Effect of mixing conditions and polymer particle size on the properties of polypropylene/graphite nanoplatelets micromoldings
Bibliographic record
Abstract
Abstract In this study, properties of polypropylene/graphite nanoplatelets (PP/GNP) composites and corresponding micromoldings were systematically studied in terms of filler loading concentrations and mixing methods. PP of different forms, i.e., PP pellets and powders, were adopted to fabricate PP/GNP composites. Additionally, a comparative study of precoating GNP and PP powders using solvent-based solution blending and ultrasonication-assisted mixing was performed. Results showed that PP/GNP composites prepared using powder form PP resulted in at least one order of magnitude higher electrical conductivity than using pellet form PP and further reduced the percolation threshold from 12.5 to 10 wt%, which was related to the state of filler distribution within corresponding moldings. Morphology observations revealed that microparts prepared with powder-PP/GNP composites exhibited less preferential alignment of GNP particles along the flow direction when compared with those molded using pellet-PP/GNP counterparts, which was helpful in improving the overall electrical conductivity for PP/GNP micromoldings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".