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Record W2333888486 · doi:10.1166/jnn.2007.200

Lamellar Phase Supported Synthesis of Colloidal Gold Nanoparticles, Nanoclusters, and Nanowires

2007· article· en· W2333888486 on OpenAlexaff
Mandeep Singh Bakshi, Poonam Sharma, Tarlok S. Banipal, Gurinder Kaur, Kanjiro Torigoe, Nils O. Petersen, Fred Possmayer

Bibliographic record

VenueJournal of Nanoscience and Nanotechnology · 2007
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsNanoclustersLamellar structureMaterials scienceNucleationLamellar phaseNanowirePulmonary surfactantCationic polymerizationPhase (matter)NanoparticleChemical engineeringColloidal goldColloidNanostructureAqueous solutionNanotechnologyCrystallographyPolymer chemistryOrganic chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

Gold nanoparticles (Au NP) have been synthesized in aqueous phase under ambient conditions in the presence of a series of various cationic double chain as well as dimeric (gemini) surfactants. The spacer chain and twin tail length of these surfactants has been systematically varied to see the effect of hydrophobicity on their capping ability. It has been observed that the increase in the length of spacer chain (from 12-2-12 to 12-6-12) and twin tails (from 10-2-10 to 14-2-14) significantly increases the lamellar phase formation and which in return acts as a wonderful template to accommodate the NP in the form of nanoclusters and nanowires. The lamellar phase practically facilitates the nucleation of Au degrees and produces large NP (15 +/- 2 nm). All reactions have also been carried out in the presence of beta-cyclodextrin (CYC) which has strong ability to complex with surfactant tail. The presence of CYC induces a tendency to form nanowire and it is more prominent in the case of surfactants with longer spacer group.

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)0.002
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 score0.025
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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

Citations19
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nanoscience and NanotechnologySame topicGold and Silver Nanoparticles Synthesis and ApplicationsFrench-language works237,207