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Record W2611266854 · doi:10.1049/iet-map.2016.0931

Magneto‐dielectric substrate‐based microstrip antenna for RFID applications

2017· article· en· W2611266854 on OpenAlexaff
Jamal Zaid, Mohammadmahdi Farahani, Tayeb A. Denidni

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2017
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMagnetoMicrostrip antennaSubstrate (aquarium)Materials scienceDielectricMicrostripAntenna (radio)OptoelectronicsElectronic engineeringElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

A new planar magneto‐dielectric substrate (MDS) is used for miniaturising a rectangular microstrip patch antenna for radio frequency identification (RFID) applications. The proposed magneto‐dielectric unit cells are embedded underneath the microstrip patch. Increasing the constitutive parameters of the host substrate decreases the size of the antenna. This use of a MDS as the host substrate allows the antenna size to be reduced by up to 80% compared with a conventional microstrip patch antenna, and the proposed smaller antenna exhibits almost the same performance. The simulated and measured results show a good agreement. The magneto‐dielectric layer is thin enough to be embedded underneath the antenna. The proposed antenna offers a reasonable impedance bandwidth from 847 to 853 MHz. The antenna is therefore suitable for RFID applications.

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 score0.935
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.241
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

Citations24
Published2017
Admission routes1
Has abstractyes

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