Reducing Material Costs with Microcellular/Fine-celled Foaming
Bibliographic record
Abstract
Over the past few years, the steady increase in the cost of oil has resulted in higher resin prices. This market trend has imposed a significant burden on plastic parts manufacturers since resin typically accounts for 50—60% of the total manufacturing cost of plastics. In turn, many companies have been looking for ways to reduce the amount of resin they employ in order to compensate for their losses. In this study, high-density foaming experiments using polyethylene (HDPE) and polypropylene (PP) are carried out, demonstrating the extent to which these foaming processes represent breakthrough alternatives for plastics producers. N2 and talc are used as a blowing agent and as a nucleating agent, respectively. Two different pressure-drop rates are applied to study the effects of pressure-drop rates on HDPE and PP foams. It has been found that the cell density is the governing factor that determines the void fraction: the higher the cell density, the higher the void fraction. The authors successfully produced plastic foams that exhibited void fractions of up to 50% for HDPE and 40% for PP; these void fractions accounted for 40—50% reduction in material cost.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".