Rheological Behavior of Coating Colors: Influence of Thickener
Bibliographic record
Abstract
Abstract In this work we have investigated the effect of rheology modifiers on the rheological properties of concentrated (65 solids mass%) kaolin suspensions and six different coating colors. Measurements have been performed on kaolin‐based suspensions, without rheology modifier and with either a classic cellulose thickener or associative polymers. It was noticed that suspensions containing a thickener had a much larger viscosity and storage and loss moduli than suspensions containing no rheology modifier. The enhancement of the rheological properties was found to be much more important for the suspensions containing the associative polymer. These observations have been related to steric stabilization of the suspensions, and to the occurrence of entanglements and bridging when the associative polymer was used as the thickener. The influence of the thickener on the rheological properties of the coating colors was found to be similar to that observed for the concentrated kaolin suspensions.
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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 | 0.000 | 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 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".