Development of polylactide open‐cell foams with bimodal structure for high‐acoustic absorption
Bibliographic record
Abstract
ABSTRACT In this study, a highly porous and interconnected foam structure was fabricated using compression molding combined with particulate‐leaching technique. The foamed structures were fabricated with polylactide (PLA) and polyethylene glycol (PEG) with salt as the particulate. The pore size of the foam structure is controlled by the particulates size and higher interconnectivity is achieved by the co‐continuous blending morphology of the PLA matrix with the water‐soluble PEG. PLA is a fully bio‐based thermoplastic polymer and is derived from renewable resources, such as cornstarch or sugarcanes. PEG is also fully biodegradable polymer produced from ethylene. Fabricated foams were characterized for cellular, acoustic, and mechanical properties. The acoustic performance of the foams was studied by measuring the normal incident absorption coefficient in accordance with the ASTM E1050 standard. The results show open porosity as high as 88% was achieved and the effect of water‐soluble polymer on cellular properties and acoustic and mechanical performance of the foams was studied. As a result of the secondary porous structure formed into cell walls by water soluble polymer, the overall absorption of fabricated PLA foams was increased to above 90% while the average absorption of the foams remained unchanged. In addition, the resulting acoustic foams are benign and environmentally friendly. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 39518.
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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) | 0.001 | 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".