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Record W2057058778 · doi:10.1002/pen.10876

Epoxy + montmorillonite nanocomposite: Effect of composition on reaction kinetics

2001· article· en· W2057058778 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 Engineering and Science · 2001
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsBell Helicopter Textron (Canada)
FundersUniversity of North Texas
KeywordsMontmorilloniteMaterials scienceEpoxyDifferential scanning calorimetryCuring (chemistry)KineticsNanocompositePolymerizationScanning electron microscopePolymer chemistryEnthalpyChemical engineeringComposite materialPolymer

Abstract

fetched live from OpenAlex

Abstract The objective of this investigation is to determine the effects of montmorillonite layered silicates on the curing kinetics of an epoxy resin. Differential scanning calorimetry was used to probe the changes in reactivity due to the presence of montmorillonite and due to the diamine hardener. The enthalpy of polymerization was strongly affected at compositions greater than 5% (wt) montmorillonite for epoxy + montmorillonite reactions. On introduction of the hardener, epoxy + amine kinetics dominate the reaction for all compositions except for a montmorillonite concentration of 2.5 wt%. X‐ray diffraction was used to determine if the reacted system was exfoliated. The results show a strong montmorillonite composition dependence on the exfoliated state. Transmission electron microscopy of the cured epoxies confirmed a mixed intercalated and exfoliated dispersion at compositions having montmorillonite greater than 2.5 wt%.

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 score0.006
Threshold uncertainty score0.486

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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