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Record W2650825582 · doi:10.18311/jsst/2008/1896

Synthesis of Gold Nanoparticles Supported by Aggregated Assemblies of Triblock Copolymers in Aqueous Phase : Effect of Temperature

2008· article· en· W2650825582 on OpenAlexaff
Poonam Bhandari, Poonam Sharma, Gurinder Kaur, Mandeep Singh Bakshi, Tarlok S. Banipal

Bibliographic record

VenueJournal of Surface Science and Technology · 2008
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsCollege of the North Atlantic
Fundersnot available
KeywordsNucleationCopolymerPolymerMaterials scienceAqueous solutionNanoparticleChemical engineeringPolymer chemistryPhase (matter)Colloidal goldOxideNanotechnologyChemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The effect of temperature on the self-assembled behavior of polymers P103 and P84, and their subsequent use as soft templates for the synthesis of gold (Au) nanoparticles (NP) have been studied with the help of SEM, TEM, and UV-vis spectral measurements. Both the triblock copolymers (TBP) exist in the form of liquid crystalline thread like assemblies. P103 being more hydrophobic shows a structural transition from liquid crystal (LC) threads to sheets at 50°C and bear uniformly distributed Au NP, the size of which increases with the increase in temperature. P84 being more hydrophilic shows only LC threads and no sheets, but the LC threads bearing running groove at 50°C, act as wonderful nucleation sites for the growth of large cubic Au NP. The presence of surface cavities constituted by polyethylene oxide (PEO) and polypropylene oxide (PPO) blocks on LC phase of both TBPs are considered to be the nucleation sites for Au NP. The greater hydrophobicity of P103 in comparison to P84 favors the uniform distribution of NP throughout the LC phase while an increase in the temperature facilitates this process.

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)0.001
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 score0.008
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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