Polyelectrolyte Multilayer Films as Templates for the In Situ Photochemical Synthesis of Silver Nanoparticles
Bibliographic record
Abstract
Multilayer films formed by the sequential adsorption of polyelectrolytes (PEs) from aqueous solution were used as templates for the in situ growth of silver nanoparticles. When films consisting of poly(acrylic acid) (PAA) and poly(allylamine hydrochloride) (PAH) or PAA and poly(ethyleneimine) (PEI) are immersed in AgNO 3 solution, functional groups within the film bind silver cations from solution. Bound Ag ions were photochemically reduced to metal nanoparticles upon exposure to UV radiation. The number of available binding groups and binding capacity of multilayer films were shown to be strongly dependent on multilayer processing conditions, including chemical structure of PEs, multilayer assembly pH, as well as the AgNO 3 solution concentration and time interval used for Ag + binding. These parameters were studied using a combinatorial approach to multilayer analysis, which provides a means to investigate in parallel the variables that affect particle synthesis. By using UV−vis spectroscopy and scanning transmission electron microscopy (STEM), the optimal conditions were determined to generate composite films containing small (3−5 nm) isolated spherical nanoparticles that are distributed randomly throughout the PE matrix. A striking discovery was the sensitivity of Ag + binding to the structure of deposited PEs. Films consisting of branched PEI and PAA assembled at specific pH values have displayed a remarkably high affinity for metal cations relative to PAH/PAA films assembled at the same conditions.
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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) | 0.001 | 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 | 0.001 |
| 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".