Increasing the Use of High-Yield Pulp in Coated High-Quality Wood-Free Papers: From Laboratory Demonstration to Mill Trials
Bibliographic record
Abstract
Although high-yield pulps (HYP) are gaining increasing use to replace hardwood kraft pulp in paper grades such as uncoated and coated fine papers, the amount has been typically limited to less than 20% because there are concerns about its potential impact on papermaking operation and product quality. To address these concerns, laboratory experiments that mimic the actual paper machine operation were carried out and coated paper samples from mill trials were examined to clarify the impact of high-level HYP substitution on the properties of coated wood-free papers. Results showed that the HYP substitution, even at 40%, did not yield negative effects on strength properties such as tensile and tear; in fact the Scott bond increased with the HYP addition. The small increase in the surface roughness from the HYP addition can be eliminated by the filler addition, precalendering, and coating process. The lower brightness and CIE (Commission Internationale d'Eclairage) whiteness of the HYP can be compensated for by the addition of optical brightening agents (OBAs) and dyes, as well as pigments in the coating color. The analysis of samples collected from mill trials indicated that coated paper containing 40% HYP has lower coating penetration than that containing 40% HYP content paper samples. This was attributed to the smaller pore size created by HYP substitution. No significant differences were found between the samples containing 17 and 40% HYP on print gloss, color gamut, and print gloss uniformity. The implication from this study is that the HYP substitution level can be increased up to 40% in the production of coated wood-free paper without significant negative effect on the paper quality.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".