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Record W1970434278 · doi:10.1117/12.644378

Cavity ring-down spectroscopy with a pulsed distributed feedback quantum cascade laser

2006· article· en· W1970434278 on OpenAlexafffund
Oleksandr Sukhorukov, A. Lytkine, J. Manne, J. Tulip, Wolfgang Jäger

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpectroscopyQuantum cascade laserLaserCascadeAtomic physicsCavity ring-down spectroscopyAnalytical Chemistry (journal)Materials scienceChemistryPhysicsOptics

Abstract

fetched live from OpenAlex

A pulsed distributed feedback quantum cascade laser operating near 970 cm-1 (10.3 μm) was coupled with the technique of cavity ring-down spectroscopy, as described here for the first time. The newly constructed set-up was tested by recording three relatively weak rotational lines of the 1000→0001 vibrational band of CO2 in the range from 966.75 cm-1 to 971.5 cm-1. The CO2 lines were recorded by measuring the decay time of a CO2 - N2 mixture flowing through an open sample tube placed between the cavity ring-down mirrors. The quantum cascade laser frequency was tuned at a rate of ~ 0.071 cm-1/K by changing the heat sink temperature in the range between -20 and 50 °C. The first results demonstrated the applicability and high sensitivity of the cavity ring-down spectroscopy - pulsed quantum cascade laser combination and encouraged us to extend our research to the study and detection of ammonia. We demonstrated that a detection limit of ammonia of ~ 25 ppbv can be attained with the current set-up. Basic instrument performance and optimization of the experimental parameters for sensitivity improvement are discussed.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.222
Teacher spread0.216 · 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

Citations11
Published2006
Admission routes2
Has abstractyes

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