Environmentally Friendly and Zero-Formamide EVA/LDPE Microcellular Foams via Supercritical Carbon Dioxide Solid Foaming
Bibliographic record
Abstract
Abstract Elastomeric polyolefin foams with excellent mechanical properties, environmentally friendly performance, and cost effectiveness are highly promising. Nevertheless, it is a huge challenge to obtain these advantages in elastomeric polyolefin foams using chemical or common physical blowing agents. Therefore, a strategy was applied to the ethylene–vinyl acetate copolymer (EVA)/low-density polyethylene (LDPE) (EVA/LDPE) system by combining crosslinking, microphase separation, crystallization, and supercritical CO2 (scCO2) solid foaming. Consequently, environmentally friendly EVA/LDPE foams of zero formamide with the desired uniform cellular structure of expansion ratio over 8, average cell size less than 50 μm, and cell density over 109 #/cm3 were obtained. The lightweight EVA/LDPE foams show excellent tensile strength and compression strength, much higher than those of other elastomeric polyolefin foams. The reasons for this are that (1) the introduction of crosslinking and entanglement structures in EVA enhances the viscoelasticity, which is beneficial to bubble nucleation and bubble stability in the foam, and simultaneously improves the mechanical properties of the foam; (2) the existence of LDPE segments in EVA leads to microphase separation, which is beneficial to bubble nucleation; (3) low-temperature solid foaming enhances the mechanical properties of the foam due to the uniform microcellular structure; and (4) scCO2 foaming has zero formamide, which meets the safety requirements and specifications of children’s floor mats (T/CTJPA 005-2018).
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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 | 0.000 | 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 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".