High biomass filled biodegradable plastic in engineering sustainable composites
Bibliographic record
Abstract
The production of single-use, non-renewable plastic has persistently impacted the environment through non-biodegradable plastic accumulation. Injection-moulded biodegradable polymer blend [poly(butylene succinate-co-butylene-adipate) (PBSA) and poly(butylene adipate-co-terephthalate) (PBAT)] with an inexpensive filler, walnut shell powder (WSP), enables an appropriate melt flow behaviour after incorporating compatibilizer as confirmed by rheological analysis. The sustainable composites with 60 wt% WSP showed a decrement of 68.4% in tensile strength as compared to PBSA/PBAT blend. However, the inclusion of a 5% compatibilizer in PBSA/PBAT/60wt%WSP composite increased tensile strength by 48.7%, indicating improved interfacial adhesion. Further, the improvements in tensile (694%) and flexural moduli (461%) of PBSA/PBAT blend were observed with the addition of 60% WSP in presence of 7% compatibilizer due to fibrillar morphology of filler. Thus, signifying enhanced stiffness with increased filler, leading to a composite suitable for rigid packaging. Scanning electron microscopy (SEM) confirmed an improved adhesion between matrix and filler interfaces with the addition of a compatibilizer as gaps decreased, subsequently leading to increased mechanical properties. The novelty of this work establishes a high loading of filler can be incorporated with biodegradable polymers and improved properties in presence of compatibilizer makes it more suitable for injection moulding applications to produce a low-cost biocomposite capable of being used as a single-use plastic alternative in rigid packaging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".