Effects of Formulation Design on Thermal Properties of Wood/Thermoplastic Composites
Bibliographic record
Abstract
In this study, thermal properties of wood/HDPE composites were measured by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The composites comprised of different wood (45%, 55%, and 65%) and maleic anhydride grafted polypropylene (MAPP) contents (0%, 1.5%, and 3%), and particle size (20, 40, and 80 mesh) were produced by extrusion method. TGA measurements showed that wood content is the most important factor affecting the thermal stability, initial mass loss, and ash content of the composites. Any increase in wood content led to increase in ash content and less thermally stable composites. MAPP and particle size were found to have less impact on thermal stability. By retarding the formation of charcoal MAPP influenced thermal stability of composites adversely in composites consisting of bigger particle. Composites made of 65% wood content with 20 mesh size and 0% MAPP were more thermally stable than composites made of 65% wood content with 80 mesh size and 3% MAPP, in the temperature range of 270-500°C. Melting point measurements by DSC showed that melting point had no relationship with wood and MAPP contents, and particle size.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".