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Record W2919837278 · doi:10.1002/pc.25251

Processing, manufacturing, and characterization of vibration damping in epoxy composites modified with graphene nanoplatelets

2019· article· en· W2919837278 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolymer Composites · 2019
Typearticle
Languageen
FieldEngineering
TopicTribology and Wear Analysis
Canadian institutionsCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceEpoxyComposite materialNanocompositeAcetoneVibrationGrapheneCantileverDamping ratioExfoliated graphite nano-plateletsNanotechnology

Abstract

fetched live from OpenAlex

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

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.178
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it