Adhesion to wet cellulose – Comparing adhesive layer-by-layer assembly to coating polyelectrolyte complex suspensions 2<sup>nd</sup> ICC 2007, Tokyo, Japan, October 25–29, 2007
Bibliographic record
Abstract
Abstract Polyelectrolyte complexes are routinely used as adhesives to strengthen fiber-fiber contacts in paper. This work evaluates different approaches to putting the polyelectrolyte complexes into the adhesive joint. Instead of conventional wet paper mechanical testing, a wet cellulose film delamination technique was employed permitting direct comparison of different approaches to applying the polymeric adhesive to the cellulose-cellulose joint. The adhesion strengths of layer-by-layer polyelectrolyte complexes assembled on wet cellulose films and the adhesion strengths of the corresponding polyelectrolyte complex coated on wet cellulose films are compared. The wet adhesion strengths were measured by peel delamination. The polyelectrolyte complexes were based on mixtures of cationic polyvinylamine (PVAm) and anionic carboxymethyl cellulose (CMC). The layer-by-layer assemblies of PVAm and CMC yielded stronger wet adhesion than did coated films of the corresponding colloidal complexes or pure PVAm at the same coverage (mass of polymer/joint area). The role of CMC was to give ionic crosslinks with PVAm which increase the cohesive strength of thick PVAm layers. PVAm gives much stronger wet adhesion to cellulose compared to the oxidized silicon wafer surfaces. It is proposed that imine and aminal bonds can form between the polyamine and hemiacetals in the regenerated cellulose films which cannot form with silica.
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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) | 0.001 | 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) | 0.002 | 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".