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Record W2069337138 · doi:10.3390/s150204253

Differential Wide Temperature Range CMOS Interface Circuit for Capacitive MEMS Pressure Sensors

2015· article· en· W2069337138 on OpenAlexafffund
Yucai Wang, Vamsy P. Chodavarapu

Bibliographic record

VenueSensors · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCMOSCapacitive sensingLinearityMaterials scienceCapacitanceMicroelectromechanical systemsElectrical engineeringInterface (matter)Pressure sensorOptoelectronicsElectronic engineeringBiasingVoltageEngineeringChemistryMechanical engineering

Abstract

fetched live from OpenAlex

We describe a Complementary Metal-Oxide Semiconductor (CMOS) differential interface circuit for capacitive Micro-Electro-Mechanical Systems (MEMS) pressure sensors that is functional over a wide temperature range between -55 °C and 225 °C. The circuit is implemented using IBM 0.13 μm CMOS technology with 2.5 V power supply. A constant-gm biasing technique is used to mitigate performance degradation at high temperatures. The circuit offers the flexibility to interface with MEMS sensors with a wide range of the steady-state capacitance values from 0.5 pF to 10 pF. Simulation results show that the circuitry has excellent linearity and stability over the wide temperature range. Experimental results confirm that the temperature effects on the circuitry are small, with an overall linearity error around 2%.

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: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.237
Teacher spread0.216 · 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

Citations19
Published2015
Admission routes2
Has abstractyes

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