Preparation and Properties of Wheat Straw Fiber-polypropylene Composites. Part II. Investigation of Surface Treatments on the Thermo-mechanical and Rheological Properties of the Composites
Bibliographic record
Abstract
Composites made of polypropylene (PP) and wheat straw fiber treated by alkalization, acetylation, and maleic anhydride polypropylene (MAPP) were prepared, and the dynamic mechanical, thermal, and rheological properties of the treated composites have been investigated. The PP composites reinforced with the treated wheat straw fiber exhibited higher brittleness. The melt flow studies were carried out at the temperature of 170, 180, and 190°C and shear rate of 0.01—0.1 s —1 . The PP composites reinforced with the alkalized wheat straw fiber showed the high melt viscosity due to the strong chemical interaction among polymer and wheat straw fiber. The introduction of MAPP to the system increased the flow behavior of the polymer dispersed the wheat straw fiber uniformly, and decreased the melt viscosity. The PP composites introduced by 2 wt% MAPP showed the lowest storage flexural modulus (E ′ ) over the entire temperature range from 25—150°C, due to better compatibility between the wheat straw fiber and matrix. The PP composites made of with 20 wt% alkalized and MAPP treated wheat straw fiber showed the highest E ′ . The differential scanning calorimeter (DSC) study revealed that introducing the wheat straw fiber to PP matrix increased the melting temperature and crystallization temperature. The PP composites reinforced with the alkalized and MAPP treated fiber had the highest rate of crystallization as a consequent of the co-effect of alkalization and esterfication.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".