Lead‐207 NMR spectroscopy at 1.4 T: Application of benchtop instrumentation to a challenging <i>I</i> = ½ nucleus
Bibliographic record
Abstract
Abstract The practicality of obtaining liquid‐ and solid‐state 207Pb nuclear magnetic resonance (NMR) spectra with a low permanent‐field magnet is investigated. Obtaining 207Pb NMR spectra of salts in solution is shown to be viable for samples as dilute as 0.05 M. The concentration dependence of the 207Pb chemical shifts for lead nitrate was investigated; the results are comparable with those obtained with high‐field instruments. Likewise, the isotope effect of substituting D2O for H2O as the solvent was investigated and found to be comparable with those reported previously. Obtaining solid‐state 207Pb NMR spectra is challenging, but we demonstrate the ability to obtain such spectra for three unique solid samples. An axially symmetric 207Pb powder pattern for lead nitrate and the powder pattern expected for lead chloride reveal linewidths dominated by shielding anisotropy, while 207Pb‐35/37Cl J‐coupling dominates in the methylammonium lead chloride perovskite material. Finally, recent innovations and the future potential of the instruments are considered.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".