Batch foaming poly(vinyl alcohol)/microfibrillated cellulose composites with<scp>CO</scp><sub>2</sub>and water as co‐blowing agents
Bibliographic record
Abstract
ABSTRACT We studied the foaming behavior of poly(vinyl alcohol) (PVOH) and microfibrillated cellulose (MFC) composites in a batch process using supercritical carbon dioxide (scCO2) and water as co‐blowing agents. In PVOH/MFC composites, water is an economical plasticizer. It not only suppresses the potential thermal degradation of PVOH but also extends the processing window. A uniform cell structure and a high cell density were achieved in the PVOH/MFC foams. The results showed that cell density was increased by increased water content. Further, the MFC contained both micro‐ and nano‐sized fibers. These created numerous heterogeneous nucleation sites and caused local pressure variations. However, cell density decreased when the MFC was overdosed. Due to the high crystallinity that then developed around the MFC, the gas content was too low, and the stiffness was too high. The experimental results also showed that the cell morphology and density could both be controlled by the water and the MFC content. The effects of the foaming temperature and pressure on the cellular morphology of the PVOH/MFC composite foams were examined systematically. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci.2015,132, 42551.
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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 | 0.001 |
| 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".