Solid-State <sup>137</sup>Ba NMR Spectroscopy: An Experimental and Theoretical Investigation of <sup>137</sup>Ba Electric Field Gradient Tensors and Their Relation to Structure and Symmetry
Bibliographic record
Abstract
Ultrawideline (137)Ba SSNMR spectra of several barium-containing systems (barium nitrate, barium carbonate, barium chlorate monohydrate, barium chloride dihydrate, anhydrous barium chloride, and barium hydrogen phosphate) were acquired at two different magnetic field strengths (9.4 and 21.1 T) using frequency-stepped techniques. The recently reported WURST-QCPMG pulse sequence (O'Dell et al. Chem. Phys. Lett. 2008, 464, 97-102) is shown to be very useful for rapidly acquiring high signal-to-noise (137)Ba SSNMR spectra. The breadths of the second-order quadrupolar-dominated spectra and experimental times are notably reduced for experiments conducted at 21.1 T. Analytical simulations of the (137)Ba SSNMR spectra at both fields yield the quadrupolar parameters, and in select cases the barium chemical shift anisotropies (CSAs). Quadrupolar interactions dominate the (137)Ba powder patterns, with quadrupolar coupling constants, C(Q)((137)Ba), ranging from 7.0 to 28.8 MHz. The (137)Ba electric field gradient (EFG) parameters extracted from these spectra are correlated to the local environments at the barium sites, via consideration of molecular symmetry and structure, and first principles calculations of (137)Ba EFG tensors performed using CASTEP software. The rapidity with which (137)Ba SSNMR spectra can be acquired using the WURST pulse sequence and/or at ultrahigh magnetic fields and the sensitivity of the (137)Ba EFG tensor parameters to the changes in the barium environment suggest that (137)Ba SSNMR has great potential for structural characterization of a variety of barium-containing materials.
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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 | 0.000 | 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".