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Record W2761301896 · doi:10.1109/mwsym.2017.8058827

Flexible coupled microwave ring resonators for contactless microbead assisted volatile organic compound detection

2017· article· en· W2761301896 on OpenAlexaff
Zahra Abbasi, Mohammad H. Zarifi, Pooya Shariati, Zaher Hashisho, Mojgan Daneshmand

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicrowaveMaterials scienceResonatorOptoelectronicsSubstrate (aquarium)AdsorptionDetectorElectrodeAnalytical Chemistry (journal)ChemistryElectrical engineeringChromatographyComputer science

Abstract

fetched live from OpenAlex

In this paper, a new microwave contactless sensor is presented to monitor the level of volatile organic compound (VOC) in a dry gas stream. The platform is based on two passive ring resonators, which are magnetically coupled where the sensing tag is implemented on a flexible RF substrate. The wireless coupling between the reader and the tag, enables contactless as well as sensitive sensing. The microwave sensor operates at 4 GHz while the distance between the reader and the tag can be extended up to 1.5 cm. To increase the sensitivity of the sensor, VOC polymeric adsorbent beads (V503) are used inside a cylindrical quartz reactor and the tag monitors the adsorption on the V503 bed directly. Various concentrations of Methyl Ethyl Ke-tone (MEK) and Cyclohexane in the range of 250 to 1000 ppm are detected distinctively. The sensor demonstrates a sensitivity of 40 kHz/ppm for MEK and 2 kHz/ppm for Cyclohexane operating as a real-time detector.

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.248
Teacher spread0.226 · 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

Citations33
Published2017
Admission routes1
Has abstractyes

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