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?
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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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".