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Record W1967756142 · doi:10.1109/tvlsi.2011.2148130

Temperature Characteristics and Analysis of Monolithic Microwave CMOS Distributed Oscillators With ${G}_{m}$-Varied Gain Cells and Folded Coplanar Interconnects

2011· article· en· W1967756142 on OpenAlexaff
Kalyan Bhattacharyya, Ted H. Szymanski

Bibliographic record

VenueIEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2011
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhase noiseCMOSAmplifierOptoelectronicsMicrowaveElectrical engineeringMonolithic microwave integrated circuitCoplanar waveguidedBcMaterials scienceTopology (electrical circuits)PhysicsAnalytical Chemistry (journal)Computer scienceTelecommunicationsChemistryEngineering

Abstract

fetched live from OpenAlex

The performance of a novel Monolithic Microwave CMOS Distributed Oscillator is reported over a temperature range of -25°C to 75°C for the first time, along with an analysis of its design characteristics and its temperature stability. The oscillator is stable over the entire temperature range of 100°C. The monolithic distributed oscillator (DO) is designed and fabricated in an industry standard 0.18 μ m CMOS process, using an n-FET-based traveling wave amplifier (TWA), coplanar waveguides (CPW), and a new coplanar interconnect structure called a 'folded CPW'. The measured loss of the “folded CPW” is 1.259 dB at 10 GHz. The distributed oscillator uses a novel architecture ofGm-varied gain cells and operates at a bias of 1.8 V. The measured oscillation frequency is 11.7 GHz with 6.1 dBm output power and the measured phase noise is -116.02 dBc/Hz at 1 MHz offset, which represent the best reported power and one of the best phase noise results for silicon DOs with temperature stability.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.011
GPT teacher head0.186
Teacher spread0.175 · 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
Published2011
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Very Large Scale Integration (VLSI) SystemsSame topicRadio Frequency Integrated Circuit DesignFrench-language works237,207