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Record W4254757227 · doi:10.1002/mmce.20336

Composite right/left handed artificial transmission line structures in CMOS for controlled insertion phase at 30 GHz

2008· article· en· W4254757227 on OpenAlexaff
Symon K. Podilchak, Brian Frank, A.P. Freundorfer, Yahia M. M. Antar

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2008
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsQueen's UniversityRoyal Military College of Canada
Fundersnot available
KeywordsInsertion lossCMOSMetamaterialTransmission lineInductorCapacitorPhase (matter)Electrical engineeringExtremely high frequencyMaterials scienceEngineeringTopology (electrical circuits)OptoelectronicsPhysicsTelecommunicationsVoltage

Abstract

fetched live from OpenAlex

Two CMOS integrated circuits are presented that utilize metamaterial composite right/left handed (CRLH) transmission lines (TLs) for zero insertion phase at 30 GHz. Specifically, 2 and 3 unit cell structures are presented with controlled insertion phase that is achieved by cascading lumped element capacitors and spiral inductors in an LC network configuration defining the TL unit cells. Furthermore, the fixed TL structures suggest the possibility of zero, advanced or delayed insertion phases by element variation, or by the use of simple active components. Simulation and measured results are in good agreement with CRLH TL theory, and display a linear insertion phase and flat group delay values that are dependent on the number of unit cells with an insertion loss of ∼0.8 dB per cell. These findings suggest that such high speed CRLH TLs structures can be implemented for linear array feeding networks and compact antenna designs in CMOS at millimeter wave frequencies. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.

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 score0.003

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 head0.019
GPT teacher head0.267
Teacher spread0.248 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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