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Record W2020940866 · doi:10.1021/cm0000752

Excited-State Behavior of Nile Blue H-Aggregates Bound to SiO<sub>2</sub>and SnO<sub>2</sub>Colloids

2000· article· en· W2020940866 on OpenAlexaff
Chouhaid Nasr, Surat Hotchandani

Bibliographic record

VenueChemistry of Materials · 2000
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsExcited stateNile blueAqueous solutionColloidAbsorption (acoustics)Ultrafast laser spectroscopyElectron transferChemistryCationic polymerizationPhotochemistryAnalytical Chemistry (journal)Materials scienceChemical physicsPhysical chemistryFluorescenceLaserAtomic physics

Abstract

fetched live from OpenAlex

The spectroscopic characterization of a cationic dye, Nile Blue A (NB), in negatively charged SnO 2 and SiO 2 colloidal suspensions has been carried out. The results show that NB, in the presence of these colloidal suspensions, forms aggregates of H-type which are nonfluorescent and have blue-shifted absorption compared to the NB monomer in aqueous solution. Laser photolysis experiments have been carried out to study the excited-state dynamics of the NB aggregates. The transient absorption measurements of NB adsorbed on SiO 2 colloids (inert support) show that the H-aggregates of NB have a relatively short-lived excitonic singlet state (τ = 40 ps); the lifetime of the excited singlet of the monomer in aqueous solution is ∼390 ps. On a reactive semiconductor support like SnO 2, the NB aggregates also inject electrons into SnO 2 . This is characterized by the formation of the cation radical, (NB) 2 • +, of the NB aggregates and by the trapping of electrons the in SnO 2 nanocrystallites. The monophotonic dependence of the formation of (NB) 2 • + on SnO 2 surface supports the charge transfer from NB aggregates to SnO 2 . The rate constant for this heterogeneous electron-transfer process is ∼3.3 × 10 8 s - 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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.218
Teacher spread0.211 · 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.

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

Citations33
Published2000
Admission routes1
Has abstractyes

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