Influence of Alkali Metal Cations in the Formation of the Heterobimetallic Actinide tert-Butoxides [AnM3(OtBu)7] and [AnM2(OtBu)6] (AnIV = Th, U; MI = Li, Na, K, Rb, Cs)
Bibliographic record
Abstract
These are the raw data for the modulated structure pertaining to compound URb. The following is the abstract of the corresponding paper. Heterobimetallic tert-butoxides of alkali metal cations and tetravalent actinide centers exhibit two distinctive structural motifs, [AnM2(OtBu)6] and [AnM3(OtBu)7] (AnIV = Th, U and MI = Li, Na, K, Rb, Cs), evidently govern by the size of the alkali metal ions. Both [AnM3(OtBu)7] AnM3 (AnIV = U, MI = Li; AnIV = Th, MI = Li, Na) and [AnM2(OtBu)6] AnM2 (AnIV = U, MI = Na – Cs; AnIV = Th, MI = K - Cs) compounds are obtained in nearly quantitative yields by reacting the actinide and alkali metal silyl amides with excess of tert-butyl alcohol. The AnM3 complexes form a cubane-type coordination motif, whereas the AnM2 complexes display a geometry resembling two face-shared bipyramids. The sodium derivatives of thorium and uranium (ThNa3 and UNa2) allow to determine the structural transition threshold as function of the ratio of the ionic radii, ri(AnIV)/ri(MI). The AnM3 complexes are formed for ratios above 0.92 and the AnM2 type is formed for ratios below 0.87. All compounds are unambiguously characterized in both solution and the solid-state via NMR and IR spectroscopic studies and single crystal X-ray diffraction analyses, respectively.
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 | 0.000 |
| 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".