Unraveling the Roles of the Acid Medium, Experimental Probes, and Terminal Oxidant, (NH<sub>4</sub>)<sub>2</sub>[Ce(NO<sub>3</sub>)<sub>6</sub>], in the Study of a Homogeneous Water Oxidation Catalyst
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Bibliographic record
Abstract
The oxidation of water catalyzed by [Ru(tpy)(bpy)(OH(2))](ClO(4))(2) (1; tpy = 2,2';6'',2''-terpyridine; bpy = 2,2'-bipyridine) is evaluated in different acidic media at variable oxidant concentrations. The observed rate of dioxygen evolution catalyzed by 1 is found to be highly dependent on pH and the identity of the acid; e.g., d[O(2)]/dt is progressively faster in H(2)SO(4), CF(3)SO(3)H (HOTf), HClO(4), and HNO(3), respectively. This trend does not track with thermodynamic driving force of the electron-transfer reactions between the terminal oxidant, (NH(4))(2)[Ce(NO(3))(6)] (CAN), and Ru catalyst in each of the acids. The particularly high reactivity in HNO(3) is attributed to the NO(3)(-) anion: (i) enabling relatively fast electron-transfer steps; (ii) participating in a base-assisted concerted atom-proton transfer process that circumvents the formation of high energy intermediates during the O-O bond formation process; and (iii) accelerating the liberation of dioxygen from the catalyst. Consequently, the position of the rate-determining step within the catalytic cycle can be affected by the acid medium. These factors collectively contribute to the position of the rate-determining step within the catalytic cycle being affected by the acid medium. This offering also outlines how other experimental issues (e.g., spontaneous decay of the Ce(IV) species in acidic media; CAN/catalyst molar ratio; types of catalytic probes) can affect the Ce(IV)-driven oxidation of water catalyzed by homogeneous molecular complexes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it