Thermal, mechanical, and morphological properties of functionalized graphene‐reinforced bio‐based polyurethane nanocomposites
Bibliographic record
Abstract
In this study, the reinforcement effects of graphene on the properties of bio‐based polyurethane (PU) were studied with the use of 1 wt% three functionalized graphene (dispersible graphene, reduced graphene oxide‐NH 2 , and reduced graphene oxide‐tetraethylene pentamine). Scanning electron microscope (SEM) revealed the relatively homogeneous dispersion of graphene nanoplatelets in the PU matrix. It was found that the addition of 1 wt% of the different graphenes could lead to a significant reinforcement effect on the bio‐based PU. Especially, PU nanocomposite with 1 wt% dispersible graphene exhibited 6°C improvement in the T g , 75% increment in storage modulus at 25°C, 34% increase in tensile strength, and 30% increase in Young's modulus. Practical applications: Different graphene were used to reinforce the bio‐based PU. A significant reinforcement effect of graphene on bio‐based PU was found. This strategy has the potential for the fabrication of advanced bio‐based materials. A significant graphene reinforcement effect on bio‐based PU was found. This strategy has the potential for the fabrication of advanced bio‐based materials.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".