Bibliographic record
Abstract
Bimetallic anionic and neutral clusters, consisting of group III elements (Aln−1B1, Aln−2B2, Aln−1In1, and Inn−1Al1, n=11–14), have been theoretically investigated by density functional theory at the B3LYP/6-31G* (LanL2DZ for the In element) level. The calculated optimized equilibrium geometries and total energies of neutral and anionic clusters give a satisfactory interpretation of magic number clusters observed in time of flight mass spectra (TOF-MS). Our results show that Al11B2− is the most stable among Aln−2B2− (n=11–14) cluster anions and keeps an icosahedronlike structure, contrary to what had been suggested previously. Whether a magic number turns out in TOF-MS likely depends more on the stability of the neutral clusters than on the stability of the anions. The Al11B2 neutral cluster is less stable than Al12B2, and this is why Al11B2− does not appear as a magic number in TOF-MS. In addition, we found that icosahedral structures do not always hold for the magic cluster anions considered in the present study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".