Wood Microfibres - Effective Reinforcing Agents for Composites
Bibliographic record
Abstract
This work is based on a process to develop novel cellulose microfibre reinforced composite materials, and to understand fundamental mechanical properties of these composites. Cellulose microfibres having diameters <1 μm were generated from bleached kraft pulp by a combination of high shear refining and subsequent cryocrushing under liquid nitrogen, followed by filtration through a 60 mesh screen. Through film casting in polyvinyl alcohol, theoretical stiffness of the microfibres was calculated as 69 GPa. Subsequently, these microfibres were successfully dispersed in the bioplastics thermoplastic starch and polylactic acid (PLA), using conventional processing equipments. The high aspect ratio of these microfibres coupled with their high tensile properties imparted superior mechanical strength and stiffness to the composites. These indicated that by suitably choosing the polymer, excellent reinforcement can be achieved for high end applications like automotive parts.
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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) | 0.003 | 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".