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Record W4220798489 · doi:10.1139/cjc-2021-0299

Theoretical study of water-assisted reaction between methane and nitrosonium cation

2022· article· en· W4220798489 on OpenAlexaffvenue
Gennady V. Shustov

Bibliographic record

VenueCanadian Journal of Chemistry · 2022
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsChemistryCatalysisMoleculeProtonationMethaneHydrateDensity functional theoryReactivity (psychology)DecompositionActivation energyComputational chemistryPhotochemistryPhysical chemistryOrganic chemistryIon

Abstract

fetched live from OpenAlex

The water-assisted reaction between CH 4 and NO + has been studied employing post Hartree–Fock and density functional theory methods. Two reaction pathways were considered: (i) a frontside NO + attack on the C–H bond of methane with retention of configuration and (ii) a backside attack with inversion of configuration. The first pathway leads to a thermodynamically more favorable hydrate of N-protonated nitrosomethane, and the second one leads to its O-protonated isomer. The catalytic effect of a single water molecule is expressed in decreasing the activation energy for the elementary step by about a factor of two for the frontside mechanism and by a factor of four to five for the backside one when compared with the calculated literature data on water-free methane nitrosation. The combination of the activation strain model of reactivity and the energy decomposition analysis reveals that the activation barriers are largely determined by the relative stability of the termolecular reactant complexes. The crucial factor that stabilizes these complexes comes from the electrostatic attraction. The catalytic effect of the key water molecule is decreased with introduction of additional one or two explicit water molecules, which form a coordinate O→N bonding with NO + . On the contrary, an additional water molecule hydrogen bonded to the key catalytic water molecule enhances the catalytic effect.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.424

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 integrity0.0000.000
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 head0.213
Teacher spread0.202 · 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
Published2022
Admission routes2
Has abstractyes

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