3D Printing of Sustainable Poly (Lactic Acid) (PLA)/ Bio Poly (Butylene Succinate) (BioPBS) Polymeric Blends via Fused Deposition Modelling
Bibliographic record
Abstract
Fused deposition modelling (FDM) is a popular additive manufacturing (AM) technique for 3D printing thermoplastics. The biomedical industry has benefited from 3D printing technology because of the ability to fabricate complex objects and customized medical parts. Poly (lactic acid) (PLA) is an excellent 3D printable bioplastic that is biocompatible and biodegradable. However, its brittleness hinders its wider use in biomedical applications. A potential solution to enhance PLA toughness, without compromising its biodegradability and biocompatibility, is polymer blending with tough polymers such as poly (butylene succinate) (PBS). The objective of this research was producing 3D printable material with improved mechanical performance. The fabricated PLA/BioPBS (90/10) blend achieved higher tensile and impact strengths than neat PLA. It was found that the alternating layers of the 3D samples enhanced the impact strength in comparison to injection molded sample. However, voids formation during 3D printing can negatively affect the tensile and flexural strengths.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".