Thermochemical Aerobic Oxidation Catalysis in Water Proceeds via Coupled Electrochemical Half-Reactions
Bibliographic record
Abstract
Heterogeneous aqueous-phase aerobic oxidations are an important emerging class of catalytic transformations, particularly for upgrading next generation bio-derived substrates. The mechanism of these reactions and the precise role of O2 in particular remains unclear. Herein, we test the hypothesis that thermochemical aerobic oxidation proceeds via two coupled electrochemical half-reactions for oxygen reduction and substrate oxidation. We collect electrochemical and thermochemical data on common noble metal catalysts under identical reaction/transport environments, and find that the electrochemical polarization curves of the O2 reduction and the substrate oxidation half-reaction closely predict the mixed potential of the catalyst measured in operando during thermochemical catalysis across 13 diverse variables spanning reaction conditions, catalyst composition, reactant identity, and pH. Additionally, we find that driving the oxidation half-reaction reaction electrochemically in the absence of O2 at the mixed potential leads to very similar rates and selectivities as for the thermochemical reaction in all cases examined. These findings strongly indicate that the role of O2 in thermochemical aerobic oxidation is solely as an electron scavenger that provides an incipient electrochemical driving force for substrate oxidation. These studies provide a quantitative and predictive link between thermochemical and electrochemical catalysis, thereby enabling the rational design of new thermochemical liquid-phase aerobic oxidation schemes by applying the principles of electrochemistry.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".