Competition between mixing and segregation in bimetallic Ag<sub><i>n</i></sub>Rb<sub><i>n</i></sub> clusters (<i>n</i> = 2–10)<sup>,</sup>
Bibliographic record
Abstract
We found the minimum-energy structures of AgnRbn (n = 2–10) clusters by a combination of density functional theory (DFT) and taboo search global optimization. The global minimum geometry is mixed for n ≤ 4 and segregated, with a core-shell arrangement, for n > 4. There is a change in the nature of the bonding, from ionic to metallic, between n = 4 and n = 5. Although metallic bonding dominates at n > 4, large atomic charges (in the order of ±0.5) persist. These atomic charges (negative on the interior Ag atoms, positive on the surface Rb atoms) make AgnRbn clusters analogous to Zintl compounds and could prevent them from coalescing. This makes them intriguing potential building blocks for cluster-assembled materials. Ag4Rb4 is relatively stable compared with other AgnRbn clusters; it has a nearly cubic shape, a large HOMO–LUMO gap (2 eV), and a highly ionic character with atomic charges equal to roughly ±1 au.
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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) | 0.002 | 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".