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Record W1978447571 · doi:10.1029/2003ja010132

Dissociative recombination of N<sub>2</sub><sup>+</sup>, O<sub>2</sub><sup>+</sup>, and NO<sup>+</sup>: Rate coefficients for ground state and vibrationally excited ions

2004· article· en· W1978447571 on OpenAlexaff
C Sheehan

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsWestern University
Fundersnot available
KeywordsDissociative recombinationExcited stateIonAtomic physicsRecombinationGround statePhysicsExcitationElectronDissociation (chemistry)ChemistryPhysical chemistryNuclear physics

Abstract

fetched live from OpenAlex

We review recent advances in the study of the dissociative recombination of molecular ions with electrons with a primary emphasis on experimental studies. In particular, we focus on previous experimental measurements of recombination rates for N 2 + , O 2 + , and NO + ions. In the context of this review, we present temperature dependent rate coefficients from recent merged beam studies of the dissociative recombination of N 2 + , O 2 + , and NO + ions with electrons. Identifying underlying physical differences between the various experimental techniques enables a discussion of the effects of vibrational excitation on the dissociative recombination of these major ionospheric species of ions. For T &lt; 1200 K, we conclude that the recombination rates for N 2 + , O 2 + , and NO + ions in the ground electronic and vibrational states respectively are 2.2 × 10 −7 (T e /300) −0.39 cm 3 s −1 , 1.95 × 10 −7 (T e /300) −0.70 cm 3 s −1 , and (3.5 ± 0.5) × 10 −7 (T e /300) −0.69 cm 3 s −1 . Vibrational excitation is shown to play a significant role in laboratory measurements of these recombination rates. For each of these species, vibrationally excited ions yielded a lower recombination rate than the ground state. We also discuss the recombination of these species of ions for T &gt; 1200 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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
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 head0.020
GPT teacher head0.275
Teacher spread0.255 · 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 designSimulation or modeling
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

Citations114
Published2004
Admission routes1
Has abstractyes

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