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Record W2009807238 · doi:10.1021/jp076855g

Ozone Reactions with Alkaline-Earth Metal Cations and Dications in the Gas Phase:  Room-Temperature Kinetics and Catalysis

2007· article· en· W2009807238 on OpenAlexaff
S. Feil, G. K. Koyanagi, Albert A. Viggiano, Diethard K. Böhme

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsYork University
Fundersnot available
KeywordsChemistryAlkaline earth metalOzoneCatalysisMoleculeMetalInorganic chemistryAnalytical Chemistry (journal)Mass spectrometryQualitative inorganic analysisOrganic chemistry

Abstract

fetched live from OpenAlex

Room-temperature rate coefficients and product distributions are reported for the reactions of ozone with the cations and dications of the alkaline-earth metals Ca, Sr, and Ba. The measurements were performed with a selected-ion flow tube (SIFT) tandem mass spectrometer in conjunction with either an electrospray (ESI) or an inductively coupled plasma (ICP) ionization source. All the singly charged species react with ozone by O-atom transfer and form monoxide cations rapidly, k = 4.8, 6.7, and 8.7 x 10(-10) cm3 molecule(-1) s(-1) for the reactions of Ca+, Sr+, and Ba+, respectively. Further sequential O-atom transfer occurs to form dioxide and trioxide cations. The efficiencies for all O-atom transfer reactions are greater than 10%. The data also signify the catalytic conversion of ozone to oxygen with the alkaline-earth metal and metal oxide cations serving as catalysts. Ca2+ reacts rapidly with O3 by charge separation to form CaO+ and O2+ with a rate coefficient of k = 1.5 x 10(-9) cm3 molecule(-1) s(-1). In contrast, the reactions of Sr2+ and Ba2+ are found to be slow and add O3, (k >/= 1.1 x 10-11 cm3 molecule-1 s-1). The initial additions are followed by the rapid sequential addition of up to five O3 molecules with values of k between 1 and 5 x 10(-10) cm3 molecule(-1) s(-1). Metal/ozone cluster ions as large as Sr2+(O3)5 and Ba2+(O3)4 were observed for the first time.

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 score0.687
Threshold uncertainty score0.150

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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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

Citations26
Published2007
Admission routes1
Has abstractyes

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