Effect of POSS as compatibilizing agent on structure and dielectric response of LDPE/TiO2 nanocomposites
Bibliographic record
Abstract
Two types of nanocomposites were prepared. The first type was prepared by ball milling-blending of untreated titanium dioxide (TiO2) nanoparticles into low density polyethylene (LDPE). For the second type, a commercial chemically treated TiO2with trisilanol phenyl polyhedral oligomeric silsesquioxane (TSP-POSS) as dispersant was ball milling-blended into LDPE. In this paper, titanium dioxide was selected as a model to show the effect of POSS on dispersion improvement of metal oxides nanoparticles and to understand the correlation between structure and dielectric response of LDPE/TiO2nanocomposites. The microscopic observation by AFM showed that the TiO2treated with the POSS were better dispersed in the polymer matrix as compared to untreated TiO2. Furthermore, the dielectric loss for the nanocomposites filled with treated TiO2was significantly lower than that for nanocomposites filled with untreated TiO2nanoparticles.
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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".