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Record W2081962109 · doi:10.1063/1.3603967

On the effect of electron correlation on the static second hyperpolarizability of π conjugated oligomer chains

2011· article· en· W2081962109 on OpenAlexaff
Peter A. Limacher, Qingxu Li, Hans Peter Lüthi

Bibliographic record

VenueThe Journal of Chemical Physics · 2011
Typearticle
Languageen
FieldMaterials Science
TopicNonlinear Optical Materials Research
Canadian institutionsMcMaster University
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsHyperpolarizabilityElectronic correlationOligomerExtrapolationExcited stateCoupled clusterConjugated systemAb initioChain (unit)Molecular physicsChemistryComputational chemistryElectronMaterials scienceAtomic physicsPhysicsPolarizabilityQuantum mechanicsMathematicsMoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

In this article, we report on the ab initio calculation of the static longitudinal second hyperpolarizability (γ) of π conjugated unsaturated oligomer chains using polyacetylene and polyyne as model compounds. The common observation is that the electron correlation enhances γ in these systems. The present study reveals that for extended chain lengths the opposite appears to be true: Electron correlation may have a damping effect on this property. For double-zeta basis sets, a negative contribution from electron correlation to γ is found within the range of chain lengths investigated. For triple-zeta basis sets, the same behavior must be anticipated at larger chain lengths based on extrapolation schemes. The analysis of the excitation energies and transition moments shows that transition moments between excited states as predicted by the Hartree-Fock and coupled cluster methods have a different response to chain length extension. There also are indications that higher order correlation effects will enhance γ.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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

Citations24
Published2011
Admission routes1
Has abstractyes

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