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Record W2131768873 · doi:10.1109/lawp.2010.2076342

Full-Composite Fractal Antenna Using Carbon Nanotubes for Multiband Wireless Applications

2010· article· en· W2131768873 on OpenAlexaff
Aidin Mehdipour, I.D. Rosca, Abdel-Razik Sebak, C.W. Trueman, Suong V. Hoa

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2010
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsFractal antennaMaterials scienceCarbon nanotubeRadiation patternSierpinski triangleComposite numberAntenna (radio)FabricationBluetoothFractalMicrostrip antennaOptoelectronicsAntenna efficiencyWirelessComposite materialAcousticsElectrical engineeringComputer scienceEngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

In this letter, single-wall carbon nanotube (CNT) composite materials are explored for the design of multiband antennas. An accurate electromagnetic (EM) model of the modified Sierpinski fractal composite antenna is developed using Microwave Studio for numerical analysis. For antenna fabrication, we printed CNT on both sides of a substrate and then cut out the desired antenna pattern using a high-precision milling machine. The CNT material was hardened by resin infiltration in order to be processed on the milling machine. The CNT antenna shows satisfactory gain and radiation patterns for UHF-RFID (900 MHz), Bluetooth (2.4 GHz), and WLAN (5.5 GHz) applications. Good agreement between computed and measured results is observed.

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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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

Citations53
Published2010
Admission routes1
Has abstractyes

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