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Record W3007474744 · doi:10.1088/1361-6528/ab7048

Microfabrication of monolithic wafer-level miniaturized millimeter-wave air-filled half-mode waveguide filter based on the inward curving split ring resonator array

2020· article· en· W3007474744 on OpenAlexafffund
Qihui Zhou, Thomas R. Jones, Hamid Moghadas, Mojgan Daneshmand

Bibliographic record

VenueNanotechnology · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilCMC Microsystems
KeywordsMicrofabricationMaterials scienceCenter frequencyBand-pass filterCutoff frequencyExtremely high frequencyInsertion lossResonatorWaveguideOptoelectronicsMillimeterPassbandBandwidth (computing)Transmission lossOpticsFabricationTelecommunicationsPhysicsEngineering

Abstract

fetched live from OpenAlex

In this paper, we propose a miniaturized monolithic bandpass filter utilizing an air-filled half-mode waveguide and an inward curving split ring resonator array in the millimeter-wave band. The waveguide blocks the wave below cutoff frequency and the uniplanar array forms a rejection band above the transmission band. The microfabrication process of the filter adopts photoimageable technology and the combination of films with different thicknesses to build a 3D structure. The measured prototype has a center frequency at 65.5 GHz with a 3 dB fractional bandwidth of 30.7%. The minimum insertion loss is 2.1 dB. The proposed component offers excellent performance including a wide transmission band, a low pass-band insertion loss, an excellent isolation in the stop-band, and a steep roll-off at the upper cutoff frequency. Besides, due to the scalability of the waveguide and periodic array, this filter can be adapted for other frequency ranges.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.001
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 head0.029
GPT teacher head0.217
Teacher spread0.188 · 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
Published2020
Admission routes2
Has abstractyes

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