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Record W2081216851 · doi:10.1139/v10-108

Nonlinear time-dependent density functional theory investigation and visualization of ionizations in CO<sub>2</sub> — Effects of laser intensities and molecular orientations

2010· article· en· W2081216851 on OpenAlexafffundvenue
Emmanuel Penka Fowe, André D. Bandrauk

Bibliographic record

VenueCanadian Journal of Chemistry · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryIonizationTime-dependent density functional theoryAtomic orbitalAtomic physicsMolecular orbitalLaserDensity functional theoryElectronHigh harmonic generationPolarization (electrochemistry)Molecular physicsIonization energyComputational chemistryMoleculePhysicsOpticsIonQuantum mechanics

Abstract

fetched live from OpenAlex

Time-dependent density functional theory (TDDFT) studies of the ionization of CO2 by intense laser pulses Io ≥ 1 × 1014 W/cm2, at 800 nm are presented using the LB94 and the LDA potentials. Results reveal that for lower laser peak intensity, Io = 3.5 × 1014 W/cm2, the highest occupied molecular orbital (HOMO) contributes significantly to ionization owing to its lower ionization potential (IP), whereas the inner orbitals play the important role for higher laser peak intensities. Even though such lower orbitals have higher IP, the ionization process occurs when orbital densities are maximum along the direction of the laser field polarization. These findings are confirmed through the analysis of the images from the time-dependent electron localization function (TDELF) and the spectra of higher order harmonic generation (HOHG). Additionally, in spite of the IP difference between Kohn–Sham orbitals from LDA and LB94 potentials, our results show almost the same trend for both.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0030.000

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 head0.003
GPT teacher head0.203
Teacher spread0.200 · 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
Published2010
Admission routes3
Has abstractyes

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