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Record W2037209527 · doi:10.1093/mnras/stu2508

Small molecules from the decomposition of interstellar carbons

2014· article· en· W2037209527 on OpenAlexaff
W. W. Duley, Ali Zaidi, Michal J. Wesolowski, S. Kuzmin

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInterstellar mediumMoleculeAstrochemistryBenzeneDecompositionHydrocarbonMass spectrumCarbon fibersPhysicsRadicalAlkaneInfrared spectroscopyAlkylPhotochemistryMass spectrometryChemistryAstrophysicsMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

We have studied the molecular products of the photo-induced decomposition of hydrogenated amorphous carbon (HAC) and solid hexane, C6H14, using mass spectroscopy. Mass spectra of HAC are dominated by simple hydrocarbon molecules having fewer than four carbon atoms. Notable products include C3H2, phenyl, C6H5, benzene, C6H6, and a variety of partially dehydrogenated alkane molecules with the composition CnH2n-1. Hexane, chosen as a representative solid alkane, has a more complex mass spectrum which includes Cn and a number of hydrocarbon molecules with up to 10 carbon atoms. As alkyl radicals, CnH2n-1, are commonly found in the decomposition of alkanes, we have used high precision density functional theory to simulate the infrared spectrum of 1-, 2-, and 3-hexyl radicals as well as that of the 3-hexyl ion, C6H13+. The latter could be detectable in interstellar/circumstellar sources via a strong feature at 3.66 μm. The appearance of C3H2 as a decomposition product of photodissociated HAC may be related to the ubiquitous presence of c-C3H2 in the interstellar medium. The production of such molecules in the interstellar medium through a ‘top-down’ chemistry deriving from the decomposition of HAC is discussed.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.382

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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 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

Citations28
Published2014
Admission routes1
Has abstractyes

Explore more

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