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Record W2761572503 · doi:10.1109/mwsym.2017.8058984

Wideband LTCC transitions of flip-chip to waveguides/connectors for a highly dense phased array system-in-package at 60 GHz

2017· article· en· W2761572503 on OpenAlexaff
Saman Jafarlou, Atabak Rashidian, M. Tazlauanu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPeraso Technologies (Canada)
Fundersnot available
KeywordsWidebandStriplineTaperingStub (electronics)Phased arrayFlip chipCable glandSurface-mount technologyImpedance matchingMaterials scienceBandwidth (computing)InterconnectionElectrical impedanceChipInsertion lossElectrical engineeringPrinted circuit boardElectronic engineeringOptoelectronicsEngineeringComputer scienceTelecommunicationsAntenna (radio)

Abstract

fetched live from OpenAlex

This paper presents two types of wideband transitions from a flip-chip interconnect to external v-band rectangular waveguides and surface-mount coaxial connectors, based on LTCC technology. The flip-chip interconnect is directly connected to a multi-level stacked via allowing compact routing of RF signals for a highly dense phased array system-in-package. The signal is guided from striplines into the waveguides using a T-shape launcher and impedance matching is performed by several means including implementing a stub and tapering a near-quarter wavelength embedded waveguide. In the other design, mm-wave signals are directed from a stripline to a surface-mount 1.85 mm v-type connector to provide a compact solution for multiple input/output transceivers. Both types of transitions are fabricated and initial measurement results are presented. Compactness and low loss (0.5 dB) performance along with over 20 % bandwidth from 55 to 67 GHz make the transitions suitable for 60 GHz WiGig applications.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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