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Record W2153450730 · doi:10.1109/icsens.2004.1426418

New optical sensor for volatile organic compounds (VOC) using birefringent porous glass

2006· article· en· W2153450730 on OpenAlexaff
Éric Pinet, M. Vachon-Savary, S. K. Dube

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsFISO Technologies (Canada)
Fundersnot available
KeywordsPolarizerMaterials scienceBirefringenceMicroporous materialPorosityPyrolytic carbonPorous glassOptoelectronicsOpticsComposite materialChemistryPyrolysisOrganic chemistry

Abstract

fetched live from OpenAlex

Changes observed in polarized light transmission through an anisotropic material, such as birefringent porous glass, upon contact with air bearing vapors of volatile organic compounds serve as the basis for a very sensitive broadband chemical sensor. When properly designed, vapor sensors based on such porous glasses show changes in transmitted light intensity or spectral content (color) detectable by eye. When placed between two crossed polarizers, the form-birefringent porous glass produces an observable phase shift that undergoes a readily detectable decrease upon exposure to all organic vapors we tested thus far. The optical effects resulting from exposure to vapors are reversible and believed to result from capillary condensation of solvent vapors and attendant reduction of anisotropy. A good control of the microporous structure as well of the surface chemistry offers flexibility for tuning the sensor response to VOC industrial applications. Simple sensor miniaturization with low cost materials is possible.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

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