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Modeling electrical conductivities of nanocomposites with aligned carbon nanotubes

2011· article· en· W2118496441 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanotechnology · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsMcGill UniversityThe King's UniversityCanada Research ChairsYork UniversityUniversity of TorontoUniversity of King's College
FundersNatural Sciences and Engineering Research Council of CanadaQatar National Research Fund
KeywordsMaterials scienceCarbon nanotubePercolation (cognitive psychology)NanocompositeElectrical resistivity and conductivityConductivityComposite materialResistorPercolation thresholdMonte Carlo methodCuboid

Abstract

fetched live from OpenAlex

We have developed an improved three-dimensional (3D) percolation model to investigate the effect of the alignment of carbon nanotubes (CNTs) on the electrical conductivity of nanocomposites. In this model, both intrinsic and contact resistances are considered, and a new method of resistor network recognition that employs periodically connective paths is developed. This method leads to a reduction in the size effect of the representative cuboid in our Monte Carlo simulations. With this new technique, we were able to effectively analyze the effects of the CNT alignment upon the electrical conductivity of nanocomposites. Our model predicted that the peak value of the conductivity occurs for partially aligned rather than perfectly aligned CNTs. It has also identified the value of the peak and the corresponding alignment for different volume fractions of CNTs. Our model works well for both multi-wall CNTs (MWCNTs) and single-wall CNTs (SWCNTs), and the numerical results show a quantitative agreement with existing experimental observations.

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 categoriesMeta-epidemiology (narrow)
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 score0.015
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
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.224
Teacher spread0.204 · 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