Helium gas barrier and water absorption behavior of bamboo fiber reinforced recycled polypropylene
Bibliographic record
Abstract
Helium gas permeability and water absorption behavior of the recycled polypropylene/short bamboo fiber composite membrane were investigated. The effects of short bamboo fiber content and fiber chemical treatment on gas permeability and water absorption properties of composites have been examined. Our research showed that the solubility coefficient of helium increased as the fiber content of the bamboo increases but the diffusivity coefficient seemed to decrease with increasing amount of bamboo fiber in the composite formulation due to the poor adhesion between bamboo fiber and polymer matrix. The structure of recycled polypropylene/bamboo fibers have also investigates by X-ray diffraction technique. The chemical treatment of the bamboo fiber by alkali solution increased fiber surface roughness within the composite; in consequence, a more homogeneous dispersion of these fibers appears in the polymer matrix. The process of absorption of water was found to follow the kinetics and mechanisms described by Fick’s theory. A considerable loss in mechanical properties of the water-saturated samples after 3 months of aging in water was observed and this reduction could be delayed by fiber chemical treatment. This study provided the useful information about the behavior of recycled polypropylene/bamboo fiber composite materials during their service life time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".