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Record W3208333713 · doi:10.3390/electronics10212646

A 6.89-MHz 143-nW MEMS Oscillator Based on a 118-dBΩ Tunable Gain and Duty-Cycle CMOS TIA

2021· article· en· W3208333713 on OpenAlexaff
Ahmed Kira, Mohannad Y. Elsayed, Karim Allidina, Vamsy P. Chodavarapu, Mourad N. El-Gamal

Bibliographic record

VenueElectronics · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsDuty cycledBcPhase noiseTransimpedance amplifierResonatorCMOSMaterials scienceMicroelectromechanical systemsAmplifierElectrical engineeringOptoelectronicsVoltageEngineeringOperational amplifier

Abstract

fetched live from OpenAlex

This article presents a 6.89 MHz MEMS oscillator based on an ultra-low-power, low-noise, tunable gain/duty-cycle transimpedance amplifier (TIA) and a bulk Lamé-mode MEMS resonator that has a quality factor (Q) of 3.24 × 106. Self-cascoding and current-starving techniques are used in the TIA design to minimize the power consumption and tune the duty-cycle of the output signal. The TIA was designed and fabricated in TSMC 65 nm CMOS process technology. Its open-loop performance has been measured separately. It achieves a tunable gain between 107.9 dBΩ and 118.1 dBΩ while dissipating only 143 nW from a 1 V supply. The duty-cycle of the output waveform can be tuned from 23.25% to 79.03%. The TIA has been interfaced and wire bonded in a series-resonant oscillator configuration with the MEMS resonator and mounted in a small cavity standard package. The closed-loop performance of the whole oscillator has been experimentally measured. It exhibits a phase noise of −128.1 dBc/Hz and −133.7 dBc/Hz at 1 kHz and 1 MHz offsets, respectively.

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 score0.386
Threshold uncertainty score0.870

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 head0.005
GPT teacher head0.202
Teacher spread0.198 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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