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Record W4392791075 · doi:10.1139/cjc-2024-0003

DFT computation of the electron spectra of thiophene

2024· article· en· W4392791075 on OpenAlexaffvenue
Delano P. Chong

Bibliographic record

VenueCanadian Journal of Chemistry · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryDensity functional theoryThiopheneSynchrotron radiationValence electronIonizationAtomic physicsValence (chemistry)SpectroscopyCore electronElectronElectron spectroscopyIonization energySynchrotronBinding energySpectral lineComputational chemistryPhysics

Abstract

fetched live from OpenAlex

Recent experiments on thiophene using synchrotron radiation stimulated the present density functional theory (DFT) study of the various types of electron spectroscopy using the DFT methods we developed in our laboratory. Besides the confirmation of the experimental interpretations, the results of the present study strongly validate the methods used for the various types of electron spectroscopy. The average absolute deviations of the DFT results for thiophene from experiment are 0.22 eV for vertical ionization energies of outer valence electrons, 0.10 eV for carbon 1s binding energies, 0.19 eV for vertical valence excitation energies, and 0.18 eV for X-ray absorption energies. The calculated carbon 1s binding energies for bithiophene and terthiophene are also within 0.1 eV of synchrotron experiment. We conclude that workers using synchrotron radiation to study electronic processes of gas-phase molecules can apply our DFT methods for the interpretation of their experimental results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.004
GPT teacher head0.217
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes2
Has abstractyes

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