Grafting <scp>PEG</scp> and alkyl comb polymers onto bleached wood pulp fibres
Bibliographic record
Abstract
Abstract Comb polymers were prepared by reacting a poly(ethylene‐alt‐maleic anhydride) with alkyl amines or poly(ethylene glycol) (PEG) amines. The resulting polymers were used to modify bleached softwood kraft pulp fibre surfaces by catalyst‐free grafting in a process suitable for pulp mill implementation. Pulp fibres were impregnated with a polymer solution and cured above 100°C. High grafting yields were obtained despite having up to 88% of the anhydride groups consumed by amine derivatization. Grafting yields were more than 90% when the polymer dosage was <13 g/kg (dry polymer/dry fibre) for alkyl derivatives and < 38 g/kg for PEG derivatives. We propose that the upper dosage limit for efficient grafting reflects the need for direct contact between cellulose and every polymer chain for ester linkage formation. For a given polymer dosage, the cured pulp sheets had a maximum wet tensile index, TI max , when either curing time or temperature was increased. Both the alkyl and PEG derivatives fit the power law for the wet TI max ~ β Γ ru 0.54–0.62 where β values were the estimated conversion of succinic acid moieties to anhydrides when the pulp sheets were cured, and Γ ru is the dimensionless polymer content that is numerically equal to the amount of applied polymer in mmol repeat units/g dry fibre. However, high polymer dosages give experimental TI max values that fall below the power law, irrespective of curing intensity, because the pulp sheets contain unfixed polymer chains that lubricate fibre/fibre joints, lowering wet strength.
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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".