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Record W2124793126 · doi:10.1021/jp0768975

Pulsed Field Gradient NMR Studies of Polymer Adsorption on Colloidal CdSe Quantum Dots

2008· article· en· W2124793126 on OpenAlexaff
Lei Shen, Ronald Soong, Mingfeng Wang, Anna Lee, Chi Wu, Gregory D. Scholes, Peter M. Macdonald, Mitchell A. Winnik

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2008
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPulsed field gradientQuantum dotColloidAdsorptionPolymerMaterials scienceField (mathematics)Chemical physicsNanotechnologyNuclear magnetic resonanceChemistryPhysicsPhysical chemistryMoleculeComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Pulsed field gradient nuclear magnetic resonance (PFG NMR) experiments have been used to examine ligand exchange between poly(2-(N,N-dimethylamino)ethyl methacrylate) (PDMA) (Mn = 12,000, Mw/Mn = 1.20, Nn = 78) and trioctylphosphine oxide (TOPO) bound to the surface of CdSe/TOPO quantum dots (QDs). We show that PFG 1H NMR can quantify the displacement of TOPO by PDMA through its ability to differentiate signals due to TOPO bound to the QDs versus those from TOPO molecules free in solution. For CdSe QDs with a band edge absorption maximum at 558 nm (diameter 2.7 nm by transmission electron microscopy), we determined that, at saturation, 8 polymer chains on average displace greater than 90% of the surface TOPO groups. At partial saturation, with an average of 6 polymer chains/QD, each TOPO displaced requires 28 DMA repeat units. Assuming that one Me2N- group binds to a surface Cd2+ for each TOPO displaced, we infer that only about 3% of the DMA units are directly bound to the surface. The remaining groups are present as loops or tails that protrude into the solvent and increase the hydrodynamic diameter of the particles.

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 score0.278

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 head0.040
GPT teacher head0.274
Teacher spread0.234 · 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

Citations42
Published2008
Admission routes1
Has abstractyes

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