Water sorption and mechanical performance of preheated wood/ thermoplastic composites
Bibliographic record
Abstract
Wood samples heat treated at 175°C, 190°C, and 205°C with different amounts of high density polyethylene and coupling agent were used for the production of wood/plastic composites. Measuring water sorption, thickness swelling, and diffusion coefficients of composites for a 40-week period immersion in water showed that composites with wood treatment at 190°C and 205°C had considerably higher water resistance. Adding a coupling agent reduced water sorption, thickness swelling, and diffusion coefficients, more pronounced in composites with untreated wood. Measurements of flexural properties in a control state and after 4 and 12 weeks immersion periods in water proved that heat treatment is an effective way to ease detrimental effects of water on mechanical properties. Modulus of elasticity showed more sensitivity to water exposure than modulus of rupture. Strain at maximum load increased after water exposure. Treating wood at 190°C resulted in good flexural properties and excellent water resistance.
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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 | 0.000 |
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".