Thermally conductive polymer-graphene nanoplatelet composite foams
Bibliographic record
Abstract
A new class of thermally conductive microcellular polymer nanocomposites of graphene nanoplatelets (GnP) is reported. Foamed and solid high-density-polyethylene (HDPE)-GnP composites containing different GnP contents (0-18 vol.%) were injection-molded. Foamed composites were fabricated using a facile technique of melt mixing followed by supercritical fluid-treatment and physical foaming in an injection molding process. The effects of foaming on the dispersion, exfoliation, orientation and inter-connectivity of platelets, and heat dissipation functionality were investigated. The introduction of microcellular foaming, significantly changed the orientation of platelets, enhanced their inter-connectivity and further exfoliated GnPs in the polymer. Hence, foaming reduced the density of the injection-molded samples and enhanced the thermal conductivity of product up to 800% (3.75 W/m.k). The results revealed that lightweight, highly thermally conductive products with lower filler loading, can be fabricated using foam injection molding for various applications in miniaturized electronic devices, and electric motor systems.
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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 | 0.000 |
| 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".