Influence of Charge and Coordination Number on Bond Dissociation Energies, Distances, and Vibrational Frequencies for the Phosphorus–Phosphorus Bond
Bibliographic record
Abstract
We report a comprehensive and systematic experimental and computational assessment of the P-P bond in prototypical molecules that represent a rare series of known compounds. The data presented complement the existing solid-state structural data and previous computational studies to provide a thorough thermodynamic and electronic understanding of the P-P bond. Comparison of homolytic and heterolytic bond dissociation for tricoordinate-tricoordinate, tricoordinate-tetracoordinate, and tetracoordinate-tetracoordinate P-P bonds in frameworks 1-6 provides fundamental insights into covalent bonding. For all types of P-P bond discussed, homolytic dissociation is favored over heterolytic dissociation, although the distinction is small for 2(1+) and 6(1+). The presence of a single cationic charge in a molecule substantially strengthens the P-P bond (relative to analogous neutral frameworks) such that it is comparable with the C-C bond in alkanes. Nevertheless, P-P distances are remarkably independent of molecular charge or coordination number, and trends in values of d(PC) and νsymm(PC) imply that a molecular cationic charge is distributed over the alkyl substituents. In the gas phase, the diphosphonium dication 3(2+) has similar energy to two [PMe3](+) radical cations, so that it is the lattice enthalpy of 3[OTf]2 in the solid-state that enables isolation, highlighting that values from gas-phase calculations are poor guides for synthetic planning for ionic compounds. There are no relationships or correlations between bond lengths, strengths, and vibrational frequencies.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".