The Importance of Ligand‐Induced Backdonation in the Stabilization of Square Planar d <sup>10</sup> Nickel π‐Complexes
Bibliographic record
Abstract
Abstract The electronic nature of Ni π‐complexes is underexplored even though these complexes have been widely postulated as intermediates in organometallic chemistry. Herein, the geometric and electronic structure of a series of nickel π‐complexes, Ni(dtbpe)(X) (dtbpe=1,2‐bis(di‐ tert ‐butyl)phosphinoethane; X=alkene or carbonyl containing π‐ligands), is probed using a combination of 31 P NMR, Ni K‐edge XAS, Ni K β XES, and DFT calculations. These complexes are best described as square planar d 10 complexes with π‐backbonding acting as the dominant contributor to M−L bonding to the π‐ligand. The degree of backbonding correlates with 2 J PP from NMR and the energy of the Ni 1s→4p z pre‐edge in the Ni K‐edge XAS data, and is determined by the energy of the π* ip ligand acceptor orbital. Thus, unactivated olefinic ligands tend to be poor π‐acids whereas ketones, aldehydes, and esters allow for greater backbonding. However, backbonding is still significant even in cases in which metal contributions are minor. In such cases, backbonding is dominated by charge donation from the diphosphine, which allows for strong backdonation, although the metal centre retains a formal d 10 electronic configuration. This ligand‐induced backbonding can be formally described as a 3‐centre‐4‐electron (3c‐4e) interaction, in which the nickel centre mediates charge transfer from the phosphine σ‐donors to the π* ip ligand acceptor orbital. The implications of this bonding motif are described with respect to both structure and reactivity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".