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Record W3022301959 · doi:10.5267/j.esm.2020.2.002

Carbon Nano-tube Reinforced Nylon 6,6 Composites: A Molecular Dynamics Approach

2020· article· en· W3022301959 on OpenAlexvenueno aff
Upinder Kumar, Rajeev Rathi, Sumit Sharma

Bibliographic record

VenueEngineering Solid Mechanics · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceComposite materialNano-Molecular dynamicsTube (container)Carbon fibersComposite number

Abstract

fetched live from OpenAlex

Composites prepared by Single Wall Carbon Nano-tube (SWCNT) as well as Nylon assume a vital part in practical applications as in ultrastrong lightweight materials, vehicle and flying machine parts. In the present work, the influence of aspect proportion (l/d) on the longitudinal Young's modulus (E11) as well as transverse modulus (E22) for the SWCNT/Nylon 66 composite have been critically analyzed through utilizing tools of Molecular Dynamics (MD) simulations. Materials Studio 8.0 simulation software utilized in the current study for finding Young modulus. Aspect proportion (l/d) of used CNT in the composite was ranged from l/d = 5 up to l/d = 30 while the fraction of volume (Vf) of the CNT had been kept constant at 8%. Results demonstrated however that the lengthwise Young's modulus for the current composite increment essentially by expanding the aspect ratio (l/d) of Nano-tube while the change in transverse modulus with fluctuating perspective proportion was not exceptionally noteworthy. The results of the simulation have been consequently matched with the Mori-Tanaka model as well as the Finegan model.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.501
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

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