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Record W2964466453 · doi:10.15278/isms.2019.tf06

PRODUCT BRANCHING AND LOW TEMPERATURE REACTION KINETICS BY CHIRPED-PULSE FOURIER TRANSFORM MM-WAVE SPECTROSCOPY IN A PULSED UNIFORM SUPERSONIC FLOW

2019· article· en· W2964466453 on OpenAlexaboutno aff
Nureshan Dias, Bernadette M. Broderick, Arthur G. Suits, Nicolas Suas-David, Ritter Krueger

Bibliographic record

VenueProceedings of the 74th International Symposium on Molecular Spectroscopy · 2019
Typearticle
Languageen
FieldEngineering
TopicField-Flow Fractionation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsFourier transform spectroscopyMaterials scienceBranching (polymer chemistry)Fourier transformChoked flowSupersonic speedSpectroscopyFourier transform infrared spectroscopyPulse (music)OpticsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

The CRESU technique (French acronym for “reaction kinetics in uniform supersonic flows”) has been applied with great success in the past two decades to study the kinetics of reactions at low temperatures. In this approach, a uniform low temperature flow is produced via a Laval nozzle expansion giving a wall-less reactor at constant pressure and low temperature. Product detection in that work has been either with laser-induced fluorescence directly in the flow or vacuum ultraviolet photoionization after sampling. We have recently combined low temperature Laval flows with broadband mm-wave detection (chirped-pulse/uniform flow or “CPUF”) to study product branching in photodissociation and reaction.\\footnote{Oldham, J. M.; Abeysekera, C.; Joalland, B.; Zack, L. N.; Prozument, K.; Sims, I. R.; Park, G. B.; Field, R. W.; Suits, A. G. 2014, 141, 154202} Because chirped-pulse microwave detection requires monitoring the free induction decay on the timescale of microseconds, it cannot be employed at the high densities we achieve in the flows. We have used two approaches to overcome this limitation. In one, we used a “quasi-uniform” flow in which an unoptimized Laval flow was followed by a second expansion to lower temperature and density.\\footnote{Dias, N.; Joalland, B.; Ariyasingha, N. M.; Suits, A. G.; Broderick, B. M. The Journal of Physical Chemistry A 2018, 122, 7523-7531.}\\footnote{Broderick, B. M.; Suas-David, N.; Dias, N.; Suits, A. G. Physical Chemistry Chemical Physics 2018, 20, 5517-5529.} Detailed fluid dynamics simulations allow us to understand the temperature and density throughout that flow. Product branching can be measured under these conditions but not kinetics, as the conditions vary throughout the flow. Recently we have implemented airfoil sampling\\footnote{Soorkia, S.; Liu, C.-L.; Savee, J. D.; Ferrell, S. J.; Leone, S. R.; Wilson, K. R. Review of Scientific Instruments 2011, 82, 124102.} of an optimized flow. This allows us to study low temperature kinetics as in CRESU, but with the power of broadband mm-wave spectroscopy. Recent results for several systems relevant to chemistry in cold molecular clouds and planetary atmospheres will be presented using both the quasi-uniform flow and airfoil sampling.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score1.000

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 integrity0.0000.001
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 head0.003
GPT teacher head0.200
Teacher spread0.197 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the 74th International Symposium on Molecular SpectroscopySame topicField-Flow Fractionation TechniquesFrench-language works237,207