Unusual Photochemistry in Aromatic Dithioimides: Quantitative Thione Reduction Promoted by Ether Solvents
Bibliographic record
Abstract
Abstract We report a mechanistic investigation of an aromatic dithioimide ( 2SS ) displaying puzzling yet efficient photochemistry in ether solvents. Perplexingly, 2SS dissolved in ether solvents in a sealed and degassed vial was photochemically converted to the corresponding diimide ( 2OO ), as determined by 1 H NMR following product extraction. With no external sources of oxygen in the sample, could the oxygen in 2OO be from the ether itself? To study this unprecedented proposition, we attempt to uncover the ether's involvement in this reaction. As seen by laser‐flash photolysis, 2SS appears to first react with the solvent from its singlet excited state. Following the reaction by NMR under rigorously oxygen‐ and water‐free conditions led to the identification of a photoreductive pathway that quantitatively transformed one thione into a methylene to yield 2SH 2 . Subsequent oxidation of 2SH 2 or irradiation of 2SS under air proved that molecular oxygen was indeed necessary to observe an oxidative pathway leading to 2OO , ruling out the initially proposed involvement of an ether oxygen. An explanation of 2SS desulfurization was further revealed through the study of solvent by‐products by GC‐MS analysis. Supported by DFT calculations, a mechanism is proposed to involve a chain reaction initiated by photochemically generated ether radical.
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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".