Solid‐State Nuclear Magnetic Resonance: Spin‐1/2 Nuclei Other than Carbon and Proton
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Solid‐state nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique with a wide range of applications in chemistry, biochemistry and materials science. Solid‐state NMR is amenable to studies of molecular systems that are not suitable either for liquid‐state NMR because of insolubility or for single‐crystal diffraction techniques because of poor crystallinity. Therefore, solid‐state NMR provides a natural connection between liquid‐state NMR and single‐crystal diffraction techniques. Furthermore, solid‐state NMR is the best way of studying the anisotropic nature of nuclear magnetic properties, thus potentially yielding more complete information about molecular structure and chemical bonding. This article provides an overview of the fundamental principles of solid‐state NMR with selected examples of chemical applications. Emphasis is placed on the fundamental information and practical aspects of solid‐state multinuclear NMR experiments for the following spin‐ $\def\tovr#1#2{{\scriptstyle{#1\over #2}}} \tovr{1}{2}$ nuclei: 15 N, 29 Si, 31 P, 77 Se, 113 Cd, 199 Hg, 117 Sn, 195 Pt, 207 Pb, 57 Fe, 89 Y, 109 Ag and 183 W. A brief introduction to the second‐order quadrupolar effect on spin‐ $\def\tovr#1#2{{\scriptstyle{#1\over #2}}} \tovr{1}{2}$ NMR spectra is also provided.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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 it