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Record W2312760377 · doi:10.1021/la2038894

Facile Phase Transfer of Large, Water-Soluble Metal Nanoparticles to Nonpolar Solvents

2012· article· en· W2312760377 on OpenAlexaff
Paul J. G. Goulet, Gilles R. Bourret, R. Bruce Lennox

Bibliographic record

VenueLangmuir · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsSolventDichloromethaneChemistryNanoparticleTetrahydrofuranBromideTolueneLigand (biochemistry)ChloroformPolystyreneNanomaterialsMetalAcetonePhase (matter)DiglymeAdsorptionInorganic chemistryOrganic chemistryChemical engineeringMaterials scienceNanotechnologyPolymer

Abstract

fetched live from OpenAlex

The facile phase-transfer of large, water-soluble metal nanoparticles to nonpolar solvent is reported here. Thiol-terminated polystyrene (PS-SH) is ligand-exchanged onto water-soluble metal nanoparticles in single-phase acetone/water mixtures, generating a precipitate. The solvent is then removed and the particles are redissolved in nonpolar solvent. This approach is demonstrated for nanoparticles of different metal (Au and Ag), size (3 to >100 nm), shape (spheres, rods, and wires, etc.), and leaving ligand (citrate, cetyltrimethylammonium bromide, poly(vinylpyrrolidone), and 4-dimethylaminopyridine. The resulting PS-SH-stabilized nanoparticles maintain their initial size and shape, and are highly stable. They are soluble in various organic solvents (toluene, benzene, chloroform, dichloromethane, and tetrahydrofuran), and can be readily dried, purified, and re-dissolved. This method makes possible the utilization of a full range of existing nanoparticle cores in nonpolar solvents with a single ligand. It provides access to numerous nanomaterials that cannot be obtained through direct synthesis in nonpolar solvent, and is expected to be of significant value in a number of 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.044
Threshold uncertainty score1.000

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)0.0010.001

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 head0.025
GPT teacher head0.283
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

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

Citations52
Published2012
Admission routes1
Has abstractyes

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