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Record W2027516789 · doi:10.1016/j.proeng.2012.07.357

Compressive Properties of Nanoclay/Epoxy Nanocomposites

2012· article· en· W2027516789 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProcedia Engineering · 2012
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsnot available
FundersComposites Innovation Centre
KeywordsEpoxyMaterials scienceCompressive strengthExfoliation jointComposite materialNanocompositeMontmorilloniteCompression (physics)Dispersion (optics)GrapheneNanotechnology

Abstract

fetched live from OpenAlex

The effect of montmorillonite clay on the compressive properties of Epikote 828 epoxy was studied. A series of epoxy-based nanocomposites with 1-5 wt.% nanoclay content was prepared. The degree of dispersion and exfoliation was investigated using transmission electron microscopy. Static uniaxial compression tests were conducted in order to study the effect of nanoclay on the compressive stress-strain behaviour and compressive properties of the Epikote 828 polymer. It was found that the compressive properties depend on the degree of exfoliation of the clay nanoplatelets in the epoxy. Reduction in compressive strength for 1 and 3 wt% nanoclay was recorded. This is because the intercalated structure of nanoclay in the polymer creates high localised stresses in the matrix during compression that leads to premature failure.

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 score0.018
Threshold uncertainty score0.597

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 head0.014
GPT teacher head0.190
Teacher spread0.176 · 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