A Solid-State NMR and Computational Study of Sodium and Potassium Tetraphenylborates: <sup>23</sup>Na and <sup>39</sup>K NMR Signatures for Systems Containing Cation−π Interactions
Bibliographic record
Abstract
Sodium and potassium tetraphenylborates were examined by solid-state 23 Na and 39 K NMR spectroscopy. Analyses of solid-state NMR spectra obtained at 4.70, 11.75, and 19.60 T yielded the following 23 Na and 39 K NMR parameters: Na[BPh 4 ], | C Q | = 1.24 ± 0.05 MHz, η Q = 0.0 ± 0.1, δ iso = −45.6 ± 0.5 ppm, and Ω = 14 ± 2 ppm; K[BPh 4 ], | C Q | = 1.32 ± 0.05 MHz, η Q = 0.0 ± 0.1, and δ iso = −92 ± 1 ppm. In both Na[BPh 4 ] and K[BPh 4 ], the electric field gradient and chemical shift tensors at the metal site are axially symmetric, in agreement with the crystallographic symmetry. Extensive quantum mechanical calculations were performed for Na[BPh 4 ] and K[BPh 4 ] as well as for a large number of model cation−π systems containing Na + and K + ions and common aromatic compounds. Experimental and theoretical studies confirm that a highly shielded environment at the metal cation site is a characteristic feature for cation−π interactions, making it useful as a NMR signature for identifying cation−π interactions in proteins and nucleic acids. In this study, powder X-ray diffraction spectra for Na[BPh 4 ] and K[BPh 4 ] were also reported.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".