High sensitivity and resolution in <sup>43</sup>Ca solid-state NMR experiments
Bibliographic record
Abstract
A thorough investigation of solid-state NMR signal enhancement schemes and high-resolution techniques for application to the spin-7/2 43Ca nuclide are presented. Signal enhancement experiments employing double frequency sweeps, hyperbolic secant pulses, and rotor-assisted population transfer, which manipulate the satellite transitions of half-integer quadrupolar nuclei to polarize the central transition (m = + 1/2 ↔ –1/2), are carried out on four well-characterized 43Ca isotopically enriched calcium salts: Ca(NO3)2, Ca(OD)2, CaSO4·2H2O, and Ca(OAc)2·H2O. These results, in conjunction with numerical simulations of 43Ca NMR spectra under magic-angle spinning conditions, are used to identify the technique that provides the most uniform (or quantitative) polarization enhancement as well as the largest signal enhancement factors independent of size of the 43Ca quadrupolar coupling constant, which is the most significant source of resonance broadening in 43Ca NMR spectra. These samples are further investigated using 43Ca double-rotation NMR spectroscopy to yield isotropic, or solution-like, NMR spectra with exquisite resolution. In addition, three unique calcium sites are resolved for the hemihydrated form of calcium acetate (unknown structure), Ca(OAc)2·0.5H2O, with double-rotation NMR, whereas the more common, but more time-consuming, multiple quantum magic-angle spinning technique only clearly resolves two calcium sites. The results shown herein will be useful for other NMR spectroscopists attempting to acquire 43Ca solid-state NMR data for unknown and more complex materials with a higher degree of both sensitivity and resolution.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".