Impact of melt impregnation on the color of wood–plastic composites
Bibliographic record
Abstract
Abstract The aesthetics of wood–plastic composites (WPCs) can affect the acceptance of the products by consumers. This study was aimed at providing a better understanding of how impregnation variables affect color changes, thereby allowing for the development of an optimal process for WPCs. The effects of impregnation parameters and impregnants on the WPC color were investigated in this study via a screening design. Sixteen runs of resolution IV design for seven factors at two levels were conducted. The seven factors were the ratio of maleated polyethylene in the formulations, the ratio of polyethylenes with different molecular weights, four process factors (vacuum, pressure, time, and temperature), and wood species (red maple and aspen). The studied color parameters included the lightness change, chroma change, hue angle change, saturation change, and total color change. All treatments darkened the wood and increased the chroma values and the saturation. Even though all treatments had an impact on the hue angle, the changes were very small. The wood species, impregnants, impregnation time, and temperature played significant roles in the color change and chroma coordinates. However, no parameter dominated the hue angle change and saturation. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 2149–2157, 2006
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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 | 0.000 | 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 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".