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Record W2127105985 · doi:10.1109/lmwc.2006.872116

A millimeter-wave bandpass waveguide filter using a width-stacked silicon bulk micromachining approach

2006· article· en· W2127105985 on OpenAlexaff
Micah Stickel, P.C. Kremer, George V. Eleftheriades

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSurface micromachiningBand-pass filterMaterials scienceInsertion lossOptoelectronicsResonatorBenzocyclobuteneOhmic contactWaveguideWaveguide filterCoplanar waveguideSiliconCenter frequencyWaferEtching (microfabrication)Extremely high frequencyDeep reactive-ion etchingElectronic engineeringFilter (signal processing)OpticsPrototype filterReactive-ion etchingElectrical engineeringFilter designComputer scienceMicrowaveEngineeringPhysicsTelecommunicationsNanotechnologyFabrication

Abstract

fetched live from OpenAlex

A 30-GHz bandpass filter is realized in a novel waveguide topology, through the use of bulk micromachining of standard (low-resistivity) silicon wafers. In this new design, the width of the rectangular waveguide structure is created through the stacking of etched silicon wafer pieces. This width-stacking approach eliminates the presence of convex corners in the design, resulting in more controllable etching. Also, this design enables the simple implementation of the split-block technique, which alleviates Ohmic contact resistance issues. This latter aspect, combined with a double-sided etching strategy that enables deep cavities to be formed, leads to very high-Q silicon micromachined resonators (Q/sub 0//spl ap/4500). A three-cavity bandpass filter was fabricated and tested leading to a deembedded insertion loss of 1dB at a center frequency of 29.7GHz, with a 3-dB bandwidth of 0.654GHz (2.2%). These results validate this new micromachined waveguide approach, and demonstrates a significant improvement over other millimeter-wave micromachined waveguide filters.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.020
GPT teacher head0.197
Teacher spread0.177 · 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

Citations27
Published2006
Admission routes1
Has abstractyes

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