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Record W2066678093 · doi:10.1063/1.4906255

Electrically tunable materials for microwave applications

2015· article· en· W2066678093 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Physics Reviews · 2015
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceMicrowaveOptoelectronicsVoltageDielectricDissipation factorBeam steeringFerroelectricityMicrowave applicationsFlexibility (engineering)CeramicElectronic engineeringAntenna (radio)Computer scienceElectrical engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Microwave devices based on tunable materials are of vigorous current interest. Typical applications include phase shifters, antenna beam steering, filters, voltage controlled oscillators, matching networks, and tunable power splitters. The objective of this review is to assist in the material selection process for various applications in the microwave regime considering response time, required level of tunability, operating temperature, and loss tangent. The performance of a variety of material types are compared, including ferroelectric ceramics, polymers, and liquid crystals. Particular attention is given to ferroelectric materials as they are the most promising candidates when response time, dielectric loss, and tunability are important. However, polymers and liquid crystals are emerging as potential candidates for a number of new applications, offering mechanical flexibility, lower weight, and lower tuning voltages.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.053
GPT teacher head0.289
Teacher spread0.236 · 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