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Record W2325772006 · doi:10.1021/jp406196a

Charge Transfer in CdSe Nanocrystal Complexes with an Electroactive Polymer

2013· article· en· W2325772006 on OpenAlexaff
Megan Oh, Ming Chen, Chi-Hung Chuang, Gerard J. Wilson, Clemens Burda, Mitchell A. Winnik, Gregory D. Scholes

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2013
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNanocrystalChemical physicsMaterials sciencePassivationSolventDielectricSemiconductorPolymerCharge (physics)Electron transferNanotechnologyPhotochemistryChemistryOptoelectronicsOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

A better understanding of the essential interaction of semiconductor nanocrystals with their adsorbates and surrounding media can be used for controlling and optimizing the energy or charge transfer reactions found in these systems and also for comparing a diverse assortment of photoexcited charge transfer systems found in the latest materials research. In this study, the photoinduced interfacial charge transfer system, a complex of CdSe semiconductor nanocrystals and electroactive polymers containing ruthenium(II) tris(bipyridine), is characterized and then investigated in a comprehensive range of dielectric solvents from toluene to water. The effects of the solvent on the nanocrystal and adsorbate/ligand as well as the charge transfer dynamics of the system are explored through the fluorescence lifetime of the nanocrystal. Through this investigation it was found that fluorescence decays showed the presence of two decay components, which are influenced by solvent dielectric contributions on nanocrystal passivation and surface traps, and charge transfer processes present in the system. The results of the fluorescence decays were put into perspective using Marcus theory, providing some general insight on QD-based charge transfer systems and the effects of solvent polarity.

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 score0.001
Threshold uncertainty score0.876

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)0.0010.000

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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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

Citations20
Published2013
Admission routes1
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicQuantum Dots Synthesis And PropertiesFrench-language works237,207