Volumes of activation for electrode processes of various charge-types in nonaqueous solvents
Bibliographic record
Abstract
Volumes of activation (ΔVel) are reported for electron transfer at a Pt electrode of Mn(CN-cyclo-C6H11)62+/+in acetonitrile, acetone, methanol, and propylene carbonate, and of Fe(phen)33+/2+in acetonitrile. In all cases, ΔVelis markedly positive, whereas for the homogeneous self-exchange reactions of these couples in the same solvents the corresponding parameter is known to be strongly negative. The rate constants for the electrode reactions correlate loosely with the mean reactant diffusion coefficients (i.e., with solvent fluidity) and the ΔVelvalues with the volumes of activation for diffusion (i.e., for viscous flow), consistent with solvent dynamical control of the electrode reaction rate in organic solvents. A detailed analysis of ΔVelvalues of the kind presented for a couple with an uncharged member (Zhou and Swaddle, Can. J. Chem. 79, 841 (2001)) fails, however, either because of ion-pairing effects with these more highly charged couples or because of breakdown of transition-state theory in predicting the contribution of the activational barrier. Attempts to measure ΔVelfor the oxidation of the uncharged molecule ferrocene at various electrodes in acetonitrile were unsuccessful, although ΔVelwas again seen to be clearly positive.Key words: electrode kinetics, volumes of activation, nonaqueous electron transfer, solvent dynamics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".