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Record W2141232868 · doi:10.1002/cphc.201201008

Understanding Photophysical Effects of Cucurbituril Encapsulation: A Model Study with Acridine Orange in the Gas Phase

2013· article· en· W2141232868 on OpenAlexafffund
Martin F. Czar, Rebecca A. Jockusch

Bibliographic record

VenueChemPhysChem · 2013
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFluorescenceCucurbiturilChemistryAcridine orangePhotochemistrySolvatochromismExcimerAqueous solutionCyanineChemical physicsSolventMoleculeOrganic chemistrySupramolecular chemistryOptics

Abstract

fetched live from OpenAlex

Encapsulation of dyes by cucurbituril macrocycles has proven profitable as a strategy to alter fluorescence characteristics in useful ways. Encapsulation generally results in longer fluorescence lifetimes, enhanced brightness, and solvatochromic effects not normally seen in the condensed phase. These effects have been attributed variously to both the removal of interactions with solvent molecules and to the confined environment of extremely low polarizability provided by the cucurbituril interior. It is difficult to disentangle these effects in solution. Here, we present results from gas-phase experiments designed to separate these effects, using cucurbit[7]uril (CB7), and the cationic dye acridine orange (AOH(+)) as a probe. Fluorescence properties of gaseous AOH(+) are compared with those of the gaseous AOH(+)-CB7 complex and with the properties of the dye and complex in aqueous solution. The dependence on the local environment of several spectroscopic properties is discussed, including the fluorescence excitation and emission maxima, the size of the Stokes shift, fluorescence lifetime and relative brightness. An understanding of the modulation of fluorescence properties by the local environment, such as that promoted by this work, will aid in the rational design of improved fluorophores and fluorescent sensors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.025
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.042
GPT teacher head0.286
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 teacher head, 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

Citations37
Published2013
Admission routes2
Has abstractyes

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