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Record W4293868768 · doi:10.1109/ims37962.2022.9865393

Substrate-Integrated Hybrid Metallo-Dielectric Waveguide for Millimeter-Wave and Terahertz Applications

2022· article· en· W4293868768 on OpenAlexaff
Chunmei Liu, Ke Wu

Bibliographic record

Venue2022 IEEE/MTT-S International Microwave Symposium - IMS 2022 · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTerahertz radiationWaveguideExtremely high frequencyOptoelectronicsMaterials scienceDielectricElectronic circuitSubstrate (aquarium)Integrated circuitDielectric lossMillimeterInterconnectionOpticsElectrical engineeringComputer scienceTelecommunicationsPhysicsEngineering

Abstract

fetched live from OpenAlex

In millimeter-wave (mmW) and terahertz (THz) applications, the loss behavior of circuits becomes critical for the overall performance of a system in question. It is imperative to develop a low-loss interconnect that should be used as the building component of a circuit. In this work, a hybrid metallo-dielectric waveguide is proposed and studied. The hybrid waveguide consists of a substrate-integrated dielectric waveguide and a substrate-integrated nonradiative dielectric waveguide. A back-to-back D-band prototype is investigated theoretically and validated experimentally. This hybrid waveguide shows its potential in the development of low-loss highly integrated mmW and THz circuits and systems.

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)0.001
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: Empirical
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.212
Teacher spread0.202 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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