Underutilized Agricultural Co-Product as a Sustainable Biofiller for Polyamide 6,6: Effect of Carbonization Temperature
Bibliographic record
Abstract
Polyamide 6,6 (PA66)-based biocomposites with low-cost carbonaceous natural fibers (i.e., soy hulls, co-product from soybean industry) were prepared through twin-screw extrusion and injection molding. The soy hull natural fiber was pyrolyzed at two different temperatures (500 °C and 900 °C denoted as BioC500 and BioC900 respectively) to obtain different types of biocarbons. The BioC500 preserved a higher number of functional groups as compared to BioC900. Higher graphitic carbon content was observed on the BioC900 than BioC500 as evident in Raman spectroscopy. Both biocarbons interact with the PA66 backbone through hydrogen bonding in different ways. BioC900 has a greater interaction with N-H stretching, while BioC500 interacts strongly with the amide I (C=O stretching) linkage. The BioC500 interrupts the crystallite growth of PA66 due to strong bond connection while the BioC900 promotes heterogeneous crystallization. Dynamic mechanical analysis shows that both biocarbons result in an increasing storage modulus and glass transition temperature with increasing content in the BioC/PA66 biocomposites over PA66. Rheological analysis shows that the incorporation of BioC900 results in decreasing melt viscosity of PA66, while the incorporation of BioC500 results in increasing the melt viscosity of PA66 due to greater filler-matrix adhesion. This study shows that pyrolyzed soy hull natural fiber can be processed effectively with a high temperature (>270 °C) engineering plastic for biocomposites fabrication with no degradation issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".