Interactions between Ultrastable Na <sub>4</sub> Ag <sub>44</sub> (SR) <sub>30</sub> Nanoclusters and Coordinating Solvents: Uncovering the Atomic-Scale Mechanism
Why this work is in the frame
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Bibliographic record
Abstract
Recently, silver nanoclusters have garnered considerable attention after the high-yield synthesis and crystallization of a thiolate-protected silver nanocluster, Na4Ag44(SR)30 (SR, protecting thiolate ligand). One intriguing feature of Na4Ag44(SR)30 is its outstanding stability and resistance to chemical reactions, in striking difference from other silver nanostructures whose susceptibility to oxidation (tarnishing) has been commonly observed and thus limits their applications in nanotechnology. Herein, we report the mechanism on the ultrahigh stability of Na4Ag44(SR)30 by uncovering how coordinating solvents interact with the Na4Ag44(SR)30 nanocluster at the atomic scale. Through synchrotron X-ray experiments and theoretical calculations, it was found that strongly coordinating aprotic solvents interact with surface Ag atoms, particularly between ligand bundles, which compresses the Ag core and relaxes surface metal–ligand interactions. Furthermore, water was used as a cosolvent to demonstrate that semiaqueous conditions play an important role in protecting exposed surface regions and can further influence the local structure of the silver nanocluster itself. Notably, under semiaqueous conditions, aprotic coordinating solvent molecules preferentially remain on the metal surface while water molecules interact with ligands, and ligand bundling persisted across the varied solvation conditions. This work offers an atomic level mechanism on the ultrahigh stability of the Na4Ag44(SR)30 nanoclusters from the nanocluster-coordinating solvent interaction perspective, and implies that nanocluster-solvent interactions should be carefully considered moving forward for silver nanoclusters, as they can influence the electronic/chemical properties of the nanocluster as well as the surface accessibility of small molecules for potential catalytic and biomedical applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it