Broadband adiabatic inversion experiments for the measurement of longitudinal relaxation time constants
Bibliographic record
Abstract
Accurate measurements of longitudinal relaxation time constants (T1) in solid-state nuclear magnetic resonance (SSNMR) experiments are important for the study of molecular-level structure and dynamics. Such measurements are often made under magic-angle spinning conditions; however, there are numerous instances where they must be made on stationary samples, which often give rise to broad powder patterns arising from large anisotropic NMR interactions. In this work, we explore the use of wideband uniform-rate smooth-truncation pulses for the measurement of T1 constants. Two experiments are introduced: (i) BRAIN-CPT1, a modification of the BRAIN-CP (BRoadband Adiabatic-INversion-Cross Polarization) sequence, for broadband CP-based T1 measurements and (ii) WCPMG-IR, a modification of the WURST-CPMG sequence, for direct-excitation (DE) inversion-recovery experiments. A series of T1 constants are measured for spin-1/2 and quadrupolar nuclei with broad powder patterns, such as 119Sn (I = 1/2), 35Cl (I = 3/2), 2H (I = 1), and 195Pt (I = 1/2). High signal-to-noise spectra with uniform patterns can be obtained due to signal enhancements from T2eff-weighted echo trains, and in favorable cases, BRAIN-CPT1 allows for the rapid measurement of T1 in comparison to DE experiments. Protocols for spectral acquisition, processing, and analysis of relaxation data are discussed. In most cases, relaxation behavior can be modeled with either monoexponential or biexponential functions based upon measurements of integrated powder pattern intensity; however, it is also demonstrated that one must interpret such T1 values with caution, as demonstrated by measurements of T1 anisotropy in 119Sn, 2H, and 195Pt NMR spectra.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".