Quadrupole-Central-Transition <sup>23</sup>Na, <sup>39</sup>K, <sup>87</sup>Rb NMR Studies of Alkali Metal Ions under Different Molecular Tumbling Conditions: A Simple Model to Treat Chemical Exchange Involving Quadrupolar Nuclei
Bibliographic record
Abstract
We report a new NMR method for treating two-site chemical exchange involving half-integer quadrupolar nuclei in a solution. The new method was experimentally verified with extensive 23 Na ( I = 3/2), 39 K ( I = 3/2), and 87 Rb ( I = 3/2) NMR results from alkali metal ions (Na +, K +, and Rb + ) in a solution over a wide range of molecular tumbling conditions. In the fast-motion limit, all allowed single-quantum NMR transitions for a particular quadrupolar nucleus are degenerate giving rise to one Lorentzian signal. In the slow-motion regime, although the NMR signal from quadrupolar nuclei should in principle exhibit a multi-Lorentzian line shape, only the quadrupole central transition (QCT) is often detectable in practice. In all the cases studied in this work, we found that alkali metal ions undergo fast exchange between free and bound states. Using the new theoretical method, we were able to interpret the experimental transverse relaxation data (i.e., line widths) obtained for 23 Na, 39 K, and 87 Rb NMR signals including QCT signals over a large temperature range and extract information about ion-binding dynamics in different chemical environments. This work fills a gap in the literature where a unified approach for treating NMR transverse relaxation data for quadrupolar nuclei over the entire range of motion has been lacking. Our results suggest that the new approach is applicable in the study of alkali metal ion binding to biological macromolecules.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".