<sup>77</sup>Se Solid-State NMR Investigation of Selenium Chemical Shift Tensors of Chalcogen Bonds in Selenadiazole Cocrystals
Bibliographic record
Abstract
This study focuses on 3,4-dicyano-1,2,5-selenadiazole and substituted 2,1,3-benzoselenadiazole-based cocrystals synthesized via mechanochemical methods and characterized by a combination of X-ray diffraction and solid-state NMR spectroscopy. Eight new single-crystal structures are reported, revealing a variety of chalcogen bond (ChB) geometries and binding motifs that are found to promote low-dimensional molecular architectures. We find that 77 Se isotropic chemical shifts follow exponential decay or growth trends along with the ChB length, while also depending on the electrostatic contribution of the ChB donor. These trends are shown to be governed by changes to the intermediate selenium chemical shift tensor component, δ 22 . Such behavior is further exploited to estimate ChB lengths in compounds unsuitable for single-crystal structure determination. This methodology highlights the utility of solid-state NMR as a powerful alternative for probing ChB interactions, particularly in systems where traditional crystallographic techniques are not applicable. The results offer critical physical insights into the origins of the selenium chemical shift tensors of ChB-based 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 | 0.000 |
| 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".