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Record W2293999363 · doi:10.1002/adfm.201504604

Free‐Standing Functionalized Graphene Oxide Solid Electrolytes in Electrochemical Gas Sensors

2016· article· en· W2293999363 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Functional Materials · 2016
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsAlcohol Countermeasure Systems (Canada)University of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsMaterials scienceElectrolyteGrapheneElectrochemical gas sensorOxideDetection limitElectrochemistryConductivityChemical engineeringAcetoneSelectivityNanotechnologyElectrodeOrganic chemistryChromatographyCatalysis

Abstract

fetched live from OpenAlex

A free‐standing sulfonic acid functionalized graphene oxide (fSGO)‐based electrolyte film is prepared and used in an electrochemical gas sensor, an alcohol fuel cell sensor (AFCS), for the detection of alcohol. The fSGO electrolyte film‐based AFCS detects ethanol vapor with excellent response, linearity, and sensitivity, since it possesses a high proton conductivity (58 mS cm −1 at 55 °C). An ethanol detection limit level as low as 25 ppm is achieved and high selectivity for ethanol over acetone is demonstrated. These results do not only show the promising potential of fSGO films in an electrochemical gas sensors, specifically a portable breathalyzer, but also open an alternative pathway to investigate the application of graphene derivatives in the field of gas sensors.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.018
Threshold uncertainty score0.998

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)0.0030.000

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 head0.194
Teacher spread0.188 · 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