Solid-State Nitrogen-15 NMR and Quantum Chemical Study of<i>N</i>,<i>N</i>-Dimethylaniline Derivatives
Bibliographic record
Abstract
In this study the components of the nitrogen chemical shift (CS) tensor are examined for a series of para substituted N,N-dimethylaniline derivatives. This is done through measurement of the 15N NMR spectra of powder samples and through quantum chemical calculations on the isolated molecules. Experiments and calculations show that the isotropic CS, delta(iso), decreases with increasing electron donating ability of the para substituent, in agreement with previous solution studies. More importantly, this study shows that this decrease in the isotropic (solution) CS is due to decreasing values of the CS tensor component delta(11) and component delta(33). The component delta(22) is essentially invariant to the electron donating/withdrawing ability of the para substituent. Through Ramsey's theory of nuclear magnetic shielding, it can be seen that the variation in delta(11) and delta(33), and hence delta(iso), is due to changes in the n-pi* and the sigma-pi* energy gaps in N,N-dimethylaniline. This, in turn, is a result of the change in the energy of the pi* molecular orbital with change in the pi-electron donating ability of the para substituent. The effects of nitrogen inversion on the components of the nitrogen CS tensor components are also discussed. This study also shows the feasibility of performing 15N cross-polarization experiments on nonspinning powder samples at natural isotopic abundance.
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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 | 0.000 |
| 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 | 0.000 |
| 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".