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Record W2318479923 · doi:10.1021/am200652f

Interaction Stresses in Carbon Nanotube–Polymer Nanocomposites

2011· article· en· W2318479923 on OpenAlexaff
Meysam Rahmat, Kaushik Das, Pascal Hubert

Bibliographic record

VenueACS Applied Materials & Interfaces · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceCarbon nanotubeNanocompositevan der Waals forceComposite materialPolymerStress (linguistics)Yield (engineering)AdhesionPolymer nanocomposite

Abstract

fetched live from OpenAlex

A new technique of atomic force microscopy interaction measurement is used to obtain the three-dimensional stress field in nanocomposites made of single-walled carbon nanotubes (SWNT) and poly(methyl methacrylate) (PMMA) matrix. This original approach expands the current capability of AFM from imaging and force mapping to three-dimensional stress field measurements. Latest developments in the field have been limited to three-dimensional imaging at the surface only, and one value (adhesion) force mapping. The current work provides the interaction stress results for a PMMA-SWNT nanocomposite and shows a maximum estimated load transfer of less than 7 MPa (the maximum attraction stress estimated). This value is obtained for an unfunctionalized nanocomposite and hence the interaction stress is mainly based on van der Waals interactions. This means that for this system, carbon nanotubes behave similar to an elastic-fully plastic material with a yield stress of less than 7 MPa. This phenomenon illustrates why carbon nanotubes may not show their strong mechanical properties (yield strength of above 10 GPa) in polymeric nanocomposites.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.016
Threshold uncertainty score1.000

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.245
Teacher spread0.224 · 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.

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

Citations26
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueACS Applied Materials & InterfacesSame topicCarbon Nanotubes in CompositesFrench-language works237,207