Development and Characterization of PHB-PLA/Corncob Composite for Fused Filament Fabrication
Bibliographic record
Abstract
The development of environmentally friendly polymeric composites holds great potential for agricultural leftovers. This study explores the effects of lignocellulosic corncob powder as a filler in a polyhydroxybutyrate (PHB)/polylactic acid (PLA) biopolymer matrix. The PHB-PLA matrix consists of a 55% to 45% blend, respectively, while the filler loadings range from 0 wt.% to 8 wt.%. The components are combined and directly extruded into fused filaments for three-dimensional (3D) printing. The tensile strength of both the filament and dog-bone samples, flexural strength, and Charpy impact toughness of the composites, all decreased as filler loading increased. The tensile and flexural modulus of all samples examined improved noticeably with increasing filler loading. The filler particles had dense, mildly elongated sheet-like shapes, whereas the fractured surfaces of the composite samples had flat features for the pure polymer blend, but became rougher and jagged as filler loading increased. The fractured surface of Charpy impact test samples had smoother morphology when tested at cryogenic temperatures, compared to room temperature testing. All attributes showed a fourth-degree polynomial relationship to filler loading and all improved as filler loading increased, with the best results obtained at 6 wt.% loading.
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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".