Investigation and characterization of dielectric, thermal, and chemical properties of recycled <scp>high‐density polyethylene</scp> blended with virgin <scp>polyethylene</scp>
Bibliographic record
Abstract
Abstract Dielectric performance of post‐consumer recycled HDPE blended with virgin HDPE was investigated to evaluate the possibility of using these materials for the insulation of electrical wires and cables. The presence of organic and inorganic impurities was investigated using thermal and chemical methods (TGA, DSC, and EDX). The characterization of impurities revealed different amount of inorganic impurities in recycled material that was depending on the execution of melt filtration by the recycler to prepare the recycled material. Higher values of both dielectric losses and dielectric constant were observed for post‐consumer recycled PE, with the dielectric loss of recycled material almost 17 times higher than the one of virgin PE at power frequency (60 Hz). The short‐term breakdown strength of post‐consumer recycled HDPE was observed to be slightly lower than that of virgin PE. The experimental result showed that blending the recycled stream with virgin materials was effective in order to enhance dielectric properties of recycled material. In this regards, dielectric losses decreased by almost 50% when 50% of virgin HDPE was added to the recycled material. In addition, breakdown strength was improved when virgin HDPE was added.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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, 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".