Co-Production of Cellulose Nanocrystals and Fermentable Sugars Assisted by Endoglucanase Treatment of Wood Pulp
Bibliographic record
Abstract
In this study, fermentable sugars and cellulose nanocrystals (CNCs) were co-produced from endoglucanase treatment of wood pulp, followed by acid hydrolysis. Enzymatic hydrolysis was performed using two endoglucanases differentiated by the presence or absence of a cellulose-binding domain (CBD). The enzyme with an intact CBD gave the higher glucan conversion (up to 14.1 ± 1.2 wt %) and improved the degree of crystallinity of the recovered wood pulp fiber (up to 83.0 ± 1.0%). Thus, this endoglucanase-assisted treatment successfully removed amorphous content from the original cellulosic feedstock. CNC recovery (16.9 ± 0.7 wt %) from the feedstock going into the acid hydrolysis was improved relative to untreated pulp (13.2 ± 0.6 wt %). The mass loss from enzymatic treatment did not cause a decrease in the CNC yield from the starting material. The characteristics of CNCs obtained through acid hydrolysis (with or without enzyme treatment of pulp) were analyzed using X-ray diffraction, transmission electron microscopy, dynamic light scattering, Fourier transform infrared spectroscopy, and differential scanning calorimetry as characterization techniques. The CNCs generated through acid hydrolysis of endoglucanase-treated wood pulp displayed comparable properties relative to those generated using untreated pulp. Thus, endoglucanase treatment can enable co-production of CNCs and sugars for biofuel fermentation.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".