Influence of polyacrylamide conformation on fabric of “tunable” kaolin–polymer composite
Bibliographic record
Abstract
“Tunable” clay–polymer composites have the potential to improve the engineering properties of clay materials. The importance of these materials derives from the ability of the responsive polymer to adopt various conformations (coiled, partially extended or extended), which in turn impacts the mesoscale properties of the material. However, the influence of polymer molecule conformation on particle arrangement and overall composite behavior is not well understood. The purpose of this study is to understand the fabric development due to the conformational behavior of the polymer, and thus the clay–polymer composite, over a wide range of solids content and stress levels. The polymer molecule conformation was controlled using selected fluid pH and ionic concentrations. Results show that the polymer conformation significantly influences clay fabric formation. When the polymer molecules are likely to have extended conformation, the dominant fabric mode is face-to-face and particle mobilization increases. Both face-to-face and edge-to-edge fabric formation dominate the behavior of the composite when coiled conformation is likely, resulting in a decrease in interparticle movement. Thus, the polymer conformation can be used to manipulate both the interparticle spacing between particles and (or) aggregates and arrangement of particles.
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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 | 0.000 |
| 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) | 0.001 | 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".