Redox-Active Micelle-Based Reaction Platforms for <i>In Situ</i> Preparation of Noble Metal Nanocomposites with Photothermal Conversion Capability
Bibliographic record
Abstract
Polyferrocenylsilane (PFS)-based polymers are an attractive family of organometallic polymers with unique redox-active properties. Herein, we report a novel amphiphilic redox-active PFS-based homopolymer, poly(ferrocenylmethylethylthiocarboxypropylsilane) (PFC), with a hydrophobic backbone chain and hydrophilic carboxylic acid side groups in each repeating unit. Self-assembly was induced by addition of water to a molecularly dispersed solution of PFC in DMSO. Spherical PFC micelles with controllable hydrodynamic diameters (60–180 nm) were obtained under various conditions. These PFC micelles could be readily endocytosed by A549 cells and HUVEC cells and show no significant cytotoxicity toward them at the concentration of 200 μg/mL. On this basis, Au nanoparticles (AuNPs) were prepared through in situ reduction of HAuCl 4 by PFC micelles as nanoreactors without requiring any other reductants. The PFC/Au nanocomposites (NCs) were found to exhibit significant photothermal behavior. Moreover, PFC micelles could also act as nanoreactors for other noble metals such as Ag, Pd, and Pt. By taking advantage of properties of the nanostructures and noble metal nanoparticles comprising these materials, the PFC micelles and PFC/noble metal NCs may have great potential in biomedical or catalytic applications.
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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".