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Record W2027214243 · doi:10.1117/12.804794

Pulsed quantum cascade laser based cavity ring-down and cavity enhanced spectroscopy for the detection of ethylene.

2008· article· en· W2027214243 on OpenAlexafffund
J. Manne, Wolfgang Jäger, J. Tulip

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsQuantum cascade laserLaserCavity ring-down spectroscopySpectroscopyMaterials scienceCascadeDemodulationOptical cavityOpticsDetection limitOptoelectronicsAnalytical Chemistry (journal)ChemistryPhysics

Abstract

fetched live from OpenAlex

We investigated the use of a pulsed, distributed feedback (DFB) quantum cascade (QC) laser centered at 970 cm<sup>-1</sup> in combination with cavity ring-down spectroscopy (CRDS) and cavity enhanced spectroscopic (CES) techniques for the detection of ethylene. In these techniques, the laser is coupled to a high-finesse cavity formed by high reflectivity mirrors. In the CRDS application, the laser frequency was tuned at a rate of ~0.071 cm<sup>-1</sup>/K by changing the heat sink temperature in the range between -20 and 50&deg;C. For off-axis CES, the laser was excited with short current pulses (5-10 ns), and the pulse amplitude was modulated with an external current ramp which gave a frequency scan of ~0.3 cm<sup>-1</sup>. We utilized a demodulation approach followed by numerical filtering to improve the signal-to-noise ratio. Basic instrument performance and optimizations of the experimental parameters for sensitivity improvement are discussed. We demonstrated a detection limit of ~130 ppb with CRDS and ~15 ppb with off-axis CES for ethylene.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.063
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.239
Teacher spread0.228 · 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.

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

Citations1
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicSpectroscopy and Laser ApplicationsFrench-language works237,207