Use of Endoglucanase and Accessory Enzymes to Facilitate Mechanical Pulp Nanofibrillation
Bibliographic record
Abstract
Although selective enzyme treatments have been used to successfully fibrillate chemical pulps, high lignin-containing mechanical pulps have proven to be more recalcitrant. When a bleached chemi-thermomechanical pulp (BCTMP) was sulfonated prior to enzymatic treatment, relatively good fibrillation was achieved, although some pulp hydrolysis occurred after 6 h hydrolysis when using a commercial cellulase enzyme preparation (Cellic CTec 3). To try to minimize pulp losses, various enzyme cocktails, including endoglucanase (EG), xylanase, mannanase, and lytic polysaccharide monooxygenase (LPMO), were assessed for their ability to enhance fibrillation while minimizing cellulose hydrolysis. It was apparent that the yield as well as the zeta potential of the lignin-containing cellulose nanofibrils increased with enzyme treatment. This was likely due to an increase in surface charge and a decrease in particle size after LPMO and hemicellulase treatments, respectively. When carbohydrate-binding modules (CBMs) were used to quantify fiber changes, it was apparent that sulfonation had increased the accessibility of enzymes, while the combined action of the hemicellulases and LPMO increased EG accessibility to the less-ordered regions of the mechanical pulp, resulting in enhanced fibrillation. This work described, for the first time, the synergistic action of EG and various accessory enzymes enhancing mechanical pulp nanofibrillation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".