Probing <i>f</i> -Block Covalency at the Limits of Hard-Metal/Soft-Ligand Interactions through Chalcogenoether Complexes
Bibliographic record
Abstract
We report a systematic probe of covalency at the boundaries of f -block hard-metal/soft-ligand interactions by employing monoanionic ligands containing formally neutral chalcogen donors to facilitate isostructural comparisons of early to middle trivalent actinides (An = U, Np, Pu, Am) and their near isoradial lanthanide counterparts (Ln = La, Ce, Pr, Nd). The single-crystal structural data on [(AE 2 Ph2 ) 2 M III I] ( 1-M, E = S, M = La, Ce, Pr, Nd, U, Np, Pu, Am; 2-M, E = Se, M = La, Ce, Pr, Nd, Np, Pu, Am; AE 2 Ph2 = 4,5-bis(phenylchalcogenido)-2,7,9,9-tetramethylacridanide) provides metrical definition of the first transuranium actinide selenoether bonds to Np, Pu, and Am as well as the first Pr and Nd selenoether complexes. Additionally, rare examples of transuranium thioether and lanthanum/cerium-selenoether complexes are reported. The shorter metal–chalcogen bonds in the actinide complexes compared to lanthanide congeners suggest stronger covalent interactions, though it becomes less pronounced as the f -block series is traversed to the Am vs Nd comparison. Computational analyses support these findings, showing increased metal–ligand participation in the U, Np, and Pu complexes and further participation of valence shell orbitals when moving from S to Se as the chalcogenoether donor atom.
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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".