Wet Cross-Linking of Cellulose Fibers via a Bioconjugation Reaction
Bibliographic record
Abstract
A well-known bioconjugation reaction, the EDC-assisted reaction of carboxyl and amine groups, is shown to be extremely well-adapted for cross-linking fibers under papermaking conditions. By using such chemistry we obtained increases as high as 500% and 100% in the wet-web strength (WWS) of papers made from, respectively, unbeaten and beaten hardwood kraft pulps, after pretreating the fibers with carboxymethyl cellulose and using adipic dihydrazide as the cross-linker. These increments exceed previous attempts in most cases by about 1 order of magnitude. Experiments show that the cross-linking reaction does not counteract the beating effect, as has usually occurred in the past for other cross-linking routes, but instead complements it. The ability of EDC for promoting covalent bonding under very wet conditions appears to make it an excellent agent for the enhancement of the WWS of paper, the property that ultimately determines the runnability of a papermaking machine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".