Role of cationic polyacrylamide in fiber‐CaCO<sub>3</sub> pigment interactions
Bibliographic record
Abstract
Abstract It is believed that the action of cationic polyacrylamide as a retention aid for incorporating pigment particles into a paper is based on its ability to form a polymeric bridge between particles and pulp fiber suspended in water. When the polymer is added to a mixture of fibers and pigments, this process is complicated by the different rates of polymer adsorption on the fibers and the pigment particles, the rate of collision between them, and the charge reversal of the polymer from the hydrolysis. To elucidate under which conditions the polymer can form a bridge, the processes of polymer adsorption and pigment–fiber interaction were separated. A deposition of pigment particles onto fibers suspended in water was investigated, using both components pretreated with the polymer. The results indicated that polymer adsorbed on fiber can form a bridge with untreated pigment particles regardless of the polymer charge. On the other hand, negatively charged hydrolyzed polymer adsorbed on the pigment does not form a bridge with untreated fiber. When both the fiber and the pigment are pretreated, the bridge formation depends on their surface coverage by polymer and its charge. No deposition takes place when both components are sufficiently coated by anionic hydrolyzed polymer, which indicates electrosteric repulsion. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 2409–2415, 2003
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".