Steady Shear Rheology of Suspensions of Mixtures of Starch Nanoparticles and Cellulose Nanocrystals
Bibliographic record
Abstract
The steady shear rheology of suspensions of mixtures of rod-shaped cellulose nanocrystals (NCC) and spherical starch nanoparticles (SNPs) was investigated experimentally over a broad range of NCC and SNP concentrations. The NCC concentration varied from about 1 to 6.7 wt% and the SNP concentration varied from 5 to 30 wt%. The suspensions of mixtures of NCC and SNPs were pseudoplastic (shear-thinning) in nature. The viscous behavior of suspensions of mixtures of NCC and SNPs could be described adequately using the power-law model. The power-law parameters, that is, consistency index and flow behavior index, were dependent on the concentrations of both NCC and SNPs. The consistency index increased substantially with increases in NCC and SNP concentrations. The flow behavior index generally decreased with an increase in NCC and SNP concentrations; that is, the suspension mixtures became more shear-thinning with increases in NCC and SNP concentrations. However, the dependence of the consistency index and flow behavior index on NCC concentration was much stronger as compared with the SNP concentration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".