Terpyridine-Decorated Polymer Nanosphere Latex: Template Nanocarriers for the Synthesis of Cu–CeO<sub>2</sub> Hollow Spheres
Bibliographic record
Abstract
Water-soluble polymers with the ability to complex metal ions through complexing ligands have attracted significant interest in diverse domains, such as optical or catalyst applications. In this paper, we successfully synthesized, through a one-pot process combining polymerization-induced self-assembly and reversible addition-fragmentation chain transfer polymerization, aqueous dispersions of terpyridine-decorated poly[poly(ethylene glycol)methyl ether methacrylate]- b -poly(methyl methacrylate) (tpy-PPEGMA- b -PMMA) amphiphilic block copolymers. The in-situ formation of well-defined amphiphilic block copolymers and their self-assembly led to nanosphere latex with the hydrodynamic diameters increasing from 17 to 52 nm and the length of the copolymers increasing from 21,000 to 51,000 g·mol –1 . These aqueous dispersed tpy-PPEGMA- b -PMMA nanospheres effectively complex metal ions, such as Cu 2+, in a stoichiometric ratio of 2:1. Subsequently, these metal-complexed nanospheres were employed as soft template nanocarriers to control, on the nanometer scale, the dispersion of metal on a nanostructured support. This is exemplified by the synthesis of copper supported on cerium oxide hollow spheres (Cu–CeO 2 ) using Cu 2+ -tpy-PPEGMA- b -PMMA as template nanocarriers and CeO 2 nanoparticles. This novel assembly engineering strategy for the preparation of atomically dispersed metal on a nanostructured support was highlighted through the utilization of Cu–CeO 2 hollow spheres as an electrocatalyst for the nitrate reduction reaction (NO 3 RR) to NH 3 . These encouraging outcomes emphasize the potential of metal–metal oxide-nanostructured materials to treat contaminated water sources with nitrate while allowing the green production of ammonia.
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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".