Enhancing mechanical performance of polystyrene carbon composite foams through supercritical CO <sub>2</sub> foaming: An experimental study
Bibliographic record
Abstract
Conventional polystyrene (PS) foams are widely used in packaging and insulation, but suffer from limited mechanical strength, which restricts their use in load-bearing applications. This study investigates the enhancement of the mechanical performance of PS foam through the incorporation of graphene nanoplatelets (GNP) and flaked graphite (FG), processed via supercritical CO 2 (sc-CO 2 ) extrusion foaming at two pressures (17.3 MPa and 20.6 MPa). The influence of sc-CO 2 pressure on additive dispersion and mechanical behavior was evaluated using compression testing, dynamic mechanical analysis (DMA), micro-computed tomography (micro-CT). Results showed that increasing the sc-CO 2 pressure significantly enhanced compressive strength from 0.30 MPa to 0.40 MPa for 0.75 wt% GNP foams (34% increase) and from 0.30 MPa to 0.50 MPa for 0.75 wt% FG foams (66% increase). Enhanced storage and loss moduli in DMA confirmed improvements in stiffness and energy dissipation. Micro-CT imaging revealed more well-defined closed-cell structures and uniform carbon particle dispersion at the higher pressure. Overall, these findings emphasize the importance of pressure-optimized sc-CO 2 foaming as an effective strategy for producing lightweight, durable PS-carbon composite foams suitable for structural, insulation, and packaging 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".