Self-assembly of nanoparticles onto the surfaces of polystyrene spheres with a tunable composition and loading
Bibliographic record
Abstract
Functional colloidal materials were prepared by design through the self-assembly of nanoparticles (NPs) on the surfaces of polystyrene (PS) spheres with control over NP surface coverage, NP-to-NP spacing, and NP composition. The ability to control and fine tune the coating was extended to the first demonstration of the co-assembly of NPs of dissimilar composition onto the same PS sphere, forming a multi-component coating. A broad range of NP decorated PS (PS@NPs) spheres were prepared with uniform coatings attributed to electrostatic and hydrogen bonding interactions between stabilizing groups on the NPs and the functionalized surfaces of the PS spheres. This versatile two-step method provides more fine control than methods previously demonstrated in the literature. These decorated PS spheres are of interest for a number of applications, such as catalytic reactions where the PS spheres provide a support for the dispersion, stabilization, and recovery of NP catalysts. The catalytic properties of these PS@NPs spheres were assessed by studying the catalytic degradation of azo dyes, an environmental contaminant detrimental to eye health. The PS@NPs spheres were used in multiple, sequential catalytic reactions while largely retaining the NP coating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".