Ethanol Electro-oxidation on Palladium Revisited Using Polarization Modulation Infrared Reflection Absorption Spectroscopy (PM-IRRAS) and Density Functional Theory (DFT): Why Is It Difficult To Break the C–C Bond?
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Bibliographic record
Abstract
Insights into the ethanol electro-oxidation reaction mechanism on palladium in alkaline media are presented combining polarization modulation infrared reflection absorption spectroscopy (PM-IRRAS) and density functional theory (DFT) calculations. The synergy between PM-IRRAS and DFT calculations helps to explain why the C–C bond is not broken during ethanol electro-oxidation, and the reaction stops at acetate. Coupling chronoamperometry (CA) with in situ PM-IRRAS enables us to simultaneously identify ethanol electro-oxidation products on the catalyst surface and in the bulk solution. We show that, at lower potential, it is possible to break the C–C bond on Pd/C in alkaline media to form CO 2 . However, the selectivity is poor, because of competition with the formation of acetate and other side products, which gets worse at higher potentials. DFT computations complete the picture using the computational hydrogen electrode approach. The computations highlight the pivotal role of the CH 3 CO intermediate that can either undergo a C–C bond scission yielding CO and then CO 2 or that can be oxidized toward CH 3 COO – . The latter is a dead end in the reaction scheme toward CO 2 production, since it cannot be easily oxidized nor broken into C 1 fragments. However, CH 3 CO is not the most favored intermediate formed from ethanol electro-oxidation on Pd, hence limiting the production of CO 2 .
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Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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