Dielectric properties of various metallic Oxide/LDPE nanocomposites compounded by different techniques
Bibliographic record
Abstract
Metallic oxide reinforced thermoplastics are good candidates as insulating material for HVDC cables because of their ability to limit or suppress space charges injection and accumulation. In this paper, LDPE based nanocomposites reinforced by Magnesium Oxide (MgO), Polyhedral Oligomeric Silsesquioxanes (POSS) or Zinc Oxide (ZnO) were prepared either by mechanical alloying or by melt mixing and their dielectric properties were investigated for low loadings from 0 to 5 wt% in order to assess the efficiency of the compounding procedure in producing enhanced dielectric properties. The thermal step method was used to investigate the space charge behavior of the various samples. The space charge measurements have shown differences between the different nanocomposites reinforced by different kind of nanofillers and made by different preparation protocols, just after manufacturing and also after different conditions of DC poling. None of the prepared nanocomposites showed significant increases in their dielectric losses in a broad range of frequencies and temperatures and no significant increase in their DC conductivity.
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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) | 0.001 | 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".