Compression, impact and residual strength after impact properties of graphene/fiberglass/epoxy multiscale composites
Bibliographic record
Abstract
ABSTRACT: The effect of graphene nanoplatelets (GNPs), graphene oxide (GO), and reduced-graphene oxide (rGO) on compression, impact and residual strength after impact properties of glass-fiber reinforced polymer composites (GFRPs) were examined. Vacuum-assisted resin transfer molding (VARTM) method was used to simultaneously modify the fibers and the matrix with carbon nanomaterials. A solution of nanoparticle/epoxy mixed in a solvent was sprayed onto the fabric and was also introduced into the epoxy matrix by an agitator mixer. The results from tensile testing indicated that the addition of GNPs, GO, and rGO augmented the mechanical properties of glass fiber-reinforced composites. According to our experimental results, both fiber and matrix-dominant properties were improved under compression, impact and residual strength after impact properties tests, leading to a superior composite.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".