Investigation into synthesis and the microstructure of silver nanoparticles coated with alkanethiols and thiol-functionalized polymers
Bibliographic record
Abstract
A comprehensive investigation into the synthesis and the characterization of discrete silver nanoparticles coated with alkanethiols and thiolate functionalized polymers is presented. Small and uniform alkanethiol capped silver nanoparticles were synthesized via the Brust and Schiffrin method. To improve the characteristics of the resulting nanoparticles, the intermediate stage of this reaction was investigated. The major precursor to the silver nanoparticles was identified and its microstructure was characterized. \nPolymers bearing single or multiple thiolates were prepared by synthesis of well-defined precursors via RAFT polymerization and their subsequent post-polymerization modification. Nanoparticles stabilized with thiol-terminated PMMA were produced via a “grafting-to” process. A novel method was developed for the synthesis of small, uniform, and re-dispersible nanoparticles encapsulated with multiple-thiolate functional random copolymers of vinylbenzyl chloride. The effect of reaction conditions on the quality of these nanoparticles were evaluated. Adsorption of the copolymers on the nanoparticles were studied by 1H NMR relaxation measurements.
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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) | 0.000 | 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".