Monomeric and Polymeric Mesoionic <i>N</i>-Heterocyclic Carbene-Tethered Silver Nanoparticles: Synthesis, Stability, and Catalytic Activity
Bibliographic record
Abstract
In recent years, N -heterocyclic carbenes (NHCs) have garnered significant attention as promising alternatives to thiols to stabilize metallic nanoparticles and planar surfaces. While most studies thus far have focused on NHC-functionalized gold nanoparticles (AuNPs), as an ideal platform to investigate the role of NHCs in stabilizing such nanoparticles, their ability to protect more unstable coinage metal nanoparticles, such as silver nanoparticles (AgNPs), has been largely overlooked. This is despite the fact that AgNPs possess a much more sensitive optical response that, upon their enhanced stability, can broaden their scope of application in various fields, including nanomedicine and catalysis. In this study, the synthesis and use of monomeric and polymeric mesoionic NHC–Ag(I) complexes as precursors to mono- and multidentate NHC-tethered AgNPs are reported. The polymeric analog was obtained by first synthesizing a polymer, containing 1,2,3-triazole repeat units, employing the copper-catalyzed alkyne–azide cycloaddition click polymerization of monomers containing diazide- and dialkyne functional groups. Subsequent quaternization of the triazole moieties and Ag insertion yielded the target NHC–Ag-containing polymer. Using this polymer as well as its monomeric analog as substrates, AgNPs with either catenated networks of NHCs or monomeric NHCs were fabricated by their reduction using borane– tert -butylamine complex. Our stability studies demonstrate that while monomeric NHCs impart some degree of stability to AgNPs, particularly at elevated temperatures in aqueous as well as organic medium, their polymeric analogs further enhance their stability in acidic environment (pH = 2) and against glutathione (3 mM), as an example of a biologically relevant thiol, in aqueous media. To highlight the application of these NHC-functionalized AgNPs in catalysis, we explore the aqueous phase reduction of methyl orange and 4-nitrophenol.
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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".