<sup>13</sup>C and<sup>19</sup>F solid-state NMR and X-ray crystallographic study of halogen-bonded frameworks featuring nitrogen-containing heterocycles
Bibliographic record
Abstract
Halogen bonding is a noncovalent interaction between the electrophilic region of a halogen (σ-hole) and an electron donor. We report a crystallographic and structural analysis of halogen-bonded compounds by applying a combined X-ray diffraction (XRD) and solid-state nuclear magnetic resonance (SSNMR) approach. Single-crystal XRD was first used to characterize the halogen-bonded cocrystals formed between two fluorinated halogen-bond donors (1,4-diiodotetrafluorobenzene and 1,3,5-trifluoro-2,4,6-triiodobenzene) and several nitrogen-containing heterocycles (acridine, 1,10-phenanthroline, 2,3,5,6-tetramethylpyrazine, and hexamethylenetetramine). New structures are reported for the following three cocrystals, all in the P 2 1 / c space group: acridine–1,3,5-trifluoro-2,4,6-triiodobenzene (1/1), C 6 F 3 I 3 ·C 13 H 9 N, 1,10-phenanthroline–1,3,5-trifluoro-2,4,6-triiodobenzene (1/1), C 6 F 3 I 3 ·C 12 H 8 N 2 , and 2,3,5,6-tetramethylpyrazine–1,3,5-trifluoro-2,4,6-triiodobenzene (1/1), C 6 F 3 I 3 ·C 8 H 12 N 2 . 13 C and 19 F solid-state magic-angle spinning (MAS) NMR is shown to be a convenient method to characterize the structural features of the halogen-bond donor and acceptor, with chemical shifts attributable to cocrystal formation observed in the spectra of both nuclides. Cross polarization (CP) from 19 F to 13 C results in improved spectral sensitivity in characterizing the perfluorinated halogen-bond donor when compared to conventional 1 H CP. Gauge-including projector-augmented wave density functional theory (GIPAW DFT) calculations of magnetic shielding constants, along with optimization of the XRD structures, provide a final set of structures in best agreement with the experimental 13 C and 19 F chemical shifts. Data for carbons bonded to iodine remain outliers due to well-known relativistic effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".