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Record W4214725564 · doi:10.1088/1361-6455/ac4e66

Carbon K-edge x-ray emission spectroscopy of gas phase ethylenic molecules

2022· article· en· W4214725564 on OpenAlexaff
Rebecca A. Ingle, Ambar Banerjee, Camila Bacellar, T. Barillot, Luca Longetti, Marcello Coreno, Monica de Simone, F. Zuccaro, Luca Poletto, Paolo Miotti, Anja Röder, Albert Stolow, Michael S. Schuurman, Michael Odelius, Majed Chergui

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsUniversity of Ottawa
FundersH2020 Marie Skłodowska-Curie ActionsCarl Tryggers Stiftelse för Vetenskaplig ForskningNational Science CouncilEuropean CommissionSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungVetenskapsrådetNational Science Foundation
KeywordsAlleneSpectral lineChemistryContext (archaeology)MoleculeEmission spectrumSpectroscopyDensity functional theoryCarbon fibersAtomic physicsMaterials sciencePhysicsComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract We report on the C K-edge x-ray absorption spectra and the resonant (RXES) and non-resonant (NXES) x-ray emission spectra of ethylene, allene and butadiene in the gas phase. The RXES and NXES show clear differences for the different molecules. Overall both types of spectra are more structured for ethylene and allene, than for butadiene. Using density functional theory–restricted open shell configuration interaction single calculations, we simulate the spectra with remarkable agreement with the experiment. We identify the spectral features as being due to transitions involving localised 1s orbitals. For allene, there are distinct spectral bands that reflect transitions predominantly from either the central or terminal carbon atoms. These results are discussed in the context of ultrafast x-ray studies aimed at detecting the passage through conical intersections in polyatomic molecules.

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 categoriesMeta-epidemiology (narrow)
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 score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.263
Teacher spread0.256 · 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 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

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

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