Water vapor adsorption and volumetric swelling of melt‐impregnated wood–polymer composites
Bibliographic record
Abstract
Abstract Wood–plastic composites were prepared through impregnation of solid wood with polyethylene. A resolution IV screening design of 16 runs for seven factors at two levels was adopted. The seven factors tested were ratio of maleated polyethylene in formulations, ratio of polyethylene of different molecular weights, four process factors (vacuum, pressure, time, and temperature), and wood species (red maple and aspen). Moisture adsorption content and volumetric changes as a function of time were investigated. This study also examined the effects of impregnation parameters and impregnants on water vapor adsorption and dimensional stability. The process parameters (pressure and temperature), polymer impregnants (polyethylene of different molecular weights), and wood species contributed significantly to the equilibrium moisture content (EMC), whereas the moisture adsorption rate was mainly affected by the polymer impregnants (polyethylene of different molecular weights). The EMC was inversely proportional to polymer retention. However, none of the variables significantly contributed to volumetric swelling; the volumetric swelling rate was mainly affected by wood species, the molecular weight of the polyethylene, and impregnation vacuum. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 2668–2676, 2006
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".