How PEO-PPO-PEO Triblock Polymer Micelles Control the Synthesis of Gold Nanoparticles: Temperature and Hydrophobic Effects
Bibliographic record
Abstract
Aqueous micellar solutions of F68 (PEO(78)-PPO(30)-PEO(78)) and P103 (PEO(17)-PPO(60)-PEO(17)) triblock polymers were used to synthesize gold (Au) nanoparticles (NPs) at different temperatures. All reactions were monitored with respect to reaction time and temperature by using UV-visible studies to understand the growth kinetics of NPs and the influence of different micellar states on the synthesis of NPs. The shape, size, and locations of NPs in the micellar assemblies were determined with the help of TEM, SEM, and EDS analyses. The results explained that all reactions were carried out with the PEO-PPO-PEO micellar surface cavities present at the micelle-solution interface and were precisely controlled by the micellar assemblies. Marked differences were detected when predominantly hydrophilic F68 and hydrophobic P103 micelles were employed to conduct the reactions. The UV-visible results demonstrated that the reduction of gold ions into nucleating centers was channeled through the ligand-metal charge-transfer complex (LMCT) and carried out by the surface cavities. Excessive hydration of the surface cavities in the case of F68 micelles produced a few small NPs, but their yield and size increased as the micelles were dehydrated under the effect of increasing temperature. The results concluded that the presence of well-defined predominantly hydrophobic micelles with a compact micelle-solution interfacial arrangement of surface cavities ultimately controlled the reaction.
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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 | 0.000 |
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.
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".