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Record W2950674901 · doi:10.3390/s19122680

A Sub-mW 18-MHz MEMS Oscillator Based on a 98-dBΩ Adjustable Bandwidth Transimpedance Amplifier and a Lamé-Mode Resonator

2019· article· en· W2950674901 on OpenAlexafffund
Anoir Bouchami, Mohannad Y. Elsayed, Frédéric Nabki

Bibliographic record

VenueSensors · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec – Nature et technologiesCMC Microsystems
KeywordsTransimpedance amplifierPhase noiseResonatordBcBandwidth (computing)CMOSCapacitive sensingAmplifierElectrical engineeringCapacitanceOptoelectronicsMaterials sciencePhysicsDifferential amplifierEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a microelectromechanical system (MEMS)-based oscillator based on a Lamé-mode capacitive micromachined resonator and a fully differential high-gain transimpedance amplifier (TIA). The proposed TIA is designed using TSMC 65 nm CMOS technology and consumes only 0.9 mA from a 1-V supply. The measured mid-band transimpedance gain is 98 dB Ω and the TIA features an adjustable bandwidth with a maximum bandwidth of 142 MHz for a parasitic capacitance C P of 4 pF. The measured input-referred current noise of the TIA at mid-band is below 15 pA/ Hz . The TIA is connected to a Lamé-mode resonator, and the oscillator performance in terms of phase noise and frequency stability is presented. The measured phase noise under vacuum is -120 dBc/Hz at a 1-kHz offset, while the phase noise floor reaches -127 dBc/Hz. The measured short-term stability of the MEMS-based oscillator is ±0.25 ppm.

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 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 score0.259
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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.

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

Citations8
Published2019
Admission routes2
Has abstractyes

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