Sensitivity of Structural and Electronic Properties of Gold–Thiolate Nanoclusters to the Atomic Composition: A Comparative X-ray Study of Au<sub>19</sub>(SR)<sub>13</sub> and Au<sub>25</sub>(SR)<sub>18</sub>
Bibliographic record
Abstract
With the recent successful synthesis of an increasing number of atomically precise thiolate–gold nanoclusters (NCs), there are growing demands for a better understanding of their atomic structures and structure–property relationships in response to composition change. Herein, we present X-ray experimental results on structural and electronic properties of a recently synthesized gold–thiolate nanocluster, Au 19 (SR) 13, in comparison with the structurally well-known Au 25 (SR) 18 reference. The atomic structure of Au 19 (SR) 13 was first probed with extended X-ray absorption fine structure (EXAFS). A multishell EXAFS fitting method (consisting of one Au–S and three Au–Au shells) allowed for a detailed structural comparison of the two nanoclusters, which revealed a sizable increase of the bond distances between the surface–surface and surface–staple Au atoms upon the decrease of Au atoms in the nanocluster. X-ray photoemission experiments and ab initio calculations further demonstrated the sensitive change of electronic properties of the nanoclusters when the cluster composition was varied, that is, the Au 19 (SR) 13 nanocluster has a differently shaped and positively shifted Au 5d band relative to Au 25 (SR) 18 . These experimental findings highlight the sensitivity of the local structure and electronic properties of thiolate-gold nanoclusters to even a small change of the metal core from Au 13 to Au 11 .
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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".