Cellulose microfibrils: A novel method of preparation using high shear refining and cryocrushing
Bibliographic record
Abstract
Abstract This paper describes a novel technique to produce cellulose microfibrils through mechanical methods. The technique involved a combination of severe shearing in a refiner, followed by high-impact crushing under liquid nitrogen. Fibers treated in this way were subsequently either freeze-dried or suspended in water. The fibers were characterized using SEM, TEM, AFM, and high-resolution optical microscopy. In the freeze-dried batch, 75% of the fibrils had diameters of 1 μm and below, whereas in the water dispersed batch, 89% of the fibrils had diameters in this range. The aspect ratio of the microfibrils ranged between 15 and 55 for the freeze-dried fibrils, and from 20 to 85 for the fibrils dispersed in water. These measurements suggest that the microfibrils have the potential to produce composites with high strength and stiffness for high-performance applications. The microfibrils in water were compounded with polylactic acid polymer to form a biocomposite. Laser confocal microscopy showed that the microfibrils were well dispersed in the polymer matrix.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".