Application of Multiple-Pulse Experiments to Characterize Broad NMR Chemical-Shift Powder Patterns from Spin-<sup>1</sup>/<sub>2</sub>Nuclei in the Solid State
Bibliographic record
Abstract
The utility of the Carr-Purcell Meiboom-Gill (CPMG) experiment and a modified-CPMG experiment in characterizing NMR chemical-shift powder patterns for spin- 1 / 2 nuclei is demonstrated. Heavier NMR-active nuclei such as 195 Pt, 199 Hg, and 207 Pb are known to be extremely sensitive to their local environment and as such have very large chemical-shift ranges. In the solid state, such nuclei commonly exhibit chemical shifts that range well over 1000 ppm, depending upon the orientation of the molecule within the applied magnetic field. Thus, acquiring NMR spectra of polycrystalline samples is often an experimental challenge because of these very broad powder patterns. In acquiring chemical-shift powder patterns of these nuclei, we provide several examples that demonstrate that a considerable saving in time is realized by using the CPMG experiment as opposed to the standard one-pulse or spin-echo experiment. In general, this time saving is even greater if a modified-CPMG experiment is used. Homonuclear dipolar interactions are considerably reduced in the CPMG experiment and are almost completely removed in the modified-CPMG experiment. For samples containing 1 H, larger enhancements are realized by combining the CPMG experiment with cross polarization. By use of the CPMG and the modified-CPMG experiments, the principal components of the chemical-shift tensors are determined for each of the samples studied.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".