Nature of S–N Bonding in Sulfonamides and Related Compounds: Insights into π-Bonding Contributions from Sulfur K-Edge X-ray Absorption Spectroscopy
Bibliographic record
Abstract
Molecules containing sulfur–nitrogen bonds, like sulfonamides, have long been of interest because of their many uses and interesting chemical properties. Understanding the factors that cause sulfonamide reactivity is important, yet there continues to be controversy regarding the relevance of S–N π bonding in describing these species. In this paper, we use sulfur K-edge X-ray absorption spectroscopy (XAS) in conjunction with density functional theory (DFT) to investigate the role of S 3p contributions to π-bonding in sulfonamides, sulfinamides, and sulfenamides. We explore the nature of the electron distribution of the sulfur atom to its nearest neighbors and widen our scope to its effects on rotational barriers along the sulfur–nitrogen axis. The experimental XAS data together with time-dependent DFT calculations confirm that sulfonamides—and the other sulfinated amides in this series—have essentially no S–N π bonding involving S 3p contributions and that electron repulsion is the dominant force affecting rotational barriers along the S–N axis.
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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) | 0.002 | 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".