Polymer transfer during fines detachment under turbulent flow : Mechanism and implications
Bibliographic record
Abstract
Le transfert de polymere entre les surfaces de fabrication du papier a ete caracterise pour divers sequestrants commerciaux. Le transfert de polymere pendant le detachement des particules stabilise la suspension et mene a une alteration des couches de polymere. Un modele cinetique, decrivant la deposition des particules simultanement avec le transfert des polymeres, a ete mis au point et valide. Lors des essais, les depots de fines sur les fibres enduites de polymere ont fait l'objet d'un suivi. L'effet de la chimie du polymere, de la concentration de sel et du taux de cisaillement sur les parametres cinetiques a fait l'objet d'un examen. On peut distinguer deux principaux ensembles de caracteristiques cinetiques correspondant aux mecanismes de floculation par inversion des charges et encapsulation. Les polymeres d'encapsulation produisent des liaisons plus resistantes, mais ils sont plus facilement transferes. Par contre, des polymeres tres charges, induisant l'agregation par inversion des charges ou neutralisation, produisent des liaisons plus faibles mais font l'objet de moins de transfert. Les constantes cinetiques observees ont ete extrapolees aux taux de cisaillement de la fabrication du papier. Meme lorsque les estimations sont conservatrices, les fines sont rapidement detachees, et de facon permanente, en presence d'un cisaillement eleve. Ces resultats pourraient expliquer la perte de retention observee sur les machines a papier a haute vitesse.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".