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Record W2103810430 · doi:10.1002/ejoc.201000252

Synthesis of Fluorine‐Containing Molecular Rotors and Their Assembly on Gold Nanoparticles

2010· article· en· W2103810430 on OpenAlexaff
Dominic Thibeault, Michéle Auger, Jean‐François Morin

Bibliographic record

VenueEuropean Journal of Organic Chemistry · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSonogashira couplingChemistryMoietyColloidal goldMoleculeNuclear magnetic resonance spectroscopySpectroscopyNanoparticleLinear molecular geometrySolid-state nuclear magnetic resonanceMolecular dynamicsFluorineRegioselectivityCombinatorial chemistryNanotechnologyStereochemistryOrganic chemistryComputational chemistryCatalysisMaterials science

Abstract

fetched live from OpenAlex

Abstract A series of eight rotors containing thiol groups for attachment to gold surfaces and fluorine atoms for solid‐state 19 F NMR spectroscopy have been prepared through linear, multistep synthesis. The common rotating part of the rotors (rotator), consisting of a 2,6‐difluorobenzene moiety, is introduced into the rotor structure through an unusual regioselective Sonogashira coupling with 2,6‐difluoro‐1,4‐diiodobenzene. Rotors with different bulky trityl headgroups were prepared, along with their linear, less hindered analogues. These molecular rotors were assembled on gold nanoparticles (AuNPs) and preliminary characterization was performed on these AuNPs in order to study the effects of the sizes of the molecules on the packing behaviour on the AuNP surfaces. As expected, we found that linear molecules adopt more closely packed structures on the surfaces than their bulky analogues. This offers a very promising opportunity to study rotation dynamics at the molecular level by solid‐state NMR spectroscopy.

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 score0.009
Threshold uncertainty score0.504

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 head0.008
GPT teacher head0.225
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

Citations11
Published2010
Admission routes1
Has abstractyes

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