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Record W2054774070 · doi:10.1002/pc.21139

Effect of the addition of modified mica on mechanical and durability properties of FRP composite materials for civil engineering

2011· article· en· W2054774070 on OpenAlexaff
Mathieu Robert, Patrice Cousin, Amir Fam, Brahim Benmokrane

Bibliographic record

VenuePolymer Composites · 2011
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsUniversité de SherbrookeQueen's University
Fundersnot available
KeywordsMaterials scienceDurabilityComposite materialFibre-reinforced plasticComposite numberAbsorption of waterMicaPolymerStiffness

Abstract

fetched live from OpenAlex

Abstract The durability of fiber reinforced polymer (FRP) composite materials in humid and harsh environments is an important consideration for acceptance of these materials in civil engineering applications. Reducing the moisture ingress may improve the durability of FRPs. The addition of modified inorganic powder, such as clay nanoparticles, may improve several important properties of polymers, such as barrier properties, fire retardancy, dimensional stability, and mechanical strength. The present work aims to evaluate the effect of the addition of modified mica on FRP properties used in civil engineering applications. To conduct this preliminary study, the following steps were taken: (1) prepare and characterize composites made from lab‐made modified mica, (2) determine the maximum water uptake, water absorption rate and coefficient of diffusion, (3) characterize the mechanical properties, and finally, (4) evaluate the UV resistance. The experimental results show that the use of nanoparticles leads to a decrease of the coefficient of diffusion of water and a significant increase of stiffness and UV resistance. POLYM. COMPOS., © 2011 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 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 score0.002
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.203
Teacher spread0.184 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations13
Published2011
Admission routes1
Has abstractyes

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