Interaction Tensors and Local Dynamics in Common Structural Motifs of Nitrogen: A Solid-State <sup>14</sup>N NMR and DFT Study
Bibliographic record
Abstract
(14)N solid-state NMR powder patterns have been obtained at high field (21.1 T) using broadband, frequency-swept pulses and a piecewise acquisition method. This approach allowed the electric field gradient (EFG) tensor parameters to be obtained from model organic and inorganic systems featuring spherically asymmetric nitrogen environments (C(Q) values of up to ca. 4 MHz). The advantages and limitations of this experimental approach are discussed, and the observation of (14)N T(2) relaxation anisotropy in certain systems is also reported, which can shed light on dynamic processes, allowing motional geometries and jump rates to be probed. In particular, we show that observable effects of dynamics on (14)N spectra can be mediated by modulation of either the EFG tensor or heteronuclear dipolar couplings. It is demonstrated that the QCPMG protocol can be used to selectively enhance certain types of nitrogen environments on the basis of differences in T(2). We also present the results of extensive density functional theory calculations on these systems, which show remarkably good correlation with the experimental results and allow the prediction of tensor orientations, assignment of parameters to crystallographic sites, and a rationalization of the origin of the EFG tensors in terms of contributions from individual molecular orbitals. This work demonstrates that ultra-wideline (14)N solid-state NMR can, under favorable circumstances, be a straightforward, useful, and informative probe of molecular structure and dynamics.
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 | 0.000 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".