An Overview of Glycerol Electrooxidation Mechanisms on Pt, Pd and Au
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Bibliographic record
Abstract
Abstract In the most recent decade, glycerol electrooxidation (GEOR) has attracted extensive research interest for valorization of glycerol: the conversion of glycerol to value‐added products. These reactions at platinum, palladium, and gold electrodes have a lot of uncertainty in their reaction mechanisms, which has generated some controversies. This review gathers many reported experimental results, observations and proposed reaction mechanisms in order to draw a full picture of GEOR. A particular focus is the clarification of two propositions: Pd is inferior to Pt in cleaving the C−C bonds of glycerol during the electrooxidation and the massive production of CO 2 at high overpotentials is due to the oxidation of the already‐oxidized carboxylate products. It is concluded that the inferior C−C bond cleavability with Pd electrodes, as compared with Pt electrodes, is due to the inefficiency of deprotonation, and the massive generation of CO 2 as well as other C1/C2 side products is partially caused by the consumption of OH – at the anodes, as a lower pH reduces the amount of carboxylates and favors the C−C bond scission. A reaction mechanism is proposed in this review, in which the generation of side products are directly from glycerol (“competition” between each side product) rather than from the further oxidation of C2/C3 products. Additionally, GEOR results and associated interpretations for Ni electrodes are presented, as well as a brief review on the performances of multi‐metallic electrocatalysts (most of which are nanocatalysts) as an introduction to these future research hotpots.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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