Lignosulfonates Enable the Coproduction of Fibrillated Lignocellulose and Fermentable Sugars from Chemi-Thermomechanical Wood Fibers
Bibliographic record
Abstract
Lignosulfonates (LS) are known to reduce the recalcitrance of wood fibers to enzymatic hydrolysis. This study furthers the use of LS for the bioconversion of chemi-thermomechanical pulp (CTMP, ca. 26% lignin) at high solids content (10%) using a cellulase and hemicellulase prehydrolysis complex combined with LS loading (dual treatment). The process (10% solids, 12 h) increases the sugar yield by 20% and produces high-quality lignin-containing cellulose nanofibrils (LCNF) by mechanical fibrillation. Moreover, the dual treatment yields nanofibrils of smaller lateral size and enables better colloidal stability compared with those obtained by enzyme treatment alone or by sequential application (LS addition after enzyme). Translucent films were produced with LCNF, which are shown for their reduced hydrophilicity, high mechanical strength, and UV shielding performance. The introduced approach for efficient utilization of lignocellulose resources to coproduce high-value fibrillated lignocellulose and sugars is expected to lead to new opportunities given the availability of CTMP under the persistent reduction in demand of newsprint and printing grades.
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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".