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Record W7029962257

Low temperature kinetics of the CH3OH + OH reaction.

2014· article· en· W7029962257 on OpenAlexaboutno aff

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsReaction rate constantAnalytical Chemistry (journal)Atmospheric temperature rangeKineticsWork (physics)MethanolYield (engineering)Quantum yieldRange (aeronautics)
DOInot available

Abstract

fetched live from OpenAlex

The rate constant of the reaction between methanol and the hydroxyl radical has been studied in the temperature range 56-202 K by pulsed laser photolysis-laser induced fluorescence in two separate experiments using either a low temperature flow tube coupled to a time-of-flight mass spectrometer or a pulsed Laval nozzle apparatus. The two independent techniques yield rate constants that are in mutual agreement and consistent with the results reported previously below 82 K [Shannon et al. Nat. Chem. 2013, 5, 745-749] and above 210 K [Dillon et al. Phys. Chem. Chem. Phys. 2005, 7, 349-355], showing a very sharp increase with decreasing temperature with an onset around 180 K. This onset is also signaled by strong chemiluminescence tentatively assigned to formaldehyde, which is consistent with the formation of the methoxy radical at low temperature by quantum tunnelling, and its subsequent reaction with H and OH. Our results add confidence to the previous low temperature rate constant measurements and consolidate the experimental reference data set for further theoretical work required to describe quantitatively the tunnelling mechanism operating in this reaction. An additional measurement of the rate constant at 56 K yielded a value of (4.9 ± 0.8) × 10(-11) cm(3) molecule(-1) s(-1) (2σ), showing that the rate constant is increasing less rapidly at temperatures below 70 K.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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