Role of Au<sub>4</sub> Units on the Electronic and Bonding Properties of Au<sub>28</sub>(SR)<sub>20</sub> Nanoclusters from X-ray Spectroscopy
Bibliographic record
Abstract
The emergence of FCC-ordered core structures in thiolate-protected gold nanoclusters has motivated researchers in this area to reconsider the possibility of nonicosahedral core frameworks. With the recent elucidation of a four-membered FCC-ordered core series (Au 20 (SR) 16, Au 28 (SR) 20, Au 36 (SR) 24, and Au 44 (SR) 28 ), it is now of significant interest to understand how their electronic and bonding properties are influenced by the cluster composition and how they differ from, or may be linked to, their icosahedral counterparts. Of recent, attention has been focused on the presence of small Au 4 units, which comprise the majority of the known FCC-ordered thiolate-protected gold nanocluster core structures. Herein, the Au 28 (SR) 20 nanocluster with a 20 Au atom FCC-ordered core is investigated with temperature-dependent X-ray absorption spectroscopy experiments and ab initio simulations to elucidate the bonding and electronic properties of the second member of the FCC-ordered core series. By comparing the results of Au 28 (SR) 20 with its larger FCC-ordered relative, Au 36 (SR) 24, and its icosahedral counterpart, Au 25 (SR) 18, the significant role of Au 4 core units on the bonding properties of FCC-ordered gold nanoclusters is highlighted in this work.
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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".