Elevated‐temperature mechanical performance of <scp>GFRP</scp> composite with functionalized hybrid nanofiller
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this article, alteration in the mechanical performance of glass fiber/epoxy (GE) composite due to individual and simultaneous incorporation of multi‐walled carbon nanotubes (CNT) and multi‐layered graphene sheets (MLG) in both their pristine and oxidized forms are discussed. Further, the effect of two different nanofiller concentrations (0.1 and 0.3 wt%) were also studied to optimize the performance. Flexural testing of these composites was performed at room temperature (RT), 70 and 110°C in‐situ temperatures to understand their temperature dependence behavior. From all considered composites, GE composite with 0.1 wt% of oxidized CNT and MLG mixture (O‐(CNT‐MLG)) (1:1) showed best flexural performance at all the in‐situ temperatures. The presence of oxidized CNTs and MLGs in the GE composite provided a synergetic strengthening effect like CNT pull‐outs and crack bridging confirmed through SEM imaging. Besides, oxidation helped in the dispersion of CNT and MLG in the composite. Glass transition temperature ( T g ) of all the considered composites was evaluated using Differential Scanning Calorimetry (DSC). Fourier Transformed Infra‐red Spectroscopy (FTIR) was also conducted to confirm the functionalization of CNT and MLG after oxidation. During the fractography study, these composites showed variation in fiber/matrix interfacial bonding, matrix deformation, dispersion of nanofillers and fiber imprints, which helped to understand different failure modes responsible for the gross failure of the composites.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it