Investigation of physical properties of microalgae‐pectin‐based bio‐composite with addition of pine needle for environmental application
Bibliographic record
Abstract
Abstract Polymers and biopolymers have gained significance due to their applicability and use in industry reducing the negative impact of polymers based on petroleum. A possible solution for the conventional polymer's biodegradability is bio‐composites, which contain natural fibers or aggregates such as microalgae. Hence, microalgae biomass has a promising application to address the biodegradability issue of conventional polymers. In this study, Chlorella vulgaris biomass was mixed with pectin for control samples with glycerol as plasticizer. The mixture microalgae‐pectin‐glycerol, and the addition of pine needles was used to evaluate the tensile strength and compression of the bio‐composite. This bio‐composite showed a higher Young's modulus of 95.66 MPa for blend C2 and a higher strength with 20% of pectin concentration in the mixture. Additionally, the pine needle addition did not have a low effect between the compression results. On the other hand, analysis on elasticity showed that the full recovery of the bio‐composite happened after 10 min in all the blends. Also, the bio‐composite showed a slow release of nitrogen and phosphorous after 5 days of water addition, indicating an effective slow release for blend B for both nutrients. Water uptake capacity and loss of soluble material was studied using pullulan, chitosan, and cetyltrimethylammonium bromide additives. These cationic surfactants demonstrated their potential for reduction of water solubility of the bio‐composite.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".