Processing, manufacturing, and characterization of vibration damping in epoxy composites modified with graphene nanoplatelets
Bibliographic record
Abstract
This research aims to characterize the vibration and damping properties of epoxy composites modified with pristine and amino‐functionalized graphene nanoplatelets (GNPs) at four different nanofiller loadings (0.2, 0.4, 0.6, 1.2 wt%). The GNPs/acetone solution was mixed with epoxy through mechanical stirring. The mixture was then heated by means of a hot plate to evaporate the acetone. Once the mixture was cooled down, the hardener was added and the mixture injected into aluminum molds to form the nanocomposite test coupons. A shaker generated a periodic signal to excite the cantilever nanocomposite specimens at the fixed end. The frequency response functions (FRFs), damping ratios and natural frequencies measured using the forced vibration technique. The experimental results confirmed the beneficial effect of graphene nanoplatelets on the damping ratio of high content epoxy nanocomposites. POLYM. COMPOS., 40:3914–3922, 2019. © 2019 Society of Plastics Engineers
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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) | 0.000 | 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 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".