Diiron Complexes of 3 <i>H</i> ‐1,2,3,5‐Dithiadiazolines and the Fate of the Parent Dithiadiazolyl: A Crystallographic and Computational Study
Bibliographic record
Abstract
Low‐temperature crystal structures of iron carbonyl complexes of diamagnetic 4‐aryl‐3 H ‐1,2,3,5‐dithiadiazolines, [Fe 2 {S 2 N(NH)CAr}(CO) 6 ] (Ar = 4‐C 6 H 4 CF 3 ( 2 ), and 4‐C 6 H 4 OMe ( 3 )) are reported, alongside a new low‐temperature structure of [Fe 2 {S 2 N(NH)CPh}(CO) 6 ] ( 1 ), in which the presence of an NH bond is established unambiguously. Diverse NH···N hydrogen bonding networks in 1 , 2 , and several variants of 3 ( 3a – c ) are observed, with intermolecular distances refined to neutron‐diffraction accuracy using Hirshfeld atom refinement with nonspherical atomic scattering factors, using a state‐of‐the‐art method. To rationalize the formation of 1 – 3 from Fe 3 (CO) 12 and 1,2,3,5‐dithiadiazolyl radicals, i.e., the conspicuous absence of paramagnetic [Fe 2 (S 2 N 2 CAr)(CO) 6 ] ( 1 ′– 3 ′), the thermochemistry of the reactions, and properties of viable intermediates are profiled using density functional theory (DFT) methods. From these calculations, a clear electronic basis for the instability of 1 ′– 3 ′ is revealed: unlike S 2 N 2 CAr • , which are stable π radicals, their iron complexes are reactive σ radicals that abstract a hydrogen atom from dry toluene to form the observed diamagnetic complexes. Furthermore, the putative paramagnetic complexes are uniquely susceptible to hydrogen atom transfer and are thus probable intermediates in the syntheses of 1 – 3 .
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".