Bibliographic record
Abstract
Density functional calculations have been performed to investigate some features of the phase diagrams of alloys of Pb with the alkali metals. Alkali-rich intermetallic compounds occur for Pb with Li and Na, but not with heavier alkalis. But, although for the Li-Pb and Na-Pb systems compounds form near the octet stoichiometry there are no exact 4:1 stoichiometric compounds. Calculations for free clusters already provide some qualitative insight into these questions. In addition we have performed simulations of the assembling of solid compounds using free clusters as building blocks. There is substantial rearrangement during the assembling process as the clusters coalesce to form the solid, but the trends in the A-Pb alloys as A varies down the alkali group seem to be closely related to such characteristic properties of the clusters as the highest occupied molecular orbital and lowest unoccupied molecular orbital gap, and alkali atomic size effects. The striking absence of octet stoichiometric compounds in the Li-Pb and Na-Pb systems is accounted for as a result of competition between compounds with slightly different compositions. The enhanced stability of the nonstoichiometric compounds can be understood in terms of preferential filling of bonding orbitals leading to enhanced ionic binding.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".