Electron Transfer to Sulfides and Disulfides: Intrinsic Barriers and Relationship between Heterogeneous and Homogeneous Electron‐Transfer Kinetics
Bibliographic record
Abstract
The electron-acceptor properties of series of related sulfides and disulfides were investigated in N,N-dimethylformamide with homogeneous (redox catalysis) and/or heterogeneous (cyclic voltammetry and convolution analysis) electrochemical techniques. The electron-transfer rate constants were determined as a function of the reaction free energy and the corresponding intrinsic barriers were determined. The dependence of relevant thermodynamic and kinetic parameters on substituents was assessed. The kinetic data were also analyzed in relation to corresponding data pertaining to reduction of diaryl disulfides. All investigated reductions take place by stepwise dissociative electron transfer (DET) which causes cleavage of the C(alkyl)--S or S--S bond. A generalized picture of how the intrinsic electron-transfer barrier depends on molecular features, ring substituents, and the presence of spacers between the frangible bond and aromatic groups was established. The reduction mechanism was found to undergo a progressive (and now predictable) transition between common stepwise DET and DET proceeding through formation of loose radical anions. The intrinsic barriers were compared with available results for ET to several classes of dissociative- and nondissociative-type acceptors, and this led to verification that the heterogeneous and the homogeneous data correlate as predicted by the Hush theory.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".