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Record W2087427089 · doi:10.1021/jp053142u

Influence of π-Stacking on the Resonant Enhancement of the Second-Order Nonlinear Optical Response of Dipolar Chromophores

2005· article· en· W2087427089 on OpenAlexafffund
Wei Zhang, Anthony F. Cozzolino, A.H. Mahmoudkhani, Mark Tulumello, Sarah Mansour, Ignacio Vargas‐Baca

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2005
Typearticle
Languageen
FieldMaterials Science
TopicNonlinear Optical Materials Research
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHyperpolarizabilityChromophoreDipoleStackingSecond-harmonic generationWavelengthExcitationMolecular physicsMaterials scienceNonlinear opticsCrystal (programming language)Rayleigh scatteringNonlinear opticalScatteringChemistryMoleculeNonlinear systemOpticsOptoelectronicsPhotochemistryPhysicsPolarizability

Abstract

fetched live from OpenAlex

The wavelength-dependent second-harmonic generation (SHG) efficiency of two simple dipolar chromophores, 4-NO2C6H4N(H)Bun (1) and 4-NO2C6H4SN(H)But (2), was compared in solution and in the solid state. Hyper-Rayleigh scattering measurements at 532 nm provided comparable molecular first hyperpolarizabilities. Both compounds crystallize in non-centrosymmetric space groups, but a more efficient arrangement of dipole moments results in a significantly larger deff value for 2. Kurtz-Perry experiments from 450 to 700 nm revealed an important difference in the resonant component of the nonlinear optical responses of these compounds; the SHG efficiency of crystalline 1 depends more strongly on the incident wavelength than that of 2. This would be in contradiction with the TD-DFT excitation energies calculated for these molecules, but the observation can be explained by the resonant contribution from low-energy interchromophore excitations enabled by pi-stacking in the crystal of 1.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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 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

Citations6
Published2005
Admission routes2
Has abstractyes

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