Green Composites from Residual Microalgae Biomass and Poly(butylene adipate-<i>co</i>-terephthalate): Processing and Plasticization
Bibliographic record
Abstract
Abstract Innovative biocomposites from residual microalgae biomass (RMB), a byproduct of biodiesel production, and PBAT (poly(butylene adipate-co-terephthalate)) have been prepared in this study. RMB was characterized by Fourier transform infrared spectroscopy (FT-IR) and its thermal stability was determined. Subsequently, RMB and PBAT biocomposites were prepared by extrusion and injection molding. Incorporation of 10, 20 and 30% RMB in the biocomposites was studied. The biocomposites were characterized using FT-IR and thermogravimetric analysis, and their mechanical properties were compared, including tensile, flexural and impact strength. The effect of RMB on the morphology of the polymer matrix was analyzed by scanning electron microscopy and confocal laser scanning microscopy. RMB plasticization was performed with glycerol and urea, comparing different proportions of glycerol and urea. The studies show that it is possible to use RMB in the manufacture of biocomposites with PBAT, obtaining the best extrusion results with 20% RMB. Optimal result was achieved with 30% glycerol and 7.5 phr of urea.
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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) | 0.001 | 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".