Why Are Some Pnictogen(III) Pincer Complexes Planar and Others Pyramidal?
Bibliographic record
Abstract
Geometrically-constrained pnictogen pincer complexes have emerged in recent years as platforms for unique stoichiometric and catalytic chemical transformations. These complexes feature dynamic conformations ranging from fully planar at the pnictogen centre to distorted-pyramidal geometries, as well as variation between phases. Although the valued reactivity of pnictogen pincer complexes is ascribed to their geometries, there is no unified model to explain the observed conformational outcomes across different ligands and pnictogen centres. Here we propose such a model through computational analysis of more than 1300 structures across 64 complexes (16 ligands and 4 heavy pnictogens), explaining the experimental observations and making new predictions. By looking at signatures of bond stability (bond lengths, Wiberg bond indices) and delocalization (NPA charges, Hirshfeld charges), our framework posits a pnictogen-based σ-bonding effect that favours pyramidalization and exists in competition with a ligand-based π-bonding effect that favours planarity. Variations in structure as a function of pnictogen identity, ligand tethering, electronics, and aromaticity can be reconciled with reference to a balance between these two opposing forces. Careful consideration of the σ/π-bonding effects may aid in the rational design of future pnictogen pincer complexes with predictable geometries and reactivities.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".