Structure and Strength of Flocs of Precipitated Calcium Carbonate Induced by Various Polymers Used in Papermaking
Bibliographic record
Abstract
Because of persistent economic pressure on cost reduction, inorganic fillers such as precipitated calcium carbonate (PCC) have become increasingly economically attractive in the papermaking process. The increase of filler level in paper can be achieved by adding it to pulp prior to the headbox, either as individual filler particles or as preaggregates, while maintaining paper strength and minimizing their negative impact. Consequently, the floc structure and strength of PCC aggregates was studied using flocculants and dry strength agents, using static light scattering/diffraction (SLS), real time fluorescent video imaging (RTFVI), image analysis, photometric dispersion analysis (PDA), and scanning electron microscopy (SEM). It was found that PEO/cofactor induced PCC aggregates were weaker at high shear and far more irreversible than those induced by the partially hydrolyzed polyvinyl formamide copolymerized with acrylic acid (PVFA/NaAA) or cationic starch. Flocs produced at low polymer dosages were smaller and weaker than those produced at higher dosages. The number of discrete PCC particles in aggregates was measured using real time fluorescent video imaging combined with image analysis. Finally, we speculate that when two scalenohedral crystal type PCC particles aggregate, there is a small effective surface area to bind them, mainly through classical bridging or charge neutralization flocculation. Moreover, additional polymer adsorption results in higher coverage of the external and internal surfaces and prevents further aggregation due to electrosteric repulsion.
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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".