Comparing enzymatic post-treatments by endoglucanase (EG) and lytic polysaccharide monooxygenase (LPMO) on microfibrillated cellulose (MFC) to enhance cellulose film fabrication
Bibliographic record
Abstract
Cellulose is the world's most abundant natural polymer and it can be used as a substitute for fossil derived products. The work described here evaluated the use of mono-component enzyme treatment, using endoglucanase (EG) and lytic polysaccharide monooxygenase (LPMO), to improve the properties of micro-fibrillated cellulose (MFC) produced from mechanically refined kraft pulp. Endoglucanase treatment of the pulp significantly reduced the degree of polymerization (DP) of the cellulose by promoting fiber cutting. In contrast, LPMO treatment only slightly reduced the fiber length and pulp viscosity. However, the introduction of carboxylic acid groups by the action of LPMO appeared to enhance the accessible surface area of cellulose. Enzyme-treated MFC showed improved nano-fibrillation with transmittance and water retention values increased after both enzyme treatments. The cellulose films derived from enzyme-treated MFC showed enhanced mechanical properties with the LPMO-treated films showing superior tensile strength (77 MPa) and Young's modulus (3600 MPa). Thermogravimetric analysis (TGA) also indicated improved thermal stability for both enzyme-treated films. LPMO treatments proved more effective, promoting nano-fibrillation while maintaining fiber integrity and enhanced intermolecular interactions. • EG and LPMO treatments enhance the mechanical properties of MFC. • Neither EG nor LPMO changes the composition of MFC. • EG treatment resulted in both fiber cleavage and fibrillation. • LPMO treatment is more selective, promoting fibrillation over fiber cleavage.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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 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".