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Record W2103408804 · doi:10.1002/pen.20656

Constitutive modeling for intercalated PMMA/clay nanocomposite foams

2006· article· en· W2103408804 on OpenAlexaff
Choonghee Jo, Jin Fu, Hani E. Naguib

Bibliographic record

VenuePolymer Engineering and Science · 2006
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceComposite materialNanocompositePolymer clayViscoelasticityUltimate tensile strengthConstitutive equationTensile testingIntercalation (chemistry)ModulusPolymerStructural engineeringFinite element method

Abstract

fetched live from OpenAlex

Abstract A constitutive model for tensile behavior of PMMA/clay nanocomposite foams was developed in this study. The elastic modulus of the nanocomposites is affected by the form of clays embedded in the polymer matrix. The reinforcing effect by intercalation of the clays and the detrimental effect by clay agglomeration were considered for the determination of the elastic modulus of the nanocomposites. A viscoelastic model was adapted for the tensile behavior of the material. The developed constitutive equation is expressed in terms of clay morphology and material properties. The aspect ratio of clays and the expansion of clay layer spacing in the intercalated clay clusters were proved to play a vital role in the reinforcing mechanism. For the verification of the constitutive model, Poly(methyl‐methacrylate) (PMMA)/clay nanocomposite foams were manufactured by batch process method and their uniaxial tensile test results were compared with theoretical predictions. Compared with the experimental results, the proposed constitutive equation showed agreement with the experimental test results. POLYM. ENG. SCI. 46:1787–1796, 2006. © 2006 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2006
Admission routes1
Has abstractyes

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