Rheological behavior of high‐density polyethylene (HDPE) filled with paper mill sludge
Bibliographic record
Abstract
ABSTRACT A comparative study was conducted of composites made with sludge from three different paper mills. Sludges were obtained from a thermomechanical pulp (TMP), a chemico‐TMP (CTMP), and a Kraft mill with a feedstock of primarily black spruce. The primary sludge (PS) and secondary sludge (SS) were mixed at two different ratios (PS:SS = 7:3 and 9:1) and blended with high‐density polyethylene (HDPE) at 20%, 30%, and 40% proportion. The blends were tested using plate–plate geometry before subjection to frequency sweep by oscillation rheometry. The storage modulus ( G ′), loss modulus ( G ″), and complex viscosity (η*) increased with increasing paper sludge content. Decreasing the PS:SS ratio from 9:1 to 7:3 decreased G ′, G ″, and η*. Differential scanning calorimetry showed that sludge addition increased both the melting and crystallization temperature, for a positive effect on crystallinity. Although the behavior of sludge–high‐density polyethylene blends differed from that of traditional wood plastic composite made with wood flour, they obtained G ′, G ″, and η* values of the same magnitude. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135 , 46484.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".