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Record W2329515167 · doi:10.1177/0892705714533375

Effects of foaming through leaching on the electrical behavior of polystyrene/carbon nanotube composites

2014· article· en· W2329515167 on OpenAlexaff
Majid TabkhPaz, Kaushik Parmar, Anam Mohammed Ali, Simon Park

Bibliographic record

VenueJournal of Thermoplastic Composite Materials · 2014
Typearticle
Languageen
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaterials scienceComposite materialCarbon nanotubeNanocompositeCompression moldingComposite numberPolystyreneElectromagnetic shieldingMolding (decorative)Polymer

Abstract

fetched live from OpenAlex

The aim of this study was to investigate the effects of foaming on the electrical properties of carbon nanotube (CNT)-reinforced polystyrene (PS). A pseudo-three-dimensional (3D) model based on random walk simulation was developed for predicting the electrical properties of CNT nanocomposites. The electromagnetic interference shielding effectiveness (EMI SE) of foamed PS/CNT composites was also studied through a network analyzer, measuring the EMI SE of specimens through reflection and absorption mechanisms. Six types of nanocomposites, including foamed and nonfoamed PS/CNT composites with a CNT loading of 2.1 vol% and different void contents, were manufactured using compression molding and leaching techniques. To realize the effects of foaming on the electrical conductivity of PS/CNT composites, electrochemical impedance spectroscopy analyses were carried out and compared with the pseudo-3D model. We also found that foaming via the leaching method improved the EMI shielding properties of the composites up to 24%.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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 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

Citations14
Published2014
Admission routes1
Has abstractyes

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