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Record W2314537361 · doi:10.1149/1.3367231

(Invited) Investigation into the Photophysics and Diffusion Properties of Water Soluble Quantum Dots Using Fluorescence Correlation Spectroscopy

2010· article· en· W2314537361 on OpenAlexafffund
Robert Peters, Jane Betty Goh, J. Dinglasan, Anupma Thakur, Shyemaa Shehata, Darren Anderson, Cécile Fradin

Bibliographic record

VenueECS Transactions · 2010
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsQuantum dotFluorescence correlation spectroscopyQuantum yieldFluorescenceSpectroscopyMaterials scienceChemical physicsAqueous solutionDiffusionNanoparticleChemistryAnalytical Chemistry (journal)PhotochemistryNanotechnologyPhysical chemistryPhysicsOpticsQuantum mechanicsOrganic chemistry

Abstract

fetched live from OpenAlex

Because of their superior photostability and fluorescence quantum yield, quantum dots are of great interest for biological applications. Unfortunately, most commercial quantum dots require a surfactant solubilizing layer to disperse in aqueous media. This significantly increases their effective diameter and limits their appeal for single molecule studies. Thus Carboxylate capped CdTe nanoparticles, which are water soluble, represent an attractive solution. We used fluorescence correlation spectroscopy to characterize the properties of these quantum dots. Our study confirms that they have small ~ 10 nm hydrodynamic radii. It also confirms that they undergo an excitation intensity dependent blinking process characterized by a power law distribution of "on" and "off" dwell times. This power law breaks down at dwell times on the order of ~10 μs.

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 score0.060
Threshold uncertainty score0.433

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 studies0.0010.000
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 head0.021
GPT teacher head0.218
Teacher spread0.197 · 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

Citations2
Published2010
Admission routes2
Has abstractyes

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