Solvent Effects on C–H Abstraction by Hydroperoxyl Radicals: Implication for Antioxidant Strategies
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Kinetic solvent effects (KSE) on hydrogen atom transfer (HAT) reactions play a pivotal role in processes such as photoredox catalysis, electrochemical synthesis, and antioxidant defense. While general principles of KSE are well established, the influence of solvent-radical interactions on the reactivity of the hydroperoxyl radical (HOO • ) remains largely uncharacterized. Here, we examine the effects of noncovalent interactions and acid–base equilibria on HOO • reactivity, using the autoxidation of 1,4-cyclohexadiene (CHD) as convenient HOO • source in chlorobenzene (PhCl) or acetonitrile solutions containing cosolvents (S) with varying hydrogen bond acceptor basicities (β 2 H ). Equilibrium ( K S ) and CHD + HOO • ( k p S ) rate constants in PhCl were determined for cosolvents including MeOH, MeCN, DMSO, pyridine, and DABCO. As β 2 H increased from 0.41 (MeOH) to ∼0.70 (DABCO), K S increased from 50 to 3 × 10 6 M –1, while k p S decreased from 90 to 0.1 M –1 s –1 . MeCN (β 2 H = 0.44) gave K S = 70 M –1 and k p S = 130 M –1 s –1 . For DMSO (β 2 H = 0.78) and pyridine (β 2 H = 0.62) K S values were 2.0 × 10 3 and 3 × 10 5 M –1, respectively, with corresponding k p S values of 20 and 5 M –1 s –1 . The observed K S values show a qualitative correlation with the solvent β 2 H values of the solvents. Moreover, the calculated α 2 H values for HOO • in nonbasic cosolvents (MeOH, MeCN, DMSO) cluster around 0.87 ± 0.07, consistent with prior estimates. Experiments in MeCN solution suggest HOO • deprotonation with alkylamines, and the p K a of HOO • is estimated as 18–19. These findings provide mechanistic insight into HOO • reactivity in complex media and suggest new strategies for modulating oxidative radical chemistry in both synthetic and biological contexts.
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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 | 0.001 |
| 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".