Kinetic and mechanistic studies of the reactions of 2-mercaptoethanol and thioglycolic acid with a Co(III)-bound superoxide complex
Bibliographic record
Abstract
In acid media ([H+] = 0.01–0.06 M), 2-mercaptoethanol (HSCH2CH2OH, abbreviated as MERCAP) and thioglycolic acid (HSCH2COOH, abbreviated as TGA) reduce the superoxo complex [(en)(dien)CoIII(O2)CoIII(en)(dien)]5+ (1) to the corresponding peroxo complex [(en)(dien)CoIII(μ-O2)CoIII(en)(dien)]4+ (2). The observed rate (ko), although proportional to both [MERCAP] and [TGA], is higher for TGA than for MERCAP, which is contrary to the expected trend on the basis of standard reduction potential (–0.14 versus –0.26 V, respectively). Moreover, ko values decrease with increasing media ionic strength (I) and [H+] and thus, thiolate anions are supposed to be the reactive forms of the reductants. Under the experimental conditions, the concentrations of such reductants (–SCH2CH2OH and HOOCCH2S–, respectively) from MERCAP (pKa = 9.7) and TGA (pKa1, pKa2 = 3.53, 10.10) are very small. However, for TGA, the tautomerization between HSCH2COO– and –SCH2COOH (pKi = 7.0) plays a significant role in increasing the concentration of HOOCCH2S–. The rates of both of the reactions are limited by the rate of solvent diffusion and this fact is also supported by the relatively low activation energy (Ea), for the reactions. The Ea values for the reactions with MERCAP and TGA are close enough (29.6 ± 1.3 and 27.0 ± 0.4 kJ M−1 respectively) to suggest a common reaction mechanism for both.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".