Synergistic Effects of Carbon Additives and Supercritical <scp>CO<sub>2</sub></scp> on Cell Morphology and Thermal Insulation of Extruded Polystyrene Composite Foam
Bibliographic record
Abstract
ABSTRACT Polystyrene (PS) foams with carbon additives are widely used in building applications due to their excellent thermal insulation properties, contributing to reduced energy consumption. However, the role of supercritical CO 2 (sc‐CO 2 ) as a blowing agent, in synergy with different forms of carbon additives, remains not fully understood in the context of PS extrusion foaming. In this study, composite foams were prepared by incorporating graphene nanoplatelets (GNP) and flaked graphite (FG) into PS using an extrusion foaming process. Results show that sc‐CO 2 pressure plays a critical role in enhancing carbon dispersion, thereby significantly influencing foam morphology. At high sc‐CO 2 pressure, the cell density of PS foam increased by up to two‐fold with a relatively low carbon loading (0.75 wt%). Moreover, the thermal conductivity of PS composite foam with 1.5 wt% FG was reduced by 6%, reaching a value of 32 mW/(m K). Transmission electron microscopy (TEM) confirmed a uniform dispersion of carbon particles in foams produced at elevated sc‐CO 2 pressures. This study proposes a viable processing strategy for developing carbon‐reinforced PS composite foams with enhanced thermal insulation for energy‐efficient building applications.
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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 | 0.001 |
| 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".