Block Copolymer Micelles as Nanoreactors for Self-Assembled Morphologies of Gold Nanoparticles
Bibliographic record
Abstract
Self-assembled gold (Au) nanoparticles (NPs) were synthesized in micelle surface cavities of a L121 block polymer in the presence of zwitterionic (viz. DPS, TPS, and HPS) and sugar surfactants (OG and DDM) in aqueous phase at 70 °C by using the surface cavities of L121 as reducing sites for converting Au(III) into Au(0). All reactions were monitored simultaneously by UV-visible spectroscopy to determine the growth kinetics in gold nucleating centers on the basis of surface plasmon resonance that also helped in tracing the structure micelle transitions over a wide temperature range of 10-70 °C. The surfactant/L121 mole ratio was changed systematically from 0.5 to 2.5 by keeping L121 and HAuCl4 concentrations constant at 10 and 0.25 mM, respectively, to determine the shape and size of the micelles and their relation to the self-assembled behavior of Au NPs. TEM studies were used to have a direct insight into the morphology of micelle templates and their shape and size for self-assembled NPs. L121 along with DPS (C12 carbon chain) produced well-defined micelles loaded with tiny NPs of 3-6 nm in the L121-rich region of the mixture, while large flower-like compound micelles with a clear core-shell morphology were produced in the DPS-rich region. TPS and HPS (C14 and C16 hydrocarbon chains, respectively) with stronger hydrophobicity than DPS also produced almost similar micelles loaded with tiny NPs in the L121-rich region, but they disappear in the surfactant-rich region. Replacement of zwitterionic with ionic surfactants did not yield micelle templates for self-assembled NPs. Results conclude that well-defined micelles of L121 are the fine templates for self-assembled NPs that can only be achieved in the presence of a neutral surfactant with low concentration and low hydrophobicity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".