Bonding properties of thiolate-protected gold nanoclusters and structural analogs from X-ray absorption spectroscopy
Bibliographic record
Abstract
Abstract Subnanometer, atomically precise thiolate-protected gold nanoclusters represent an important advancement in our understanding of thiolate-protected gold nanoparticles and thiolate-gold chemistry. Aside from being a link between larger gold nanoparticles and small gold complexes, gold nanoclusters exhibit extraordinary molecule-like optical, electronic, and physicochemical properties that are promising for next-generation imaging agents, sensing devices, or catalysts. The success in elucidating a number of unique thiolate-gold surface and gold core structures has greatly improved our understanding of thiolate-gold nanoclusters. Nevertheless, monitoring the structural and electronic behavior of thiolate-protected gold nanoclusters in a variety of media or environments is crucial for the next step in advancing this class of nanomaterials. Not to mention, there are a number of thiolate-protected gold nanoclusters with unknown structures or compositions that could reveal important insights on application-based properties such as luminescence or catalytic activity. This review summarizes some of the recent contributions from X-ray absorption spectroscopy (XAS) studies on the intriguing bonding properties of thiolate-protected gold nanoclusters and some structural analogs. Advantages from XAS include a local structural, site- and element-specific analysis, suitable for ultra-small particle sizes (1–2 nm), along with versatile experimental 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) | 0.000 | 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".