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Record W2008394718 · doi:10.1021/la703812t

Multidentate Surface Ligand Exchange for the Immobilization of CdSe/ZnS Quantum Dots and Surface Quantum Dot-Oligonucleotide Conjugates

2008· article· en· W2008394718 on OpenAlexaff
W. Russ Algar, Ulrich J. Krull

Bibliographic record

VenueLangmuir · 2008
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersVlaamse regering
KeywordsQuantum dotChemistryDenticityLigand (biochemistry)Bathochromic shiftOligonucleotideNanotechnologyMaterials scienceMetalFluorescenceOrganic chemistryDNA

Abstract

fetched live from OpenAlex

A method for synthesizing multidentate thiol ligands on fused silica surfaces (e.g., optical fibers) was developed for the immobilization of CdSe/ZnS quantum dots (QDs) capped with hydrophilic or hydrophobic ligands. This work was motivated by the poor stability of QDs immobilized via monodentate thiol ligands and the need for stable immobilization strategies in the development of sensor technologies based on QDs. Multi-dentate immobilization was able to withstand washing protocols, and surface ligand exchange occurred via self-assembly through the zinc-metal affinity interaction. Atomic force and scanning electron microscopy images suggested that the QDs were immobilized at high density, approximately 2-4 x 10 (13) cm (-2). It was possible to immobilize one, two, or three colors of QD. Upon immobilization, 1-2 nm bathochromic shifts in the PL spectra were observed. This was attributed to both ligand exchange and the change in local environment. The change in environment was accompanied by a decrease in PL lifetime. Self-assembly of immobilized QD-oligonucleotide and QD-avidin conjugates was also demonstrated. These conjugates were able to hybridize with complementary oligonucleotide and bind biotin, respectively. This versatile immobilization chemistry is an important step in the development of surface-based QD nanosensors. Such technology requires QDs to be immobilized such that they remain accessible to target molecules in solution.

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)0.001
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 score0.027
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.257
Teacher spread0.217 · 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

Citations49
Published2008
Admission routes1
Has abstractyes

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