Bio-Based Composites from Industrial By-products and Wastes as Raw Materials
Bibliographic record
Abstract
Innovative bio-based composites combining humins as biorefinery by-product with keratin or lignin as wastes or industrial side-products were developed. The bio-composites were prepared using three types of matrix formulations allowing the synthesis of elastic to rigid thermosets. These matrices were combined with chicken feathers powder, non-woven chicken feathers mat or lignin to produce bio-composites. A maximum quantity of bio-fillers was used, around 10 wt.%. The effect of the bio-fillers on the matrix’s crosslinking was studied by rheology and DSC. Then, the obtained materials were analyzed by TGA, DMA, tensile tests, water absorption and SEM. The results show a very good compatibility of the humins matrix with the bio-fillers, without any preliminary modification of the matrix, that is exceptional for the point of view of a composite. The overall performances of the neat matrix were maintained or improved through the composites. Therefore, bio-composites with potentially interesting thermal and mechanical properties have been synthesized. In the case of the elastic ductile matrix the Young’s modulus value was improved from 1 to 22 MPa, while for the rigid matrix the increase was from 106 to 443 or 667 MPa, in the case of composites with non-woven chicken feathers mat or lignin. To our knowledge this is the first study combining humins matrix with keratin. The obtained bio-composites are sustainable materials linked via the used raw materials to the circular economy and biomass valorization.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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 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".