Pre-treatment of Flax Fibers for use in Rotationally Molded Biocomposites
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objective of this study was to determine the effects of pre-treated flax fibers on the performance of the fiber-reinforced composites. Lack of good interfacial adhesion and poor resistance to moisture absorption make the use of natural fiber-reinforced composites less attractive. In order to improve fiber/matrix interfacial properties, fibers were subjected to chemical treatments, namely, mercerization, silane treatment, benzoylation, and peroxide treatment. Selective removal of non-cellulosic compounds constitutes the main objective of the chemical treatments of flax fibers to improve the performance of fiber-reinforced composites. Flax fibers were derived from Saskatchewan-grown flax straws. Composites consisting of high-density polyethylene (HDPE) or linear low-density polyethylene (LLDPE) or HDPE/LLDPE mix, chemically treated fibers and additives were prepared by the extrusion process. The test samples were prepared by rotational molding. The fiber surface morphology and the tensile fracture surfaces of the composites were characterized by scanning electron microscopy (SEM). The effects of the different chemical treatments on the mechanical and the physical properties of natural fiber-reinforced composites were investigated. The differential scanning calorimetry (DSC) was used to measure the melting point of the fiber-reinforced composites.
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.
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) | 0.000 | 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) | 0.000 | 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 it