thus, the suspensions became more shear-thinning with the increases in N20 and NCC concentrations. The shear-thinning of suspensions was due to two different mechanisms: the orientation of rod-shaped cellulose nanocrystals in the flow direction with the increase in shear rate and the break-up of large agglomerates of fumed silica aggregates with the increase in shear 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 | 0.001 |
| 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) | 0.000 | 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".