PAE adsorption on polyelectrolyte-grafted pulp fibers
Bibliographic record
Abstract
Abstract The adsorption of cationic polyamide-amine epichlorohydrin (PAE) paper wet-strength resin onto bleached kraft pulp fibers was increased by grafting hydrolyzed poly(ethylene-alt-maleic anhydride) (PEMAc) onto fiber surfaces before PAE adsorption. The highly negatively charged PEMAc increased the sparse negative charge density on untreated fibers, enhancing PAE adsorption. The adsorption isotherm analysis provided estimates of adsorbed PAE on exterior fiber surfaces, Γ ex , as well as the ideality index, IX , a new measure of isotherm ideality. IX increases when grafting lowers the access of adsorbing polymer to interior surfaces, whereas IX decreases when grafting enhances the adsorption capacity of interior surfaces. A library of 18 adsorption isotherms compares PAE and poly(diallyldimethylammonium chloride) adsorption on unmodified pulps, grafted pulps, and TEMPO-oxidized pulps. The grafted pulps include PEMAc polymers modified with pendent short alkyl or poly(ethylene glycol) chains. A grafted PEMAc content of 4.1 mg PEMAc per g of dry fiber tripled the amount of adsorbed PAE on exterior fiber surfaces. About two anionic PEMAc carboxylic acid groups were required for every adsorbed PAE cationic charge. Modification of the PEMAc with pendent chains had little effect. TEMPO oxidation, at the same total fiber charge content, had no positive impact on PAE adsorption.
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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".