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Record W1823154646 · doi:10.1139/cjc-2013-0349

Reichardt’s dye: the NMR story of the solvatochromic betaine dye

2013· article· en· W1823154646 on OpenAlexvenueno aff
Michal Afri, Hugo E. Gottlieb, Aryeh A. Frimer

Bibliographic record

VenueCanadian Journal of Chemistry · 2013
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsnot available
FundersBar-Ilan University
KeywordsSolvatochromismChemistryBetaineChemical shiftPolarity (international relations)SolventCarbon-13 NMRPolarProtonationMoleculePhotochemistryProton NMRAbsorption (acoustics)TautomerChemical polarityComputational chemistryPhysical chemistryOrganic chemistryIon

Abstract

fetched live from OpenAlex

Reichardt’s dye, 2,6-diphenyl-4-(2,4,6-triphenyl-1-pyridinio)phenolate (1), has a very large negative solvatochromism in the long wavelength absorption in the UV–vis spectrum when going from nonpolar to polar solvents. This shift provides the basis of the important and widely used ET(30) scale of solvent polarity. While many papers have investigated the properties of this dye, only a few describe the 1H and 13C NMR assignments in any detail. We report herein, our detailed analysis of the proton and carbon chemical shift assignments for this molecule based on 1D and 2D NMR measurements, as well as those of the protonated and methoxy derivatives 2 and 3, respectively. Much to our surprise, some of the critical chemical shift values we observed were significantly different from those previously reported. In addition, we discovered a good correlation not only between the solvent polarity and the chemical shifts of carbons C1 and C4 of Reichardt’s dye (1), but also between the concentration of the dye and these chemical shifts.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.007
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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