Tuning cellular structure in a previously developed microcellular acrylonitrile butadiene styrene/thermoplastic polyurethane blend foams
Bibliographic record
Abstract
Abstract This study investigates the cell structure control in 50% thermoplastic polyurethane (TPU) and 50% acrylonitrile butadiene styrene (ABS) blend foam using CO 2 as a physical blowing agent, focusing on the effects of variable foaming parameters on the microstructure. Samples measuring 25 × 25 × 1 mm were produced and analyzed for foam structure. The foaming process involved saturating the samples with CO 2 gas at pressures of 4, 5.5, and 7 MPa, followed by rapid pressure release and immersion in a hot glycerol bath. The foaming parameters included varied temperatures (80, 90, and 120°C) and times (5–80 s). Scanning electron microscope (SEM) analysis provided data on cell size and density. Results indicated that increasing the saturation pressure enhanced CO 2 uptake in the ABS/TPU blend, with the CO 2 uptake rate peaking early in the process. Higher foaming temperatures and extended foaming times led to increased cell size, cell density, and expansion ratio. These findings highlight the significant role of process parameters in controlling the cell structure of ABS/TPU blend foams, offering valuable insights into optimizing foam properties for industrial applications. Highlights Optimization of foam parameters leads to cell structure control in ABS/TPU composite foams for industrial applications. Increasing saturation pressure significantly boosts CO 2 uptake in ABS/TPU composite foams. Increasing the foaming temperature and duration leads to larger cell sizes, higher cell density, and greater expansion ratios in ABS/TPU composite foams.
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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 | 0.001 |
| 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 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".