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Record W2138805924 · doi:10.1139/v2012-036

Ab initio calculation of the low-lying electronic states of the ZrN molecule

2012· article· en· W2138805924 on OpenAlexvenueno aff
Ayman Farhat, Mahmoud Korek, Miguel A. L. Marques, Saleh Abdul-Al

Bibliographic record

VenueCanadian Journal of Chemistry · 2012
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryComplete active spaceAb initioAtomic physicsElectronic structureDipoleExcitationConfiguration interactionPotential energyMultireference configuration interactionGround stateMoleculeComputational chemistryPhysicsQuantum mechanicsBasis setDensity functional theory

Abstract

fetched live from OpenAlex

An ab initio calculation of the low-lying electronic states of zirconium nitride (ZrN) were performed by using a complete active space self-consistent field with multireference single and double excitation configuration interaction (MRSDCI). The potential energy curves of 21 low-lying electronic states of the ZrN molecule with different spin and spatial symmetries, in the representation 2s+1Λ(+/−) and below 30 000 cm–1, were identified. The harmonic frequency (ωe), the equilibrium internuclear distance (Re), the rotational constants (Be), the electronic energy with respect to the ground state (Te), and the permanent dipole moment (µ) were calculated for the considered electronic states. The comparison of these values with those available in the literature shows a very good agreement with either theoretical or experimental data. Fifteen new electronic states were studied here for the first time.

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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.167
Teacher spread0.162 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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