Cost Reduction and Mechanical Enhancement of Biopolyesters Using an Agricultural Byproduct from Konjac Glucomannan Processing
Bibliographic record
Abstract
Extensive applications of many sustainable biopolyester materials are limited due to their high cost and poor properties. To resolve these problems, we developed a strategy using an agricultural byproduct derived from konjac glucomannan processing, the konjac fly powders (KFPs), to reduce the cost, preserve the biodegradability, and improve the mechanical properties of biopolyesters. The result indicated that the multiple components in KFPs complicate our understanding of the reinforcing mechanism. However, from the tensile and dynamic mechanical behavior, matrix–filler interaction, and fracture morphology of composites, we concluded that the mechanical enhancement of KFPs was selective. By controlling melt mixing and compression molding, the elongation at break and tensile strength of poly(3-hydroxybutyrate- co -4-hydroxybutyrate) (P(3,4)HB) rather than polybutylene succinate (PBS) or polylactide (PLA) could be enhanced by 205% and 111%, respectively, and the cost of composites reduced by 4–22%. Also, the onset degradation temperature of P(3.4)HB at a low KFP loading was about 40 °C higher than neat P(3,4)HB. The enhancing effect of KFPs was mainly attributed to its strong interaction with P(3,4)HB and the homogeneous structure of their composites.
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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) | 0.001 | 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".