The Supercritical State Paradigm in Thermoplastic Foaming
Bibliographic record
Abstract
“Supercritical” has become automatically and intrinsically associated with “carbon dioxide foaming”, with this combination generally resulting into claimed benefits such as microcellular structure, high cell density and enhanced mechanical properties. However the supercritical state remains accessible to any blowing agents. The newly-introduced hydrofluorocarbons (HFCs), following the ban put on chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) in the polystyrene foam industry, are other examples of foaming agents that are processed under temperature and pressure conditions that belong to the supercritical region. Unfortunately, such unusual conditions have resulted in the past into typical processing difficulties that make the resulting benefits associated to the supercritical state questionable. The supercritical state may not be apparently the panacea usually claimed… and sought for! In this work, density characteristics of supercritical fluids were reviewed and linked to the foam nucleation stage. Foaming experiments using a specific polymercarbon dioxide system were conducted at the vicinity of the critical locus and the sequence leading to phase separation monitored using an ultrasonic technique. The results suggested a phase separation mechanism similar to that of spinodal decomposition. Density fluctuations reported for supercritical fluids close to their critical locus would translate for the foaming process into concentration fluctuations typical of the spinodal decomposition.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".