Injection Molded Sustainable Biocomposites From Poly(butylene succinate) Bioplastic and Perennial Grass
Bibliographic record
Abstract
Biocomposites from poly(butylene succinate) (PBS) and perennial grass (miscanthus fibers) were successfully prepared by extrusion and injection molding methods with different fiber loadings. The tensile strength of uncompatibilized PBS/miscanthus composites was much lower compared to that of neat PBS. Unlike tensile strength, the flexural and impact strengths were significantly enhanced after incorporation of miscanthus fibers into the PBS matrix. The enhanced flexural strength was attributed to the reinforcing effect of miscathus fibers. The fiber pull-out mechanism is likely responsible for the observed impact strength improvement. Addition of 5 wt % maleic anhydride (MAH) grafted PBS (MAH- g -PBS) into PBS composites showed a significant improvement in tensile and flexural strength compared to the corresponding uncompatibilized composites and neat matrix. For example, the PBS composites with 50 wt % miscanthus fiber and 5 wt % MAH- g -PBS resulted in 22, 139, and 47% improvements in tensile, flexural, and impact strength compared to neat PBS. These improvements were attributed to the enhanced interfacial interaction between the components, as confirmed by adhesion parameter values and by surface morphological analysis. The load-bearing capacity of the compatibilized and uncompatibilized PBS/miscanthus composites was analyzed using a mathematical model. Overall, this study provides an option for preparing a sustainable biocomposite with superior mechanical and thermo-mechanical properties.
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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".