Injection moulded composites from high biomass filled biodegradable plastic: Properties and performance evaluation for single-use applications
Bibliographic record
Abstract
Biodegradable plastic-based items play an essential role in ensuring the sustainability of the food packaging industry due to their high biodegradability and minimized use of fossil fuels. The incorporation of low-cost waste biomass into bio-based polymers to produce biodegradable composites supports the circular economy model and reduces landfilling and carbon footprint challenges associated with petroleum-based plastics. This work discusses the utilization of waste almond shell powder (ASP) up to 50 wt.% with poly(butylene succinate-co-butylene adipate) (PBSA) to develop sustainable biocomposites through injection moulding for rigid packaging applications. At a lower angular frequency (0.1 s − 1), the complex viscosity of the PBSA/50%ASP biocomposite was reduced by ∼65% after adding 5 wt.% compatibilizer, as confirmed by a rheological analysis. The heat deflection temperature, flexural strength, and tensile and flexural moduli of the PBSA/50% ASP biocomposite with 5 wt.% compatibilizer were improved by ∼24, 125, 368, and 385%, respectively, compared to pristine PBSA. These improvements are attributed to the high stiffness and load-bearing capacity of ASP and the enhanced interfacial adhesion and particle dispersion caused by the compatibilizer, as corroborated by SEM analyses. Hence, the formulated biocomposites show a suitable structure-property-processing co-relationship for injection moulding of single-use products.
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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".