Substituent Effects on the [N–I–N]<sup>+</sup> Halogen Bond
Bibliographic record
Abstract
We have investigated the influence of electron density on the three-center [N-I-N](+) halogen bond. A series of [bis(pyridine)iodine](+) and [1,2-bis((pyridine-2-ylethynyl)benzene)iodine](+) BF4(-) complexes substituted with electron withdrawing and donating functionalities in the para-position of their pyridine nitrogen were synthesized and studied by spectroscopic and computational methods. The systematic change of electron density of the pyridine nitrogens upon alteration of the para-substituent (NO2, CF3, H, F, Me, OMe, NMe2) was confirmed by (15)N NMR and by computation of the natural atomic population and the π electron population of the nitrogen atoms. Formation of the [N-I-N](+) halogen bond resulted in >100 ppm (15)N NMR coordination shifts. Substituent effects on the (15)N NMR chemical shift are governed by the π population rather than the total electron population at the nitrogens. Isotopic perturbation of equilibrium NMR studies along with computation on the DFT level indicate that all studied systems possess static, symmetric [N-I-N](+) halogen bonds, independent of their electron density. This was further confirmed by single crystal X-ray diffraction data of 4-substituted [bis(pyridine)iodine](+) complexes. An increased electron density of the halogen bond acceptor stabilizes the [N···I···N](+) bond, whereas electron deficiency reduces the stability of the complexes, as demonstrated by UV-kinetics and computation. In contrast, the N-I bond length is virtually unaffected by changes of the electron density. The understanding of electronic effects on the [N-X-N](+) halogen bond is expected to provide a useful handle for the modulation of the reactivity of [bis(pyridine)halogen](+)-type synthetic reagents.
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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 | 0.001 | 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".