Development And Characterization Of Biocomposites From Polyhydroxybutyrate (PHB)/ Polylactic Acid (PLA) Filled With Agricultural Residue
Bibliographic record
Abstract
Abundant agricultural residues such as corncob are promising for making polymeric composites. Due to its capacity to replicate complicated shapes and geometries while maintaining outstanding mechanical qualities, three-dimensional (3D) printing has become a popular method for quick prototype development and manufacture. In order to create low-cost bio-polymer composites from a largely underutilized corncob biomass, this study investigates the potentials of employing this agricultural residue as filler material and to ultimately promote environmental sustainability. This is in-line with the drive for improved biomaterials as Canada anticipates banning single use non-degradable plastics by 2030.\nA manufacturing procedure was developed for producing affordable polyhydroxybutyrate (PHB) / polylactic acid (PLA) - corncob (PHB/PLA-CC) composite filaments for 3D printers. Test samples were made by blending generic PHB and PLA pellets in the percentage ratio of 55%:45% (PHB:PLA) w/w and, subsequently, corncob powder with an average particle size of 25.48 µm and particle density of 2.91 g/cm3 was added as a filler at varying weight percentages (wt.%) of 0, 2, 4, 6 and 8. The composite mix was extruded using a Filabot single screw extruder to produce a fused filament for 3D-printing having a consistent diameter of 2.85 mm. These filaments were tested under tensile loading until fracture to establish the tensile properties. Subsequently, the filaments were made into mechanical tensile test samples (dog bones), flexural test samples as well as Charpy impact test samples and tested. \nResults showed that the tensile strength of both the filament and dog bone samples, flexural strength and Charpy impact toughness of the composites all reduced with increase in filler loading. However, the tensile and flexural modulus of all samples tested showed a significant improvement with increasing filler loading. SEM analysis revealed that the cellulose content and grinding of the filler particles gave rise to dense, slightly elongated sheet-like shapes for the filler particles. The fractured surfaces of the composite samples displayed flat and cleavage features for pure polymer blends but turned rougher and jagged as filler loading increased. The fractured surface of Charpy impact samples tested at cryogenic temperatures showed smoother morphology compared to those tested at room temperature. Modulus generally improved as filler loading is increased, with best results mostly at 6 wt.% filler loading. The results show this is a promising composite filament material for 3D printing applications.
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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) | 0.000 | 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".