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Record W2118901455 · doi:10.1021/nn203272p

Probing the “Dark” Fraction of Core–Shell Quantum Dots by Ensemble and Single Particle pH-Dependent Spectroscopy

2011· article· en· W2118901455 on OpenAlexafffund
Nela Durisic, Antoine G. Godin, Derrel Walters, Peter Grütter, Paul W. Wiseman, Colin D. Heyes

Bibliographic record

VenueACS Nano · 2011
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsMcGill University
FundersNational Center for Research ResourcesCanadian Institutes of Health Research
KeywordsQuantum dotFluorescenceFluorescence correlation spectroscopyParticle (ecology)Fluorescence spectroscopySpectroscopyMaterials scienceChemical physicsBrightnessChemistryAnalytical Chemistry (journal)Molecular physicsPhotochemistryNanotechnologyPhysicsOptics

Abstract

fetched live from OpenAlex

The optical properties of core-shell CdSe-ZnS quantum dots (QDs) are characterized by complex photophysics leading to difficulties in interpreting quantitative measurements based on QD emission. By comparing the pH dependence of fluorescence of single QDs to that of an ensemble, we have been able to propose a molecular scale model of how QD surface chemical and physical processes are affected by protons and oxygen. We show that the connection between the ensemble fluorescence intensity and the single QD fluorescence properties such as dark fraction, blinking, particle brightness, and a multiexponential fluorescence lifetime decay is not trivial. The ensemble fluorescence intensity is more weakly dependent on pH than the single particle fluorescence which, together with fluorescence lifetime analysis, provided evidence that the dark fraction of QDs emits photons with low quantum efficiency and long lifetime. We uncovered two surface-dependent mechanisms that affected the fluorescence emission: an immediate physical effect of charges surrounding the QD and an irreversible chemical effect from reaction of the H(+) and O(2) with the QD shell surface. These results will have important implications for those using QD-based fluorescence lifetime imaging as well as for proper implementation of these probes for quantitative cellular imaging applications.

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 score0.002
Threshold uncertainty score0.285

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 head0.047
GPT teacher head0.239
Teacher spread0.192 · 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

Citations77
Published2011
Admission routes2
Has abstractyes

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