Comparisons of modified effective medium theory with experimental data on shear thinning of concentrated latex dispersions
Bibliographic record
Abstract
Measured viscosity vs shear rate relationships were analyzed for a wide variety of carboxylated latexes reported in the literature using a modified effective-medium theory proposed by one of the authors. The theory contains three main parameters, cm, ko, and δ, which are the maximum volume fraction, a particle interaction parameter, closely related to the secondary electroviscous effect, and the thickness of the stabilizing surface layer, respectively. It is assumed that sheared dispersions always approach close packing for high volume fractions, i.e., cm=0.74 (for monodisperse suspensions). In general, ko increases with the magnitude of the secondary electroviscous effect and its value varies typically between 2.46 and 4.0 for low Péclet numbers, Pe, and approaches 1.7 for very high Pe. For dispersions of highly charged particles at low electrolyte concentrations, the electroviscous effects become especially significant and experiments show that the viscosity can increase by more than three orders of magnitude when the electrolyte concentration is reduced from 10−1 to 10−3 M, an effect predicted by the modified effective medium theory. The viscosity of carboxylated latex is also influenced by a “hairy” surface layer, the thickness, δ, of which appears to be closely related to the amount and type of functional monomers, and the degree of dissociation of carboxylic acid groups on the latex surface. The theory also explains the shear thinning behavior of blends of latexes with different size.
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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".