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Record W2492043868 · doi:10.1039/c6cp04173f

Methanol dimer formation drastically enhances hydrogen abstraction from methanol by OH at low temperature

2016· article· en· W2492043868 on OpenAlexaff
Willem Siebrand, Zorka Smedarchina, Emilio Martı́nez-Núñez, Antonio Fernández‐Ramos

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMethanolDimerHydrogen atom abstractionAbstractionChemistryHydrogenHydrogen bondPhotochemistryOrganic chemistryMolecule

Abstract

fetched live from OpenAlex

The kinetics of the reaction of methanol with hydroxyl radicals is revisited in light of the reported new kinetic data, measured in cold expansion beams. The rate constants exhibit an approximately 10(2)-fold increase when the temperature decreases from 200 to 50 K, a result that cannot be fully explained by tunneling, as we confirm by new calculations. These calculations also show that methanol dimers are much more reactive to hydroxyl than monomers and imply that a dimer concentration of about 30% of the equilibrium concentration can account quantitatively for the observed rates. The assumed presence of dimers is supported by the observation of cluster formation in these and other cold beams of molecules subject to hydrogen bonding. The calculations imply an important caveat with respect to the use of cold expansion beams for the study of interstellar chemistry.

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 score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.006
GPT teacher head0.235
Teacher spread0.229 · 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

Citations33
Published2016
Admission routes1
Has abstractyes

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