Influence of the Molecular Structure on the Electrocatalytic Hydrogenation of Carbonyl Groups and H<sub>2</sub> Evolution on Pd
Bibliographic record
Abstract
We investigated the electrocatalytic hydrogenation (ECH) of model aldehydes and ketones over carbon-supported Pd in the aqueous phase. We propose reaction mechanisms based on kinetic measurements and on spectroscopic and electrochemical characterization of the working catalyst. The reaction rates of ECH and of the H 2 evolution reaction (HER) vary with the applied electric potential following trends that strongly depend on the organic substrate. The intrinsic rates of hydrogenation and H 2 evolution are influenced, in opposing ways, by the sorption of the reacting organic substrate. Strong interactions, that is, higher standard free energies of adsorption of the organic compound, induce high hydrogenation rates. The fast hydrogenation kinetics produces a hydrogen-depleted environment that kinetically hinders the HER and the bulk phase transition of Pd to a H-rich bulk Pd hydride, which is triggered by the applied potential in the absence of reacting organic compounds. As a consequence of strong organic–metal interactions, hydrogenation dominates at low overpotential. However, the coverages of organic substrates on the metal surface decrease, and the rates of H 2 evolution surpass those of hydrogenation with increasingly negative electric potential. We determined the range of electric potential favoring hydrogenation on Pd and quantitatively deconvoluted the effects of the sorption of the organic compound, and of the rates of proton-coupled electron transfers, on the kinetics of both ECH and HER. The results indicate that electrocatalysis offers hydrogenation pathways for polar molecules which are different and, in some cases, faster than those dominating in the absence of an external electric potential.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".