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Record W3111628629 · doi:10.1109/jsen.2020.3042485

An 8 mW Fully Integrated Regenerative Resonant MEMS CO<sub>2</sub> Sensor Using Linear Polyethylenimine as a Capture Layer

2020· article· en· W3111628629 on OpenAlexafffund
Alberto Prud’homme, Frédéric Nabki

Bibliographic record

VenueIEEE Sensors Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolyethylenimineResonatorMaterials scienceAnalytical Chemistry (journal)Microelectromechanical systemsPressure sensorAtmospheric pressureOptoelectronicsChemistryPhysicsEngineeringChromatographyMechanical engineering

Abstract

fetched live from OpenAlex

A fully integrated regenerative CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> MEMS sensor using a micro-resonator coated with Linear Polyethylenimine as an adsorbent layer is presented. The pyramidal cantilever micro-resonator used has a resonant frequency of 315.24 kHz with a Q factor of 1125 at atmospheric pressure. The micro-resonator was integrated with a sustaining amplifier that consumes 8 mW. The MEMS sensor sensitivity was characterized in a CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> concentration range from 1200 to 10500 ppm, showing a frequency shift of -12 Hz at 1200 ppm with a slope of -3.50 mHz / ppm over the characterized range. The adsorption and recovery times are characterized to be as low as 170 seconds and 280 seconds, respectively. The impacts of pressure, temperature and humidity on the sensor were also characterized. The behavior of the MEMS sensor is compared to that of an optical CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> sensor.

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 categoriesMeta-epidemiology (narrow)
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 score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.255
Teacher spread0.225 · 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.

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
Published2020
Admission routes2
Has abstractyes

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