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Record W2025414424 · doi:10.1063/1.3514931

Metastable anions of dinitrobenzene: Resonances for electron attachment and kinetic energy release

2010· article· en· W2025414424 on OpenAlexfundno aff
Andreas Mauracher, Stephan Denifl, Achim Edtbauer, Michaela Hager, M. Probst, O. Echt, T. D. Märk, P. Scheier, T. A. Field, K. Graupner

Bibliographic record

VenueThe Journal of Chemical Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
FundersEuropean Social FundEuropean CommissionQueen's UniversityÖsterreichischen Akademie der WissenschaftenAustrian Science FundQueen's University Belfast
KeywordsMetastabilityKinetic energyChemistryDissociation (chemistry)Yield (engineering)ElectronAdiabatic processAtomic physicsPhysical chemistryMaterials sciencePhysicsNuclear physicsThermodynamics

Abstract

fetched live from OpenAlex

Attachment of free, low-energy electrons to dinitrobenzene (DNB) in the gas phase leads to DNB(-) as well as several fragment anions. DNB(-), (DNB-H)(-), (DNB-NO)(-), (DNB-2NO)(-), and (DNB-NO(2))(-) are found to undergo metastable (unimolecular) dissociation. A rich pattern of resonances in the yield of these metastable reactions versus electron energy is observed; some resonances are highly isomer-specific. Most metastable reactions are accompanied by large average kinetic energy releases (KER) that range from 0.5 to 1.32 eV, typical of complex rearrangement reactions, but (1,3-DNB-H)(-) features a resonance with a KER of only 0.06 eV for loss of NO. (1,3-DNB-NO)(-) offers a rare example of a sequential metastable reaction, namely, loss of NO followed by loss of CO to yield C(5)H(4)O(-) with a large KER of 1.32 eV. The G4(MP2) method is applied to compute adiabatic electron affinities and reaction energies for several of the observed metastable channels.

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 score0.254
Threshold uncertainty score0.395

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 head0.261
Teacher spread0.252 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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