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Record W1969226800 · doi:10.1116/1.2013311

Silver coplanar waveguides as the passive components of choice for microwave integrated circuits

2005· article· en· W1969226800 on OpenAlexaff
Vladislav V. Levenets, Rony E. Amaya, N. G. Tarr, T. Smy, John Rogers

Bibliographic record

VenueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena · 2005
Typearticle
Languageen
FieldMaterials Science
TopicCopper Interconnects and Reliability
Canadian institutionsCarleton University
Fundersnot available
KeywordsCoplanar waveguideMonolithic microwave integrated circuitMicrowaveMaterials scienceElectromigrationResistive touchscreenOptoelectronicsFabricationElectronic circuitElectrical engineeringElectronic componentBroadbandIntegrated circuitElectronic engineeringCMOSTelecommunicationsComputer scienceEngineeringComposite materialAmplifier

Abstract

fetched live from OpenAlex

High quality broadband passive components are needed for MMIC/MIC in silicon. Coplanar waveguides (CPW) provide an effective way to implement passives in microwave ICs. Silver “fat” wires in the back end interconnects, used for CPW fabrication, will reduce the bulk resistive loss in metallization to the lowest possible level, which is vital to minimize noise. Electromigration, electrochemical migration, and agglomeration issues are not a problem for silver microwave passive components, because of their coarse dimensions and the low current densities encountered in these structures. In this work Ag and Cu CPWs were designed, fabricated, and tested. Silver CPWs showed a 2–3Ω∕cm improvement in resistance over copper devices at 20GHz.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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